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Environ. Sci. Proc., 2022, ECAS 2022

The 5th International Electronic Conference on Atmospheric Sciences

Online | 16–31 July 2022

Volume Editors:
Anthony Lupo, University of Missouri, USA
Daniele Contini, Consiglio Nazionale delle Ricerche, Italy
Patricia Quinn, National Oceanic and Atmospheric Administration, USA
Peter Domonkos, Independent Researcher, Spain
Andreas Matzarakis, University of Freiburg, Germany
Muhammad Mainuddin Patwary, Khulna University, Bangladesh
Srijan Sengupta, North Carolina State University, USA

Number of Papers: 63
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Cover Story (view full-size image): For the fifth electronic conference in atmospheric sciences, the range of topics will remain more general, but we would be open to subject areas with a thematic topic of importance. During the last [...] Read more.
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1 pages, 169 KiB  
Abstract
Assessing the Impact of COVID-19 Lockdown on Surface Urban Heat Island and Normalized Difference Vegetation Index in Dhaka Megacity, Bangladesh
by Muhammad Mainuddin Patwary and Md. Mijanur Rahman
Environ. Sci. Proc. 2022, 19(1), 37; https://doi.org/10.3390/ecas2022-12830 - 15 Jul 2022
Viewed by 929
Abstract
Growing evidence has shown that rapid development and urbanization have been associated with the alteration of the thermal environment of the urban area. The massive burning of fossil fuels in the transportation, urban, and industrial sectors results in increased temperatures and a deterioration [...] Read more.
Growing evidence has shown that rapid development and urbanization have been associated with the alteration of the thermal environment of the urban area. The massive burning of fossil fuels in the transportation, urban, and industrial sectors results in increased temperatures and a deterioration of air quality as a result of carbon emissions. However, the COVID-19-induced lockdown situation resulted in the shutdown of industries, transportation systems, and day-to-day regular operations and changes in air quality and weather. The reduction in the number of running cars and moving people on the road during the lockdown time reduced pollutants and had a direct beneficial effect on the urban environment. The present study examines the changes in land surface temperature (LST) and the normalized difference vegetation index (NDVI) during the lockdown period in Dhaka City, Bangladesh in the earlier periods (2017 to 2019) to compare the environmental status. The findings show that the LST of Dhaka City decreased, and the NDVI increased throughout the lockdown period, with the LST–NDVI connection becoming more negative. Additionally, the analysis demonstrates that the city’s climate improved during the lockdown. Numerous actions have been undertaken at global and regional levels to control increasing temperature and climate change, but no positive consequence has been achieved yet. While such a lockdown is temporarily detrimental to economic progress, it demonstrates the curative impact of urban climate. Thus, the findings of this study could provide a quantitative foundation for decision makers for surface heat island mitigation and public health care. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)

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6 pages, 1933 KiB  
Proceeding Paper
Air Quality and Climate Comfort INDICES over the Eastern Mediterranean: The Case of Rhodes City during the Summer of 2021
by Ioannis Logothetis, Christina Antonopoulou, Georgios Zisopoulos, Adamantios Mitsotakis and Panagiotis Grammelis
Environ. Sci. Proc. 2022, 19(1), 1; https://doi.org/10.3390/ecas2022-12833 - 14 Jul 2022
Cited by 2 | Viewed by 969
Abstract
Climate and weather conditions have a profound influence on humans’ sense of comfort and discomfort. In addition, the impact of emissions and human activities on air quality seems to be scientifically indisputable. The maintenance of low levels of environmental nuisance in areas of [...] Read more.
Climate and weather conditions have a profound influence on humans’ sense of comfort and discomfort. In addition, the impact of emissions and human activities on air quality seems to be scientifically indisputable. The maintenance of low levels of environmental nuisance in areas of high environmental and cultural interest, such as some Greek islands, is becoming increasingly important. Thus, exploring the combination of the effect of air quality and climate comfort in a high-traffic area falls within the scope of the principles and practices of sustainable development in such areas. The current study aims to shed some light on this field, for the case of Rhodes city, which is located in the eastern Mediterranean, during the summer of 2021. For the analysis, measurements of the concentration of pollutants (PM2.5, NOΧ and O3) and meteorological recordings (wind speed, wind direction and temperature) from a mobile air quality system located in the center of Rhodes city were conducted. Furthermore, meteorological data from the ERA5 reanalysis (wind speed, temperature, relative humidity, precipitation, cloud cover and height of boundary layer) over a geographical domain around Rhodes Island were included in the study. Results show that climate conditions and emissions are closely linked to traffic and tourism activities, which in turn affect the variability of pollutant concentrations. The calculation of the discomfort index shows that during periods of higher levels of air pollution, the population of Rhodes city feels partially comfortable, while the holiday climate index values show that the climatic conditions are suitable for tourist activities. In conclusion, this study could enhance our understanding of climate comfort and air quality by providing some evidence of the benefits of implementing a sustainable development policy in such tourist areas. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>The position of mobile monitoring station (red star): (<bold>a</bold>) in the city of Rhodes and (<bold>b</bold>) focusing in the area near the mobile monitoring station. (source: Rhodes city. Google Earth v9.159.0.0. 36°26′49″ N and 28°13′15″. (<bold>a</bold>) ~1700 m (<bold>b</bold>) ~800 m, assessed: 17 May 2022).</p>
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<p>Timeseries of (<bold>a</bold>–<bold>c</bold>) the concentration of pollutants <inline-formula><mml:math id="mm20"><mml:semantics><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mi>M</mml:mi><mml:mrow><mml:mn>2.5</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>, <inline-formula><mml:math id="mm21"><mml:semantics><mml:mrow><mml:mi>N</mml:mi><mml:msub><mml:mi>O</mml:mi><mml:mi>Χ</mml:mi></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula> and <inline-formula><mml:math id="mm22"><mml:semantics><mml:mrow><mml:msub><mml:mi>O</mml:mi><mml:mn>3</mml:mn></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula> and (<bold>d</bold>–<bold>f</bold>) the metrological factors T, WDir and WS. The orange/(green) lines denote the high/(low) emissions period. </p>
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<p>Composite difference between HP and LP for the (<bold>a</bold>) boundary layer height, (<bold>b</bold>) precipitation, (<bold>c</bold>) wind speed. The dotted region represents the statistically significant difference at 95%, as estimated using a Student’s <italic>t</italic>-test.</p>
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<p>(<bold>a</bold>) Discomfort index and (<bold>b</bold>) holiday climate index for the city of Rhodes during the summer period of 2021.</p>
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7 pages, 258 KiB  
Proceeding Paper
Lung Dosimetry Modelling in Nanotoxicology: A Critical Analysis of the State of the Art
by Wells Utembe and Natasha Sanabria
Environ. Sci. Proc. 2022, 19(1), 2; https://doi.org/10.3390/ecas2022-12801 - 14 Jul 2022
Viewed by 1386
Abstract
The estimation of the dose of inhaled nanomaterials is of fundamental importance in occupational and environmental health. Indeed, the toxicology and risk assessment of inhaled NMs depends on deposition rates in various parts of the lung, coupled with clearance/retention rates that depend on [...] Read more.
The estimation of the dose of inhaled nanomaterials is of fundamental importance in occupational and environmental health. Indeed, the toxicology and risk assessment of inhaled NMs depends on deposition rates in various parts of the lung, coupled with clearance/retention rates that depend on processes such as physical removal by ciliary clearance, macrophage-mediated clearance and lymphatic clearance, together with dissolution and disintegration. A number of lung dosimetry models have been designed to estimate the deposition and retention of inhaled particles, including empirical models, deterministic models, stochastic statistical models and mechanistic multiple-path models. Various assumptions are used in these models, including use of a symmetrical or asymmetrical lung, which affects the performance of these models. This study presents the most recent developments of in vivo dosimetry in nanotoxicology, with a focus on the design and modelling approach, and the required input data used, together with verification and validation status of the model. Widely implemented models in nanotoxicology were identified and analyzed, i.e., the Multiple Path Particle Dosimetry (MPPD) model, International Commission on Radiological Protection (ICRP) models, the National Council on Radiation Protection and Measurement (NCRP) model, the Exposure Dose Model (ExDoM) and the Integrated Exposure and Dose Modeling and Analysis System (EDMAS). Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
8 pages, 2135 KiB  
Proceeding Paper
Review of Particulate Matter Levels and Sources in North Africa over the Period 1990–2019
by Mounia Tahri, Abdelfettah Benchrif and Fatiha Zahry
Environ. Sci. Proc. 2022, 19(1), 3; https://doi.org/10.3390/ecas2022-12798 - 14 Jul 2022
Cited by 2 | Viewed by 1574
Abstract
Africa, particularly West and North Africa, has some of the highest levels of average PM pollution, second only to South and East Asia and the Middle East. This study reports the PM2.5 and PM10 concentrations and their emissions sectors in North Africa from [...] Read more.
Africa, particularly West and North Africa, has some of the highest levels of average PM pollution, second only to South and East Asia and the Middle East. This study reports the PM2.5 and PM10 concentrations and their emissions sectors in North Africa from 1990 to 2019. The data were collected online from the following platforms: EDGAR (Emissions Database for Global Atmospheric Research), Climate Watch, Our World in Data, and the World Bank. The analysis of data indicated that outdoor air pollution in North Africa is the fourth leading risk factor for death, with 3.4 million deaths in total from 1990 to 2019. Globally, 43% of PM10 emissions in North Africa from 1970 to 2015 were contributed by buildings, 16.6% by other industrial combustion, 13.7% by transport, 11.4% by other sectors, 9.6% by agriculture, 5.3% by power industry, and 0.2% by waste. For PM2.5, the major emitter sector in North Africa, during the same period, was also buildings with 38.2%, followed by transport (21.5%), other industrial combustion (17.3%), other sectors (12.4%), power industry (6%), agriculture (4.5%), and waste (0.2%). Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>North Africa Region (source: <uri>https://d-maps.com/pays.php?num_pay=6&amp;lang=en/</uri>, accessed on 25 August 2022 [<xref ref-type="bibr" rid="B18-environsciproc-19-00003">18</xref>]).</p>
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<p>The total number of deaths by risk factor, measured across all age groups and both sexes in North Africa, over the period 1990–2019 (data source: <uri>https://ourworldindata.org/</uri>, accessed on 25 August 2022 [<xref ref-type="bibr" rid="B19-environsciproc-19-00003">19</xref>]).</p>
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<p>North Africa PM10 emissions by Sector, over the period 1970–2015 (data source: <uri>https://edgar.jrc.ec.europa.eu/</uri>, accessed on 15 August 2022 [<xref ref-type="bibr" rid="B20-environsciproc-19-00003">20</xref>]).</p>
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<p>Contribution of each sector to total PM10 emissions in North Africa averaged over the period 1970–2015 (data source: <uri>https://edgar.jrc.ec.europa.eu/</uri>, accessed on 25 August 2022 [<xref ref-type="bibr" rid="B20-environsciproc-19-00003">20</xref>]).</p>
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<p>North Africa PM2.5 emissions by Sector over the period 1970–2015 (data source: <uri>https://edgar.jrc.ec.europa.eu/</uri>, accessed on 25 August 2022 [<xref ref-type="bibr" rid="B20-environsciproc-19-00003">20</xref>]).</p>
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<p>The share of each sector in total PM2.5 emissions in North Africa averaged over the period 1970–2015 (data source: <uri>https://edgar.jrc.ec.europa.eu/</uri>, accessed on 25 August 2022 [<xref ref-type="bibr" rid="B20-environsciproc-19-00003">20</xref>]).</p>
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<p>Trends in PM2.5 annual exposure mean in the North African countries, over the period 1990–2019, compared to the PM2.5 annual WHO air quality guideline and PM2.5 annual WHO Interim Target 1 (data source: <uri>www.stateofglobalair.org</uri>, accessed on 25 August 2022 [<xref ref-type="bibr" rid="B22-environsciproc-19-00003">22</xref>]).</p>
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7 pages, 1089 KiB  
Proceeding Paper
The Vorticity Budget of an Individual Atmospheric Vortex for the Hawaiian High
by Iuliia Mukhartova, Irina Zheleznova, Anastasia Nesvyatipaska and Alexander Kislov
Environ. Sci. Proc. 2022, 19(1), 4; https://doi.org/10.3390/ecas2022-12853 - 25 Jul 2022
Viewed by 900
Abstract
The study of atmospheric vortex structures based on the analysis of the vorticity field decomposition into empirical orthogonal functions (EOFs) was performed. We consider an atmospheric vortex that exists quasi-permanently in a certain region (the Hawaiian High was chosen as the study object). [...] Read more.
The study of atmospheric vortex structures based on the analysis of the vorticity field decomposition into empirical orthogonal functions (EOFs) was performed. We consider an atmospheric vortex that exists quasi-permanently in a certain region (the Hawaiian High was chosen as the study object). The study of individual atmospheric vortex evolution was based on the vorticity budget equation. The spatial structure analysis of the Hawaiian High vorticity field showed that the first mode of EOF decomposition describes more than 60% of the total variability. This allows us to consider the budget equation only for the principal component (PC) in the first EOF mode. It was concluded that the change in vorticity in the upper troposphere and vertical motions make the main contribution to the evolution of anticyclonic vorticity in the considered case. Re-analysis errors and a number of assumptions led to the appearance of a discrepancy in the equation that was approximated by regression through a first EOF mode PC and a white noise term. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>(<bold>a</bold>) The spatial structure of the vorticity field at the level of 925 hPa, corresponding to the first three modes of the EOF analysis. (<bold>b</bold>) Principal components for the first three modes of the EOF decomposition.</p>
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<p>Time coefficients for the terms of the vorticity budget equation projected onto the first spatial mode of the EOF decomposition. The vorticity change values (black dashed line) are multiplied by a factor 5 for better representation.</p>
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<p>Approximation of the discrepancy of Equation (5) (light blue line) using linear (grey line) and cubic (dark blue line) expressions from <inline-formula><mml:math id="mm48"><mml:semantics><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:semantics></mml:math></inline-formula>.</p>
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8 pages, 1510 KiB  
Proceeding Paper
Ensemble Prediction of Tropical Cyclone Tracks from NTHF, SisPI and SPNOA Systems
by Lisandra Fundora-Jiménez and Maibys Sierra-Lorenzo
Environ. Sci. Proc. 2022, 19(1), 5; https://doi.org/10.3390/ecas2022-12835 - 20 Jul 2022
Viewed by 1004
Abstract
Tropical cyclones are extreme hydrometeorological events whose impact can cause human, material and economic losses. The inaccuracies in the forecast of the trajectory of these phenomena often lead to inefficient decisions, such as unnecessary evacuation. This study proposes a combination of three forecasting [...] Read more.
Tropical cyclones are extreme hydrometeorological events whose impact can cause human, material and economic losses. The inaccuracies in the forecast of the trajectory of these phenomena often lead to inefficient decisions, such as unnecessary evacuation. This study proposes a combination of three forecasting tools NTHF, SisPI and SPNOA in the generation of ensemble prediction systems, with the aim of improving the tracking forecasts of tropical cyclones. Three variants were used for the construction of time-lagged ensembles, and for their evaluation the best track and historical errors (2016–2020) of the National Hurricane Center (NHC) were used. The ensembles led to an improvement in tropical cyclone track forecasts. Position errors vary from case to case, but ensembles generally tend to be more accurate than independent forecasts. Compared to the historical errors of the NHC, the results obtained are promising because they are superior in some cases. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Scheme that exemplifies the ensemble prediction method based on initializations with different runs.</p>
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<p>Members used in the construction of the selective set when the initializations of the NTHF, SisPI and SPNOA are available.</p>
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<p>Tropical Cyclone Irma: initializations corresponding to 9 September 2017 at 0000 UTC. (<bold>a</bold>) Employed members; (<bold>b</bold>) obtained ensembles.</p>
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<p>Tropical Cyclone Irma: initializations corresponding to 9 November 2020 at 1200 UTC. (<bold>a</bold>) Employed members; (<bold>b</bold>) obtained ensembles.</p>
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13 pages, 10266 KiB  
Proceeding Paper
Development and Trajectory of Hurricane Eta—Case Study Using the WRF Model with Dynamic Update of the Sea Surface Temperature (SST)
by Gretell Sosa-Martínez, Maibys Sierra-Lorenzo and Osniel Armas-Forteza
Environ. Sci. Proc. 2022, 19(1), 6; https://doi.org/10.3390/ecas2022-12850 - 25 Jul 2022
Viewed by 1061
Abstract
This research aims to describe the synoptic and general circulation environment in which Eta developed using the ERA5 reanalysis; design experiments with the WRF model; and describe, from the numerical outputs, the meteorological conditions that influenced the two analyzed Eta life periods. When [...] Read more.
This research aims to describe the synoptic and general circulation environment in which Eta developed using the ERA5 reanalysis; design experiments with the WRF model; and describe, from the numerical outputs, the meteorological conditions that influenced the two analyzed Eta life periods. When analyzing the maps of the ERA5 reanalysis system, a general underestimation of the wind speed during the analyzed periods was identified. The first moment was characterized by a system in the development phase that failed to intensify under the influence of a trough over the southeastern Gulf of Mexico that generated shear conditions that were maintained during the second moment. Through the experiments that were carried out with WRF-SST, and from the numerical outputs, it was possible to describe with greater precision the meteorological conditions that influenced the development, trajectory and intensity changes of Eta. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Simulation domain used in the WRF model.</p>
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<p>WRF-SST vertical wind shear map at 09:00 UTC on (<bold>a</bold>) 7 November 2020 and (<bold>b</bold>) 8 November 2020.</p>
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<p>WRF-SST Flow Map of 7 November 2020 at 21:00 UTC at the level of: (<bold>a</bold>) 925 hPa, (<bold>b</bold>) 825 hPa, (<bold>c</bold>) 700 hPa y (<bold>d</bold>) 500 hPa.</p>
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<p>WRF-SST flow map of 8 November 2020 at 00:00 UTC at the level of (<bold>a</bold>) 925 hPa, (<bold>b</bold>) 825 hPa, (<bold>c</bold>) 700 hPa y (<bold>d</bold>) 500 hPa.</p>
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<p>WRF-SST Flow Map of November 8 at 09:00 UTC at the level of 200 hPa.</p>
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<p>WRF-SST Relative Humidity Map of November 8 at the level of 700 hPa at (<bold>a</bold>) 00:00 UTC, (<bold>b</bold>) 12:00 UTC, (<bold>c</bold>) 18:00 UTC, (<bold>d</bold>) 21:00 UTC.</p>
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<p>WRF-SST relative humidity‘s vertical cross-section and reflectivity on November 8 at 21:00 UTC.</p>
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<p>WRF-SST geopotential height maps of 9 November at 00:00 UTC in the levels: (<bold>a</bold>) 925 hPa, (<bold>b</bold>) 825 hPa, (<bold>c</bold>) 700 hPa, (<bold>d</bold>) 500 hPa, (<bold>e</bold>) 300 hPa, (<bold>f</bold>) 200 hPa.</p>
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<p>Relative humidity map on November 9 at 00:00 UTC in 500 hPa level.</p>
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<p>WRF-SST geopotential height maps on November 11, 2020, in 500 hPa level at: (<bold>a</bold>) 00:00 UTC, (<bold>b</bold>) 06:00 UTC, (<bold>c</bold>) 12:00 UTC, (<bold>d</bold>) 21:00 UTC.</p>
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<p>WRF-SST geopotential height maps on November 11, 2020, in 500 hPa level at: (<bold>a</bold>) 00:00 UTC, (<bold>b</bold>) 06:00 UTC, (<bold>c</bold>) 12:00 UTC, (<bold>d</bold>) 21:00 UTC.</p>
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<p>Minimum central pressure graph.</p>
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<p>Bar chart of the minimum central pressure and absolute error.</p>
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<p>Maximum wind speed graph.</p>
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<p>Bar chart of the maximum wind speed and absolute error.</p>
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<p>Trajectory map.</p>
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6 pages, 549 KiB  
Proceeding Paper
Spatio-Temporal Optimal Interpolation of Aerosol Optical Depth Observations Using a Chemical Transport Model
by Natallia Miatselskaya, Andrey Bril, Anatoly Chaikovsky, Alexander Miskevich, Gennadi Milinevsky and Yuliia Yukhymchuk
Environ. Sci. Proc. 2022, 19(1), 7; https://doi.org/10.3390/ecas2022-12797 - 14 Jul 2022
Viewed by 834
Abstract
To estimate the spatial and temporal distribution of aerosol optical depth (AOD), we used the optimal interpolation (OI). In OI, observational data and a model forecast are linearly combined according to their relative accuracies. Weight coefficients are chosen to minimize the mean-square error [...] Read more.
To estimate the spatial and temporal distribution of aerosol optical depth (AOD), we used the optimal interpolation (OI). In OI, observational data and a model forecast are linearly combined according to their relative accuracies. Weight coefficients are chosen to minimize the mean-square error in the estimate. To obtain weight coefficients, correlations between model errors in the different grid points are used. In classical OI, only spatial correlations are considered. We used spatial and temporal correlation functions. To obtain error statistics, we used observations from European stations of ground-based sun photometers, the Aerosol Robotic Network (AERONET), and simulations by a chemical transport model GEOS-Chem, assuming a negligible error of AERONET AOD observations. The estimates of the daily mean AOD distribution over Europe are obtained. The reduction of the root-mean-square error of the AOD estimate based on the OI method in comparison with the GEOS-Chem model results is discussed. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Location of the Aerosol Robotic Network (AERONET) stations considered in the assimilation scheme. In red are marked the sites chosen for validation.</p>
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8 pages, 2479 KiB  
Proceeding Paper
Source Apportionment and Diurnal Variability of Autumn-Time Black Carbon in a Coastal City of Salé, Morocco
by Anas Otmani, Abdelfettah Benchrif, Abdeslam Lachhab, Mounia Tahri, Bouamar Baghdad, Mohammed El Bouch and El Mahjoub Chakir
Environ. Sci. Proc. 2022, 19(1), 8; https://doi.org/10.3390/ecas2022-12832 - 18 Jul 2022
Cited by 1 | Viewed by 924
Abstract
This research aims to understand the temporal variation of concentrations of equivalent black carbon (eBC) and to calculate the fossil fuel (BCff) and biomass combustion (BCwb) contribution to eBC during the 2020 autumn season. In-situ measurements of eBC and NO2 were performed [...] Read more.
This research aims to understand the temporal variation of concentrations of equivalent black carbon (eBC) and to calculate the fossil fuel (BCff) and biomass combustion (BCwb) contribution to eBC during the 2020 autumn season. In-situ measurements of eBC and NO2 were performed for this aim in Sale, Morocco. The contribution of BCff and BCwb was assigned based on the spectrum dependence of BC absorption. The average eBC concentration was 1.9 ± 2.2 µg/m3 with a contribution of 13% for BCwb. The eBC was strongly correlated with NO2 (R2 = 0.63). Fossil fuel combustion is the most significant contributor to eBC and NO2 concentrations. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Location map of the measurement site at The Médersa of Mérinides in Salé.</p>
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<p>Temporal variation of Hour mean temperature and relative humidity (RH) at Salé during sampling period.</p>
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<p>Wind rose diagram at Salé during the sampling period.</p>
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<p>Hourly mean variation of eBC and NO<sub>2</sub>.</p>
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<p>Relationship between eBC and NO<sub>2</sub>.</p>
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<p>Rose pollutant of eBC depicting the relationships between mean eBC concentrations (ng/m<sup>3</sup>), wind speed, and wind direction over the study period.</p>
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<p>The diurnal distribution of BC, BCff, and BCwb. The horizontal lines represent the medians; the limits of the boxes are the 1st and 3rd quartiles. The whiskers extend to one and a half times the interquartile range. Hours are in local time, LT.</p>
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7 pages, 3106 KiB  
Proceeding Paper
An Aerosol Optical Depth Comparison Study Based on Satellite Observations of the Western Indian Region, Surat
by Ranjitkumar Solanki and Kamlesh Pathak
Environ. Sci. Proc. 2022, 19(1), 9; https://doi.org/10.3390/ecas2022-12861 - 31 Jul 2022
Cited by 1 | Viewed by 950
Abstract
The aerosol optical depth (AOD) was measured along the Tapi River in the Gulf of Khambhat in Surat, Gujarat (India). Satellite data from MODIS relating to the aerosol optical depth (AOD) were collected from the Giovanni site, developed by NASA. In this study, [...] Read more.
The aerosol optical depth (AOD) was measured along the Tapi River in the Gulf of Khambhat in Surat, Gujarat (India). Satellite data from MODIS relating to the aerosol optical depth (AOD) were collected from the Giovanni site, developed by NASA. In this study, the data from a period of 5 years (January to December 2015 to 2019) are discussed. Variations in the regional meteorological conditions are related to aerosol optical depth characteristics. The annual average AOD variation was observed from the data obtained from January to December 2015–2019. The average annual changes in the aerosol optical depth (AOD) revealed a peak value during the monsoon season, while the seasonal mean aerosol optical depth (AOD) was lowest during the pre-monsoon season, and it was somewhat moderate in the winter season. The post-monsoon season’s variations in the aerosol optical depth (AOD) were comparable to those of the winter and pre-monsoon seasons in 2016. Following this, the values increased and exceeded the maximum for both the Aqua and Terra measurements, owing to changes in the local boundary layer. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Daily variation in the AOD in 2015 using MODIS Aqua observations.</p>
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<p>Daily variation in the AOD in 2015 using MODIS Terra observations.</p>
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<p>MODIS Aqua AOD (550 nm) monthly variation during the years 2015–2019.</p>
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<p>MODIS Terra AOD (550 nm) monthly variation during the years 2015–2019.</p>
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<p>MODIS Aqua and Terra AOD (550 nm) seasonal variation during the years 2015–2019.</p>
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4 pages, 658 KiB  
Proceeding Paper
Long-Term (2012–2021) Variation in Carbonaceous Aerosols of PM2.5 at an Urban Site of Megacity Delhi Situated over Indo-Gangetic Plain of India
by Sudhir Kumar Sharma, Tuhin Kumar Mandal, Rubiya Banoo, Akansha Rai and Martina Rani
Environ. Sci. Proc. 2022, 19(1), 10; https://doi.org/10.3390/ecas2022-12860 - 31 Jul 2022
Viewed by 782
Abstract
A long-term (January 2012 to December 2021) study on carbonaceous aerosols of fine particulates (PM2.5) was conducted over the megacity of Delhi, India, to evaluate their seasonal and yearly variations. During the entire study period, the observed annual mean levels (µg [...] Read more.
A long-term (January 2012 to December 2021) study on carbonaceous aerosols of fine particulates (PM2.5) was conducted over the megacity of Delhi, India, to evaluate their seasonal and yearly variations. During the entire study period, the observed annual mean levels (µg m−3) of PM2.5 and its carbonaceous components (OC, POC, SOC, EM, EC, TCM, and TC) were recorded as 126 ± 72, 15.6 ± 11.6, 9.3 ± 6.3, 6.4 ± 5.1, 8.2 ± 5.6, 7.3 ± 5.1, 33.2 ± 21.9, and 23.1 ± 16.5, respectively. On average, the CAs/TCM ratio accounts for 26% of PM2.5 concentrations. During the monsoon (minimum) and post-monsoon (maximum) season, significant seasonal variability in PM2.5 and its carbonaceous species (OC, EC, POC, SOC, and TCM) was observed. Based on the linear association (OC vs. EC) and ratios (OC/EC as well as EC/TC) of species, three significant sources of CAs (vehicular emissions (VE), fossil fuel combustion (FFC), and biomass burning (BB)) were identified. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Annual trend in PM<sub>2.5</sub>, EC, OC, and TC levels over Delhi.</p>
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<p>Seasonal mean of (error bar: ± SD) OC, EC, TC, and TCM of PM<sub>2.5</sub> in Delhi.</p>
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6 pages, 1258 KiB  
Proceeding Paper
Integrated Ground-Based and Satellite Remote Sensing of the Earth’s Surface and Atmosphere in East and West Antarctica with Lidar and Radiometric Systems
by Aleksey Malinka, Anatoli Chaikovsky, Alexander Prikhach, Eugeny Ilkevich, Andrey Bril, Vladislav Peshcharankou, Natallia Miatselskaya, Vladimir Dick, Mikhail Korol, Vladislav Basylevich, Alexander Kalevich, Igor Alekseev, Fiodar Asipenka, Burcu Ozsoy, Mahmut Oguz Selbesoglu, Ozgun Oktar, Bahadir Celik and Mustafa Fahri Karabulut
Environ. Sci. Proc. 2022, 19(1), 11; https://doi.org/10.3390/ecas2022-12808 - 14 Jul 2022
Viewed by 970
Abstract
We have developed remote ground-based and satellite methods and hardware and software for studying atmospheric aerosols, clouds, and the underlying surface in Eastern and Western Antarctica. The ground-based equipment includes: (1) a CIMEL solar spectrum photometer, which measures the spectrum of solar radiation [...] Read more.
We have developed remote ground-based and satellite methods and hardware and software for studying atmospheric aerosols, clouds, and the underlying surface in Eastern and Western Antarctica. The ground-based equipment includes: (1) a CIMEL solar spectrum photometer, which measures the spectrum of solar radiation transmitted and scattered by the atmosphere, (2) a multi-wavelength Raman lidar, which measures the vertical backscatter profile, (3) an albedometer, which measures the spectral albedo of the surface, primarily snow, and (4) a reflectometer, which measures the directional spectral reflectance of snow. The ground-based measurement data were integrated with data from satellite radiometers MODIS or OLCI and the satellite lidar CALIOP. A synergy of the manifold data results in retrieval of various atmosphere and surface characteristics such as the aerosol optical depth, profiles of concentration of the fine and coarse aerosol fractions, spatial distribution of the effective snow grain size, fraction of outcrops, etc. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Results of optical measurements at station <italic>Gora Vechernyaya:</italic> (<bold>a</bold>) AOD spectrum. Markers denote the measured spectral AOD and its standard deviations for the measurement period 2008–2021. Straight lines are the linear regression of the spectral dependences in the logarithmic scale; the slopes are indicated in the legend. (<bold>b</bold>) Altitude distributions of the fine and coarse fractions averaged over 2018–2019.</p>
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<p>Maps of the effective grain size: (<bold>a</bold>) Antarctic Peninsula, Terra, 01/07/2022; (<bold>b</bold>) East Antarctica, Terra, 01/07/2022; (<bold>c</bold>) Antarctic Peninsula, Aqua, 01/08/2022; (<bold>d</bold>) East Antarctica, Aqua, 01/07/2022. The color scale is in micrometers.</p>
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3 pages, 604 KiB  
Proceeding Paper
Comparison of Measures of PM2.5 and Carbonaceous Aerosol in Air at Cotonou, Benin in 2005 and 2015
by Julien Djossou, Aristide B. Akpo, Cathy Liousse and Jean-François Léon
Environ. Sci. Proc. 2022, 19(1), 12; https://doi.org/10.3390/ecas2022-12824 - 14 Jul 2022
Viewed by 808
Abstract
This study focuses on the comparison of carbonaceous aerosol measurements in the air at Cotonou in 2015 compared to 2005. Working within the framework of two international programs, African Monsoon Multidisciplinary Analysis (AMMA) and Dynamics Aerosol-Cloud-Chemistry Interactions in West Africa (DACCIWA), monitoring data [...] Read more.
This study focuses on the comparison of carbonaceous aerosol measurements in the air at Cotonou in 2015 compared to 2005. Working within the framework of two international programs, African Monsoon Multidisciplinary Analysis (AMMA) and Dynamics Aerosol-Cloud-Chemistry Interactions in West Africa (DACCIWA), monitoring data for PM2.5 microns were collected at one of the most polluted urban site of Cotonou (Dantokpa) in Benin (West Africa) in 2005 and 2015, respectively. The obtained results indicate that the carbonaceous aerosol measures, black carbon (BC), and organic carbon (OC) were higher in 2005 than those obtained in 2015. PM2.5 concentrations related mainly to traffic sources for two wheeled vehicles were 34 g/m3 in May 2005 and 28 µg/m3 in May 2015. In May 2005, OC and BC concentrations were from 15 µg/m3 and 2.3 µg/m3, while in May 2015, they were from 8 µg/m3 for OC and 1.3 µg/m3 for BC. In May 2005 and 2015, the total carbon (TC) accounted for 50% and 32% of the PM2.5, respectively. In this study, the OC/EC ratio exceeded 2.0, which confirms the presence of secondary organic aerosols. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Site of measurement in Cotonou.</p>
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7 pages, 3340 KiB  
Proceeding Paper
Impact of the Assimilation of Non-Precipitating Echoes Reflectivity Data on the Short-Term Numerical Forecast of SisPI
by Adrian Luis Ferrer Hernández, Pedro Manuel González Jardines, Maibys Sierra Lorenzo and Darielis de la Caridad Aguiar Figueroa
Environ. Sci. Proc. 2022, 19(1), 13; https://doi.org/10.3390/ecas2022-12845 - 25 Jul 2022
Viewed by 1187
Abstract
The research carried out an evaluation of the 3DVAR method with different options for the assimilation of reflectivity data, which were applied to the SisPI system with the purpose of determining which scheme presents the best results in the short-term numerical weather prediction. [...] Read more.
The research carried out an evaluation of the 3DVAR method with different options for the assimilation of reflectivity data, which were applied to the SisPI system with the purpose of determining which scheme presents the best results in the short-term numerical weather prediction. For this, data from six meteorological radars with coverage over a domain with 3 km of spatial resolution were used, utilizing the indirect method with (3DVAR-NoRain) and without (3DVAR) activating an option to also consider null echoes of reflectivity without the presence of precipitation. As a test case, the cold front that affected Cuba on 10 December 2018 was taken. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Domain configuration and meteorological observations used.</p>
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<p>Test case of 10 December 2018 at 0000 UTC: (<bold>a</bold>) GOES-16 (Channel 14) infrared image and (<bold>b</bold>) KBYX Radar reflectivity observation (Key West, Florida) at 0.5 elevation angle.</p>
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<p>Comparison of the cost functions of the experiments carried out.</p>
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<p>Vertical cross-sections of relative humidity of experiments with and without radar data assimilation.</p>
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<p>Comparison of the temperature of cloud tops observed by GOES-16 satellite with respect to outputs of WRF model assimilating radar data with (3DVAR noRain) and without (3DVAR) activating the null-echo option during the first 2 h of simulation.</p>
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<p>Mean absolute error (mm/3 h) of precipitation forecast: (<bold>a</bold>) verification with 68 synoptic stations of INSMET and (<bold>b</bold>) verification with Casablanca (La Habana) synoptic station (WMO 78325).</p>
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8 pages, 2259 KiB  
Proceeding Paper
A Comparison of Different Metrics for Analyzing the Troposphere/Stratosphere Transitions Using High-Resolution Ozonesondes
by Orla Dingley, Michael Connolly, Ronan Connolly and Willie Soon
Environ. Sci. Proc. 2022, 19(1), 14; https://doi.org/10.3390/ecas2022-12807 - 14 Jul 2022
Viewed by 1915
Abstract
In recent years, NOAA Earth System Research Laboratories (ESRL) have been launching very high quality and high resolution ozonesondes from eight sites across the globe: Antarctica; Greenland; American Samoa; Fiji; and several sites in USA (Alabama, California, Colorado and Hawai’i). These locations collectively [...] Read more.
In recent years, NOAA Earth System Research Laboratories (ESRL) have been launching very high quality and high resolution ozonesondes from eight sites across the globe: Antarctica; Greenland; American Samoa; Fiji; and several sites in USA (Alabama, California, Colorado and Hawai’i). These locations collectively cover the tropics, mid-latitudes and polar regions. The balloons provide in situ measurements approximately every second throughout their vertical ascent and descent in the troposphere, tropopause and stratosphere (up to ~30–35 km altitude). This unique high quality and publicly archived dataset allows direct inter-comparisons between various new and old techniques for analyzing the troposphere/stratosphere transitions that were not previously possible. With this in mind, we have analyzed one complete year (2016) of ozonesonde data from these eight locations in terms of several definitions of the tropopause. We find a surprising cohesiveness between many of the independent definitions of the tropopause that does not appear to have been properly recognized until now. These definitions appear to hold over all eight locations—from the tropics to the poles—for all seasons. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Locations of the eight ozonesonde stations.</p>
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<p>Relevant measurements from a typical ozonesonde plotted against atmospheric pressure—launched from Boulder, Colorado on 13 October 2016. (<bold>a</bold>) Time elapsed since the sonde was launched; (<bold>b</bold>) altitude; (<bold>c</bold>) temperature; (<bold>d</bold>) water content; (<bold>e</bold>) ozone content. NOAA’s estimate of the tropopause (as provided with each ozonesonde record) is indicated in each panel by a horizontal dashed gray line. As Boulder is a mountainous location, the ground level has a relatively low atmospheric pressure as indicated by the green boxes in panels (<bold>a</bold>,<bold>c</bold>–<bold>e</bold>).</p>
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<p>Calculated metrics from the same ozonesonde as <xref ref-type="fig" rid="environsciproc-19-00014-f002">Figure 2</xref>. (<bold>a</bold>) The observed molar density is plotted in black along with a straight line slope in yellow that is fit over the region 30,000–50,000 Pa, as discussed in the text; (<bold>b</bold>) temperature lapse rate in K m<sup>−</sup><sup>1</sup>; (<bold>c</bold>) water content lapse rate in ppmv m<sup>−</sup><sup>1</sup>; (<bold>d</bold>) ozone content lapse rate in ppmv m<sup>−</sup><sup>1</sup>. All lapse rates are calculated using a 31-point centered box car average. The tropopause calculated from each approach is indicated on the corresponding panel by horizontal dashed lines with distinct colors matching those in <xref ref-type="fig" rid="environsciproc-19-00014-f004">Figure 4</xref>.</p>
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<p>Changes in the location of the tropopause for the eight stations for the entire year of 2016, as calculated using each of the metrics described in the text: (<bold>a</bold>) Greenland; (<bold>b</bold>) California, USA; (<bold>c</bold>) Colorado, USA; (<bold>d</bold>) Alabama, USA; (<bold>e</bold>) Hawai’i,USA; (<bold>f</bold>) American Samoa; (<bold>g</bold>) Fiji; (<bold>h</bold>) Antarctica. The colors used for each estimate are the same ones used for the equivalent horizontal lines in <xref ref-type="fig" rid="environsciproc-19-00014-f002">Figure 2</xref> and <xref ref-type="fig" rid="environsciproc-19-00014-f003">Figure 3</xref>.</p>
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6 pages, 1561 KiB  
Proceeding Paper
Local Climate Zones (LCZs) and Urban Morphological Parameters Using GIS: An Application to Italian Cities
by Riccardo Buccolieri, Antonio Esposito, Gianluca Pappaccogli, Myrtille Grulois, Antonio Donateo, Jose Luis Santiago, Alberto Martilli, Giuseppe Maffeis and Pietro Salizzoni
Environ. Sci. Proc. 2022, 19(1), 15; https://doi.org/10.3390/ecas2022-12795 - 14 Jul 2022
Viewed by 1562
Abstract
LCZs refer to a classification system that exists out of 17 classes, 10 of which can be described as urban, proposed as the new standard for characterizing and comparing urban landscapes. This study evaluates the reliability of the LCZ level 0 map obtained [...] Read more.
LCZs refer to a classification system that exists out of 17 classes, 10 of which can be described as urban, proposed as the new standard for characterizing and comparing urban landscapes. This study evaluates the reliability of the LCZ level 0 map obtained from WUDAPT by comparing it with a more detailed LCZ map inferred from the morphological information of several Italian cities. Morphological data from Digital Elevation Models (DEMs) are used to obtain a detailed morphological characterization of each city. Preliminary results for the city of Lecce show that the WUDAPT L0 method misclassified some LCZs, especially at the core urban cells, whereas wider matching is observed at the boundary between urban and rural areas. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Urban (1–10) and natural (A–G) LCZ types and their characteristics and colour code used in the WUDAPT framework. B: buildings; C: cover; M: materials; F: function; Tall: &gt;10 stories, Mid-rise: 3–9 stories, Low: 1–3 stories [<xref ref-type="bibr" rid="B3-environsciproc-19-00015">3</xref>].</p>
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<p>Examples of morphological parameters obtained from GIS for the city of Lecce.</p>
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<p>LCZ maps obtained using morphological parameters (LCZ GIS) and generated in WUDAPT (LCZ WUDAPT) for the city of Lecce, with indication of percentage area and percentage occurrence for the different LCZ classes.</p>
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6 pages, 938 KiB  
Proceeding Paper
Wintertime Variation in Carbonaceous Components of PM10 in the High Altitudes of Himalayas
by Nikki Choudhary, Priyanka Srivastava, Monami Dutta, Sauryadeep Mukherjee, Akansha Rai, Sakshi Gupta, Jagdish Chandra Kuniyal, Renu Lata, Abhijit Chatterjee, Manish Naja, Tuhin Kumar Mandal and Sudhir Kumar Sharma
Environ. Sci. Proc. 2022, 19(1), 16; https://doi.org/10.3390/ecas2022-12802 - 14 Jul 2022
Viewed by 1140
Abstract
Carbonaceous aerosols play a significant role in the Earth’s atmospheric system by affecting visibility, the hydrological cycle, the climate, radiative forcing, and human health. The present study analyses PM10 samples that were collected at three distinct urban locations (Mohal-Kullu, Nainital, and Darjeeling) [...] Read more.
Carbonaceous aerosols play a significant role in the Earth’s atmospheric system by affecting visibility, the hydrological cycle, the climate, radiative forcing, and human health. The present study analyses PM10 samples that were collected at three distinct urban locations (Mohal-Kullu, Nainital, and Darjeeling) over the Himalayan region of India during winter 2019. The mass concentrations of PM10 were recorded as 51 ± 16 μg m−3, 38 ± 9 μg m−3, and 52 ± 18 μg m−3 for Mohal-Kullu, Nainital, and Darjeeling, respectively. Organic carbon (OC) dominated over elemental carbon (EC) and was found to be 50.2%, 42.8%, and 47% of total carbon (TC) at Mohal-Kullu, Nainital, and Darjeeling, respectively. The respective mass concentrations of carbonaceous species [OC, EC, water-soluble organic carbon (WSOC), and total carbonaceous aerosol (TCA)] were higher at Mohal-Kullu (OC: 11.1 ± 5.3, EC: 4.2 ± 1.9, WSOC: 5.3 ± 1.3 μg m−3, and TCA: 22.1 ± 10.4 μg m−3) followed by Darjeeling (OC: 5.4 ± 2.0, EC: 2.7 ± 1.0, WSOC: 3.9 ± 1.3 μg m−3, and TCA: 22.1 ± 10.4 μg m−3) and Nainital (OC: 2.9 ± 1.0, EC: 1.3 ± 0.6, WSOC: 2.1 ± 0.6 μg m−3, and TCA: 6.7 ± 2.4 μg m−3). The OC/EC and WSOC/OC ratio at Mohal-Kullu (2.6 ± 0.3, 0.6 ± 0.2), Nainital (2.0 ± 0.4, 0.7 ± 0.2), and Darjeeling (2.3 ± 0.5, 0.7 ± 0.2), respectively, indicates the dominance of fossil fuel combustion (coal and vehicular exhaust), with signified additional contribution from secondary organic carbon (SOC). Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>(<bold>a</bold>) Mass concentration of carbonaceous components of PM<sub>10</sub> (<bold>b</bold>) diagnostic ratios of carbonaceous components at different study sites of the Indian Himalayan Region IHR.</p>
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<p>Scatter plots of carbonaceous components of PM<sub>10</sub> (<bold>a</bold>) OC with EC (<bold>b</bold>) WSOC with OC (<bold>c</bold>) SOC with OC at different sites of the IHR.</p>
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<p>Wintertime air-mass backward trajectories of the study sites at 500 m AGL.</p>
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5 pages, 2029 KiB  
Proceeding Paper
Impact of the Atmospheric Correction on Infrared Camera Measurements
by Jesús Zarza Belmonte and Antonio Serrano Pérez
Environ. Sci. Proc. 2022, 19(1), 17; https://doi.org/10.3390/ecas2022-12859 - 28 Jul 2022
Viewed by 949
Abstract
Monitoring clouds is necessary for many applications, such as aircraft navigation, astronomical observations and others. The height of the top and the bottom of the clouds can be retrieved from satellites and ground-based stations, respectively, by measuring their brightness temperature. In this context, [...] Read more.
Monitoring clouds is necessary for many applications, such as aircraft navigation, astronomical observations and others. The height of the top and the bottom of the clouds can be retrieved from satellites and ground-based stations, respectively, by measuring their brightness temperature. In this context, ground-based infrared cameras offer interesting information about the spatial distribution of clouds and the height of their bases. Some atmospheric gases interact significantly with the radiation emitted by clouds, aerosols, atmospheric gases and the Earth’s surface, so an atmospheric correction is needed to obtain reliable estimates of a cloud base. In this study, the influence of water vapor and carbon dioxide on the downward radiance measured by a FLIR infrared camera on a height variable cloudy scenario is analyzed. The FLIR A325SC camera spectral response function is considered and standard atmospheric profiles are used. The infrared absorption and emission of the profiles of water vapor and carbon dioxide is estimated by the Python package ‘RADIS’. The results show a positive net atmospheric effect on the downward radiance for all the standard atmospheric profiles considered, which indicates a higher emission contribution of the atmospheric gases compared with the absorption. However, the magnitude of the atmospheric effect significantly depends on the specific atmospheric profile. For example, the atmospheric net emission effect on the downward radiation for high clouds with a Tropical atmospheric profile is around 30 W/(m2·sr), whereas for a Subarctic Winter atmospheric profile it is less than 8 W/(m2·sr). The main results show that the atmospheric effect notably depends also on the vertical gradient, being particularly high for the Tropical profile. Moreover, regarding a specific profile, the atmospheric correction becomes more important for high clouds than for medium or low clouds. Therefore, the atmospheric correction should not be neglected if accurate estimations of the cloud height are to be obtained. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Standard spectral response function of an FLIR infrared camera.</p>
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<p>Cloud radiance registered by a typical FLIR infrared camera considering six standard atmospheric profiles: (<bold>a</bold>) US Standard (<bold>b</bold>) Tropic (<bold>c</bold>) Mid-Latitude Summer (<bold>d</bold>) Mid-Latitude Winter (<bold>e</bold>) Subarctic Summer (<bold>f</bold>) Subarctic Winter. The red line represents cloud radiance without atmospheric effect and the blue line represents cloud radiance considering the radiative effect of the atmospheric gases.</p>
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<p>(<bold>a</bold>) Standard temperature profiles. (<bold>b</bold>) Standard relative humidity profiles.</p>
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<p>Difference between the cloud radiance considering the effect of the atmosphere and the cloud radiance without atmospheric effect.</p>
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14 pages, 471 KiB  
Proceeding Paper
An Introduction to Atmospheric Pollutant Dispersion Modelling
by Joel B. Johnson
Environ. Sci. Proc. 2022, 19(1), 18; https://doi.org/10.3390/ecas2022-12826 - 14 Jul 2022
Cited by 7 | Viewed by 11047
Abstract
Modelling the dispersion of atmospheric pollutants plays an important role in regulatory and epidemiological settings. Although the majority of modelling concepts were developed in the 1980s, a significant amount of optimisation and refinement of dispersion models has occurred since this time. In addition, [...] Read more.
Modelling the dispersion of atmospheric pollutants plays an important role in regulatory and epidemiological settings. Although the majority of modelling concepts were developed in the 1980s, a significant amount of optimisation and refinement of dispersion models has occurred since this time. In addition, some completely novel models such as computational fluid dynamics have emerged. Furthermore, next generation models are continually improving the accuracies of the results obtained. This review provides a non-technical outline of the mechanisms of atmospheric pollutant dispersion modelling and discusses common model types and their applications. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>A representation of a Gaussian plume model. Image by Milton Beychok; reproduced under Creative Commons 3.0 licence.</p>
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6 pages, 520 KiB  
Proceeding Paper
Occupational Risk Assessment in E-Waste Plant: Progress Achieved over Years
by Giulia Simonetti, Leonardo Romani, Carmela Riccardi, Donatella Pomata, Patrizia Di Filippo and Francesca Buiarelli
Environ. Sci. Proc. 2022, 19(1), 19; https://doi.org/10.3390/ecas2022-12796 - 14 Jul 2022
Cited by 1 | Viewed by 1045
Abstract
The present paper deals with the risk assessment of the exposure of workers to polybrominated diphenyl ethers, polychlorobiphenyls and some brominated flame retardants detected in both settled dust and airborne particulate matter collected in an e-waste recycling plant. The concentration values of target [...] Read more.
The present paper deals with the risk assessment of the exposure of workers to polybrominated diphenyl ethers, polychlorobiphenyls and some brominated flame retardants detected in both settled dust and airborne particulate matter collected in an e-waste recycling plant. The concentration values of target analytes were used to perform the risk assessment by considering the three different exposure routes: inhalation, ingestion and the dermal absorption of particles. Both carcinogenic and non-carcinogenic risk factors were determined to estimate the human health risk associated to the study site and to evaluate how plant improvements affected air quality and reduced risks for workers involved in recycling operations. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Carcinogenic and non-carcinogenic risk for PCBs (panel (<bold>a</bold>)), PBDEs (panel (<bold>b</bold>)), and BFRs (panel (<bold>c</bold>)) for the three exposure routes over years. For PBDEs and BFRs, inhalation HQ is displayed on the secondary axis.</p>
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7 pages, 1454 KiB  
Proceeding Paper
Data Assimilation System Applied to Short-Range Forecast System
by Pedro M. González, Maibys Sierra and Adrián L. Ferrer
Environ. Sci. Proc. 2022, 19(1), 20; https://doi.org/10.3390/ecas2022-12806 - 14 Jul 2022
Viewed by 806
Abstract
An evaluation of 3DVAR, 3DEnVAR and 4DEnVAR methods is carried out, assimilating in a combined way prepbufr and radiances data, applied to the Short-range Forecast System to determine which scheme is more suitable for short-term forecasting purposes. The results suggest that hybrid schemes [...] Read more.
An evaluation of 3DVAR, 3DEnVAR and 4DEnVAR methods is carried out, assimilating in a combined way prepbufr and radiances data, applied to the Short-range Forecast System to determine which scheme is more suitable for short-term forecasting purposes. The results suggest that hybrid schemes tend to generate more accurate forecasts than 3DVAR; however, 4DEnVAR is the most robust scheme and therefore the one that provides more realistic solutions. The forecast of the accumulated rainfall in 24 h constitutes the greatest difficulty since all the assimilation schemes generate underestimates related to the 24 h rainfall forecast. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>SisPI’s domains. Red box represents the parent domain; blue box represents the 9 km nested domain and green box the high-resolution domain (3 km).</p>
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<p>Cost function reduction obtained by the different methods, (<bold>a</bold>) experiment initialized on 7 November 2020 at 12 UTC corresponding to tropical storm ETA; (<bold>b</bold>) experiment initialized on 23 May 2020 at 12 UTC corresponding to mesoscale convective system.</p>
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<p>Cross-section showing the incremental analysis corresponding to 00:00 UTC initialization for mesoscale convective system case. Shaded represent the temperature increments and contour lines the specific humidity increments. (<bold>a</bold>) 3DVAR; (<bold>b</bold>) 3DEnVAR; (<bold>c</bold>) 4DEnVAR.</p>
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<p>Performance evaluation of 24 h accumulated precipitation forecast derived from SisPI and the different assimilation schemes. (<bold>a</bold>) Eta’s case, (<bold>b</bold>) thunderstorm’s case, both initialized at 00:00 UTC.</p>
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10 pages, 5901 KiB  
Proceeding Paper
Performance Assessment of CHIRPSv2.0 and MERRA-2 Gridded Precipitation Datasets over Complex Topography of Turkey
by Hamed Hafizi and Ali Arda Sorman
Environ. Sci. Proc. 2022, 19(1), 21; https://doi.org/10.3390/ecas2022-12815 - 14 Jul 2022
Cited by 3 | Viewed by 1454
Abstract
Precipitation is a major component of the global water cycle, and its accurate measurement, especially over complex topography, requires a dense gauge network, which is often limited for many parts of the world. In recent decades, gridded precipitation datasets (GPDs) that merge information [...] Read more.
Precipitation is a major component of the global water cycle, and its accurate measurement, especially over complex topography, requires a dense gauge network, which is often limited for many parts of the world. In recent decades, gridded precipitation datasets (GPDs) that merge information from satellites, numerical weather prediction models, and available ground data could be a potential alternative source for many hydro-climatic studies. However, their validation is a prerequisite task before utilizing them for different applications. This study aims to evaluate the spatio-temporal consistency of CHIRPSv2.0 and MERRA-2 datasets over different elevation ranges in Turkey based on five hydrological years (2015–2019) under Kling-Gupta Efficiency (KGE) metric for daily and monthly time steps. Moreover, three categorical indicators, including Threat Score (TS), Pierce Skill Score (PSS), and Gilbert Skill Score (GSS), are employed to address GPD detectability strength for various precipitation intensities. In general, GPDs show high performance for monthly (median KGE of; 0.62–0.76) time step than daily (median KGE of; 0.19–0.28), and MERRA-2 outperforms CHIRPSv2.0 considering daily precipitation, while CHIRPSv2.0 shows higher performance for monthly precipitation, comparatively. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Shows the digital elevation model (DEM) using 30 m SRTM (Shuttle Radar Topography Mission—<uri>https://eartheplorer.usgs.gov</uri> (accessed on 3 May 2022)) and station distribution over different elevation ranges.</p>
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<p>Mean daily and monthly precipitation from observed, CHIRPSv2.0, and MERRA-2 over the entire region and four elevation ranges.</p>
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<p>Reliability of CHIRPSv2.0 and MERRA-2 at the station location expressed in the form of KGE and its three components for daily and monthly precipitation.</p>
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<p>Reliability of CHIRPSv2.0 and MERRA-2 at the regional scale expressed in the form of KGE and its three components for daily and monthly precipitation.</p>
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<p>GPDs’ skill in reproducing daily precipitation events of different intensities is stated in the form of TS, PSS, and GSS over the entire region and four elevation ranges.</p>
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7 pages, 508 KiB  
Proceeding Paper
Stochastics Modelling of Rainfall Process in Asia Region: A Systematics Review
by Hilda Ayu Pratikasiwi, Elma Dwi Putri Sinaga, Hanny Nirwani, Milkah Royna, Perdinan and Akhmad Faqih
Environ. Sci. Proc. 2022, 19(1), 22; https://doi.org/10.3390/ecas2022-12816 - 14 Jul 2022
Viewed by 1071
Abstract
In recent years, use of the stochastic model has been growing due to the high complexity and dynamics of the atmosphere, especially the rainfall process. Various concepts have been applied to rainfall modeling, ranging from simplistic approaches to more complex models. It is [...] Read more.
In recent years, use of the stochastic model has been growing due to the high complexity and dynamics of the atmosphere, especially the rainfall process. Various concepts have been applied to rainfall modeling, ranging from simplistic approaches to more complex models. It is important to understand different stochastic rainfall modeling approaches, as well as their advantages and limitations. This paper determines the development of the latest stochastic rainfall models in the Asia region, where different concepts of stochastic rainfall models were highlighted. It reviews the different methodologies used, including rainfall forecasting, spatio-temporal analysis, and extreme event. We select 30 articles from 1571 literature published between 2013–2022 from the Scopus database. The results show that the stochastic models often used in the literature consist of Markov chain, weather generator, probability distribution, ARIMA, and the Bayesian model. In the recent development in Asia, stochastic models in rainfall modeling research are widely used to generate the occurrence and amount of rainfall data, statistical downscaling, future rainfall trends, and estimation of extreme values. The difference in spatio-temporal, climate conditions, and the parameters model can cause the performance of each model to be different. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Flowchart outlining protocol of review using PRISMA.</p>
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10 pages, 2696 KiB  
Proceeding Paper
Drop Size Distribution Retrievals for Light Rain and Drizzle from S-Band Polarimetric Radars
by Merhala Thurai, Viswanathan Bringi, David Wolff, David Marks, Charanjit Pabla and Patrick Kennedy
Environ. Sci. Proc. 2022, 19(1), 23; https://doi.org/10.3390/ecas2022-12794 - 14 Jul 2022
Cited by 2 | Viewed by 1076
Abstract
Measurements of full drop size distribution (DSD) spectra were used as input for scattering calculations to derive fitted equations for light rain and drizzle for estimating the mass-weighted mean diameter, Dm, from radar reflectivity (Zh) at S-band. Testing was [...] Read more.
Measurements of full drop size distribution (DSD) spectra were used as input for scattering calculations to derive fitted equations for light rain and drizzle for estimating the mass-weighted mean diameter, Dm, from radar reflectivity (Zh) at S-band. Testing was performed using Zh measured S-band polarimetric radars over two different disdrometer locations versus Dm from disdrometer measurements. Consistent results were obtained but only for Zh < 18 dBZ for light rain and <5 dBZ for drizzle. Additionally, gridded radar data were used to identify light rain and drizzle regions, and their Dm histograms were compared with those derived from stratiform and convective rain regions. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Scattering simulations using DSD measurements. DSD-based D<sub>m</sub> versus (<bold>a</bold>) Z<sub>dr</sub> and (<bold>b</bold>) Z<sub>h</sub> both at S-band. The orange points represent the measurements in stratocumulus drizzle (aircraft) and the green points represent measurements from ground-based disdrometers in Greeley, Colorado, and Huntsville, Alabama.</p>
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<p>Same as panel (b) of <xref ref-type="fig" rid="environsciproc-19-00023-f001">Figure 1</xref> but with experimental data (black points) superimposed from an event on 17 April 2015 at Greeley, Colorado, with Dm values from 3 min DSD disdrometer measurements and Z<sub>h</sub> from the CSU-CHILL S-band radar measurements over the disdrometer site.</p>
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<p>Same as panel (b) of <xref ref-type="fig" rid="environsciproc-19-00023-f001">Figure 1</xref> but with experimental data (red points) superimposed from an event over the Delmarva peninsula (outer-rainbands of category-1 Hurricane Dorian on 6 September 2019), shown as red points, with D<sub>m</sub> values from 3-min DSD disdrometer measurements and Z<sub>h</sub> from the NPOL S-band radar measurements over the disdrometer site.</p>
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<p>Same as <xref ref-type="fig" rid="environsciproc-19-00023-f001">Figure 1</xref>, with fitted curves superimposed for both drizzle (orange-line) and the ground-based data (green).</p>
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<p>D<sub>m</sub>’s from 3 min DSDs (purple) for the long duration event on 17 April 2015 and D<sub>m</sub> estimates from the CSU-CHILL S-band radar dBZ over the disdrometer site using the fitted equation for (<bold>a</bold>) light rain (green points) and (<bold>b</bold>) drizzle (orange). The orange and the green arrows represent the time intervals when the drizzle fit and the light-rain fit yield better agreement with the DSD-based D<sub>m</sub>s, respectively.</p>
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<p>(<bold>a</bold>) D<sub>m</sub> comparisons for another event (10 August 2015) in the same way as <xref ref-type="fig" rid="environsciproc-19-00023-f005">Figure 5</xref>. (<bold>b</bold>) CHILL S-band RHI scan taken along the azimuth angle of the disdrometer site (at 13 km range, marked with a dashed white line) at 22:03 UTC. The blue arrows point to the different rain types as they passed over the disdrometer site corresponding to the UTC in panel (a).</p>
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<p>(<bold>a</bold>) The 500 m × 500 m gridded data (dBZ) constructed from NPOL volume scan during an embedded line convection event over the Delmarva peninsula on 30 April 2021 (see [<xref ref-type="bibr" rid="B20-environsciproc-19-00023">20</xref>] for details). (<bold>b</bold>) Rain-type classification (retrieved DSD-based) for stratiform, convective, and mixed rain types and regions identified as light rain marked in black. (<bold>c</bold>) D<sub>m</sub> histograms estimated for the regions identified as light rain compared with those for stratiform and convective rain.</p>
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<p>(<bold>a</bold>) The 500 m × 500 m gridded data (dBZ) constructed from NPOL volume scan during remnants of storm Sally over the Delmarva peninsula on 17–18 September 2020. (<bold>b</bold>) D<sub>m</sub> histogram estimated for the region identified as light rain (grey) compared with that for other rain regions from the NPOL data (blue) and from 3 min DSD measurements (green). (<bold>c</bold>) D<sub>m</sub> from 3 min DSD measurements from disdrometers for the entire event.</p>
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3 pages, 204 KiB  
Proceeding Paper
Study on the Relationship of WSIS of PM2.5 with NH3 and Other Trace Gases over Delhi, India
by Garima Kotnala, Sudhir Kumar Sharma and Tuhin Kumar Mandal
Environ. Sci. Proc. 2022, 19(1), 24; https://doi.org/10.3390/ecas2022-12817 - 14 Jul 2022
Viewed by 749
Abstract
The water soluble ionic species (WSIS) i.e., NH4+, SO42−, NO3 and Cl of PM2.5 and trace gases (NH3, NO, NO2, SO2, HNO3) were measured to [...] Read more.
The water soluble ionic species (WSIS) i.e., NH4+, SO42−, NO3 and Cl of PM2.5 and trace gases (NH3, NO, NO2, SO2, HNO3) were measured to study the relationship of ambient NH3 in the formation of secondary inorganic aerosols in Delhi, India from January 2013–December 2018. During the study period, the average concentrations of NH3, NO, NO2, SO2 and HNO3 were 19.1 ± 3.8 ppb, 20.8 ± 4.3 ppb, 17.9 ± 4.2 ppb, 2.45 ± 0.47 ppb, 1.11 ± 0.35 ppb, respectively. The concentrations of trace gases were higher during post-monsoon whereas the concentrations of WSIS in PM2.5 were estimated higher in winter. The correlation matrix of trace gases reveal that the ambient NH3 neutralize the acid gases (NO, NO2 and SO2) at the monitoring site. Study reveals that the abundance of particulate NH4+ at Delhi to neutralized the SO42−, NO3, Cl particles during all the seasons. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
6 pages, 1239 KiB  
Proceeding Paper
Statistical Correction of the Distribution of Solar Radiation, Estimated by the Heliosat Method for Cuba
by Krystine Naranjo-Villalón and Israel Borrajero-Montejo
Environ. Sci. Proc. 2022, 19(1), 25; https://doi.org/10.3390/ecas2022-12862 - 1 Aug 2022
Viewed by 902
Abstract
In this work, a statistical correction of the distribution of solar radiation in Cuba estimated by the Heliosat method is obtained, using images collected from the GOES-13 satellite for the period 2012–2017. A need has arisen for an improvement in the updating of [...] Read more.
In this work, a statistical correction of the distribution of solar radiation in Cuba estimated by the Heliosat method is obtained, using images collected from the GOES-13 satellite for the period 2012–2017. A need has arisen for an improvement in the updating of the distribution of solar radiation in the country, because when the average annual maps of solar radiation estimated by the Heliosat method are compared with data from stations where solar radiation is measured, and when compared with the Annual Average Map of solar radiation published by the firm Solargis, an overestimation of solar radiation values was noted, as if the effect of cloud cover attenuation, as calculated by Heliosat, was less than the effect of real cloud attenuation. Therefore, it is necessary to improve the updating of the behavior of solar radiation in Cuba due to the relevance of this information related to solar radiation as a renewable source of energy, and due to its use in the evaluation of the country’s helioenergetic potential. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Annual mean map of global solar radiation (<inline-formula><mml:math id="mm18"><mml:semantics><mml:mrow><mml:mi>Wh</mml:mi><mml:mo>/</mml:mo><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mn>2</mml:mn></mml:msup></mml:mrow></mml:semantics></mml:math></inline-formula>).</p>
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<p>Error distribution (Heliosat-Stations) based on the value estimated by Heliosat and the adjusted second-degree equation.</p>
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<p>(<bold>a</bold>) Dispersion diagram for the independent sample of the daily sum values of global solar radiation estimated by Heliosat and reported at the stations. The values are shown without rectification. (<bold>b</bold>) Dispersion diagram for the independent sample of the daily sum values of global solar radiation estimated by Heliosat and reported at the stations. The rectified values are shown.</p>
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<p>Annual mean map of rectified global solar radiation.</p>
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5 pages, 2112 KiB  
Proceeding Paper
Particle Size Distribution from Municipal Solid Waste Burning over National Capital Territory, India
by Rahul Arya, Sakshi Ahlawat, Lokesh Yadav, Ritu Jangirh, Arnab Mondal, Sudhir Kumar Sharma, Bhola Ram Gurjar, Eiko Nemitz and Tuhin Kumar Mandal
Environ. Sci. Proc. 2022, 19(1), 26; https://doi.org/10.3390/ecas2022-12813 - 14 Jul 2022
Cited by 2 | Viewed by 1634
Abstract
Emission of particulate matter (PM) of different sizes from Municipal Solid Waste (MSW) burning may have an impact on air quality and human health of the National Capital Territory (NCT) of India, particularly during winter months. MSW samples were collected from three sanitary [...] Read more.
Emission of particulate matter (PM) of different sizes from Municipal Solid Waste (MSW) burning may have an impact on air quality and human health of the National Capital Territory (NCT) of India, particularly during winter months. MSW samples were collected from three sanitary landfill sites in the NCT Delhi. Experiments were performed to mimic real world burning during different stages of sample combustion (ignition, flaming smoldering, smoldering and pyrolysis). We determined the emission factor for the number and mass concentration of particles of different sizes, ranging from 0.34 to 9.05 µm, for MSW burning. Present results confirm the assumption that MSW burning emits the maximum number concentration (No/cm3) of particles (90%) in the range < 1.0 µm, or fine-mode aerosol. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Location (<bold>a</bold>) of collection over NCT and experiment setup (<bold>b</bold>).</p>
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<p>(<bold>a</bold>–<bold>c</bold>) Particle number concentration by size from different phases during burning of MSW samples collected from three sites: (<bold>a</bold>) Bhlaswa (Site-I), (<bold>b</bold>) Ghazipur (Site-II) and (<bold>c</bold>) Okhla (Site-III) (dilution ratio 1:100).</p>
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<p>Percentage distribution of particle number concentration for different size ranges (0.37–1.0, 1.0–2.5 and 2.5–10 µm) at Bhlaswa (Site-I), Ghazipur (Site-II) and Okhla (Site-III) (dilution ratio 1:100).</p>
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<p>Emission factor (mg/kg) for particles of different size at the sample sites, namely, Bhlaswa (Site-I), Ghazipur (Site-II) and Okhla (Site-III) (dilution ratio 1:100).</p>
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7 pages, 540 KiB  
Proceeding Paper
Tropical Waves and Their Transit through Cuba during the Period 2012–2020
by Laura E. Guerra, Miguel A. Hernández and Evelio A. García
Environ. Sci. Proc. 2022, 19(1), 27; https://doi.org/10.3390/ecas2022-12822 - 14 Jul 2022
Viewed by 790
Abstract
Fundamentally, during the rainy season, the transit of tropical waves through the seas adjacent to the Cuban archipelago occurs, stimulating deep convection and, later, the occurrence of severe local storms; this is why the general objective is to analyze the behavior of the [...] Read more.
Fundamentally, during the rainy season, the transit of tropical waves through the seas adjacent to the Cuban archipelago occurs, stimulating deep convection and, later, the occurrence of severe local storms; this is why the general objective is to analyze the behavior of the tropical waves that passed through Cuba during the 2012–2020 period. This research will examine the most relevant characteristics of tropical waves, the associated dangerous phenomena, and the number of intensifications or dissipations that occurred after passing through the country. The results obtained contribute to the expansion of knowledge on Tropical Meteorology and aid in making meteorological forecasts related to these systems more effective. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Study area.</p>
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<p>Annual distribution of tropical waves taking into account their travel speed.</p>
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7 pages, 1203 KiB  
Proceeding Paper
Projection of Thermal Bioclimate Conditions over West Bengal, India in Response to Global Warming Based on Climate Model
by Sourabh Bal and Ingo Kirchner
Environ. Sci. Proc. 2022, 19(1), 28; https://doi.org/10.3390/ecas2022-12820 - 14 Jul 2022
Viewed by 1226
Abstract
The study of human bioclimatic conditions is becoming popular in climate perception for the improvement of the public health system. The objective of the present study is to analyze the past and future thermal bioclimate conditions over 15 stations in West Bengal (WB), [...] Read more.
The study of human bioclimatic conditions is becoming popular in climate perception for the improvement of the public health system. The objective of the present study is to analyze the past and future thermal bioclimate conditions over 15 stations in West Bengal (WB), India. The bioclimate conditions are measured by the daily Physiologically Equivalent Temperature (PET) based on climate data extracted from the Coordinated Regional Downscaling Experiment (CORDEX)-South Asia. The initial purpose of this study is to present the interannual distribution of PET classes over the considered stations of WB for the past period (1986–2005) and two future time periods, namely (i) near future (2016–2035) and (ii) mid-21st century (2046–2065). The results from the monthly distribution of PET reveal heat stress conditions from April to June and acceptable thermal conditions from November that persist till March for all the stations except Darjeeling, a hill station. To focus on future PET changes over WB in context to the reference period (1986–2005), warm and hot PET classes show prominent rises in the future epochs under the RCP4.5 and RCP8.5 emission scenarios. The highest percentage in the warm PET class (35.7–43.8 °C) appears in stations near the Bay of Bengal such as Digha, Diamond Harbour, Canning, and Baruipur during the mid-21st century time slice under RCP8.5 conditions. Simultaneously, hot PET class (>43.8 °C) records up to 10% for Kolkata, Dum Dum, Kharagpur, Siliguri and more than 10% in Sriniketan, Malda, Asansol, and Birbhum. Darjeeling will experience the greatest decrease in the very cool PET class (<3.3 °C) in the medium term. The explicit amount of change in temperature is seemingly connected to the increasing levels of heat stress over WB, as is evident from the relative mean monthly changes in PET. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Intra-annual frequency diagram of various PET classes over the investigated stations extracted from the CORDEX (2046–2065) under RCP8.5 conditions. The abbreviations of each station are explained in <xref ref-type="table" rid="environsciproc-19-00028-t001">Table 1</xref>.</p>
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<p>Mean monthly differences of PET and temperature for 15 WB stations considered under CORDEX RCP4.5 and RCP8.5 during 2046–2065 compared to the reference period (1986–2005). The abbreviations of all the investigated stations are described in <xref ref-type="table" rid="environsciproc-19-00028-t001">Table 1</xref>.</p>
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6 pages, 1101 KiB  
Proceeding Paper
A Comparative Analysis of Analytical Hierarchy Process and Machine Learning Techniques to Determine the Fractional Importance of Various Moisture Sources for Iran’s Precipitation
by Mojtaba Heydarizad, Nathsuda Pumijumnong and Luis Gimeno
Environ. Sci. Proc. 2022, 19(1), 29; https://doi.org/10.3390/ecas2022-12839 - 20 Jul 2022
Cited by 2 | Viewed by 772
Abstract
Iran is a semi-arid and arid region in southwest Asia. Hence, studying the moisture sources of precipitation in this country has great importance. Iran’s moisture sources were determined for dry (May to October) and wet (November to April) periods. Understanding the importance of [...] Read more.
Iran is a semi-arid and arid region in southwest Asia. Hence, studying the moisture sources of precipitation in this country has great importance. Iran’s moisture sources were determined for dry (May to October) and wet (November to April) periods. Understanding the importance of each moisture source influencing Iran has great application in climatological models. In this study, the fractional importance of various water bodies providing moisture for Iran was determined for more than 35 years (1981–2015) by various machine learning as well as analytical hierarchy process (AHP) and fuzzy AHP models. Finally, the accuracy of the developed models was validated by the coefficient of determination (R2) and mean squared error (MSE). Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Seasonal variation of (E−P) &gt; 0 (mm/day) for wet (<bold>a</bold>) and dry periods (<bold>b</bold>) between 1981 and 2015 [<xref ref-type="bibr" rid="B9-environsciproc-19-00029">9</xref>].</p>
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<p>The contribution percentage of various moisture sources in Iran for wet and dry periods.</p>
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<p>The fractional importance of various moisture sources influences precipitation across Iran during wet and dry periods.</p>
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6 pages, 1882 KiB  
Proceeding Paper
LSTM Model for Wind Speed and Power Generation Nowcasting
by Adrián Fuentes-Barrios, Maibys Sierra-Lorenzo and Alfredo E. Roque-Rodríguez
Environ. Sci. Proc. 2022, 19(1), 30; https://doi.org/10.3390/ecas2022-12851 - 25 Jul 2022
Viewed by 813
Abstract
In the following work, the design of an LSTM-type neural network model for wind speed and power generation nowcasting, with measurements taken every 10 min and for up to two hours, is presented. For this study, the wind speed measurements were taken every [...] Read more.
In the following work, the design of an LSTM-type neural network model for wind speed and power generation nowcasting, with measurements taken every 10 min and for up to two hours, is presented. For this study, the wind speed measurements were taken every 10 min at different heights above the ground by the measurement tower located in Los Cocos in the province of Holguín (Cuba), where the wind farms Gibara I and II are located. The real data were complemented with the wind speed numerical hourly forecasts from SisPI. The data covered the period between 1 February 2019 and 31 January 2020, that is, one year of measurements. Several LSTM models were built and evaluated, both considering the measurements alone and combining the measurements with the forecasts generated by SisPI. The results suggest that the constructed models perform better than other more traditional statistical models and other neural network models used in the country for similar purposes. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Simulation domains for SisPI. The green square corresponds with the 3km resolution domain used in this study.</p>
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<p>LSTM configuration.</p>
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<p>Behavior of the MAE for the 12 forecast terms of the validation set. The red line represents the results obtained with the data from Torre Los Cocos, and the blue line corresponds to the results obtained by training the LSTM with the SisPI forecast and the tower observations.</p>
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<p>Forecast wind values for each of the case studies rows in order: 11 March 2019 (<bold>a</bold>,<bold>b</bold>), 28 May 2019 (<bold>c</bold>,<bold>d</bold>), 2 August 2019 (<bold>e</bold>,<bold>f</bold>) and 18 November 2019 (<bold>g</bold>,<bold>h</bold>); using the LSTM model trained with observations only (<bold>left column</bold>) and the LSTM model input with SisPI and observations (<bold>right column</bold>).</p>
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<p>Forecast wind values for each of the case studies rows in order: 11 March 2019 (<bold>a</bold>,<bold>b</bold>), 28 May 2019 (<bold>c</bold>,<bold>d</bold>), 2 August 2019 (<bold>e</bold>,<bold>f</bold>) and 18 November 2019 (<bold>g</bold>,<bold>h</bold>); using the LSTM model trained with observations only (<bold>left column</bold>) and the LSTM model input with SisPI and observations (<bold>right column</bold>).</p>
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7 pages, 652 KiB  
Proceeding Paper
Particulate Matter (PM2.5) Concentration Forecasting through an Artificial Neural Network in Port City Environment
by Bárbara A. Macías-Hernández, Edgar Tello-Leal, Ulises Manuel Ramirez-Alcocer and Jaciel David Hernandez-Resendiz
Environ. Sci. Proc. 2022, 19(1), 31; https://doi.org/10.3390/ecas2022-12856 - 25 Jul 2022
Cited by 2 | Viewed by 1204
Abstract
This study aims to analyze maritime traffic’s effect on air quality through multiple regression analysis using recurrent neural networks (RNN), allowing one to forecast the daily concentration of PM2.5. The data set used the hourly average of the pollutant concentration levels [...] Read more.
This study aims to analyze maritime traffic’s effect on air quality through multiple regression analysis using recurrent neural networks (RNN), allowing one to forecast the daily concentration of PM2.5. The data set used the hourly average of the pollutant concentration levels and meteorological factors from 1 May 2021 to 31 January 2022, and the entry and exit of cargo ships and petroleum tankers to the port area in the same range of dates. The regression model based on the ANN reaches an acceptable accuracy with a root-mean-squared error (RMSE) of 5.9554 and a mean absolute error (MAE) of 4.5732. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Correlation matrix of variables of air pollution, meteorological parameters, CS and PT.</p>
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<p>Prediction accuracy comparison between actual and predicted data.</p>
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6 pages, 1021 KiB  
Proceeding Paper
Prediction of Stable Isotopes (18O and 2H) in the Bangkok Metropolitan Area’s Precipitation Using an Artificial Neural Network
by Mojtaba Heydarizad and Nathsuda Pumijumnong
Environ. Sci. Proc. 2022, 19(1), 32; https://doi.org/10.3390/ecas2022-12792 - 14 Jul 2022
Viewed by 894
Abstract
The role of local (wind speed, potential evaporation, vapor pressure, air temperature, and precipitation amount) and regional parameters (teleconnection indices such as Indian Ocean Dipole (IOD), Bivariate ENSO index (BEST), North Atlantic Oscillation (NAO), Southern Oscillation index (SOI), and Quasi Biennial Oscillation (QBO) [...] Read more.
The role of local (wind speed, potential evaporation, vapor pressure, air temperature, and precipitation amount) and regional parameters (teleconnection indices such as Indian Ocean Dipole (IOD), Bivariate ENSO index (BEST), North Atlantic Oscillation (NAO), Southern Oscillation index (SOI), and Quasi Biennial Oscillation (QBO) on the stable isotope content in the precipitation in Bangkok was investigated. First, a simple artificial neural network (ANN) and a Deep Learning Neural Network (DNN) were used to predict the stable isotope content in precipitation. Second, studying the fractional importance of various parameters on the stable isotope content of precipitation demonstrated that among the local and regional parameters, precipitation amount and potential evaporation (local) and the BEST teleconnection index (regional) had dominant roles in controlling the stable isotope content of the precipitation. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>The main air masses influencing Thailand, the direction of SW and NE monsoons, and the study area location (adapted from Laonamsai et al. [<xref ref-type="bibr" rid="B3-environsciproc-19-00032">3</xref>]).</p>
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<p>The comparison between the real and simulated stable isotopes data using the DNN and ANN models on Bangkok’s precipitation.</p>
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<p>The regression correlation between the real and simulated stable isotopes data of Bangkok’s precipitation and R<sup>2</sup> score values.</p>
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8 pages, 514 KiB  
Proceeding Paper
Performance of a Simple Mobile Source Dispersion Model Using Three-Phase Turbulence Model
by Saisantosh Vamshi Harsha Madiraju and Ashok Kumar
Environ. Sci. Proc. 2022, 19(1), 33; https://doi.org/10.3390/ecas2022-12847 - 25 Jul 2022
Viewed by 1016
Abstract
Atmospheric/plume turbulence parametrization is an important input for the estimation of dispersion of pollutants from vehicular exhaust. A Three-Phase Turbulence (TPT) model was proposed by Madiraju and Kumar (2021) considering the critical parameters such as initial vertical plume spread, downwind distance, wind velocity, [...] Read more.
Atmospheric/plume turbulence parametrization is an important input for the estimation of dispersion of pollutants from vehicular exhaust. A Three-Phase Turbulence (TPT) model was proposed by Madiraju and Kumar (2021) considering the critical parameters such as initial vertical plume spread, downwind distance, wind velocity, additional spread due to vehicular wake, thermal turbulence, atmospheric turbulence, road width, residence time and mixing height of mobile source dispersion. The flow regime of the TPT model is divided into the initial phase, transition phase, and dispersion phase. The paper presents the performance of these two types of modeling approaches based on the current practice using dispersion curves from point sources and the new TPT model. The statistical indicators (including mean, sigma, bias, NMSE, correlation coefficient, FA2, and FB) are used as a performance measure to identify the variations in the model results using observed data from three different field studies. The study indicates the changes in the performance of the basic mobile source model with the use of the TPT model. Overall, the performance of the basic mobile source dispersion model has improved slightly by using the TPT model. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>The phases in the TPT model and associated turbulence.</p>
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6 pages, 2296 KiB  
Proceeding Paper
Climatological Variations in the Intensity of Tropical Cyclones Formed over the North Atlantic Basin Using the Hurricane Maximum Potential Intensity (HuMPI) Model
by Albenis Pérez-Alarcón and José C. Fernández-Alvarez
Environ. Sci. Proc. 2022, 19(1), 34; https://doi.org/10.3390/ecas2022-12828 - 14 Jul 2022
Cited by 1 | Viewed by 926
Abstract
In this study, we investigated the variations in the intensity of the tropical cyclones (TCs) formed in the North Atlantic basin from 1982 to 2021, based on the outputs from the Hurricane Maximum Potential Intensity (HuMPI) model. To feed HuMPI, we computed the [...] Read more.
In this study, we investigated the variations in the intensity of the tropical cyclones (TCs) formed in the North Atlantic basin from 1982 to 2021, based on the outputs from the Hurricane Maximum Potential Intensity (HuMPI) model. To feed HuMPI, we computed the annual Sea Surface Temperature (SST) as the SST average from 1 June to 30 November using the Daily Optimum Interpolation SST database. The information for all major hurricanes (MHs, category 3+ on the Saffir–Simpson wind scale) was obtained from the HURDAT2 dataset. While the trend (p < 0.05) in the mean maximum potential intensity (MPI) was approximately 1.14 m/s per decade for the maximum sustained wind speed and −1.57 hPa/decade for the minimum central pressure, the MH intensity did not exhibit any statistically significant trend. The behaviour of the MPI could be explained by the increase (p < 0.05) of the SST at a rate of 0.20 °C/decade. In addition, the increase of the TC intensity in the last 20 seasons (2002–2021) in relation to the period 1982–2001 was quite similar for MHs and MPI, being an increase of 3.89% and 3.20% for the mean maximum wind speed, respectively. Meanwhile, the minimum central pressure decreased by approximately 0.36% in both cases. This latter result is promising for investigating the changes in TC intensity resulting from global warming based on the HuMPI model. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>The red box (5–30° N in latitude and 10–100° W in longitude) delimits the area in which the annual mean Sea Surface Temperature and the Maximum Potential Intensity were computed.</p>
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<p>Annual averaged SST in the red box showed in <xref ref-type="fig" rid="environsciproc-19-00034-f001">Figure 1</xref>. The red dashed line denotes the trend line statically significant at 95%.</p>
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<p>Annual averaged of (<bold>a</bold>) maximum wind speed and (<bold>b</bold>) minimum central pressure for the major hurricanes, based on the HURDAT2 database. The black dashed line represents the linear trend (<italic>p</italic> &gt; 0.05). The discontinuities in the black solid lines denotes a TC season without major hurricanes.</p>
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<p>Annual averaged of (<bold>a</bold>) potential maximum wind speed and (<bold>b</bold>) potential minimum central pressure based on the HuMPI model outputs. The red dashed line represents the linear trend statistically significant at 95%.</p>
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<p>Changes (in percentage) of the mean Sea Surface Temperature, major hurricane intensity and maximum potential intensity in the period 2002–2021 in relation to the period 1982–2001.</p>
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4 pages, 755 KiB  
Proceeding Paper
Recent Changes in Drought Conditions over Greece
by Ioannis Koutsogiannis, Chris G. Tzanis, Ioanna Molla and Kostas Philippopoulos
Environ. Sci. Proc. 2022, 19(1), 35; https://doi.org/10.3390/ecas2022-12819 - 14 Jul 2022
Viewed by 985
Abstract
Different regions of the world are expected to experience an increase in the frequency, duration and intensity of drought phenomena as a result of the ongoing climate change. Enhanced evaporation and water deficiency over large time periods under warmer conditions will have devastating [...] Read more.
Different regions of the world are expected to experience an increase in the frequency, duration and intensity of drought phenomena as a result of the ongoing climate change. Enhanced evaporation and water deficiency over large time periods under warmer conditions will have devastating consequences on the natural ecosystems, food production as well as the global economy. In order to monitor the evolution of climate conditions that may lead to increasing drought phenomena at local, regional or global level, a series of indicators and statistical methods have been developed. In our work, the values of various drought indices from observational data in Greece were studied over the period 1990–2020. By applying the Sen and Mann–Kendall methods, the trends and statistical significance were examined. The results showed that serious drought events take place during summer especially in the southern regions. However, the number of consecutive dry days tends to decrease. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Locations of meteorological stations under study.</p>
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<p>Example of the application of the Sen’s slope <italic>(f = Qt + B)</italic> and Mann-Kendall method to the yearly time series of the CDD index for the Kerkira meteorological station. A positive (negative) trend is indicated by a positive (negative) Z value. <italic>Q</italic> and <italic>B</italic> denote trend’s slope and intercept at 95% and 99% confidence levels.</p>
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7 pages, 2873 KiB  
Proceeding Paper
Near-Reference Air Quality Sensors Can Support Local Planning: A Performance Assessment in Milan, Italy
by Silvia Moroni, Francesco Cruz Torres, Paolo Palomba, Umberto Dal Santo and Cristina Colombi
Environ. Sci. Proc. 2022, 19(1), 36; https://doi.org/10.3390/ecas2022-12814 - 14 Jul 2022
Viewed by 1029
Abstract
At present, 4.2 million deaths occur every year due to ambient air pollution, according to the World Health Organization. In view of reducing such a figure, air quality monitoring and reliable data are essential. Nevertheless, local authorities in urban environments, where pollution levels [...] Read more.
At present, 4.2 million deaths occur every year due to ambient air pollution, according to the World Health Organization. In view of reducing such a figure, air quality monitoring and reliable data are essential. Nevertheless, local authorities in urban environments, where pollution levels are highest, often face a dilemma. On the one hand, the high costs of reference monitors make their large-scale adoption prohibitive, while the easily scalable low-cost sensors often feature significantly lower data quality and lack of calibration. Near reference monitors have been voiced as a promising solution, as they exhibit limited costs, though specific studies assessing their performance against reference monitors are still lacking. This article provides an in-depth assessment of three near reference sensors’ stations performance, through their collocation with regional reference monitors from December 2021 onwards. Two sensors were positioned at high-traffic locations, while the third recorded background pollution levels in Milan, Italy. The sensors’ performance was quantified not only via the coefficient of determination (R2) and the regression model, but also with the Mean Normalized Bias (MNB) and median values. After a first measurement period, sensors were re-calibrated to also appraise their behavioral change, generally exhibiting a performance increase. Results show high correlation for all hourly-recorded pollutants, with peaks for Ozone (O3) (R2 = 0.94) and BC (R2 = 0.93). Although location-specific, such results show an interesting potential for near reference sensors in support of urban air quality planning. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Relationship between near reference and reference monitors’ NO<sub>2</sub> measurements in viale Marche. (<bold>a</bold>) Before calibration; (<bold>b</bold>) after calibration; (<bold>c</bold>) day and night concentrations before calibration; (<bold>d</bold>) day and night concentrations after calibration.</p>
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<p>Relationship between near reference and reference monitors’ measurements (<bold>a</bold>) O<sub>3</sub> concentration evolution over time in via Pascal; (<bold>b</bold>) Linear regression model fitted to the O<sub>3</sub> concentrations in via Pascal; (<bold>c</bold>) BC concentration evolution over time in via Pascal; (<bold>d</bold>) Linear regression model fitted to the BC concentrations in via Pascal.</p>
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<p>Relationship between near and reference monitors’ CO measurements in via Senato. (<bold>a</bold>) concentration evolution over time before calibration; (<bold>b</bold>) linear regression model before calibration; (<bold>c</bold>) concentration evolution over time after calibration; (<bold>d</bold>) linear regression model after calibration.</p>
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7 pages, 281 KiB  
Proceeding Paper
Climate Forcings and Their Influence in the Cordillera Blanca, Perú, Deduced from Spectral Analysis Techniques
by Adrián Fernández-Sánchez, Jose Úbeda Palenque, Luis Miguel Tanarro García, Nuria Naranjo Fernández, José Antonio Álvarez Aldegunde and Johan Chancafé
Environ. Sci. Proc. 2022, 19(1), 38; https://doi.org/10.3390/ecas2022-12831 - 15 Jul 2022
Cited by 1 | Viewed by 908
Abstract
The Cordillera Blanca of Peru (Central Andes) has the highest elevation in the country, and is mostly affected by tropical and regional climate forcings. Spectral techniques are applied to temperature and precipitation records in order to discern the hidden periodicities and to correlate [...] Read more.
The Cordillera Blanca of Peru (Central Andes) has the highest elevation in the country, and is mostly affected by tropical and regional climate forcings. Spectral techniques are applied to temperature and precipitation records in order to discern the hidden periodicities and to correlate the influence of different climate forcing indexes that are also submitted to analysis. Similar periodicities are found for Madden–Julian oscillation (MJO) and intra- and interseasonal scale temperature events; the Humboldt Current and South American low-level jet (SALLJ) periodicities are close to annual meteorological events, and El Niño–Southern Oscillation (ENSO) and Intertropical Convergence Zone (ITCZ) displacements are correlated with interannual scale temperature and precipitation events. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
7 pages, 1196 KiB  
Proceeding Paper
COSMO-CLM Russian Arctic Hindcast, 1980–2016: Surface Wind Speed Evaluation and Future Perspectives
by Vladimir Platonov and Aksinia Boiko
Environ. Sci. Proc. 2022, 19(1), 39; https://doi.org/10.3390/ecas2022-12823 - 14 Jul 2022
Cited by 1 | Viewed by 853
Abstract
The surface wind speed reproduction by the novel COSMO-CLM Russian Arctic hindcast, with a ~12 km grid size, for the period 1980–2016, was evaluated in this study, according to station and satellite data. The mean wind speed was well reproduced by the hindcast, [...] Read more.
The surface wind speed reproduction by the novel COSMO-CLM Russian Arctic hindcast, with a ~12 km grid size, for the period 1980–2016, was evaluated in this study, according to station and satellite data. The mean wind speed was well reproduced by the hindcast, while the errors related mainly to cases when the wind speed was overestimated by the model data, up to 2 m/s. However, the extreme values (0.95 and 0.999 quantiles), according to the hindcast, were underestimated to up to −5–−10 m/s. The evaluation, according to the SAR Radarsat-2, high-resolution satellite images, including the FSS score, revealed the hindcast’s capability to reproduce β-mesoscale processes, unlike the γ-scale processes. For all 5 m/s threshold-exceeding features, a ~45 km resolution was enough for the relevant reproduction by the hindcast. At the same time, the given model grid size (~12 km) was not sufficient to reproduce extreme wind speeds, exceeding 20 m/s. Future perspectives of the COSMO-CLM Russian Arctic hindcast include the evaluations of diurnal cycles; wind speed trends; satellite data analysis for other regions of the Russian Arctic; the focus on extreme and severe events’ statistics evaluation; and quality estimation, based on other high-resolution, recent datasets. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>COSMO-CLM Russian Arctic hindcast area [<xref ref-type="bibr" rid="B6-environsciproc-19-00039">6</xref>] (<bold>a</bold>) and weather station locations selected in this study (<bold>b</bold>).</p>
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<p>Mean errors for hindcast wind speed according to station data (<bold>a</bold>), m/s; difference between hindcast and station data in 0.999 quantiles (<bold>b</bold>), m/s.</p>
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<p>SAR (<bold>left</bold>) and hindcast (<bold>right</bold>) wind speed data, interpolated on the common grid after applying land and sea ice masks, m/s (<bold>a</bold>); FSS score plot with regard to number of grid points (size <italic>n</italic>) for 5 m/s threshold, (<bold>b</bold>) for 28 November 2015 case.</p>
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9 pages, 8137 KiB  
Proceeding Paper
Analysis of SisPI Performance to Represent the North Atlantic Subtropical Anticyclone
by Jaina María Paula Méndez, Maibys Sierra Lorenzo and Pedro Manuel González Jardines
Environ. Sci. Proc. 2022, 19(1), 40; https://doi.org/10.3390/ecas2022-12804 - 14 Jul 2022
Viewed by 995
Abstract
This research evaluates the performance of the Short-Range Forecast System (SisPI by its acronym in Spanish) to represent the North Atlantic subtropical anticyclone over the parent domain during the 2020 wet season. For this, an average for the 2010–2019 decade was calculated using [...] Read more.
This research evaluates the performance of the Short-Range Forecast System (SisPI by its acronym in Spanish) to represent the North Atlantic subtropical anticyclone over the parent domain during the 2020 wet season. For this, an average for the 2010–2019 decade was calculated using data from the ERA5 reanalysis at different levels of the troposphere for variables of geopotential height, relative humidity, temperature and wind to characterize the main systems that disturb the weather in the study area, to obtain the corresponding anomalies and to determine if the errors influence these anomalies or the SisPI configuration. For this, it was necessary to interpolate SisPI data to make them match the resolution of ERA5 reanalysis and to be able to perform the calculations and generate the maps, for which a Python code was designed. The results suggest that SisPI tends to locate the high geopotential areas further south of their real position, which modifies the synoptic flow forecasted. On the other hand, the northern and southern borders of the domain have the largest errors, mainly to the north, where, according to the decadal mean and the anomalies obtained in 2020, a baroclinic zone that creates additional noise tends to be generated. To the south, this baroclinic zone lies on segments of the ITCZ which may also be the reason for additional errors in the model. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Mean geopotential height maps at the 500 hPa level in May (<bold>a</bold>) and June (<bold>b</bold>) with their respective relative humidity maps (<bold>c</bold>,<bold>d</bold>) for 2010–2019.</p>
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<p>Mean geopotential height maps (<bold>a</bold>) and temperature (<bold>b</bold>) at 200 hPa level in July from ERA5 reanalysis for 2010–2019.</p>
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<p>ERA5 mean geopotential height maps for May 2020 at the 200 hPa level; (<bold>a</bold>) decadal mean for said month; and (<bold>b</bold>) the correlation between the values obtained for 2020 (blue) and the anomalies compared to the decade (red); (<bold>c</bold>) mean map of the temperature anomalies; and (<bold>d</bold>) the mean map of wind anomalies for the same level in that month.</p>
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<p>ERA5 average maps of geopotential height (<bold>a</bold>) and temperature fields (<bold>b</bold>) at 200 hPa level in July. The relationship between the obtained values in 2020 are shown in blue and the anomalies compared to the decade (red).</p>
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<p>Mean maps of september (<bold>a</bold>) and october (<bold>b</bold>) for gepotencial and wind anomalies at the 1000 hPa level.</p>
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<p>Mean SisPI error maps corresponding to the geopotential (<bold>a</bold>) temperature (<bold>b</bold>) and wind (<bold>c</bold>); at the level of 200 hPa for May 2020.</p>
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<p>Mean maps of SisPI errors geopotential (<bold>a</bold>) and temperature (<bold>b</bold>) fields for July 2020 at 200 hPa level.</p>
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<p>Comparison between the mean representation of geopotential (<bold>a</bold>) and wind (<bold>b</bold>) fields between ERA5 and SisPI at the level of 200 hPa in October 2020.</p>
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<p>Comparison between the representation of the flow obtained by ERA5 (<bold>a</bold>) and that calculated by SisPI (<bold>b</bold>) corresponding to the month of May in 500 hPa.</p>
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<p>Average synoptic flow represented by SisPI in blue and the errors with respect to ERA5 data in red (<bold>a</bold>,<bold>b</bold>); with the humidity errors obtained (<bold>c</bold>,<bold>d</bold>) for September and October at 500 hPa.</p>
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6 pages, 1805 KiB  
Proceeding Paper
Impact of Various Sources of Disturbances on the Atmospheric Electric Field and the Lower Ionosphere
by Valentina Antonova, Vadim Lutsenko, Galina Gordiyenko and Sergey Kryukov
Environ. Sci. Proc. 2022, 19(1), 41; https://doi.org/10.3390/ecas2022-12868 - 8 Aug 2022
Viewed by 836
Abstract
The possible impact of solar activity on the atmospheric electric field, thunderstorm activity and lower ionosphere was investigated. The investigation was based on the electric field measurements and ionospheric observations at Alma-Ata (Kazakhstan). The investigation showed a decrease in the atmospheric electric field [...] Read more.
The possible impact of solar activity on the atmospheric electric field, thunderstorm activity and lower ionosphere was investigated. The investigation was based on the electric field measurements and ionospheric observations at Alma-Ata (Kazakhstan). The investigation showed a decrease in the atmospheric electric field (~40 ÷ 50 V/m) under “fair” weather conditions, fluctuations under magnetic storms, and anomalous changes before and during significant and weak earthquakes. The study indicated a tendency for thunderstorm appearance with a 1–2-day delay after the impact of CME or HSS events on the Earth’s magnetosphere. Noticeable changes in the lower ionosphere during these periods were found. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Diurnal variation in the electric field at the high-mountain Tien-Shan station under “fair weather” conditions in summer and winter.</p>
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<p>Values of the atmospheric electric field after the CME 27.02.2014 and 01.12.2014.</p>
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<p>The values of the atmospheric electric field under the impact of the large geomagnetic storm (<bold>left</bold> panel) and power spectra of variations in the atmospheric electric field during magnetic storms (<bold>right</bold> panel, dashed-line curve).</p>
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<p>Variations of the Dst index and the occurrence of thunderstorm activity in July 2013.</p>
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<p>Lightning occurrence as a function of time delay between an observed thunderstorm and the arrival of geoeffective HSSs (<bold>left</bold> panel) and CMEs (<bold>right</bold> panel) to the Earth.</p>
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7 pages, 1184 KiB  
Proceeding Paper
Household Indoor Concentration Levels of Nitrogen Dioxide (NO2) and Ozone (O3) in Eskisehir, Turkey
by Seda Naz Sarıca, Özlem Özden Üzmez and Semra Malkoç
Environ. Sci. Proc. 2022, 19(1), 42; https://doi.org/10.3390/ecas2022-12865 - 1 Aug 2022
Viewed by 916
Abstract
The concentrations of nitrogen dioxide (NO2) and ozone (O3) were determined at five indoor environments (corridor, living area, bedroom, kitchen, bathroom) of two homes located in different regions of Eskisehir, Turkey. Home 1 is located in the city center [...] Read more.
The concentrations of nitrogen dioxide (NO2) and ozone (O3) were determined at five indoor environments (corridor, living area, bedroom, kitchen, bathroom) of two homes located in different regions of Eskisehir, Turkey. Home 1 is located in the city center and urban residential area and Home 2 is located in a suburban area. In order to determine the indoor and outdoor concentration ratios of the pollutants (I/O), outdoor sampling was also carried out simultaneously with indoor sampling. Sampling studies were performed in one-day periods in four seasons using a passive sampling method. The indoor NO2 concentrations varied between 8.80 and 124.18 µg/m3, while O3 concentrations varied between 4.15 and 22.10 µg/m3. The highest NO2 concentrations were determined in the kitchens both in two homes. This can be due to the intensive cooking activities carried out in the kitchens. The variation in O3 concentrations in the measured indoor environments varied in homes. When the outdoor concentrations were examined, it was seen that NO2 concentrations were higher in Home 1 and O3 concentrations were higher in Home 2 in all seasons. This result is related to the location of the homes. The I/O ratios for NO2 were generally >1 for the kitchens. Moreover, all I/O ratios for NO2 in Home 2 were found >1 in autumn season. The I/O ratios for O3 were found to be <1 in both homes in all seasons. Seasonal variations in the pollutant concentration levels were also observed for indoor environments. Indoor NO2 concentrations, especially in Home 1, and O3 concentrations, especially in Home 2, were higher in spring and summer compared to other seasons. The reason for this is thought to be more active natural ventilation due to the warming of the weather in these seasons. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>The homes included in the study: (<bold>a</bold>) the location of the first home (Home 1) in Bahçelievler neighborhood; (<bold>b</bold>) the location of the second home (Home 2) in Aşağı Söğütönü neighborhood.</p>
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<p>Floor plan and indoor–outdoor sampling points in: (<bold>a</bold>) home 1; (<bold>b</bold>) home 2. 1: Corridor, 2: Living Room, 3: Bedroom, 4: Kitchen, 5: Bathroom, 6: Outdoor.</p>
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<p>Parts of the tailor-made passive sampler [<xref ref-type="bibr" rid="B19-environsciproc-19-00042">19</xref>].</p>
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8 pages, 4371 KiB  
Proceeding Paper
Projecting the Potential Evapotranspiration of Egypt Using a High-Resolution Regional Climate Model (RegCM4)
by Samy Ashraf Anwar, Zeinab Salah, Wael Khald and Ashraf Saber Zakey
Environ. Sci. Proc. 2022, 19(1), 43; https://doi.org/10.3390/ecas2022-12841 - 22 Jul 2022
Cited by 7 | Viewed by 1508
Abstract
A regional climate model (RegCM4) was used to project the potential evapotranspiration (PET) of Egypt under two future scenarios: RCP45 and RCP85. Spatially, the RegCM4 has a higher PET under the RCP85 than the RCP45. Among all locations, the RegCM4 was able to [...] Read more.
A regional climate model (RegCM4) was used to project the potential evapotranspiration (PET) of Egypt under two future scenarios: RCP45 and RCP85. Spatially, the RegCM4 has a higher PET under the RCP85 than the RCP45. Among all locations, the RegCM4 was able to capture the monthly variability in PET with respect to the Climate Research Unit (CRU). In addition, the simulated PET was notably improved when a linear regression model (LRM) was used. Further, future PET projects a strong increased trend under the RCP85; meanwhile, future PET projects a weak increased trend under the RCP45. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>The figure shows the Egypt domain.</p>
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<p>The figure shows Average 2m air temperature (hereafter TMP; in °C) over Egypt during 1986–2005 (RF) (<bold>a</bold>) and the potential change during the period of 2021 to 2040 (<bold>b</bold>), the period of 2041 to 2060 (<bold>c</bold>), the period of 2061 to 2080 (<bold>d</bold>), the period of 2081 to 2100 (<bold>e</bold>) according to the RCP85 scenario.</p>
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<p>The figure shows the average evapotranspiration (in mm/day) over Egypt during 1986–2005 (RF) (<bold>a</bold>) and potential change during the period of 2021 to 2040 (<bold>b</bold>), the period of 2041 to 2060 (<bold>c</bold>), the period of 2061 to 2080 (<bold>d</bold>), the period of 2081 to 2100 (<bold>e</bold>) according to the RCP85 scenario.</p>
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<p>The figure shows the monthly times series of potential evapotranspiration (PET; in mm/day) by the RegCM in the historical period (1981–2005) of the twelve locations in comparison with the CRU product (in red), before applying the LRM (RegCM; in blue) and after applying the LRM (RegCMnew; in green).</p>
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<p>The figure shows the future corrected PET changes (in %) under the two future scenarios (RCP45; in blue) and (RCP85; in red) for the twelve locations.</p>
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6 pages, 8627 KiB  
Proceeding Paper
Tropospheric Patterns Associated with Cold Fronts That Generate Heavy Rainfall in Cuba and Their Relationship with the NAO
by Yamila García-Pérez, Ernesto Rodríguez-Acosta and Ailyn Justiz-Águila
Environ. Sci. Proc. 2022, 19(1), 44; https://doi.org/10.3390/ecas2022-12793 - 14 Jul 2022
Viewed by 908
Abstract
Cold fronts (CF) are the meteorological systems that affect a country in the dry season, which when combined with other meteorological conditions or local factors can generate precipitation that is sometimes greater than 100 mm in 24 h. Some studies have analyzed the [...] Read more.
Cold fronts (CF) are the meteorological systems that affect a country in the dry season, which when combined with other meteorological conditions or local factors can generate precipitation that is sometimes greater than 100 mm in 24 h. Some studies have analyzed the synoptic patterns that are associated with the cold fronts that generate heavy rains in Cuba and the internal structure of these patterns. Similarly, from the 1990s, studies associated with the behavior of the North Atlantic Oscillation (NAO) teleconnection event within the winter period and the systems that are developed within it increased. However, the incidence of this event in the cold fronts that generated the intense rains in Cuba in the winter period of 1980–1981 to 2016–2017 has not been taken into account. For this, the tropospheric patterns that are associated with these winter systems were identified, the behavior of this event was characterized in those winter seasons with intense rains, and the mean field of temperature, humidity, and wind and its derivatives were associated with these meteorological systems when they generate intense rains and its relationship with said teleconnection event. The results that were obtained show that the NAO teleconnection event in the study period showed a preference to be negative. The temperature, the relative humidity, and the fields that were derived from the wind presented homogeneity in the two phases of this event. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Absolute monthly frequency of each of the NAO phases in the study sample. The graph was created by the authors using the software Microsoft Excel.</p>
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<p>Short-wave trough pattern associated with surface cold front. Left panel shows the variable at level 200 hPa and right one at 0 hPa. The graphs were created by the authors in the software GrADS.</p>
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<p>Long-wave trough pattern associated with surface cold front. Left panel shows the variable at 200 hPa and the right one at 0 hPa. The graphs were created by the authors in the software GrADS.</p>
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<p>Long-wave trough pattern associated with frontal surface trough. Left panel shows the variable at 200 hPa and the right one at 0 hPa. The graphs were created by the authors in the software GrADS.</p>
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<p>Short-wave trough pattern associated with frontal surface trough. Left panel shows the variable at 200 hPa and the right one at 0 hPa. The graphs were created by the authors in the software GrADS.</p>
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8 pages, 1486 KiB  
Proceeding Paper
Main Climatic Characteristics of the International Airport “Antonio Maceo” during the Period 2017–2021
by Beatriz Valdés Díaz, Amanda Maria De Armas Echevarria and Patricia Coll-Hidalgo
Environ. Sci. Proc. 2022, 19(1), 45; https://doi.org/10.3390/ecas2022-12855 - 25 Jul 2022
Cited by 1 | Viewed by 866
Abstract
The climatological characterization of variables allows us to understand the average behavior of atmospheric conditions, detect extremes and fluctuations, and the relationships of variables with geographic physical factors; it is presented as another aide for weather forecasting. The aim of this research is [...] Read more.
The climatological characterization of variables allows us to understand the average behavior of atmospheric conditions, detect extremes and fluctuations, and the relationships of variables with geographic physical factors; it is presented as another aide for weather forecasting. The aim of this research is characterizing the behavior of the meteorological variables at the Antonio Maceo International Airport in Santiago de Cuba for the period 2017–2021. Antonio Maceo International Airport has the particularity of being located in a complex relief, exposed to marked breeze influences, and a significant number of wind shear pilot reports. The characterization was based on the concepts and graphs of descriptive statistics. The mean monthly distribution of the variables: temperature, relative humidity, atmospheric pressure, and wind speed and direction was obtained and is represented. The distributions of the maximum monthly and annual accumulations, the cloud cover, and the ranges of the reduction of the horizontal and vertical visibility were analyzed. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Location of the “Antonio Maceo” International Airport in Santiago de Cuba.</p>
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<p>Mean distribution of mean, maximum, and minimum air temperatures.</p>
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<p>The behavior of (<bold>a</bold>) the mean air temperature and (<bold>b</bold>) relative humidity in MUCU during the period 2017–2021.</p>
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<p>Annual behavior of the mean, minimum, and maximum atmospheric pressure in MUCU during the period 2017–2021.</p>
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<p>Behavior (<bold>a</bold>) monthly and (<bold>b</bold>) annual of the accumulated precipitation in MUCU during the period 2017–2021.</p>
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<p>Rose of the wind direction and velocity for the period 2017–2021.</p>
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6 pages, 1824 KiB  
Proceeding Paper
Future Projections of Cloud Cover and Surface Relative Humidity Over Greece during the 21st Century Based on EURO-CORDEX Simulations
by Ioannis Logothetis, Kleareti Tourpali and Dimitrios Melas
Environ. Sci. Proc. 2022, 19(1), 46; https://doi.org/10.3390/ecas2022-12799 - 14 Jul 2022
Cited by 1 | Viewed by 1004
Abstract
Greece is located over a climate-change-prone region. The aim of this study is to investigate the projection of cloud cover fraction and surface relative humidity during the period from 1970 to 2099. In this analysis, we use six high-resolution regional climate model simulations [...] Read more.
Greece is located over a climate-change-prone region. The aim of this study is to investigate the projection of cloud cover fraction and surface relative humidity during the period from 1970 to 2099. In this analysis, we use six high-resolution regional climate model simulations (RCMs) available from the EURO-CORDEX program. The RCMs include the historical period from 1970 to 2005 and the future period from 2006 to 2099 under the influence of the representative concentration pathway (rcp) scenarios rcp2.6, rcp4.5, and rcp8.5. Results show significant projected changes mainly during the last period of the 21st century according to the rcp8.5 scenario. In particular, during the 2070–2099 period, with respect to a reference period (1976–2005), both the cloud cover fraction and the surface relative humidity are reduced by about 5% and 5% to 8%, respectively, over continental Greece. Focusing on the winter season, the comparison between future and reference periods shows that the cloud cover fraction presents a significant decrease of about 10% to 20% mainly during the last period of the 21st century. Finally, the surface relative humidity in 2070–2099 shows insignificant changes according the low and moderate scenarios (rcp2.6 and 4.5) and limited changes for the high emission scenario (rcp8.5). Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Annual mean sRH composite difference according to the rcp8.5 scenario of (<bold>A</bold>) F1 and RF and (<bold>B</bold>) F3 and RF for each simulation. The dotted points denote statistical significance at 95%.</p>
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<p>Annual mean ccf composite difference according to the rcp8.5 scenario of (<bold>A</bold>) F1 and RF and (<bold>B</bold>) F3 and RF for each simulation. The dotted points denote statistical significance at 95%.</p>
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<p>Winter (DJF) season relative composite difference (%) of (<bold>A</bold>) sRH of F3 according to the (<bold>a</bold>–<bold>i</bold>) rcp2.6, (<bold>g</bold>–<bold>l</bold>) rcp4.5, and (<bold>m</bold>–<bold>r</bold>) rcp8.5 scenarios with respect to RF and (<bold>B</bold>) ccf of F3 according to the (<bold>a</bold>–<bold>i</bold>) rcp2.6, (<bold>g</bold>–<bold>l</bold>) rcp4.5, and (<bold>m</bold>–<bold>r</bold>) rcp8.5 scenarios with respect to RF for each simulation. The dotted points denote statistical significance at 95%.</p>
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7 pages, 575 KiB  
Proceeding Paper
Spatial Distribution of an Index of Impact on Solar and Wind Generation Facilities Based on Meteorological Phenomena
by Lourdes Álvarez-Escudero and Israel Borrajero Montejo
Environ. Sci. Proc. 2022, 19(1), 47; https://doi.org/10.3390/ecas2022-12849 - 25 Jul 2022
Viewed by 996
Abstract
Meteorological phenomena may have a positive or negative impact on solar and wind-generating facilities. This work intends to build an impact index that comprises the frequency of occurrence of a set of phenomena, weight each one according to expert criteria for 68 meteorological [...] Read more.
Meteorological phenomena may have a positive or negative impact on solar and wind-generating facilities. This work intends to build an impact index that comprises the frequency of occurrence of a set of phenomena, weight each one according to expert criteria for 68 meteorological stations over Cuba, and analyze the spatial distribution. The classification is given in five categories, ranging from “very unfavorable” to “very favorable”. Overall, it shows that the phenomena under study have a greater incidence on solar than wind facilities since “clear skies”, “thunderstorms”, and “precipitation” have a strong impact, favorable or unfavorable, according to the specific phenomenon. “Thunderstorms” are the most influencing phenomenon for wind facilities with an unfavorable character. The spatial distribution shows favorable zones with regard to solar facilities in the provinces of Pinar del Río, Ciego de Ávila, Camagüey, the north coast of Las Tunas, Holguín, and around the Gulf of Guacanayabo, and for wind generators at Pinar del Río, Artemisa, Ciego de Ávila, Camagüey, Las Tunas, and the south coast of the Central and Eastern regions. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Spatial distribution of the PAI with respect to the solar energy production facilities for the Cuban territory.</p>
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<p>Spatial distribution of the PAI with respect to the wind turbines for the Cuban territory.</p>
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7 pages, 1187 KiB  
Proceeding Paper
A Study of Southwest Monsoon Rainfall in West Bengal and Orissa and Its Correlation with Sunspot Numbers
by Dhruba Banerjee and Ramaprosad Bondyopadhaya
Environ. Sci. Proc. 2022, 19(1), 48; https://doi.org/10.3390/ecas2022-12854 - 25 Jul 2022
Viewed by 825
Abstract
This paper presents a study of the comparison of the southwest monsoon rainfall (SWMR) over two East Coastal States of India with the sunspot number (SSN) of the solar cycle, when the SSN is 50% or more of the maximum SSN of any [...] Read more.
This paper presents a study of the comparison of the southwest monsoon rainfall (SWMR) over two East Coastal States of India with the sunspot number (SSN) of the solar cycle, when the SSN is 50% or more of the maximum SSN of any cycle, during 1880–2003. Firstly, it was found that in many cases the SSN of MAP has the tendency to increase with time, having an embedded oscillation of a period of 22 years (similar to double the solar cycle period). The analysis of the SWMR in those states separately or combined reveals that it is moderately influenced by solar activities, provided the SSN lies between 90 and 130. When the SSN is less than 90 it becomes too weak to influence; no definite pattern of change of SWMR appears. However, when the SSN increases from 90 to 130, SWMR tends to decrease. The SSN has an inverse significant effect on SWMR. Finally, when linear trend lines for SWMR are compared, it becomes apparent that gradients of SWMR for West Bengal are slightly positive, for Orissa are slightly negative, and are almost zero for total SWMR. This implies that, overall, there is no change in the amount of rainfall due to southwest monsoons in the combined area of West Bengal and Orissa. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Variation Sunspot number and More active period.</p>
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<p>Variation of average monsoon rain fall of West Bengal and Orissa with Sunspot number.</p>
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<p>Variation of average monsoon rain fall of West Bengal and Orissa with Sunspot number.</p>
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<p>Variation of MR (West Bengal + Orissa) and MAP during 1880–2003.</p>
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<p>Variation of Monsoon Rain fall (MR) and More active period (MAP).</p>
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<p>Variation of Monsoon Rain fall (MR) and More active period (MAP).</p>
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8 pages, 6723 KiB  
Proceeding Paper
Usefulness of UAV-Mounted Multi-Sensors System for In Situ Atmospheric Measurement: A Case Study from Wrocław, Poland
by Anetta Drzeniecka-Osiadacz, Tymoteusz Sawiński, Magdalena Korzystka-Muskała, Marek Kowalczyk and Piotr Modzel
Environ. Sci. Proc. 2022, 19(1), 49; https://doi.org/10.3390/ecas2022-12843 - 22 Jul 2022
Viewed by 927
Abstract
Air pollution, especially particulate matter (PMx), is one of the most serious environmental threats worldwide. It is challenging in terms of both public health, impact on climate, and the reduction in visibility. The assessment of spatial variability of PMx allows [...] Read more.
Air pollution, especially particulate matter (PMx), is one of the most serious environmental threats worldwide. It is challenging in terms of both public health, impact on climate, and the reduction in visibility. The assessment of spatial variability of PMx allows us to better understand the processes that cause smog episodes, and may also be an additional element for the validation of the results of dispersion models. This study presents the results of measurements of basic meteorological parameters and air pollution involving a multi-sensor system. A Matrice 600 hexacopter with an installed environmental head was used as the measurement platform. This system enables us to measure the concentrations of PM2.5, PM10, air temperature and humidity. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>The examples of data processing and distribution of particulate matter concentration PM<sub>2.5</sub> [μg m<sup>−3</sup>] for different height achieved during one-day campaign (red areas indicate the location of PM emission sources).</p>
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<p>Examples of the visual interpretation of temperature and particulate matter vertical profiles from drone measurements.</p>
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<p>Vertical profile of air temperature (<bold>a</bold>), environmental lapse rates (<bold>b</bold>) and PM<sub>2.5</sub> concentration (<bold>c</bold>), diurnal distribution of PM<sub>x</sub> and wind speed (<bold>d</bold>) and vertical profile of temperature and wind speed from balloon sounding (<bold>e</bold>) (<uri>www.weather.uwyo.edu/upperair/sounding.html</uri> (accessed on 1 June 2022). Flights on 30 October 2019.</p>
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<p>Vertical profile of air temperature (<bold>a</bold>), environmental lapse rates (<bold>b</bold>) and PM<sub>2.5</sub> concentration (<bold>c</bold>), diurnal distribution of PM<sub>x</sub> and wind speed (<bold>d</bold>) and vertical profile of temperature and wind speed from balloon sounding (<bold>e</bold>) (<uri>www.weather.uwyo.edu/upperair/sounding.html</uri> (accessed on 1 June 2022). Flights on 30 October 2019.</p>
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<p>Vertical profile of air temperature (<bold>a</bold>), environmental lapse rates (<bold>b</bold>) and PM<sub>2.5</sub> concentration (<bold>c</bold>), diurnal distribution of PM<sub>x</sub> and wind speed (<bold>d</bold>) and sodar echogram (<bold>e</bold>; dark horizontal areas indicate inversion layer, so-called “spiky echoes” during day indicate convection), and results of horizontal profiling (<bold>f</bold>,<bold>g</bold>). Flights on 24 November 2020.</p>
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<p>Vertical profile of air temperature (<bold>a</bold>), environmental lapse rates (<bold>b</bold>) and PM<sub>2.5</sub> concentration (<bold>c</bold>), diurnal distribution of PM<sub>x</sub> and wind speed (<bold>d</bold>) and sodar echogram (<bold>e</bold>; dark horizontal areas indicate inversion layer, so-called “spiky echoes” during day indicate convection), and results of horizontal profiling (<bold>f</bold>,<bold>g</bold>). Flights on 24 November 2020.</p>
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<p>Vertical profile of air temperature (<bold>a</bold>), environmental lapse rates (<bold>b</bold>) and PM<sub>2.5</sub> concentration (<bold>c</bold>), diurnal distribution of PM<sub>x</sub> and wind speed (<bold>d</bold>) and sodar echogram (<bold>e</bold>; dark horizontal areas indicate inversion layer, so-called “spiky echoes” during the day indicate convection). Flights on 17 December 2020.</p>
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8 pages, 1668 KiB  
Proceeding Paper
Application of a Local Three-Dimensional (3D) Atmospheric Model for Description of Carbon Dioxide Exchange over a Non-Uniform Land Surface
by Iuliia Mukhartova, Julia Kurbatova and Alexander Olchev
Environ. Sci. Proc. 2022, 19(1), 50; https://doi.org/10.3390/ecas2022-12838 - 20 Jul 2022
Viewed by 825
Abstract
A three-dimensional hydrodynamic model was developed to describe the turbulent transfer of carbon dioxide (CO2) within the atmospheric surface layer, taking into account the horizontal land surface heterogeneity. It was based on the ”one and a half” E–ω closure for the [...] Read more.
A three-dimensional hydrodynamic model was developed to describe the turbulent transfer of carbon dioxide (CO2) within the atmospheric surface layer, taking into account the horizontal land surface heterogeneity. It was based on the ”one and a half” E–ω closure for the system of averaged Navier–Stokes and continuity equations. The model was applied to assess the spatial wind and atmospheric CO2 flux distribution in a non-uniform forest peatland ecosystem in the central part of European Russia. The modeling results showed a very strong spatial heterogeneity of the wind speed and atmospheric CO2 fluxes. The results also showed very good agreement with the results of eddy covariance flux measurements. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Geographical location of the study area and the spatial pattern of the leaf area index (LAI) within the modeling domain, derived from Landsat imagery.</p>
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<p>Spatial distributions of the vertical and horizontal wind components at heights of 3 m ((<bold>a</bold>,<bold>c</bold>) and (<bold>b</bold>,<bold>d</bold>), respectively). For calculations, the weather conditions observed at 14:00 on 25 June 2016 were used. The prevailing wind direction at the upper boundary of the modeling domain was southeast.</p>
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<p>Vertical CO<sub>2</sub> flux at heights of 3 m (<bold>a</bold>) and 30 m (<bold>c</bold>), as well as the horizontal CO<sub>2</sub> fluxes at heights of 3 m (<bold>b</bold>) and 30 m (<bold>d</bold>) above the surface. The calculations were conducted for 14:00 on 25 June 2016. The CO<sub>2</sub> fluxes are expressed in µmol m<sup>−2</sup> s<sup>−1</sup>.</p>
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<p>Comparisons of the local flux tower and the mean peatland CO<sub>2</sub> fluxes at different levels above the ground surface under (<bold>a</bold>) southeast (14:00 on 25 June 2016) and (<bold>b</bold>) northwest (13:30 on 28 June 2016) wind directions. The blue line is the total vertical CO<sub>2</sub> fluxes; the green line is the sum of the total vertical and horizontal fluxes at the flux tower site; the red line is the mean vertical flux averaged for the entire peatland area; and the black line is the sum of the vertical and horizontal fluxes averaged for the entire peatland area.</p>
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4 pages, 808 KiB  
Proceeding Paper
Climatology of Extreme Precipitation from Observational Records in Greece
by Chris G. Tzanis, Aris Nasl Pak, Ioannis Koutsogiannis and Kostas Philippopoulos
Environ. Sci. Proc. 2022, 19(1), 51; https://doi.org/10.3390/ecas2022-12818 - 14 Jul 2022
Cited by 1 | Viewed by 886
Abstract
Precipitation is widely considered an important parameter and a key indicator of the evolving climate change. The intensity as well as the frequency of precipitation can be largely affected by disturbances of the hydrological cycle as a result of the increasing temperature of [...] Read more.
Precipitation is widely considered an important parameter and a key indicator of the evolving climate change. The intensity as well as the frequency of precipitation can be largely affected by disturbances of the hydrological cycle as a result of the increasing temperature of the atmosphere and the oceans. Through a variety of statistical methods, it is possible to assess changes in precipitation over the recent years, both regionally and globally. In this work, precipitation data from seven WMO stations in the Greek region were studied over the period of 1990−2020. By analyzing a set of extreme precipitation indices and applying the Sen and Mann-Kendall statistical methods, the trends and statistical significance of precipitation in the area of study were investigated. The results reveal an increase in the yearly number of days with extreme precipitation events as well as in the total amount of precipitation. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Distribution of meteorological stations.</p>
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<p>Example of the application of the Sen’s slope <italic>(f = Qt + B)</italic> and Mann-Kendall method to the yearly time series of the RX1day index for the Souda meteorological station. A positive (negative) <italic>Z</italic> number indicates a positive (negative) trend. By <italic>Q</italic> and <italic>B,</italic> the slope of the trend and intercept are denoted along with the 95% and 99% confidence levels, respectively. In case the trend is statistically significant, it is marked with a star (*).</p>
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6 pages, 835 KiB  
Proceeding Paper
Seasonal Variability of Carbon Dioxide and Methane Fluxes in a Subarctic Palsa Mire in North-Central Siberia
by Alexander Olchev, Viacheslav Zyrianov, Alexey Panov, Elizaveta Satosina, Iuliia Mukhartova, Elena Novenko and Anatoly Prokushkin
Environ. Sci. Proc. 2022, 19(1), 52; https://doi.org/10.3390/ecas2022-12837 - 20 Jul 2022
Cited by 1 | Viewed by 1017
Abstract
The main goal of the study was to obtain new experimental data on the seasonal variability of carbon dioxide (CO2) and methane (CH4) fluxes in a subarctic palsa mire in north-central Siberia, as well as to assess the sensitivity [...] Read more.
The main goal of the study was to obtain new experimental data on the seasonal variability of carbon dioxide (CO2) and methane (CH4) fluxes in a subarctic palsa mire in north-central Siberia, as well as to assess the sensitivity of the CO2 and CH4 fluxes to environmental changes. The results of field measurements in 2017 and 2018 showed that the palsa mire served as a sink of CO2 from the atmosphere for the period between mid-June to the end of August for both years. Maximum daily CO2 uptake rates in 2017 were observed at the beginning of July (up to 4.5 gC m−2 d−1), mainly due to high incoming solar radiation, optimal air temperature and sufficient soil moisture conditions. Seasonal variability of CH4 fluxes was relatively high and governed mainly by weather conditions. During both growing seasons the palsa mire served mostly as a CH4 source for the atmosphere. The periods with prevailed CH4 emission alternated with periods of CH4 uptake and the fluxes varied between −8.3 to 13.6 mgC m−2 per day in 2017 and between −4.5 to 21.8 mgC m−2 per day in 2018. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Geographical location of the study area.</p>
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<p>Seasonal variability of the mean daily air temperature, precipitation, CO<sub>2</sub> and CH<sub>4</sub> fluxes in the palsa mire in 2017.</p>
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<p>Seasonal variability of the mean daily air temperature, precipitation, CO<sub>2</sub> and CH<sub>4</sub> fluxes in the palsa mire in 2018.</p>
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7 pages, 4624 KiB  
Proceeding Paper
Application of the Sliding Window Method to the Short Range Prediction System for the Correction of Precipitation Forecast Errors
by Dayana Rodríguez Garrido and Maibys Sierra Lorenzo
Environ. Sci. Proc. 2022, 19(1), 53; https://doi.org/10.3390/ecas2022-12803 - 14 Jul 2022
Viewed by 910
Abstract
The SisPI is used in INSMET to provide precipitation forecasts. Generally, these numerical forecasts present errors in precipitation amount as well as position. In order to reduce these errors, in this work, we propose to improve the precision of the precipitation forecast by [...] Read more.
The SisPI is used in INSMET to provide precipitation forecasts. Generally, these numerical forecasts present errors in precipitation amount as well as position. In order to reduce these errors, in this work, we propose to improve the precision of the precipitation forecast by the implementation of the sliding window method. It is obtained as a result that the spatial error presented by SisPI can be reduced by using a window of size N = 15 and the maximum and average instructions. The quantitative error was decreased more optimally with the medium instruction using the same window size. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Representation of the sliding window method.</p>
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<p>BIAS values of the first case study for the initialization of 12:00 UTC. (<bold>a</bold>) For window width N = 3. (<bold>b</bold>) For window width N = 15.</p>
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<p>Plotted BIAS values. (<bold>a</bold>) shows those provided by SisPI in the forecast period (10–11) with the initialization at 12:00 UTC and (<bold>b</bold>) shows those provided by SisPI once the window method was applied with the average instruction for a window width N = 3.</p>
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<p>Plotted values of the BIAS. (<bold>a</bold>) shows those provided by the SisPI once the method was applied with the maximum instruction in the forecast period (10–11) with the initialization of the 12:00 UTC and in (<bold>b</bold>) the ones provided by SisPI with the median instruction and the same initialization, both images refer to the method with a window width N = 3.</p>
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<p>Plotted BIAS values. (<bold>a</bold>) shows those provided by SisPI in the forecast period (10–11) with the initialization at 12:00 UTC and (<bold>b</bold>) shows those provided by SisPI once the window method was applied with the average instruction. for a window size N = 15.</p>
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<p>Plotted BIAS values. (<bold>a</bold>) shows those provided by SisPI in the forecast period (10–11) with the initialization at 12:00 UTC and (<bold>b</bold>) shows those provided by SisPI once the window method was applied with the average instruction. for a window size N = 15.</p>
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<p>Plotted values of the BIAS, in (<bold>a</bold>) those provided by the SisPI are shown once the method has been applied with the maximum instruction and in (<bold>b</bold>) those provided by SisPI with the median instruction, both images for a window width N = 15 in the forecast period (10–11) with the initialization of 12:00 UTC.</p>
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6 pages, 1249 KiB  
Proceeding Paper
The September 2019 Flash Flood Event in Eastern Spain: Synoptic Analysis and Extreme Rainfall Assessment
by Maria Sol Hernández-Conesa, Igor Gómez and Guillermo Carballo-Lafuente
Environ. Sci. Proc. 2022, 19(1), 54; https://doi.org/10.3390/ecas2022-12800 - 14 Jul 2022
Viewed by 1099
Abstract
The western Mediterranean region is frequently affected by torrential rains, such as that developed between 10th and 13th September 2019. Accumulated rainfall above 400 mm considering the whole precipitation event as well as precipitation values close to 200 mm were recorded in some [...] Read more.
The western Mediterranean region is frequently affected by torrential rains, such as that developed between 10th and 13th September 2019. Accumulated rainfall above 400 mm considering the whole precipitation event as well as precipitation values close to 200 mm were recorded in some places in just 2 h. The synoptic environment of this event is characterized by an advection of easterly maritime winds focusing on the southeast western Mediterranean basin and the presence of an upper level isolated low over the area of intense torrential rainfall. In this study, the spatial distribution and temporal evolution of this rainfall event are analyzed. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>(<bold>a</bold>) Geopotential height (m, shaded color), temperature in °C (solid green line) and wind (arrows) at 500 hPa on the 11 September 2019 at 12:00 UTC; (<bold>b</bold>) geopotential height (m, shaded color), temperature in °C (solid green line) and wind (arrows) at 500 hPa on the 12 September 2019 at 12:00 UTC.</p>
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<p>(<bold>a</bold>) Sea level pressure (contour, mb), wind (arrow, m/s) and relative humidity (shaded, %) on the 12 September 2019 at 12:00 UTC; (<bold>b</bold>) sea level pressure (contour, mb), wind (arrow, m/s) and relative humidity (shaded, %) on the 13 September 2019 at 18:00 UTC.</p>
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<p>Representation of the accumulated precipitation by means of a diagram in the different study areas of the Valencia and Murcia regions for the days 11, 12, 13 and 14 September 2019.</p>
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<p>Temporal evolution of 24 h of accumulated precipitation (mm) from 00:00 a.m. to 12:00. p.m. to 00:00 p.m. during the days 11, 12, 13 and 14 September 2019.</p>
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6 pages, 4375 KiB  
Proceeding Paper
Comparison of Selyaninov’s Hydrothermal Coefficient (Aridity Criterion) over Buryatia, Russia, in the Summer Period from 1979 to 2019 according to Meteorological Stations and ECMWF ERA5
by Elena Devyatova, Elena Kochugova and Mergen Cydenzapov
Environ. Sci. Proc. 2022, 19(1), 55; https://doi.org/10.3390/ecas2022-12805 - 14 Jul 2022
Viewed by 1403
Abstract
We studied moisture content/aridity conditions in Buryatia (Russia) in summertime for the period of 1979–2019. Selyaninov’s hydrothermal coefficient (HTC) was used as the aridity criterion. The HTC was calculated on the basis of precipitation and 2 m temperature data from two datasets: meteorological [...] Read more.
We studied moisture content/aridity conditions in Buryatia (Russia) in summertime for the period of 1979–2019. Selyaninov’s hydrothermal coefficient (HTC) was used as the aridity criterion. The HTC was calculated on the basis of precipitation and 2 m temperature data from two datasets: meteorological stations and the ECMWF ERA5 project. A comparison of the HTC calculations for these two datasets was performed. The ERA5 data showed underestimated HTC values compared to the observations. The inconsistencies found are mainly related to the underestimation of precipitation in the ERA5 project compared to the observational data. The air temperature obtained from the two datasets agrees well for most stations, both in value and in long-term dynamics. It has been shown that at the stations in central and southern Buryatia, the increase in aridity (and decreased HTC) in 1979–2019 is mainly due to the increase in air temperature. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Meteorological stations in Buryatia whose data were used: 1—Taksimo, 2—Bagdarin, 3—Barguzin, 4—Romanovka, 5—Sosnovo-Ozerskoye, 6—Ulan-Ude, 7—Ivolginsk, 8—Babushkin, 9—Tunka, and 10—Orlik.</p>
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<p>HTCs from ERA5 in the four grid points nearest to the Ulan-Ude (<bold>left</bold>), Ivolginsk (<bold>center</bold>), and Tunka (<bold>right</bold>) stations.</p>
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<p>HTCs in June. Blue—meteorological stations data; orange—ERA5 data. k is the correlation coefficient. X-axis—years; Y-axis—HTC.</p>
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<p>HTCs in July. Blue—meteorological station data; orange—ERA5 data. k is the correlation coefficient. X-axis—years; Y-axis—HTC.</p>
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<p>HTCs in August. Blue—meteorological station data; orange—ERA5 data. k is the correlation coefficient. X-axis—years; Y-axis—HTC.</p>
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<p>Air temperature (<bold>top</bold>) and precipitation (<bold>bottom</bold>) in June at the Ulan-Ude, Ivolginsk, and Tunka stations.</p>
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5 pages, 1353 KiB  
Proceeding Paper
Comparison of Extreme Bioclimatic Episodes in Kolkata (India) and Two Neighboring Suburban Stations
by Sourabh Bal and Adwitia Bal
Environ. Sci. Proc. 2022, 19(1), 56; https://doi.org/10.3390/ecas2022-12858 - 27 Jul 2022
Viewed by 791
Abstract
The objective of the present study is to estimate the duration of extreme thermal bioclimate conditions in and around Kolkata, one of the highly densely populated cities in India. The biometeorological conditions have been calculated by Physiologically Equivalent Temperature (PET) using the RayMan [...] Read more.
The objective of the present study is to estimate the duration of extreme thermal bioclimate conditions in and around Kolkata, one of the highly densely populated cities in India. The biometeorological conditions have been calculated by Physiologically Equivalent Temperature (PET) using the RayMan model at 05:30 h and 14:30 h (IST) based on meteorological data for the stations Kolkata (Alipore), Dum Dum, and Diamond Harbour for the period January 2020 to December 2021. Dum Dum is located to the north of Kolkata, and Diamond Harbour is situated to the south of Kolkata. The meteorological data were retrieved from the station data measured by the Indian Meteorological Department (IMD). The atmospheric variables required to calculate the PET index are air temperature, relative humidity, cloud cover, and wind speed. A recent study reported that stations outside Kolkata suffer warmer human thermal stress conditions. To account for the prolonged thermal stress periods, PET greater than 40 °C is categorized as an episode if it turns up consecutively between 1 and 5 days, 6 and 10 days, 11 and 15 days, 16 and 20 days, 21 and 25 days, and 26 and 30 days. The number distribution of days not exceeding 40 °C remains the same for all the stations. The number of episodes occurring successively for 6–10 days, 11–15 days, 16–20 days, and 21–25 days is highest in Diamond Harbour relative to Kolkata and Dum Dum at 14:30 h. Episodes occurring successively for 26–30 days appear in Kolkata and Dum Dum, whereas no episodes appear in Diamond Harbour. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Monthly frequency diagram (in percentages) exhibiting the mean PET for Alipore (KOL), Dum Dum (DMM), and Diamond Harbour (DHR) from the top at 05:30 h, 08:30 h, 11:30 h, 14:30 h, 17:30 h, and 20:30 h from 2020 to 2021.</p>
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<p>From the top <bold>first row</bold> depicts number of days with PET less than 40 °C. Number of episodes with PET value greater than 40 °C and sustains between 1 to 5 days (<bold>second row</bold>), 6 to 10 days (<bold>third row</bold>), 11 to 15 days (<bold>fourth row</bold>), 16 to 20 days (<bold>fifth row</bold>), 21 to 25 days (<bold>sixth row</bold>), and 26 to 30 days (<bold>seventh row</bold>). Each column from the left represents 05:30 h, 08:30 h, 11:30 h, 14:30 h, 17:30 h, and 20:30 h, respectively.</p>
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7 pages, 3264 KiB  
Proceeding Paper
The Early 20th Century Warming in the East-European Plain Climate: Extreme Drought in 1920–1940, Atmospheric Circulation Anomalies and Links with the Sea Ice Variability
by Valeria Popova, Tatiana Matveeva and Daria Bokuchava
Environ. Sci. Proc. 2022, 19(1), 57; https://doi.org/10.3390/ecas2022-12864 - 1 Aug 2022
Cited by 1 | Viewed by 999
Abstract
Analysis of climatic characteristics, Palmer Drought Severity Index, and large-scale river runoff based on observational data (CRUTEM.5, GISSTEMP v4, CRU TS4.05, CRU-scPDSI) and 20th century reanalysis (ERA20C, CERA20C) shows that the early 20th century warming period, in particular the 1930s, on the East-European [...] Read more.
Analysis of climatic characteristics, Palmer Drought Severity Index, and large-scale river runoff based on observational data (CRUTEM.5, GISSTEMP v4, CRU TS4.05, CRU-scPDSI) and 20th century reanalysis (ERA20C, CERA20C) shows that the early 20th century warming period, in particular the 1930s, on the East-European Plain was marked by the strong long-lasting drought that has no analogues during the observation period. The atmospheric circulation patterns and drivers of this phenomena, as well as the associated reduction in the sea ice extent of the Kara Sea, are studied. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>(<bold>a</bold>) Annual runoff, percent as compared with 1961–1990, for the rivers Severnaya Dvina, Volga, Vyatka, Belaya, and Oka. (<bold>b</bold>) Spatially averaged (20–60 E; 45–70 N) variations of the SAT anomalies, °C, 1, GISSTEMP, 2, CRUTEM, 3, ERA20C, CERA20C, and precipitation, percent as compared with 1961–1990, for summer (JJA), autumn (SON), and cold period (November–April).</p>
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<p>(<bold>a</bold>) Spatially averaged (20–60 E; 45–70 N) PDSI for summer (JJA) and autumn (SON), and its (<bold>b</bold>,<bold>c</bold>) spatial distribution for the (<bold>b</bold>) “wet” (1923, 1926, 1927, 1928) and (<bold>c</bold>) “dry” (1936, 1938, 1939, 1940) years.</p>
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<p>Patterns of the SLP, gPa, on average for the years of (<bold>a</bold>) maxima (1931, 1936, 1938) and (<bold>b</bold>) minima (1923, 1926, 1928) summer (JJA) SAT on the EEP and (<bold>c</bold>) the difference between them; (<bold>d</bold>) EOF3 of SLP variability in summer months (JA); (<bold>e</bold>) SLP PC3 and AMO(×4) (upper panel) and correlation coefficients between (blue) PC3 and SAT, (red) AMO and SAT, calculated over 15-year running periods (bottom panel).</p>
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<p>Difference in SIC (%) in years of high water and low water phases of the Volga River (<bold>a</bold>) in May and (<bold>b</bold>) in August.</p>
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<p>Correlation coefficients between SIA in the Barents Sea in May and SLP anomalies in July for 1924–1950.</p>
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10 pages, 1682 KiB  
Proceeding Paper
Ecosystems: Climate Change Vulnerability and Resilience
by Oksana N. Lipka and Tatiana B. Shishkina
Environ. Sci. Proc. 2022, 19(1), 58; https://doi.org/10.3390/ecas2022-12836 - 20 Jul 2022
Cited by 1 | Viewed by 2095
Abstract
Since 1976, mean annual temperature in Russia has been rising at 0.47 °C per decade (in the Arctic at 1 °C per decade). This process determines shifts in biome boundaries and large-scale ecosystem restructuring. Biome boundaries should have moved 400 to 500 km [...] Read more.
Since 1976, mean annual temperature in Russia has been rising at 0.47 °C per decade (in the Arctic at 1 °C per decade). This process determines shifts in biome boundaries and large-scale ecosystem restructuring. Biome boundaries should have moved 400 to 500 km northwards in the Arctic and 200 to 300 km northwards in other climate zones and are likely to shift another 200–500 km to the north. Arctic, mountain, steppe, and the Far East ecosystems are the most vulnerable to adverse climate change. Creation of protected areas has become a priority measure for the adaptation of ecosystems. On average, protected areas (PAs) of federal significance account for 7.6 percent of a biome territory across the country. However, in five biomes no PA has been established. For the purpose of effective adaptation to climate change it is advisable to increase the total territory covered by all-category PAs to 17 percent of each biome. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Linear trend coefficient for mean annual surface temperature in Russia in 1976–2021 (°C/10 years), adapted with permission from Ref. [<xref ref-type="bibr" rid="B3-environsciproc-19-00058">3</xref>].</p>
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<p>Distribution of PA of federal significance by biomes. The numbers on horizontal axis correspond to the numbers of biomes on the map [<xref ref-type="bibr" rid="B6-environsciproc-19-00058">6</xref>]. Vertical axis is for the amount.</p>
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<p>Distribution of PA of federal significance by biomes (ranking): the numbers correspond to the numbers of biomes on the map [<xref ref-type="bibr" rid="B6-environsciproc-19-00058">6</xref>]. 0—no PA of federal significance; 1—1–3 PA; 2—4–6 PA; 3—7–10 PA; 4—more than 10 PA.</p>
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<p>Distribution of fractions of PA area in total biome territory. The numbers correspond to biome numbers on the map [<xref ref-type="bibr" rid="B6-environsciproc-19-00058">6</xref>].</p>
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<p>Distribution of fractions of PA area in total biome territory. The numbers correspond to biome numbers on the map [<xref ref-type="bibr" rid="B6-environsciproc-19-00058">6</xref>]. 1—PA amount to less than 1% of a biome territory; 2—1%-up to 5%; 3—5%-up to 10%; 4—10%-up to 20%; 5—more than 20%.</p>
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6 pages, 622 KiB  
Proceeding Paper
Wildfire Pollution Exposure and Human Health: A Growing Air Quality and Public Health Issue
by Srijan Sengupta, Viney P. Aneja and Julia Kravchenko
Environ. Sci. Proc. 2022, 19(1), 59; https://doi.org/10.3390/ecas2022-12809 - 14 Jul 2022
Viewed by 845
Abstract
Wildfires emit large quantities of air pollutants into the atmosphere. As wildfires increase in frequency, intensity, duration, and coverage area, such emissions have become a significant health hazard for residential populations, particularly vulnerable groups. This health hazard is exacerbated by two factors: first, [...] Read more.
Wildfires emit large quantities of air pollutants into the atmosphere. As wildfires increase in frequency, intensity, duration, and coverage area, such emissions have become a significant health hazard for residential populations, particularly vulnerable groups. This health hazard is exacerbated by two factors: first, wildfires are expected to increase in frequency as a result of climate change and, second, human health is adversely impacted by fine particulate matter produced from wildfires. Recent toxicological studies suggest that wildfire particulate matter may be more toxic than equal doses of ambient PM2.5. The role of ammonia emissions from wildfires on PM2.5 is examined. The impact of poor air quality on human health is examined and some strategies are discussed to forecast the burden of diseases associated with exposures to wildfire events, both short and long term, and help develop mitigation strategies. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Daily PM<sub>2.5</sub> emissions and NH<sub>3</sub> emissions in Southeast Australia during (29 December 2019–4 January 2020). The circles represent PM<sub>2.5</sub> and NH<sub>3</sub> emissions as kg per day. The black vertical bars in the figure represent ± 1SD. (Source: [<xref ref-type="bibr" rid="B16-environsciproc-19-00059">16</xref>]).</p>
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<p>Daily NH<sub>3</sub> vs PM<sub>2.5</sub> emissions in Southeast Australia during the study period (source: [<xref ref-type="bibr" rid="B16-environsciproc-19-00059">16</xref>]). Linear equation: y = 8.94x × 10<sup>6</sup> + 11.62x with Adjusted R-squared: 0.95.</p>
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<p>Monthly PM<sub>2.5</sub> emissions (wildfire + prescribed burn) for the CFIRE inventory (source: [<xref ref-type="bibr" rid="B17-environsciproc-19-00059">17</xref>]). Total emissions in 2014 were approximately 1507 × 10<sup>6</sup> kg per year.</p>
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5 pages, 984 KiB  
Proceeding Paper
Comparing Methods to Estimate Cloud at the Geophysical Observatory of the Institute of Solar-Terrestrial Physics SB RAS (Tory, Republic of Buryatia, Russia) in December 2020
by Elena Devyatova, Stepan Podlesnyi and Roman Vasilyev
Environ. Sci. Proc. 2022, 19(1), 60; https://doi.org/10.3390/ecas2022-12852 - 25 Jul 2022
Cited by 1 | Viewed by 749
Abstract
This work addresses the issue of how much cloud cover data obtained using model-interpolation techniques are suitable for determining conditions for the optical observations at a local geophysical observatory. For this purpose, we compared the dynamics of cloud cover from ECMWF’s ERA5 with [...] Read more.
This work addresses the issue of how much cloud cover data obtained using model-interpolation techniques are suitable for determining conditions for the optical observations at a local geophysical observatory. For this purpose, we compared the dynamics of cloud cover from ECMWF’s ERA5 with the night atmosphere transparency according to a digital camera in December 2020 at the Geophysical Observatory of the Institute of Solar-Terrestrial Physics, located in the Baikal Natural Territory near the village of Tory (Buryatia, Russia). The comparative analysis showed a generally good agreement between cloud cover from ECMWF’s ERA5 climate reanalysis and those observed with the camera. Disadvantages are the lack of information on rapid variations in cloud cover in the reanalysis and positive and negative delays in the dynamics of cloud fields that last about two hours. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Plots of Kc (blue) and ERA5 total cloud cover (green). The entire period (December 2020) is divided into 10-day intervals for ease of analysis. (<bold>a</bold>) 01.12.2020–09.12.2020; (<bold>b</bold>) 10.12.2020–19.12.2020; (<bold>c</bold>) 20.12.2020–31.12.2020.</p>
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5 pages, 260 KiB  
Proceeding Paper
Climatic Variability of Precipitation Simulated by a Regional Dynamic Model in Tropical South America
by Cláudio M. Santos e Silva, Bergson Guedes Bezerra, Pedro Rodrigues Mutti, Paulo Sergio Lucio, Keila Rêgo Mendes, Daniele Rodrigues, Cristiano Prestrelo Oliveira, Felipe Medeiros, Maria Leidinice Silva, Layara Campelo dos Reis, Glayson Francisco Bezerra das Chagas, Weber Andrade Gonçalves and Lara de Melo Barbosa Andrade
Environ. Sci. Proc. 2022, 19(1), 61; https://doi.org/10.3390/ecas2022-12821 - 14 Jul 2022
Viewed by 868
Abstract
The present study aimed to analyze the seasonal and interannual variability of simulated rainfall over two contrasting regions of tropical South America. Unlike several previous studies, our analyses were focused on areas with different rainfall regimes within two major regions: the Amazon Basin [...] Read more.
The present study aimed to analyze the seasonal and interannual variability of simulated rainfall over two contrasting regions of tropical South America. Unlike several previous studies, our analyses were focused on areas with different rainfall regimes within two major regions: the Amazon Basin (AMZ) and northeast Brazil (NEB). For this purpose, we used the RegCM4.6 climate model and performed two continuous 30-year simulations (1981–2010) with a 50 km grid spacing. In the EXP_EM simulation, we used the convection parameterization of Emanuel (1991), and in the EXP_GR experiment, we used Grell’s parameterization (1993). Differences between simulations and observations were assessed using the Student’s t-test, with a p-value > 0.01. The mean bias and Willmott’s coefficient of agreement were calculated. Considering these metrics, the EXP_EM simulation presented an overall advantage over the EXP_GR simulation. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
4 pages, 1834 KiB  
Proceeding Paper
Elemental Variation and Health Risk Assessment of PM2.5 at Delhi during North-East Monsoon and South-West Monsoon
by Martina Rani, Sakshi Ahlawat, Sakshi Gupta, Rubiya Banoo, Akansha Rai, Rahul Arya, Pooja Yadav, Sashank Choudhary, Narayanasamy Vijayan, Tuhin Kumar Mandal and Sudhir Kumar Sharma
Environ. Sci. Proc. 2022, 19(1), 62; https://doi.org/10.3390/ecas2022-12842 - 22 Jul 2022
Viewed by 1012
Abstract
This study elucidates the variation of PM2.5 concentrations in Delhi during the north-east monsoon (NEM) and the south-west monsoon (SWM) period of 2014–2019. The average concentrations of PM2.5 were 113 ± 48 µg/m3 and 50 ± 19 µg/m3 during [...] Read more.
This study elucidates the variation of PM2.5 concentrations in Delhi during the north-east monsoon (NEM) and the south-west monsoon (SWM) period of 2014–2019. The average concentrations of PM2.5 were 113 ± 48 µg/m3 and 50 ± 19 µg/m3 during NEM and SWM, respectively. Further, the elemental composition of PM2.5 was analyzed using wavelength dispersive X-ray Fluorescence (WD-XRF). During NEM, it was observed that the Na, Cl and S dominating over the region, whereas Na, S, Al, dominated during the SWM season. Backward trajectories analysis suggested the long-range transportation of air mass from the Sahara Desert (SD), Arabian Sea (AS), and Bay of Bengal (BOB) for both the seasons (NEM and SWM), thus significantly affecting the loading of mass concentration of PM2.5 at the study site of Delhi. We also evaluated the hazard quotient (HQ) of elements present in PM2.5 over Delhi during this period. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Sampling site.</p>
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<p>PM<sub>2.5</sub> concentrations during NEM and SWM.</p>
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6 pages, 806 KiB  
Proceeding Paper
Analysis of Some Properties of the Intense Cold Conditions in Havana
by Beatriz Velázquez Zaldívar, Dunia Hernández González, Sinaí Barcia Sardiñas, Osniel Armas Forteza and Antonio Vladimir Guevara Velazco
Environ. Sci. Proc. 2022, 19(1), 63; https://doi.org/10.3390/ecas2022-12825 - 9 Nov 2022
Viewed by 1115
Abstract
In this article, statistical characteristics such as gusts, persistence and the conditioned probabilities of days with the Intense Cold Condition in Havana are analyzed. The bioclimatic indicator used is generated from thermal sensations at contrasting times of the day (07:00 and 13:00 h), [...] Read more.
In this article, statistical characteristics such as gusts, persistence and the conditioned probabilities of days with the Intense Cold Condition in Havana are analyzed. The bioclimatic indicator used is generated from thermal sensations at contrasting times of the day (07:00 and 13:00 h), depending on the presence or absence of wind. The climatic data belong to the meteorological stations of Casablanca and Santiago de las Vegas, in the period 1981–2018. Through the study, it was possible to obtain additional information on the behavior and manifestations of the Intense Cold Condition in the province of Havana, laying the foundations for later extending its use to the entire country. The persistence values of the phenomenon are lower as the gusts increase, showing that these events are generally limited to periods of a few days. Full article
(This article belongs to the Proceedings of The 5th International Electronic Conference on Atmospheric Sciences)
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<p>Meteorological stations in the province of Havana.</p>
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<p>Gusts of days with CFI in the two study stations.</p>
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<p>Number of gusts in more than 3 days or not: without wind (<bold>left</bold>) and with wind (<bold>right</bold>).</p>
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<p>Persistence and probabilities in the variant without wind and with it, for the two study stations.</p>
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