Study on environmental pollution loss measurement model of energy consumption emits and its application in industrial parks

Han, Xiuyan; Sun, Tao; Feng, Qing

doi:10.1016/j.scitotenv.2019.03.002

Cited by 32 publications

(21 citation statements)

References 11 publications

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“…For the first part of the B problem, we investigated the history, environment, industry, humanities and other factors among the states, and collected 50 years of energy exports such as four states in the data source [8], for all types of non-renewable energy consumption, various types of typical clean energy consumption, various types of non-clean energy consumption, such as more than 30 kinds of data types were analyzed by multiple regression analysis, the results of the analysis found four states of the economy and all kinds of energy distribution and consumption relationship. According to the relevant data, we think that CA has the best prospect of developing clean energy.…”

Section: Model Building and Solving Partmentioning

confidence: 99%

Modeling and Prediction of New Energy Use

Yang¹

2019

JENR

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This paper looks into clean energy consumption in the four states of California (CA), Arizona (AZ), New Mexico (NM) and Texas (TX) by analyzing and comparing the methods of energy consumption, the similarity and difference of their energy composition and the causes for it, and finding out the state with the optimal ways of energy consumption, and based on it, predicts the future energy composition of these states and proposes a target for interstate energy convention. And through multiple regression analysis, and the corresponding indicators of the methods of energy consumption in these states, we compare the ways of new energy consumption in these states, and analyze the difference from the perspective of industries and geographies in these states, which prepares necessary reference for the following modeling. After some basic analysis of the data, we establish a multi-attribute decision making to find a state with optimal composition of energies through the five indicators of energy composition, volume of clean energy consumption etc; and based on the analysis, we find the different characteristics of energy consumption in these states. Then we set up a GM (1, 1) model to make prediction based on the data of energy consumption of the near 20 years and project energy consumption of the four states in 2025 and 2050. By means of multi-attribute decision making, we find out the state with optimal energy composition, and propose a target of the energy convention based on a two-year clean energy consumption in this state. After analyzing the difference of energy consumption methods in these four states, and in order to coordinate and integrate energy production and consumption in these states, we propose the 6 suggestions for action. In addition to the multiple regression analysis, multi-attribute decision making for the analysis of the energy consumption in these four states, principal component analysis also plays an important role. This method helps to find the significance of different ways of energy consumption, figure out the current and future energy consumption in these four states, and the state with optimal energy consumption method. Finally, by means of comparing with different models, we have nearly the same conclusion: CA is a state with optimal energy combination and has best practice for future development. There in projecting the 2025 and 2050 energy consumption, we can use CA as a reference state and set such as the target for energy convention between these four states.

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Section: Model Building and Solving Partmentioning

confidence: 99%

Modeling and Prediction of New Energy Use

Yang¹

2019

JENR

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“…The development of China's industrial parks not only promotes the rapid economic growth, but also produces environmental pollution to a certain extent. The evaluation of ecological compensation effect of environmental pollution loss has been raised, and gradually becomes a major problem that needs to be solved (Han et al, 2019). For a long time, the problem of ecological compensation for environmental pollution loss in China's industrial parks has not been paid enough attention to, so the environmental pollution level of industrial parks has been kept at a high level.…”

Section: Introductionmentioning

confidence: 99%

“…There are still many studies in China that focus on environmental pollution and ecological compensation in urbanization. (Han et al, 2018(Han et al, , 2019Liu et al, 2020); Some researchers used niche models to evaluate urban forest landscape quality (Han et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Study on the Evaluation of Ecological Compensation Effect for Environmental Pollution Loss from Energy Consumption: Taking Nanjing MV Industrial Park as an Example

Han¹,

Cao²

2021

Preprint

Self Cite

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In order to explore the effective method of the ecological compensation effect evaluation (ECEE) of the environmental pollution loss (EPS) in the industrial parks, based on the literature review and the current situation analysis, this paper selected four kinds of 26 evaluation indicators to build the evaluation indicators system. The spatial niche suitability model (SNSM) is reconstructed after analysis and improvement. Then, taking Nanjing MV Industrial Park as an example, SNSM and related research data were used to perform an application test of ecological compensation effect evaluation. The evaluation results showed that although the ecological compensation effect of the Nanjing MV industrial park's environmental pollution loss showed an upward trend in 2011–2018, the upward situation showed an imbalance. The effect of ecological environment compensation input status and ecological environment pollution status is significantly lagging behind. They are still the focus of future work of Nanjing MV Industrial Park. The research proved that the niche suitability model's evaluation results conform to Nanjing MV Industrial Park's actual situation. This paper's research results provide an effective quantitative analysis method for the management of ecological compensation effects in industrial parks and the improvement of ecological compensation effects.

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“…Therefore, to better develop and survive, SMEs usually put profits first and ignore environmental protection. However, with the rapid development of world economy, environmental pollution becomes more and more serious, so the protection of environment has become very urgent (Song et al, 2017a;Han et al, 2019). People pay more attention to the living environment problems closely related to their health and have a strong willingness to change the harsh environment.…”

Section: Introductionmentioning

confidence: 99%

Analysis of two financing modes in green supply chains when considering the role of data collection

Zhao

Qiang

2020

IMDS

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PurposeMore and more attention has been paid to the financing of small- and medium-sized enterprises (SMEs) and environmental protection. Many literatures have done detailed research on them; yet, few of them studied the interaction between corporate financing behaviors and environmental concerns. This study aims to incorporate the impact of the role of data collection into the mathematical model to explore the optimal financial and ordering strategies when considering environmental protection.Design/methodology/approachA Stackelberg game modeling and backward induction methods are used to derive the optimal equilibrium solutions, using numerical experiments to further explore the influences of various financing strategies on the green degree of product and ordering policies.FindingsNo matter which financing modes the capital-constrained retailer chooses, both the loan interest rate and order quantity considering environmental protection are larger than that without environmental protection concerns. As the retailer's initial capital increases, the optimal loan interest rates under various financing modes are all decreasing. The application of big data technology would promote the environmental protection of enterprises and increase the accuracy of financing decisions.Originality/valueThis paper studies financing activities of a supply chain considering data collection and environmental protection behaviors, which provides meaningful guidance for the financing and environmental decision-making of enterprises.

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Study on environmental pollution loss measurement model of energy consumption emits and its application in industrial parks

Cited by 32 publications

References 11 publications

Modeling and Prediction of New Energy Use

Modeling and Prediction of New Energy Use

Study on the Evaluation of Ecological Compensation Effect for Environmental Pollution Loss from Energy Consumption: Taking Nanjing MV Industrial Park as an Example

Analysis of two financing modes in green supply chains when considering the role of data collection

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