广西壮族自治区碳排放时空规律及达峰预测

高淼; 吴秀芹

doi:10.11932/karst20230410

广西壮族自治区碳排放时空规律及达峰预测

doi: 10.11932/karst20230410

高淼,
吴秀芹^,

北京林业大学水土保持学院, 北京 100083

基金项目: 广西重点研发计划（广西岩溶生态系统碳汇功能及固碳潜力提升技术研究与示范）（桂科AB22035004）

详细信息

作者简介:
高淼（1998－），女，硕士，研究方向：3S技术集成开发与应用。E-mail：530799032@qq.com

通讯作者:
吴秀芹（1974－），女，教授，博士，研究方向：为3S应用、土地利用变化。E-mail：wuxq@bjfu.edu.cn。

中图分类号: X321
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出版历程
- 收稿日期: 2022-06-14
- 录用日期: 2023-02-23
- 刊出日期: 2023-11-28

Temporal and spatial characteristics and peak prediction of carbon emissions in Guangxi Zhuang Autonomous Region

GAO Miao,
WU Xiuqin^,

School of Soil and Water Conservation, Beijing Forestry University, Beijing, 100083, China

摘要

摘要: 广西壮族自治区是国家重要的工业原料供应地，但工业化进程缓慢致使碳排放增长显著，为了积极响应国家减排号召，探究广西历史及未来碳排放规律，以期尽早实现碳达峰目标。由于县级碳排放数据可获取性方面的限制，研究以2003—2017年广西县级碳排放数据，进行广西碳排放量、碳排放强度及碳排放压力的时空变化分析，划分广西不同地域碳排放类型和碳排放情景，并利用可扩展的随机性环境影响模型（STIRPAT）对2022—2035年间广西各地域碳排放类型进行了不同情景下碳排放达峰预测。（1）2003—2017年间，广西碳排放总量、碳排放压力增幅明显，碳排放强度明显降低。碳排放总量变异系数总体趋势平稳，呈高强度变异。（2）依据碳排放总量、强度、压力分级组合，碳排放可分为高总量−高强度−高压力型等6种地域类型，根据广西碳排放影响因素的现状及未来发展趋势划分基准情景、节能情景等7种情景。（3）广西全域达峰预测结果显示，4种节能发展情景均能在2030年前完成达峰目标。不同地域类型达峰预测结果显示高总量−高强度−低压力型与高总量−低强度−低压力型采用节能情景可以实现达峰目标。高总量−高强度−高压力型和高总量−低强度−高压力型无法完成达峰目标。低总量−低强度−低压力型，基准情景等5种情景均能在2030年前完成达峰目标。低总量−高强度−低压力型在2018年便已实现达峰目标。研究系统分析了广西整体及内部碳排放变化，指出了可达峰的情景模式，可为广西碳排放预测，制定减排措施提供理论与技术支持。
- 广西壮族自治区 /
- 县域碳排放 /
- 时空变化特征 /
- STIRPAT模型
Abstract: Under the background of increasing international attention to the topic of global warming, in 2020 China was committed to peaking carbon emissions by 2030 with its enhancing independent contribution and powerful policies and measures. All provinces and localities actively respond to the commitment. Guangxi Zhuang Autonomous Region is an important source of industrial raw materials for China, but the slow industrialization and the excessive reliance of economic growth on industrial development have led to a significant increase in carbon emissions. Therefore, the purpose of exploring the historical and future laws of carbon emissions in Guangxi Zhuang Autonomous is to achieve the carbon peak goal as soon as possible.The research is based on the county-level carbon emission data of Guangxi Zhuang Autonomous Region from 2003 to 2017, sourced from Carbon Emission Accounts and Datasets (CEADS) which has the longest time span (from 1997 to 2017), the widest coverage and the highest accuracy of China's data on county-level carbon emissions. By GIS spatial analysis method, trend analysis and analysis of exploratory spatial data, the temporal and spatial changes of three indicators—carbon emissions, carbon emission intensity and carbon emission pressure—are analyzed at provincial, municipal and county levels in Guangxi. According to the hierarchical combination of the three indicators, Guangxi Zhuang Autonomous Region is divided into six different types of regional carbon emissions, and on this basis, seven carbon emission scenarios are simulated in terms of future population, and social and economic development. The extensible stochastic environmental impact model (STIRPAT) is used to predict the peak of carbon emissions in different scenarios for the types of regional carbon emissions in Guangxi from 2022 to 2035. (1) From 2003 to 2017, the total carbon emissions of Guangxi Zhuang Autonomous Region increased significantly, and the carbon emissions at the city level showed a spatial pattern of Nanning City being the highest and Fangchenggang City being the lowest. Carbon emissions at the county level showed disequilibrium. Though the carbon emission intensity significantly reduced, it showed a spatial pattern of being the highest in Laibin City and the lowest in Hezhou City. The index of carbon emission pressure increased significantly. The overall trend of variation coefficient of total carbon emissions is stable, showing high-intensity variation. (2) According to the classification and combination of total carbon emission, carbon emission intensity and carbon emissions pressure, carbon emissions can be divided into six regional types, including high total amount-high intensity-high pressure type (H-H-H), high total amount-low intensity-high pressure type (H-L-H), high total amount-low intensity-low pressure type (H-L-L), high total amount-high intensity-low pressure type (H-H-L), low total amount-high intensity-low pressure type (L-H-L), and low total amount-low intensity-low pressure type (L-L-L). According to the current scenario and future development of influencing factors of carbon emissions in Guangxi, seven scenarios are divided, including benchmark scenario, energy-saving scenario, scenario of rapid economic development, scenarios of simultaneous development of economy and emission reduction (a and b), scenario of green development and scenario of emission reduction. (3) The forecast results of Guangxi's whole carbon peak period show that four scenarios such as energy-saving scenario, scenario of simultaneous development of economy and emission reduction (b), scenario of green development and scenario of emission reduction can achieve the peak carbon emmissions by 2030. The peak time of carbon emissions is 2023, 2030, 2029 and 2030 respectively. The prediction results of reaching peak carbon emissions in different regions show that the energy-saving scenarios of H-H-L and H-L-L can achieve the goal of peak reaching. The H-H-H type and H-L-H type cannot achieve the peak goal. The benchmark scenario and the rest five scenarios of L-L-L can all achieve the peak by 2030. The L-H-L type reached its peak in 2018. The research systematically analyzes the overall and internal changes of carbon emissions in Guangxi Zhuang Autonomous Region, and points out the scenario mode of reaching the peak carbon emissions, which provides a strong reference for the measures and plans of emission reduction taken by Guangxi government. In the future, Guangxi Zhuang Autonomous Region should coordinate the relationship between energy supply and emission reduction, and take specific measures for emission reduction according to local conditions by referring to the scenario model of peak carbon emissions, so as to achieve the goal of reaching the peak carbon emissions in 2030.
- Guangxi Zhuang Autonomous Region /
- carbon emissions at the county level /
- the temporal and spatial changes /
- STIRPAT

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图 1 研究区行政分布示意图

注：基于自然资源部标准地图服务网GS（2019）3333号标准底图制作，底图边界无修改。

Figure 1. Schematic diagram of the study area

Note: The above map is produced based on the standard base map (GS (2019) 3333) from the standard map service network of the Ministry of Natural Resources. The base map boundary is not modified.

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图 2 广西碳排放量趋势图

Figure 2. Carbon emission trend of Guangxi

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图 3 广西县级碳排放分布图

注：基于自然资源部标准地图服务网GS（2019）3333号标准底图制作，底图边界无修改。

Figure 3. Distribution of carbon emissions at the county level in Guangxi

Note: The above map is produced based on the standard base map (GS (2019) 3333) from the standard map service network of the Ministry of Natural Resources. The base map boundary is not modified.

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图 4 广西碳排放强度图

Figure 4. Carbon emission intensity of Guangxi

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图 5 广西碳排放压力指数图

Figure 5. Carbon emission pressure of Guangxi

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图 6 广西碳排放分类图

注：基于自然资源部标准地图服务网GS（2019）3333号标准底图制作，底图边界无修改

Figure 6. Classification of carbon emissions in Guangxi

Note: The above map is produced based on the standard base map (GS (2019) 3333) from the standard map service network of the Ministry of Natural Resources. The base map boundary is not modified.

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图 7 广西碳排放预测

注：黑色三角代表达峰时间

Figure 7. Prediction of carbon emissions in Guangxi

Note: Black triangle represents time to peak.

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图 8 广西不同地域类型碳排放预测

Figure 8. Prediction of carbon emissions in terms of different regional types in Guangxi

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表 1 广西碳排放岭回归方程

Table 1. Ridge regression equation of carbon emissions in Guangxi

类型	名称	岭回归方程	k值	R²
广西	广西	lnC=−10+1.93lnP+0.17nG−0.24lnD+0.9lnS	0.18	0.98
H-H-H	高总量−高强度−高压力	lnC=9.10+0.22lnP+0.19lnG−0.24lnD−0.66lnS	0.13	0.98
H-H-L	高总量−高强度−低压力	lnC=8.1+2.3lnP+0.0.33lnG+0.0002lnD+0.38lnS	0.08	0.97
H-L-H	高总量−低强度−高压力	lnC=2.04+0.41lnP+0.23lnG−0.25lnD+0.71lnS	0.20	0.95
H-L-L	高总量−低强度−低压力	lnC=−3.19+1.46lnP+0.3lnG−0.11lnD+0.31lnS	0.15	0.97
L-H-L	低总量−高强度−低压力	lnC=−23.97+4.21lnP−0.33lnG−0.34lnD+0.95lnS	0.16	0.91
L-L-L	低总量−低强度−低压力	lnC=−15.93+2.76lnP+0.12lnG−0.05lnD+0.63lnS	0.18	0.98
注：K为岭参数，K值的确定原则是各个自变量标准化回归系数趋于稳定时的最小K值，K值越小偏差越小；R²为方程显著性水平，越接近于1，拟合效果越好。 Note: K is ridge parameter and its determination principle of K value is the minimum K value when the standardized regression coefficient of each independent variable tends to be stable. The smaller the K value is, the smaller the deviation is. R² is the significance level of the equation, and the closer it is to 1, the better the fitting effect is.

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表 2 广西碳排放影响因素发展模式设定

Table 2. Model setting of developing influencing factors of carbon emissions in Guangxi

影响因素	设定模式	设定参数	备注
人口	高	2025年达峰，每年降0.1%	1) 《国家人口发展规划（2016—2030年）》以下简称《规划》中提到我国人口数量在2030年左右达到最大值。
	中	2030年达峰，每年降0.06%	2) 《纲要》中提到广西人口年平均增长率为0.83%，近五年持续降低。
	低	2035年达峰，每年降0.045%	3) 《规划》中提到未来三孩政策的实施有可能使增长速率提升。
人均GDP	高	年平均增长率6.5%	1) 《纲要》中提到2016—2020年人均GDP年平均增长率为5.2%
	中	年平均增长率5.5%	2) 《纲要》中提到未来五年人均GDP年平均增长率为5.5%。
	低	年平均增长率4.5%	3) 未来经济增长速度会逐渐放缓^[34]。
碳排放强度	高	年平均降低率2.5%	1) 自主行动目标提出到2030年碳排放强度要比2005年下降60−65%^[35]。
	中	年平均降低率3.5%	2) 基于论文3.1研究结果显示近五年碳排放强度年平均下降3.4%
	低	年平均降低率4.5%	3) 未来技术水平可能突破困难^[36]。
第二产业占比	高	年平均降低率0.65%	1) 2016—2020年《广西统计年鉴》中提到广西产业结构年平均下降率1.8%。
	中	年平均降低率0.55%	2) 《纲要》中提到未来广西省将大力发展旅游业、农业
	低	年平均降低率0.45%	3) 第二产业实体业也不可丢弃^[37]。

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表 3 广西碳排放情景

Table 3. Scenario model of carbon emissions in Guangxi

情景	人口 (P)	人均 GDP(G)	碳排放强度(D)	第二产业占比(S)
基准情景	中	中	中	中
节能情景	低	低	高	高
高经济发展情景	高	高	低	低
经济与减排同步发展情景a	高	高	高	高
经济与减排同步发展情景b	中	高	中	高
绿色发展情景	中	中	中	低
减排情景	中	中	高	中

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表 4 广西不同类型碳排放达峰时间

Table 4. peak time of different types of carbon emissions in Guangxi under seven scenarios

情景	广西全域	H-H-H型	H-H-L型	H-L-H型	H-L-L型	L-H-L	L-L-L型
基准情景	2032	持续增长	持续增长	持续增长	持续增长	持续下降	2030
节能情景	2023	持续增长	2030	2031	2029	持续下降	2023
高经济发展情景	持续增长	持续增长	持续增长	持续增长	持续增长	持续下降	持续增长
经济与减排同步发展情景a	2031	持续增长	持续增长	持续增长	持续增长	持续下降	2034
经济与减排同步发展情景b	2030	持续增长	持续增长	持续增长	持续增长	持续下降	2029
绿色发展情景	2029	持续增长	持续增长	持续增长	持续增长	持续下降	2029
减排情景	2030	持续增长	持续增长	持续增长	持续增长	持续下降	2030

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