Journal ArticleDOI
Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China
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TLDR
In this article, the authors examined the impact factors of population, economic level, technology level, urbanization level, GDP per capita, industrialization level and service level on the energy-related CO2 emissions in Guangdong Province, China from 1980 to 2010 using an extended STIRPAT model.Citations
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Can Energy Structure Optimization, Industrial Structure Changes, Technological Improvements, and Central and Local Governance Effectively Reduce Atmospheric Pollution in the Beijing–Tianjin–Hebei Area in China?
TL;DR: In this article, the authors take carbon emission as a pollution index, and adopts an extended stochastic impacts by regression on population, affluence, and technology (STIRPAT) model in order to study the impact of the optimization of industry structure (in particular the reduction of the proportion of energy-intensive secondary industry), optimization of the energy structure, and technological improvements on the atmospheric environmental quality.
Journal ArticleDOI
Driving Factors of CO2 Emissions: Further Study Based on Machine Learning
TL;DR: In this paper, the authors investigated the relationship between CO2 emissions and economic growth, industry structure, urbanization, research and development (R&D) investment, actual use of foreign capital, growth rate of energy consumption in China between 2000 and 2018.
Journal ArticleDOI
Panel estimation for the impact factors on carbon dioxide emissions: A new regional classification perspective in China
TL;DR: Wang et al. as mentioned in this paper investigated the regional differences in terms of the effect of population size, GDP per capita, energy structure, energy intensity, urbanization level and industrialization level on CO2 emissions by STIRPAT model.
Journal ArticleDOI
Impact of land use changes on catchment soil erosion and sediment yield in the northeastern China: A panel data model application
TL;DR: In this paper, a panel data method was applied to quantify the impact of land use change on SESY in 1954, 1975, and 2015, based on the WaTEM/SEDEM model and seven landscape metrics for 25 reservoir catchments in northeastern China.
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Analysis of Influencing Factors and Trend Forecast of CO2 Emission in Chengdu-Chongqing Urban Agglomeration
TL;DR: The results show that, first, the CO2 emissions of the Chengdu-Chongqing urban agglomeration have accumulated year by year, but by 2030, as predicted, it will not reach its peak, and the spatial layout ofCO2 emissions in this region is not expected to undergo major changes by 2030.
References
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Journal ArticleDOI
Ridge regression: biased estimation for nonorthogonal problems
TL;DR: In this paper, an estimation procedure based on adding small positive quantities to the diagonal of X′X was proposed, which is a method for showing in two dimensions the effects of nonorthogonality.
Journal ArticleDOI
Impact of Population Growth
Paul R. Ehrlich,John P. Holdren +1 more
TL;DR: In this paper, the authors argue that population growth causes a disproportionate negative impact on the environment and that the control of population is necessary but not sufficient means of seeing us through the whole crisis of environmental deterioration.
Journal ArticleDOI
Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
TL;DR: In this article, the authors discuss a class of biased linear estimators employing generalized inverses and establish a unifying perspective on nonlinear estimation from nonorthogonal data.
Journal ArticleDOI
STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts
TL;DR: In this paper, the STIRPAT model is augmented with measures of ecological elasticity, which allows for a more precise specification of the sensitivity of environmental impacts to the forces driving them.
Book
Multicollinearity in Regression Analysis; the Problem Revisited
TL;DR: An attempt is made to define multicollinearity in terms of departures from a hypothesized statistical condition, and measures are proposed here that fill this need.
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STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts
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