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Study of spatiotemporal variation and annual emission of CH_(4)in Shaoxing Yangtze River Delta,China,Using a portable CH4 detector on the UAV

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Journal of environmental Sciences 2025年第5期151卷 140-149页

作者： Xiaobing Pang Qianqian Shang Lang Chen Songhua Sun Gaosheng Zhao Zhentao Wu Canming Zhao Youhao Lu Qianqian Sun Yan Lyu Baozhen Wang College of Environment Zhejiang University of TechnologyHangzhou 310000China Shaoxing Institute of Zhejiang University of Technology Shaoxing 312000China Shaoxing Ecological and environmental monitoring center of Zhejiang province Shaoxing 312000China School of environmental and Chemical Engineering Shanghai UniversityShanghai 200444China Green Intelligence environmental School Yangtze Normal UniversityChongqing 408100China

Methane(CH_(4))is the second greenhouse gas and has a profound impact on global climate change due to its high global warming potential and *** 2022,the CH_(4)concentration was approximately 1.9 ppm,which was 264%of the pre-industrial *** spatiotemporal distribution of CH_(4)was investigated by a portable CH_(4)detector on an unmanned aerial vehicle and electric bicycles in Shaoxing,a city situated in the Yangtze River Delta,*** vertical distribution revealed CH_(4)concentration generally decreased slowly with ***,the inversion condition and low atmospheric boundary layer height(ABLH)leaded to the enhancement of CH_(4)with *** highest CH_(4)concentration(2.2±0.1 ppm,n=1428)was observed in winter and the lowest(2.0±0.2 ppm,n=1530)in *** the daily variation,CH_(4)concentration peaked at 5:00 local time(LT)and reached its lowest level at 14:00 LT,which was attributed to the daily variation of ABLH,lowest in the early morning and highest in the *** urban areas,CH_(4)concentrations showed higher levels near restaurants,natural gas stations and sewerage well,with a maximum value of 13.1 ppm,which was caused by CH_(4)emission and natural gas leakage from these *** annual CH_(4)emission in Shaoxing were estimated to be approximately 69 ton/(km^(2)·year)by the mass balance *** with other cities in the world,the CH_(4)emission is in higher level which imply some control measures should be conducted to reduce CH_(4)emission in Shaoxing.

关键词： Portable CH_(4)detector Spatiotemporal variation Annual CH_(4)emission Unmanned aerial vehicle

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Establishment and verification of anthropogenic speciated VOCs emission inventory of Central China

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Journal of environmental Sciences 2025年第3期149卷 406-418页

作者： Xuan Lu Dong Zhang Lanxin Wang Shefang Wang Xinran Zhang Yali Liu Keying Chen Xinshuai Song Shasha Yin Ruiqin Zhang Shanshan Wang Minghao Yuan College of Chemistry Zhengzhou UniversityZhengzhou 450001China Research Institute of environmental Sciences Zhengzhou UniversityZhengzhou 450001China School of Ecology and Environment Zhengzhou UniversityZhengzhou 450001China Zhengzhou Ecological Environment monitoring center of Henan province Zhengzhou 450000China

Improving the accuracy of anthropogenic volatile organic compounds(VOCs)emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air *** this study,an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan province at a 3 km×3 km spatial resolution based on the emission *** 2019 VOCs emission in Henan provincewas 1003.5 Gg,while industrial process source(33.7%)was the highest emission source,Zhengzhou(17.9%)was the city with highest emission and April and August were the months with the more *** VOCs emission regions were concentrated in downtown areas and industrial *** and aromatic hydrocarbons were the main VOCs contribution *** species composition,source contribution and spatial distribution were verified and evaluated through tracer ratio method(TR),Positive Matrix Factorization Model(PMF)and remote sensing inversion(RSI).Results show that both the emission results by emission inventory(EI)(15.7 Gg)and by TRmethod(13.6 Gg)and source contribution by EI and PMF are *** spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of *** verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.

关键词： VOCs verification Species composition Tracer ratio PMF Remote sensing inversion

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Exploring the HONO source during the COVID-19 pandemic in a megacity in China

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Journal of environmental Sciences 2025年第3期149卷 616-627页

作者： Mingkai Wang Shenbo Wang Ruiqin Zhang Minghao Yuan Yifei Xu Luqi Shang Xinshuai Song Xinyuan Zhang Yunxiang Zhang School of Ecology and Environment Zhengzhou UniversityZhengzhou 450000China Research Institute of environmental Sciences Zhengzhou UniversityZhengzhou 450000China Zhengzhou Ecological Environment monitoring center of Henan province Zhengzhou 450000China College of Chemistry Zhengzhou UniversityZhengzhou 450000China

HONO is a critical precursor of•OH,but its sources are controversial due to its complex formation *** study conducted comprehensive observations in Zhengzhou from April 26 to May 11,*** NO_(x)concentrations were observed during the Covid epidemic period(EP)(10.4±3.0 ppb),compared to the pre-epidemic period(PEP)(12.5±3.8 ppb).The mean HONO concentration during EP(0.53±0.34 ppb)was 0.09 ppb lower than that during PEP(0.62±0.53 ppb).The decrease in HONO concentration during EP came mainly at night due to the reduction in the direct emission(P_(emi))(0.03 ppb/hr),the homogeneous reaction between•OHandNO(P_(OH+NO))(0.02 ppb/hr),and the heterogeneous conversion of NO_(2)on the ground(0.01 ppb/hr).Notably,there was no significant change in daytime HONO *** daytime HONO budget indicated that the primary HONO sources during PEP were the nitrate photolysis(P_(nitrate)),followed by the P_(OH+NO),Pemi,the photo-enhanced reaction of NO_(2)on the ground(P_(ground+hv))and aerosol surface(Paerosol+hv).The primary HONO sources were Pnitrate,POH+NO,P_(emi),and_(Paerosol+hv)during EP,*** missing source has a high correlation with solar radiation,there might be other photo-related HONO sources or the contributions of photosensitized reactions were *** the extremely underestimated cases,HONO production rates fromthe P_(nitrate),P_(ground+hv),and Paerosol+hv increased by 0.17,0.10,and 0.10 ppb/hr during PEP,0.23,0.13,and 0.16 ppb/hr during EP,and P_(nitrate)was still the primary source during both PEP and EP.

关键词： Nitrous acid Nitrogen oxides COVID-19 HONO budget Unknown sources

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Distributions and risk assessment of heavy metals in solid waste in lead-zinc mining areas and across the soil, water body, sediment and agricultural product ecosystem in their surrounding areas

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China Geology 2025年第1期8卷 92-106页

作者： Zhi-qiang Wu Hai-ying Li Liu-yan Lü Guo-jun Liang Ting-ting Wu Jiang-xia Zhu No.117 Geological Team Bureau of Geology and Mineral Exploration and Development of Guizhou ProvinceGuiyang 550023China Ecological Environment monitoring center of Guizhou province Guiyang 550023China Guizhou Institute of Geological Survey Guiyang 550081China environmental Engineering Assessment center of Anshun City Anshun 561000China environmental Emergency center of Anshun City Anshun 561000China

To identify the root causes of heavy metal contamination in soils as well as prevent and control such contamination from its sources,this study explored the accumulation patterns and ecological risks of heavy metals like Cd and Pb in solid waste in mining areas and across the water body,sediment,soil and agricultural product ecosystem surrounding the mining *** on the residual solid waste samples in lead-zinc deposits in a certain area of Guizhou province,along with samples of topsoils,irrigation water,river sediments,and crops from surrounding *** study analyzed the distributions of eight heavy metals,i.e.,Cd,As,Cr,Hg,Pb,Zn,Cu,and Ni,in the samples through field surveys and sample ***,this study assessed the contamination levels and ecological risks of heavy metals in soils,sediments,and agricultural products using methods such as the single-factor index,Nemerow composite index,and potential ecological risk *** results indicate that heavy metals in the solid waste samples all exhibited concentrations exceeding their risk screening values,with 60%greater than their risk intervention *** soils and sediments demonstrate slight and moderate comprehensive ecological risks of heavy *** single-factor potential ecological risks of heavy metals in both the soil and sediment samples decreased in the order of Hg,Cd,Pb,As,Cu,Zn,Cr,and Ni,suggesting the same sources of heavy metals in the soils and *** of the agricultural product samples exhibited over-limit concentrations of heavy metals dominated by Cd,Pb,Ni,and Cr,excluding Hg and *** agricultural product assessment using the Nemerow composite index reveals that 35%of the agricultural product samples reached the heavy metal contamination level,implying that the agricultural products from farmland around the solid waste dumps have been contaminated with heavy *** eight heavy metals in the soil,sediment,and agricultural product samples manifested hig

关键词： Lead-zinc mining area Solid waste Soil Water body Sediment Agricultural product Nemerow composite index Cd,Pb,Ni,Cr elements Heavy metal contamination Ecological risk assessment Coefficients of variation(CVs) environmental restoration engineering

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High summer background O_(3)levels in the desert of northwest China

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Journal of environmental Sciences 2025年第5期151卷 516-528页

作者： Xinbing Ren Fang Wang Bayi Wu Shaoting Zhang Lei Zhang Xingjun Zhou Yuanzhe Ren Yongjing Ma Feng Hao Yongli Tian Jinyuan Xin Key Laboratory of Atmospheric Environment and Extreme Meteorology Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry(LAPC) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China Inner Mongolia environmental monitoring center Alashan Substation 750300China Inner Mongolia environmental monitoring center Hohhot 010011China Laboratory for Supervision and Evaluation of Pollution Reduction and Carbon Reduction in Arid and Semi-Arid Regions Inner Mongolia Environmental Monitoring CenterHohhot 010011China

Generally speaking,the precursors of ozone(O_(3)),nitrogen oxides and volatile organic compounds are very low in desert areas due to the lack of anthropogenic emissions and natural emissions,and thus O_(3)concentrations are relatively ***,high summer background concentrations of about 100μg/m^(3)or 60 ppb were found in the Alxa Desert in the highland of northwest China based on continuous summer observations from 2019 to 2021,which was higher than the most of natural background areas or clean areas in world for summer O_(3)background *** high O_(3)background concentrations were related to surface features and ***-intensity anthropogenic activity areas in desert areas can cause increased O_(3)concentrations or pollution,but also generated O_(3)depleting substances such as nitrous oxide,which eventually reduced the regional O_(3)baseline *** dioxide(NO2)also had a dual effect on O_(3)generation,showing promotion at low concentrations and inhibition at high *** addition,sand-dust weather reduced O_(3)clearly,but O_(3)eventually stabilized around the background concentration values and did not vary with sand-dust particulate matter.

关键词： Alxa Desert O_(3)background concentration Anthropogenic effect Sand-dust weather Northwest China

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High-resolution Simulation Dataset of Hourly PM_(2.5)Chemical Composition in China(CAQRA-aerosol)from 2013 to 2020

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Advances in Atmospheric Sciences 2025年第4期42卷 697-712页

作者： Lei KONG Xiao TANG Jiang ZHU Zifa WANG Bing LIU Yuanyuan ZHU Lili ZHU Duohong CHEN Ke HU Huangjian WU Qian WU Jin SHEN Yele SUN Zirui LIU Jinyuan XIN Dongsheng JI Mei ZHENG Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China China National environmental monitoring Centre Beijing 100012China Guangdong Ecological Environment monitoring Centre Guangzhou 510308China Wuhan environmental monitoring Centre Hubei 430015China Hubei province Academy of Eco-environmental Sciences Hubei 430072China Peking University Beijing 100871China

Scientific knowledge on the chemical compositions of fine particulate matter(PM_(2.5)) is essential for properly assessing its health and climate effects,and for decisionmakers to develop efficient mitigation strategies.A high-resolution PM_(2.5) chemical composition dataset(CAQRA-aerosol)is developed in this study,which provides hourly maps of organic carbon,black carbon,ammonium,nitrate,and sulfate in China from 2013 to 2020 with a horizontal resolution of 15 *** paper describes the method,access,and validation results of this *** shows that CAQRA-aerosol has good consistency with observations and achieves higher or comparable accuracy with previous PM_(2.5) composition *** on CAQRA-aerosol,spatiotemporal changes of different PM_(2.5) compositions were investigated from a national viewpoint,which emphasizes different changes of nitrate from other *** estimated annual rate of population-weighted concentrations of nitrate is 0.23μg m^(−3)yr^(−1) from 2015 to 2020,compared with−0.19 to−1.1μg m^(−3)yr^(−1) for other *** whole dataset is freely available from the China Air Pollution Data center(https://***/10.12423/capdb_***).

关键词： PM_(2.5)composition dataset black carbon organic carbon ammonium nitrate sulfate

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Advances in regional-scale crop growth and associated process modeling

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Science China Earth Sciences 2025年第3期68卷 653-668页

作者： Wenfeng LIU Yawei BAI Taisheng DU Mengxue LI Hong YANG Shichao CHEN Chuanbin LIANG Shaozhong KANG State Key Laboratory of Efficient Utilization of Agricultural Water Resources China Agricultural University National Field Scientific Observation and Research Station on Efficient Water Use of Oasis Agriculture in Wuwei of gansu province center for Agricultural Water Research in China China Agricultural University 2w2e environmental Consulting GmbH

In the context of global change, ensuring national food security and achieving sustainable development of agricultural production systems have become major challenges worldwide. To address these issues, regional-scale crop growth and associated process(CROP-AP) models, with their robust simulation and predictive capabilities, have emerged as important tools for studying a wide range of issues relating to agricultural production at river basin, national, and even global scales. Here, we provide a systematic review of the advances of regional-scale CROP-AP models. First, regional-scale CROP-AP models are categorized based on model characteristics: statistical models, crop growth models, hydrology-crop coupling models, and ecosystem models. The origin, development, principle, structure, and application of each model type are introduced. Then, the main functions of regional-scale CROP-AP models are critically reviewed from five aspects: crop yield prediction, crop water consumption, agricultural non-point source pollution, greenhouse gas emissions, and climate change impact and ***, the future development trends and research priorities of regional-scale CROP-AP models are explored from six key perspectives: model validation and calibration, the ability to simulate the coupling of crop physiology and human activities,enhancing model scalability, multi-model ensembles, data and code sharing, and the integration of artificial intelligence. This review aims to provide comprehensive references and insights for the further development and application of large-scale, high-precision CROP-AP models.

关键词： Regional scale Crop model Biophysical processes Model functions Global change

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Development of an automated photolysis rates prediction system based on machine learning

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Journal of environmental Sciences 2025年第5期151卷 211-224页

作者： Weijun Pan Sunling Gong Huabing Ke Xin Li Duohong Chen Cheng Huang Danlin Song State Key Laboratory of Severe Weather&Key Laboratory of Atmospheric Chemistry of CMA Chinese Academy of Meteorological SciencesBeijing 100081China College of environmental Sciences and Engineering Peking UniversityBeijing 100871China State environmental Key Laboratory of Reginal Air Quality monitoring Guangdong Ecological Environmental Monitoring CenterGuangzhou 510308China State environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex Shanghai Academy of Environmental SciencesShanghai 200233China Chengdu Academy of environmental Sciences Chengdu 610072China National Observation and Research Station of Coastal Ecological Environments in Macao Macao Environmental Research InstituteMacao University of Science and TechnologyMacao 999078China

Based on observed meteorological elements,photolysis rates(J-values)and pollutant concentrations,an automated J-values predicting system by machine learning(J-ML)has been developed to reproduce and predict the J-values of O^(1)D,NO_(2),HONO,H_(2)O_(2),HCHO,and NO_(3),which are the crucial values for the prediction of the atmospheric oxidation capacity(AOC)and secondary pollutant concentrations such as ozone(O_(3)),secondary organic aerosols(SOA).The J-ML can self-select the optimal“Model+Hyperparameters”without human *** evaluated results showed that the J-ML had a good performance to reproduce the J-values wheremost of the correlation(R)coefficients exceed 0.93 and the accuracy(P)values are in the range of 0.68-0.83,comparing with the J-values from observations and from the tropospheric ultraviolet and visible(TUV)radiation model in Beijing,Chengdu,Guangzhou and Shanghai,*** hourly prediction was also well performed with R from 0.78 to 0.81 for next 3-days and from 0.69 to 0.71 for next 7-days,*** with O_(3)concentrations by using J-values from the TUV model,an emission-driven observation-based model(e-OBM)by using the J-values from the J-ML showed a 4%-12%increase in R and 4%-30%decrease in ME,indicating that the J-ML could be used as an excellent supplement to traditional numerical *** feature importance analysis concluded that the key influential parameter was the surface solar downwards radiation for all J-values,and the other dominant factors for all J-values were 2-m mean temperature,O_(3),total cloud cover,boundary layer height,relative humidity and surface pressure.

关键词： J-values Automated prediction system Machine learning Short-term prediction O_(3) simulated improvement

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Chemical characteristics and sources apportionment of volatile organic compounds in the primary urban area of Shijiazhuang,North China Plain

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Journal of environmental Sciences 2025年第3期149卷 465-475页

作者： Xiao Zhang Junfeng Wang Jiangwei Zhao Junliang He Yali Lei Kai Meng RuiWei Xue Zhang Miaomiao Zhang Shuangying Ni Eleonora Aruffo College of geographical sciences and Environment Shijiazhuang UniversityShijiazhuang 050035China Jiangsu Key Laboratory of Atmospheric Environment monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science and TechnologyNanjing 210044China Hebei province Ecology environmental monitoring center Shijiazhuang 050037China Key Lab of Geographic Information Science of the Ministry of Education School of Geographic SciencesEast China Normal UniversityShanghai 200241China Hebei Provincial Institute of Meteorological Sciences Shijiazhuang 050021China Key Laboratory of Meteorology and Ecological Environment of Hebei province Shijiazhuang 050021China Hebei Provincial Academy of Ecological environmental Science Shijiazhuang 050037China Department of Advanced Technologies in Medicine&Dentistry University“G.d’Annunzio”of Chieti-PescaraChieti 66100Italy center for Advanced Studies and Technology-CAST Chieti 66100Italy

VOCs(Volatile organic compounds)exert a vital role in ozone and secondary organic aerosol production,necessitating investigations into their concentration,chemical characteristics,and source apportionment for the effective implementation of measures aimed at preventing and controlling atmospheric *** to October 2020,onlinemonitoringwas conducted in the main urban area of Shijiazhuang to collect data on VOCs and analyze their concentrations and ***,the PMF(positive matrix factorization)method was utilized to identify the VOCs *** indicated that the TVOCs(total VOCs)concentration was(96.7±63.4μg/m^3),with alkanes exhibiting the highest concentration of(36.1±26.4μg/m^3),followed by OVOCs(16.4±14.4μg/m^3).The key active components were alkenes and aromatics,among which xylene,propylene,toluene,propionaldehyde,acetaldehyde,ethylene,and styrene played crucial roles as reactive *** sources derived from PMF analysis encompassed vehicle emissions,solvent and coating sources,combustion sources,industrial emissions sources,as well as plant sources,the contribution of which were 37.80%,27.93%,16.57%,15.24%,and 2.46%,***,reducing vehicular exhaust emissions and encouraging neighboring industries to adopt low-volatile organic solvents and coatings should be prioritized to mitigate VOCs levels.

关键词： Volatile organic compounds Pollution characteristics Ozone formation potential OH radical loss rate Source apportionment

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A comparative study on the formation of nitrogen-containing organic compounds in cloud droplets and aerosol particles

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Journal of environmental Sciences 2025年第3期149卷 456-464页

作者： Guohua Zhang TaoWang Qinhao Lin Kun Liu Wei Sun Duohong Chen Lei Li Xinming Wang Xinhui Bi State Key Laboratory of Organic Geochemistry and Guangdong Provincial Key Laboratory of environmental Protection and Resources Utilization Guangzhou Institute of GeochemistryChinese Academy of Sciences(CAS)Guangzhou 510640China Guangdong-Hong Kong-Macao Joint Laboratory for environmental Pollution and Control Guangzhou Institute of GeochemistryCASGuangzhou 510640China University of Chinese Academy of Sciences Beijing 100049China School of environmental Science and Engineering Institute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China State environmental Protection Key Laboratory of Regional Air Quality monitoring Guangdong Environmental Monitoring CenterGuangzhou 510308China Institute of Mass Spectrometer and Atmospheric Environment Jinan UniversityGuangzhou 510632China

Nitrogen-containing organic compounds(NOCs)may potentially contribute to aqueous secondary organic aerosols,yet the different formation of NOCs in aerosol particles and cloud droplets remains *** the in-situ measurements performed at a mountain site(1690 m a.s.l.)in southern China,we investigated the formation of NOCs in the cloud droplets and the cloud-free particles,based on their mixing state information of NOCscontaining particles by single particle mass *** relative abundance of NOCs in the cloud-free particles was significantly higher than those in cloud residual(cloud RES)*** were highly correlated with carbonyl compounds(including glyoxalate and methylglyoxal)in the cloud-free particles,however,limited correlation was observed for cloud RES *** of their mixing state and temporal variations highlights that NOCs was mainly formed from the carbonyl compounds and ammonium in the cloud-free particles,rather than in the cloud RES *** results support that the formation of NOCs from carbonyl compounds is facilitated in concentrated solutions in wet aerosols,rather than cloud *** addition,we have identified the transport of biomass burning particles that facilitate the formation of NOCs,and that the observed NOCs is most likely contributed to the light *** findings have implications for the evaluation of NOCs formation and their contribution to light absorption.

关键词： Nitrogen-containing organic compounds Individual particles Cloud Carbonyl compounds Mixing state

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