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Applied Modeling for Energy and Environmental Risks

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Hazards and Sustainability".

Deadline for manuscript submissions: closed (26 March 2023) | Viewed by 1785

Special Issue Editors


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Guest Editor
Mathematical Sciences and Southampton Statistical Sciences Research Institute, University of Southampton, Southampton SO17 1BJ, UK
Interests: nonlinear financial time series modeling and financial statistics/econometrics; statistical inference and computation for nonlinear modeling and prediction of spatial/temporal big data and intelligent modeling; applied temporal/spatial modeling for financial, environmental and socioeconomic risks; non-parametric/semi-parametric modeling and statistical learning; health statistical modeling and others (Bayesian, survival/missing data, logistic, mixture and robust modeling)

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Guest Editor
Institute of Management and Decision, Shanxi University, Taiyuan 030006, China
Interests: interval time series modeling and financial statistics; applied econometric modeling for financial, energy and socioeconomic risks; financial stability and financial risk contagion; prediction and decision evaluation for energy and environmental efficiency

Special Issue Information

Dear Colleagues,

Environmental risk assessment [1] is a process of assessing the likelihood of adverse effects from environmental stressors. With the development of modern industrialization and urbanization, the continuously increasing energy consumption has given rise to a series of problems and impact on our environment, e.g., various environmental pollutions. In particular, fossil fuels such as coal, oil, and natural gas do substantial harm [2], causing air, soil and water pollution and damage to public health, wildlife and habitat, as well as global warming emissions. Environmental problems associated with the use of energy span a wide range of pollutants, hazards and accidents, as well as degradation of environmental quality and natural ecosystems. Deciding how to model and quantify such risks is an important but yet difficult task.  

This Special Issue hence focuses on the innovation and application of mathematical, statistical and econometric models in the evaluation and analysis of energy and environmental risks. Various related risk issues, such as energy generation risk, consumption and poverty risk, financial and geopolitical risk in energy systems, natural, regional or industrial environmental risk and influencing factors and energy–environmental risk transmission mechanisms and policy on risk precaution are just some examples of the topics of interest in this Special Issue. Papers on risk estimation, analysis and evaluation, risk decision-making and risk precaution measures by applying quantitative models based on experimental data, historical data or survey data, relating to the above topics, are welcome. Innovative model design and application that deal with energy and environmental risks in a simultaneously relevant way are especially sought after.

Theoretical, methodological and empirical papers on the modeling of energy and environmental risks are considered. Review papers describing the potential risk and modeling method relating to the focus of this Special Issue, i.e., the existing risk categories, estimation methods and analysis models on energy and environmental risks, will be considered as well.

Reference:

  1. Risk assessment. Available online: https://en.wikipedia.org/wiki/Risk_assessment#Environment (accessed date: 25 January 2021)
  2. Fossil Fuels. Available online: https://www.ucsusa.org/energy/fossil-fuels (accessed date: 25 January 2021)

Prof. Dr. Zudi Lu
Prof. Dr. Wei Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • energy risks
  • environmental risks
  • energy-environmental policy
  • mathematical, statistical and econometric models
  • risk decision making and precaution
  • risk estimation and analysis
  • risk influencing factors
  • risk transmission mechanism

Published Papers (1 paper)

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Research

12 pages, 3836 KiB  
Article
Differentiation Rule and Driving Mechanisms of Collapse Disasters in Changbai County
by Lihui Qian and Shuying Zang
Sustainability 2022, 14(4), 2074; https://0-doi-org.brum.beds.ac.uk/10.3390/su14042074 - 11 Feb 2022
Cited by 6 | Viewed by 1185
Abstract
The differentiation rule and driving mechanisms of collapse disasters in various regions are unclear, and the results from existing methods of research are not sufficiently scientific. To reveal the nature of collapse disasters, this study utilized data from the 1:50,000 geological disaster investigation [...] Read more.
The differentiation rule and driving mechanisms of collapse disasters in various regions are unclear, and the results from existing methods of research are not sufficiently scientific. To reveal the nature of collapse disasters, this study utilized data from the 1:50,000 geological disaster investigation results database, 1:50,000 topographic data, and TM images. Topography, human activity intensity, rock mass structure, hydrological conditions, vegetation status, and meteorological conditions were used as indicators in the DEA model to analyze their validity and to explore the differentiation law and driving mechanisms of the highway slope along the YaLu river, a location of frequent geological disasters in Changbai County. In the analysis process, each index was quantitatively graded, i.e., the number of disaster points corresponding to each index was used as an input index, and the number of disaster points and the scale and stability of disaster points corresponding to the graded quantitative index were used as the output indexes. The results of the analysis of the study area indicate that there are significant differences in geological disasters due to different regional characteristics. We carried out three evaluations and performed spatial superposition analysis of the indicators corresponding to the effective values and the regional collapse points. The driving factors of collapse disasters can be divided into three categories, namely the impact of human activities, rainfall, and gravity stress. The GIS analysis and mapping found that the collapse points located to the south of the Grand Canyon of Changbai County were primarily affected by rainfall. Additionally, the areas affected by activity intensity are mostly concentrated in county towns with concentrated populations and road slopes. Full article
(This article belongs to the Special Issue Applied Modeling for Energy and Environmental Risks)
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