Article
Environmental Sciences
Behzad Kianian, Yang Liu, Howard H. Chang
Summary: The task of environmental health research is to create complete pollution exposure maps despite limited monitoring data. Satellite-derived aerosol optical depth (AOD) is often used to improve PM2.5 estimation in various models, with lattice kriging and random forest ensemble methods showing potential for enhancing AOD gap-filling. Random forest models for PM2.5 predictions remained largely consistent regardless of the inclusion of gap-filled AOD, except for some variability in daily model predictions.
Article
Environmental Sciences
Weijie Fu, Xu Yue, Zhengqiang Li, Chenguang Tian, Hao Zhou, Kaitao Li, Yuwen Chen, Xu Zhao, Yuan Zhao, Yihan Hu
Summary: The study reveals a weak correlation between surface PM2.5 concentrations and AOD in China, and emphasizes the importance of specific humidity in decoupling these associations. Including specific humidity in the model improves the prediction of PM2.5 concentrations.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Environmental Sciences
Qingyang Xiao, Guannan Geng, Jing Cheng, Fengchao Liang, Rui Li, Xia Meng, Tao Xue, Xiaomeng Huang, Haidong Kan, Qiang Zhang, Kebin He
Summary: This study reviewed and compared four gap-filling strategies for high-resolution PM2.5 predictions and found that regression-based methods were more robust, while decision tree filling was more time-efficient. Additionally, CTM simulations were beneficial for improving the accuracy of PM2.5 spatial distribution predictions in all models.
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Meteorology & Atmospheric Sciences
Tingting Jiang, Bin Chen, Zhen Nie, Zhehao Ren, Bing Xu, Shihao Tang
Summary: The study estimated hourly PM2.5 concentrations in China from March 2018 to February 2019 at a 1-km spatial resolution using a two-stage random forest model. The model achieved accurate and robust estimations of PM2.5 concentrations, but the performance varied across different seasons.
ATMOSPHERIC RESEARCH
(2021)
Article
Environmental Sciences
Lechao Dong, Siwei Li, Jia Xing, Hao Lin, Shansi Wang, Xiaoyue Zeng, Yaming Qin
Summary: Our study demonstrates the importance of the feature differences of surrounding stations and satellite-retrieved AOD in representing the regional pattern of PM2.5 and improving the accuracy of machine-learning based models in estimating surface PM2.5.
ATMOSPHERIC ENVIRONMENT
(2022)
Article
Environmental Sciences
Jana Handschuh, Thilo Erbertseder, Frank Baier
Summary: The latest epidemiological studies have shown that PM2.5 has adverse health effects on not only respiratory and cardiovascular diseases, but also brain development and metabolic diseases. Therefore, accurate and spatio-temporally resolved PM2.5 data is needed. Although satellite data has been increasingly used for monitoring PM2.5 distributions, most studies still rely on a single sensor. This study systematically evaluates four satellite-based AOD datasets obtained from different sensors and retrieval methodologies to derive ground-level PM2.5 concentrations.
Article
Environmental Sciences
Jing Lu, Yuhu Zhang, Mingxing Chen, Lu Wang, Shaohua Zhao, Xiao Pu, Xuegang Chen
Summary: Using satellite observations to estimate PM2.5 concentrations is feasible for monitoring air pollution, with a Random Forest model performing well in studying the long-term spatiotemporal variations of PM2.5 concentrations in the Beijing-Tianjin-Hebei region and its surrounding areas. The study found a decreasing trend in PM2.5 concentrations from 2002 to 2018, with the worst pollution occurring in winter and a U-shaped pattern in monthly concentrations.
Article
Environmental Sciences
Danlu Zhang, Linlin Du, Wenhao Wang, Qingyang Zhu, Jianzhao Bi, Noah Scovronick, Mogesh Naidoo, Rebecca M. Garland, Yang Liu
Summary: This study developed a random forest model to estimate daily PM2.5 concentrations in South Africa, showing high prediction accuracy and spatial resolution. The study identified satellite AOD, seasonal indicator, total precipitation, and population as the most important predictors in PM2.5 modeling.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Qiulun Li, Qingyang Zhu, Muwu Xu, Yu Zhao, K. M. Venkat Narayan, Yang Liu
Summary: China implemented a nationwide lockdown in response to COVID-19, leading to changes in air quality. Using machine learning and remote sensing data, this study analyzed PM2.5 concentrations, showing a decrease in levels during the pandemic period.
Article
Environmental Sciences
Somaya Falah, Fadi Kizel, Tirthankar Banerjee, David M. Broday
Summary: A new method is developed to predict surface PM2.5 concentrations by utilizing information on aerosol type retrieved from satellite observations. The method uses Random Forest and eXtreme Gradient Boosting models with input of widely available satellite aerosol products and surface meteorological data, resulting in improved risk assessment of PM2.5 exposure and more accurate radiative forcing calculations.
ENVIRONMENTAL POLLUTION
(2023)
Article
Environmental Sciences
Shashi Tiwari, Alok Kumar, Supriya Mantri, Sagnik Dey
Summary: This study used a random forest model to estimate PM2.5 exposure in Delhi from 2002 to 2019 and found a correlation between exposure variations and increased mortality burden. The results demonstrate the potential of machine learning in hyperlocal air quality management in cities.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Bryan N. Vu, Jianzhao Bi, Wenhao Wang, Amy Huff, Shobha Kondragunta, Yang Liu
Summary: This study successfully estimated the PM2.5 concentration during the Camp Fire episode, the deadliest wildfire in California history, by using a random forest model combined with multiple data sources. The results demonstrate that the model can aid in epidemiological investigations of intense and acute exposure to PM2.5 through hourly predictions.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Ling Qi, Haotian Zheng, Dian Ding, Dechao Ye, Shuxiao Wang
Summary: This study investigates the inter-annual variations of aerosol optical depth (AOD) and surface PM2.5 in China between 2006 and 2017, and finds that meteorology changes have a larger impact on AOD trends than on surface PM2.5. Meteorology changes are beneficial to AOD and surface PM2.5 reduction in spring but have an adverse effect on aerosol reduction in summer.
Article
Geography, Physical
Yue Jing, Long Pan, Yanling Sun
Summary: Due to the uneven distribution of environmental monitoring sites, there are data gaps in concentrations of PM2.5 obtained using traditional methods. Satellite products, such as MODIS AOD, can be used as an alternative data source. However, there are data gaps in winter. This study used VIIRS AOD to supplement MODIS AOD and developed a three-stage model to estimate PM2.5 with high accuracy.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2023)
Article
Environmental Sciences
Xuan Li, Chaofan Wu, Michael E. Meadows, Zhaoyang Zhang, Xingwen Lin, Zhenzhen Zhang, Yonggang Chi, Meili Feng, Enguang Li, Yuhong Hu
Summary: The study analyzed the spatiotemporal variations in key factors influencing PM2.5 in Zhejiang Province, China from 2000 to 2019 using random forest and SHAP algorithms. The results showed that factors influencing PM2.5 varied significantly, with meteorological factors being the most important, followed by socioeconomic factors and topography/land cover factors. While GDP and transportation factors initially increased in importance, their contribution has declined recently, indicating that economic and infrastructural development may not necessarily lead to higher PM2.5 concentrations. Vegetation productivity, as indicated by NDVI changes, has become more essential in improving air quality in the region.
Article
Environmental Sciences
Jian Lei, Ting Yang, Suijie Huang, Huichu Li, Yixiang Zhu, Ya Gao, Yixuan Jiang, Weidong Wang, Cong Liu, Haidong Kan, Renjie Chen
Summary: This study investigated the associations of PM2.5 and PM2.5-10 with pulmonary function in asthmatic patients in China from 2017 to 2020. The results showed generally inverse associations of PM2.5 and PM2.5-10 with pulmonary function indicators, with PM2.5-10 having stronger associations, especially in southern China. The associations were significant and could last for one week, indicating potential hazards of PM2.5-10 on pulmonary function.
ENVIRONMENT INTERNATIONAL
(2022)
Article
Engineering, Environmental
Jiuli Yang, Mingyang Liu, Qu Cheng, Lingyue Yang, Xiaohui Sun, Haidong Kan, Yang Liu, Michelle L. Bell, Rohini Dasan, Huiwang Gao, Xiaohong Yao, Yang Gao
Summary: This study investigated the relationship between air pollution exposure and acute myocardial infarction (AMI) and chronic obstructive pulmonary disease (COPD) in Qingdao, China. The findings showed significant associations between PM2.5, PM10, NO2, SO2, and CO exposure and AMI, particularly in older adults and females during the cold season. Only NO2 and SO2 were associated with COPD, with different lag associations for females and those over 65 years old. The two-pollutant model did not significantly change the exposure-response relationship.
FRONTIERS OF ENVIRONMENTAL SCIENCE & ENGINEERING
(2022)
Article
Infectious Diseases
Ye Yao, Jie Tian, Xia Meng, Haidong Kan, Lian Zhou, Weibing Wang
Summary: Our study constructed a COVID-19 severity self-assessment scale that can be used by patients in the community to predict their risk of developing severe illness and the need for further medical assistance.
BMC INFECTIOUS DISEASES
(2022)
Article
Cardiac & Cardiovascular Systems
Renjie Chen, Yixuan Jiang, Jialu Hu, Honglei Chen, Huichu Li, Xia Meng, John S. Ji, Ya Gao, Weidong Wang, Cong Liu, Weiyi Fang, Hongbing Yan, Jiyan Chen, Weimin Wang, Dingcheng Xiang, Xi Su, Bo Yu, Yan Wang, Yawei Xu, Lefeng Wang, Chunjie Li, Yundai Chen, Michelle L. Bell, Aaron J. Cohen, Junbo Ge, Yong Huo, Haidong Kan
Summary: This study found that short-term exposure to air pollutants such as PM2.5, NO2, SO2, and CO may trigger the onset of ACS and its subtypes. The associations were strongest in the first hour of exposure and attenuated thereafter.
Article
Environmental Sciences
Xueyi Xu, Yihui Ge, Weidong Wang, Xiaoning Lei, Haidong Kan, Jing Cai
Summary: This study aimed to measure noise levels in different seasons in Shanghai and establish a land-use regression (LUR) model to assess the spatial variability and potential sources of intra-urban noise. The study found that road-related variables were the most contributory predictors of noise level, followed by urban area, total area of buildings, and number of restaurant clusters. The results can be used to create a noise prediction map, indicating high noise levels in urban areas and near traffic arteries.
ENVIRONMENT INTERNATIONAL
(2022)
Article
Critical Care Medicine
Jing Cai, Yang Shen, Yan Zhao, Xia Meng, Yue Niu, Renjie Chen, Guangbin Quan, Huichu Li, John A. Groeger, Wenchong Du, Jing Hua, Haidong Kan
Summary: Research has found that prenatal and postnatal exposure to fine particulate matter (PM2.5) is associated with sleep quality and sleep disturbances in children. The association is stronger for postnatal exposure, particularly during the first 3 years of life, and is more evident in sleep-disordered breathing and daytime sleepiness.
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
(2023)
Review
Chemistry, Multidisciplinary
Aaron Albert Aryee, Yang Liu, Runping Han, Lingbo Qu
Summary: The rising pollution of water resources is a serious threat to human health and ecosystems, requiring advanced methods for water purification. Bimetallic adsorbents have recently been developed as effective solutions for water and wastewater treatment due to their multiple functionalities, easy fabrication, high specific surface area and volume ratio. This review focuses on the preparation methods, characterization, substrates, mechanisms and cost of bimetallic adsorbents, including graphene, polymers, metal-organic frameworks, zeolite, mesoporous silica, cellulose, chitosan, clay, carbonaceous waste and composites. It is observed that the synergy between the substrate and metal ions enhances the adsorption capacity by providing more active adsorption sites.
ENVIRONMENTAL CHEMISTRY LETTERS
(2023)
Article
Environmental Sciences
Su Shi, Weidong Wang, Xinyue Li, Yun Hang, Jian Lei, Haidong Kan, Xia Meng
Summary: This study aims to identify optimized modeling time windows for capturing the long-term variation of PM2.5 in China during 2005-2019 by including modeling data with multiple time windows. The results showed that training models with data of current years performed better during 2013-2019, while models with data of 2013 and 2014 performed better in predicting historical PM2.5 concentrations before 2013.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Engineering, Environmental
Tao Xue, Mingkun Tong, Meng Wang, Xinyue Yang, Yanying Wang, Huan Lin, Hengyi Liu, Jiajianghui Li, Conghong Huang, Xia Meng, Yixuan Zheng, Dan Tong, Jicheng Gong, Shiqiu Zhang, Tong Zhu
Summary: Nitrogen dioxide (NO2) exposure in China has led to a significant burden of premature deaths, especially in urban areas. This environmental inequality is evident as a small high-risk subgroup bears the majority of the NO2-related health impacts. Although there has been a reduction in the overall health impact of NO2 exposure from 2013 to 2020, inequality has slightly increased.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Meteorology & Atmospheric Sciences
Claudia Di Napoli, Marina Romanello, Kelton Minor, Jonathan Chambers, Shouro Dasgupta, Luis E. Escobar, Yun Hang, Risto Haenninen, Yang Liu, Martin Lotto Batista, Rachel Lowe, Kris A. Murray, Fereidoon Owfi, Mahnaz Rabbaniha, Liuhua Shi, Mikhail Sofiev, Meisam Tabatabaei, Elizabeth J. Z. Robinson
Summary: As the connection between extreme weather, climate changes, and health impacts becomes clearer, it is crucial to make climate-smart decisions to improve the responsiveness and resilience of the public health sector. Climate services for health integrate climate and health information to provide decision-support tools. The Lancet Countdown monitoring system uses global climate reanalyses products to track annual changes in health-related outcomes. By retrieving and processing multiple variables from reanalysis datasets, the system captures various climate-related hazards and their impacts on human health across the globe.
METEOROLOGICAL APPLICATIONS
(2023)
Article
Environmental Sciences
Ying Wang, Zhicheng Du, Yuqin Zhang, Shirui Chen, Shao Lin, Philip K. Hopke, David Q. Rich, Kai Zhang, Xiaobo X. Romeiko, Xinlei Deng, Yanji Qu, Yu Liu, Ziqiang Lin, Shuming Zhu, Wangjian Zhang, Yuantao Hao
Summary: Using state-of-the-art causal inference approaches, this large cohort study in southern China found a causal relationship between long-term exposure to particulate matter (PM) and chronic obstructive pulmonary disease (COPD) mortality. The detrimental effects were more pronounced among the elderly and inactive participants. Therefore, there is an urgent need for more effective strategies to reduce PM exposure and pay particular attention to vulnerable groups.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Keyong Huang, Qingyang Zhu, Xiangfeng Lu, Dongfeng Gu, Yang Liu
Summary: This study developed a satellite-based ensemble machine learning model to predict 16-year NO2 levels in China and identified a high mortality burden attributed to NO2, which has significant implications for environmental policy making.
Article
Geosciences, Multidisciplinary
Yutong Wang, Yu Zhao, Yiming Liu, Yueqi Jiang, Bo Zheng, Jia Xing, Yang Liu, Shuai Wang, Chris P. Nielsen
Summary: Near-surface ozone pollution is one of the biggest challenges in China's air quality management. This study uses measurements from the national air quality monitoring network to analyze the spatiotemporal evolution of ozone concentrations from 2010 to 2021. The results show that the national air pollution control programme has effectively reduced ozone levels in China, with emission reductions and changing meteorological conditions playing a role. Furthermore, the effectiveness of emission controls varies by region and season, with rural areas and summer showing greater improvements. Thus, future efforts to control ozone pollution should consider these regional and seasonal variations to target the most important precursors.
Article
Environmental Sciences
Xiaoting Zhang, Yang Liu, Lingbo Qu, Runping Han
Summary: In this study, a green adsorbent (Fe3O4-UiO-66-NH2) was synthesized using a co-precipitation method and showed excellent adsorption performance for 2,4-D and GP. The adsorbent demonstrated a wide pH range, high salt tolerance, and good regeneration performance. It can effectively remove 2,4-D and GP from water.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Engineering, Environmental
Danlu Zhang, Wenhao Wang, Yuzhi Xi, Jianzhao Bi, Yun Hang, Qingyang Zhu, Qiang Pu, Howard Chang, Yang Liu
Summary: As wildland fires become more frequent and intense, the impact of fire smoke on air quality has worsened significantly, especially on the West Coast and in the Southeastern U.S. Over the past decade, fire smoke contributed over 25% of daily PM2.5 concentrations at most monitoring sites in the U.S., with residents further away from monitoring sites experiencing a higher smoke impact. Furthermore, excluding the contribution of fire smoke would result in a higher compliance rate with the national ambient air quality standard.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)