Article
Computer Science, Interdisciplinary Applications
Sheen Mclean Cabaneros, Ben Hughes
Summary: The use of data-driven techniques, such as artificial neural network (ANN) models, for outdoor air pollution forecasting has been popular in the past two decades. However, research on the uncertainty surrounding the development of ANN models has been limited. This review outlines the approaches for addressing model uncertainty and reveals that input uncertainty has received the most attention, while structure, parameter, and output uncertainties have been less focused on. Ensemble approaches, particularly neuro-fuzzy networks, have been widely employed, but the direct measurement of uncertainty has received less attention. The study also suggests the need for development and application of approaches that can handle and quantify uncertainty in ANN model development.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Energy & Fuels
Enrico Prataviera, Jacopo Vivian, Giulia Lombardo, Angelo Zarrella
Summary: The energy consumption of cities is increasing rapidly due to global population growth and urbanization. Using Urban Building Energy Models (UBEMs) to simulate energy demand in different urban scenarios shows promise. However, uncertainty in input parameters and the lack of high-quality, open energy consumption data hinder the effective use of UBEMs. This study proposes a method that combines physics-based UBEMs with Uncertainty and Sensitivity Analysis to obtain reliable urban simulations, using aggregated energy use data from regional/national statistics.
Article
Mathematics
Venelin Todorov, Ivan Dimov
Summary: Currently, many regions have adopted strategies to limit and decrease air pollution levels across borders, with environmental protection being a global priority. Sensitivity analysis is crucial in validating air pollution models for accuracy and reliability. This study introduces two new digital sequences methods that significantly improve the measurement of sensitivity indices in digital ecosystems.
Article
Engineering, Multidisciplinary
Nima Pirhadi, Xusheng Wan, Jianguo Lu, Jilei Hu, Mahmood Ahmad, Farzaneh Tahmoorian
Summary: Liquefaction, a destructive phenomenon caused by earthquakes, has been studied extensively. In this study, two Artificial Neural Network (ANN) models were developed to estimate the liquefaction resistance of sandy soil. The models showed higher accuracy compared to previous models, and the fine content was identified as an important parameter affecting liquefaction resistance.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Environmental Sciences
Fan Yang, Chao Jia, Xiao Yang, Haitao Yang, Wenbo Chang
Summary: This study aims to assess the health threats, water quality, and hydrochemistry of groundwater in the Weibei Plain, northern China. The findings show that excessive geogenic fluoride and anthropogenic nitrate are prevalent in the groundwater, posing risks to human health. The study highlights the accuracy of stochastic simulation in assessing health risks.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Chemistry, Multidisciplinary
Alexandre S. Avaro, Juan G. Santiago
Summary: This article presents a quantification of the uncertainty in the experimental determination of kinetic rate parameters for enzymatic reactions. The authors examine several sources of uncertainty and bias and compute typical uncertainties of kcat, KM, and catalytic efficiency. The extraction of these parameters for CRISPR-Cas systems is analyzed as a salient example. Reports of enzymatic kinetic rates for CRISPR diagnostics have been highly unreliable and inconsistent.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2022)
Article
Thermodynamics
Mi Dong, Ya Li, Dongran Song, Jian Yang, Mei Su, Xiaofei Deng, Lingxiang Huang, M. H. Elkholy, Young Hoon Joo
Summary: This paper presents an analytical framework for uncertainty in the cost of wind power generation, improving cost prediction accuracy by considering inflation and the learning curve. The study finds that the scale parameter has the most significant impact on the levelized cost of energy, and a 38% margin is needed to ensure a 95% reliability for changes caused by uncertainty factors.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Engineering, Mechanical
Ruifeng Chen, Ying Min Low
Summary: In this study, a method for reducing the variance of Monte Carlo simulation estimator of fatigue damage is proposed, utilizing auto control variates technique, which successfully enhances efficiency. The method is unbiased, provides an error estimate, and the variance reduction is implemented at the post-processing stage.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Multidisciplinary
Changqi Luo, Behrooz Keshtegar, Shun Peng Zhu, Osman Taylan, Xiao-Peng Niu
Summary: This research introduces a novel enhanced MCS approach called HEMCS, which utilizes machine learning methods to achieve accurate approximation of failure probability with high-efficiency computations. The method offers higher flexibility and accuracy for predicting failure probability in various engineering problems, including laminated composite plates and turbine bladed disks.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Environmental Sciences
Mohammad Mehdi Riyahi, Hossien Riahi-Madvar
Summary: Detention rockfill dams are important in flood control projects due to their minimal technical requirement, low cost, minimal environmental side effects, and self-automotive operation process. However, reliable design of these dams is challenging due to the complexity of Non-Darcian flow interactions with stability and uncertainties of dam. This study examines the effects of uncertainties in probabilistic design of these dams and proposes a reliable design framework with a focus on stability analysis.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Mariia Kozlova, Robert J. Moss, Julian Scott Yeomans, Jef Caers
Summary: This paper introduces a framework for quantitative sensitivity analysis using the SimDec visualization method, and tests its effectiveness on decision-making problems. The framework captures critical information in the presence of heterogeneous effects, and enhances its practicality by introducing a formal definition and classification of heterogeneous effects.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Mathematics
Venelin Todorov, Slavi Georgiev, Ivan Georgiev, Snezhinka Zaharieva, Ivan Dimov
Summary: In this study, an advanced air pollution modeling approach incorporating stochastic techniques for large-scale simulations of long-range air pollutant transportation is proposed. The Unified Danish Eulerian Model (UNI-DEM) is utilized as a crucial mathematical framework with numerous applications in studying the detrimental effects of heightened air pollution levels. The proposed methodology employs a highly convergent quasi-Monte Carlo technique that relies on a unique symmetrization lattice rule, combining the concepts of special functions and optimal generating vectors to enhance the performance of calculating the Sobol sensitivity indices of the UNI-DEM model.
Article
Water Resources
Leining Liu, Jianhua Wu, Song He, Lei Wang
Summary: This study examined the spatial distribution of fluoride and manganese in groundwater and assessed overall groundwater quality using the entropy weight water quality index. Health risks associated with fluoride and manganese were evaluated through a Monte Carlo stochastic simulation method. The research found that groundwater quality is impacted by agricultural activities, industrial development, and local hydrogeological conditions, with children facing higher health risks compared to adults.
EXPOSURE AND HEALTH
(2022)
Article
Engineering, Marine
Ruifeng Chen, Ying Min Low
Summary: Accurate fatigue assessment is crucial in riser design and must consider various sea states. An efficient method based on time domain simulation, considering wave directionality, has been proposed to reduce computational cost.
Article
Nuclear Science & Technology
Joseph Konadu Boahen, Ahmed S. G. Khalil, Mohsen A. Hassan, Samir A. Elsagheer Mohamed
Summary: In this study, a simple Monte Carlo code, EJUSTCO, is developed for simulating gamma radiation transport in shielding materials, and a deep learning neural network is proposed to predict exponential transformation parameter. The developed code can be used to assess the performance of radiation shielding materials, and the validation results are consistent with theoretical, experimental, and literary results.
NUCLEAR SCIENCE AND TECHNIQUES
(2023)
Article
Engineering, Environmental
Meng Gao, Hongzhen Zheng
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2018)
Article
Meteorology & Atmospheric Sciences
Meng Gao, Ye Yang, Honghua Shi, Zhiqiang Gao
ATMOSPHERIC RESEARCH
(2019)
Article
Meteorology & Atmospheric Sciences
Ye Yang, Meng Gao, Naru Xie, Zhiqiang Gao
ATMOSPHERIC RESEARCH
(2020)
Article
Environmental Sciences
Ye Yang, Naru Xie, Meng Gao
Article
Environmental Sciences
Naru Xie, Yidi Sun, Meng Gao
Article
Meteorology & Atmospheric Sciences
Meng Gao, Yidi Sun, Qian Zheng
Summary: Extratropical cyclones over East Asia and Northwest Pacific were identified and tracked using an objective algorithm applied to ERA-Interim reanalysis data. The study found that ETC activities are mainly influenced by the West Pacific (WP) and Pacific/North American (PNA) patterns, with negligible impact from the Polar/Eurasia pattern. Composite analysis results supported the close associations of ETC activities with WP and PNA teleconnection patterns.
Article
Environmental Sciences
Yueqi Wang, Zhiqiang Gao, Jicai Ning
Summary: This study proposes an adaptive piecewise harmonic analysis method (AP-HA) to reconstruct multi-year seasonal data series, which introduces a cross-validation scheme to adaptively determine the optimal harmonic model and employs an iterative piecewise scheme to better track the local traits. When applied to the sea surface chlorophyll-a time series, the AP-HA method obtains reliable reconstruction results and outperforms conventional methods.
Article
Meteorology & Atmospheric Sciences
Meng Gao, Qian Zheng, Naru Xie
Summary: This study identified and tracked 215 continental ETCs crossing the Bohai Sea and Yellow Sea, classifying them into three groups based on their geographical positions of cyclogenesis and cyclone tracks. The first group consists of Mongolian cyclones, the second group mainly originates from the North China Plain and the leeside of the Loess Plateau, and the third group originates around southwest and central China. Despite different tracks, the surface impacts of ETCs in the second and third groups were similar.
Article
Engineering, Environmental
Meng Gao, Han Zhang, Aidi Zhang, Yueqi Wang
Summary: In this study, nonhomogeneous Poisson process (NHPP) models derived from extreme value theory were used to fit summer high temperature extremes (HTEs) in 321 meteorological stations across China. The seasonality and six notable atmospheric teleconnection patterns in the Northern Hemisphere were incorporated into the NHPP models to account for the non-stationarity of occurrence rate in HTEs. Additionally, a Poisson regression model was applied to establish the link between HTEs and these teleconnection patterns. The study identified the associations between HTEs and teleconnection patterns through both NHPP modeling and Poisson regression. Composite maps were constructed to illustrate the impacts of atmospheric circulation patterns on extreme heat events.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2022)
Article
Physics, Multidisciplinary
Meng Gao, Aidi Zhang, Han Zhang, Yufei Pang, Yueqi Wang
Summary: This study investigates the sea level rise using multifractal analysis, and discovers complex scaling behavior and spatial patterns. The multifractality of sea level changes can be partly explained by mechanisms such as thermal expansion, ocean currents shift, and river injections, all associated with global climate change.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Mathematics, Applied
Meng Gao, Ying Zhao, Zhen Wang, Yueqi Wang
Summary: A modified extreme event-based synchronicity measure that incorporates both positive and negative extreme events in climate anomalies is proposed in this study. The statistical significance of the measure is tested by Monte-Carlo simulations, and it is found to outperform the traditional event synchronicity measure. The modified measure can capture both synchronous and antisynchronous features between climate time series, and can be easily applied to other types of time series.
Article
Environmental Sciences
Haoyu Jiang, Jun Li, Jiaqi Wang, Hongxing Jiang, Yangzhi Mo, Jiao Tang, Ruijie Zhang, Wanwisa Pansak, Guangcai Zhong, Shizhen Zhao, Jicai Ning, Chongguo Tian, Gan Zhang
Summary: This study deployed PUF-PASs to monitor atmospheric monosaccharides and biomass burning-related biomarkers in the ICP and Southwest China, revealing fluctuations in BB emissions concentrations before and after the monsoon season. The importance of resolving MODIS unresolved fires for accurately estimating regional atmospheric pollutants was emphasized.
ENVIRONMENT INTERNATIONAL
(2022)
Article
Mathematics, Interdisciplinary Applications
Meng Gao, Aidi Zhang, Han Zhang, Yueqi Wang
Summary: The climate network is used to detect the existence and propagation of Rossby waves in the extratropics of global oceans, showing its potential in detecting oceanic dynamics.
JOURNAL OF COMPLEX NETWORKS
(2023)
Proceedings Paper
Ecology
Jicai Ning, Zhiqiang Gao, Maosi Chen
REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY XV
(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)