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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Spatial Variation of NO2 and Its Impact Factors in China: An Application of Sentinel-5P Products
TL;DR: The comparison of Coefficient of Variation and spatial autocorrelation models at two kinds of administrative scales indicates that although the spatial heterogeneity of NO2 column concentration is less affected by the observed scale, there is a “delayed effect” of about one month in the process of NO1 column concentration fluctuation.
Journal ArticleDOI
The role of economic policy uncertainty in the energy-environment nexus for China: Evidence from the novel dynamic simulations method.
Azka Amin,Eyup Dogan +1 more
TL;DR: In this article, the authors explore the function of economic policy uncertainty in the energy-environment nexus for China by using the novel bounds testing with dynamic simulations, and they find that an increase in EPU causes an increase of the volume of carbon emissions.
Journal ArticleDOI
Scenario analysis of carbon emissions' anti-driving effect on Qingdao's energy structure adjustment with an optimization model, Part I: Carbon emissions peak value prediction
TL;DR: In this paper, an extended STIRPAT model was introduced to determine the relationship between CO2 emissions and different driving factors (permanent resident population, economic level, technical level, urbanization level, energy consumption structure, service level, and foreign trade degree).
Journal ArticleDOI
Examining the effects of socioeconomic development on China's carbon productivity: A panel data analysis
TL;DR: The results indicated that China's carbon productivity increased gradually between 1997 and 2016, and carbon productivity in East China was much higher than that of their counterparts in Central China and West China, and Provincial administrative units with highly developed economies witnessed spectacular increases in carbon productivity.
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An extended STIRPAT model-based methodology for evaluating the driving forces affecting carbon emissions in existing public building sector: evidence from China in 2000–2015
TL;DR: Wang et al. as discussed by the authors utilized the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and ridge regression analysis to evaluate the driving forces affecting CECPB from 2000 to 2015.
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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