2018
DOI: 10.3390/ijerph15112343
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Can Environmental Quality Improvement and Emission Reduction Targets Be Realized Simultaneously? Evidence from China and A Geographically and Temporally Weighted Regression Model

Abstract: The reductions of industrial pollution and greenhouse gas emissions are important actions to create an ecologically stable civilization. However, there are few reports on the interaction and variation between them. In this study, the vertical and horizontal scatter degree method is used to calculate a comprehensive index of industrial pollution emissions. Then based on carbon density, a geographically and temporally weighted regression (GTWR) model is developed to examine the interaction between industrial pol… Show more

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Cited by 7 publications
(2 citation statements)
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“…The current study uses the vertical and horizontal layer-by-layer scatter degree method for multidimensional health level measurement. This method is a dynamic measurement of panel data that builds a time series three-dimensional data table, processing the underlying data layer by layer from the bottom up, calculating the weights, and obtaining the composite index [ 41 ]. The basic principle of this method is as follows:…”
Section: Methodsmentioning
confidence: 99%
“…The current study uses the vertical and horizontal layer-by-layer scatter degree method for multidimensional health level measurement. This method is a dynamic measurement of panel data that builds a time series three-dimensional data table, processing the underlying data layer by layer from the bottom up, calculating the weights, and obtaining the composite index [ 41 ]. The basic principle of this method is as follows:…”
Section: Methodsmentioning
confidence: 99%
“…Through the SDA-EIOT model, Liang and Zhang [13] analyzed the factors that affect carbon emissions in Jiangsu Province, the manufacturing center of Southern China, pointing out that Jiangsu Province should not only focus on the reduction of energy consumption intensity and the optimization of energy consumption structure, but also pay more attention to the decline of hidden carbon in international export trade. By weighing the geographic information and energy consumption changes of the provinces, Dong et al [14] analyzed the correlation between industrial pollution and CO 2 emissions in eastern, western, and central China, pointing out that industrial carbon emissions play a significant role in promoting the increase of carbon density. Due to spatio-temporal heterogeneity, this kind of promoting effect differs between provinces, while the estimated parameter results of neighboring provinces are not substantially different.…”
Section: Literature Reviewmentioning
confidence: 99%