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A non-parametric cause-effect testing for environmental variables — method and application
Traditional similarity or resemblance indexes are insufficient to directly reveal the cause-effect relations between environmental variables. Even the typical regression methods are not persuasive enough, since they rely on the assumptions about the data distribution and thus they are not really sui...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9244047/ https://www.ncbi.nlm.nih.gov/pubmed/35759102 http://dx.doi.org/10.1007/s11356-022-21423-3 |
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author | Chen, Ray-Ming |
author_facet | Chen, Ray-Ming |
author_sort | Chen, Ray-Ming |
collection | PubMed |
description | Traditional similarity or resemblance indexes are insufficient to directly reveal the cause-effect relations between environmental variables. Even the typical regression methods are not persuasive enough, since they rely on the assumptions about the data distribution and thus they are not really suitable for small amount of data. In this research, we devise a method to measure the strength of cause and effect (SCE), which is then turned into a non-parametric statistic. By analysing the empirical environmental data from the European Union, we calculate the SCE of these related variables. In addition, by constructing the ranking space and calculating the statistic distribution, we further specify the critical levels and values to conduct the cause-effect testing of these variables. The results show some sectoral activities do, to some degree, directly affect the quality of water and air. Moreover, there is a very clear-cut cause-effect relation between water quality and biodiversity. These results shall provide the policy makers with some ideas regarding the relations between environmental variables. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-022-21423-3. |
format | Online Article Text |
id | pubmed-9244047 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-92440472022-06-30 A non-parametric cause-effect testing for environmental variables — method and application Chen, Ray-Ming Environ Sci Pollut Res Int Research Article Traditional similarity or resemblance indexes are insufficient to directly reveal the cause-effect relations between environmental variables. Even the typical regression methods are not persuasive enough, since they rely on the assumptions about the data distribution and thus they are not really suitable for small amount of data. In this research, we devise a method to measure the strength of cause and effect (SCE), which is then turned into a non-parametric statistic. By analysing the empirical environmental data from the European Union, we calculate the SCE of these related variables. In addition, by constructing the ranking space and calculating the statistic distribution, we further specify the critical levels and values to conduct the cause-effect testing of these variables. The results show some sectoral activities do, to some degree, directly affect the quality of water and air. Moreover, there is a very clear-cut cause-effect relation between water quality and biodiversity. These results shall provide the policy makers with some ideas regarding the relations between environmental variables. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-022-21423-3. Springer Berlin Heidelberg 2022-06-27 2022 /pmc/articles/PMC9244047/ /pubmed/35759102 http://dx.doi.org/10.1007/s11356-022-21423-3 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Research Article Chen, Ray-Ming A non-parametric cause-effect testing for environmental variables — method and application |
title | A non-parametric cause-effect testing for environmental variables — method and application |
title_full | A non-parametric cause-effect testing for environmental variables — method and application |
title_fullStr | A non-parametric cause-effect testing for environmental variables — method and application |
title_full_unstemmed | A non-parametric cause-effect testing for environmental variables — method and application |
title_short | A non-parametric cause-effect testing for environmental variables — method and application |
title_sort | non-parametric cause-effect testing for environmental variables — method and application |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9244047/ https://www.ncbi.nlm.nih.gov/pubmed/35759102 http://dx.doi.org/10.1007/s11356-022-21423-3 |
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