Article
Environmental Sciences
Hao Zhou, Xu Yue, Yadong Lei, Chenguang Tian, Yimian Ma, Yang Cao
Summary: Diffuse radiation can increase plant photosynthesis light use efficiency. By using an artificial neural network model to bias-correct global hourly diffuse fraction, the updated data shows better correlations and reduced errors compared to original reanalysis, leading to improved simulations of global gross primary productivity.
GLOBAL BIOGEOCHEMICAL CYCLES
(2021)
Article
Agronomy
Hang Xu, Zhiqiang Zhang, Xiaoyun Wu, Jiaming Wan
Summary: Estimating dynamic changes in gross primary productivity (GPP) of terrestrial ecosystems has always been challenging. Improved big-leaf and two-leaf light use efficiency (LUE) models have been developed to address the effects of diffuse radiation on GPP. However, their global performance has not been comprehensively evaluated.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Plant Sciences
Peirong Liu, Xiaojuan Tong, Jinsong Zhang, Ping Meng, Jun Li, Jingru Zhang, Yu Zhou
Summary: This study explores the impacts of diffuse fraction (DF) on gross primary productivity (GPP) and light use efficiency (LUE) based on a 6-year dataset of carbon flux in a warm-temperate mixed plantation site in North China. The results show that canopy photosynthesis and the apparent quantum yield (alpha) are significantly higher on cloudy days compared to clear days. Increasing DF enhances GPP and LUE, and both variables are mainly controlled by DF and photosynthetically active radiation (PAR). Incorporating DF into the Michaelis-Menten model improves GPP estimation. The findings emphasize the importance of considering DF in carbon sequestration estimation.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Environmental Sciences
T. Chakraborty, X. Lee, D. M. Lawrence
Summary: The diffuse radiation fertilization effect, an understudied aspect of atmosphere-biosphere interactions, can have important implications for our understanding of the Earth system and future climate projections. However, limited observational data make it difficult to globally constrain this mechanism. Simulations show that uncertainties in the diffuse fraction of sunlight significantly affect simulated gross primary productivity and terrestrial evapotranspiration.
Article
Environmental Sciences
Yimian Ma, Xu Yue, Hao Zhou, Cheng Gong, Yadong Lei, Chenguang Tian, Yang Cao
Summary: This study conducted sensitivity tests on GPP modeling at FLUXNET sites, revealing that biases in meteorology, especially related to photosynthetically active radiation, play a critical role in modulating GPP uncertainties. Simulations using specific forcings help reduce climate-driven biases in GPP significantly.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Geosciences, Multidisciplinary
Zhaoyang Zhang, Meng Fan, Minghui Tao, Yunhui Tan, Quan Wang
Summary: Four remote sensing data-driven (RS) models were evaluated in simulating the effect of diffuse radiation on water-use efficiency (WUE). There was a large divergence among RS models in estimating the response of WUE to fraction of diffuse PAR (FDP). PML model performed better than other RS models in simulating the diffuse radiation effect on WUE.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Daqian Kong, Dekun Yuan, Haojie Li, Jiahua Zhang, Shanshan Yang, Yue Li, Yun Bai, Sha Zhang
Summary: In this study, a hybrid model combining machine learning and a LUE model was developed to estimate GPP, and it showed better performance in GPP prediction and greater adaptability to climate change. The study also found that the hybrid model could reasonably represent the responses of LUE to meteorological variables.
Article
Remote Sensing
Xin Li, Hongyu Liang, Weiming Cheng
Summary: The study found that the PAR(dif) fraction and aerosol optical depth have significant impacts on the accuracy of vegetation GPP estimation. In months with high PAR(dif) fractions, both models showed substantial underestimation of GPP; while at sites with high aerosol optical depth, the underestimation of GPP estimation by both models was more pronounced. The TL-LUE model demonstrated better performance in reducing underestimation and root-mean-square error (RMSE) values when the PAR(dif) fraction was above a certain threshold, indicating the sensitivity of GPP estimation models to environmental factors.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Multidisciplinary Sciences
Jing Fang, Xing Li, Jingfeng Xiao, Xiaodong Yan, Bolun Li, Feng Liu
Summary: Vegetation phenology, crucial in regulating the terrestrial carbon cycle and climate, has often been studied using inadequate traditional vegetation indices. In this study, we used the latest gross primary productivity product based on solar-induced chlorophyll fluorescence (GOSIF-GPP) to create an annual vegetation photosynthetic phenology dataset from 2001 to 2020 at a spatial resolution of 0.05 degrees. We employed smoothing splines and multiple change-point detection to retrieve phenology metrics for terrestrial ecosystems above 30 degrees N latitude (Northern Biomes), including the start of the growing season (SOS), end of the growing season (EOS), and length of growing season (LOS). Our phenology product can be valuable for validating and developing phenology or carbon cycle models, as well as monitoring climate change impacts on terrestrial ecosystems.
Article
Geosciences, Multidisciplinary
Xiaoqing Deng, Jing Zhang, Yunfei Che, Lihua Zhou, Tianwei Lu, Tian Han
Summary: This study investigates the effects of aerosol loading and cloud cover on radiation and carbon cycling in ecosystems. The results show that the aerosol model accurately estimates the aerosol effects; GPP increases and then decreases with increasing diffuse radiation fraction; vegetation canopy has higher light-use efficiency under diffuse light conditions; temperature and vapor pressure deficit have varying impacts on GPP and NEE.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Multidisciplinary Sciences
Jinshi Jian, Vanessa Bailey, Kalyn Dorheim, Alexandra G. Konings, Dalei Hao, Alexey N. Shiklomanov, Abigail Snyder, Meredith Steele, Munemasa Teramoto, Rodrigo Vargas, Ben Bond-Lamberty
Summary: A study finds discrepancies in historical estimates of global gross primary productivity (GPP) and respiration (RS), highlighting the uncertainty in the terrestrial carbon cycle. Estimating GPP based on RS measurements shows significantly higher GPP values compared to literature estimates, while global RS:GPP ratios are inconsistent with individual site calculations and model results. These discrepancies have implications for our understanding of carbon turnover times and terrestrial sensitivity to climate change.
NATURE COMMUNICATIONS
(2022)
Article
Ecology
Hui Guo, Xiao Zhou, Yi Dong, Yahui Wang, Sien Li
Summary: In this study, three machine learning models (Support vector regression (SVR), artificial neural network (ANN), and long short-term memory networks (LSTM)) were investigated for predicting GPP in northwest China and compared them with the traditional physical models. The analysis showed that machine learning models performed better than traditional physical models, with SVR model performing the best. When the training data was sufficient, SVR, ANN, and LSTM achieved similar prediction accuracy, but SVR was slightly higher. When the training data was small, the simulation accuracy of SVR was better than ANN and LSTM.
ECOLOGICAL MODELLING
(2023)
Article
Agronomy
Jamal Elfarkh, Kasper Johansen, Marcel M. El Hajj, Samir K. Almashharawi, Matthew F. McCabe
Summary: The trade-off between increasing agricultural production and groundwater conservation is a major challenge. Monitoring water use efficiency (WUE) is important for reducing irrigation without impacting yield. This study used Sentinel-2 data and models to evaluate ET, GPP, and WUE, showing the potential of high-resolution satellite data for assessing water resources management and supporting agricultural production in water-limited regions.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Environmental Sciences
Zhenyu Zhang, Xiaoyu Li, Weimin Ju, Yanlian Zhou, Xianfu Cheng
Summary: Accurate estimation of terrestrial gross primary productivity (GPP) is crucial for studying carbon exchange between the atmosphere and biosphere. The recently developed P model shows better performance than traditional Light Use Efficiency (LUE) models. In this study, 5 water stress factors were integrated into the P model to improve accuracy. The resulting global GPP dataset, called PGPP, outperforms other widely-used GPP products.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
Jingxue Zhao, Huaize Feng, Tongren Xu, Jingfeng Xiao, Rossella Guerrieri, Shaomin Liu, Xiuchen Wu, Xinlei He, Xiangping He
Summary: Drought, as a natural hydrometeorological phenomenon, has become more frequent and widespread due to climate change, with water availability strongly regulating the coupling between carbon uptake and water loss. Different vegetation types show varying effects on WUE, with VPD and Gc playing important roles in controlling WUE.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Engineering, Electrical & Electronic
Peng Zhou, Tianyi Zhang, Terrence W. Simon, Tianhong Cui
Summary: This paper presents the design and optimization of two-dimensional fluidic diodes for micropumps with high diodicity, achieving a measured flow rate of 34 ml/h for the Tesla-type fluidic diode. The use of numerical simulation and three-dimensional modeling enhances the efficiency of fluid flow, showing positive prospects for application.
JOURNAL OF MICROELECTROMECHANICAL SYSTEMS
(2022)
Article
Food Science & Technology
Xin Zhang, Yu Zhao, Tianyi Zhang, Yan Zhang, Lianzhou Jiang, Xiaonan Sui
Summary: This study investigated the potential use of a mixture of soy protein concentrate (SPC) and wheat gluten (WG) in the production of meat analogs through high moisture extrusion. The results showed that a blend of SPC-WG at a 50/50 ratio resulted in the best fibrous structures, and hydrogen and disulfide bonds played a major role in the extrusion process.
LWT-FOOD SCIENCE AND TECHNOLOGY
(2022)
Article
Chemistry, Analytical
Tianyi Zhang, Peng Zhou, Terrence Simon, Tianhong Cui
Summary: This study introduces a vibrating air bubble as a stirrer to enhance mass transfer in electrochemical sensing, leading to a twelve-fold increase in mass transfer coefficient compared to the static case. The enhanced sensing performance is quantified experimentally with an integrated electrochemical metal ion sensor, showing potential for various electrochemical sensing applications limited by slow molecular diffusion.
SENSORS AND ACTUATORS B-CHEMICAL
(2022)
Article
Chemistry, Multidisciplinary
Tianyi Zhang, Song Peng, Yang Jia, Junkai Sun, He Tian, Chuliang Yan
Summary: This paper establishes slip estimation models for China's Mars rover using Gaussian process regression. The models show high accuracy and estimation potential in predicting slip values and their confidence intervals under Mars conditions.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Software Engineering
Qian Fu, Xue Bai, Yafeng Zheng, Runsheng Du, Dongqing Wang, Tianyi Zhang
Summary: This research developed a visual learning analytics dashboard named VisOJ for the OJ system, which includes two types of user interfaces: teacher and student. The teacher interface helps teachers monitor students' learning status and provide feedback, while the student interface promotes students' self-reflection and self-regulation.
Article
Agronomy
Yanying Shi, Lizhi Wang, Shukun Jiang, Erjing Guo, Tao Li, Litao Zhou, Wenmeng Zhang, Haoyu Ma, Kaixin Guan, E. Li, Tianyi Zhang, Xiaoguang Yang
Summary: In Northeast China, the frequency and intensity of chilling events have been increasing, posing a risk to rice production. While previous studies have shown the detrimental effects of continuous chilling on rice grain yield, the effects of intermittent chilling at different growth stages have been rarely reported. This study conducted a temperature-controlled experiment to investigate the effects of continuous and intermittent chilling at the tillering, booting, and flowering stages on rice yield.
JOURNAL OF AGRONOMY AND CROP SCIENCE
(2023)
Article
Green & Sustainable Science & Technology
Tingting Liu, Yingjie Li, Mengqin Feng, Yan Chen, Tianyi Zhang
Summary: Mobile reading is seen as a promising method for achieving sustainable education goals. While there have been numerous studies on the mobile reading habits of young readers and their comprehension, there is little focus on college students in China and the factors affecting their engagement in mobile reading. This study aimed to investigate these factors, using interviews and qualitative content analysis. The participants were thirty college students from three universities in Shanghai, China. The results identified various factors influencing college students' engagement in mobile reading, including motivational needs, reading experience, efficacy, and strategies. The intention to be entertained was found to be the most common factor leading to engagement. However, students' difficulties in engaging stemmed from an imbalance between their needs and their engagement. Understanding these factors is crucial for improving mobile reading engagement and assisting college students' independent learning and sustainable development.
Article
Environmental Sciences
Xin Dong, Tianyi Zhang, Xiaoguang Yang, Tao Li
Summary: By establishing different scenarios representing the levels of chilling sensitivity, heat sensitivity, and maturity type, the study evaluates the performance of rice varieties in adapting to future climate change in Northeast China. The results suggest that late-maturing varieties have higher adaptability and greater potential for yield increase compared to low-sensitivity varieties, making them recommended as the primary breeding target for climate change adaptation in the region.
Article
Biophysics
Xin Dong, Tianyi Zhang, Xiaoguang Yang, Tao Li, Xichen Li
Summary: Rice in Northeast China has been positively affected by climate warming, leading to a 10% increase in yield since 1980. Currently, the decrease in chilling and increase in growing degree-day contribute to higher yields, while high-temperature extremes have a limited negative impact. However, as warming continues, the harmful effects of high-temperature extremes will outweigh other positive climate effects. Therefore, climate change mitigation and heat tolerance breeding measures are necessary for rice production in Northeast China.
INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
(2023)
Article
Agriculture, Multidisciplinary
Yu-Hao Zhang, Shan-Shan Yang, Qi Zhang, Tian-Tian Zhang, Tian-Yi Zhang, Bo-Hang Zhou, Le Zhou
Summary: Based on the structural features of succinate dehydrogenase inhibitors (SDHIs) and targeted covalent inhibitors, N-phenylpropiolamides with a Michael acceptor moiety were designed to find new antifungal compounds. Nineteen compounds demonstrated potent inhibition activity on nine plant pathogenic fungi. Compound 13 showed complete inhibition of Physalospora piricola infection on apples at a concentration of 200 μg/mL over 7 days and exhibited high safety to plant germination and seedling growth. It was identified as an SDH inhibitor with comparable activity to the positive drug boscalid.
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
(2023)
Article
Plant Sciences
Yunyan Zhai, Tianyi Zhang, Yanbing Guo, Chenxi Gao, Lipan Zhou, Li Feng, Tao Zhou, Wang Xumei
Summary: The potential of rhubarb in treating various diseases has been revealed, and molecular markers have been developed to identify high-quality germplasms of rhubarb. The evolutionary history and biogeography of the rhubarb complex have also been elucidated. These findings contribute to a better understanding of the classification, divergence, and geographic distribution of rhubarb.
JOURNAL OF PLANT RESEARCH
(2023)
Article
Forestry
Li Feng, Lipan Zhou, Tianyi Zhang, Xumei Wang
Summary: Ecological niches play a crucial role in lineage diversification. Differentiated adaptation or movement patterns can occur within a species in response to climate change. This study examines the potential distribution ranges and niche dynamics of three intraspecific lineages of Quercus aquifolioides. The results show differentiated climatic niches among the lineages, with some areas of overlap. The study highlights the importance of modeling intraspecific responses to climate change and provides insights into lineage diversification within Q. aquifolioides.
Article
Green & Sustainable Science & Technology
Nan Xu, Xueshi Liang, Tianyi Zhang, Juexian Dong, Yuan Wang, Yi Qu
Summary: Hydrological connectivity is crucial for the stability and biodiversity of wetland ecosystems, and it has been significantly impacted by socio-economic activities, leading to the loss of biodiversity and degradation of ecological functions. This study focused on the wetland biodiversity hotspots in Sanjiang Plain and used a combination of the Systematic Conservation Planning method and hydrological connectivity indices to analyze the changes in hydrological connectivity. The findings revealed varying degrees of decline in hydrological connectivity within the identified hotspots between 1995 and 2015.
Article
Multidisciplinary Sciences
Junkai Sun, Zezhou Sun, Pengfei Wei, Bin Liu, Yaobing Wang, Tianyi Zhang, Chuliang Yan
Summary: This paper proposes a path planning algorithm based on the Theta* algorithm and Timed Elastic Band (TEB) algorithm to solve the difficulty of path planning resulting from the variable configuration of the wheel-legged robot for future deep space explorations. The proposed algorithm divides the path planning of the wheel-legged robot into the planning of the body path and the planning of the wheel path, by simplifying the body as a point using virtual obstacles. Hierarchical planning and multiple optimization algorithms are used to optimize and smooth the path. The simulations show that the proposed algorithm effectively plans the path of the wheel-legged robot by using variable configurations for different types of obstacles.
Article
Multidisciplinary Sciences
Wenmeng Zhang, Tianyi Zhang, Xiaoguang Yang
Summary: Crop-specific, high-resolution phosphorus rate information is crucial for sustainable agricultural fertilizer management in China. The current phosphorus fertilizer dataset based on coarse national statistics lacks accuracy and crop-specific information. This study utilized provincial and county-level data to generate detailed maps of phosphorus rate for rice, wheat, and maize from 2004 to 2016 (CN-P). CN-P provides improved spatial heterogeneity and more accurate estimates of phosphorus rate for each crop compared to the existing dataset. The CN-P dataset has great potential for modeling sustainable agricultural fertilizer management strategies and addressing phosphorus pollution.
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)
