Atmosphere

24 pages, 11539 KiB

Open AccessArticle

Characteristics of Clouds and Raindrop Size Distribution in Xinjiang, Using Cloud Radar Datasets and a Disdrometer

by Yong Zeng, Lianmei Yang, Zuyi Zhang, Zepeng Tong, Jiangang Li, Fan Liu, Jinru Zhang and Yufei Jiang

Atmosphere 2020, 11(12), 1382; https://doi.org/10.3390/atmos11121382 - 21 Dec 2020

Cited by 22 | Viewed by 4019

Abstract

Observation data from March to May 2020 of the Ka-band millimeter-wave cloud radar and disdrometer, located in Xinjiang, a typical arid region of China, were used to study the diurnal variation of clouds and precipitation, raindrop size distribution (DSD), and the physical parameters [...] Read more.

Observation data from March to May 2020 of the Ka-band millimeter-wave cloud radar and disdrometer, located in Xinjiang, a typical arid region of China, were used to study the diurnal variation of clouds and precipitation, raindrop size distribution (DSD), and the physical parameters of raindrops. The results showed that there are conspicuous diurnal changes in clouds and precipitation. There is a decreasing trend of the cloud base height (CBH) from 05:00 to 19:00 CST (China Standard Time, UTC +8) and a rising trend of CBHs from 20:00 to 04:00 CST. The cloud top height (CTH) and the cloud thickness show a rising trend from 03:00 to 05:00 CST, 12:00 to 14:00 CST, and 20:00 to 01:00 CST. The diurnal variation of clouds is mainly driven by wind and temperature closely related to the topography of the study area. There are three apparent precipitation periods during the day, namely, 02:00–09:00 CST, 12:00 CST, and 17:00–21:00 CST. The changes in the physical parameters of raindrops are more drastic and evident with a lower CBH, lower CTH, and higher number of cloud layers from 12:00 to 21:00 CST than other times, which are closely related to day-to-day variations of systems moving through, and incoming solar radiation and the mountain–valley wind circulation caused by the trumpet-shaped topography that opens to the west played a secondary role. The DSD is in agreement with a normalized gamma distribution, and the value of the shape factor μ is significantly different from the fixed μ value in the Weather Research and Forecasting (WRF) Model. The rain in arid Xinjiang had a higher concentration of raindrops and a smaller average raindrop diameter than the rain in other humid regions of the Central and Southeast Asian continent. In the

Z - R

(radar reflectivity–rain rate) relationship,

Z = 249 R^{1.20}

is derived for stratiform rain, and it is significantly different from humid regions. Using

Z / D_{m}

(mass–weighted mean diameter) and R, a new empirical relationship

Z / D_{m} = 214 R^{1.20}

is established, and improvement is obtained in rain retrieval by using the

Z / D_{m} - R

relation relative to the conventional

Z - R

relation. Additionally, the

N_{t} - R

,

D_{m} - R

,

N_{w} - R

, and

N_{t} - N_{w}

relationships with larger differences from humid regions are established by fitting the power-law equations. These results are useful for improving the data parameters of microphysical processes of WRF and the accuracy of quantitative precipitation estimation in arid regions. Full article

(This article belongs to the Section Meteorology)

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16 pages, 1701 KiB

Open AccessArticle

Increases in Biogenic Volatile Organic Compound Concentrations Observed after Rains at Six Forest Sites in Non-Summer Periods

by Takafumi Miyama, Tomoaki Morishita, Yuji Kominami, Hironori Noguchi, Yukio Yasuda, Natsuko Yoshifuji, Michiaki Okano, Katsumi Yamanoi, Yasuko Mizoguchi, Satoru Takanashi, Kenzo Kitamura and Kazuho Matsumoto

Atmosphere 2020, 11(12), 1381; https://doi.org/10.3390/atmos11121381 - 21 Dec 2020

Cited by 8 | Viewed by 3221

Abstract

Since biogenic volatile organic compounds (BVOCs) are important precursors of ozone, the monitoring of the BVOC concentration distributions is needed. In general, forest BVOC concentrations increase in summer as well as in other seasons. This study aims to detect temporally sporadic increases in [...] Read more.

Since biogenic volatile organic compounds (BVOCs) are important precursors of ozone, the monitoring of the BVOC concentration distributions is needed. In general, forest BVOC concentrations increase in summer as well as in other seasons. This study aims to detect temporally sporadic increases in BVOC concentrations in the non-summer months and to analyze the occurring climatic conditions. Using a uniform sampling system and shared gas chromatography–mass spectrometry, the concentrations of isoprene and monoterpenes in six Japanese forests were observed approximately once a month for 3 years. Using the observed data, the relations between the BVOC concentration increases and meteorological factors were evaluated. Twenty instances of temporal increases in BVOC concentrations were observed. These mainly occurred in spring for isoprene and in autumn for monoterpenes. Most of the increases in the non-summer months were observed after a rainfall event, when the daily temperature range was large, suggesting that wind, rain, and a rapid diurnal temperature rise could be factors in the non-summer months. Thus, the network monitoring of BVOC concentrations might be effective for understanding the effects of factors other than temperature, and the mechanisms and frequency of the temporal increases, on the BVOC concentrations in various forests. Full article

(This article belongs to the Special Issue Tropospheric Ozone Observations)

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16 pages, 231 KiB

Open AccessCommentary

Lessons Learned from Coupled Fire-Atmosphere Research and Implications for Operational Fire Prediction and Meteorological Products Provided by the Bureau of Meteorology to Australian Fire Agencies

by Mika Peace, Joseph Charney and John Bally

Atmosphere 2020, 11(12), 1380; https://doi.org/10.3390/atmos11121380 - 21 Dec 2020

Cited by 6 | Viewed by 2736

Abstract

Coupled fire-atmosphere models are simulators that integrate a fire component and an atmospheric component, with the objective of capturing interactions between the fire and atmosphere. As a fire releases energy in the combustion process, the surrounding atmosphere adjusts in response to the energy [...] Read more.

Coupled fire-atmosphere models are simulators that integrate a fire component and an atmospheric component, with the objective of capturing interactions between the fire and atmosphere. As a fire releases energy in the combustion process, the surrounding atmosphere adjusts in response to the energy fluxes; coupled fire-atmosphere (CFA) models aim to resolve the processes through which these adjustments occur. Several CFA models have been developed internationally, mostly by meteorological institutions and primarily for use as a research tool. Research studies have provided valuable insights into some of the atmospheric processes surrounding a fire. The potential to run CFA models in real time is currently limited due to the intensive computational requirements. In addition, there is a need for systematic verification to establish their accuracy and the appropriate circumstances for their use. The Bureau of Meteorology (the Bureau) is responsible for providing relevant and accurate meteorological information to Australian fire agencies to inform decisions for the protection of life and property and to support hazard management activities. The inclusion of temporally and spatially detailed meteorological fields that adjust in response to the energy released by a fire is seen as a component in developing fire prediction systems that capture some of the most impactful fire and weather behavior. The Bureau’s ten-year research and development plan includes a commitment to developing CFA models, with the objective of providing enhanced services to Australian fire agencies. This paper discusses the operational use of fire predictions and simulators, learnings from CFA models and potential future directions for the Bureau in using CFA models to support fire prediction activities. Full article

(This article belongs to the Special Issue Coupled Fire-Atmosphere Simulation)

10 pages, 3509 KiB

Open AccessArticle

Atmospheric Mercury Deposition in Macedonia from 2002 to 2015 Determined Using the Moss Biomonitoring Technique

by Trajče Stafilov, Lambe Barandovski, Robert Šajn and Katerina Bačeva Andonovska

Atmosphere 2020, 11(12), 1379; https://doi.org/10.3390/atmos11121379 - 21 Dec 2020

Cited by 13 | Viewed by 2708

Abstract

The moss biomonitoring technique was used in 2002, 2005, 2010 and 2015 in a potentially toxic elements study (PTEs) in Macedonia. For that purpose, more than 70 moss samples from two dominant species (Hypnum cupressiforme and Homalothecium lutescens) were collected during the [...] Read more.

The moss biomonitoring technique was used in 2002, 2005, 2010 and 2015 in a potentially toxic elements study (PTEs) in Macedonia. For that purpose, more than 70 moss samples from two dominant species (Hypnum cupressiforme and Homalothecium lutescens) were collected during the summers of the mentioned years. Total digestion of the samples was done using a microwave digestion system, whilst mercury was analyzed by cold vapour atomic absorption spectrometry (CV–AAS). The content of mercury ranged from 0.018 mg/kg to 0.26 mg/kg in 2002, from 0.010 mg/kg to 0.42 mg/kg in 2005, from 0.010 mg/kg to 0.60 mg/kg in 2010 and from 0.020 mg/kg to 0.25 mg/kg in 2015. Analysis of the median values shows the increase of the content in the period 2002–2010 and a slight reduction of the air pollution with Hg in the period 2010–2015. Mercury distribution maps show that sites with increased concentrations of mercury in moss are likely impacted by anthropogenic pollution. The results were compared to similar studies done during the same years in neighboring countries and in Norway—which is a pristine area and serves as a reference, and it was concluded that mercury air pollution in Macedonia is significant primarily in industrialized regions. Full article

(This article belongs to the Special Issue Atmospheric Mercury Monitoring, Analysis, and Chemistry: New Insights and Progress toward Minamata Convention Goals)

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20 pages, 8133 KiB

Open AccessArticle

Circulation Specific Precipitation Patterns over Svalbard and Projected Future Changes

by Andreas Dobler, Julia Lutz, Oskar Landgren and Jan Erik Haugen

Atmosphere 2020, 11(12), 1378; https://doi.org/10.3390/atmos11121378 - 21 Dec 2020

Cited by 6 | Viewed by 3393

Abstract

Precipitation on Svalbard can generally be linked to the atmospheric circulation in the Northern Atlantic. Using an automated circulation type classification, we show that weather type statistics are well represented in the Max Planck Institute Earth System Model at base resolution (MPI-ESM-LR). For [...] Read more.

Precipitation on Svalbard can generally be linked to the atmospheric circulation in the Northern Atlantic. Using an automated circulation type classification, we show that weather type statistics are well represented in the Max Planck Institute Earth System Model at base resolution (MPI-ESM-LR). For a future climate projection following the Representative Concentration Pathway scenario RCP8.5, we find only small changes in the statistics. However, convection permitting simulations with the regional climate model from the Consortium for Small-scale Modeling in climate mode (COSMO-CLM) covering Svalbard at 2.5 km demonstrate an increase in precipitation for all seasons. About 74% of the increase are coming from changes under cyclonic weather situations. The precipitation changes are strongly related to differences in atmospheric conditions, while the contribution from the frequencies of weather types is small. Observations on Svalbard suggest that the general weather situation favouring heavy precipitation events is a strong south-southwesterly flow with advection of water vapour from warmer areas. This is reproduced by the COSMO-CLM simulations. In the future projections, the maximum daily precipitation amounts are further increasing. At the same time, weather types with less moisture advection towards Svalbard are becoming more important. Full article

(This article belongs to the Special Issue Regional Climate Modeling with COSMO-CLM: Performance Assessment and Climate Projections)

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15 pages, 2614 KiB

Open AccessArticle

Quantifying the Independent Influences of Land Cover and Humidity on Microscale Urban Air Temperature Variation in Hot Summer: Methods of Path Analysis and Genetic SVR

by Weifang Shi, Nan Wang, Aixuan Xin, Linglan Liu, Jiaqi Hou and Yirui Zhang

Atmosphere 2020, 11(12), 1377; https://doi.org/10.3390/atmos11121377 - 21 Dec 2020

Cited by 2 | Viewed by 2165

Abstract

Mitigating high air temperatures and heat waves is vital for decreasing air pollution and protecting public health. To improve understanding of microscale urban air temperature variation, this paper performed measurements of air temperature and relative humidity in a field of Wuhan City in [...] Read more.

Mitigating high air temperatures and heat waves is vital for decreasing air pollution and protecting public health. To improve understanding of microscale urban air temperature variation, this paper performed measurements of air temperature and relative humidity in a field of Wuhan City in the afternoon of hot summer days, and used path analysis and genetic support vector regression (SVR) to quantify the independent influences of land cover and humidity on air temperature variation. The path analysis shows that most effect of the land cover is mediated through relative humidity difference, more than four times as much as the direct effect, and that the direct effect of relative humidity difference is nearly six times that of land cover, even larger than the total effect of the land cover. The SVR simulation illustrates that land cover and relative humidity independently contribute 16.3% and 83.7%, on average, to the rise of the air temperature over the land without vegetation in the study site. An alternative strategy of increasing the humidity artificially is proposed to reduce high air temperatures in urban areas. The study would provide scientific support for the regulation of the microclimate and the mitigation of the high air temperature in urban areas. Full article

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Figure 1
Schematic of the field measurement. Full article ">Figure 2
Two priori models for path analysis. (a) Priori model one; (b) Priori model two. Full article ">Figure 3
Framework of the genetic support vector regression. Full article ">Figure 4
Over flowchart of genetic support vector regression (SVR) training to optimize parameters. Full article ">Figure 5
Box plots of Air Temperature Difference (∆Ta) (a) and Relative Humidity Difference (∆RH) (b). Full article ">Figure 6
Air Temperature Difference (∆Ta) varying with Distance (∆X) at ∆RH = 0. Full article ">Figure 7
Air Temperature Difference (∆Ta) varying with Relative Humidity Difference (∆RH) at ∆X = 0. Full article ">Figure 8
Air Temperature Difference (∆Ta) varying with Relative Humidity Difference (∆RH) at ∆X = 30 m. Full article ">

13 pages, 6844 KiB

Open AccessArticle

A 5000-Year Sedimentary Record of East Asian Winter Monsoon from the Northern Muddy Area of the East China Sea

by Yanping Chen, Yan Li, Wenzhe Lyu, Dong Xu, Xibin Han, Tengfei Fu and Liang Yi

Atmosphere 2020, 11(12), 1376; https://doi.org/10.3390/atmos11121376 - 20 Dec 2020

Cited by 8 | Viewed by 3111

Abstract

The variability of the winter monsoon is one of the key components of the Asian monsoon, significantly influencing paleoenvironmental evolution in East Asia. However, whether the winter or the summer monsoon is the dominated factor controlling sedimentary dynamics of the muddy areas of [...] Read more.

The variability of the winter monsoon is one of the key components of the Asian monsoon, significantly influencing paleoenvironmental evolution in East Asia. However, whether the winter or the summer monsoon is the dominated factor controlling sedimentary dynamics of the muddy areas of the continental shelves of the East China Sea is debated, due to lack of consistency between various winter monsoon proxies in previous studies. In this work, the sediments of the upper part of core ECS-DZ1 with several marine surface samples were studied in terms of sediment grain size and radiocarbon dating, and changes in sedimentary dynamics of the northern muddy area of the ECS over the past 5000 years were documented. The main findings are as follows: (1) regional sedimentary dynamics were low and did not significantly change since the middle Holocene; (2) coarse particles are the dominated component in the sediments; (3) a proxy can be derived to indicate changes in winter monsoon. Based on this reconstructed winter monsoon record, we found that this record was generally negatively correlated to the stalagmite-based summer monsoon variability over the past 3500 years, but positively correlated before that. Moreover, this record can be well correlated to changes in the Kuroshio Current and the Bond ice-rafting debris events in the North Atlantic on millennial timescales, inferring large-scale and common atmospheric dynamics across the Asian continent over the past 5000 years. Therefore, we concluded that the winter monsoon is the predominant factor controlling sedimentary dynamics in the northern part of the ECS and proposed that the contribution of coarse particles may be one of potential indices to identify the role of the winter and the summer monsoons in sedimentary evolution. Full article

(This article belongs to the Section Climatology)

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Figure 1
Location of core ECS-DZ1 with 6 sites of surface samples (H1-H6) and regional climatic and oceanographic systems. The solid arrows denote warm currents (YSWC, Yellow Sea warm current; KC, Kuroshio current), and the dashed arrows indicate coastal cold waters (YSCC, Yellow Sea coast cold water). The base map data was generated using the open and free software DIVA-GIS 7.5 (<a href="http://www.diva-gis.org/" target="_blank">http://www.diva-gis.org/</a>). Full article ">Figure 2
Core photos and profile of core ECS-DZ1 about component percentages of clay (<4 μm), silt (4–63 μm), and sand (>63 μm), median size (Md), mean size (Mz), C value (the one percentile of grain size distribution), and AMS 14C dating results with an age-depth model. Full article ">Figure 3
Characteristics of sediment grain size of core ECS-DZ1 and six surface samples. (a) Ternary diagrams; (b) C-M diagrams; (c) grain size distribution; (d) principal component analysis. Lcomp1 and Lcomp2 are the two characterized grain-size components through mathematical partitioning of sediment grain-size spectrum; and Fcomp1, Fcomp2, and Fcomp3 are the three components by VPCA. Full article ">Figure 4
Changes in sediment grain-size parameters of core ECS-DZ1. Full article ">Figure 5
Comparison between various paleoenvironmental proxies over the past 5000 years. (a) 5-point moving average of five grain-size parameters of core ECS-DZ1; (b) Fcom2 record of core ECS-DZ1 indicating changes in the winter monsoon; (c) DET YS-GS index, indicating winter dust storms in Central Asia [<a href="#B40-atmosphere-11-01376" class="html-bibr">40</a>]; (d) ice-rafting debris (IRD), stack ice-rafting debris data from Bond, et al. [<a href="#B41-atmosphere-11-01376" class="html-bibr">41</a>]; (e) Stack KC, integrated indicator from four time series [<a href="#B42-atmosphere-11-01376" class="html-bibr">42</a>]; (f) Stalagmite δ18O series of Sanbao Cave [<a href="#B43-atmosphere-11-01376" class="html-bibr">43</a>], indicating East Asian summer monsoon (EASM) intensity. Full article ">

26 pages, 25251 KiB

Open AccessEditor’s ChoiceArticle

Graz Lagrangian Model (GRAL) for Pollutants Tracking and Estimating Sources Partial Contributions to Atmospheric Pollution in Highly Urbanized Areas

by Aleksey A. Romanov, Boris A. Gusev, Egor V. Leonenko, Anastasia N. Tamarovskaya, Alexander S. Vasiliev, Nikolai E. Zaytcev and Ilia K. Philippov

Atmosphere 2020, 11(12), 1375; https://doi.org/10.3390/atmos11121375 - 19 Dec 2020

Cited by 19 | Viewed by 9525

Abstract

Computational modeling allows studying the air quality problems in depth and provides the best solution reducing the population risks. This research demonstrates the Graz Lagrangian model effectiveness for assessing emission sources contributions to the air pollution: particles tracking and accumulation estimate. The article [...] Read more.

Computational modeling allows studying the air quality problems in depth and provides the best solution reducing the population risks. This research demonstrates the Graz Lagrangian model effectiveness for assessing emission sources contributions to the air pollution: particles tracking and accumulation estimate. The article describes model setting up parameters and datasets preparation for the analysis. The experiment simulated the dispersion from the main groups of emission sources for real weather conditions during 96 h of December 2018, when significant excess of NO₂, CO, SO₂, PM10, and benzo(a)pyrene concentrations were observed in the Krasnoyarsk surface atmospheric layer. The computational domain was a parallelepiped of 40 × 30 × 2.5 km, which was located deep inside the Eurasian continent on a heterogeneous landscape exaggerated by high-rise buildings, with various pollutions sources and the ice-free Yenisei River. The results demonstrated an excellent applicability of the Lagrange model for hourly tracking of particle trajectories, taking into account the urban landscape. For values <1 MPC (maximum permissible concentration) of peak pollutants concentrations, the coincidences were 93 cases, and for values < 0.1 shares of MPC, there were 36 cases out of the total number of 97. The same was found for the average daily concentration for values <1 MPC—31, and for values <0.1 MPC—5 matches out of 44. Wind speeds COR—65.3%, wind directions COR—68.6%. The Graz Lagrangian model showed the ability to simulate air quality problems in the Krasnoyarsk greater area conditions. Full article

(This article belongs to the Special Issue Atmospheric Trace Gas Source Detection and Quantification)

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25 pages, 6870 KiB

Open AccessArticle

Comparing Approaches for Reconstructing Groundwater Levels in the Mountainous Regions of Interior British Columbia, Canada, Using Tree Ring Widths

by Stephanie C. Hunter, Diana M. Allen and Karen E. Kohfeld

Atmosphere 2020, 11(12), 1374; https://doi.org/10.3390/atmos11121374 - 19 Dec 2020

Cited by 6 | Viewed by 2903

Abstract

Observed groundwater level records are relatively short (<100 years), limiting long-term studies of groundwater variability that could provide valuable insight into climate change effects. This study uses tree ring data from the International Tree Ring Database (ITRDB) and groundwater level data from 22 [...] Read more.

Observed groundwater level records are relatively short (<100 years), limiting long-term studies of groundwater variability that could provide valuable insight into climate change effects. This study uses tree ring data from the International Tree Ring Database (ITRDB) and groundwater level data from 22 provincial observation wells to evaluate different approaches for reconstructing groundwater levels from tree ring widths in the mountainous southern interior of British Columbia, Canada. The twenty-eight reconstruction models consider the selection of observation wells (e.g., regional average groundwater level vs. wells classified by recharge mechanism) and the search area for potential tree ring records (climate footprint vs. North American Ecoregions). Results show that if the climate footprint is used, reconstructions are statistically valid if the wells are grouped according to recharge mechanism, with streamflow-driven and high-elevation recharge-driven wells (both snowmelt-dominated) producing valid models. Of all the ecoregions considered, only the Coast Mountain Ecoregion models are statistically valid for both the regional average groundwater level and high-elevation recharge-driven systems. No model is statistically valid for low-elevation recharge-driven systems (rainfall-dominated). The longest models extend the groundwater level record to the year 1500, with the highest confidence in the later portions of the reconstructions going back to the year 1800. Full article

(This article belongs to the Special Issue Past Climate Reconstructed from Tree Rings)

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Figure 1
Location map of observation wells within the southern Interior Plateau Region of British Columbia and tree ring records available from the International Tree Ring Database (ITRDB). Tree ring records used for the Explorative Data Analysis (EDA) are circled in red. The inset map shows the location of the study region within western Canada and the northwestern United States. Observation wells are colour-coded by aquifer–stream system type and classified using hysteresis plots as discussed in <a href="#sec2dot1-atmosphere-11-01374" class="html-sec">Section 2.1</a>. Source for basemap digital elevation model (DEM): HydroSHEDS Database, available from <a href="http://hydrosheds.cr.usgs.gov" target="_blank">http://hydrosheds.cr.usgs.gov</a>. Full article ">Figure 2
Representative hysteresis plots for (a) a streamflow-driven system characterized by a negative or counter-clockwise loop, and (b) a recharge-driven system characterized by a positive or clockwise hysteresis loop. Full article ">Figure 3
Climate footprint for the BC Interior showing the spatial extent of significant correlation (p < 0.10) between average depth to groundwater levels and gridded 12-month Standardized Precipitation Evaporation Index (SPEI) (Koninklijk Nederlands Meteorologisch Instituut (KNMI) Climate Explorer). Full article ">Figure 4
Example groundwater (black solid line) and streamflow (shaded grey area) hydrographs for (a) a streamflow-driven system and b) a recharge-driven system. Temperature (grey dashed line) and precipitation (blue/light blue bars distinguishing rain from snow) are also shown in a) and (b). Corresponding tree ring width/depth to groundwater level correlation graphs are shown for (c) a streamflow-driven system and (d) a recharge-driven system. The standard chronologies produced using dplR are shown for the two sample chronologies which were located near these observations wells: (e) Cana 229 and (f) Cana 234, with the grey solid line indicating annual ring width indices, grey shading indicating the sample depth through time, and the solid red line showing a 20-year smoothing spline. Full article ">Figure 5
Tree ring records used in the (a) low-elevation recharge-driven, (b) streamflow-driven, and (c) high-elevation recharge-driven groundwater level models, using the climate footprint to select potential tree ring records. Full article ">Figure 6
Final groundwater level reconstructions and actual groundwater levels (GWL, shown in dark blue) for the average of wells in the (a) streamflow-driven and (b) high-elevation recharge-driven models using the climate footprint, and the (c) all-wells and (d) high-elevation recharge-driven models created using the Coast Mountain Ecoregions. The number of tree ring records used in each model throughout time is shown with the dashed red line. The black arrow indicates the time at which the reconstruction models might be truncated due to increasing uncertainty moving farther back into time (see <a href="#sec4-atmosphere-11-01374" class="html-sec">Section 4</a>). Full article ">

19 pages, 1528 KiB

Open AccessReview

Monitoring of Selected CBRN Threats in the Air in Industrial Areas with the Use of Unmanned Aerial Vehicles

by Anna Rabajczyk, Jacek Zboina, Maria Zielecka and Radosław Fellner

Atmosphere 2020, 11(12), 1373; https://doi.org/10.3390/atmos11121373 - 19 Dec 2020

Cited by 11 | Viewed by 4926

Abstract

Unmanned aerial vehicles (UAVs) play an increasingly important role in various areas of life, including in terms of protection and security. As a result of fires, volcanic eruptions, or other emergencies, huge amounts of toxic gases, dust, and other substances are emitted into [...] Read more.

Unmanned aerial vehicles (UAVs) play an increasingly important role in various areas of life, including in terms of protection and security. As a result of fires, volcanic eruptions, or other emergencies, huge amounts of toxic gases, dust, and other substances are emitted into the environment, which, together with high temperature, often leads to serious environmental contamination. Based on the available literature and patent databases, an analysis of the available UAVs models was carried out in terms of their applicability in air contaminated conditions in industrial areas, in the event of emergencies, such as fire, chemical contamination. The possibilities of using the devices were analyzed in terms of weather conditions, construction, and used materials in CBRN (chemical, biological, radiological, nuclear) threat situations. It was found that, thanks to the use of appropriate sensors, cameras, and software of UAVs integrated with a given system, it is possible to obtain information on air quality at a given moment, which is very important for the safety of people and the environment. However, several elements, including the possibility of use in acidification conditions, requires refinement to changing crisis conditions. Full article

(This article belongs to the Section Air Quality)

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13 pages, 1991 KiB

Open AccessArticle

Improving Air Quality for Operators of Mobile Machines in Underground Mines

by Andrzej Szczurek, Monika Maciejewska, Marcin Przybyła and Wacław Szetelnicki

Atmosphere 2020, 11(12), 1372; https://doi.org/10.3390/atmos11121372 - 18 Dec 2020

Cited by 1 | Viewed by 2941

Abstract

In underground mines, mobile mining equipment is critical for the production system. The microenvironment inside the mobile machine may cause exposure to strongly polluted mine air, which adversely affects the health and working performance of the operator. Harmful pollutants may access the cabin [...] Read more.

In underground mines, mobile mining equipment is critical for the production system. The microenvironment inside the mobile machine may cause exposure to strongly polluted mine air, which adversely affects the health and working performance of the operator. Harmful pollutants may access the cabin together with the ventilation air delivered from the machine’s surroundings. This work proposes a solution that is able to ensure that the air for the machine operator is of proper quality. The proposal emerged from an analysis of the compliance of cabins of mobile machines working underground in mines with occupational health and safety (H&S) standards. An analytical model of air quality in a well-mixed zone was utilized for this purpose. The cabin atmosphere was investigated with regard to the concentration of gaseous species in the surrounding air, the cabin ventilation rate, and human breathing parameters. The analysis showed that if currently available ventilation approaches are used, compliance with multiple H&S standards cannot be attained inside the cabin if standards are exceeded in the surroundings of the machine. The proposed solution overcomes this problem by combining elements that are already in place, i.e., ventilation, air-conditioning, and filtration with a personal supply of clean air. The concept is generic and may be adapted to various specific requirements. Full article

(This article belongs to the Special Issue Exposure Assessment of Air Pollution)

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Figure 1
Cabin of a loader—autonomous mobile machine operating in underground mines. Internal dimensions: A—1275 mm, C—1335 mm, D—800 mm. Full article ">Figure 2
Time when the concentration of a substance in cabin air increases from the clean air level to the predefined threshold value. The time is displayed as a function of the air exchange rate between the cabin and its surroundings, for various concentrations of a substance in the mine air. The concentration in the mine air refers to the threshold level multiple, using <math display="inline"><semantics> <mi>b</mi> </semantics></math>. Solid lines refer to substances emitted only outside the cabin, such as NO, NO2, and CO. Dotted lines refer to CO2. Full article ">Figure 3
H&S standard compliance in cabin air with respect to substances emitted exclusively outside cabin, such as NO, NO2, and CO. Full article ">Figure 4
H&S standard compliance in cabin air with respect to CO2. Full article ">Figure 5
Isolines display the fraction of time when the threshold concentration may be exceeded in the cabin air (no more than threshold multiple), while in the remaining time the concentration remains below the threshold (no more than the threshold fraction). This ensures H&S standard compliance. Full article ">Figure 6
Isolines display the fraction of the clean air, <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mrow> <mi>P</mi> <mi>U</mi> <mi>R</mi> </mrow> </msub> <mo>,</mo> </mrow> </semantics></math> that has to be delivered to the breathing zone of the mobile machine operator, to ensure the required quality of the breathing air (threshold fraction) for the particular composition of the cabin air (threshold multiple). Solid lines refer to the substances emitted only outside the cabin such as NO, NO2, and CO. Dotted lines refer to CO2. Full article ">

12 pages, 2079 KiB

Open AccessArticle

Vertical Profiles of Atmospheric Species Concentrations and Nighttime Boundary Layer Structure in the Dry Season over an Urban Environment in Central Amazon Collected by an Unmanned Aerial Vehicle

by Patrícia Guimarães, Jianhuai Ye, Carla Batista, Rafael Barbosa, Igor Ribeiro, Adan Medeiros, Tianning Zhao, Wei-Chun Hwang, Hui-Ming Hung, Rodrigo Souza and Scot T. Martin

Atmosphere 2020, 11(12), 1371; https://doi.org/10.3390/atmos11121371 - 18 Dec 2020

Cited by 22 | Viewed by 3704

Abstract

Nighttime vertical profiles of ozone, PM_2.5 and PM₁₀ particulate matter, carbon monoxide, temperature, and humidity were collected by a copter-type unmanned aerial vehicle (UAV) over the city of Manaus, Brazil, in central Amazon during the dry season of 2018. The vertical [...] Read more.

Nighttime vertical profiles of ozone, PM_2.5 and PM₁₀ particulate matter, carbon monoxide, temperature, and humidity were collected by a copter-type unmanned aerial vehicle (UAV) over the city of Manaus, Brazil, in central Amazon during the dry season of 2018. The vertical profiles were analyzed to understand the structure of the urban nighttime boundary layer (NBL) and pollution within it. The ozone concentration, temperature, and humidity had an inflection between 225 and 350 m on most nights, representing the top of the urban NBL. The profile of carbon monoxide concentration correlated well with the local evening vehicular congestion of a modern transportation fleet, providing insight into the surface-atmosphere dynamics. In contrast, events of elevated PM_2.5 and PM₁₀ concentrations were not explained well by local urban emissions, but rather by back trajectories that intersected regional biomass burning. These results highlight the potential of the emerging technologies of sensor payloads on UAVs to provide new constraints and insights for understanding the pollution dynamics in nighttime boundary layers in urban regions. Full article

(This article belongs to the Special Issue Atmospheric Measurements Using Unmanned Systems)

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Figure 1
Representative image of the study area in the city of Manaus, Brazil, in central Amazon. The urban region is crossed by rivers and interspersed with forests. Nighttime flights to collect vertical profiles took place on the campus of the Amazonas State University (marked as a red disc and labeled “UEA”) in the middle of the city. The green region in the inset shows the state of Amazonas, Brazil, in South America. Full article ">Figure 2
Box-whisker plots of the statistics of ozone concentration at different altitudes. Results are presented for the (a) wet and (b) dry seasons of 2018 (57 and 84 flights, respectively). The red line represents the median, the box edges show the quartiles, and the horizontal black lines indicate the minimum and maximum values, excluding outliers. Flights took place between 20:00 and 00:00 (local time (LT)). LT was 4 h earlier than UTC. The data of panel (a) are from Guimarães et al. [<a href="#B10-atmosphere-11-01371" class="html-bibr">10</a>]. Full article ">Figure 3
Box-whisker statistics plots of the height of the nighttime boundary layer during the dry season of 2018 based on (a) ozone concentration, (b) potential temperature, and (c) specific humidity (84 flights). The median (red line), quartiles (blue box edges), and the minimum and maximum values (black lines) are represented, excluding outliers. Flights took place between 20:00 and 00:00 (LT). Local time (LT) was 4 h earlier than UTC. Full article ">Figure 4
Vertical profiles of the concentrations of ozone, carbon monoxide, PM2.5, and PM10 from land surface to an altitude of 500 m for 8 flights on 29 September 2018 between 20:00 and 00:00 (LT). The red line represents the median of the data at each altitude. The dashed line represents the instrumental limit of detection for ozone (3 ppbv). Individual profiles are plotted in <a href="#app1-atmosphere-11-01371" class="html-app">Figure S2</a>. Full article ">Figure 5
Evolution of vertical profiles of the concentrations of ozone, carbon monoxide, PM2.5, and PM10 from land surface to an altitude of 500 m on 27 September 2018 from 20:00 to 22:00 (LT). Full article ">

16 pages, 3752 KiB

Open AccessArticle

Local Weather Conditions Create Structural Differences between Shallow Firn Columns at Summit, Greenland and WAIS Divide, Antarctica

by Ian E. McDowell, Mary R. Albert, Stephanie A. Lieblappen and Kaitlin M. Keegan

Atmosphere 2020, 11(12), 1370; https://doi.org/10.3390/atmos11121370 - 17 Dec 2020

Cited by 2 | Viewed by 3376

Abstract

Understanding how physical characteristics of polar firn vary with depth assists in interpreting paleoclimate records and predicting meltwater infiltration and storage in the firn column. Spatial heterogeneities in firn structure arise from variable surface climate conditions that create differences in firn grain growth [...] Read more.

Understanding how physical characteristics of polar firn vary with depth assists in interpreting paleoclimate records and predicting meltwater infiltration and storage in the firn column. Spatial heterogeneities in firn structure arise from variable surface climate conditions that create differences in firn grain growth and packing arrangements. Commonly, estimates of how these properties change with depth are made by modeling profiles using long-term estimates of air temperature and accumulation rate. Here, we compare surface meteorology and firn density and permeability in the depth range of 3.5–11 m of the firn column from cores collected at Summit, Greenland and WAIS Divide, Antarctica, two sites with the same average accumulation rate and mean annual air temperature. We show that firn at WAIS Divide is consistently denser than firn at Summit. However, the difference in bulk permeability of the two profiles is less statistically significant. We argue that differences in local weather conditions, such as mean summer temperatures, daily temperature variations, and yearly wind speeds, create the density discrepancies. Our results are consistent with previous results showing density is not a good indicator of firn permeability within the shallow firn column. Future modeling efforts should account for these weather variables when estimating firn structure with depth. Full article

(This article belongs to the Special Issue Modeling and Measuring Snow Processes across Scales)

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Figure 1
Location of firn core collection and automated weather station sites: (a) Summit, Greenland (GIS Summit) and (b) West Antarctic Ice Sheet (WAIS) Divide, Antarctica (WAIS Divide). Coring locations are plotted on the Greenland 5 km digital elevation model (DEM) [<a href="#B18-atmosphere-11-01370" class="html-bibr">18</a>] and the Antarctic 1 km DEM [<a href="#B19-atmosphere-11-01370" class="html-bibr">19</a>]. Greenland and Antarctica are displayed using the WGS 1984 Arctic and Antarctic Polar Stereographic Coordinate systems, respectively. The Summit firn core was collected from ~3200 m above sea level and the elevation at WAIS Divide was ~1800 m. Full article ">Figure 2
Firn density profiles (a,b) and permeability profiles (c,d) between 3.5 m and 11 m depth at GIS Summit (a,c) and WAIS Divide (b,d). The solid black line in panels (a,b) is the modeled firn density profile generated from Herron and Langway (1980) [<a href="#B12-atmosphere-11-01370" class="html-bibr">12</a>]. In panels (c,d), the solid black line represents the modeled permeability profile from Adolph and Albert (2014) [<a href="#B14-atmosphere-11-01370" class="html-bibr">14</a>] and the dashed black line shows modeled permeability profiles using the model of Freitag et al. (2002) [<a href="#B15-atmosphere-11-01370" class="html-bibr">15</a>]. All modeled density and permeability profiles shown were generated using an accumulation rate of 0.22 m yr−1, mean air temperature of −28 °C, and surface snow density of 0.34 kg m−3. Full article ">Figure 3
Distribution of density (a,c) and permeability (b,d) in the depth range of 3.5–11 m in the firn column at GIS Summit (a,b) and WAIS Divide (c,d). The number of measurements, n, used to create each histogram are as follows: GIS Summit density n = 137, GIS Summit permeability n = 137, WAIS Divide density n = 86, WAIS Divide permeability n = 71. Bin widths were set to 0.2 kg m−3 for density histograms and 7.0 × 10−10 m2 for permeability histograms. Box plots above each distribution show interquartile range and whiskers extend to encompass 95% of the data. The median value is indicated by a line within the interquartile range. Full article ">Figure 4
Meteorological data from both Summit (panels (a,c,e)) and WAIS Divide (panels (b,d,f). Air temperatures at the two sites are shown in panels (a,b), relative humidity values are displayed in panels (c,d), and wind speeds are plotted in panels (e,f). Hourly data are plotted from the years 1997–2007 for Summit and 2009–2019 for WAIS Divide vs. the day of the collection year with grey transparent lines, so that progressively darker greys show overlapping data. Black lines show a mean meteorological value for the given day of the year, averaged over the collection period. Full article ">Figure 5
Variability of daily air temperatures at Summit (a) and WAIS Divide (b). Averaged daily minimum and maximum temperatures are plotted, with the shaded area representing the daily temperature variability. The difference between the highest and lowest daily temperatures are plotted in panel (c). Full article ">Figure A1
NCEP-NCAR reanalysis temperature and relative humidity (grey) plotted with 30-day running means of AWS observed variables (black) for Summit, Greenland (a,c) and WAIS Divide, Antarctica (b,d). Dashed grey lines show least-squares regression fits to the reanalysis data, showing that meteorological conditions remained essentially constant over the previous 25 years. Discrepancies between observed data and reanalysis data are attributed to local variability not captured in the regional nature of the 2.5° × 2.5° gridded reanalysis output. Full article ">

22 pages, 4312 KiB

Open AccessArticle

The Use of Gaussian Mixture Models with Atmospheric Lagrangian Particle Dispersion Models for Density Estimation and Feature Identification

by Alice Crawford

Atmosphere 2020, 11(12), 1369; https://doi.org/10.3390/atmos11121369 - 17 Dec 2020

Cited by 10 | Viewed by 5001

Abstract

Atmospheric Lagrangian particle dispersion models, LPDM, simulate the dispersion of passive tracers in the atmosphere. At the most basic level, model output consists of the position of computational particles and the amount of mass they represent. In order to obtain concentration values, this [...] Read more.

Atmospheric Lagrangian particle dispersion models, LPDM, simulate the dispersion of passive tracers in the atmosphere. At the most basic level, model output consists of the position of computational particles and the amount of mass they represent. In order to obtain concentration values, this information is then converted to a mass distribution via density estimation. To date, density estimation is performed with a nonparametric method so that output consists of gridded concentration data. Here we introduce the use of Gaussian mixture models, GMM, for density estimation. We compare to the histogram or bin counting method for a tracer experiment and simulation of a large volcanic ash cloud. We also demonstrate the use of the mixture model for automatic identification of features in a complex plume such as is produced by a large volcanic eruption. We conclude that use of a mixture model for density estimation and feature identification has potential to be very useful. Full article

(This article belongs to the Special Issue Forecasting the Transport of Volcanic Ash in the Atmosphere)

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16 pages, 4819 KiB

Open AccessArticle

Carbonaceous Aerosols in PM₁, PM_2.5, and PM₁₀ Size Fractions over the Lanzhou City, Northwest China

by Xin Zhang, Zhongqin Li, Feiteng Wang, Mengyuan Song, Xi Zhou and Jing Ming

Atmosphere 2020, 11(12), 1368; https://doi.org/10.3390/atmos11121368 - 17 Dec 2020

Cited by 30 | Viewed by 3552

Abstract

Carbonaceous particles have been confirmed as major components of ambient aerosols in urban environments and are related to climate impacts and environmental and health effects. In this study, we collected different-size particulate matter (PM) samples (PM₁, PM_2.5, and PM [...] Read more.

Carbonaceous particles have been confirmed as major components of ambient aerosols in urban environments and are related to climate impacts and environmental and health effects. In this study, we collected different-size particulate matter (PM) samples (PM₁, PM_2.5, and PM₁₀) at an urban site in Lanzhou, northwest China, during three discontinuous one-month periods (January, April, and July) of 2019. We measured the concentrations and potential transport pathways of carbonaceous aerosols in PM₁, PM_2.5, and PM₁₀ size fractions. The average concentrations of OC (organic carbon) and EC (elemental carbon) in PM₁, PM_2.5, and PM₁₀ were 6.98 ± 3.71 and 2.11 ± 1.34 μg/m³, 8.6 ± 5.09 and 2.55 ± 1.44 μg/m³, and 11.6 ± 5.72 and 4.01 ± 1.72 μg/m³. The OC and EC concentrations in PM₁, PM_2.5, and PM₁₀ had similar seasonal trends, with higher values in winter due to the favorable meteorology for accumulating pollutants and urban-increased emissions from heating. Precipitation played a key role in scavenge pollutants, resulting in lower OC and EC concentrations in summer. The OC/EC ratios and principal component analysis (PCA) showed that the dominant pollution sources of carbon components in the PMs in Lanzhou were biomass burning, coal combustion, and diesel and gasoline vehicle emissions; and the backward trajectory and concentration weight trajectory (CWT) analysis further suggested that the primary pollution source of EC in Lanzhou was local fossil fuel combustion. Full article

(This article belongs to the Special Issue Chemistry of Aqueous Surfaces in the Atmospheric Context)

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(a) Geographical location of Lanzhou, China and (b) locations of the sampling site on the topographic map. Background map was retrieved from Google Earth. Full article ">Figure 2
Time series of the EC and OC concentrations in PM1, PM2.5, and PM10, respectively. The temperature, relative humidity (RH), precipitation, and wind speed (WS) and direction (WD) were recorded by the automatic weather station. Full article ">Figure 3
Seasonal variations of OC and EC in the PMs, where each box indicates the 99%, 75%, 50%, 25%, and 1% quartiles of the data from the top to the bottom. Full article ">Figure 4
Seasonal variation of POC, SOC, OC/EC, and POC/SOC in different-sized PMs. Full article ">Figure 5
Regressions between OC and EC in PM1, PM2.5, and PM10. Different lines (colour) represent the Regressions between in different seasons. Full article ">Figure 6
Seasonal variation and size distribution of carbon components. Full article ">Figure 7
Five-day backward trajectories of Lanzhou and the ratio between OC and EC in each cluster in 500-m layer in (a) winter, (b) spring, and (c) summer. Different lines (colour) represent different clusters. Full article ">Figure 8
Concentration-weighted trajectory (CWT) of OC in (a) winter, (b) spring, and (c) summer and of EC in (d) winter, (e) spring, and (f) summer in PM10 in Lanzhou. Full article ">

29 pages, 10275 KiB

Open AccessArticle

Rainfall Threshold for Shallow Landslides Initiation and Analysis of Long-Term Rainfall Trends in a Mediterranean Area

by Anna Roccati, Guido Paliaga, Fabio Luino, Francesco Faccini and Laura Turconi

Atmosphere 2020, 11(12), 1367; https://doi.org/10.3390/atmos11121367 - 17 Dec 2020

Cited by 30 | Viewed by 4949

Abstract

The effects of climate change on landslide activity may have important environmental, socio-economic, and political consequences. In the last decades, several short-term extreme rainfall events affected Mediterranean regions, resulted in damaging geo-hydrological processes and casualties. It is unequivocal that the impact of landslides [...] Read more.

The effects of climate change on landslide activity may have important environmental, socio-economic, and political consequences. In the last decades, several short-term extreme rainfall events affected Mediterranean regions, resulted in damaging geo-hydrological processes and casualties. It is unequivocal that the impact of landslides in several Mediterranean countries is increasing with time, but until now, there has been little or no quantitative data to support these increases. In this paper, both rainfall conditions for the occurrence of shallow landslides and rainfall trends were investigated in the Portofino promontory, which extends in the Ligurian Sea, where heavy rainfall and related ground effects often occur. Adopting a frequentist approach, the empirical intensity-duration threshold was estimated. Our findings highlight that the rainfall intensity required to trigger landslides is lower for the same duration than those expected in other similar environments, suggesting a high susceptibility to rainfall-induced landslides in the Portofino territory. Further, the Mann-Kendall test and Hurst exponent were used for detecting potential trends. Analysis of long-term rainfall time series showed statistically significant increasing trends in short duration precipitation occurrence and rainfall rates, suggesting a possible future scenario with a more frequent exceedance of the threshold triggering value and an increase of landslide risk. Full article

(This article belongs to the Special Issue Geo-Hydrological Extreme Events in the Mediterranean and Black Sea Areas)

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16 pages, 2176 KiB

Open AccessArticle

Pollution Caused by Potentially Toxic Elements Present in Road Dust from Industrial Areas in Korea

by Hyeryeong Jeong, Jin Young Choi, Jaesoo Lim and Kongtae Ra

Atmosphere 2020, 11(12), 1366; https://doi.org/10.3390/atmos11121366 - 17 Dec 2020

Cited by 16 | Viewed by 3509

Abstract

We examined the pollution characteristics of potentially toxic elements (PTEs) in road dust (RD) from nine industrial areas in South Korea to assess PTE pollution levels and their environmental risks for devising better strategies for managing RD. The median concentrations (mg/kg) were in [...] Read more.

We examined the pollution characteristics of potentially toxic elements (PTEs) in road dust (RD) from nine industrial areas in South Korea to assess PTE pollution levels and their environmental risks for devising better strategies for managing RD. The median concentrations (mg/kg) were in the order Zn (1407) > Cr (380) > Cu (276) > Pb (260) > Ni (112) > As (15) > Cd (2) > Hg (0.1). The concentration of PTEs was the highest at the Onsan Industrial Complex, where many smelting facilities are located. Our results show that Onsan, Noksan, Changwon, Ulsan, Pohang, and Shihwa industrial areas are heavily polluted with Cu, Zn, Cd, and Pb. The presence of these toxic elements in RD from the impervious layer in industrial areas may have a moderate to severe effect on the health of the biota present in these areas. The potential ecological risk index (

E_{r}^{i}

) for PTEs was in the decreasing order of Cd > Pb > Hg > Cu > As > Zn > Ni > Cr, indicating that the dominant PTE causing ecological hazards is Cd owing to its high toxicity. Our research suggests the necessity for the urgent introduction of an efficient management strategy to reduce RD, which adds to coastal pollution and affects human health. Full article

(This article belongs to the Special Issue Road Dust in Urban and Industrial Environments: Sources, Pollutants, Impacts, and Management)

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17 pages, 2392 KiB

Open AccessArticle

Spatial Distribution, Source Apportionment, Ozone Formation Potential, and Health Risks of Volatile Organic Compounds over a Typical Central Plain City in China

by Kun He, Zhenxing Shen, Jian Sun, Yali Lei, Yue Zhang and Xin Wang

Atmosphere 2020, 11(12), 1365; https://doi.org/10.3390/atmos11121365 - 16 Dec 2020

Cited by 9 | Viewed by 3125

Abstract

The profiles, contributions to ozone formation, and associated health risks of 56 volatile organic compounds (VOCs) species were investigated using high time resolution observations from photochemical assessment monitoring stations (PAMs) in Luoyang, China. The daily averaged concentration of total VOCs (TVOCs) was 21.66 [...] Read more.

The profiles, contributions to ozone formation, and associated health risks of 56 volatile organic compounds (VOCs) species were investigated using high time resolution observations from photochemical assessment monitoring stations (PAMs) in Luoyang, China. The daily averaged concentration of total VOCs (TVOCs) was 21.66 ± 10.34 ppbv in urban areas, 14.45 ± 7.40 ppbv in suburbs, and 37.58 ± 13.99 ppbv in an industrial zone. Overall, the VOCs levels in these nine sites followed a decreasing sequence of alkanes > aromatics > alkenes > alkyne. Diurnal variations in VOCs exhibited two peaks at 8:00–9:00 and 19:00–20:00, with one valley at 23:00–24:00. Source apportionment indicated that vehicle and industrial emissions were the dominant sources of VOCs in urban and suburban sites. The industrial site displayed extreme levels, with contributions from petrochemical-related sources of up to 38.3%. Alkenes and aromatics displayed the highest ozone formation potentials because of their high photochemical reactivity. Cancer and noncancer risks in the industrial site were higher than those in the urban and suburban areas, and USEPA possible risk thresholds were reached in the industrial site, indicating PAMs VOC–related health problems cannot be ignored. Therefore, vehicle and industrial emissions should be prioritized when considering VOCs and O₃ control strategies in Luoyang. Full article

(This article belongs to the Special Issue Physicochemistry of Indoor and Outdoor Particulate Matter and Health Effects)

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19 pages, 1983 KiB

Open AccessArticle

Impact of Environmental Conditions on Grass Phenology in the Regional Climate Model COSMO-CLM

by Eva Hartmann, Jan-Peter Schulz, Ruben Seibert, Marius Schmidt, Mingyue Zhang, Jürg Luterbacher and Merja H. Tölle

Atmosphere 2020, 11(12), 1364; https://doi.org/10.3390/atmos11121364 - 16 Dec 2020

Cited by 3 | Viewed by 3359

Abstract

Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM [...] Read more.

Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM (CCLM) at three locations in Germany covering the period 1999 to 2015 in order to study the sensitivity of grass phenology to different environmental conditions by implementing a new phenology module. We provide new evidence that the annually-recurring standard phenology of CCLM is improved by the new calculation of leaf area index (LAI) dependent upon surface temperature, day length, and water availability. Results with the new phenology implemented in the model show a significantly higher correlation with observations than simulations with the standard phenology. The interannual variability of LAI improves the representation of vegetation in years with extremely warm winter/spring (e.g., 2007) or extremely dry summer (e.g., 2003) and shows a more realistic growth period. The effect of the newly implemented phenology on atmospheric variables is small but tends to be positive. It should be used in future applications with an extension on more plant functional types. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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Map (center) with the three experimental locations (Lindenberg, Linden, and Selhausen) surrounded by their (Selhausen—topleft, Linden—bottomleft, Lindenberg—right) climate diagrams (data from Reference [<a href="#B42-atmosphere-11-01364" class="html-bibr">42</a>], 1982–2012), where the monthly precipitation sums are marked with blue bars and the annual cycle of monthly mean temperatures is shown in red. Full article ">Figure 2
Leaf area index (LAI) satellite (dotted) and in-situ (solid lines) observations at Linden and Selhausen for the years shown in the legend on the left in different colors. In-situ measurements are only available for the given years and dates. At Linden, the shown simulated years are (except 1998) the same as the in-situ observations. At Selhausen, the six years of simulations before the in-situ observations are shown. The mean annual cycle of the satellite LAI for the given years is shown in black (–). Full article ">Figure 3
Mean (1999–2015) annual cycle of LAI. Results with the standard phenology(_old, –), with only the dependence on temperature implemented (_T, –), with the dependence on day length added (_TD, –), with the fully implemented new phenology (_TDW, –), and satellite observations (_Obs, –) are shown at the three experimental domains Lindenberg, Linden, and Selhausen. Full article ">Figure 4
Start of the growing season (SGS) in number of days for each year from 1999 to 2015 and each domain (Lindenberg, Linden, and Selhausen) for satellite observations (_Obs, –), the standard phenology simulations (_old, –), and the new phenology simulations (_TDW, –). Full article ">Figure 5
Annual cycle of LAI of the year 2003 with extremely dry summer (top) and the year 2007 with extremely warm spring (bottom) at Lindenberg (left), Linden (middle), and Selhausen (right). In black (–) are the satellite observations (_Obs) and in different colors the simulations with the standard phenology (_old, –), with only the dependence on temperature (_T, –), the dependence on temperature and day length (_TD, –), and with the new phenology (_TDW, –). Full article ">Figure 6
Mean diurnal cycle of latent heat flux during March 2007 and during July 2003 at Lindenberg for the simulations with the standard phenology (_old, –), the simulations with the new phenology (_TDW, –) and the observations (_Obs, –). Full article ">Figure 7
Heavy precipitation events with more than 20 mm per day (top) and very warm days within the 90 th Percentile of the observed maximum temperatures (bottom) in each year of the period 1999 to 2015 at Lindenberg, Linden and Selhausen for the HYRAS observations (_Obs, –), the simulations with the standard phenology (_old, –) and the simulations with the new phenology (_TDW, –). Full article ">

27 pages, 8504 KiB

Open AccessEditor’s ChoiceArticle

A Long-Term, 1-km Resolution Daily Meteorological Dataset for Modeling and Mapping Permafrost in Canada

by Yu Zhang, Budong Qian and Gang Hong

Atmosphere 2020, 11(12), 1363; https://doi.org/10.3390/atmos11121363 - 16 Dec 2020

Cited by 5 | Viewed by 4568

Abstract

Climate warming is causing permafrost thaw and there is an urgent need to understand the spatial distribution of permafrost and its potential changes with climate. This study developed a long-term (1901–2100), 1-km resolution daily meteorological dataset (Met1km) for modeling and mapping permafrost at [...] Read more.

Climate warming is causing permafrost thaw and there is an urgent need to understand the spatial distribution of permafrost and its potential changes with climate. This study developed a long-term (1901–2100), 1-km resolution daily meteorological dataset (Met1km) for modeling and mapping permafrost at high spatial resolutions in Canada. Met1km includes eight climate variables (daily minimum, maximum, and mean air temperatures, precipitation, vapor pressure, wind speed, solar radiation, and downward longwave radiation) and is suitable to drive process-based permafrost and other land-surface models. Met1km was developed based on four coarser gridded meteorological datasets for the historical period. Future values were developed using the output of a new Canadian regional climate model under medium-low and high emission scenarios. These datasets were downscaled to 1-km resolution using the re-baselining method based on the WorldClim2 dataset as spatial templates. We assessed Met1km by comparing it to climate station observations across Canada and a gridded monthly anomaly time-series dataset. The accuracy of Met1km is similar to or better than the four coarser gridded datasets. The errors in long-term averages and average seasonal patterns are small. The error occurs mainly in day-to-day fluctuations, thus the error decreases significantly when averaged over 5 to 10 days. Met1km, as a data generating system, is relatively small in data volume, flexible to use, and easy to update when new or improved source datasets are available. The method can also be used to generate similar datasets for other regions, even for the entire global landmass. Full article

(This article belongs to the Special Issue Climate Data for Agricultural Applications: Downscaling and Scenarios)

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19 pages, 591 KiB

Open AccessArticle

Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data

by David Stevens, Pedro M. A. Miranda, René Orth, Souhail Boussetta, Gianpaolo Balsamo and Emanuel Dutra

Atmosphere 2020, 11(12), 1362; https://doi.org/10.3390/atmos11121362 - 16 Dec 2020

Cited by 11 | Viewed by 3983

Abstract

The surface-atmosphere turbulent exchanges couple the water, energy and carbon budgets in the Earth system. The biosphere plays an important role in the evaporation process, and vegetation related parameters such as the leaf area index (LAI), vertical root distribution and stomatal resistance are [...] Read more.

The surface-atmosphere turbulent exchanges couple the water, energy and carbon budgets in the Earth system. The biosphere plays an important role in the evaporation process, and vegetation related parameters such as the leaf area index (LAI), vertical root distribution and stomatal resistance are poorly constrained due to sparse observations at the spatio-temporal scales at which land surface models (LSMs) operate. In this study, we use the Carbon Hydrology Tiled European Center for Medium-Range Weather Forecasts (ECMWF) Scheme for Surface Exchanges over Land (CHTESSEL) model and investigate the sensitivity of the simulated turbulent fluxes to these vegetation related parameters. Observed data from 17 FLUXNET towers were used to force and evaluate model simulations with different vegetation parameter configurations. The replacement of the current LAI climatology used by CHTESSEL, by a new high-resolution climatology, representative of the station’s location, has a small impact on the simulated fluxes. Instead, a revision of the root profile considering a uniform root distribution reduces the underestimation of evaporation during water stress conditions. Despite the limitations of using only one model and a limited number of stations, our results highlight the relevance of root distribution in controlling soil moisture stress, which is likely to be applicable to other LSMs. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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2 pages, 128 KiB

Open AccessEditorial

Special Issue Air Quality and Smoke Management

by Scott L. Goodrick

Atmosphere 2020, 11(12), 1361; https://doi.org/10.3390/atmos11121361 - 15 Dec 2020

Viewed by 1749

Abstract

The Atmosphere Special Issue “Special Issue Air Quality and Smoke Management” explores our ability to simulate wildland fire smoke events and the potential to link such modeling to future studies of human health impacts [...] Full article

(This article belongs to the Special Issue Air Quality and Smoke Management)

14 pages, 2106 KiB

Open AccessArticle

Evaluating Satellite Sounding Temperature Observations for Cold Air Aloft Detection

by Rebekah Esmaili, Nadia Smith, Mark Schoeberl and Chris Barnet

Atmosphere 2020, 11(12), 1360; https://doi.org/10.3390/atmos11121360 - 15 Dec 2020

Cited by 3 | Viewed by 2334

Abstract

Cold Air Aloft (CAA) can impact commercial flights when cold air descends below 12,192 m (40,000 ft) and temperatures drop dramatically. A CAA event is identified when air temperature falls below −65 °C, which decreases fuel efficiency and poses a safety hazard. This [...] Read more.

Cold Air Aloft (CAA) can impact commercial flights when cold air descends below 12,192 m (40,000 ft) and temperatures drop dramatically. A CAA event is identified when air temperature falls below −65 °C, which decreases fuel efficiency and poses a safety hazard. This manuscript assesses the performance of the National Oceanic and Atmospheric Administration Unique Combined Atmospheric Processing System (NUCAPS) in detecting CAA events using sounders on polar-orbiting satellites. We compare NUCAPS air temperature profiles with those from Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) for January–March 2018. Of 1311 collocated profiles, 236 detected CAA. Our results showed that NUCAPS correctly detects CAA in 48.1% of profiles, while 17.2% are false positives and 34.7% are false negatives. To identify the reason for these detection states, we used a logistic regression trained on NUCAPS diagnostic parameters. We found that cloud cover can impact the skill even at higher vertical levels. This work indicates that a CAA-specific quality flag is feasible and may be useful to help forecasters to diagnose NUCAPS in real-time. Furthermore, the inclusion of an additional sounder data source (e.g., NOAA-20) may increase CAA forecast accuracy. Cloud scenes change rapidly, so additional observations provide more opportunities for correct detection. Full article

(This article belongs to the Special Issue Weather and Aviation Safety)

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(a) Illustration of how the tropopause height is lower in the poles. (b) Flights are often diverted when widespread Cold Air Aloft (CAA) is present in the upper troposphere and lower stratosphere, which coincides with commercial flight zones in high latitudes. Air temperatures below −65 °C can cause water within the jet fuel to freeze and common fuels begins to form wax crystals, which can reduce fuel efficiency or pose a safety hazard. Full article ">Figure 2
Radiosonde temperature profiles from 14 Alaskan sites for February through March 2018. A total of 1180 profiles are shown. Radiosondes are released twice daily at 00 UTC and 12 UTC. Red points indicate where CAA is detected. The vertical layer between the two dashed lines in each plot shows the typical transpolar flight cruising altitudes, assuming a standard atmosphere. Full article ">Figure 3
A National Oceanic and Atmospheric Administration Unique Combined Atmospheric Processing System (NUCAPS) horizontal slice along the 200 hPa isobar on 26 February 2018 over the study domain, 40–80° N, 169° E–131° W. (a) Several combined overpasses between 1100 and 1700 UTC and (b) matchups between with Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) profiles within 150 km for the same time period. Blue coloring indicates where the air temperature is below 208 K (−65 °C) to distinguish the presence of a CAA event. Profiles annotated in (b) are shown in <a href="#atmosphere-11-01360-f004" class="html-fig">Figure 4</a>. Full article ">Figure 4
(a) NUCAPS profiles showing the matchups between COSMIC (black dashed line) and NUCAPS (blue solid lines), where the shaded blue box indicates the temperature and pressure criteria for CAA. The profile locations are annotated in <a href="#atmosphere-11-01360-f003" class="html-fig">Figure 3</a>. (b) The mean (solid line) and standard deviation (error bars) of the averaging kernel matrix (AKM) diagonal vectors are a function of pressure in the study domain on 26 February 2018. Full article ">Figure 5
Percentage of matchup profiles between January and March 2018 for the true positive, false positive, and false negative CAA detection states that are summarized in <a href="#atmosphere-11-01360-t001" class="html-table">Table 1</a>. Profiles categorized as true negative are the most numerous (N = 1026) but for clarity, are not shown. Full article ">Figure 6
Results for a logistic regression on diagnostic parameters for the four CAA detection states described in <a href="#atmosphere-11-01360-t001" class="html-table">Table 1</a>. X indicates diagnostic parameters that do not meet statistical significance requirements. Full article ">

2 pages, 147 KiB

Open AccessEditorial

Special Issue Editorial: Study of Brake Wear Particle Emissions

by Jens Wahlström

Atmosphere 2020, 11(12), 1359; https://doi.org/10.3390/atmos11121359 - 15 Dec 2020

Cited by 2 | Viewed by 1808

Abstract

n/a Full article

(This article belongs to the Special Issue Study of Brake Wear Particle Emissions)

31 pages, 2404 KiB

Open AccessReview

Radiation in the Atmosphere—A Hazard to Aviation Safety?

by Matthias M. Meier, Kyle Copeland, Klara E. J. Klöble, Daniel Matthiä, Mona C. Plettenberg, Kai Schennetten, Michael Wirtz and Christine E. Hellweg

Atmosphere 2020, 11(12), 1358; https://doi.org/10.3390/atmos11121358 - 14 Dec 2020

Cited by 26 | Viewed by 9452

Abstract

Exposure of aircrew to cosmic radiation has been recognized as an occupational health risk for several decades. Based on the recommendations by the International Commission on Radiological Protection (ICRP), many countries and their aviation authorities, respectively have either stipulated legal radiation protection regulations, [...] Read more.

Exposure of aircrew to cosmic radiation has been recognized as an occupational health risk for several decades. Based on the recommendations by the International Commission on Radiological Protection (ICRP), many countries and their aviation authorities, respectively have either stipulated legal radiation protection regulations, e.g., in the European Union or issued corresponding advisory circulars, e.g., in the United States of America. Additional sources of ionizing and non-ionizing radiation, e.g., due to weather phenomena have been identified and discussed in the scientific literature in recent years. This article gives an overview of the different generally recognized sources due to weather as well as space weather phenomena that contribute to radiation exposure in the atmosphere and the associated radiation effects that might pose a risk to aviation safety at large, including effects on human health and avionics. Furthermore, potential mitigation measures for several radiation sources and the prerequisites for their use are discussed. Full article

(This article belongs to the Special Issue Weather and Aviation Safety)

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The radiation field at aviation altitudes is created in repeated interactions of the primary and secondary radiation with the constituents of the atmosphere. Full article ">Figure 2
Variations of the effective dose rate over time (a) and the dependency on the magnetic shielding expressed by the cut-off rigidity RC (b) at 29,000 ft. and 41,000 ft. during solar minimum (dose rates are calculated with the PANDOCA model [<a href="#B29-atmosphere-11-01358" class="html-bibr">29</a>]). Full article ">Figure 3
Model predicted GCR total neutron fluence rate dependence on the altitude from PANDOCA [<a href="#B22-atmosphere-11-01358" class="html-bibr">22</a>] (black solid line) and CARI-7 [<a href="#B25-atmosphere-11-01358" class="html-bibr">25</a>] (black dashed line) and for neutron energies greater than 10 MeV from PANDOCA (grey line) without geomagnetic shielding (RC = 0 GV) during solar minimum. Full article ">Figure 4
Dose rates and accumulated doses were calculated for the altitude of 41,000 ft. (FL410) and locations at 90° N 0° for GLE42 and 70° N 50° E for GLE70, respectively. Full article ">Figure 5
D-Scale for aviation with Space Weather D-Indices from 0 to 5. Full article ">

21 pages, 2674 KiB

Open AccessArticle

Air Pollution Measurements and Land-Use Regression in Urban Sub-Saharan Africa Using Low-Cost Sensors—Possibilities and Pitfalls

by Asmamaw Abera, Kristoffer Mattisson, Axel Eriksson, Erik Ahlberg, Geremew Sahilu, Bezatu Mengistie, Abebe Genetu Bayih, Abraham Aseffaa, Ebba Malmqvist and Christina Isaxon

Atmosphere 2020, 11(12), 1357; https://doi.org/10.3390/atmos11121357 - 14 Dec 2020

Cited by 18 | Viewed by 5020

Abstract

Air pollution is recognized as the most important environmental factor that adversely affects human and societal wellbeing. Due to rapid urbanization, air pollution levels are increasing in the Sub-Saharan region, but there is a shortage of air pollution monitoring. Hence, exposure data to [...] Read more.

Air pollution is recognized as the most important environmental factor that adversely affects human and societal wellbeing. Due to rapid urbanization, air pollution levels are increasing in the Sub-Saharan region, but there is a shortage of air pollution monitoring. Hence, exposure data to use as a base for exposure modelling and health effect assessments is also lacking. In this study, low-cost sensors were used to assess PM2.5 (particulate matter) levels in the city of Adama, Ethiopia. The measurements were conducted during two separate 1-week periods. The measurements were used to develop a land-use regression (LUR) model. The developed LUR model explained 33.4% of the variance in the concentrations of PM2.5. Two predictor variables were included in the final model, of which both were related to emissions from traffic sources. Some concern regarding influential observations remained in the final model. Long-term PM2.5 and wind direction data were obtained from the city’s meteorological station, which should be used to validate the representativeness of our sensor measurements. The PM2.5 long-term data were however not reliable. Means of obtaining good reference data combined with longer sensor measurements would be a good way forward to develop a stronger LUR model which, together with improved knowledge, can be applied towards improving the quality of health. A health impact assessment, based on the mean level of PM2.5 (23 µg/m³), presented the attributable burden of disease and showed the importance of addressing causes of these high ambient levels in the area. Full article

(This article belongs to the Special Issue Challenges in Measuring and Assessing Environmental Health)

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The location of Adama on the East African continent and the selected classes of variables for the land-use regression (LUR) model. Full article ">Figure 2
Time series of particulate matter (PM2.5) were obtained by changing the positions of 5 sensors such that 20 sites were sampled during the campaign (see <a href="#sec2dot2-atmosphere-11-01357" class="html-sec">Section 2.2</a> and <a href="#sec4dot2-atmosphere-11-01357" class="html-sec">Section 4.2</a> for details). For comparison see <a href="#app1-atmosphere-11-01357" class="html-app">Figure S3</a> in which sensors were not moved. Full article ">Figure 3
Original classes for road type in open street maps were reclassified to seven classes. Full article ">Figure 4
Road distribution for all road types included in Adama and measurement sites locations. Full article ">Figure 5
A 4-day time series measured by Purple Air illustrating the typical diurnal pattern, with elevated levels during early morning and late afternoon rush hours, seen throughout the Adama measurement sites. Full article ">Figure 6
Frequency of wind direction for 2018–2019 during (a) the dry season, and (b) the wet season. Full article ">

12 pages, 3756 KiB

Open AccessArticle

The Lagged Effect of Anthropogenic Aerosol on East Asian Precipitation during the Summer Monsoon Season

by Su-Jung Lee, Yong-Cheol Jeong and Sang-Wook Yeh

Atmosphere 2020, 11(12), 1356; https://doi.org/10.3390/atmos11121356 - 14 Dec 2020

Cited by 2 | Viewed by 2899

Abstract

The authors investigated the lagged effect of anthropogenic aerosols (AAs) during the premonsoon season (April–May–June) on the East Asian precipitation during the postmonsoon season (July–August) using the aerosol optical depth (AOD) from a satellite dataset and reanalysis datasets. When the AOD is high [...] Read more.

The authors investigated the lagged effect of anthropogenic aerosols (AAs) during the premonsoon season (April–May–June) on the East Asian precipitation during the postmonsoon season (July–August) using the aerosol optical depth (AOD) from a satellite dataset and reanalysis datasets. When the AOD is high in Eastern China during the premonsoon season, the amount of precipitation increases in the western North Pacific, including the Korean Peninsula and Japan, during the postmonsoon season. The amount of cloud in the western-to-central North Pacific in the premonsoon season increases during the high-AOD period. Subsequently, it cools the sea surface temperature until the postmonsoon season, which strengthens the North Pacific High. The strengthened North Pacific High in the postmonsoon season expands to the western North Pacific, which leads to the enhancement of the moisture flows from the ocean. This results in the increase in precipitation in the western North Pacific, including the Korean Peninsula and Japan, during the postmonsoon season. Full article

(This article belongs to the Special Issue Aerosol-Climate Interaction)

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(a) Distribution of climatological (2000–2017) aerosol optical depth (AOD). The green box indicates the East Asian region (110.5–122.5° E, 22.5–40.5° N), where AOD is the highest. (b) The black line denotes time series data of the AOD index, averaged over the green box area shown in (a). The blue line denotes normalized time series data with the linear trend removed from the black line. (c) The composite difference of AOD during April–May–June (AMJ; high AOD minus low AOD). Regions with black cross-hatching indicate a statistical significance at a 95% confidence level. Full article ">Figure 2
The composite difference between high AOD and low AOD of (a) AMJ cloud fraction (CF), (b) AMJ surface net solar radiation (SSRD; 10−7 J/m2), and (c) AMJ surface air temperature (SAT; ℃). Regions with black cross-hatching indicate a statistical significance at a 95% confidence level. Solid black lines denote the climatological (2000–2017) mean. Full article ">Figure 3
The difference (high AOD minus low AOD) of composited precipitation from the Global Precipitation Climatology Project (GPCP) between the high AOD and the low AOD in July–August (JA). Regions with a red dot indicate a statistical significance at a 95% confidence level. The unit is mm/day. Full article ">Figure 4
The composite difference between high AOD and low AOD of (a) JA surface air temperature (SAT; ℃), (b) JA sea level pressure (SLP; hPa), (c) JA wind speed (shading) (m/s) and moisture transport (vector) (kg*m/s), and (d) JA latent heat flux (10−6 J/m2). Regions with black cross-hatching indicate a statistical significance at a 95% confidence level. Solid black lines denote the climatological (2000–2017) mean. Full article ">Figure 5
The composite difference of AOD during JA (high AOD minus low AOD). Regions with black cross-hatching indicate a statistical significance at a 95% confidence level. Full article ">Figure 6
Schematic diagram showing the process through which AA variability in AMJ affects precipitation in JA. Full article ">

12 pages, 10892 KiB

Open AccessEditor’s ChoiceArticle

Air Pollution and Long Term Mental Health

by Younoh Kim, James Manley and Vlad Radoias

Atmosphere 2020, 11(12), 1355; https://doi.org/10.3390/atmos11121355 - 14 Dec 2020

Cited by 28 | Viewed by 5136

Abstract

We study the long-term consequences of air pollution on mental health, using a natural experiment in Indonesia. We find that exposure to severe air pollution has significant and persistent consequences on mental health. An extra standard deviation in the pollution index raises the [...] Read more.

We study the long-term consequences of air pollution on mental health, using a natural experiment in Indonesia. We find that exposure to severe air pollution has significant and persistent consequences on mental health. An extra standard deviation in the pollution index raises the probability of clinical depression measured 10 years past exposure by almost 1%. Women in particular seem to be more affected, but some effects persist for men as well. Pollution exposure increases the likelihood of clinical depression for women and also the severity of depressive symptoms for both sexes. It is not clear if men are more resistant to pollution or they simply recover faster from it. Education, perceived economic status, and marriage seem to be the best mitigators for these negative effects. Full article

(This article belongs to the Special Issue Contributions of Aerosol Sources to Health Impacts)

24 pages, 6405 KiB

Open AccessArticle

Effect of Various Types of ENSO Events on Moisture Conditions in the Humid and Subhumid Tropics

by Daria Gushchina, Irina Zheleznova, Alexander Osipov and Alexander Olchev

Atmosphere 2020, 11(12), 1354; https://doi.org/10.3390/atmos11121354 - 13 Dec 2020

Cited by 17 | Viewed by 3848

Abstract

Moisture anomaly conditions within humid and subhumid tropics that are associated with different types of El Niño and La Niña phenomena are described and analyzed with a focus on their spatial distribution and seasonal variability. Five dryness indices (Keetch–Byram Drought Index, Weighted Anomaly [...] Read more.

Moisture anomaly conditions within humid and subhumid tropics that are associated with different types of El Niño and La Niña phenomena are described and analyzed with a focus on their spatial distribution and seasonal variability. Five dryness indices (Keetch–Byram Drought Index, Weighted Anomaly Standardized Precipitation Index, Standardized Precipitation Index, Palmer Drought Severity Index, and Percent of Normal Precipitation) were derived from ECMWF (European Centre for Medium-Range Weather Forecasts) fifth generation reanalysis (ERA5) reanalysis and University Corporation for Atmospheric Research (UCAR) datasets for the period from 1979 to 2019. Cross-correlation analysis was used to evaluate the relationships between the El Niño Southern Oscillation (ENSO) and selected dryness indices. To describe the seasonal variability of the ENSO–surface moisture relationships, the composite maps of dryness indices in different seasons were analyzed. The results showed a significant heterogeneity of the ENSO-induced moisture anomaly conditions both within and across various geographical regions. Four main areas in humid and subhumid tropics with the maximum effects of El Niño/La Niña events on the surface moisture conditions were found: Southeast Asia and Australia, Eastern and South Africa, Northeastern and Eastern South America, and Central America. It was shown that the effects of La Niña were usually opposite to those of El Niño, while the responses to the two types of El Niño differed mostly in the moisture anomaly intensity and its spatial patterns. Full article

(This article belongs to the Special Issue Response of Boreal and Tropical Forest Ecosystems to Extreme Weather Events)

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16 pages, 3167 KiB

Open AccessArticle

Farming Practices for Reducing Ammonia Emissions in Polish Agriculture

by Arkadiusz Piwowar

Atmosphere 2020, 11(12), 1353; https://doi.org/10.3390/atmos11121353 - 13 Dec 2020

Cited by 11 | Viewed by 3736

Abstract

The main source of ammonia emissions in Poland is agriculture. In 2017, approximately 94% of the total ammonia emissions in Poland came from agriculture, of which the largest part (78%) was related to livestock manure and 22% to nitrogen fertilization. This study presents [...] Read more.

The main source of ammonia emissions in Poland is agriculture. In 2017, approximately 94% of the total ammonia emissions in Poland came from agriculture, of which the largest part (78%) was related to livestock manure and 22% to nitrogen fertilization. This study presents the results of representative research on the implementation of technologies and techniques that reduce ammonia emissions on farms in Poland. The research methodology, including statistical data analysis (multiple correspondence analysis), allowed comparisons to be made of the applied low-carbon practices, taking into account farmers’ characteristics (e.g., age and education) and farm attributes (area size, location, etc.). According to the research, both in the case of mineral fertilization and animal production, farmers in Poland relatively rarely undertake pro-ecological practices aimed at reducing ammonia emissions. The most frequently undertaken activities include dividing the doses of nitrogen fertilizers (in terms of plant production) and the use of feed additives (in terms of livestock production). Empirical studies, supported by correspondence analyses, confirmed a significant differentiation of coexistence and strength of the relationship between the studied variables. The use of correspondence analysis made it possible to precisely recognize the differentiation and co-occurrence of variable categories. In the course of analytical work, a relatively strong correlation was found between the use of divided doses of nitrogen fertilizers and the economic size of farms (φ² = 0.11571). In turn, the use of feed additives was most strongly determined by the economic size of farms (φ² = 0.072614) and the location of farms (φ² = 0.072223). Full article

(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)

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Main food producing areas in Poland and spatial extent of field studies [<a href="#B37-atmosphere-11-01353" class="html-bibr">37</a>]. Full article ">Figure 2
Declarations of respondents engaged in plant production on the methods of reducing ammonia emissions. Source: own study based on questionnaire surveys (n = 1034) Full article ">Figure 3
Declarations of respondents engaged in livestock production on the methods of reducing ammonia emissions. Source: own study based on questionnaire surveys (n = 520). Full article ">Figure 4
Graphical presentation of the results of the correspondence analysis between the declarations of sharing nitrogen fertilizer doses with the researched characteristics of farmers and farms. Source: own study based on questionnaire surveys (n = 1034). Full article ">Figure 5
Graphical presentation of the results of the correspondence analysis between the declarations of using appropriately selected feed additives with the tested characteristics of farmers and farms. Source: own study based on questionnaire surveys (n = 520). Full article ">Figure 5 Cont.
Graphical presentation of the results of the correspondence analysis between the declarations of using appropriately selected feed additives with the tested characteristics of farmers and farms. Source: own study based on questionnaire surveys (n = 520). Full article ">

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