基于LEAP模型和KAYA模型的主城区碳达峰预测及不确定性分析

doi:10.19741/j.issn.1673-4831.2022.0205

摘要/Abstract

摘要： CO₂排放是城市碳达峰预测研究的重要内容,准确核算碳排放对实现城市产业绿色转型发展与碳中和具有重要意义。主城区产业以生活功能、生产研发和服务业为主,缺乏独立的主城区能源消费统计,导致碳排放核查存在空白。为此,以南京某市辖区为研究对象,结合2011-2020年南京市能源统计数据,从碳排放影响因素和终端能源消费计算2个方面分析市辖区碳排放特征,并采用Kaya碳排放恒等式和LEAP模型,设置不同的情景,预测未来碳排放趋势和达峰时间。结果表明:2011-2020年研究区能源消费从108.99万增长至222.02万t (以标准煤计),CO₂排放量仍处于快速增长期,2020年碳排放量相比2011年增长82.27%,但能耗强度由0.324下降到0.200 t·万元^-1,化石燃料使用占比逐渐减少,用电量增加。2020年研究区碳排放强度为0.337 t·万元^-1,低于南京市平均水平(0.75 t·万元^-1)。积极推动低碳转型发展,研究区可实现2030年前碳达峰的目标。人均生产总值和能源强度是影响主城区碳排放的最重要因素。研究结果为主城区碳达峰预测提供了一种可行的核算方法,对城市碳排放核算、减排模式优选及减排任务分解具有指导意义。

关键词: 碳排放, 主城区, 能源, 情景预测, 碳达峰

Abstract: Carbon (CO₂) emission is an important part of researches on urban carbon peak emission prediction. Accurate accounting of carbon emission is of great significance to achieve urban green transformation and development of urban industries and carbon neutrality. The industries in the main urban area are mainly based on living functions and Production R & D, and service industries, and there is a lack of independent statistical data such as energy consumption, which resulting in gaps in carbon emission verification. To this end, taking a municipal district in Nanjing City, Jiangsu Province as the research object, combined with the energy consumption statistics of Nanjing City from 2011 to 2020, this paper judges the carbon emission peaking situation in the municipal districts from the two aspects of "carbon emission influencing factors" and "terminal energy consumption calculation", The Kaya carbon emission identity and LEAP model were used to set different scenarios to predict the future carbon emission trend and peak time. The results show that:(1) From 2011 to 2020, energy consumption in the study area increased from 1 089 900 tons of standard coal to 2 220 200 tons of standard coal, and CO₂ emissions were still in a period of rapid growth. Carbon emissions in 2020 increased by 82.27% compared with 2011. However, the energy consumption intensity gradually decreased from 0.324 to 0.200 tons of standard coal per 10 000 yuan; the proportion of the use of fossil fuels gradually decreased, while the electricity consumption increased. (2) The carbon emission intensity of the study area in 2020 is 0.337 t·10 000 yuan^-1, which is lower than the average level of Nanjing (0.75 t·10 000 yuan^-1). By actively promote low-carbon transformation development, the research area will be able to achieve the goal of carbon emmision peaking by 2030. (3) GDP per capita and energy intensity are the two most important factors affecting urban carbon emissions. The research results provide a feasible accounting method for the prediction of carbon emission peaking in the main urban area, which has guiding significance for urban carbon emission accounting, emission reduction model optimization and emission reduction task allocation.

Key words: carbon emissions, main urban area, energy, scenario forecasts, carbon emission peaking

中图分类号:

X24
X196

杜涵蓓, 赵立君, 刘臣炜, 仇宽彪, 李海东. 基于LEAP模型和KAYA模型的主城区碳达峰预测及不确定性分析[J]. 生态与农村环境学报, 2022, 38(8): 983-991.

DU Han-bei, ZHAO Li-jun, LIU Chen-wei, QIU Kuan-biao, LI Hai-dong. Prediction of Peaking Carbon Dioxide Emissions in Main City Areas Based on LEAP Model and KAYA Model and Analyses on Its Uncertainty[J]. Journal of Ecology and Rural Environment, 2022, 38(8): 983-991.

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