工业工程最新文献

{"title":"Bio-inspired natural fibers-derived e-skin equipped with intelligent drug-release system for advanced robustly-integrated melanoma therapy","authors":"Xinhua Liu,&nbsp;Yifan Fei,&nbsp;Boqiang Cui,&nbsp;Xing Chen,&nbsp;Jiamin Zhang,&nbsp;Ouyang Yue,&nbsp;Zhongxue Bai,&nbsp;Ling Wen,&nbsp;Huie Jiang","doi":"10.1186/s42825-025-00210-z","DOIUrl":"10.1186/s42825-025-00210-z","url":null,"abstract":"<div><p>Malignant melanoma, a highly aggressive malignancy, necessitates innovative therapeutic strategies integrating biomaterial innovation with multimodal treatment modalities. Herein, we report the development of a collagen-derived bioelectronic skin (c-ADM) nanoengineered via interfacial assembly of porcine acellular dermal matrix (ADM)—a natural collagen-rich scaffold—with conductive poly (3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) and copper sulfide nanoparticles (CuS-NPs). This hybrid system synergizes photothermal ablation, stimuli-responsive drug delivery, and electrostimulation (ES) for comprehensive postoperative melanoma management and tissue regeneration. The c-ADM platform exhibits superior mechanical robustness, enzymatic resistance, and biocompatibility, enabling real-time motion monitoring while maintaining structural integrity in dynamic physiological environments. Leveraging the photothermal efficiency of CuS-NPs, localized hyperthermia (ΔT &gt; 40 °C) under near-infrared (NIR) irradiation induces irreversible melanoma cell apoptosis. Concurrently, laser-triggered temperature-responsive drug release enables synchronized photothermal-chemotherapy, with sustained doxorubicin release profiles at tumor sites. Notably, pH-responsive Cu²⁺ liberation from CuS-NPs facilitates intelligent functional switching: bactericidal activity at tumor microenvironment pH (5.0–6.0) and pro-regenerative effects under physiological pH (7.4) for wound healing. In vitro/in vivo assessments confirm c-ADM’s dual therapeutic efficacy including ES-enhanced cancer cell death via mitochondrial dysfunction and accelerated full-thickness skin regeneration through collagen remodeling and angiogenesis modulation. This work establishes a collagen-based bioelectronic scaffold for personalized oncological care, integrating intraoperative tumor eradication, postoperative surveillance, and adaptive tissue reconstruction.</p><h3>Graphic Abstract</h3><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":640,"journal":{"name":"Journal of Leather Science and Engineering","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://JLSE.SpringerOpen.com/counter/pdf/10.1186/s42825-025-00210-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144843175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Land Cover Simulation and Carbon Stock Assessment in Huainan City Based on FLUS- InVEST Model].","authors":"Hai-Yue Zheng, Lei Wang, Tao Wei, Xin-Xin Qi, Yue Chen","doi":"10.13227/j.hjkx.202409033","DOIUrl":"https://doi.org/10.13227/j.hjkx.202409033","url":null,"abstract":"<p><p>To explore the impact of land use change on carbon storage, taking Huainan City as an example, the future land use simulation （FLUS） model was used to simulate the spatial distribution of land use in 2030 under the inertia development scenario, farmland protection scenario, and ecological priority scenario. By combining this result with the integrated valuation of ecosystem services and trade-offs （InVEST） model, the carbon storage of the three scenarios in 1990, 2000, 2010, 2020, and 2030 was estimated. The study produced the following results： ① The main land type in Huainan City is cropland, which accounts for more than 75% of the total area. From 1990 to 2020, the area of cropland, grassland, and forest land in Huainan City continued to decrease, while the area of construction land continued to increase. The main land type transfer was the conversion of cropland to construction land. Compared with the other scenarios, the farmland protection scenario can better promote the increase of farmland area and effectively suppress the expansion of construction land. ② From 1990 to 2020, the carbon storage in Huainan City decreased by 8.29×10⁵ t, with a continuous decreasing trend. Cropland was the main carbon reservoir in Huainan City, and the conversion of cropland to construction land was the main reason for the decrease in carbon storage in Huainan City. ③ The carbon stocks in Huainan City under the 2030 inertia development scenario, cropland protection scenario, and ecological priority scenario are 50 766×10³, 50 822.21×10³, and 50 597.95×10³ t, respectively. The carbon storage decreases compared to the level in 2020 under the three scenarios, among which the cropland protection scenario has the most significant inhibitory effect on the reduction of carbon storage. In the future, prioritizing the protection of cropland should be considered.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"4754-4764"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Estimation of Soil Organic Carbon Content in Gannan Grassland Based on SSA Optimized CatBoost].","authors":"Zi-Ming Ma, Mei-Ling Zhang, Xing-Yu Liu","doi":"10.13227/j.hjkx.202408081","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408081","url":null,"abstract":"<p><p>Estimating the content of soil organic carbon （SOC） in Gannan Tibetan Autonomous Prefecture, studying its spatial distribution characteristics, and clarifying the main influencing factors of SOC are of great significance for improving grassland quality, optimizing management, regulating climate, and maintaining ecosystem functions. Taking the grassland in Gannan Tibetan Autonomous Prefecture of Gansu Province as the research object, multi-feature factor data were constructed by integrating data such as soil properties, meteorological factors, elevation, and vegetation index, and 24 significant feature factors were screened out using Pearson correlation analysis. Then, the normalized contribution degree was obtained according to the SHAP value. The machine learning model was used to divide the 8∶2 training set and test set, and the results were obtained by ten-fold cross-validation. According to the evaluation models such as MAE, RMSE, and <i>R</i>², the sparrow search algorithm （SSA） and whale optimization algorithm （WOA） were used to optimize the parameters and estimate the SOC content. The results showed that the spatial distribution of SOC reserves on grassland surface in Gannan Tibetan Autonomous Prefecture based on the model was gradually decreasing from west to east, being high in the northwest and low in the southeast, with relatively low average temperature and high organic carbon content in the northwest. The annual average temperature, enhanced vegetation index （EVI）, and digital elevation model （DEM） contributed significantly to the SOC content of Gannan grassland, which were the main factors affecting the spatial distribution of SOC. Among the random forest, decision tree, gradient lifting regression, CatBoost, XGBoost, and LightGBM, the CatBoost model performed best on the test set. According to the convergence rate curves of SSA and WOA, it was found that SSA converged faster, and updating parameters was more effective. The optimized SSA-CatBoost model performed best in predicting SOC content. The spatial distribution of SOC has an important impact on the ecosystem and carbon cycle in the region. The grassland in the northwest of the Gannan region has greater potential in soil fertility and carbon storage, which is helpful to formulate more effective soil management and ecological protection strategies, slow down the process of climate warming, and further promote the sustainable development of the global ecosystem.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"4961-4970"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Prediction of Soil Salinity and Analysis of Influencing Factors in Coastal Plains Based on Geographically Weighted Random Forests].","authors":"Ze Li, Zhe Du, Shan-Ting Bi, Teng Ye, Qing Zhang, Ying Chen","doi":"10.13227/j.hjkx.202407011","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407011","url":null,"abstract":"<p><p>Accurate monitoring of the spatial distribution characteristics of soil salinization and its influencing factors is crucial for combating soil degradation and ensuring global food security. Although studies have been conducted using machine learning to predict soil salinization, local modeling studies incorporating spatial information are still limited. Meanwhile, selecting influencing factors from a global perspective to develop precise prevention and control measures for the region is difficult. Therefore, taking the coastal plain of Hebei Province as the study area, a soil salinization prediction model based on geographically weighted regression （GWR）, random forest regression （RF）, and geographically weighted random forest regression （GWRF） was constructed by using multi-source data such as climate, topography, and hydrology, salinity index, vegetation index, and soil moisture index. The predictive performance of each model was systematically compared, and the variability of environmental variables in explaining the spatial variability of salinization was explored. The results showed that： ① The GWRF model was the best in predicting the spatial characteristics of soil salinization in the coastal area （<i>R</i>²=0.82, RMSE=0.10 g·kg^-1, MAE=0.06 g·kg^-1）. ② The degree of soil salinization in the coastal plain of Hebei Province increased from the inland to the coastal area, with soil salinization being the most severe in the eastern part of the coastal plain. ③ Significant differences were observed in the spatial distribution of the importance of different environmental variables. Overall, climate （mean annual precipitation and evapotranspiration） and depth to groundwater were important factors in predicting soil salinization in the coastal plain. This study provides a new perspective for the prediction and analysis of soil salinization in the coastal zone and also provides a scientific basis for regional ecological planning.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"4982-4992"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Occurrence Characteristics of Microplastics and Influencing Factors in Coastal Salinized Soil].","authors":"Wei-Ming Li, Lei Xu, Li-Chang Zhang, Cai-Ling Shi, Wen-Jun Xie","doi":"10.13227/j.hjkx.202407154","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407154","url":null,"abstract":"<p><p>Microplastics are widespread in terrestrial and marine environments. As a transition zone between land and ocean, coastal soils have unique microplastic pollution characteristics. To reveal the characteristics of microplastic pollution in coastal soils, soils with different salinization levels were collected from Wudi County toward the sea. The distribution characteristics of microplastics and their relationship with soil physical and chemical properties were analyzed through density separation, oxidative digestion, and micro-Raman spectroscopy techniques. The pollutant load index method was used to assess its ecological risk. The results showed that microplastics were detected in 51 sampling points of coastal soil in Wudi County, and the abundance of microplastics ranged from 550 to 3 950 n·kg^-1. Polyethylene （PE）, polyethylene terephthalate （PET）, polypropylene （PP）, polystyrene （PS）, and polyvinyl chloride （PVC） accounted for 53.1%, 13.9%, 16.4%, 8.4%, and 8.2%, respectively. The shapes of microplastics mainly included film （accounting for 62.0%）, fiber （accounting for 13.7%）, sphere （accounting for 13.2%）, and sheet （accounting for 11.1%）. Microplastics with grain size less than 1 000 μm accounted for 85.0%. The lowest abundance of microplastics appeared in the bare land with the highest degree of salinization, and the highest abundance appeared in the non-salinized cotton soil. The abundance of microplastics was significantly correlated with soil salinization levels （<i>P</i>&lt; 0.05）. With saline level increasing, the total abundance of microplastics and the abundance of film, PE, and PET microplastics decreased significantly （<i>P</i>&lt; 0.05）. The proportion of microplastics with grain size greater than 1 000 μm decreased significantly （<i>P</i>&lt; 0.05）, but the proportion of microplastics with grain size less than 100 μm increased significantly （<i>P</i>&lt; 0.05）. This may be because of the different soil use types and different sources of microplastics in soils with varied saline levels. Soil organic carbon （SOC） was significantly positively correlated with the abundance of microplastics （<i>P</i>&lt; 0.05）. The risk load index （PLI） values of all soil samples ranged from 1.19 to 2.41, which were low risk level pollution. Among them, the PLI values of wasteland and bare land with high saline level were lower, and the PLI values of soils with low saline level were higher. The results of this study can provide an important basis for understanding the microplastic pollution and exploring the relationship between soil properties and microplastic distribution characteristics in coastal saline soils.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"5325-5335"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Characterization of Spatial and Temporal Divergence and Coupling of Net Agricultural Carbon Sinks in China: A Case Study from 2000 to 2022].","authors":"Xiao-Wen Dai, Yi Chen, Yan-Qiu He, Fang Wang","doi":"10.13227/j.hjkx.202407038","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407038","url":null,"abstract":"<p><p>Low-carbon agriculture is crucial for China's agricultural green transformation and the development of an ecological civilization. The net carbon sink of agriculture plays a vital role in this process. Here, we take China's 31 provinces （municipalities and autonomous regions） as the research object, select the data from 2000 to 2022, and discuss them from multiple perspectives around the three dimensions of time series, space, and coupling. Additionally, we constructed an environment-economy coupling index and refined it by phases to analyze the relationship between stages and regions. The study revealed the following： ① China's overall agricultural carbon emissions fluctuated and decreased, while the agricultural carbon sink continued to expand, showing steady growth. ② The net agricultural carbon sink was distributed among provinces, and the gap between provinces in terms of net carbon sink tended to widen. Agricultural net carbon sinks exhibited regional aggregation characteristics, forming two distinct growth areas. The traditional growth area comprised Shandong and Henan as the core and Hebei, Anhui, and Jiangsu as the neighboring radiation areas. The other emerging growth areas in Northeast China included Heilongjiang, Jilin, and Liaoning. ③ The net agricultural carbon sink demonstrated a clear positive spatial correlation. However, a tendency was observed for the spatial correlation to weaken and an increase in the spatial type of low-low form of aggregation over the years. ④ From 2000 to 2022, the coupling relationship between net agricultural carbon sinks and agricultural economic growth improved, with most provinces shifting from weak or strong decoupling to expanding negative decoupling. Six provinces, namely, Zhejiang, Fujian, Yunnan, Gansu, Xinjiang, and Inner Mongolia, have shown the most significant shifts. Overall, the net agricultural carbon sinks and agricultural economic growth are expected to be in a state of negative expansion or weak decoupling for a prolonged period in the future. While the contribution of agricultural carbon sinks to the resource reserve will be substantial, the sustainable growth of the agricultural economy will face challenges.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"4839-4849"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Evaluation of Ecological Quality in the Chengdu-Chongqing Economic Circle Based on Human Footprint].","authors":"Yue Chang, Deng-Feng Wei, Hui Yang, Ting-Gang Zhou","doi":"10.13227/j.hjkx.202407079","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407079","url":null,"abstract":"<p><p>As an important economic center in western China, the rapid urbanization and economic development of the Chengdu-Chongqing economic circle needs to be coordinated with ecological environmental protection. In this study, we utilized remote sensing technology and multi-source data, leveraging the Google earth engine platform to construct the human remote sensing ecological index （HRSEI）, which included indicators of greenness, wetness, dryness, heat, and the human footprint. This index was used to assess the ecological quality of the Chengdu-Chongqing economic circle from 2013 to 2022. The results showed that during this period, the intensity of human activities in the region increased significantly, exerting a profound impact on ecological quality. The spatial distribution of ecological changes exhibited a core-periphery pattern, centered on Chengdu and Chongqing, radiating along major transportation corridors. Ecological quality demonstrated complex trends amidst rapid urbanization and economic growth. Among them, the largest area of ecological degradation involved transitions from \"good\" to \"fair,\" accounting for 22.8%, followed by a change from \"excellent\" to \"good\" （7.3%） and a change from \"fair\" to \"poor\" （3.6%）. The deterioration of \"poor\" and \"very poor\" ecological quality was mainly concentrated around the core city and its transportation network, while \"good\" and \"excellent\" areas had improved their ecological quality. The ecological improvement and restoration of the \"good\" and \"excellent\" areas were closely linked to the implementation of regional environmental protection policies. Geo-detector analysis further revealed that the interactions between natural factors （such as elevation and temperature） and human activities （such as land use） had an important influence on the dynamic changes of ecological quality in the Chengdu-Chongqing economic circle. This study provides a scientific basis for future coordinated regional development and ecological environmental protection.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"5169-5179"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Research Progress on the Extraction, Qualitative, and Quantitative Methods of Microplastics in Biological Samples].","authors":"Min Li, Fei-Ping Wang, Zi-Qi Chen, Xin-Yu Li, Hai-Long Liu, Xiao-Zhi Wang, Wan-Ying Zhang, Jian Xu","doi":"10.13227/j.hjkx.202407196","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407196","url":null,"abstract":"<p><p>Microplastics （MPs）, which usually refer to plastic fragments, particles, or fibers with a diameter or length of less than 5 mm, are contaminants of emerging concern （CECs） that have a significant impact on the ecological system. MPs have been widely detected in the soil, surface water, ocean, and atmosphere. These MPs could accumulate in organisms via absorption and/or ingestion, transfer along the food chain, and ultimately pose a threat to the health of higher trophic organisms and even human beings. Therefore, the determination of MPs types and contents in organisms is important for understanding the accumulation of MPs in organisms and their potential ecological risks. Hence, in this study, we focus on the analysis of MPs in biological samples. After researching the domestic and foreign literature, the basic principles, suitable application conditions, as well as the advantages and disadvantages of each method used in four processes of MPs analysis, including biological sample collection, MPs extraction （including the digestion of biological samples and separation of MPs from digestion solutions）, and qualitative and quantitative analysis, were discussed. On this basis, a combination of different analysis methods is proposed to improve the detection accuracy of MPs analysis in biological samples, which requires further investigation in the field of MPs analysis in biological samples. Meanwhile, more efforts should be exerted on the investigation of the standard method used in biological sample pretreatment and MPs analysis.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"5303-5315"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatial-temporal Patterns and Driving Factors of Net Carbon Sink in Planting Industry in the West China Development Area].","authors":"Li-Chen Tang, Jie Li, Hui Chen, Mi Chen, Xian-Gang Zeng, Zhong-Yuan Zhang","doi":"10.13227/j.hjkx.202407194","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407194","url":null,"abstract":"<p><p>On the basis of calculating the spatiotemporal pattern changes of net carbon sink in the planting industry in the West China Development Area from 2001 to 2022, the GBR model was used to reveal its key driving factors and nonlinear response mechanisms. The results showed that： ① During the inspection period, the net carbon sink of the planting industry in the West China Development Area （calculated as C） showed an upward trend, but the growth rate gradually slowed, increasing from 125.641 3 million tons in 2001 to 219.106 1 million tons in 2022. ② The high value areas of net carbon sink in the planting industry were mainly in the southwest region, and the number of provinces in the high value range of net carbon sink continued to increase, showing an expanding trend from a few clusters to large-scale clusters. The net carbon sink intensity of planting industry exhibited obvious spatial agglomeration and non-equilibrium characteristics, and the net carbon sink intensity of all provinces gradually decreased during the inspection period. ③ The industrial structure factor had an inverted U-shaped relationship with the net carbon sink of the planting industry. The agricultural production structure, agricultural disaster rate, urban-rural income gap, and urbanization rate factors had a fluctuating inhibitory effect, while other factors had a significant promoting effect. At different periods, the importance of farmland irrigation condition and agricultural mechanization level factors were prominent.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"4850-4863"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatiotemporal Pattern and Driving Mechanism of PM_2.5 Population Exposure Risk in Urban Agglomerations in China].","authors":"Jun Zhang, Lei-Yu Liu, Teng-Fei Zhang, Ya-Ni Geng","doi":"10.13227/j.hjkx.202405319","DOIUrl":"https://doi.org/10.13227/j.hjkx.202405319","url":null,"abstract":"<p><p>At present, China's urban agglomerations are high-risk and high-risk clusters of PM_2.5 population exposure. Based on the remote sensing data of PM_2.5 from 2000 to 2021, this study analyzed the temporal and spatial evolution characteristics of PM_2.5 population exposure risk in urban agglomerations in China by using the population exposure risk model and spatial autocorrelation method and used seven factors such as average temperature, annual precipitation, and per capita GDP as independent variables, combined with geographic detectors and spatiotemporal geographically weighted regression models to explore the spatial differentiation mechanism of PM_2.5 population exposure risk. The results showed that： ① From 2000 to 2021, the temporal range of PM_2.5 exposure risk in urban agglomerations in China was small. ② From 2000 to 2021, the PM_2.5 population exposure risk of China's urban agglomerations changed significantly in space, and the high-risk areas of PM_2.5 population exposure were concentrated in the Beijing-Tianjin-Hebei urban agglomeration, the Yangtze River Delta urban agglomeration, and the central Shanxi urban agglomeration, and the PM_2.5 population exposure risk in China's urban agglomerations showed a marked positive correlation in space, and the spatial agglomeration characteristics were obvious. ③ The exposure risk of urban agglomerations with low population density was greatly affected by annual precipitation and annual average temperature, while urban agglomerations with high population density were greatly affected by population density and environmental regulatory factors. Industrial structure and population density factors played a positive role in enhancing the population exposure risk of PM_2.5 in urban agglomerations, energy consumption and environmental regulation factors played a negative inhibiting effect, and annual average wind speed and annual precipitation factors mainly played a positive role in enhancing and negatively inhibiting the population exposure risk of the urban agglomeration on the northern slope of the Tianshan Mountains. The results of this study provide a scientific basis for atmospheric environment management and pollution prevention and control in urban agglomerations in China.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 8","pages":"5000-5012"},"PeriodicalIF":0.0,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144856633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}