环境科学最新文献

{"title":"[Spatiotemporal Evolution and Inequality of Marginal Cost of Carbon Emission Reduction in Chinese Cities].","authors":"Xiao-Hong Chen, Fang-Yi Zhou, Ji-Xin Cheng, Dong-Bin Hu","doi":"10.13227/j.hjkx.202408127","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408127","url":null,"abstract":"<p><p>Studying the spatiotemporal evolution and inequality characteristics of the marginal cost of carbon reduction at the city level is crucial for formulating effective and fair carbon reduction policies. Using panel data from 236 prefecture-level cities in China during the period 2006-2019， this study employed a directional distance function parameter estimation method to measure the marginal carbon dioxide reduction costs in cities in China. Building on this result， the study analyzed the temporal and spatial evolution， classification， inequality， and spatial convergence characteristics of these marginal reduction costs using models such as kernel density functions， the Dagum Gini coefficient， and spatial convergence. The key findings are as follows： ①From 2006 to 2019， China's marginal carbon reduction cost （measured in CO₂e） showed a trend of first declining and then rising. The average value first decreased from 7.45 thousand yuan per ton to 5.58 thousand yuan per ton and then increased to 20.36 thousand yuan per ton. ②The curve of China's marginal carbon reduction cost showed a U-shaped trend over the period 2006-2019， with the majority of cities positioned to the left of the lowest point. ③The inequality in China's marginal carbon reduction costs followed a pattern of initial increase followed by decrease. The overall Gini coefficient declined from 0.220 in 2006 to 0.151 in 2019. ④From 2006 to 2019， China's city-level marginal reduction costs demonstrated <i>σ</i>-convergence characteristics and supported the <i>β</i>-spatial convergence mechanism. There was significant heterogeneity in reduction costs across different economic regions， and the classification of city-level marginal reduction costs showed a trend toward polarization. Although China has achieved some results in carbon reduction， the task difficulty and cost have gradually increased as carbon reduction action has increased. Therefore， to facilitate the coordinated reduction of carbon reduction costs across cities in China， the government should establish inter-city collaborative mechanisms for emissions reduction， promote the coordinated development of green and low-carbon industries among cities， enhance the collaborative application of energy efficiency and energy-saving technologies across urban areas， deepen the collaborative advancement of environmental education and public participation， and innovate the design of inter-city financing models and incentive mechanisms. This would not only help to reduce emission reduction costs but also promote the balanced development of the regional low-carbon economy， helping to achieve the Twin Carbon Targets.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5428-5440"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081734","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":"[Multi-scenario Land Cover Simulation and Carbon Stock Assessment in Shaanxi Province Based on the PLUS-InVEST Model].","authors":"Ming-Yue Cheng, Guang-Xing Ji, Jun-Chang Huang, Jian-Xi Geng, Ling Li, Jie Lu","doi":"10.13227/j.hjkx.202409068","DOIUrl":"https://doi.org/10.13227/j.hjkx.202409068","url":null,"abstract":"<p><p>The rapid development of global society and economy has brought heavy pressure on the natural environment， and the burning of fossil fuels releases a large amount of CO₂， which seriously harms the production and life of human beings. Based on the strategic background of the dual-carbon target， this study selected Shaanxi Province， which accounts for a large area of cropland， woodland， and grassland， as its study area and used the gas emission scenario of SSPs in the IPCC report to study the future period of the province's land-use type changes and the characteristics of its carbon stock changes to provide theoretical suggestions for the changes of ecosystem carbon stocks in Shaanxi Province in the future period. The results of the study follow： ① Under the SSP126 scenario， the change in land use types in Shaanxi Province in 2030-2050 is an increase in the area of woodland and a decrease in the area of cropland and grassland. Under the SSP245 scenario， the change in 2030-2050 is an increase in the area of cropland and building land and a decrease in the area of woodland and grassland. Under the SSP585 scenario， the change in land use types in 2030-2050 consists of an increase in the area of cropland and building land and a decrease in the area of woodland， grassland， and others. ② The simulation study of Shaanxi Province's carbon stock in 2030-2050 found that among the three SSP scenarios Shaanxi Province is most suitable for the development path of SSP126， i.e.， sustainable socioeconomic development and lower gas emissions. ③ Carbon stocks are mainly concentrated in land use types with high carbon density values， such as woodlands and grasslands. An examination of the spatial distribution of land use in Shaanxi Province revealed that areas with high carbon stock values are distributed in the Qinling Mountains in southern Shaanxi， the southern mountainous areas， and in southern Shaanxi. Areas with medium carbon stocks are distributed in the Loess Plateau in central northern Shaanxi， most of the Guanzhong Plain in the Guanzhong Region， and in Hanzhong in southern Shaanxi. Areas with low carbon stocks are mainly distributed in the areas bordering the Mu Us Desert in northern Shaanxi， concentrated or sporadically distributed along the Weihe River Basin in the Guanzhong Region， and sporadically distributed along the Hanjiang River Basin in southern Shaanxi. The area of future low-carbon reserves in Shaanxi Province is larger under the SSP585 scenario than under the other two scenarios.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5729-5740"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081819","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":"[Multi-Scenario Simulation of Land Use Change in Chengyu Economic Zone and Its Influence on Carbon Reserves].","authors":"Fang Wang, Jing Li, Jian Wang, Shou-Yi Xiang, Xin-Ting Chen, Xue-Mei Yi, Xian-Ting Huang, Ting Huang","doi":"10.13227/j.hjkx.202407242","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407242","url":null,"abstract":"<p><p>Land use change is an important factor affecting the carbon cycle and carbon reserves， and multiple scenario simulation of the impact of regional land use change on carbon reserves can provide decision support for formulating scientific land use policies. Taking the Chengdu-Chongqing Economic Zone as an example， based on the evolution characteristics of land use from 1990 to 2020， the impact of land use change on carbon reserves during the 30 years was estimated using the InVEST model， and the coupling PLUS model was used to predict land use change and its impact on carbon reserves in 2030 under the natural development， urban development， and ecological protection scenarios. The study produced several interesting results： ① During 1990-2020， the land use structure in the research area was mainly cultivated land and forest land， which accounted for more than 86% of the area； cultivated land and grassland decreased； construction land， water area， forest land， and unused land increased； and land use transfer was mainly manifested in the mutual transformation between cultivated land and forest land and the transfer of cultivated land for construction land. ② From 1990 to 2020， the carbon reserves showed a distribution pattern of \"middle low， surroundings high\" and a change trend of \"decrease-increase-decrease.\" The total accumulation decreased by 9.29×10⁶ t， which was mainly attributable to the transfer of forest land to other land. The carbon reserves of cultivated land and forest land， which are the main sources of carbon reserves in the research area， accounted for about 90% of the total. ③ From 2020 to 2030， the areas of cultivated land， water area， and unused land all declined， the area of grassland increased， forest land increased under only the ecological protection scenario， and construction land expanded significantly under the urban development scenario. ④ Under the scenarios of natural development and urban development， carbon reserves decreased significantly， while under the scenario of ecological protection， carbon reserves increased significantly due to lower transfer probability of cultivated land， grassland， and forest land to construction land.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5718-5728"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081801","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":"[Analysis of Spatial and Temporal Variation of Vegetation Coverage and Its Influencing Factors in the Kashgar River Basin from 2000 to 2022].","authors":"Fang-Yu Sheng, Fan Gao, Hai-Liang Xu, Bing He, Jie Wu, Kun Liu","doi":"10.13227/j.hjkx.202407188","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407188","url":null,"abstract":"<p><p>Natural vegetation in arid regions plays a crucial role in combating land desertification and maintaining soil and water balance， and understanding its spatiotemporal dynamics and exploring the influencing factors are essential for ecological restoration and policy formulation. This study focused on the Kashgar River Basin， a watershed located in the arid region of northwest China. Using the Google Earth Engine （GEE） platform and MODIS data， fractional vegetation coverage （FVC） was extracted. The Theil-Sen + Mann-Kendall method， coefficient of variation， Hurst index， and multivariate residual regression analysis were employed to examine the spatiotemporal evolution， stability， and persistence of vegetation coverage in the Kashgar River Basin and to assess the impact of climate change and human activities on FVC changes quantitatively. The results of the study follow： ① From 2000 to 2022， the overall trend of FVC in the Kashgar River Basin showed fluctuating growth， with significant spatial heterogeneity. Vegetation coverage was relatively higher in the plains， while mountainous areas were dominated by lower coverage. ② The overall stability of vegetation coverage was high， with 56.88% of the area showing significant improvement in FVC， and the average Hurst index of FVC was 0.48. Future trends suggest that 35.62% of the region will continue to improve. ③ The combined effects of climate change and human activities were identified as the primary drivers of FVC changes in the plains， and precipitation was the main factor influencing FVC in mountainous areas. Human activities significantly impacted FVC， particularly through land use changes， where the interchange between grassland and cropland led to notable improvements in FVC in some regions. These findings provide scientific evidence for land use planning and vegetation restoration in arid regions.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5800-5812"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081911","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":"[Simulation and Prediction of Carbon Storage Change in Ecological Restoration Project Area Based on PLUS-InVEST Model in Aksu River Basin].","authors":"Zhi-Yuan Xu, Bin Wu, Fan Gao, Kun Liu","doi":"10.13227/j.hjkx.202407214","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407214","url":null,"abstract":"<p><p>The geological environment of the arid region in northwest China is unique， characterized by a long-term scarcity of water resources， which results in an extremely fragile ecosystem. In this context， studying the changes in carbon storage characteristics and the driving factors of spatial differentiation before and after the implementation of ecological restoration projects can provide a scientific basis for ecological restoration and sustainable development in arid regions. Based on land use data from 2008， 2013， 2018， and 2023， the study analyzed and predicted land use changes and carbon storage under different historical and future scenarios and explored the driving mechanisms. The study produced several interesting results： ① The spatial distribution pattern of land use changed significantly during 2008-2023. The expansion of cultivated land area was the most significant change， an increase of 12.89×10⁴ hm². ② During 2008-2023， the total carbon storage showed an increasing trend， increasing by 483.97×10⁴ t. ③ Temperature is the main driving factor affecting the spatial distribution of carbon stocks （<i>q</i> value of 0.513）， and the interaction between annual average temperature and distance to government detected by the interaction factor is the main driving factor affecting the spatial distribution of carbon stocks （<i>q</i> value of 0.605）. ④Carbon storage is predicted to show an increasing trend in 2028 under the three scenarios of natural development， ecological protection， and dual protection of farmland ecology. Carbon storage will increase significantly in the ecological protection scenario， but the dual protection of ecology and farmland scenario increases farmland area while protecting the ecology and improving carbon storage. This study provides technical support for evaluating the ecological restoration effectiveness of the Shanshui Project and also provides a scientific reference for local realization of the carbon peaking and carbon neutrality goals. ⑤ With the implementation of ecological restoration projects， the area of ecological land in the region has increased in comparison to the period prior to these projects. Moreover， carbon storage has transitioned from a reduction of 382.95×10⁴ t in the previous period to an increase of 277.2×10⁴ t， indicating the significant effectiveness of the ecological protection initiatives.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5752-5764"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081923","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 and Temporal Dynamic Evolution of Carbon Emission Intensity of County Energy Consumption in Gansu Province and Its Emission Reduction Effectiveness].","authors":"Wei-Ping Zhang, Pei-Ji Shi, Fan-Yuan Cheng","doi":"10.13227/j.hjkx.202407238","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407238","url":null,"abstract":"<p><p>Scientifically estimating and dynamically monitoring the development trend of regional energy consumption carbon emissions and their intensity is the scientific basis and basic guarantee for formulating， implementing， and evaluating regional carbon reduction strategies. Based on long time-series DMSP/OLS and NPP/VIIRS nighttime light datasets， this paper simulates the carbon emissions and their intensity of energy consumption in counties in Gansu Province from 2000 to 2020. Non-parametric kernel density estimation， spatial Markov chain， spatial variation function， and other models are used to analyze the spatiotemporal dynamic evolution characteristics of carbon emission intensity， and correction coefficients are used to test the effectiveness of reducing carbon emission intensity in each county. The results follow： ① During the research period， the overall carbon emission intensity of energy consumption in Gansu Province showed a downward trend， with a 64.82% decrease in energy consumption carbon emission intensity in 2020 compared to 2000. ② The carbon emission intensity of counties showed obvious spatial agglomeration characteristics， and the high carbon intensity areas mainly in Lanzhou City in Longzhong， Jiuquan City in Hexi， and Qingyang City in Longdong are gradually transforming into low-carbon intensity areas. ③ The carbon emission intensity at the county level showed a club convergence effect and spatial correlation， and the spatial differences in carbon emission intensity at the county level gradually decreased. ④ By 2020， more than half of the counties in Gansu Province had achieved significant emission reduction results， but there were still some counties whose carbon emission intensity had decreased below the provincial average， indicating that county units should also follow the principle of common but differentiated responsibilities when promoting carbon reduction. The research results provide important references for promoting regional green and low-carbon transformation and energy conservation and carbon reduction in Gansu Province.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5490-5502"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081866","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":"[Analysis of Vegetation Changes and Influencing Factors in Guiyang City over the Past 33 Years Based on the kNDVI and OPGD Model].","authors":"Zu-Lun Zhao, Xiao Jiang, Yin Su, Lin-Jiang Yin, Ting Luo, Wei-Quan Zhao, Jun-Hua Luo","doi":"10.13227/j.hjkx.202408129","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408129","url":null,"abstract":"<p><p>The vegetation index is a critical indicator for monitoring changes in terrestrial ecosystems， and understanding the spatiotemporal characteristics of vegetation changes and their potential driving factors is essential for improving regional ecological protection and management. This study utilized eight periods of Landsat remote sensing images from 1990 to 2023 to calculate the kernel normalized difference vegetation index （kNDVI） for Guiyang City using the Google Earth engine （GEE） platform. The Theil-Sen + Mann-Kendall trend analysis method was applied to assess the trends and significance levels of kNDVI changes， and the Hurst index was used to evaluate the persistence and future trends of kNDVI. Additionally， the optimal parameters geographic detector （OPGD） was employed to analyze the driving mechanisms behind the spatial differentiation of kNDVI. The study produced the following results： ① From 1990 to 2023， the kNDVI in Guiyang City exhibited a fluctuating upward trend over four distinct phases， with significant spatial differentiation， generally displaying a north-high， south-low distribution pattern. ② Over the 33 years， 74.62% of the area in Guiyang City experienced improvement in vegetation cover， while 25.14% showed signs of degradation. ③ The average Hurst index was 0.610 2， indicating weak persistence and suggesting a trend of continued improvement into the future for vegetation kNDVI in Guiyang City. ④ The land-use type factor （0.231 2） showed the strongest explanatory power for the spatial differentiation of vegetation kNDVI. The interactions between factors exhibited both nonlinear enhancement and bi-factor enhancement， with the combination of land use and other factors synergistically explaining the spatial differentiation of kNDVI more effectively.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5839-5849"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081986","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":"[Driving Effect of Digital Economy Development on Urban Carbon Emissions： From Spatial Spillover to Spatial Network].","authors":"Fei-Fei Tan, Chen-Yu Sun","doi":"10.13227/j.hjkx.202407203","DOIUrl":"https://doi.org/10.13227/j.hjkx.202407203","url":null,"abstract":"<p><p>The digital economy， as a new driving force leading the technological revolution， integrates informatization and greening， thus serving as a crucial lever for advancing the development of new productive forces. It offers new opportunities for China's green and low-carbon development and strengthens the network connections between regions through spatial effects， effectively reducing urban carbon emissions. Based on panel data at the level of 278 prefecture-level cities from 2011 to 2019， an empirical analysis was performed to assess the impact and spatial mechanisms of China's digital economy development on urban carbon emissions. The results showed that the level of digital economy development drives urban carbon reduction， and this conclusion remained valid after a series of robustness tests. The development of the digital economy has a significant spatial spillover effect on urban carbon emissions. From a spatial network perspective， higher degrees of centrality and closeness in the network aid low-carbon development driven by the digital economy. Dense urban networks facilitate the enhancement of green innovation levels， further increasing the capacity for urban carbon reduction； thus， the eastern part of the country， cities in urban agglomerations， and non-resource cities can better advantage the dividends brought by the digital economy.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5441-5453"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081662","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 China's Agricultural Non-point Source Pollution Intensity： Spatial and Temporal Differentiation， Dynamic Evolution and Spatial Agglomeration].","authors":"Yun Tian, Rui Xia, Xing-Yan Zhang","doi":"10.13227/j.hjkx.202408128","DOIUrl":"https://doi.org/10.13227/j.hjkx.202408128","url":null,"abstract":"<p><p>Accurately assessing the intensity of agricultural non-point source pollution （ANPSP） is of great practical significance for promoting the sustainable development of agriculture and the modernization of agriculture and rural areas. This paper explores the spatial and temporal differentiation， dynamic evolution， and spatial agglomeration characteristics of China's ANPSP intensity from 2005 to 2022 based on a comprehensive evaluation of China's ANPSP intensity. The results of the study follow： ① At the national level， China's ANPSP intensity increased in some years， but on the whole showed a fluctuating downward trend， which can be categorized into three different stages， namely， rapid rise， fluctuating decline， and continuous rapid decline. At the regional level， the main grain-producing areas， main grain marketing areas， and production and marketing balance areas of ANPSP intensity all showed a fluctuating downward trend， although the differences between these areas were large. The main grain-producing areas showed the largest decline， and the main grain marketing areas showed the smallest decline. At the inter-provincial level， the intensity of ANPSP in 2022 was highest in Qinghai and lowest in Shanghai. ② China's ANPSP intensity showed a decreasing trend， and the gap between regions narrowed. Although the ANPSP intensity of the main grain producing areas， main grain marketing areas， and production and marketing balance areas also showed a decreasing trend， there was still a certain difference between each. ③ Although the global Moran's index of China's ANPSP intensity from 2005 to 2022 showed some fluctuation， the overall trend was downward. Overall， there was obvious spatial positive correlation， with most provinces showing the high-high concentration or low-low concentration type. During the period of investigation， the level of China's ANPSP intensity remained stable， and the type generally did not change. The probability of no transformation of type was at least 82.03%. With the introduction of spatial factors， the ANPSP intensity level in each province continued to be stable， but some fluctuation occurred.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5608-5618"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081698","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":"[Scenario Prediction of Carbon Emissions from the Paper Industry in Guangdong Province Based on the Extended STIRPAT Model].","authors":"Hong-Ping Wang, Jian-Zhou Yang","doi":"10.13227/j.hjkx.202409169","DOIUrl":"https://doi.org/10.13227/j.hjkx.202409169","url":null,"abstract":"<p><p>Guangdong Province is one of the provinces in China with a developed paper industry， and accurately predicting carbon emissions from the paper industry in Guangdong Province and formulating reasonable and effective carbon emission reduction measures have a significant impact on achieving the carbon peaking and carbon neutrality goals of China's paper industry. To this end， total industrial output value， employment scale， per capita industrial output value， carbon productivity， energy intensity， and energy structure indicators were introduced to construct the extended stochastic environmental impact assessment （STIRPAT） model， the partial least squares method was used for regression analysis， and the carbon emissions of Guangdong's paper industry from 2023 to 2050 under four scenarios were predicted. The study produced several results： ① Total industrial output value， per capita industrial output value， employment scale， and energy intensity are positively correlated with carbon emissions， whereas carbon productivity and energy structure are negatively correlated with carbon emissions. ②Under the baseline scenario， the paper industry can only achieve carbon peaking in 2040； under the low-carbon development scenario， although the paper industry can achieve carbon peaking by 2030， its carbon emissions will remain between 16.147 Mt and 19.337 Mt by 2050； under the strong low-carbon development scenario， the paper industry can not only achieve carbon peaking by 2030 but is also expected to achieve carbon neutrality by 2060. ③Under the fast development scenario， the carbon emissions of the paper industry maintain an upward trend， and the carbon emissions reach a high level in 2050， making it basically impossible to achieve the \"dual carbon\" goal. Therefore， Guangdong's paper industry should rationally plan the development of its paper production scale， actively enhance carbon productivity， optimize energy structure， and promote green technological advancements in the industry， thereby driving green and sustainable development of the paper industry.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 9","pages":"5535-5542"},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081917","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}