| 中国高耗能产品生产与区域PM2.5浓度的动态关联效应——基于省级尺度的分析 |
| |
| 引用本文： | 金凤君,林美含,张晓平,李润奎.中国高耗能产品生产与区域PM2.5浓度的动态关联效应——基于省级尺度的分析[J].地理研究,2021,40(8):2141-2155. |
| |
| 作者姓名： | 金凤君 林美含 张晓平 李润奎 |
| |
| 作者单位： | 1. 中国科学院地理科学与资源研究所,北京 1001012. 中国科学院区域可持续发展分析与模拟重点实验室,北京 1001013. 中国科学院大学资源与环境学院,北京 100049 |
| |
| 基金项目： | 国家自然科学基金项目(41771133);中国科学院战略性先导科技专项A类项目(XDA19040403) |
| |
| 摘 要： | 面向经济高质量发展及实现“双碳”战略目标,中国传统能源密集型产业发展的资源环境效应备受学界关注。基于2000—2017年中国31个省（直辖市、自治区）的面板数据,通过构建面板向量自回归模型（PVAR）,结合脉冲响应分析和方差分解及动态系统GMM模型,探究中国火电、水泥、钢铁、焦炭等典型高耗能产品的生产规模与区域PM2.5污染的动态关联效应。结果表明：① 短期内,省域PM2.5浓度具有明显的时间惯性,火电、水泥、钢铁、焦炭产业规模的短期波动对其冲击影响有限;② 动态影响显示,区域钢铁生产规模对PM2.5浓度的影响程度最大,火电、焦炭行业次之;③ 长期影响结果显示,钢铁、焦炭产业的扩张加剧了PM2.5污染,而火电、水泥产品生产规模未与PM2.5污染表现出同步特征;④ 区域PM2.5污染成因具有复合性,研究期内控制变量如地区经济规模、工业化程度、城镇化率的提高加剧了PM2.5污染,地方政府环境污染治理力度越弱则PM2.5污染程度越重。中国在高耗能产品生产规模逐年增加的情况下,有效地控制了区域PM2.5污染的加剧。未来应进一步提高行业标准,通过技术创新和产业结构升级控制污染物排放强度;增强地方政府对环境污染的治理力度;研究能源原材料产业的适度产能规模,在满足中国新型基础设施、新型城镇化等重大工程建设对基础原材料产业需求的同时,实现环境质量的优化。
|
| 关 键 词： | 能源密集型产业 PM2.5 PVAR模型 动态关联 |
| 收稿时间： | 2020-08-25 |
Dynamic correlation of energy-intensive industrial output and regional PM2.5 concentration in China from a provincial perspective |
| |
| JIN Fengjun,LIN Meihan,ZHANG Xiaoping,LI Runkui.Dynamic correlation of energy-intensive industrial output and regional PM2.5 concentration in China from a provincial perspective[J].Geographical Research,2021,40(8):2141-2155. |
| |
| Authors: | JIN Fengjun LIN Meihan ZHANG Xiaoping LI Runkui |
| |
| Institution: | 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China2. Key Laboratory of Regional Sustainable Development Modeling, CAS, Beijing 100101, China3. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China |
| |
| Abstract: | China is working towards a high-quality economic development pathway and has entered an important stage driven by industrial transformation and upgradation, so as to fulfil national commitments of “carbon peak” and “carbon neutral” in 2030 and 2060, respectively. How to achieve economic development and balance the relationship between regional economic development and its environmental impact has attracted much attention in academic circles, among which the impact of energy-intensive industries on air quality is of great importance. Based on the panel data of 31 provincial-level regions (including provinces, municipalities and autonomous regions) in China from 2000 to 2017, this study explored the dynamic correlation between regional PM2.5 pollution and production amount of energy-intensive industries (thermal power, cement, steel and coke), by building PVAR model and Dynamic System GMM model. The results show that: (1) In the short term, regional PM2.5 had obvious time inertia, and regional PM2.5 concentration was affected by the output amount of thermal power, cement, steel and coke industries at a limited level. (2) The result of dynamic impact showed that the contribution of steel production amount to PM2.5 was greater than that of thermal power and coke industries. (3) The result of long-term impact showed that the steel and coke industries have exacerbated the regional pollution of PM2.5, while the production output of thermal power and cement industries was not synchronized with the aggravation of PM2.5 pollution. (4) The concentration of PM2.5 was also affected by the control variables such as economic scale, industrialization level, urbanization level, and loose environmental regulation. Even though the production amount of energy-intensive industries has been increasing year by year in China, regional PM2.5 concentration has not worsened, indicating effective air quality control measures and industrial upgradation in China. This suggests that measures should further be taken to improve the industry standards, innovate technology, upgrade industrial structure and strengthen environmental regulation in order to control the pollutant emission intensity of raw material industries, the demand of which is still growing to meet the new infrastructure construction and new urbanization in China. |
| |
| Keywords: | energy-intensive industry PM2 5 PVAR model dynamic correlation |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《地理研究》浏览原始摘要信息 |
| 点击此处可从《地理研究》下载免费的PDF全文 |
|
