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Hydrochemistry characteristics and genesis of shallow groundwater in diverse industrial agglomeration areas in typical alluvial plain of the Yellow River

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Science of the Total Environment 2025年 958卷 177764页

作者： Zhang, Fan Yuan, Ying Xi, Beidou Lu, Haojie Jiang, Yu Hui, Kunlong Tan, Wenbing Wang, Hui Meng, Fanhua State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution Chinese Research Academy of Environmental Sciences Beijing100012 China

The groundwater environment in the middle and upper reaches of the Yellow River in China has attracted extensive attention. But, the hydrochemistry characteristics and genesis of shallow groundwater in diverse industrial agglomeration areas in typical alluvial plain of the Yellow River are still unknown. In this study, geochemical analysis methods, the positive matrix factorisation model, and the geodetector model were used to multidimensional analyze. The results showed that 78 % of the groundwater samples had high-alkalinity-risk and high-salinity-risk, and the water quality was poor and unsuitable for irrigation. "Very poor" and "undrinkable" samples accounted for 26.31 %. The weathering of calcium magnesium minerals and the dissolution of soluble sulfate were important sources of the main chemical components of the groundwater. However, evaporation and concentration gradually dominated from the inclined plain of the piedmont to the alluvial plain of the Yellow River. Domestic and agricultural activities were important sources of nitrogen species (NO3−, NO2−, and NH4+). The presence of Al, Mn, Zn, and Pb was caused by the production activities of various enterprises. The pollution contributors of natural sources, domestic and agricultural activities, industrial production and other sources were 29.49 %, 17.05 %, 31.41 %, and 22.05 %, respectively. Groundwater velocity and enterprise type were the main factors driving groundwater pollution by these four metal substances. The interaction between enterprise type and groundwater velocity had the greatest influence on the concentrations of Al, Mn, and Zn. Moreover, the interaction between enterprise type and the distance from enterprise had the greatest influence on Pb levels. Overall, groundwater pollution in the study area was the result of both natural and human factors. The findings of this study can offer valuable insights and theoretical support for preventing groundwater pollution in other industrial agglomerat

关键词： Groundwater geochemistry

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Corrigendum to "Landscape ecological risk assessment and driving factors analysis based on optimal spatial scales in Luan River Basin, China" [Ecol. Indic. 169 (2024) 112821] (Ecological Indicators (2024) 169, (S1470160X24012780), (10.1016/***.2024.112821))

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Ecological Indicators 2025年 173卷

作者： Yang, Nijuan Zhang, Ting Li, Jianzhu Feng, Ping Yang, Nina State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation Tianjin University Tianjin300350 China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China

The authors regret "the incorrect use of Figure 1 in the paper. The original figure has now been replaced with the revised figure."[Figure presented] Revised Figure 1 The authors would like to apologise for ...

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Technology pathway to decarbonisation in the building sector based on a policy review of major economies

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Advances in Climate Change Research 2025年第1期16卷 183-198页

作者： Jie XIONG Si-Yue GUO Xian ZHANG Run-Ming YAO Pan-Yu ZHU Xue-Ting PENG Nian YANG Ya-Ting ZHANG Mai SHI Xi LU School of Environment State Key Joint Laboratory of Environment Simulation and Pollution ControlTsinghua UniversityBeijing 100084China School of Architecture and Urban Planning Chongqing Jiaotong UniversityChongqing 400074China Institute for Energy Environmental&EconomyTsinghua UniversityBeijing 100084China The Administrative Centre for China’s Agenda 21(ACCA21) Ministry of Science and Technology(MOST)Beijing 100038China School of the Built Environment University of ReadingReading RG66DFUnited Kingdom Joint International Research Laboratory of Green Buildings and Built Environments(Ministry of Education) Chongqing UniversityChongqing 400045China Synavision GmbH Bielefeld 33602Germany Beijing Laboratory of Environmental Frontier Technologies Tsinghua UniversityBeijing 100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing 100084China

Building decarbonisation is crucial to achieve the carbon neutrality *** many studies have been conducted,a gap remains in the research concerning technology development and policy *** study conducted a comprehensive review of the decarbonisation pathways proposed by the ten largest economies globally for the building sector at the national *** synthesising the relevant literature,a systemic framework of technologies applicable to the building sector is proposed,encompassing five major categories of technologies:energy efficiency,electrification and clean heating,on-site generation and flexible utilisation,green construction materials and processes,and sufficiency in operation and *** overview of each country’s emphasis on technological development,future expectations and prevailing trends in technology deployment is summarised and *** countries'policy documents address energy efficiency,electrification,and clean heating;however,the importance of flexibility and sufficiency warrants further *** balance among different technologies,the impacts of lock-in effects,and the considerations of equity and justice in renovation processes are critical concerns for the future deployment of *** study can provide a meaningful reference for the following research phase and the development of pathways to decarbonise buildings for countries worldwide.

关键词： Decarbonisation Building sector Carbon neutrality Pathway Framework of technologies

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Ultrahigh alkali resistance and regeneration capacity of the birnessite deNOx catalysts: A recyclable extraction-insertion strategy

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Separation and Purification Technology 2025年 368卷

作者： Xuan, Yue Zhu, Xiao Wang, Bin Liang, Yanjie Gao, Chuan Li, Bing Wang, Dong Peng, Yue School of Energy and Power Engineering Shandong University Shandong Jinan250061 China State Key Joint Laboratory of Environment Simulation and Pollution Control National Engineering Laboratory for Multi Flue Gas Pollution Control Technology and Equipment School of Environment Tsinghua University Beijing100084 China

The selective catalytic reduction (SCR) of NOx with NH3 in biomass combustion flue gas confronts high-concentration alkali metal (K) poisoning. Herein, we propose a recyclable extraction-insertion strategy using acid-treated birnessite-based catalysts to achieve high alkali resistance. Compared to commercial MnO2 catalyst, which suffered severe deactivation after 1 wt% K+ poisoning, the OL-1(H) catalyst showed a surprising enhancement in SCR activity by 1 wt% K+ and only a modest 15.5 % decrease in NOx conversion at 225 °C with 7 wt% K+. Physicochemical characterizations and density functional theory calculations revealed that K+ deposition form K2O on the surface of commercial MnO2, disrupting Mn-O active sites. In contrast, K+ tended to migrate from the outer surface into the interlayer, spontaneously exchanging with H+ in the OL-1(H) catalyst. The inserted K+ coordinated with six O2–, attracting surrounding electron clouds and facilitating electron loss from Mn species with unsaturated outer coordination. This resulted in an enrichment of Mn5c4+-Lewis acid sites, enhancing NH3 adsorption and activation, thereby improving NOx removal via the Eley-Rideal (E-R) mechanism. Equally important, the extraction-insertion process between H+ and K+ further regenerated the K-poisoned catalyst efficiently, restoring the NOx conversion by 23.3 % at 150 °C. The recyclable extraction-insertion strategy provides a new paradigm for designing catalysts with ultrahigh alkali resistance and regeneration capacity, applicable across various environmental fields. © 2025

关键词： Nitrogen oxides

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Assessing the Significance of Regional Transport in Ozone pollution through Machine Learning: A Case Study of Hainan Island

ACS ES&T Air

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ACS ES&T Air 2025年第3期2卷 416-425页

作者： Jun Liu Meiru Chen Biwu Chu Tianzeng Chen Qingxin Ma Yonghong Wang Peng Zhang Hao Li Bin Zhao Rongfu Xie Qing Huang Shuxiao Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China；University of Chinese Academy of Sciences Beijing 100049 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China；Center for Excellence in Regional Atmospheric Environment Institute of Urban Environment Chinese Academy of Sciences Xiamen 361021 China；University of Chinese Academy of Sciences Beijing 100049 China School of Environment Tsinghua University Beijing 100084 China College of Ecology and Environment Hainan University Haikou 570228 China；Hainan Research Academy of Environmental Sciences Haikou 571126 China School of Environmental Science and Engineering Hainan University Haikou 570228 China

Regional transport of air pollutants is a serious challenge to outdoor O3pollution control. Characterizing the transport of air pollutants by traditional air quality models heavily relies on accurate precursor emission inventories, chemical reaction mechanisms, and meteorological factors. In this study, the pollutant concentrations of upwind cities were incorporated as features into a random forest regression model (Traj-RF) to investigate the contribution of regional transport to local O3pollution. Hainan island was selected as the target area in this study, due to its air quality being affected significantly by regional transport. The Traj-RF model shows good predictive performance for O3with a coefficient of determination (R2) of 0.68 on the independent test set based on only observed air pollutants concentrations and meteorological data. The results of the Traj-RF model show that direct O3transport from upwind areas contributes approximately 27.5% to the O3concentration in Hainan, effectively highlighting the substantial role of regional transport in Hainan’s O3pollution. This refined machine learning method may have the potential to assess the impact of pollutant transport on regional air quality.

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Deciphering environmental factors influencing phytoplankton community structure in a polluted urban river

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Journal of environmental Sciences 2025年第2期148卷 375-386页

作者： Xiaxia Li Kai Chen Chao Wang Tianyu Zhuo Hongtao Li Yong Wu Xiaohui Lei Ming Li Bin Chen Beibei Chai School of Water Conservancy and Hydroelectric Power Hebei University of EngineeringHandan 056038China Collaborative Innovation Center for Intelligent Regulation and Comprehensive Management of Water Resources School of Water Conservancy and HydroelectricHebei University of EngineeringHandan 056038China Hebei Key Laboratory of Intelligent Water Conservancy Hebei University of EngineeringHandan 056038China Tianjin Water Group Binhai Water Co. Ltd.Tianjin 300308China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower ResearchBeijing 100038China School of Architecture and Civil Engineering Xi’an University of Science and TechnologyXi’an 710054China Chengdu University of Technology Chengdu 610059China College of Natural Resources and Environment Northwest A&F UniversityYangling 712100China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentBeijing Normal UniversityBeijing 100875China

Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River—which is the longest river in *** phytoplankton are sensitive indicators of trophic changes inwater bodies,characterizing phytoplankton communities and their growth influencing factors in polluted urban rivers can provide new ideas for pollution ***,we used direct microscopic count and environmental DNA(eDNA)metabarcoding methods to investigate phytoplankton community structure in Tuojiang River Basin(Chengdu,Sichuan Province,China).The association between phytoplankton community structure and water environmental factors was evaluated by Mantel *** environmental monitoring data were used to pinpoint major factors that influenced phytoplankton growth based on structural equation *** the phylum level,the dominant phytoplankton taxa identified by the conventional microscopic method mainly belonged to Bacillariophyta,Chlorophyta,and Cyanophyta,in contrast with Chlorophyta,Dinophyceae,and Bacillariophyta identified by eDNA ***α-diversity analysis,eDNA metabarcoding detected greater species diversity and achieved higher precision than the microscopic *** growth was largely limited by phosphorus based on the nitrogen-to-phosphorus ratios>16:1 in all water *** analysis and structural equation modeling also confirmed that the nitrogen-to-phosphorus ratio was the principal factor influencing phytoplankton *** results could be useful for implementing comprehensive management of the river basin *** is recommended to control the discharge of point-and surface-source pollutants and the concentration of dissolved oxygen in areas with excessive nutrients(e.g.,Jianyang-Ziyang).Algae monitoring techniques and removal strategies should be improved in 201 Hospital,Hongrihe Bridge and Colmar Town areas.

关键词： environmental DNA Microscopic count Phytoplankton growth Structural equation modeling Tuojiang River Basin

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Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

ACS ES&T Air

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ACS ES&T Air 2025年第2期2卷 249-263页

作者： Yicong He Kelsey R. Bilsback Manish Shrivastava Rahul A. Zaveri John E. Shilling John H. Seinfeld Bin Zhao Shuxiao Wang Christopher D. Cappa Jeffrey R. Pierce Shantanu H. Jathar Department of Mechanical Engineering Colorado State University Fort Collins Colorado 80523 United States；State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing 100084 China；State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China Department of Mechanical Engineering Colorado State University Fort Collins Colorado 80523 United States；PSE Healthy Energy Oakland California 94612 United States Pacific Northwest National Laboratory Richland Washington 99354 United States Divison of Chemistry and Chemical Engineering California Institute of Technology Pasadena California 91125 United States State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing 100084 China；State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China Department of Atmospheric Science Colorado State University Fort Collins Colorado 80521 United States Department of Civil and Environmental Engineering University of California Davis Davis California 95616 United States Department of Mechanical Engineering Colorado State University Fort Collins Colorado 80523 United States

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, aqueous chemistry, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of 4 in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). In addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol number size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model.

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Impact of Mixed Benzene Site Exposure on Bioaccessibility in Simulated Lung Fluids and Health Risk Assessment

SSRN

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SSRN 2025年

作者： Ma, Xuemin Wang, Ying Chen, Shuhe Wu, Changyong Wang, Weipeng Wang, Yue Engineering Research Center of Environmental Pollution Control Chinese Research Academy of Environmental Sciences Beijing100012 China State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China State Key Laboratory of Environmental Criteria and Risk Assessment State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution Chinese Research Academy of Environmental Sciences Beijing100012 China College of Urban and Rural Construction Agricultural University of Hebei Baoding071001 China

Benzene, toluene, ethylbenzene, and xylenes (BTEX) are major volatile organic compounds (VOCs) associated with petroleum production, posing significant health risks via inhalation. Conventional risk assessments primarily focus on single-compound or single-concentration exposures, overlooking the complex mixed-exposure scenarios prevalent at contaminated sites. This study refines health risk assessment frameworks by incorporating bioaccessibility-driven indices for inhalation exposure. Using a membrane oxygenator system, benzene and ethylbenzene were evaluated as representative pollutants under single and mixed exposures at low (5 mg/kg), medium (10 mg/kg), and high (20 mg/kg) concentrations. Results revealed significantly enhanced bioaccessibility of benzene and ethylbenzene in simulated lung fluid under mixed exposure compared to single exposure (P © 2025, The Authors. All rights reserved.

关键词： Lung cancer

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Historical inventories and future scenarios of multiple hazardous air pollutants (HAPs) emissions from the iron and steel production industry in China

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Science of the Total Environment 2025年 958卷 178051页

作者： Yang, Junqi Tian, Hezhong Fu, Zhiqiang Bai, Xiaoxuan Wang, Kun Liu, Wenjun Lu, Yiping Zhou, Yu Zhao, Hongyan Cui, Jiangyu Du, Qinwei State Key Joint Laboratory of Environmental Simulation & Pollution Control School of Environment Beijing Normal University Beijing100875 China Center for Atmospheric Environmental Studies Beijing Normal University Beijing100875 China Beijing100045 China Institute of Urban Safety and Environmental Science Beijing Academy of Science and Technology Beijing100054 China

Iron and steel production (ISP) is one of significant atmospheric pollution emission sources in China. With the implementation of ultra-low emission (ULE) standards, a detailed and new updated emission inventory is urgently needed for better understanding of the temporal trends and spatial variation of emission characteristics. In this study, a unit-based comprehensive emission inventory of multiple hazardous air pollutants (HAPs) for the Chinese ISP spanned from 2012 to 2021, including the conventional pollutants, 13 kinds of Trace elements as well as 2 unconventional but toxic pollutants (PCDD/Fs, F), was dedicatedly developed by integrating dynamic localized emission factors with unit-based information of both the detailed activity level and abatement technology application. Scenario analyses were also conducted to forecast future emission trends up to 2050. The results showed that the lower emission factors owing to ULE retrofits had resulted in different spatial-temporal emission characteristics between outputs and HAPs emissions. The atmospheric emissions of SO2, NOX, PM2.5, PM10, TSP, F and PCDD/Fs from Chinese ISP in 2021 were estimated at about 414.4, 450.5, 1044.3, 2001.6, 3958.8, 9.42 kt and 9.35 kg-TEQ, respectively. And most HAPs emissions were lower than those in 2012. Regarding the spatial distribution, Hebei, Jiangsu, Shanxi, ranked as the top 3 emission provinces. Moreover, different manufacturing processes (sintering, blast furnace, steel making, etc.) contributed with different magnitude for specific species, and the future trends estimation showed a great reducing potential caused by the implementation of ULE abatement measures and structure adjustment in future. © 2024 Elsevier B.V.

关键词： Iron and steel industry

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Long-term effects of PM2.5 constituents on childhood attention deficit hyperactivity disorder: evidence from a large population-based study in the Pearl River Delta Region, China

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environmental Research 2025年 277卷 121641页

作者： Zeng, Hui-Xian Meng, Wen-Jie Zeng, Qing-Guo Wei, Jing Liu, Lu-Sheng Wu, Qi-Zhen Zhao, Bin Oudin, Anna Yang, Mo Jalava, Pasi Dong, Guang-Hui Zeng, Xiao-Wen Joint International Research Laboratory of Environment and Health Ministry of Education Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment Department of Occupational and Environmental Health School of Public Health Sun Yat-sen University Guangzhou510080 China Department of Atmospheric and Oceanic Science Earth System Science Interdisciplinary Center University of Maryland College ParkMD United States State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China Department of Public Health and Clinical Medicine Umeå University Umeå Sweden Department of Environmental and Biological Science University of Eastern Finland Kuopio Finland

Background: Evidence linking fine particulate matter (PM2.5) constituents to childhood attention deficit hyperactivity disorder (ADHD) was limited. Objectives: To investigate the individual and joint effects of exposure to PM2.5 constituents on ADHD. Methods: We conducted a large population-based survey involving 110,818 school children aged 6–18 years across six cities in the Pearl River Delta region, China. The three-year average concentrations of PM2.5 constituents (black carbon (BC), organic matter (OM), sulfate, nitrate, and ammonium) were estimated using the ChinaHighAirPollutants dataset. Parents completed an ADHD checklist using the Diagnostic and Statistical Manual of Mental Disorders-IV criteria. The individual and joint associations between PM2.5 components and ADHD were estimated using generalized linear mixed models and the quantile g-computation regression model, respectively. Results: The exposure-response relationships between PM2.5 constituents and ADHD primarily exhibited a nonlinear pattern. Compared with the lowest tertile, the highest tertiles of PM2.5 and its components were linked to greater odds for ADHD (e.g., the adjusted odds ratio (OR) was 1.37 (95 % confidential interval (CI): 1.27, 1.47) for PM2.5, 1.51 (95 %CI: 1.40, 1.63) for OM, 1.29 (95 %CI: 1.20, 1.39) for BC, and 1.20 (95 %CI:1.08, 1.34) for sulfate). Similar positive associations were observed between BC and sulfate exposure and ADHD subtypes. Moreover, joint exposure to PM2.5 components was associated with ADHD (OR = 1.14, 95 % CI:1.10, 1.18), with OM and BC contributing more to the observed associations. Conclusions: These findings highlight the varying contributions of PM2.5 constituents to ADHD and underscore the importance of reducing specific PM2.5 component emissions to mitigate the burden of PM2.5-associated neurodevelopmental diseases. © 2025 Elsevier Inc.

关键词： Regression analysis

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