Analysis of CO2 Drivers and Emissions Forecast in a Typical Industry-Oriented County: Changxing County, China

Yao Qian,Xiaoqi Shang,Lina Tang,Lang Sun,Chengxiu Lu,Quanyi Qiu

doi:10.3390/en13051212

Abstract

Decomposing main drivers of CO2 emissions and predicting the trend of it are the key to promoting low-carbon development for coping with climate change based on controlling GHG emissions. Here, we decomposed six drivers of CO2 emissions in Changxing County using the Logarithmic Mean Divisia Index (LMDI) method. We then constructed a model for CO2 emissions prediction based on a revised version of the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and used it to simulate energy-related CO2 emissions in five scenarios. Results show that: (1) From 2010 to 2017, the economic output effect was a significant, direct, dominant, and long-term driver of increasing CO2 emissions; (2) The STIRPAT model predicted that energy structure will be the decisive factor restricting total CO2 emissions from 2018 to 2035; (3) Low-carbon development in the electric power sector is the best strategy for Changxing to achieve low-carbon development. Under the tested scenarios, Changxing will likely reach peak total CO2 emissions (17.95 million tons) by 2030. Measures focused on optimizing the overall industrial structure, adjusting the internal industry sector, and optimizing the energy structure can help industry-oriented counties achieve targeted carbon reduction and control, while simultaneously achieving rapid economic development.

Highlights

Human health, ecosystems, and socio-economic systems are sensitive to the pace and extent of climate change, with some adverse impacts of climate change becoming persistent or irreversible
This suggests that the cumulative total effects of CO2 emissions measured by the Logarithmic Mean Divisia Index (LMDI) decomposition
Changes in CO2This emissions (Figure 2).inThis current study with showing the highest values of the driving factors we analyzed suggests that the cumulative total effects of CO2 emissions measured by the LMDI decomposition gdp from 2010 to 2016.with

Summary

Introduction

Ecosystems, and socio-economic systems are sensitive to the pace and extent of climate change, with some adverse impacts of climate change becoming persistent or irreversible. Global average surface warming by the end of the 21st century is projected to depend mainly on accumulative CO2 emissions. The massive emissions of CO2 from various human activities are key drivers of climate change issues such as global warming. Fossil fuel combustion is a major source of CO2 emissions [1,2]. Strategies that effectively control CO2 emissions and achieve low-carbon development are needed to mitigate climate change. The international community has largely reached a consensus on low-carbon development, with most countries participating in international agreements such as the United Nations Framework Convention on Climate Change (UNFCCC), the Kyoto Protocol, and the Copenhagen Accord.

Methods

Results

Conclusion