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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Material footprints of Chinese megacities
TL;DR: Wang et al. as discussed by the authors used input-output analysis to assess total material footprints and investigate the trends of material footprints time series of four Chinese megacities ( Beijing, Shanghai, Chongqing, and Tianjin) from 2001 to 2015, along with factors that influence this material footprint by adopting STIRPAT model.
Journal ArticleDOI
A fractional multi-stage simulation-optimization energy model for carbon emission management of urban agglomeration
TL;DR: In this paper, a fractional multi-stage simulation-optimization energy model is developed to tackle multiple uncertainties in regional energy systems and reflect system efficiency under conflicting objectives by integrating support vector regression, Monte Carlo simulation and stochastic impacts by regression on population, affluence, and technology tool into a general framework.
Journal ArticleDOI
Analysis of the impact path on factors of China's energy-related CO2 emissions: a path analysis with latent variables.
TL;DR: A path analysis model with latent variables (PA-LV) is used to estimate the direct and indirect effect of factors on China’s energy-related carbon emissions and to investigate the causal relationships among variables.
Journal ArticleDOI
Greening manufacturing: Technology intensity and carbon dioxide emissions in developing countries
TL;DR: In this article , the authors investigated the effect of technology intensity across manufacturing industries on carbon dioxide emissions: are medium and high-technology manufacturing industries less emissions-intensive than low technology manufacturing industries in developing countries?
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Probing Energy-Related CO 2 Emissionsin the Beijing-Tianjin-Hebei Region Basedon Ridge Regression ConsideringPopulation Factors
Lei Wen,Zhiqun Zhang +1 more
TL;DR: In this article, the authors used the extended STIRPAT model and ridge regression method to pay attention to the impact of population factors on carbon dioxide emissions in the Beijing-Tianjin-Hebei region.
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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