Journal
JOURNAL OF CLEANER PRODUCTION
Volume 252, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.119655
Keywords
Carrying capacity; Marine resources and environment; DPPD model; Comprehensive evaluation; DPSIR framework; Coastal regions in China
Categories
Funding
- Major Program of National Social Science Foundation of China [18ZDA055]
- Key Program of National Social Science Fund of China [16AJL007]
- National Natural Science Foundation of China (NSFC) [71874167, 71462022]
- Special Funds of Taishan Scholars Project of Shandong Province [tsqn20171205]
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The evaluation index system of Marine Resources and Environment Carrying Capacity (MRECC) is incomplete and the relationships among indexes are generally neglected, resulting in the unreasonable evaluation results of existing studies. In order to solve this problem, a model named DPPD is established to evaluate the MRECC by innovatively integrating four methods, i.e., DPSIR (Driver-Pressure-State-Impact-Response), PCA (Principal Component Analysis), PA (Path Analysis), and DEMATEL (Decision Making Trial and Evaluation Laboratory). The DPSIR framework is not only employed to identify 26 indexes of MRECC on 5 factors but also provide a possible influence mechanism of factors. The PCA and PA methods are both used to test possible relationships between each pair of factors and determine the effective influence mechanism, based on which the DEMATEL is used to objectively determine the weights of factors for MRECC. The comprehensive evaluation value and contribution rate are defined to reflect the overall performance of MRECC. Finally, the DPPD model is applied on 11 coastal regions of China and some general results are obtained. The weights of factors for MRECC are 0.098 (Driver), 0.176 (Pressure), 0.200 (State), 0.178 (Impact) and 0.348 (Response). The coastal regions of China have exhibited very slight downward trends on the MRECC in recent years but are still unhealthy. In 11 coastal regions of China, 7 are driven by double factors and 4 are driven by multiple factors. (C) 2019 Elsevier Ltd. All rights reserved.
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