The impact of population factors and low-carbon innovation on carbon dioxide emissions: a Chinese city perspective
被引:13
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作者:
Li, Zhangwen
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机构:
South China Univ Technol, Sch Econ & Finance, Guangzhou 510006, Peoples R ChinaSouth China Univ Technol, Sch Econ & Finance, Guangzhou 510006, Peoples R China
Li, Zhangwen
[1
]
Zhou, Yu
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机构:
South China Univ Technol, Sch Econ & Finance, Guangzhou 510006, Peoples R ChinaSouth China Univ Technol, Sch Econ & Finance, Guangzhou 510006, Peoples R China
Zhou, Yu
[1
]
Zhang, Caijiang
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机构:
South China Univ Technol, Sch Econ & Finance, Guangzhou 510006, Peoples R ChinaSouth China Univ Technol, Sch Econ & Finance, Guangzhou 510006, Peoples R China
Zhang, Caijiang
[1
]
机构:
[1] South China Univ Technol, Sch Econ & Finance, Guangzhou 510006, Peoples R China
Population factors;
Low-carbon innovation;
Carbon dioxide emissions;
Pooled mean group;
ENERGY-CONSUMPTION;
ECONOMIC-GROWTH;
CO2;
EMISSIONS;
FINANCIAL DEVELOPMENT;
POLLUTANT EMISSIONS;
EMPIRICAL-EVIDENCE;
UNIT-ROOT;
TESTS;
GLOBALIZATION;
COINTEGRATION;
D O I:
10.1007/s11356-022-20671-7
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Carbon dioxide (CO2) emission reduction has become an important concern worldwide. During the past century, human activities have been a significant cause of the increase in the level of greenhouse gases. Past research mainly focuses on evaluating the nexus between unidimensional population factors and CO2 emissions, while few prior studies in a developing country have reported the impact of multidimensional demographic factors on CO2 emissions. As an initial attempt, this study investigates the short- and long-run associations between population factors, low-carbon innovation, and carbon dioxide emissions (CO2) for a panel consisting of 285 cities by employing the pooled mean group (PMG) estimator under the framework of the panel autoregressive distributed lag (ARDL) model. Our main findings are as follows: (1) Population size and population density could increase CO2 emissions, while population quality and low-carbon innovation were essential factors that alleviate carbon emission pressure in the long run. (2) Economic development, foreign direct investment, and industrial development were found to be factors causing the increase in carbon emissions. (3) The split-sample analysis demonstrated that the improvement of population quality still has a positive and significant long-run effect on environmental quality. Simultaneously, low-carbon innovation could realize the enormous dividends of carbon emission reduction in the long run, especially in existing relatively larger CO2 emission areas. Finally, the paper presents important policy implications.
机构:
Guangzhou Univ, Sch Management, Guangzhou, Peoples R ChinaGuangzhou Univ, Sch Management, Guangzhou, Peoples R China
Luo, Yonggen
Liu, Yue
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机构:
Guangdong Univ Finance & Econ, Sch Accounting, Guangzhou, Peoples R ChinaGuangzhou Univ, Sch Management, Guangzhou, Peoples R China
Liu, Yue
Wang, Deli
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机构:
Guangdong Univ Foreign Studies, Res Ctr Guangdong Hong Kong Macao Greater Bay Area, Guangzhou, Peoples R China
Guangdong Univ Foreign Studies, Sch Accounting, Guangzhou, Peoples R ChinaGuangzhou Univ, Sch Management, Guangzhou, Peoples R China
Wang, Deli
Han, Wenqi
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机构:
Univ Technol Sydney, UTS Business Sch, Ultimo, AustraliaGuangzhou Univ, Sch Management, Guangzhou, Peoples R China
机构:
Beijing Technol & Business Univ, Sch Econ, Beijing 100048, Peoples R ChinaBeijing Technol & Business Univ, Sch Econ, Beijing 100048, Peoples R China
Hou, Xiang
Hu, Qianlin
论文数: 0引用数: 0
h-index: 0
机构:
Beijing Technol & Business Univ, Sch Econ, Beijing 100048, Peoples R ChinaBeijing Technol & Business Univ, Sch Econ, Beijing 100048, Peoples R China
Hu, Qianlin
Liang, Xin
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机构:
Liaoning Univ, Sch Econ, Shenyang 110136, Liaoning, Peoples R ChinaBeijing Technol & Business Univ, Sch Econ, Beijing 100048, Peoples R China
Liang, Xin
Xu, Jingxuan
论文数: 0引用数: 0
h-index: 0
机构:
Beijing Technol & Business Univ, Sch Econ, Beijing 100048, Peoples R ChinaBeijing Technol & Business Univ, Sch Econ, Beijing 100048, Peoples R China
机构:
Chengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R ChinaChengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China
Pan, Ke
Liu, Bin
论文数: 0引用数: 0
h-index: 0
机构:
Chengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China
Chengdu Univ Technol, Coll Management Sci, Chengdu 610059, Peoples R ChinaChengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China
Liu, Bin
Luo, Jie
论文数: 0引用数: 0
h-index: 0
机构:
Chengdu Coll Arts & Sci, Chengdu 610401, Peoples R ChinaChengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China
Luo, Jie
Wang, Qinxiang
论文数: 0引用数: 0
h-index: 0
机构:
Chengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R ChinaChengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China
Wang, Qinxiang
Li, Jiajia
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机构:
Chengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R ChinaChengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China
Li, Jiajia
Tang, Long
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h-index: 0
机构:
Chengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R ChinaChengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China
Tang, Long
Xia, Xinyu
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机构:
Chengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R ChinaChengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China
Xia, Xinyu
Wei, Yang
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机构:
State Grid Sichuan Elect Power Res Inst, Chengdu 610095, Peoples R ChinaChengdu Univ Technol, Coll Math & Phys, Chengdu 610059, Peoples R China