Fengmei Yang

Dr. Fengmei Yang

Institute of Urban Environment, Chinese Academy of Sciences

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 December 2019 in Sustainability
Verified
Journal Article
Open access
PDF file
LSLongyu Shi
Longyu Shi
LHLinwei Han
Linwei Han
FYFengmei Yang
Fengmei Yang
LGLijie Gao
Lijie Gao
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.

24 November 2022 in Sustainable Cities and Society
Verified
Journal Article
Closed access
FYFengmei Yang
Fengmei Yang
LSLongyu Shi
Longyu Shi
LGLijie Gao
Lijie Gao

8 May 2022 in Cell Reports
Verified
Journal Article
Open access
HZHuiwen Zheng
Huiwen Zheng
YCYanli Chen
Yanli Chen
JLJing Li
Jing Li
HLHeng Li
Heng Li
XZXin Zhao
Xin Zhao
LLLongding Liu
Longding Liu
The pathological and immune response of individuals with COVID-19 display different dynamics in lung and intestine. Here, we depict the single-cell transcriptional atlas of longitudinally collected lung and intestinal tissue samples from SARS-CoV-2-infected monkeys at 3 to 10 dpi. We find that intestinal enterocytes are degraded at 3 days post-infection but recovered rapidly, revealing that infection has mild effects on the intestine. Crucially, we observe suppression of the inflammatory response and tissue damage related to B-cell and Paneth cell accumulation in the intestines, although T cells are activated in the SARS-CoV-2 infection. Compared with that in the lung, the expression of interferon response-related genes is inhibited, and inflammatory factor secretion is reduced in the intestines. Our findings indicate an imbalance of immune dynamic in intestinal mucosa during SARS-CoV-2 infection, which may underlie ongoing rectal viral shedding and mild tissue damage.

7 September 2022 in Environmental Science and Pollution Research
Verified
Journal Article
Closed access
PDF file
FYFengmei Yang
Fengmei Yang
LSLongyu Shi
Longyu Shi
XWXiaotong Wang
Xiaotong Wang
LGLijie Gao
Lijie Gao

17 November 2020 in Energies
Verified
Journal Article
Open access
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LSLongyu Shi
Longyu Shi
FYFengmei Yang
Fengmei Yang
LGLijie Gao
Lijie Gao
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.

25 January 2021 in Energies
Verified
Journal Article
Open access
PDF file
LGLijie Gao
Lijie Gao
XSXiaoqi Shang
Xiaoqi Shang
FYFengmei Yang
Fengmei Yang
LSLongyu Shi
Longyu Shi
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.