粤港澳大湾区碳排放影响因素分析与情景预测

doi:10.13776/j.cnki.resourcesindustries.20250217.002

摘要/Abstract

摘要： 科学识别碳排放增长的影响因素，准确预测碳排放峰值及碳达峰时间，对中国如期实现“双碳”目标具有重要意义。选取粤港澳大湾区，基于2010—2022年NPP-VIIRS夜间灯光数据，首先，估算出粤港澳大湾区11个城市的碳排放量，并采用莫兰指数测算各城市之间碳排放量的时空异质性特征；其次，基于区域特色构建了扩展的STIRPAT模型，深入分析碳排放及其影响因素；最后，设定3种情景预测2022—2050年碳排放情况。研究结果显示：1）粤港澳大湾区整体碳排放呈现波动上升趋势，广州、深圳等城市呈现低碳排放趋势，惠州、江门等城市则呈现快速增长趋势，反映出不同的工业发展模式和碳排放控制效果；2）碳排放呈现显著的空间集聚特征，广州始终保持高集聚状态，澳门则维持低集聚水平，惠州的碳排放从不显著转变为高集聚；3）人口规模、城市化和研发投入为该区域碳排放正向影响因素，人均GDP、产业结构以及对外开放水平为负向影响因素，发展地区与高发达地区的碳排放关系复杂，人均GDP与产业结构对碳排放有不同影响；4）在基准情景和快速增长情景下，碳排放并不能得到有效控制，而在碳达峰情景下，碳排放才能得到有效控制。基于此，提出以下政策建议：促进产业转型，支持惠州、江门等地向低碳高效产业转型；推动区域合作与知识共享，建立碳排放合作机制，强化城市间低碳发展经验交流；加强研发投入支持，通过财政补贴、税收优惠等政策激励企业加大清洁能源和绿色技术研发，提升协同创新效率；制定适应性低碳战略，根据不同发展情景，制定差异化政策，协调人口、经济、产业结构及研发投入，确保经济增长与碳减排协同推进。

关键词: 粤港澳大湾区, 碳排放, 莫兰指数, STIRPAT, 情景预测

Abstract: It is of significance for realizing the target of China's “Dual Carbon” to reveal the carbon emission factors and to precisely forecast carbon emission peak value and time. This paper selects 2010 to 2022 NPP-VIIRS night lighting data in Guangdong-Hongkong-Macao Bay area (GHMB) to estimate their carbon emission of 11 cities, and uses Moran index to measure their temporal-spatial heterogeneities, and constructs a expanded STIRPAT model to study their carbon emission factors, and forecasts the 2022 to 2050 carbon emissions under 3 scenarios. GHMB generally shows a fluctuated rising trend in its carbon emission, but a declining in Guangzhou and Shenzhen, a fast growing trend in Huizhou and Jiangmen cities, suggesting different industrial developing modes and carbon emission controls. Carbon emission shows an obvious spatial concentrating, high in Guangzhou, low in Macao, from not outstanding to high in Huizhou. Population, urbanization and research & development investment are positive factors carbon emission, while GDP per capita, industrial structure and openness are negative ones. Carbon emission in developing and developed areas varies with GDP per capita and industrial structures. Carbon emission can not be effectively controlled under benchmark or fast growing scenarios, but effectively under carbon peaking scenario. This paper presents suggestions on switching to low-carbon industrial transformation in Huizhou and Jiangmen, on establishing carbon emission cooperation, on boosting research & development investments in clean energy and green technologies, making adaptive low carbon strategy and differentiated policies in coordinating population, economy and industrial structures so as to keep economic growth same pace with carbon emission reduction.

Key words: Guangdong-Hongkong-Macao Bay Area, carbon emission, Moran index, STIRPAT, scenario forecast

中图分类号:

X321

姚小剑, 吴毓源. 粤港澳大湾区碳排放影响因素分析与情景预测[J]. 资源与产业, 2025, 27(3): 44-53.

YAO Xiaojian, WU Yuyuan. CARBON EMISSION FACTORS AND SCENARIO FORECASTS OF GUANGDONG-HONGKONG-MACAO BAY AREA[J]. Resources & Industries, 2025, 27(3): 44-53.

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