CO emissions from transportation (TC) are one of the main causes of global climate change. China faces particularly severe pressures and challenges in transportation carbon reduction. Based on the panel data of 30 provinces in China from 2000 to 2015, this study explored the influencing factors and spatial spillover effects of TC by estimating spatial panel data models. It found that China's TC will continue to increase in the future, because the increase in per capita gross domestic product (GDP) is the primary driving force to accelerate the growth of TC, but an increasing proportion of tertiary industry (PTI) in the national economy will help reduce the growth in emissions. Moreover, urban road density (URD) and per capita highway mileage (PHM) are the other two major factors promoting the growth of TC. In contrast, urban population density (UPD) has a negative direct impact on per capita CO emissions from transportation (PTC) but also has a larger positive spatial spillover effect, which indicates that these three factors should be properly planned and controlled. Meanwhile, we should actively advocate the development of urban public transport because it plays an important role on reducing TC. The conclusions provide important inspiration and a scientific basis for formulating policies to effectively curb the growth of CO emissions in China.
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http://dx.doi.org/10.1016/j.scitotenv.2019.133900 | DOI Listing |
Sci Rep
December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including the management of agricultural carbon reduction, emerging as a mainstream approach. This study examines 268 prefecture-level cities in China, measuring the carbon emission efficiency of city agriculture from 2001 to 2022. By integrating social network analysis and a modified gravity model, the study reveals the characteristics of the spatial association network of city agricultural carbon emission efficiency in China.
View Article and Find Full Text PDFSci Rep
December 2024
School of Geography, Liaoning Normal University, Dalian, 116029, China.
Sustainable development is a hot topic of global concern and sustainable human settlements (HS) are crucial to people's happiness. Thus, strengthening the construction of HS will help enrich human settlements geography with theories of HS interactions, clarify the existing problems of the Chengdu-Chongqing urban agglomeration (CC), promote the harmonization of the human-land relationship, and realize the SDGs. The results were as follows.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
December 2024
Institute of Marine Economics and Management, Shandong University of Finance and Economics, Lixia District, Second Ring East Road, Jinan, 7366250000, China.
Biodiversity is crucial for maintaining ecosystem stability and achieving sustainable development. However, global biodiversity loss is a common challenge faced by most countries. Therefore, based on the data from the International Union for Conservation of Nature (IUCN) Red List of Threatened Species and the Eora database, we used the multi-regional input-output (MRIO) model to calculate biodiversity loss in 188 countries.
View Article and Find Full Text PDFHuan Jing Ke Xue
January 2025
Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China.
Based on the super-efficiency SBM model with unexpected output, this study calculated the urban carbon emission efficiency in order to study the regional differences and spatial spillover effects of urban carbon emission efficiency in the Yangtze River Delta. From 2001 to 2020, the highest average of urban carbon emission efficiency in the Yangtze River Delta was only 0.698, with a low overall level and a flat "Inverted-U" evolution trend.
View Article and Find Full Text PDFJ Environ Manage
December 2024
Department of Economics and Management Science, Xinhua College of Ningxia University, Yinchuan, 750021, China; Graduate School of Business, Universiti Sains Malaysia, George Town, 11800, Malaysia. Electronic address:
Global warming caused by carbon emissions has become a significant concern for countries worldwide. This study thoroughly examines the spatiotemporal patterns and spatial spillover effects of carbon emissions in China. This research employs kernel density estimation, Moran's index, and the standard deviation ellipse model to analyse the spatiotemporal evolution of carbon emissions in China while utilizing the spatial Durbin model to explore the spatial spillover effects of the digital economy on carbon emissions.
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