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Traits and causes of environmental loss-related chemical accidents in China based on co-word analysis
Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
Stockholm University, Faculty of Social Sciences, Stockholm Business School. Wuhan University of Technology, China.
Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Science and Technology of China, China.
Number of Authors: 42018 (English)In: Environmental science and pollution research international, ISSN 0944-1344, E-ISSN 1614-7499, Vol. 25, no 18, p. 18189-18199Article in journal (Refereed) Published
Abstract [en]

Chemical accidents are major causes of environmental losses and have been debated due to the potential threat to human beings and environment. Compared with the single statistical analysis, co-word analysis of chemical accidents illustrates significant traits at various levels and presents data into a visual network. This study utilizes a co-word analysis of the keywords extracted from the Web crawling texts of environmental loss-related chemical accidents and uses the Pearson's correlation coefficient to examine the internal attributes. To visualize the keywords of the accidents, this study carries out a multidimensional scaling analysis applying PROXSCAL and centrality identification. The research results show that an enormous environmental cost is exacted, especially given the expected environmental loss-related chemical accidents with geographical features. Meanwhile, each event often brings more than one environmental impact. Large number of chemical substances are released in the form of solid, liquid, and gas, leading to serious results. Eight clusters that represent the traits of these accidents are formed, including leakage, poisoning, explosion, pipeline crack, river pollution, dust pollution, emission, and industrial effluent. Explosion and gas possess a strong correlation with poisoning, located at the center of visualization map.

Place, publisher, year, edition, pages
2018. Vol. 25, no 18, p. 18189-18199
Keywords [en]
Environmental losses, Chemical accident, Pollution, Co-word analysis, Clustering, Multidimensional scaling
National Category
Earth and Related Environmental Sciences Economics and Business
Identifiers
URN: urn:nbn:se:su:diva-158285DOI: 10.1007/s11356-018-1995-1ISI: 000436879200086PubMedID: 29696537OAI: oai:DiVA.org:su-158285DiVA, id: diva2:1236234
Available from: 2018-08-01 Created: 2018-08-01 Last updated: 2018-08-01Bibliographically approved

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