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As the most basic unit of the national economy and administrative management, the low-carbon transformation of the vast counties is of great significance to China’s overall greenhouse gas emission reduction. Although the low-carbon evaluation (LCE) indicator system and benchmarks have been extensively studied, most benchmarks ignore the needs of the evaluated object at the development stage. When the local economy develops to a certain level, it may be restricted by static low-carbon target constraints. This study reviews the relevant research on LCE indicator system and benchmarks based on convergence. The Environmental Kuznets Curve (EKC), a dynamic benchmark system for per capita carbon emissions (PCCEs), is proposed for low-carbon counties. Taking Changxing County, Zhejiang Province, China as an example, a dynamic benchmark for PCCEs was established by benchmarking the Carbon Kuznets Curve (CKC) of best practices. Based on the principles of best practice, comparability, data completeness, and the CKC hypothesis acceptance, the best practice database is screened, and Singapore is selected as a potential benchmark. By constructing an econometric model to conduct an empirical study on Singapore’s CKC hypothesis, the regression results of the least squares method support the CKC hypothesis and its rationality as a benchmark. The result of the PCCE benchmarks of Changxing County show that when the per capita income of Changxing County in 2025, 2030, and 2035 reaches USD 19,172.92, USD 24,483.01, and USD 29,366.11, respectively, the corresponding benchmarks should be 14.95 tons CO2/person, 14.70 tons CO2/person, and 13.55 tons CO2/person. For every 1% increase in the county’s per capita income, the PCCE allowable room for growth is 17.6453%. The turning point is when the per capita gross domestic product (PCGDP) is USD 20,843.23 and the PCCE is 15.03 tons of CO2/person, which will occur between 2025 and 2030. Prior to this, the PCCE benchmark increases with the increase of PCGDP. After that, the PCCE benchmark decreases with the increase of PCGDP. The system is economically sensitive, adaptable to different development stages, and enriches the methodology of low-carbon indicator evaluation and benchmark setting at the county scale. It can provide scientific basis for Chinese county decision makers to formulate reasonable targets under the management idea driven by evaluation indicators and emission reduction targets and help counties explore the coordinated paths of economic development and emission reduction in different development stages. It has certain reference significance for other developing regions facing similar challenges of economic development and low-carbon transformation to Changxing County to formulate scientific and reasonable low-carbon emission reduction targets.
Lijie Gao; Xiaoqi Shang; Fengmei Yang; Longyu Shi. A Dynamic Benchmark System for Per Capita Carbon Emissions in Low-Carbon Counties of China. Energies 2021, 14, 599 .
AMA StyleLijie Gao, Xiaoqi Shang, Fengmei Yang, Longyu Shi. A Dynamic Benchmark System for Per Capita Carbon Emissions in Low-Carbon Counties of China. Energies. 2021; 14 (3):599.
Chicago/Turabian StyleLijie Gao; Xiaoqi Shang; Fengmei Yang; Longyu Shi. 2021. "A Dynamic Benchmark System for Per Capita Carbon Emissions in Low-Carbon Counties of China." Energies 14, no. 3: 599.
The regional allocation of carbon emission quotas is of great significance to realize the carbon emission target. Basing on the combination of the multi-index method and the improved equal-proportion distribution method, and fully considering the differences in economic factors, population factors, energy factors, technological factors among cities, China’s 2030 carbon intensity reduction target was allocated. The results indicate that: (1) Under the target constraint of 60% reduction in CO2 emissions per unit of Gross Domestic Product (GDP) (carbon intensity) in 2030 compared to 2005, the carbon intensity target reduction rate (CITRR) of 285 Chinese cities is between 17.65% and 141.14%, with an average reduction rate of 51.52%; (2) the CITRR of cities presents significant spatial positive correlation, and the Global Moran I correlation index is 0.38; and (3) the distribution trend of CITRR is the same as the general trend of economic development of China, showing a basic trend of gradual decline from south to north and from coastal to inland. The allocation method takes into account fairness and efficiency, and reflects the differences between cities, so that the allocation results are likely to be accepted by all parties. Meanwhile, this method breaks the limitation of the lack of city’s data and is likely to implement in actual operation. Cities should choose distinguished low-carbon economic development paths, in combination with their characteristics of economic and social development, and carry out inter-city cooperation to promote carbon emission reduction steadily.
Longyu Shi; Fengmei Yang; Lijie Gao. The Allocation of Carbon Intensity Reduction Target by 2030 among Cities in China. Energies 2020, 13, 6006 .
AMA StyleLongyu Shi, Fengmei Yang, Lijie Gao. The Allocation of Carbon Intensity Reduction Target by 2030 among Cities in China. Energies. 2020; 13 (22):6006.
Chicago/Turabian StyleLongyu Shi; Fengmei Yang; Lijie Gao. 2020. "The Allocation of Carbon Intensity Reduction Target by 2030 among Cities in China." Energies 13, no. 22: 6006.
Sustainable development (SD) has become a fundamental strategy to guide the world’s social and economic transformation. However, in the process of practice, there are still misinterpretations in regards to the theory of SD. Such misinterpretations are highlighted in the struggle between strong and weak sustainable development paths, and the confusion of the concept of intra-generational and inter-generational justice. In this paper, the literature survey method, induction method, and normative analysis were adopted to clarify the gradual evolution and improvement process of the concept and objective of SD, to strengthen the comprehensive understanding of the SD theory. Moreover, we also tried to bring in the situation and concepts of China. The results show that the theory of SD has gone through three periods: the embryonic period (before 1972), the molding period (1972–1987), and the developing period (1987–present). SD is gradually implemented into a global action from the initial fuzzy concept, including increasing practical wisdom. The goal of SD evolves from pursuing the single goal of sustainable use of natural resources to Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs). This paper argues that the theory of strong sustainability should be the accepted concept of SD. Culture, good governance, and life support systems are important factors in promoting SD.
Longyu Shi; Linwei Han; Fengmei Yang; Lijie Gao. The Evolution of Sustainable Development Theory: Types, Goals, and Research Prospects. Sustainability 2019, 11, 7158 .
AMA StyleLongyu Shi, Linwei Han, Fengmei Yang, Lijie Gao. The Evolution of Sustainable Development Theory: Types, Goals, and Research Prospects. Sustainability. 2019; 11 (24):7158.
Chicago/Turabian StyleLongyu Shi; Linwei Han; Fengmei Yang; Lijie Gao. 2019. "The Evolution of Sustainable Development Theory: Types, Goals, and Research Prospects." Sustainability 11, no. 24: 7158.