Article
Environmental Sciences
Guilan Xie, Ruiqi Wang, Wenfang Yang, Landi Sun, Mengmeng Xu, Boxing Zhang, Liren Yang, Li Shang, Cuifang Qi, Mei Chun Chung
Summary: This study found an association between prenatal PM2.5 exposure and reduced birth weight and impaired renal function. Each 10 μg/m³ increment in prenatal PM2.5 was associated with decreased birth weight, glomerular filtration rate (GFR), increased blood urea nitrogen (BUN), and increased uric acid (UA). Renal function played a partial role in the relationship between prenatal PM2.5 and birth weight.
Article
Environmental Sciences
Xiaojie Wu, Pingping Xiong, Lingshan Hu, Hui Shu
Summary: This paper introduces a new carbon emission prediction model by incorporating new information priority operator and nonlinear parameter. The new model is applied to predict carbon emissions in different regions and trends, and demonstrates higher accuracy and forecasting ability.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Multidisciplinary Sciences
Junting Zhong, Xiaoye Zhang, Ke Gui, Yaqiang Wang, Huizheng Che, Xiaojing Shen, Lei Zhang, Yangmei Zhang, Junying Sun, Wenjie Zhang
Summary: Retrieving historical PM2.5 data is crucial for evaluating its long-term impacts, but satellite-based estimations have limitations. By incorporating spatial effects from meteorological data, a robust LightGBM model was developed to predict PM2.5 at high predictive capacities on different timescales. This model has great potential in reconstructing historical PM2.5 datasets and constructing real-time gridded networks with high spatial-temporal resolutions.
NATIONAL SCIENCE REVIEW
(2021)
Article
Mathematics, Interdisciplinary Applications
Shaojiu Bi, Minmin Li, Guangcheng Cai
Summary: In this paper, a mixed-order image denoising algorithm is proposed, which uses fractional-order and high-order regularization terms to suppress the staircase effect and preserve the edges and details of the image. Different regularization penalties are added in different regions to improve the denoising performance. A weight selection function is designed using the structure tensor to select the regularization terms effectively. The algorithm adaptively adjusts the regularization parameters and uses the predictor-corrector scheme to improve the accuracy and convergence.
FRACTAL AND FRACTIONAL
(2023)
Article
Engineering, Environmental
Yuelei Xu, Yan Huang, Zhongyang Guo
Summary: This study analyzed the impact of meteorological elements, AOD products, and modeling methods on the accuracy of the AOD-PM2.5 model, finding that incorporating meteorological elements that vary with time and height can significantly improve model accuracy in eastern China, Terra AOD products have a higher product index compared to Aqua AOD products, and the RF model outperforms other modeling methods in terms of performance.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2021)
Article
Engineering, Mechanical
Mingming Lu, Huacong Li, Linxiong Hong
Summary: This research proposed a new learning function formed by the combination of the conditional likelihood function and clustering constrain function for reconstructing Kriging, aiding in selecting the best next point.
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Qian Yang, Xinlei Zhang, Qing Luan, Shuai Sun, Yongqiang Zhao, Chenggege Fang, Xiaonan Mi, Mengwei Li
Summary: PM2.5 is directly related to air quality and poses a health threat, so accurate monitoring is necessary. Existing PM2.5 inversion models neglect the influence of upper-air meteorological data. To improve accuracy, a new hourly inversion model that integrates upper-air meteorological data was proposed, achieving the highest accuracy on the test set. Compared to other models, including deep neural networks and ensemble models, the proposed model showed significant improvement in reducing the root mean square error.
Article
Environmental Sciences
Chen Zuo, Jiayi Chen, Yue Zhang, Yize Jiang, Mingyuan Liu, Huiming Liu, Wenji Zhao, Xing Yan
Summary: This study evaluates four meteorological reanalysis datasets in China and finds that ERA5 is the most accurate in terms of temperature, relative humidity, wind speed, and boundary layer height, while FNL has the highest uncertainty. The spatial accuracy of all datasets is higher in the eastern region compared to the western region due to complex terrain and limited ground-based observations. ERA5 performs the best in retrieving PM2.5 in China, providing a useful guideline for subsequent satellite-based PM2.5 retrieval studies in the country.
ATMOSPHERIC ENVIRONMENT
(2023)
Article
Multidisciplinary Sciences
Ekta Chaudhary, Franciosalgeo George, Aswathi Saji, Sagnik Dey, Santu Ghosh, Tinku Thomas, Anura. V. Kurpad, Sumit Sharma, Nimish Singh, Shivang Agarwal, Unnati Mehta
Summary: This study showed that increased exposure to PM2.5 is associated with higher prevalence of anemia, acute respiratory infection, and low birth weight among children in India. Nitrate, elemental carbon, and ammonium were found to be more correlated with these health outcomes compared to other PM2.5 species. The study also suggests that using total PM2.5 mass as an indicator of air pollution exposure may underestimate the composite impact of different components of PM2.5.
NATURE COMMUNICATIONS
(2023)
Editorial Material
Computer Science, Artificial Intelligence
Ivo Bukovsky, Gejza Dohnal, Noriyasu Homma
Summary: This article provides comments on the derivation of weight-update stability in an in-parameter-linear nonlinear learning system with the gradient descent learning rule as described in the mentioned article. The purpose of the comments is not to discredit the overall contribution of the mentioned article, but to point out the issues that need to be addressed to prevent their proliferation.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Yinpeng Qu, Xiwei Wang, Xiaofei Zhang, Sheng Huang
Summary: This article proposes an adaptive method for multifaults diagnosis of motors under various working conditions, especially in cases of dramatic speed changes and unstable working states. The method includes signal preprocessing using a time-frequency parameter and resolution adaptive algorithm, resampling the well-processed signal, implementing a perception matching algorithm, and developing an adaptive model with a unified diagnose process. The proposed method shows superior performance compared to other state-of-art methods, especially in cases of fast speed changes.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Review
Engineering, Chemical
Junchao Xu, Yunfei Zhang, Jun Zhang, Haoxin Liu, Qianni Shao, Huaqiang Chu
Summary: Industrial processes release large amounts of fine particles, which pose a serious threat to human health globally. The heterogeneous condensation (HC) of water vapor is a superior method for the removal of fine particles due to its low cost, environmental friendliness, and high efficiency. This article summarizes the current status of HC for fine particle removal, explores ways to strengthen HC using various techniques, and discusses its potential applications in biomass combustion, iron and steel enterprises, and indoor air.
Article
Environmental Sciences
Yuelin Liu, Guangming Shi, Yu Zhan, Li Zhou, Fumo Yang
Summary: This study decomposed the spatial distribution of PM2.5 concentration in the Sichuan Basin into various patterns using EOF analysis. It found that anthropogenic emissions, meteorological conditions, and topography are the main factors influencing the distribution of PM2.5.
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Computer Science, Artificial Intelligence
Jianhua Dai, Ping Tan, Xing Yang, Lin Xiao, Lei Jia, Yongjun He
Summary: This paper proposes a new type of fuzzy adaptive ZNN model to solve the problem of time-variant linear matrix equations. The model demonstrates convergence and adaptability, and is able to achieve accelerated convergence to the theoretical solution within a finite time.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Engineering, Marine
Yang Liu, Nam-kyun Im, Qiang Zhang, Guibing Zhu
Summary: This paper investigates the automatic berthing problem of underactuated surface vessels in the case of uncertain dynamics and yaw rate limitation. It proposes the use of differential homeomorphism coordinate transformation, radial basis function network, and barrier Lyapunov function to solve the underactuation problem. It also applies dynamic surface control technology and minimum learning parameters to tackle differential explosion problems and computational complexity. Simulation results show that the proposed method effectively limits the yaw rate and solves the influence of model uncertainty.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Meteorology & Atmospheric Sciences
Tao Niu, Jizhi Wang, Yuanqin Yang, Yaqiang Wang, Cheng Chen
ADVANCES IN METEOROLOGY
(2017)
Article
Meteorology & Atmospheric Sciences
Junting Zhong, Xiaoye Zhang, Yaqiang Wang, Cheng Liu, Yunsheng Dong
ATMOSPHERIC RESEARCH
(2018)
Article
Environmental Sciences
Linchang An, Huizheng Che, Min Xue, Tianhang Zhang, Hong Wang, Yaqiang Wang, Chunhong Zhou, Hujia Zhao, Ke Gui, Yu Zheng, Tianze Sun, Yuanxin Liang, Enwei Sun, Hengde Zhang, Xiaoye Zhang
SCIENCE OF THE TOTAL ENVIRONMENT
(2018)
Article
Environmental Sciences
Jizhi Wang, Xiaoye Zhang, Duo Li, Yuanqin Yang, Junting Zhong, Yaqiang Wang, Haochi Che, Huizheng Che, Yangmei Zhang
SCIENCE OF THE TOTAL ENVIRONMENT
(2018)
Article
Meteorology & Atmospheric Sciences
Yangmei Zhang, Yaqiang Wang, Xiaoye Zhang, Xiaojing Shen, Junying Sun, Lingyan Wu, Zhouxiang Zhang, Haochi Che
JOURNAL OF METEOROLOGICAL RESEARCH
(2018)
Article
Meteorology & Atmospheric Sciences
Xuefei Qi, Junying Sun, Lu Zhang, Xiaojing Shen, Xiaoye Zhang, Yangmei Zhang, Yaqiang Wang, Haochi Che, Zhouxiang Zhang, Junting Zhong, Kaiyan Tan, Huarong Zhao, Sanxue Ren
JOURNAL OF METEOROLOGICAL RESEARCH
(2018)
Article
Chemistry, Multidisciplinary
Lihao Gao, Yu Zheng, Yaqiang Wang, Jiangjiang Xia, Xunlai Chen, Bin Li, Ming Luo, Yuchen Guo
Summary: A DNN model combining CNNs and CNN-BiConvLSTMs was proposed to address missing data in weather radar image sequences. The model outperformed baseline models under different missing patterns and showed minimal influence of data quality.
APPLIED SCIENCES-BASEL
(2021)
Article
Environmental Sciences
Yonghua Zhang, Shuoben Bi, Liping Liu, Haonan Chen, Yi Zhang, Ping Shen, Fan Yang, Yaqiang Wang, Yang Zhang, Shun Yao
Summary: This study proposes an alternative dual-polarization radar QPE algorithm based on deep learning, which outperforms traditional QPE algorithms, especially when the hourly rainfall intensity is less than 5 mm.
Article
Environmental Sciences
Hui Zhang, Yaqiang Wang, Dandan Chen, Dian Feng, Xiaoxiong You, Weichen Wu
Summary: Postprocess correction is crucial for improving model forecasting results, and machine learning methods are playing an increasingly important role. In this study, three machine learning methods (Linear Regression, LSTM-FCN, and LightGBM) were used to correct the temperature forecasting of the GRAPES-3km model. The evaluation results showed that all three methods performed well, with LightGBM achieving the highest forecast accuracy rate of above 84%.
Article
Environmental Sciences
Yu Zheng, Huizheng Che, Ke Gui, Xiangao Xia, Hujia Zhao, Lei Li, Lei Zhang, Xinglu Zhang, Hengheng Zhao, Yuanxin Liang, Hong Wang, Yaqiang Wang, Xiaoye Zhang
Summary: The Langley calibration method for Sun photometers at the MFYD Observatory in Beijing was assessed and verified, showing satisfactory results for atmospheric conditions, particularly in winter mornings. The aerosol optical depth results were validated against AERONET AOD, demonstrating good agreement and accuracy across different wavelengths.
Article
Environmental Sciences
Weichen Wu, Yaqiang Wang, Fengying Wei, Boqi Liu, Xiaoxiong You
Summary: This study uses deep learning to predict regional persistent extreme cold events by analyzing the low-frequency oscillation period and establishing the correlation between large-scale circulations and temperature, thereby improving the prediction accuracy for such events.
Article
Environmental Sciences
Tianze Sun, Huizheng Che, Bing Qi, Yaqiang Wang, Yunsheng Dong, Xiangao Xia, Hong Wang, Ke Gui, Yu Zheng, Hujia Zhao, Qianli Ma, Rongguang Du, Xiaoye Zhang
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2018)
Article
Environmental Sciences
Jizhi Wang, Yuanqin Yang, Xiaoye Zhang, Hua Liu, Huizheng Che, Xiaojing Shen, Yaqiang Wang
ATMOSPHERIC ENVIRONMENT
(2017)
Article
Environmental Sciences
Tingting Liu, Sunling Gong, Jianjun He, Meng Yu, Qifeng Wang, Huairui Li, Wei Liu, Jie Zhang, Lei Li, Xuguan Wang, Shuli Li, Yanli Lu, Haitao Du, Yaqiang Wang, Chunhong Zhou, Hongli Liu, Qichao Zhao
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2017)
Article
Environmental Sciences
Junting Zhong, Xiaoye Zhang, Yunsheng Dong, Yaqiang Wang, Cheng Liu, Jizhi Wang, Yangmei Zhang, Haochi Che
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2018)
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)
