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学者姓名：王前锋
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Dust aerosols significantly impact climate, human health, and ecosystems, but how land cover changes (LCC) influence dust concentrations remains unclear. Here, we applied the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to assess the effects of LCC on dust aerosol concentrations from 2000 to 2020 in northern China. Based on land cover data derived from multi-source satellite remote sensing data, we conducted two simulation scenarios: one incorporating actual annual LCC and another assuming static land cover since 2000. Results revealed that approximately 293,300 km2 of land underwent conversion over the past 20 years. LCC generally resulted in an average annual reduction of 5.70 mu g kg-1 (micrograms per kilogram of dry air) in dust aerosol concentrations. The most significant reduction occurred in winter, averaging 8.90 mu g kg-1, followed by spring (8.06 mu g kg-1), autumn (5.27 mu g kg-1), and summer (1.06 mu g kg-1). Converting bare land to forestland was most effective in reducing dust concentrations, followed by conversions to grassland and built-up areas. Conversely, conversions to bare land increased dust aerosol concentrations, especially when forestland or cultivated land was transformed into bare land. These results emphasize the importance of targeted land use strategies to mitigate the adverse environmental and health effects of dust aerosols.
Keyword ：
Air pollution Air pollution Dust concentrations Dust concentrations Dust emissions Dust emissions Land use change Land use change WRF-Chem WRF-Chem
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| GB/T 7714 | Liu, Xian , Min, Ruiqi , Zhang, Haopeng et al. Land cover changes reduce dust aerosol concentrations in Northern China (2000-2020) [J]. | ENVIRONMENTAL RESEARCH , 2025 , 268 . |
| MLA | Liu, Xian et al. "Land cover changes reduce dust aerosol concentrations in Northern China (2000-2020)" . | ENVIRONMENTAL RESEARCH 268 (2025) . |
| APA | Liu, Xian , Min, Ruiqi , Zhang, Haopeng , Wang, Qianfeng , Song, Hongquan . Land cover changes reduce dust aerosol concentrations in Northern China (2000-2020) . | ENVIRONMENTAL RESEARCH , 2025 , 268 . |
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This study evaluates the comparative performance of spatiotemporal fusion and time-series fitting methods for constructing high-spatiotemporal-resolution remote sensing time-series data. Due to in-class similarity of fusion methods and fitting methods, we employ the Fit-FC (Fitting, spatial Filtering, and residual Compensation) model as a representative fusion method and the linear harmonic fitting model as a representative fitting method. Both Fit-FC and the linear harmonic fitting are widely used for high-spatiotemporal-resolution time-series data construction, and we modify the original Fit-FC model to enable automatic time-series fusion. To ensure data representativeness, we use 3 years (2019-2021) of Harmonized Landsat and Sentinel-2 surface reflectance datasets and Terra MCD43A4 products. Eight experimental regions are selected worldwide to guarantee generalization of the comparative performance between fusion and fitting methods, covering diverse land-use types (cropland, developed land, forest, and grassland) and varying climatological conditions. Time-series of NDVI and surface reflectance are analyzed under both actual observations and simulated data-missing scenarios. The constructed time-series data reveals that (1) the modified Fit-FC and linear harmonic fitting model achieve excellent performance in constructing high-resolution time-series images; (2) the fusion method outperforms the fitting method in constructing time-series of NDVI and surface reflectance images in cropland-, forest-, and grassland-dominated regions; (3) both methods achieve comparable performance in developed-dominated regions; (4) the fusion method is more robust to missing data, and better captures abrupt phenological transitions under conditions of continuous missing data; (5) the fitting method is computationally more efficient, making it suitable for large-scale time-series image reconstruction. This study provides valuable insights for selecting optimal strategies to generate high-resolution time-series images across diverse application scenarios and lays a foundation for extensions to other vegetation indices or land surface variables.
Keyword ：
harmonic fitting harmonic fitting remote sensing data remote sensing data Spatiotemporal fusion Spatiotemporal fusion time series construction time series construction
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| GB/T 7714 | Tang, Jia , Bento, Virgilio A. , Hao, Dalei et al. Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations [J]. | GISCIENCE & REMOTE SENSING , 2025 , 62 (1) . |
| MLA | Tang, Jia et al. "Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations" . | GISCIENCE & REMOTE SENSING 62 . 1 (2025) . |
| APA | Tang, Jia , Bento, Virgilio A. , Hao, Dalei , Zeng, Yelu , Guo, Pengcheng , Chen, Yu et al. Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations . | GISCIENCE & REMOTE SENSING , 2025 , 62 (1) . |
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Drought is one of the most complicated natural hazards and is among those that pose the greatest socioeconomic risks. How long-term climate change on a large scale affects different types of drought has not been well understood. This study aimed to enhance comprehension of this critical issue by integrating the run theory for drought identification, Mann-Kendall trend analysis, and partial correlation attribution methods to analyze global drought dynamics in 1901-2018. Methodological innovations include: (1) a standardized drought severity metric enabling cross-typology comparisons; and (2) quantitative separation of precipitation and temperature impacts. Key findings reveal that socioeconomic drought severity exceeded meteorological, agricultural, and hydrological droughts by 350.48%, 47.80%, and 14.40%, respectively. Temporal analysis of Standardized Precipitation Evapotranspiration Index (SPEI) trends demonstrated intensification gradients: SPEI24 (- 0.09 slope/100 yr) > SPEI01 (- 0.088/100 yr) > SPEI06 (- 0.087/100 yr) > SPEI12 (- 0.086/100 yr). Climate drivers exhibited distinct patterns, with precipitation showing stronger partial correlations across all drought types (meteorological: 0.78; agricultural: 0.76; hydrological: 0.60; socioeconomic: 0.39) compared to temperature (meteorological: - 0.45; agricultural: - 0.38; hydrological: - 0.27; socioeconomic: - 0.18). These results quantitatively establish a hierarchical climate response gradient among drought types. The framework advances drought typology theory through three original contributions: (1) systematic quantification of cross-typology drought severity disparities; (2) precipitation-temperature influence partitioning across drought types; and (3) identification of socioeconomic drought as the most climate-decoupled yet fastest-intensifying type. This study refined drought typological theories and provides a methodological foundation for climate-resilient drought management planning.
Keyword ：
Climate change Climate change Drought severity Drought severity Global scale Global scale Multi-type drought Multi-type drought Various vegetation zones Various vegetation zones
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| GB/T 7714 | Wang, Qianfeng , Yang, Xiaofan , Qu, Yanping et al. Global Climate Change Exacerbates Socioeconomic Drought Severity Across Vegetation Zones During 1901-2018 [J]. | INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE , 2025 , 16 (2) : 291-306 . |
| MLA | Wang, Qianfeng et al. "Global Climate Change Exacerbates Socioeconomic Drought Severity Across Vegetation Zones During 1901-2018" . | INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE 16 . 2 (2025) : 291-306 . |
| APA | Wang, Qianfeng , Yang, Xiaofan , Qu, Yanping , Qiu, Han , Wu, Yiping , Qi, Junyu et al. Global Climate Change Exacerbates Socioeconomic Drought Severity Across Vegetation Zones During 1901-2018 . | INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE , 2025 , 16 (2) , 291-306 . |
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Amidst the escalating impacts of global warming, the occurrence and severity of compound extreme weather events have risen significantly, presenting substantial threats to both lives and property. Existing response strategies predominantly focus on individual events, often overlooking the cumulative effects rising from their inherent complexity. To address this critical gap, we conducted a thorough examination of sequential extreme precipitation-heatwave compound events (SEPHCE) in China from 1975 to 2020, utilizing data from 1929 meteorological stations. Our investigation revealed a consistent rise in the frequency and duration of SEPHCE, with a particularly notable surge since 1993. Furthermore, shorter interval events disproportionately affected the regions of southwestern and southeast coastal China. Furthermore, SEPHCE onset times exhibited advancement, and the endings were delayed, thereby intensifying the overall trend. These findings underscore the pressing need to prioritize effective planning and adaptation strategies to mitigate the impact of these compound event, while also addressing the potential exacerbation of inequality resulting from climate change.
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| GB/T 7714 | Miao, Lijuan , Ju, Lei , Sun, Shao et al. Unveiling the dynamics of sequential extreme precipitation-heatwave compounds in China [J]. | NPJ CLIMATE AND ATMOSPHERIC SCIENCE , 2024 , 7 (1) . |
| MLA | Miao, Lijuan et al. "Unveiling the dynamics of sequential extreme precipitation-heatwave compounds in China" . | NPJ CLIMATE AND ATMOSPHERIC SCIENCE 7 . 1 (2024) . |
| APA | Miao, Lijuan , Ju, Lei , Sun, Shao , Agathokleous, Evgenios , Wang, Qianfeng , Zhu, Zhiwei et al. Unveiling the dynamics of sequential extreme precipitation-heatwave compounds in China . | NPJ CLIMATE AND ATMOSPHERIC SCIENCE , 2024 , 7 (1) . |
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The future state of drought in China under climate change remains uncertain. This study investigates drought events, focusing on the region of China, using simulations from five global climate models (GCMs) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5) participating in the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b). The daily Standardized Precipitation Evapotranspiration Index (SPEI) is employed to analyze drought severity, duration, and frequency over three future periods. Evaluation of the GCMs' simulations against observational data indicates their effectiveness in capturing historical climatic change across China. The rapid increase in CO2 concentration under high-emission scenarios in the mid- and late-future century (2040-2070 and 2071-2100) substantially influences vegetation behavior via regulation on leaf stomata and canopy structure. This regulation decelerates the increase in potential evapotranspiration, thereby mitigating the sharp rise in future drought occurrences in China. These findings offer valuable insights for policymakers and stakeholders to develop strategies and measures for mitigating and adapting to future drought conditions in China.
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| GB/T 7714 | Xu, Feng , Qu, Yanping , Bento, Virgilio A. et al. Understanding climate change impacts on drought in China over the 21st century: a multi-model assessment from CMIP6 [J]. | NPJ CLIMATE AND ATMOSPHERIC SCIENCE , 2024 , 7 (1) . |
| MLA | Xu, Feng et al. "Understanding climate change impacts on drought in China over the 21st century: a multi-model assessment from CMIP6" . | NPJ CLIMATE AND ATMOSPHERIC SCIENCE 7 . 1 (2024) . |
| APA | Xu, Feng , Qu, Yanping , Bento, Virgilio A. , Song, Hongquan , Qiu, Jianxiu , Qi, Junyu et al. Understanding climate change impacts on drought in China over the 21st century: a multi-model assessment from CMIP6 . | NPJ CLIMATE AND ATMOSPHERIC SCIENCE , 2024 , 7 (1) . |
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The Yellow River basin of China has experienced significant land use and land cover change (LUCC) due to excessive exploitation of nature resources, ecological degradation, and rapid urbanization, which plays an important role in the regional climate. It is crucial to explore the climate patterns of the basin under different future development scenarios to mitigate climate issues and achieve "carbon peaking and carbon neutrality goals ". Here we utilized land use and land cover (LULC) data and projections of future climate under two shared socioeconomic path - representative concentration path (SSP245 and SSP585) scenarios. Using the Weather Research and Forecasting (WRF) model, we simulated four future spatial variation patterns of temperature and precipitation in the basin. Results indicated that under the SSP245 and SSP585 scenarios, the temperature is projected to increase by 0.18 degrees C and 0.46 degrees C, respectively, while precipitation is expected to rise by 32.21 mm and 134.24 mm, respectively. The impact of LUCC was found to be relatively minor and mainly concentrated in the middle reaches of the basin. It resulted in a slight increase in temperature in both scenarios and an increase in precipitation in SSP245, but a decrease in precipitation in SSP585. Changes in farmland and urban area exhibited a certain warming effect in both scenarios, with urban areas having a greater influence, leading to a temperature increase by 0.25 degrees C and 0.28 degrees C, respectively. Forest, grassland, and bare areas had a lesser impact on temperature and showed different trends under two scenarios. Regarding precipitation, forests and urban areas had a greater influence in both SSP245 and SSP585 scenarios. This study identified the significant role of LUCC under different development scenarios in shaping future temperature and precipitation changes, providing valuable insights for effectively addressing climate issues in the Yellow River basin. It also highlights the need for clear policy recommendations and identifies institutions or agencies responsible for implementing such recommendations.
Keyword ：
Climate change Climate change Land use and land cover Land use and land cover SSP-RCPs SSP-RCPs WRF WRF Yellow River basin Yellow River basin
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| GB/T 7714 | Ru, Xutong , Qiao, Longxin , Zhang, Haopeng et al. Effects of land use and land cover change under shared socioeconomic pathways on future climate in the Yellow River basin, China [J]. | URBAN CLIMATE , 2024 , 55 . |
| MLA | Ru, Xutong et al. "Effects of land use and land cover change under shared socioeconomic pathways on future climate in the Yellow River basin, China" . | URBAN CLIMATE 55 (2024) . |
| APA | Ru, Xutong , Qiao, Longxin , Zhang, Haopeng , Bai, Tianqi , Min, Ruiqi , Wang, Yaobin et al. Effects of land use and land cover change under shared socioeconomic pathways on future climate in the Yellow River basin, China . | URBAN CLIMATE , 2024 , 55 . |
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As global climate change intensifies and population growth continues, water scarcity has emerged as a critical constraint to sustainable agricultural development. Conservation management, an effective water-saving technique, plays a crucial role in enhancing soil water content (SWC) and promoting sustainable agriculture. This study utilizes CiteSpace to perform a bibliometric analysis of research literature on the effects of conservation management on SWC, encompassing publications indexed in the Web of Science database from 1992 to 2024. By systematically examining 599 papers, we analyzed key research institutions, authors' collaborative contributions, keyword co-occurrences, and shifts in research hotspots related to conservation management and its impact on SWC. The results reveal that significant topics in this field include "conservation agriculture", "water use efficiency", and "conservation tillage". China (225, 38%) and the United States (129, 22%) lead in publication volume, whereas European countries and institutions show a higher degree of collaboration. The research focus has transitioned from examining the impacts and mechanisms of conservation tillage on crop yield and soil physical and chemical properties to long-term monitoring, water use efficiency, and mitigation. Furthermore, keyword co-occurrence and temporal analysis highlight a growing emphasis on soil quality and greenhouse gas emissions. In the future, it remains imperative to enhance the implementation of automated monitoring systems, secure long-term continuous monitoring data, promote conservation agriculture technology, and bolster the early warning network for extreme climate events. These measures are crucial for preserving soil nutrient levels and ensuring the sustainable development of agriculture.
Keyword ：
network analysis network analysis publication analysis publication analysis soil moisture soil moisture sustainable agriculture sustainable agriculture
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| GB/T 7714 | Du, Can , Wu, Yuexi , Ma, Limei et al. Bibliometric Analysis of Research on the Effects of Conservation Management on Soil Water Content Using CiteSpace [J]. | WATER , 2024 , 16 (23) . |
| MLA | Du, Can et al. "Bibliometric Analysis of Research on the Effects of Conservation Management on Soil Water Content Using CiteSpace" . | WATER 16 . 23 (2024) . |
| APA | Du, Can , Wu, Yuexi , Ma, Limei , Lei, Dong , Yuan, Yin , Ren, Xiaohua et al. Bibliometric Analysis of Research on the Effects of Conservation Management on Soil Water Content Using CiteSpace . | WATER , 2024 , 16 (23) . |
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Study region: Hanjiang River Basin, China Study focus: Under the joint influences of human activities and climate change, droughts frequently occur in the Hanjiang River Basin (HRB). Quantifying the driving forces contribution on hydrological drought is crucial to enhance the early warning ability. This study employed the standardized streamflow index (SSI) to assess hydrological drought. The Soil and Water Assessment Tool (SWAT) model was utilized to reconstruct natural streamflow based on hydrological and meteorological data. By comparing the variations of drought characteristics in simulated and observed scenarios, the impacts of human activities and climate change to hydrological drought were quantified. New hydrological insights for the study region: The SWAT model is capable of effectively simulating the natural streamflow conditions of the HRB with NSE>0.7, R2>0.8, logNSE>0.7 and |PBIAS|< 20 %. Hydrological drought has intensified as a prolonged duration and greater severity affected by human activities and climate change. During the whole impact period (1968-2022), the duration and severity increased by 66.22 % and 81.16 % compared to baseline period (1956-1967). The year 1991 is detected as the mutation point. From 1968-1990 climate change has been the main factor in exacerbating hydrological drought. Since 1991, the influence of human activities has gradually exceeded the influence of climate change. These findings provide valuable insights for watershed integrated water resources management and water security.
Keyword ：
Attribution analysis Attribution analysis Hydrological drought Hydrological drought SWAT model SWAT model The Hanjiang River The Hanjiang River
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| GB/T 7714 | Li, Cheng , Qu, Yanping , Jiang, Tianliang et al. Attribution analysis of hydrological drought after the impoundment of the Danjiangkou reservoir in the Hanjiang River Basin [J]. | JOURNAL OF HYDROLOGY-REGIONAL STUDIES , 2024 , 56 . |
| MLA | Li, Cheng et al. "Attribution analysis of hydrological drought after the impoundment of the Danjiangkou reservoir in the Hanjiang River Basin" . | JOURNAL OF HYDROLOGY-REGIONAL STUDIES 56 (2024) . |
| APA | Li, Cheng , Qu, Yanping , Jiang, Tianliang , Jiang, Furen , Wang, Qianfeng , Zhang, Xuejun et al. Attribution analysis of hydrological drought after the impoundment of the Danjiangkou reservoir in the Hanjiang River Basin . | JOURNAL OF HYDROLOGY-REGIONAL STUDIES , 2024 , 56 . |
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The global food supply system is under increasing pressure due to population growth and more extreme climate events. Developing forecast models for accurate prediction of crop yields is helpful for early warning of food crises. Amid the different environmental predictors, soil moisture (SM) is an important agricultural drought indicator. However, current operational microwave SM products have generally low spatial resolution, challenging the effective characterization of SM spatial heterogeneity. In this study, empowered by the hourly land surface temperature (LST) observations from geostationary operational environmental satellites (GOES), we first spatially-downscale SM using machine learning (ML) algorithms. Then, by designing three sets of experiment respectively using downscaled SM, coarse-resolution SM, and precipitation observation, we assess the comparative performance of downscaled SM among its counterparts in estimating crop yield variability, based on three mainstream ML algorithms and two traditional regression algorithms. Our research shows that downscaled SM based on high temporal resolution GOES-LST demonstrates outstanding performance in characterizing the spatial variation of SM. With respect to yield estimation, downscaled high-resolution SM out performs coarse-resolution SM and precipitation products, with the average R-2 between the crop yield estimates and the yield records being 0.814, 0.809, and 0.805, respectively. In addition, we find that among the five algorithms, the nonlinear ML algorithms exceed the linear algorithms in crop yield estimation, with the average R-2 being 0.827 and 0.783, respectively. Our research demonstrates the great potential of infusing different satellite information to improve the monitoring of crop growing status and yield prediction.
Keyword ：
Data models Data models Land surface temperature Land surface temperature Land surface temperature (LST) Land surface temperature (LST) Machine learning algorithms Machine learning algorithms machine learning (ML) machine learning (ML) Predictive models Predictive models Soil moisture Soil moisture soil moisture (SM) downscaling soil moisture (SM) downscaling Spatial resolution Spatial resolution Switched mode power supplies Switched mode power supplies yield estimation yield estimation
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| GB/T 7714 | Mai, Ruiwen , Xin, Qinchuan , Qiu, Jianxiu et al. High Spatial Resolution Soil Moisture Improves Crop Yield Estimation [J]. | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING , 2024 , 17 : 19067-19077 . |
| MLA | Mai, Ruiwen et al. "High Spatial Resolution Soil Moisture Improves Crop Yield Estimation" . | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 17 (2024) : 19067-19077 . |
| APA | Mai, Ruiwen , Xin, Qinchuan , Qiu, Jianxiu , Wang, Qianfeng , Zhu, Peng . High Spatial Resolution Soil Moisture Improves Crop Yield Estimation . | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING , 2024 , 17 , 19067-19077 . |
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Potential toxic metal (PTM) is hazardous to human health, but the mechanism of spatial heterogeneity of PTM at a macro-scale remains unclear. This study conducts a meta-analysis on the data of PTM concentrations in the soil of 164 major cities in China from 2006 to 2021. It utilizes spatial analysis methods and geodetector to investigate the spatial distribution characteristics of PTMs. The geographic information systems (GIS) and geodetector were used to investigate the spatial distribution characteristics of PTMs, assess the influence of natural factors (NFs) and anthropogenic factors (AFs) on the spatial heterogeneity of PTMs in urban soils, and identified the potential pollution areas of PTMs. The results indicated that the pollution levels of PTMs in urban soils varied significantly across China, with higher pollution levels in the south than in the north. Cd and Hg were the most severely contaminated elements. The geodetector analysis showed that temperature and precipitation in NFs and land use type in AFs were considered as the main influencing factors, and that both AF and NF together led to the PTM variation. All these factors showed a mutually enhancing pattern which has important implications for urban soil management. PTM high-risk areas were identified to provide early warning of pollution risk under the condition of climate change.
Keyword ：
Geodetector Geodetector High-risk areas High-risk areas Influencing factors Influencing factors Potential toxic metal Potential toxic metal Urban soil Urban soil
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| GB/T 7714 | Zeng, Yue , Liu, Xinyu , Li, Yunqin et al. Analysis of driving factors for potential toxic metals in major urban soils of China: a geodetetor-based quantitative study [J]. | ENVIRONMENTAL GEOCHEMISTRY AND HEALTH , 2024 , 46 (10) . |
| MLA | Zeng, Yue et al. "Analysis of driving factors for potential toxic metals in major urban soils of China: a geodetetor-based quantitative study" . | ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 46 . 10 (2024) . |
| APA | Zeng, Yue , Liu, Xinyu , Li, Yunqin , Jin, Zhifan , Shui, Wei , Wang, Qianfeng . Analysis of driving factors for potential toxic metals in major urban soils of China: a geodetetor-based quantitative study . | ENVIRONMENTAL GEOCHEMISTRY AND HEALTH , 2024 , 46 (10) . |
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