Search Results (914)

Agriculture crop residue burning has become a major environmental problem facing the Indo-Gangetic plain, as well as contributing to global warming. This paper reports the results of a comprehensive study, examining the variations in aerosol optical, microphysical, and radiative properties that occur during biomass-burning events at Amity University Haryana (AUH), at a rural station in Gurugram (Latitude: 28.31° N, Longitude: 76.90° E, 285 m AMSL), employing ground-based observations of AERONET and Aethalometer, as well as satellite and model simulations during 7–16 November 2021. The smoke emissions during the burning events enhanced the aerosol optical depth (AOD) and increased the Angstrom exponent (AE), suggesting the dominance of fine-mode aerosols. A smoke event that affected the study region on 11 November 2021 is simulated using the regional NAAPS model to assess the role of smoke in regional aerosol loading that caused an atmospheric forcing of 230.4 W/m². The higher values of BC (black carbon) and BB (biomass burning), and lower values of AAE (absorption Angstrom exponent) are also observed during the peak intensity of the smoke-event period. A notable layer of smoke has been observed, extending from the surface up to an altitude of approximately 3 km. In addition, the observations gathered from CALIPSO regarding the vertical profiles of aerosols show a qualitative agreement with the values obtained from AERONET observations. Further, the smoke plumes that arose due to transport of a wide-spread agricultural crop residue burning are observed nationwide, as shown by MODIS imagery, and HYSPLIT back trajectories. Thus, the present study highlights that the smoke aerosol emissions during crop residue burning occasions play a critical role in the local/regional aerosol microphysical and radiation properties, and hence in the climate variability. Full article

The application value of low-quality photos taken in foggy conditions is significantly lower than that of clear images. As a result, restoring the original image information and enhancing the quality of damaged images on cloudy days are crucial. Commonly used deep learning techniques like DehazeNet, AOD-Net, and Li have shown encouraging progress in the study of image dehazing applications. However, these methods suffer from a shallow network structure leading to limited network estimation capability, reliance on atmospheric scattering models to generate the final results that are prone to error accumulation, as well as unstable training and slow convergence. Aiming at these problems, this paper proposes an improved end-to-end convolutional neural network method based on the denoising self-encoder-DenseNet (DAE-DenseNet), where the denoising self-encoder is used as the main body of the network structure, the encoder extracts the features of haze images, the decoder performs the feature reconstruction to recover the image, and the boosting module further performs the feature fusion locally and globally, and finally outputs the dehazed image. Testing the defogging effect in the public dataset, the PSNR index of DAE-DenseNet is 22.60, which is much higher than other methods. Experiments have proved that the dehazing method designed in this paper is better than other algorithms to a certain extent, and there is no color oversaturation or an excessive dehazing phenomenon in the image after dehazing. The dehazing results are the closest to the real image and the viewing experience feels natural and comfortable, with the image dehazing effect being very competitive. Full article

In recent years, northeastern Iran, particularly Khorasan Razavi province, has experienced wind erosion and dust storms, although large-scale studies are limited. To assess wind patterns, sand drift, and dust events, hourly wind data were analyzed using Fryberger’s method, along with trend analysis through the Mann–Kendall and Sen’s slope tests. Additionally, MODIS satellite data and Google Earth Engine helped identify event frequency and spatial patterns. The results show that east (12%) and southeast winds (9.6%) are the most frequent, with an average annual wind speed of 4.39 knots. Sand drift potential (DP = 96, RDP = 21.6) indicates sand movement from southeast to northwest, with a multi-directional wind system (unidirectional index of 0.22). The results of the AOD index show that the amount of dust in the north and northwest part is more than other locations, and more than 500 events with dust has been registered over the last two decades. These findings suggest that policymakers should monitor these trends to mitigate the environmental and infrastructural damage caused by blowing sand. Full article

The Brazilian Pantanal region experiences intense biomass burning during the dry season, releasing large quantities of gasses and particles into the atmosphere, which have serious implications on both the climate system and public health. Understanding the dynamics of these emissions is crucial for mitigating the impact on the ecosystem, its functioning, and potential anthropogenic disturbances. This study focused on analyzing emissions in the northern Pantanal during the 2022 drought. Concentrations of fine particulate matter (PM_2.5), black carbon (BC), and 25 chemical elements were measured using gravimetry, reflectance analysis, and X-Ray fluorescence, respectively, from samples collected between August and October 2022. The average concentrations of PM_2.5 and BC increased approximately 4-fold and 2.5-fold, respectively, compared to averages from a decade ago. Significant increases were also observed in elements such as sulfur (S), potassium (K), iron (Fe), and silicon (Si). The maximum concentrations were comparable to values typical of the southern Amazon, a region known for high deforestation rates and land use changes. Elemental analysis revealed substantial shifts in concentrations, primarily associated with biomass burning (BB) and soil suspension. Additionally, enrichment factor (Ef) analysis showed that lead (Pb) levels, correlated with human activities, were 200 times higher than those found under clean atmospheric conditions. Full article

The urban heat island (UHI) effect is one of the most prominent surface climate changes driven by human activities. This study examines the UHI characteristics and influencing factors in the Southern Xinjiang urban agglomeration using MODIS satellite data combined with observational datasets. Our results reveal a significant increase in impervious surfaces in the region between 1995 and 2015, with the most rapid expansion occurring from 2010 to 2015. This urban expansion is the primary driver of changes in UHI intensity. The analysis from 2000 to 2015 shows substantial spatial variation in UHI effects across cities. Hotan recorded the highest annual average daytime UHI intensity of 3.7 °C, while Aksu exhibited the lowest at approximately 1.6 °C. Daytime UHI intensity generally increased during the study period, with the highest intensities observed in the summer. However, nighttime UHI trends varied across cities, with most showing an increase in intensity. Temperature, precipitation, and aerosol optical depth (AOD) were identified as the main factors influencing annual average daytime UHI intensity, while PM10 concentration showed a weak and inconsistent correlation with UHI intensity, varying by city and season. Full article

The purpose of this study was to fully explore the mechanical properties of five different doses of an Argon–Oxygen Decarburization slag mixture in an unconfined compressive strength test. The peak stress, elastic modulus, and stress–strain curve of the mixture were studied for 90 days. Based on the experimental data and according to the theory of damage mechanics, the concept of damage threshold (t) was introduced to construct a damage constitutive model. Referring to the damage threshold of concrete, that of the mixture was determined to be 0.7 times higher than the peak strain, and the correlation coefficient between the established model and the test curve was above 0.85. These results indicate that the addition of AOD slag and fly ash can cause hydration reactions, increase the quantity of hydration products, and enhance the peak stress and elastic modulus of the mixture. The maximum increases were 94.9% and 43.1%, respectively. Parameters a and b reflect the peak stress and brittleness of the mixture, respectively. The incorporation of Argon–Oxygen Decarburization slag can make the mixture less brittle and improve its properties. The incorporation of Argon–Oxygen Decarburization slag can protect the mixture from damage. The maximum decrease is 40.2%. Full article

Investigating the spatiotemporal variations in Aerosol Optical Depth (AOD) in terrestrial ecosystems and their driving factors is significant for deepening our understanding of the relationship between ecosystem types and aerosols. This study utilized 1 km resolution AOD data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Mann–Kendall (M-K) trend test to analyze the spatiotemporal variations in AOD in seven ecosystems in Northern Xinjiang from 2001 to 2023. The geographic detector model was employed to investigate the effects of driving factors, including gross domestic product, population density, specific humidity, precipitation, temperature, wind speed, soil moisture, and elevation, on the distribution of AOD in the ecosystems. The results indicate that over the past 23 years, wetlands had the highest annual average AOD values, followed by settlements, farmlands, deserts, grasslands, others, and forests, respectively. Furthermore, the AOD values decrease with increasing ecosystem elevation. The annual mean of AOD in Northern Xinjiang generally shows a fluctuating upward trend. The M-K test shows that the proportion of area with an increasing trend in AOD in the settlement ecosystems is the highest (92.17%), while the proportion of area with a decreasing trend in the forest ecosystem is the highest (21.78%). On a seasonal scale, grassland, settlement, farmland, forest, and wetland ecosystems exhibit peak values in spring and winter, whereas desert and other ecosystems only show peaks in spring. Different types of ecosystems show different sensitivities to driving factors. Grassland and forest ecosystems are primarily influenced by temperature and altitude, while desert and settlement ecosystems are most affected by wind speed and humidity. Farmlands are mainly influenced by wind speed and altitude, wetlands are significantly impacted by population density and humidity, and other ecosystems are predominantly affected by humidity and altitude. This paper serves as a reference for targeted air pollution prevention and regional ecological environmental protection. Full article

Background/objectives: The way in which topics like suicide, mental health concerns and alcohol and other drug use are communicated matters. It has the potential to have either a positive or negative impact on people and communities, particularly those with a lived experience of these concerns. This article draws on the findings of a qualitative study designed to explore the experiences and perceptions of stakeholders on the imagery and language used to depict suicide, mental health concerns or alcohol and other drug use. Methods: The focus group method was used as a form of participatory action research to gain an in-depth understanding of the experiences and views of those who use or are impacted by language and imagery about suicide, mental ill-health and AOD use, including those with lived experiences of these topics. Results: A series of 10 focus groups were created in February and March 2022 with media and other professional communicators; people identifying as having a lived experience of suicide, mental ill-health or alcohol and other drug use; mental health and suicide prevention sector professionals; and people from priority populations (n = 49). From these focus groups, principles were developed as well as exemplars of helpful and less helpful depictions. Rather than prescriptive or static rules, the participants indicated that safe representations require an ongoing engagement with the principle of “do no harm”. Conclusions: A positive conclusion arose—that words and images have the potential to promote help-seeking, challenge stigma or stereotypes and create change. Full article

The use of satellite data to estimate PM_2.5 is an appropriate approach for long-term, substantial monitoring and assessment. To estimate PM_2.5, the majority of the algorithms now in use utilize the top-of-atmosphere (TOA) reflectance or aerosol optical depth (AOD) derived from scalar satellite data. However, there is relatively little research on the retrieval of PM_2.5 using multi-angle polarized data. With its directional polarimetric camera (DPC), the Chinese new-generation satellite Gaofen 5B (henceforth referred to as GF-5B) offers a unique opportunity to close this gap in multi-angle polarized observation data. In this research, we utilized TOA data from the DPC payload and applied the gradient boosting machine method to simulate the impact of the observation angle, wavelength, and polarization information on the accuracy of PM_2.5 retrieval. We identified the optimal conditions for the effective estimation of PM_2.5. The quantitative results indicated that, under these optimal conditions, the PM_2.5 concentrations retrieved by GF-5B showed a strong correlation with the ground-based data, achieving an R² of 0.9272 and an RMSE of 7.38 µg·m⁻³. By contrast, Himawari-8’s retrieval accuracy under similar data conditions consisted of an R² of 0.9099 and RMSE of 7.42 µg·m⁻³, indicating that GF-5B offers higher accuracy. Furthermore, the retrieval results in this study demonstrated an R² of 0.81 when compared to the CHAP dataset, confirming the feasibility and effectiveness of the use of GF-5B for PM_2.5 retrieval and providing support for PM_2.5 estimation through multi-angle polarized data. Full article

This paper investigates the impact of air quality and climate variability during the first wave of COVID-19 associated with accelerated transmission and lethality in Wuhan in China and four European metropolises (Milan, Madrid, London, and Bucharest). For the period 1 January–15 June 2020, including the COVID-19 pre-lockdown, lockdown, and beyond periods, this study used a synergy of in situ and derived satellite time-series data analyses, investigating the daily average inhalable gaseous pollutants ozone (O₃), nitrogen dioxide (NO₂), and particulate matter in two size fractions (PM2.5 and PM10) together with the Air Quality Index (AQI), total Aerosol Optical Depth (AOD) at 550 nm, and climate variables (air temperature at 2 m height, relative humidity, wind speed, and Planetary Boundary Layer height). Applied statistical methods and cross-correlation tests involving multiple datasets of the main air pollutants (inhalable PM2.5 and PM10 and NO₂), AQI, and aerosol loading AOD revealed a direct positive correlation with the spread and severity of COVID-19. Like in other cities worldwide, during the first-wave COVID-19 lockdown, due to the implemented restrictions on human-related emissions, there was a significant decrease in most air pollutant concentrations (PM2.5, PM10, and NO₂), AQI, and AOD but a high increase in ground-level O₃ in all selected metropolises. Also, this study found negative correlations of daily new COVID-19 cases (DNCs) with surface ozone level, air temperature at 2 m height, Planetary Boundary PBL heights, and wind speed intensity and positive correlations with relative humidity. The findings highlight the differential impacts of pandemic lockdowns on air quality in the investigated metropolises. Full article

The demand for clean and sustainable energy has led to the exploration of innovative technologies for renewable energy generation. The Savonius turbine has emerged as a promising solution for harnessing wind energy in urban environments due to its unique design, simplicity, structural stability, and ability to capture wind energy from any direction. However, the efficiency of Savonius turbines poses a challenge that affects their overall performance. Extensive research efforts have been dedicated to enhancing their efficiency and optimizing their performance in urban settings. For instance, an axisymmetric omnidirectional deflector (AOD) was introduced to improve performance in all wind directions. Despite these advancements, the effect of wind incident angles on Savonius turbine performance has not been thoroughly investigated. This study aims to fill this knowledge gap by examining the performance of standard Savonius configurations (STD) compared to the basic configuration of the deflector (AOD1) and to the optimized one (AOD2) under different wind incident angles and wind speeds. One key finding was the consistent superior performance of this AOD2 configuration across all incident angles and wind speeds. It consistently outperformed the other configurations, demonstrating its potential as an optimized configuration for wind turbine applications. For instance, at an incident angle of 0°, the power coefficient of the configuration of AOD2 was 61% more than the STD configuration. This ratio rose to 88% at an incident angle of 20° and 125% at an incident angle of 40°. Full article

Global dust events have become more frequent due to climate change and increased human activity, significantly impacting air quality and human health. Previous studies have mainly focused on determining atmospheric dust pollution levels through atmospheric parameter simulations or AOD values obtained from satellite remote sensing. However, research on the quantitative description of dust intensity and its cross-regional transport characteristics still faces numerous challenges. Therefore, this study utilized Fengyun-4A (FY-4A) satellite Advanced Geostationary Radiation Imager (AGRI) imagery, Cloud-Aerosol Lidar, and Infrared Pathfinder Satellite Observation (CALIPSO) lidar, and other auxiliary data, to conduct three-dimensional spatiotemporal monitoring and a cross-regional transport analysis of two typical dust events in the Beijing–Tianjin–Hebei (BTH) region of China using four dust intensity indices Infrared Channel Shortwave Dust (Icsd), Dust Detection Index (DDI), dust value (DV), and Dust Strength Index (DSI)) and the HYSPLIT model. We found that among the four indices, DDI was the most suitable for studying dust in the BTH region, with a detection accuracy (POCD) of >88% at all times and reaching a maximum of 96.14%. Both the 2021 and 2023 dust events originated from large-scale deforestation in southern Mongolia and the border area of Inner Mongolia, with dust plumes distributed between 2 and 12 km being transported across regions to the BTH area. Further, when dust aerosols are primarily concentrated below 4 km and PM10 concentrations consistently exceed 600 µg/m³, large dust storms are more likely to occur in the BTH region. The findings of this study provide valuable insights into the sources, transport pathways, and environmental impacts of dust aerosols. Full article

American Oyster Defensin (AOD) is a marine peptide that is derived from North American mussels. It has been demonstrated to exhibit potent antimicrobial activity and high safety in both in vitro and in vivo models. In this study, to facilitate synthesis, mutants of AOD with fewer disulfide bonds were designed and subjected to structural, antimicrobial, and anti-biofilm analysis. The antimicrobial activity of AOD-derived peptides decreased after reduction in the disulfide bond, and among its three derivatives, only AOD-1 inhibited very few bacteria with a MIC value of 64 μg/mL, whereas the others had no inhibitory effect on pathogenic bacteria. The findings demonstrated that full disulfide bonds are indispensable for bactericidal activity, with the α-helix playing a pivotal role in inhibiting bacterial membranes. Furthermore, the results of the ATP, ROS, membrane potential, and membrane fluidity assays demonstrated that intracellular ATP, reactive oxygen species, and membrane fluidity were all increased, while membrane potential was reduced. This indicated that AOD resulted in the impairment of membrane fluidity and induced metabolic disorders, ultimately leading to bacterial death. The inhibitory effect of AOD on the biofilm of S. epidermidis G-81 was determined through the crystal violet and confocal microscopy. The results demonstrated that AOD exhibited a notable inhibitory impact on the biofilm of S. epidermidis G-81. The minimum biofilm inhibitory concentration of AOD on S. epidermidis G-81 was 16 μg/mL, and the minimum biofilm scavenging concentration was 32 μg/mL, which exhibited superior efficacy compared to that of lincomycin. The inhibitory effect on the primary biofilm was 90.3%, and that on the mature biofilm was 82.85%, with a dose-dependent inhibition effect. Concurrently, AOD cleared intra-biofilm organisms and reduced the number of biofilm-holding bacteria by six orders of magnitude. These data indicate that disulfide bonds are essential to the structure and activity of AOD, and AOD may potentially become an effective dual-action antimicrobial and anti-biofilm agent. Full article

The climate impact of Arctic aerosols, like the Arctic Haze, and their origin are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study, we present a homogenised data set from a sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, of the 20 years from 2004–2023. Due to polar day and polar night, it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that autumn and winter are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn. A clear signal of large particles during the Arctic Haze can not be distinguished from large aerosols in winter. With autocorrelation analysis, we found that AOD events usually occur with a duration of several hours. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions, or wildfires in the Northern Hemisphere but did not find one single cause that clearly determines the Arctic AOD. Therefore the observed optical depth is a superposition of different aerosol sources. Full article

This study focuses on Central China (CC), including Shanxi, Henan, Anhui, Hubei, Jiangxi, and Hunan provinces. The 2019 average annual precipitation (PRE), average annual temperature (TEM), average annual wind speed (WS), population density (POP), normalized difference vegetation index (NDVI), aerosol optical depth (AOD), gross domestic product (GDP), and elevation (DEM) data were used as explanatory variables to predict the average annual PM_2.5 concentrations (PM_2.5Cons) in CC. The average annual PM_2.5Cons were predicted using different models, including multiple linear regression (MLR), back propagation neural network (BPNN), and random forest (RF) models. The results showed higher prediction accuracy and stability of the RF algorithm (RFA) than those of the other models. Therefore, it was used to analyze the contributions of the explanatory factors to the PM_2.5 concentration (PM_2.5Con) prediction in CC. Subsequently, the spatiotemporal evolution of the PM_2.5Cons from 2010 to 2021 was systematically analyzed. The results indicated that (1) PRE and AOD had the most significant impacts on the PM_2.5Cons. Specifically, the PRE and AOD values exhibited negative and positive correlations with the PM_2.5Cons, respectively. The NDVI and WS were negatively correlated with the PM_2.5Cons; (2) the southern and northern parts of Shanxi and Henan provinces, respectively, experienced the highest PM_2.5Cons in the 2010–2013 period, indicating severe air pollution. However, the PM_2.5Cons in the 2014–2021 period showed spatial decreasing trends, demonstrating the effectiveness of the implemented air pollution control measures in reducing pollution and improving air quality in CC. The findings of this study provide scientific evidence for air pollution control and policy making in CC. To further advance atmospheric sustainability in CC, the study suggested that the government enhance air quality monitoring, manage pollution sources, raise public awareness about environmental protection, and promote green lifestyles. Full article