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Engineering 2024年第7期38卷 184-193页

作者： Li Chen Gong Zhang Huijuan Liu Shiyu Miao Qingbai Chen Huachun Lan Jiuhui Qu center for water and ecology State Key Joint Laboratory of Environment Simulation and Pollution ControlSchool of EnvironmentTsinghua UniversityBeijing 100084China

Efficient metal recovery from industrial wastewater facilitates addressing of the environmental hazards and resource requirements of heavy *** conventional electrodeposition recovery method is hampered by the limitations of interfacial ion transport in charge-transfer reactions,creating challenges for simultaneous rapid and high-quality metal ***,we proposed integrating a transient electric field(TE)and swirling flow(SF)to synchronously enhance bulk mass transfer and promote interfacial ion *** investigated the effects of the operation mode,transient frequency,and flow rate on metal recovery,enabling determination of the optimal operating conditions for rapid and efficient sequential recovery of Cu in TE&SF *** conditions included low and high electric levels of 0 and 4 V,a 50%duty cycle,1 kHz frequency,and 400 L·h^(-1)flow *** kinetic coefficients of TE&SF electrodeposition were 3.5-4.3 and 1.37-1.97 times that of single TE and SF electrodeposition,*** the deposition process under TE and SF conditions confirmed the efficient concurrence of interfacial ion transport and charge transfer under TE and SF synergy,which achieved rapid and highquality metal ***,the combined deposition strategy is considered an effective technique for reducing metal pollution and promoting resource recycling.

关键词： Ion transport Reaction kinetics Transient electric field Swirling flow

Digitalizing river aquatic ecosystems

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Journal of Environmental Sciences 2024年第3期137卷 677-680页

作者： Yaohui Bai Hui Lin Chenchen Wang Qiaojuan Wang Jiuhui Qu Key Laboratory of Drinking water Science and Technology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China School of Environmental and Municipal Engineering Tianjin Chengjian UniversityTianjin 300384China center for water and ecology Tsinghua UniversityBeijing 100084China

Traditional river health assessment relies on limited water quality indices and representative organism activity,but does not comprehensively obtain biotic and abiotic information of the ***,we propose a new approach to evaluate the ecological and health risks of river aquatic ***,detailed physicochemical and biological characterization of a river ecosystem can be obtained through pollutant determination(especially emerging pollutants)and DNA/RNA ***,supervised machine learning can be applied to perform classification analysis of characterization data and ascertain river ecosystem ecology and *** proposed methodology transforms river ecosystem health assessment and can be applied in river management.

关键词： Digitalizing River ecosystem health Emerging pollutants High throughput sequencing Machine learning

Accelerating the practical application of MOFs for hydrogen storage——from performance-driven to application-oriented

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Green Energy & Environment 2024年第8期9卷 1193-1198页

作者： Yifan Wang Jinghui Wu Yidi Gao Keqing Li Chi Wang Xiaochun Cui Mingxin Huo Xianze Wang Science and Technology Innovation center for Municipal Wastewater Treatment and water quality Protection Northeast Normal University Engineering research center of Low-Carbon Treatment and Green Development of Polluted water in Northeast China Ministry of Education School of Environment Northeast Normal University Key Laboratory of Songliao Aquatic Environment Ministry of Education Jilin Jianzhu University

Metal-organic frameworks(MOFs) are highly promising porous materials known for their exceptional porosity, extensive surface area, and customizable pore structures, making them an ideal solution for hydrogen storage. However, most MOFs research remains confined to the laboratory, lacking practical applications. To address this, the author proposes a shift towards practical applications, the creation of a comprehensive MOFs database, alignment of synthesis with practical considerations, and diversification of MOFs applications. These steps are crucial for harnessing the full potential of MOFs in real-world energy challenges.

关键词： Metal–organic frameworks Hydrogen gas storage Molecular simulation Computational chemistry Machine learning

Time-sensitive prediction of NO_(2) concentration in China using an ensemble machine learning model from multi-source data

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Journal of Environmental Sciences 2024年第3期137卷 30-40页

作者： Chenliang Tao Man Jia Guoqiang Wang Yuqiang Zhang Qingzhu Zhang Xianfeng Wang Qiao Wang Wenxing Wang Big Data research center for ecology and Environment Environment Research InstituteShandong UniversityQingdao 266237China Shandong Provincial Eco-environment Monitoring center Jinan 250101China

Nitrogen dioxide(NO_(2))poses a critical potential risk to environmental quality and public health.A reliable machine learning(ML)forecasting framework will be useful to provide valuable information to support government *** on the data from1609 air quality monitors across China from 2014-2020,this study designed an ensemble ML model by integrating multiple types of spatial-temporal variables and three sub-models for time-sensitive prediction over a wide *** ensemble ML model incorporates a residual connection to the gated recurrent unit(GRU)network and adopts the advantage of Transformer,extreme gradient boosting(XGBoost)and GRU with residual connection network,resulting in a 4.1%±1.0%lower root mean square error over XGBoost for the test *** ensemble model shows great prediction performance,with coefficient of determination of 0.91,0.86,and 0.77 for 1-hr,3-hr,and 24-hr averages for the test results,*** particular,this model has achieved excellent performance with low spatial uncertainty in Central,East,and North China,the major site-dense *** the interpretability analysis based on the Shapley value for different temporal resolutions,we found that the contribution of atmospheric chemical processes is more important for hourly predictions compared with the daily scale predictions,while the impact of meteorological conditions would be ever-prominent for the *** with existing models for different spatiotemporal scales,the present model can be implemented at any air quality monitoring station across China to facilitate achieving rapid and dependable forecast of NO_(2),which will help developing effective control policies.

关键词： Air quality prediction Deep learning Ensemble method Nitrogen dioxide Spatiotemporal covariates

Greenhouse gas emissions from Daihai Lake,China:Should eutrophication and salinity promote carbon emission dynamics?

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Journal of Environmental Sciences 2024年第1期135卷 407-423页

作者： Xiangwei Li Ruihong Yu Jun Wang Heyang Sun Xinyu Liu Xiaohui Ren Shuai Zhuang Zhiwei Guo Xixi Lu Inner Mongolia Key Laboratory of River and Lake ecology School of Ecology and EnvironmentInner Mongolia UniversityHohhot 010070China Key Laboratory of Mongolian Plateau ecology and Resource Utilization Ministry of EducationHohhot 010070China Autonomous Region Collaborative Innovation center for Integrated Management of water Resources and water Environment in the Inner Mongolia Reaches of the Yellow River Hohhot 010018China Department of Geography National University of Singapore117570Singapore

Greenhouse gases(GHGs)emitted or absorbed by lakes are an important component of the global carbon ***,few studies have focused on the GHG dynamics of eutrophic saline lakes,thus preventing a comprehensive understanding of the carbon ***,we conducted four sampling analyses using a floating chamber in Daihai Lake,a eutrophication saline lake in Inner Mongolia Autonomous Region,China,to explore its carbon dioxide(CO_(2))and methane(CH_(4))*** mean CO_(2)emission flux(FCO_(2))and CH_(4)emission flux(FCH_(4))were 17.54±14.54 mmol/m^(2)/day and 0.50±0.50 mmol/m^(2)/day,*** results indicated that Daihai Lake was a source of CO_(2)and CH_(4),and GHG emissions exhibited temporal *** mean CO_(2)partial pressure(p CO_(2))and CH_(4)partial pressure(p CH_(4))were 561.35±109.59μatm and 17.02±13.45μatm,which were supersaturated relative to the *** regression and correlation analysis showed that the main influencing factors of p CO_(2)were wind speed,dissolved oxygen(DO),total nitrogen(TN)and Chlorophyll a(Chl.a),whereas the main influencing factors of p CH_(4)were water temperature(WT),Chl.a,nitrate nitrogen(NO_(3)^(-)-N),TN,dissolved organic carbon(DOC)and water *** regulated carbon mineralization and organic matter decomposition,and it was an important influencing factor of p CO_(2)and p CH_(4).Additionally,the trophic level index(TLI)significantly increased p CH_(4).Our study elucidated that salinity and eutrophication play an important role in the dynamic changes of GHG ***,research on eutrophic saline lakes needs to be strengthened.

关键词： Eutrophication Salinity Greenhouse gas emissions Inland lake Inner Mongolia Autonomous Region

Comparative Assessment of Impacts of Future Climate Change on Runoff in Upper Daqinghe Basin,China

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Chinese Geographical Science 2024年第3期34卷 564-578页

作者： INGABIRE Romaine CHANG Yuru LIU Xia CAO Bo UMUGWANEZA Adeline SHEN Yanjun Key Laboratory of Agricultural water Resources Hebei-Key Laboratory of Water Saving AgricultureCenter for Agricultural Re-sources ResearchInstitute of Genetics and Developmental BiologyChinese Academy of SciencesShijiazhuang 050022China Uni-versity of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Desert and Oasis ecology Xinjiang Insti-tute of Ecology and GeographyChinese Academy of SciencesUrumqi 830011China

Assessing runoff changes is of great importance especially its responses to the projected future climate change on local scale basins because such analyses are generally done on global and regional scales which may lead to generalized conclusions rather than specific *** change affected the runoff variation in the past in the upper Daqinghe Basin,however,the climate was mainly considered uncertain and still needs further studies,especially its future impacts on runoff for better water resources management and *** with a set of climate simulations,a daily conceptual hydrological model(MIKE11-NAM)was applied to assess the impact of climate change on runoff conditions in the Daomaguan,Fuping and Zijingguan basins in the upper Daqinghe *** hydrological data(2008–2017)were used to evaluate the applicability of the MIKE11-NAM *** bias correction,future projected climate change and its impacts on runoff(2025–2054)were analysed and compared to the baseline period(1985–2014)under three shared social economic pathways(SSP1-2.6,SSP2-4.5,and SSP5-8.5)scenarios from Coupled Model Intercomparison Project Phase 6(CMIP6)*** MIKE-11 NAM model was applicable in all three Basins,with both R^(2)and Nash-Sutcliffe Efficiency coefficients greater than 0.6 at daily scale for both calibration(2009–2011)and validation(2012–2017)periods,*** uncertainties remain,temperature and precipitation are projected to increase compared to the baseline where higher increases in precipitation and temperature are projected to occur under SSP2-4.5 and SSP5-8.5 scenarios,respectively in all the *** changes will range between 12%–19%whereas temperature change will be 2.0℃–2.5℃ under the SSP2-4.5 and SSP5-8.5 scenarios,*** addition,higher warming is projected to occur in colder months than in warmer ***,the runoff of these three basins is projected to respond to projected climate changes differe

关键词： runoff climate change MIKE11-NAM model Coupled Model Intercomparison Project Phase 6(CMIP6) upper Daqinghe Basin,China

Analyzing the spatiotemporal evolution and driving forces of gross ecosystem product in the upper reaches of the Chaobai River Basin

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Frontiers of Environmental Science & Engineering 2024年第8期18卷 117-132页

作者： Jiacheng Li Qi Han Liqiu Zhang Li Feng Guihuan Liu Beijing Key Laboratory for Source Control Technology of water Pollution College of Environmental Science and EngineeringBeijing Forestry UniversityBeijing 100083China Engineering research center for water Pollution Source Control&Eco-remediation College of Environmental Science and EngineeringBeijing Forestry UniversityBeijing 100083China center of Eco-compensation Chinese Academy of Environmental PlanningMinistry of Ecology of EnvironmentBeijing 100041China

The Chaobai River Basin,which is a crucial ecological barrier and primary water source area within the Beijing-Tianjin-Hebei region,possesses substantial ecological *** gross ecosystem product(GEP)in the Chaobai River Basin is a reflection of ecosystem conditions and quantifies nature’s contributions to humanity,which provides a basis for basin ecosystem service management and *** study investigated the spatiotemporal evolution of GEP in the upper Chaobai River Basin and explored the driving factors influencing GEP spatial *** patterns from 2005 to 2020 were analyzed,and GEP was calculated for 2005,2010,2015,and *** driving factors influencing GEP spatial differentiation were identified using the optimal parameter-based geographical detector(OPGD)*** key findings are as follows:(1)From 2005 to 2020,the main ecosystem types were forest,grassland,and *** areas experienced significant changes,and conversions mainly occurred among urban,water,grassland and agricultural ecosystems.(2)Temporally,the GEP in the basin increased from 2005 to 2020,with regulation services *** the county(district)scale,GEP exhibited a north-west-high and south-east-low pattern,showing spatial differences between per-unit-area GEP and county(district)GEP,while the spatial variations in per capita GEP and county(district)GEP were similar.(3)Differences in the spatial distribution of GEP were influenced by regional natural geographical and socioeconomic *** these factors,gross domestic product,population density,and land-use degree density contributed *** among different driving forces noticeably impacted GEP spatial *** findings underscore the necessity of incorporating factors such as population density and the intensity of land-use development into ecosystem management decision-making processes in the upper reaches of the Chaobai River *** policies

关键词： Ecosystem pattern Gross ecosystem product(GEP) Spatiotemporal evolution Optimal parameter-based geographical detector(OPGD) Chaobai River Basin

Ecological network analysis reveals complex responses of tree species life stage interactions to stand variables

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Journal of Forestry research 2024年第1期35卷 29-43页

作者： Hengchao Zou Huayong Zhang Tousheng Huang research center for Engineering ecology and Nonlinear Science North China Electric Power UniversityBeijing 102206People’s Republic of China

Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is ***,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree *** results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster *** addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high *** the forests,life stages with higher importance showed better parameter stability within *** results reveal that the structure of tree interactions among life stages is highly related to stand *** efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.

关键词： Tree interactions Life stages Interaction networks Ecological complexity

Snowpack variations and their hazardous effects under climate warming in the central Tianshan Mountains

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Advances in Climate Change research 2024年第3期15卷 442-451页

作者： Jian-Sheng HAO Yan WANG Lan-Hai LI Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences(CAS)Beijing 100101China Xinjiang Key Laboratory of water Cycle and Utilization in Arid Zone Urumqi 830011China State Key Laboratory of Desert and Oasis ecology Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqi 830011China Tianshan Snowcover and Avalanche Observation and research Station of Xinjiang Xinyuan 835800China CAS research center for ecology and Environment of Central Asia Urumqi 830011China

Climate change alters snowpack evolution,which in turn influences the likelihood of snow avalanches and flood *** lack of systemic observational data on key snow characteristics in high mountains remains a scientific challenge in terms of systematically elucidating the dynamic chain of variations in climate-snowpack-snow *** restricts our understanding and poses challenges in the prediction of snow-related disaster *** such,this study analysed the variations of temperature and snowfall and the physical characteristics of snowpacks based on ground-based observations from the Kunse River Valley situated in the Tianshan Mountains from 1967 to *** results reveal that the temperature increased significantly by 0.32°C per decade(pwater equivalent,thus indicating a higher frequency of extremely scarce or abundant snow *** low snowpack temperature gradient and earlier snowmelt dates in spring lead to earlier occurrences of snowmelt floods and wet *** the risks of these events increase,they pose greater threats to farmlands,road transportation,water-electricity infrastructure and several other human ***,these insights are critical for providing vital information that can deepen our understanding of the impact of climate change on snowpack characteristics and improve management strategies for snow-related disaster prevention and mitigation.

关键词： Climate change Snowpack variations Snow-related disaster Tianshan Mountains

Ratio of photosynthetically active radiation to global solar radiation above forest canopy in complex terrain: measurements and analyses based on Qingyuan Ker Towers

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Ecological Processes 2024年第2期13卷 204-217页

作者： Shuangtian Li Qiaoling Yan Tian Gao Xingchang Wang Qingwei Wang Fengyuan Yu Deliang Lu Huaqi Liu Jinxin Zhang Jiaojun Zhu CAS Key Laboratory of Forest ecology and Silviculture Institute of Applied Ecology Chinese Academy of Sciences Qingyuan Forest CERN National Observation and Research Station Chinese Academy of Sciences CAS-CSI Joint Laboratory of research and Development for Monitoring Forest Fluxes of Trace Gases and Isotope Elements Institute of Applied Ecology Chinese Academy of Sciences (CAS) University of Chinese Academy of Sciences center for Ecological research Northeast Forestry University

Background Understanding of the ratio of photosynthetic photon flux density（Qp） to global solar radiation（Rs）(Qp/Rs) is crucial for applying Rsto ecology-related *** studies reported Qp/Rsand its variations based on measurements from a single observatory tower,instead of multi-site-based measurements over complex *** may neglect spatial heterogeneity in the terrain,creating a gap in an understanding of how terrain affects Qp/Rsand how this effect interacts with meteorological *** Here the Qingyuan Ker Towers（three towers in a valley with different terrains:T1,T2,and T3） were utilized to measure Qpand Rsover mountainous forests of Northeast *** airborne LiDAR system was used to generate a digital elevation model,and sky view factor of sectors（SVFs） divided from the field of view of tower's pyranometer was calculated as a topographic factor to explain the variations of Qp/*** The results identified significant differences in Qp/Rsof the three towers at both daily and half-hour scales,with larger differences on clear days than on overcast ***/Rswas positively correlated with SVFsof T1 and T3,while this correlation was negative with that of *** effect of SVFson Qp/Rsinteracted with clearness index,water vapor pressure and solar zenith *** forest-based importance assessment demonstrated that explanation（R2） on Qp/Rswas improved when SVFswas included in the predictor variable set,indicating that incorporating terrain effects enhances the prediction accuracy of Qp/*** improvement in the R2values was more pronounced on clear days than on overcast days,suggesting that the effect of terrain on Qp/Rsdepended on sky *** All findings suggested that Qp/Rsis affected by terrain,and integrating terrain information into existing Qp/Rsmodels is a feasible solution to improve Qp/Rsestimates in mountainous areas.

关键词： Photosynthetic photon flux density Clearness index water vapor pressure Solar zenith angle Terrain Sky view factor