ArticleScientific reports2023
Study on spatiotemporal distribution characteristics and driving factors of carbon emission in Anhui Province.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 18 citations in OpenAlex.
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1 author at 1 institution in 1 country.
Funding
Abstract
Carbon emission is related to global ecological security, and economic development inevitably leads to an increase in carbon emission. In recent years, as a rapidly developing province in China's economy, Anhui Province has experienced significant differences in the spatiotemporal distribution of carbon emission in different regions due to differences in development foundation, urbanization level, population size, industrial structure, etc., providing representative empirical cases for research. Based on the carbon emission data of Anhui Province before the COVID-19, this study used exploratory spatial data analysis method and Geodetector to analyze the spatial and temporal distribution characteristics and drivers of carbon emission in Anhui Province. The study found that (1) the spatial differentiation and spatial correlation of carbon emission in Anhui Province are significant, At the beginning, it shows the characteristics of "high north and low south" and "high west and low east", and then the "core-edge" structure of carbon emission becomes obvious. Carbon emission hotspot areas increase and then decrease, mainly in Hefei, Fuyang and Chuzhou City, etc. The coldspot areas are mainly located in the southern and western mountainous areas, and the degree of aggregation is decreasing year by year. (3) The level of urbanization, economic development and population size are the main driving factors of the spatial variation of carbon emissions, while the industrial structure has the least influence. And most factors produce nonlinear enhancement when spatially superimposed with other factors. (4) The high value areas of economic development, population density, secondary industry structure, and energy intensity are all at high levels of carbon emission, and a combination of factors leads to the creation of high risk areas for carbon emission. The study provides a basis for reducing carbon emission in the next stage of Anhui Province, focusing on key carbon emission areas, and sustainable development.
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Registered trials
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