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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Spatio-temporal interaction heterogeneity and driving factors of carbon emissions from the construction industry in China
Xiaomin Guo,Chuanglin Fang +1 more
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Economic and environmental feasibility of re-routing the Indo-Sri Lankan shipping channel: a green initiative of sustainable development
Jayakrishna Kandasamy,Simon Peter Nadeem,Anil Kumar,Vimal K.E.K,Hrishikesh Bedekar Nikhil,Nikhilkumar Himatlal Solanki +5 more
TL;DR: In this article, the authors explored the merits of the Indo-Sri Lankan shipping canal project over the existing route circumnavigating Sri Lanka and quantified the socio-political, environmental and economic benefits reported in this study.
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The forecasting model research of rural energy transformation in Henan Province based on STIRPAT model
Lei Wen,Qianqiang Song +1 more
TL;DR: Wang et al. as discussed by the authors employed the Tapio decoupling model to investigate the pivotal factors affecting rural power consumption (PC) and total energy consumption (TEC) in Henan Province.
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Analysis of allometric relationship and formation mechanism between economic growth and carbon emissions in the Yangtze River Delta
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The Scenario Forecasting Analysis of CO2 Emissions of China
Jianjun Wang,Li Li +1 more
TL;DR: In this paper, the authors used STRIPAT models to find the impact of population, economy and technology on CO2 emissions of China and showed that if Chinas economic, population, and energy consumption is increasing 7, 0.4, 5, and 5% every year, respectively, CO2 emission will reach 21.05×108t in 2020.
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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