Mingjie Li

Prof. Mingjie Li

Guangzhou Huashang College, Guangzhou, Guangdong, China
orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

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

Representative Publications

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22 March 2022 in Sustainability
Verified
Journal Article
Open access
PDF file
YZYulin Zhu
Yulin Zhu
MLMingjie Li
Mingjie Li
SLShiwei Lu
Shiwei Lu
HWHuimin Wang
Huimin Wang
JWJinjin Wang
Jinjin Wang
WWWei Wang
Wei Wang
Based on the Wassily W. Leontief input–output model, this paper constructs an emergy input–output model of an agricultural eco-economic system based on emergy theory. This model overcomes three limitations of the traditional input–output model. First, the conversion rate of ecological energy is used to solve the problem posed by the fact that the material input–output table cannot be directly combined due to the different measurement units of different substances. Second, it transforms the research object from a pure economic system to an eco-economic system by adding resources and environmental factors. Third, this paper solves the problem posed by the fact that the value input–output model is greatly affected by inflation, and uses the model to analyze the input–output of Zoumajie town in Shuangfeng City, Hunan Province, China, by unifying dimension (solar energy value).

3 November 2022 in PLOS ONE
Verified
Journal Article
Open access
PDF file
YDYu-Xia Du
Yu-Xia Du
MLMingjie Li
Mingjie Li
JHJun-Jie Huang
Jun-Jie Huang
This study uses an input-output model to analyze the wastewater, waste gas, and solid waste emissions in Guangdong’s industrial exports from 2004 to 2015; the Logarithmic Mean Divisia Index (LMDI) is used to analyze the factors influencing such pollution. The results reveal that embodied emissions of waste gas and solid waste in Guangdong’s export trade are increasing, while the increase in wastewater emissions is not apparent. The Logarithmic Mean Divisia Index (LMDI) is used to analyze the influencing factors of pollution, specifically, the structural, scale, and technical effects. We discovered that emissions of the top five industries account for about 80% of total emissions and the wastewater emissions’ technical effect has more impact; however, it is difficult for this technical effect in terms of embodied waste gas and solid waste to offset the scale and structural effects’ impacts. Moreover, the trends and factors influencing various industries’ pollution emissions differ. This study proposes that when the government carries out environmental pollution control measures, they should consider the embodied pollution caused by products from foreign trade and focus on treating industries with severe pollution. Simultaneously, the pollution controlling measures of different industries should also vary.