粤港澳大湾区温室气体和大气污染物协同控制现状分析

刘海艳; 于会彬; 王志刚

doi:10.12153/j.issn.1674-991X.20220321

粤港澳大湾区温室气体和大气污染物协同控制现状分析

doi: 10.12153/j.issn.1674-991X.20220321

1.
中山大学环境科学与工程学院，广东省环境污染控制与修复技术重点实验室
2.
中国环境科学研究院

基金项目: 国家自然科学基金项目（22076224）

详细信息

作者简介:
刘海艳（1993—），女，硕士研究生，主要从事环境规划与管理研究，liuhy96@mail2.sysu.edu.cn

通讯作者:
王志刚（1972—），男，副教授，博士，主要从事环境规划、环境影响评价、环境政策研究，eeswzg@mail.sysu.edu.cn

中图分类号: X51
计量
- 文章访问数: 464
- HTML全文浏览量: 311
- PDF下载量: 93
- 被引次数: 0
出版历程
- 收稿日期: 2022-04-28

Analysis of the present situation of greenhouse gases and air pollutants co-control in Guangdong-Hong Kong-Macao Greater Bay Area

1.
School of Environmental Science and Engineering, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology
2.
Chinese Research Academy of Environmental Sciences

摘要

摘要:
区域联防联控能够实现温室气体和大气污染物协同减排，粤港澳大湾区已开展多项环境合作项目，具有较好的气候变化和大气污染协同控制基础，对区域层面温室气体和大气污染物协同控制现状进行研究，具有重要意义。以粤港澳大湾区11个市（区）2005—2020年的历史数据为基础，在全局熵值法的基础上选取4个一级指标（子系统）、20个二级指标构建了温室气体和大气污染物协同控制现状评价指标体系，并采用耦合协调度模型测算各指标之间的耦合度。结果表明：粤港澳大湾区温室气体和大气污染物协同控制综合评价得分总体呈上升趋势，其中生态环境水平指标得分相对滞后，影响了协同控制水平的提升；11个市（区）的协同控制水平得分均有不同程度的提高，但是一级指标间的得分差异较大；4个子系统之间的耦合度为高度耦合，耦合协调度均为较低协调水平，各子系统正处于协调发展阶段，相互之间的作用力还很小，上升发展空间较大。粤港澳三地不同的环境管理体系和环境治理诉求是制约粤港澳大湾区温室气体与大气污染物协同控制发展的主要原因。
- 温室气体 /
- 大气污染物 /
- 协同控制 /
- 全局熵值法 /
- 耦合协调度模型
Abstract:
Regional joint prevention and control can realize the coordinated emission reduction of greenhouse gases and air pollutants. Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has carried out a number of environmental cooperation projects, which has a good foundation for the co-control of climate change and air pollution. It is of great significance to study the current situation of the co-control of greenhouse gases and air pollutants at the regional level. Based on the historical data of 11 cities/regions in GBA from 2005 to 2020, a co-control evaluation index system of greenhouse gases and air pollutants was constructed by selecting 4 first-level indicators and 20 second-level indicators based on the global entropy method, and the coupling coordination degree model was used to measure the coupling degree of each indicator. The results showed that the comprehensive evaluation score of the co-control of greenhouse gases and air pollutants in GBA showed an upward trend, and the score of the eco-environmental level index lagged behind, which affected the improvement of the co-control level. The scores of co-control level of 11 cities/regions all had varying degrees of increase, but the score difference between the first-level indicators was larger. The coupling between the four subsystems was high coupling, and the coupling coordination degree was low coordination level. The subsystems were in the stage of coordinated development, and the interaction force between them was still small, so there was a large space for improvement. The different environmental management systems and environmental governance demands of the three areas were the main reasons that restricted the co-control development of greenhouse gases and air pollutants in GBA.
- greenhouse gases /
- air pollutants /
- co-control /
- global entropy method /
- coupled coordination degree model

HTML全文

图 1 粤港澳大湾区温室气体和大气污染物协同控制现状评价指标体系

注：+表示正向指标，−表示负向指标。

Figure 1. Co-control evaluation index system of greenhouse gases and air pollutants in GBA

下载: 全尺寸图片幻灯片

图 2 2005—2020年粤港澳大湾区协同控制水平综合评价得分情况

Figure 2. Comprehensive score of the co-control status in GBA from 2005 to 2020

下载: 全尺寸图片幻灯片

图 3 2005—2020年粤港澳大湾区协同控制水平一级指标得分

Figure 3. First-level indicator scores of the co-control status in GBA from 2005 to 2020

下载: 全尺寸图片幻灯片

图 4 2005—2020年粤港澳大湾区各区市协同控制一级指标年平均得分

Figure 4. First-level indicators average annual score of co-control status in various cities/regions in GBA from 2005 to 2020

下载: 全尺寸图片幻灯片

图 5 2005—2020年粤港澳大湾区协同控制评价体系耦合度和耦合协调度

Figure 5. Coupling degree and coupling coordination degree of the co-control evaluation index system in GBA from 2005 to 2020

下载: 全尺寸图片幻灯片

表 1 耦合度及耦合协调度等级划分

Table 1. Classification of coupling degree and coupling coordination degree

耦合度取值	耦合阶段	耦合协调度取值	耦合协调程度
[0，0.25]	低度耦合	[0，0.2）	极低协调水平
（0.25，0.5]	拮抗耦合	[0.2，0.4）	较低协调水平
（0.5，0.75]	磨合耦合	[0.4，0.6）	中等协调水平
（0.75，1.0]	高度耦合	[0.6，0.8）	较高协调水平
		[0.8，1.0]	高度协调水平

下载: 导出CSV

表 2 粤港澳大湾区协同控制现状评价体系指标测算结果

Table 2. Measurement results of the co-control evaluation index system in GBA

一级指标	一级指标权重	二级指标	信息熵（${\mathit{e} }_{\mathit{j} }）$	差异性系数$（{\mathit{d} }_{\mathit{j} }）$	二级指标权重
经济发展水平	0.237 8	GDP增长率	0.997 8	0.002 2	0.002 8
		人均GDP	0.900 9	0.099 1	0.124 7
		固定资产投资增长率	0.996 1	0.003 9	0.004 9
		外商投资企业进出口总额占比	0.982 4	0.017 6	0.022 1
		第二产业生产总值占比	0.933 8	0.066 2	0.083 3
社会发展水平	0.503 9	人口密度	0.855 8	0.144 2	0.181 5
		城镇人口占比	0.978 9	0.021 1	0.026 6
		人均机动车保有量	0.952 6	0.047 4	0.059 6
		城镇居民人均可支配收入	0.823 5	0.176 5	0.222 1
		居民消费价格总指数	0.988 8	0.011 2	0.014 1
生态环境水平	0.093 7	SO₂浓度	0.991 8	0.008 2	0.010 3
		PM₁₀浓度	0.979 0	0.021 0	0.026 4
		年平均气温	0.988 8	0.011 2	0.014 1
		年降水量	0.988 1	0.011 9	0.015 0
		建成区绿化覆盖率	0.977 8	0.022 2	0.027 9
可持续发展潜力	0.164 6	人均SO₂排放量	0.986 4	0.013 6	0.017 1
		人均CO₂排放量	0.992 4	0.007 6	0.009 6
		单位GDP能耗	0.974 0	0.026 0	0.032 7
		R&D经费支出占比	0.962 1	0.037 9	0.047 7
		森林覆盖率	0.954 3	0.045 7	0.057 5

下载: 导出CSV

表 3 粤港澳大湾区协同控制水平年均值与变化幅度

Table 3. Annual mean and variation range of the co-control status in GBA

市（区）	协同控制水平年均值	年均值排名	变化幅度/%	年均变化幅度排名
澳门	0.700 5	1	3.87	8
香港	0.493 9	2	2.44	10
深圳	0.349 1	3	4.24	7
广州	0.271 5	4	4.52	6
东莞	0.252 0	5	7.03	2
珠海	0.249 3	6	5.09	5
肇庆	0.227 6	7	2.39	11
中山	0.225 0	8	5.61	3
佛山	0.223 1	9	7.30	1
惠州	0.208 6	10	2.69	9
江门	0.201 6	11	5.39	4

下载: 导出CSV

参考文献(35)

[1]	WMO. WMO greenhouse gas bulletin: the state of greenhouse gases in the atmosphere based on global observations through 2020[R]. Geneva: WMO, 2021.
[2]	国家气象局. 中国气候公报(2020年)[A]. 北京: 中国气象局, 2021.
[3]	自然资源部海洋预警监测司. 2020年中国海平面公报[A]. 北京: 自然资源部海洋预警监测司, 2021.
[4]	IPCC. Climate change 2021: the physical science basis[A]. Cambridge: Cambridge University Press, 2021.
[5]	张型芳, 罗宏, 吕连宏.碳排放与经济增长的协调性分析[J]. 环境工程技术学报,2017,7(4):517-524. doi: 10.3969/j.issn.1674-991X.2017.04.071 ZHANG X F, LUO H, LÜ L H. Coordination analysis on carbon emission and economic growth[J]. Journal of Environmental Engineering Technology,2017,7(4):517-524. doi: 10.3969/j.issn.1674-991X.2017.04.071
[6]	张涵, 姜华, 高健, 等.PM_2.5与臭氧污染形成机制及协同防控思路[J]. 环境科学研究,2022,35(3):611-620. ZHANG H, JIANG H, GAO J, et al. Formation mechanism and management strategy of cooperative control of PM_2.5 and O₃[J]. Research of Environmental Sciences,2022,35(3):611-620.
[7]	翁佳烽, 梁晓媛, 邓开强, 等.不同季节肇庆市PM_2.5和O₃污染特征及潜在源区分析[J]. 环境科学研究,2021,34(6):1306-1317. WENG J F, LIANG X Y, DENG K Q, et al. Characteristics and potential sources of PM_2.5 and O₃ in different seasons in Zhaoqing City[J]. Research of Environmental Sciences,2021,34(6):1306-1317.
[8]	生态环境部. 2020年中国生态环境状况公报[A]. 北京: 生态环境部, 2021.
[9]	田丹宇, 常纪文.大气污染物与二氧化碳协同减排制度机制的建构[J]. 法学杂志,2021,42(4):101-107. doi: 10.16092/j.cnki.1001-618x.2021.04.010 TIAN D Y, CHANG J W. Construction on collaborative emission reduction of air pollutants and carbon dioxide[J]. Law Science Magazine,2021,42(4):101-107. doi: 10.16092/j.cnki.1001-618x.2021.04.010
[10]	KIM OANH N T, THUY PHUONG M T, PERMADI D A. Analysis of motorcycle fleet in Hanoi for estimation of air pollution emission and climate mitigation co-benefit of technology implementation[J]. Atmospheric Environment,2012,59:438-448. doi: 10.1016/j.atmosenv.2012.04.057
[11]	JIANG P, CHEN Y H, GENG Y, et al. Analysis of the co-benefits of climate change mitigation and air pollution reduction in China[J]. Journal of Cleaner Production,2013,58:130-137. doi: 10.1016/j.jclepro.2013.07.042
[12]	ZENG A, MAO X Q, HU T, et al. Regional co-control plan for local air pollutants and CO₂ reduction: method and practice[J]. Journal of Cleaner Production,2017,140:1226-1235. doi: 10.1016/j.jclepro.2016.10.037
[13]	CHEN Y L, SHIH Y H, TSENG C H, et al. Economic and health benefits of the co-reduction of air pollutants and greenhouse gases[J]. Mitigation and Adaptation Strategies for Global Change,2013,18(8):1125-1139. doi: 10.1007/s11027-012-9413-3
[14]	LU W F, TIAN Q, XU R J, et al. Ambient air pollution and hospitalization for chronic obstructive pulmonary disease: benefits from Three-Year Action Plan[J]. Ecotoxicology and Environmental Safety,2021,228:113034. doi: 10.1016/j.ecoenv.2021.113034
[15]	李丽平, 姜苹红, 李雨青, 等.湘潭市“十一五”总量减排措施对温室气体减排协同效应评价研究[J]. 环境与可持续发展,2012,37(1):36-40. doi: 10.3969/j.issn.1673-288X.2012.01.008 LI L P, JIANG P H, LI Y Q, et al. Study of co-benefits assessment of pollution reduction on greenhouse gas reduction in Xiangtan during 11th Five-Year Plan[J]. Environment and Sustainable Development,2012,37(1):36-40. doi: 10.3969/j.issn.1673-288X.2012.01.008
[16]	高庆先, 高文欧, 马占云, 等.大气污染物与温室气体减排协同效应评估方法及应用[J]. 气候变化研究进展,2021,17(3):268-278. GAO Q X, GAO W O, MA Z Y, et al. The synergy effect assessment method and its application for air pollutants and greenhouse gases reduction[J]. Climate Change Research,2021,17(3):268-278.
[17]	贾璐宇, 王艳华, 王克, 等.大气污染防治措施二氧化碳协同减排效果评估[J]. 环境保护科学,2020,46(6):19-26. doi: 10.16803/j.cnki.issn.1004-6216.2020.06.004 JIA L Y, WANG Y H, WANG K, et al. Evaluation of carbon dioxide coordination emission reduction based on National Air Pollution Control Plan[J]. Environmental Protection Science,2020,46(6):19-26. doi: 10.16803/j.cnki.issn.1004-6216.2020.06.004
[18]	LU Z Y, HUANG L, LIU J, et al. Carbon dioxide mitigation co-benefit analysis of energy-related measures in the Air Pollution Prevention and Control Action Plan in the Jing-Jin-Ji Region of China[J]. Resources, Conservation & Recycling:X,2019,1:100006.
[19]	邢有凯, 毛显强, 冯相昭, 等.城市蓝天保卫战行动协同控制局地大气污染物和温室气体效果评估: 以唐山市为例[J]. 中国环境管理,2020,12(4):20-28. XING Y K, MAO X Q, FENG X Z, et al. An effectiveness evaluation of co-controlling local air pollutants and GHGs by implementing blue sky defense action at city level: a case study of Tangshan City[J]. Chinese Journal of Environmental Management,2020,12(4):20-28.
[20]	NAM K M, WAUGH C J, PALTSEV S, et al. Climate co-benefits of tighter SO₂ and NO_x regulations in China[R]. Beijing: China Energy & Climate Project, 2012.
[21]	SHI X R, ZHENG Y X, LEI Y, et al. Air quality benefits of achieving carbon neutrality in China[J]. Science of the Total Environment,2021,795:148784. doi: 10.1016/j.scitotenv.2021.148784
[22]	MAO X Q, YANG S Q, LIU Q, et al. Achieving CO₂ emission reduction and the co-benefits of local air pollution abatement in the transportation sector of China[J]. Environmental Science & Policy,2012,21:1-13.
[23]	庞军, 石媛昌, 冯相昭, 等.实施低碳水泥标准的影响及协同减排效果分析[J]. 气候变化研究进展,2013,9(4):275-283. PANG J, SHI Y C, FENG X Z, et al. Analysis on impacts and co-abatement effects of implementing the low carbon cement standard[J]. Progressus Inquisitiones de Mutatione Climatis,2013,9(4):275-283.
[24]	WANG B, WANG Y F, ZHAO Y Q. Collaborative governance mechanism of climate change and air pollution: evidence from China[J]. Sustainability,2021,13(12):6785. doi: 10.3390/su13126785
[25]	ZHAO J J, CHEN S B, WANG H, et al. Quantifying the impacts of socio-economic factors on air quality in Chinese cities from 2000 to 2009[J]. Environmental Pollution,2012,167:148-154. doi: 10.1016/j.envpol.2012.04.007
[26]	HAO Y, LIU Y M. The influential factors of urban PM_2.5 concentrations in China: a spatial econometric analysis[J]. Journal of Cleaner Production,2016,112:1443-1453. doi: 10.1016/j.jclepro.2015.05.005
[27]	ZHANG Z Q, QU J S, ZENG J J. A quantitative comparison and analysis on the assessment indicators of greenhouse gases emission[J]. Journal of Geographical Sciences,2008,18(4):387-399. doi: 10.1007/s11442-008-0387-8
[28]	郭亚军. 综合评价理论、方法及应用[M]. 北京: 科学出版社, 2007.
[29]	SHANNON C E. A mathematical theory of communication[J]. Bell System Technical Journal,1948,27(3):379-423. doi: 10.1002/j.1538-7305.1948.tb01338.x
[30]	潘雄锋, 刘清, 彭晓雪.基于全局熵值法模型的我国区域创新能力动态评价与分析[J]. 运筹与管理,2015,24(4):155-162. doi: 10.3969/j.issn.1007-3221.2015.04.023 PAN X F, LIU Q, PENG X X. Evaluation and analysis of regional innovation ability in China based on overall entropy method[J]. Operations Research and Management Science,2015,24(4):155-162. doi: 10.3969/j.issn.1007-3221.2015.04.023
[31]	HE Y X, JIAO Z, YANG J. Comprehensive evaluation of global clean energy development index based on the improved entropy method[J]. Ecological Indicators,2018,88:305-321. doi: 10.1016/j.ecolind.2017.12.013
[32]	王淑佳, 孔伟, 任亮, 等.国内耦合协调度模型的误区及修正[J]. 自然资源学报,2021,36(3):793-810. doi: 10.31497/zrzyxb.20210319 WANG S J, KONG W, REN L, et al. Research on misuses and modification of coupling coordination degree model in China[J]. Journal of Natural Resources,2021,36(3):793-810. doi: 10.31497/zrzyxb.20210319
[33]	HE J Q, WANG S J, LIU Y Y, et al. Examining the relationship between urbanization and the eco-environment using a coupling analysis: case study of Shanghai, China[J]. Ecological Indicators,2017,77:185-193. doi: 10.1016/j.ecolind.2017.01.017
[34]	XING L, XUE M G, HU M S. Dynamic simulation and assessment of the coupling coordination degree of the economy-resource-environment system: case of Wuhan City in China[J]. Journal of Environmental Management,2019,230:474-487.
[35]	YANG C, ZENG W, YANG X. Coupling coordination evaluation and sustainable development pattern of geo-ecological environment and urbanization in Chongqing Municipality, China[J]. Sustainable Cities and Society,2020,61:102271. □ doi: 10.1016/j.scs.2020.102271