Article
Environmental Sciences
Yehya Elsayed, Sofian Kanan, Ahmad Farhat
Summary: This study in the GCC region near two major airports reports seasonal variations in meteorological parameters, atmospheric dust, and dust-borne heavy metals concentrations. The concentrations of heavy metals, PM2.5, and PM10 fluctuated with meteorological conditions, with potential harm to human health. The chemical correlation between atmospheric dust and regional desert sand implies the localized origin of smaller dust particles.
ENVIRONMENTAL POLLUTION
(2021)
Article
Meteorology & Atmospheric Sciences
Pengfei Ma, Zhengcai Zhang, Yan Zhang, Yixi Lamu, Duo Za
Summary: Concentrations of PM10 have significant impacts on the environment, human activities, and human health. Limited field measurements of PM10 emissions have been conducted in the Yarlung Zangbo River region, which is highly prone to dust hazards. This study used a laser particle counter to assess PM10 concentrations in different land surfaces and analyzed the spatial and temporal variability of PM10 as well as the influence of meteorological conditions. The findings highlight the importance of considering land surface characteristics and critical values of relative humidity, air temperature, and soil temperature for dust storm forecasting in the region.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Article
Environmental Sciences
Aleksei Kholodov, Konstantin Kirichenko, Igor Vakhniuk, Anvir Fatkulin, Maria Tretyakova, Leonid Alekseiko, Valeriy Petukhov, Kirill Golokhvast
Summary: This study investigates the concentrations of PM2.5 and PM10 in the air of Nakhodka city in Russia, and finds that the concentrations of particulate matter are elevated in the port and city center areas, posing potential risks to public health.
AEROSOL AND AIR QUALITY RESEARCH
(2022)
Article
Chemistry, Multidisciplinary
Soo-Min Choi, Hyo Choi
Summary: The study conducted multiple statistical prediction modeling of PM10, PM2.5, and PM1 in Gangneung city, Korea, in association with local meteorological parameters and concentrations from an upwind site in Beijing, China. It was found that PM concentrations showed different peak trends before and after the yellow dust period, with significant changes in emission sources. New linear regression models were suggested to improve the correlation coefficients between the observed and calculated PM concentrations.
APPLIED SCIENCES-BASEL
(2021)
Article
Environmental Sciences
Katalin Bodor, Robert Szep, Agnes Keresztesi, Zsolt Bodor
Summary: Modern societies are facing increased air pollution, with particulate matter (PM) being one of the major pollutants and causing significant environmental health issues. This study focused on the Ciuc basin and analyzed the time series data of PM2.5, PM10, and TSP from 2010 to 2019 to understand the characteristics of air pollution in this region. The average monthly concentrations of TSP, PM10, and PM2.5 varied within certain ranges, with the highest levels observed during the cold period. The percentage of PM10 exceedances was highest in winter, while lower percentages were observed in autumn and spring. The correlation analysis showed a moderate to high level of correlation among the studied pollutants.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Soil Science
Xingna Lin, Jianzhi Niu, Xinxiao Yu, Ronny Berndtsson, Shanshan Wu, Shiyin Xie
Summary: The study evaluates the vertical PM2.5, PM10, and dust flux from an experimental agricultural area using wind tunnel tests and simulation models, showing the different impacts of various maize residue management methods on the flux of these air pollutants.
SOIL & TILLAGE RESEARCH
(2021)
Article
Environmental Sciences
Savannah L. Lewis, Lynn M. Russell, John A. McKinsey, William J. Harris
Summary: The Oceano Dunes in California is a natural source of wind-driven dust emissions, primarily consisting of particulate matter (PM) with a particle size larger than 1 μm. To evaluate the impact of reducing PM emissions from the dune area on air quality, samples were collected during high-wind months from 2019 to 2021 to analyze the organic and elemental composition of PM10 and PM2.5. The results suggest that while the contribution of unidentified components from the dunes is relatively high, there is no evidence of toxic substances, indicating that current dust abatement strategies may not significantly improve downwind air quality.
ATMOSPHERIC ENVIRONMENT
(2023)
Article
Multidisciplinary Sciences
Tomasz Danek, Elzbieta Weglinska, Mateusz Zareba
Summary: Despite restrictive laws, Krakow has the highest level of air pollution in Europe, with pollutants transported from neighboring municipalities. This study applied a complex geostatistical approach to analyze particulate matter concentrations. The results show the relationship between topography, meteorological variables, and PM concentrations, with wind speed and terrain elevation being the main factors. The study also examined pollution migration and sources through the analysis of the PM2.5/PM10 ratio.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Information Systems
Uzair Aslam Bhatti, Yuhuan Yan, Mingquan Zhou, Sajid Ali, Aamir Hussain, Qingsong Huo, Zhaoyuan Yu, Linwang Yuan
Summary: As Pakistan's economy, transportation, and industry develop, environmental pollution has become a prominent issue, with air quality in Lahore exceeding national standards. There is a strong correlation between particulate matter and other pollutants, with future predictions showing an increase in PM2.5 concentration.
Article
Environmental Sciences
Jalil Jaafari, Kazem Naddafi, Masud Yunesian, Ramin Nabizadeh, Mohammad Sadegh Hassanvand, Mansour Shamsipour, Mohammad Ghanbari Ghozikali, Shahrokh Nazmara, Hamid Reza Shamsollahi, Kamyar Yaghmaeian
Summary: The study found that in urban areas, the health effects of anthropogenic sources of particulate matter were higher than dust storm conditions; while in rural areas, the concentration changes of hs-CRP, IL-6, and WBCs under dust storm conditions were higher than inversion and cold season conditions.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Meteorology & Atmospheric Sciences
Ismail Sezen, Elif Ercelik, Yusuf Alizade Govarchin Ghale, Ali Deniz, Alper Unal
Summary: High concentrations of particulate matter (PM) have become a major problem in Turkey due to its economic development and geographical proximity to natural dust source areas. This study analyzed PM10 data from 36 ground-based stations in 12 metropolitan cities in Turkey from 2010 to 2020. The results showed that only three cities had PM10 levels below or around the 24-hour Air Quality Guideline (AQG) level of 45 μg/m³ set by the World Health Organization (WHO). The long-term change in PM10 concentration was mostly negative, indicating a decrease in levels in most cities due to reduction in emissions.
ATMOSPHERIC RESEARCH
(2023)
Article
Environmental Sciences
Mikalai Filonchyk
Summary: In March 2021, a dust storm originating from northern China and southeastern Mongolia severely deteriorated air quality across East Asia, with a large amount of dust particles suspended in the atmosphere. Analysis of data from ground-based sensors, satellites, and atmospheric models can provide insights into this dust storm event and help in implementing relevant protective and preventive measures.
Article
Chemistry, Multidisciplinary
Alla V. Varenik
Summary: In Sevastopol, even at the background station, the concentrations of PM10 and PM2.5 particles in the air exceed the maximum permissible concentrations in the case of dust transported from deserts. The impact of both local sources and long-distance atmospheric transport depends on weather conditions.
APPLIED SCIENCES-BASEL
(2022)
Article
Environmental Sciences
Dennis R. Fitz, Kurt Bumiller, Vic Etyemezian, Hampden D. Kuhns, John A. Gillies, George Nikolich, David E. James, Rodney Langston, Russell S. Merle
Summary: Testing PM10 emissions on roadways revealed an initial rise in emission rates after street sweeping, but a rapid decay after depositing soil. Mobile measurement methods offer a cost-effective way to measure PM10 emissions from roads.
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Environmental Sciences
Mikalai Filonchyk, Michael Peterson
Summary: An intense dust storm in March 2021 originating from the Gobi Desert in Mongolia had a significant impact on northern, central, and eastern China, affecting air quality and visibility, and posing a threat to millions of lives.
Article
Computer Science, Interdisciplinary Applications
Hone-Jay Chu, Muhammad Zeeshan Ali, Thomas J. Burbey
Summary: This study estimated high spatio-temporal resolution land subsidence through data fusion, revealing that subsidence hotspots vary with time and space, aiding in explaining the spatio-temporal variability of the subsidence pattern.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Environmental Sciences
Muhammad Zeeshan Ali, Hone-Jay Chu, Yi-Chin Chen, Saleem Ullah
Summary: This study developed landslide susceptibility maps using machine learning for earthquake and typhoon-triggered landslides in Pakistan and Taiwan, comparing traditional (logistic regression) and modern techniques (decision tree). Results showed that the spatial pattern of susceptibility map from logistic regression is continuously distributed, while that from the decision tree is crisp and sharp.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Computer Science, Interdisciplinary Applications
Muhammad Zeeshan Ali, Hone-Jay Chu, Tatas, Thomas J. Burbey
Summary: This study utilized GPS data to estimate monthly groundwater levels in westcentral Taiwan for 2016-17, showing that time-dependent spatial regression provides more accurate estimation of groundwater level changes. The high correlation between observed and estimated groundwater levels indicates that GPS estimated deformations are a viable alternative for estimating seasonal groundwater changes, especially in areas with limited groundwater monitoring stations.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Engineering, Civil
Tatas, Hone-Jay Chu, Thomas J. Burbey
Summary: This study aims to estimate next-month's groundwater levels using real-world data, and the results indicate different responses of groundwater levels to reduced pumping in different regions within the alluvial fan.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Muhammad Zeeshan Ali, Hone-Jay Chu, Tatas, Thomas J. Burbey
Summary: Understanding the extent and quantity of groundwater drawdown is crucial for water management strategies. This study demonstrates the potential of using a data-driven model and InSAR-derived land deformation data for spatial estimation of groundwater drawdown, showcasing the possibility of satellite-based groundwater drawdown map prediction.
WATER AND ENVIRONMENT JOURNAL
(2022)
Article
Environmental Sciences
Wen-Chao Ho, Li-Wei Chou, Ruey-Yun Wang, Thanh-Nhan Doan, Hwa-Lung Yu, Ting-Hsuan Chou, Kang-Yung Liu, Po-Chang Wu, Shwn-Huey Shieh
Summary: The study suggests that exposure to PM2.5 is associated with an increased risk of developing Rheumatoid arthritis (RA).
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Water Resources
Tatas, Hone-Jay Chu, Thomas J. Burbey, Cheng-Wei Lin
Summary: Excessive land subsidence is occurring in the Choushui alluvial fan, Taiwan, due to unmonitored groundwater pumping. Estimating pumping volumes based on electricity consumption alone cannot accurately estimate the spatial rate and distribution of subsidence. Time-dependent spatial regression provides a reliable tool for estimating the spatial distribution of annual subsidence based on mapping pumped groundwater volumes and monitored land subsidence.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2023)
Article
Engineering, Civil
Ying-Fan Lin, Junqi Huang, Elliot J. Carr, Tung-Chou Hsieh, Hongbin Zhan, Hwa-Lung Yu
Summary: Groundwater is crucial for providing fresh water, but it is highly vulnerable to pollution. Understanding the dynamics of solute transport in groundwater and soils is essential for predicting the distribution of contaminants. In this research, we propose a new approach based on the temporally relaxed theory of Fick's Law, which introduces two relaxation times to account for solute particle collisions and attachment. Our findings show that the relaxation times have similar properties to the transport parameters in conventional models, and our solution accurately predicts transport parameters from soil column experiments. Importantly, we discovered that the relaxation times are proportional to the magnitude of Peclet number, providing deeper insight into solute transport and groundwater contamination.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Khushbakht Rehman, Nadeem Fareed, Hone-Jay Chu
Summary: Satellites are frequently launched to monitor Earth's surface processes, such as the Landsat legacy which has thrived for 50 years. However, there are fewer satellites specifically launched to address pressing scientific questions, like ICESat-2 which studies polar icecaps and their response to climate change. This study introduces the use of ICESat-2 in aeolian sand dune studies and shows that it provides high-resolution topographic details with significant improvements to existing methods.
Article
Green & Sustainable Science & Technology
Wachidatin Nisaul Chusnah, Hone-Jay Chu, Tatas, Lalu Muhamad Jaelani
Summary: Chlorophyll-a concentration is commonly used to evaluate the trophic level and water quality of lakes. This research developed a high spatiotemporal-resolution model for estimating chlorophyll-a in inland water. Machine learning models using Sentinel-2 Multispectral Instrument and Sentinel-3 Ocean and Land Color Instrument (OLCI) images were applied, and a spatiotemporal fusion technique was used to improve the spatial resolution. Results showed that the spatiotemporal fusion model effectively estimated high-resolution chlorophyll-a concentration in the Tsengwen Reservoir.
SUSTAINABLE ENVIRONMENT RESEARCH
(2023)
Article
Engineering, Marine
Adillah Alfatinah, Hone-Jay Chu, Sumriti Ranjan Tatas, Sumriti Ranjan Patra
Summary: This study used Chlorophyll-a, sea surface temperature (SST), and sea surface height (SSH) as environmental variables to identify hotspots for skipjack tuna catch. Ensemble models, including decision tree (DT) and generalized linear model (GLM), were employed to predict skipjack areas for each time slice. The study concluded that DT performs better than GLM in predicting skipjack tuna fishing areas and found that sea surface temperature (SST) was the most influential environmental variable in model construction.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Environmental Sciences
Hone-Jay Chu, Yu-Chen He
Summary: In this study, a satellite-based sparse representation optimization model is developed to estimate water quality maps under noisy environment by simultaneously determining important spectral features. The blue-green ratio is identified as an important feature for estimating chlorophyll-a concentration, and the NIR-red algorithm performs better in retrieving Chl-a in high concentration cases. By using main spectral features and constrained by observations, the Chl-a map can be estimated, allowing the assessment of spatial distribution of water quality. This study provides reliable and interpretable information for policymakers to implement effective water quality management practices.
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
(2023)
Article
Green & Sustainable Science & Technology
Muhammad Zeeshan Ali, Hone-Jay Chu, Tatas
Summary: Groundwater depletion occurs when extraction exceeds recharge, affecting water resource management worldwide, especially in developing countries. In India, groundwater level observations are mainly seasonal, with data available in January, May, August, and November. This study utilizes the Gravity Recovery and Climate Experiment (GRACE) data to estimate monthly variations in groundwater storage (GWS) and develop spatial maps of groundwater levels. The accuracy of the estimated levels is validated against observations, and the results will help identify hotspots of depletion and mitigate the adverse effects of excessive extraction.
Proceedings Paper
Remote Sensing
Chia-Hsiang Lin, Man-Chun Chu, Hone-Jay Chu
Summary: Efficient and accurate mangrove area mapping is crucial for protecting valuable mangrove ecosystems. The proposed method, MSMCA, combines convex optimization and deep learning to achieve state-of-the-art classification performance.
2022 12TH WORKSHOP ON HYPERSPECTRAL IMAGING AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS)
(2022)
Article
Environmental Sciences
Wachidatin Nisaul Chusnah, Hone-Jay Chu
Summary: This study proposed a band ratio algorithm using machine learning to estimate chlorophyll-a concentration in inland waters. The NIR-red band ratios were strongly correlated with chlorophyll-a concentration and proved to be appropriate inputs for the machine learning model. The random forest model using the three-band NIR-red and blue-green band ratios provided robust and reliable estimation of chlorophyll-a concentration.
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
(2022)
Article
Environmental Sciences
Muhammad Waqas, Majid Nazeer, Man Sing Wong, Wu Shaolin, Li Hon, Joon Heo
Summary: The socio-economic restriction measures implemented in the United States have significantly reduced nitrogen dioxide (NO2) emissions. The study highlights the impact of factors such as human mobility, population density, income, climate, and stationary sources on the reduction of NO2 at different stations. The research emphasizes the scientific impacts of the NO2 reduction and income inequality revealed by the pandemic on air quality and health disparities.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Guorui Zhi, Jinhong Du, Aizhong Chen, Wenjing Jin, Na Ying, Zhihui Huang, Peng Xu, Di Wang, Jinghua Ma, Yuzhe Zhang, Jiabao Qu, Hao Zhang, Li Yang, Zhanyun Ma, Yanjun Ren, Hongyan Dang, Jianglong Cui, Pengchuan Lin, Zhuoshi He, Jinmin Zhao, Shuo Qi, Weiqi Zhang, Wenjuan Zhao, Yingxin Li, Qian Liu, Chen Zhao, Yi Tang, Peng Wei, Jingxu Wang, Zhen Song, Yao Kong, Xiangzhe Zhu, Yi Shen, Tianning Zhang, Yangxi Chu, Xinmin Zhang, Jiafeng Fu, Qingxian Gao, Jingnan Hu, Zhigang Xue
Summary: An comprehensive emission inventory for China in 2019, which includes both air pollutants and greenhouse gases, was developed in this study. The inventory utilizes existing frameworks and data to provide comparable emissions data and demonstrates the relationship between emissions and economic development.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
I-Ting Ku, Yong Zhou, Arsineh Hecobian, Katherine Benedict, Brent Buck, Emily Lachenmayer, Bryan Terry, Morgan Frazier, Jie Zhang, Da Pan, Lena Low, Amy Sullivan, Jeffrey L. Collett Jr
Summary: Unconventional oil and natural gas development (UOGD) in the United States has expanded rapidly in recent decades, raising concerns about its impact on air quality. This study conducted extensive air monitoring during the development of several large well pads in Broomfield, Colorado, providing a unique opportunity to examine changes in local air toxics and VOC concentrations during well drilling and completions and production. The study identified significant increases in VOC concentrations during drilling operations, highlighting the importance of emissions from synthetic drilling mud. The findings suggest opportunities to mitigate emissions during UOGD operations.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Puji Lestari, Akbar R. Tasrifani, Wiranda I. Suri, Martin J. Wooster, Mark J. Grosvenor, Yusuke Fujii, Vissia Ardiyani, Elisa Carboni, Gareth Thomas
Summary: This study developed field emission factors for various pollutants in peatland fires and estimated the total emissions. Gas samples were collected using an analyzer, while particulate samples were collected using air samplers. The study found significant emissions of CO2, CO, PM2.5, carbon aerosols, water-soluble ions, and elements from the fires in Central Kalimantan, Indonesia in 2019.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Ligang Li, Yuyu Chen, Lu Fan, Dong Sun, Hu He, Yongshou Dai, Yong Wan, Fangfang Chen
Summary: A high-precision retrieval method based on a deep convolutional neural network and satellite remote sensing data is proposed to obtain accurate methane vertical profiles.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Hyung Joo Lee, Toshihiro Kuwayama, Michael Fitzgibbon
Summary: This study investigated the changes in nitrogen dioxide (NO2) air pollution levels and their disparities in California, U.S. during the pandemic of coronavirus disease 2019 (COVID-19). The results showed a decrease in NO2 concentrations, especially in urban and high-traffic areas. However, socially vulnerable populations still experienced higher levels of NO2 exposure. The study suggests that reducing NO2 disparities, particularly racial inequity, can be achieved through continued regulatory actions targeting traffic-related NOx emissions.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Maria Chiara Pietrogrande, Beatrice Biffi, Cristina Colombi, Eleonora Cuccia, Umberto Dal Santo, Luisa Romanato
Summary: This study investigates the chemical composition and oxidative potential of PM10 particles in the Po Valley, Italy, and demonstrates the impact of high levels of atmosphere ammonia. The rural area had significantly higher ammonia concentrations compared to the urban site, resulting in higher levels of secondary inorganic aerosol. Although the SIA components did not contribute significantly to the PM10 oxidative reactivity, they were correlated with the oxidative potential measurements. This suggests that the contribution of SIA to PM oxidative toxicity cannot be ignored.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Natalie Allen, Jan Gacnik, Sarrah M. Dunham-Cheatham, Mae Sexauer Gustin
Summary: Accurate measurement of atmospheric reactive mercury is challenging due to its reactivity and low concentrations. The University of Nevada, Reno Reactive Mercury Active System (RMAS) has been shown to be more accurate than the industry standard, but has limitations including long time resolution and sampling biases. Increasing the sampling flow rate negatively affected RM concentrations, but did not impact the chemical composition of RM captured on membranes.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Chin-Yu Hsu, Wei-Ting Hsu, Ching-Yi Mou, Pei-Yi Wong, Chih-Da Wu, Yu-Cheng Chen
Summary: This study estimated the daily exposure concentrations of PM2.5 for elderly individuals residing in different regions of Taiwan using land use regression with machine learning (LUR_ML) and microenvironmental exposure (ME) models. The accuracy of the models varied across regions, with the ME models exhibiting higher predictions and lower biases. The use of region-specific microenvironmental measurements in the ME model showed potential for accurate prediction of personal PM2.5 exposure.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Xiaohan Si, Kerrie Mengersen, Chuchu Ye, Wenbiao Hu
Summary: This study found that there is an interactive effect between air pollutants and weather factors, which significantly affects influenza transmission. Future research should consider the interactive effects between pollutants and temperature or humidity to evaluate the environment-influenza association.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Luxi Xu, Ruijun Xu, Yunshao Ye, Rui Wang, Jing Wei, Chunxiang Shi, Qiaoxuan Lin, Ziquan Lv, Suli Huang, Qi Tian, Yuewei Liu
Summary: This study aimed to evaluate the impact of ambient air pollution on hospital admissions for angina. The results showed that exposure to ambient particulate matter, sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone are associated with an increased risk of hospital admissions for angina. The association with nitrogen dioxide exposure was found to be the strongest.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Xinyu Yu, Man Sing Wong, Majid Nazeer, Zhengqiang Li, Coco Yin Tung Kwok
Summary: This study proposes a novel method to address the challenge of missing values in satellite-derived AOD products and creates a comprehensive daily AOD dataset for the Guangdong-Hong Kong-Macao Greater Bay Area. By reconstructing missing values and developing a new model, the derived dataset outperforms existing products and agrees well with ground-based observations. Additionally, the dataset exhibits consistent temporal patterns and more spatial details.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Yidan Zhang, Yifan Xu, Bo Peng, Wu Chen, Xiaoyu Cui, Tianle Zhang, Xi Chen, Yuan Yao, Mingjin Wang, Junyi Liu, Mei Zheng, Tong Zhu
Summary: This study developed a sensitive method to measure the metallic components of atmospheric fine particulate matter (PM2.5) and compared the results with different analysis methods. The concentrations of metallic components in personal PM2.5 samples were found to be significantly different from corresponding fixed-site samples. Personal sampling can reduce exposure misclassifications, and measuring metallic components is useful for exploring health risks and identifying sources of PM2.5.
ATMOSPHERIC ENVIRONMENT
(2024)
Review
Environmental Sciences
Jamie Leonard, Lea Ann El Rassi, Mona Abdul Samad, Samantha Prehn, Sanjay K. Mohanty
Summary: Increasing concentrations of microplastics in the Earth's atmosphere could have adverse effects on ecosystems and human health. The deposition rate of airborne microplastics is influenced by both land use and climate, and a global analysis suggests that climate may have a greater impact on the concentration and deposition rate of microplastics than land use.
ATMOSPHERIC ENVIRONMENT
(2024)
Article
Environmental Sciences
Tian Zhou, Xiaowen Zhou, Zining Yang, Carmen Cordoba-Jabonero, Yufei Wang, Zhongwei Huang, Pengbo Da, Qiju Luo, Zhijuan Zhang, Jinsen Shi, Jianrong Bi, Hocine Alikhodja
Summary: This study investigated the long-range transport and effects of North African and Middle Eastern dust in East Asia using lidar observations and model simulations. The results showed that the dust originated from multiple sources and had a long transport time. The vertical distribution of the dust was found to be crucial for assessing its impacts.
ATMOSPHERIC ENVIRONMENT
(2024)
