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Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model
Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model
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Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model
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Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model
Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model

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Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model
Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model
Journal Article

Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model

2013
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Overview
This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40-45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China's low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance.