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Academic Journal of Humanities & Social Sciences, 2020, 3(6); doi: 10.25236/AJHSS.2020.030607.

Discussion on Environmental Displaced Persons

Author(s)

Junjie Zhao

Corresponding Author:
Junjie Zhao
Affiliation(s)

Institute of computer and control engineering, North China Electric Power University, Baoding 071000, China
[email protected]

Abstract

Due to the rising sea level caused by climate change, many island countries are in danger of disappearing because of the low altitude. The disappearance of the island countries will cause many people to become environmental displaced persons (EDP). Be homeless, life-threatening, and their precious culture will also face the risk of loss due to the migration of the people. To better solve and analyze the problem of climate refugees, this paper discuss it in several aspects. Firstly, build a three-dimensional roof model to simulate the shape of the island and predict the high degree of sea-level rise and the number of population by the end of 2020 of these island countries facing the risk of climate refugees through the grey prediction model. According to the model, calculate the area of island countries to be covered by rising sea level, so the number of EDPs caused by rising sea level in the world will be about 84951 by the end of 2020. Secondly, to analyze the risk of cultural loss quantitatively, this paper set up a model of the loss of cultural index (LCI). Eight main factors closely related to culture are selected to measure; besides, this paper set up life quality indicators (LQI), and use analytic hierarchy process (AHP) to determine the weight of each factor in these two indicators. Also, this paper selected eight indicators closely related to the basic strength of the country from three aspects and obtained the receiving nations indicators (RNI) of refugee receiving countries by using the entropy weight method and variation coefficient method. Finally, after obtaining the weights of each indicator, this paper obtained the comprehensive evaluation indicators (CEI) by using the weighted average algorithm (WAA). Then take Tuvalu as an example to calculate CEI and test the model. This paper use a fuzzy cluster analysis to divide the refugee receiving countries into four categories: very suitable, suitable, general and not suitable for immigration. The results of fuzzy cluster analysis also verify the correctness and rationality of our above evaluation indexes: LCI, LQI, RNI. Fourthly, use the CNP scoring model to quantitatively analyze whether different refugee receiving countries focus on human rights protection or cultural protection. When the CNP score is lower than 2.95, the policy formulation of the refugee receiving country should pay more attention to the human rights protection of EDP, when the score is higher than 3.31, it should pay more attention to cultural protection, and when the score is between 2.95-3.31, it should pay equal attention to both aspects. Finally, devise a set of policies based on the analysis of the results from our model. This paper emphasize that it is up to international organizations such as the United Nations to adjust the arrangement and guidance of EDPs to each country through CEI, CNP scoring model, and the will and tendency between the refugee country and the receiving country. In the end, do a sensitivity analysis of the Model and discuss strengths and weaknesses.

Keywords

EDPs, Culture Preservation, Grey Prediction, Analytic Hierarchy Process

Cite This Paper

Junjie Zhao. Discussion on Environmental Displaced Persons. Academic Journal of Humanities & Social Sciences (2020) Vol. 3, Issue 6: 61-80. https://doi.org/10.25236/AJHSS.2020.030607.

References

[1] https://www.climate.gov/news-features/understanding-climate/ climate-change-global-sea-level.
[2] https://research.csiro.au/slrwavescoast/sea-level/ sea-level-changes/.
[3] ZHAO Wen-yuan. Climate change and the statehood of small island state. Master’s thesis, Fudan University, 2014.
[4] MAO Ying-jie. Public international law issues of climate refugees and solutions to them. East China University of Political Science and Law, 2013.
[5] https://tidesandcurrents.noaa.gov/sltrends/sltrends.html.
[6] ZHANG Qi-min. Grey forecasting model. Journal of Ningxia University (Natural Science Edition), 2002.
[7] https://baike.sogou.com/m/v10401.htm?rcer=hIn1TbNcpMY0E2lJs.
[8] https://data.worldbank.org.cn/.
[9] REN Ye and XIAO Sa. Discussion on comprehensive evaluation methods of logistics system. Logistics Sci-Tech, 2011.
[10] DONG Yan-ping. Research on location selection of logistics distribution center based on fuzzy analytic hierarchy process. Pioneering with Science and Technology Monthly, 2010.
[11] MENG Wei and ZHAO Mao-tao. Project location evaluation based on analytic hierarchy process and multi-factor weighted average method. Techniques and Methods, 2018.
[12] LI Chen, YIN Zi-li, WANG Xiao-hui, ZHANG Gong-lin, LIN Yu-feng, and WANG Qing-liang. Assessment on distribution network dispatching based on analytic hierarchy processand entropy weight method. Proceedings of theCSU-EPSA, 2019.
[13] YAN Jia-lun, LIN Jun-guang, LOU Ke-wei, ZHANG Xi, and SHENG De-ren. Evaluation system for building integrated energy system based on ahp-cv method. Thermal Power Generation, 2019.
[14] https://blog.csdn.net/qq_29831163/article/details/89893908.
[15] https://blog.csdn.net/qq_43585318/article/details/104106752.
[16] WU Juan-mei. The legal status and protection of climate refugees from the perspective of international law. Journal of WetFang Engineering Vocational College, 2016.
[17] YANG Xin-xing. Atmospheric greenhouse effect is a pseudo proposition. Frontier Science, 2017.