Data-Driven Analysis and Evaluation of Regional Resources and the Environmental Carrying Capacity

Aiyong Lin, Yujia Liu (), Shuling Zhou, Yajie Zhang, Cui Wang and Heping Ding
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Aiyong Lin: Business School, Suzhou University, Suzhou 234000, China
Yujia Liu: Business School, Suzhou University, Suzhou 234000, China
Shuling Zhou: Business School, Suzhou University, Suzhou 234000, China
Yajie Zhang: Business School, Suzhou University, Suzhou 234000, China
Cui Wang: Business School, Suzhou University, Suzhou 234000, China
Heping Ding: Business School, Suzhou University, Suzhou 234000, China

Sustainability, 2023, vol. 15, issue 10, 1-18

Abstract: The resources and environmental carrying capacity (RECC) of a region are considered the key and the foundation for achieving sustainable development and the benchmark of environmental protection and pollution control. However, to improve the regional RECC, we need to comprehensively consider the data information and correlation of the economy, society, resources, and the environment. Therefore, we propose a data-driven method for RECC measurement and evaluation of the regional RECC. Based on data collection and the application of the pressure-state-response (PSR) framework to reflect RECC, an evaluation index system for the regional RECC is constructed. The technique for order of preference by similarity to the ideal solution (TOPSIS) model with the entropy weight method is used to measure and evaluate the regional RECC. The obstacle degree model is adopted to select and identify the key factors affecting the regional RECC and to propose targeted policy suggestions for data application. The results indicate that the RECC level in three provinces and one city of the Yangtze River Delta region fluctuated slightly from 2010 to 2019, with an overall upward trend. Anhui Province has a relatively weak carrying capacity, and the main obstacles to RECC improvement in the region are the proportion of wetland area and the ownership of water resources. This study provides theoretical and methodological support for regional RECC research and management as well as a basis for formulating policies related to environmental protection and pollution control.

Keywords: data-driven; sustainability; resources and environmental carrying capacity; environmental pollution; entropy weight method; obstacle degree model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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