Research on Evaluation and Early-warning of Regional Ecological Security Based on NC-AHP
- DOI
- 10.2991/icseee-16.2016.152How to use a DOI?
- Keywords
- normal cloud, regional ecological security, early-warning model, the efficient ecological economic zone of the Yellow River Delta
- Abstract
In view of the problems of the randomness and fuzziness that in the process of the evolution of ecological security, in this paper, proposed a comprehensive analysis model based on NC (normal cloud) –AHP. The regional ecological security index system was constructed based on the ecosystem state, ecosystem danger and ecosystem immunity. The model was employed to quantitatively assess and dynamically early-warning the ecological security of the efficient ecological economic zone of the Yellow River Delta during the historical years (2003~2013) and the year of planning (2016). The results show that: the ecological security status from "danger" state to "sensitive" state to "good" state from 2003~2013, which demonstrate that the overall status of ecological security is undergoing increasing improvement, but all safety states are less than the general requirement of "safe" state. In 2016, the regional ecological security will be "good" state and has the tendency of developing to "sensitive" state. Atmospheric pollution, water resources shortage, energy consumption and industrial "three wastes" are the mainly short board factors of ecological environment in the efficient ecological economic zone of the Yellow River Delta.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Huizhong Dong AU - Peng Wu AU - Zongjie Wu AU - Bing Jiang AU - Tongwei Xing PY - 2016/12 DA - 2016/12 TI - Research on Evaluation and Early-warning of Regional Ecological Security Based on NC-AHP BT - Proceedings of the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016) PB - Atlantis Press SP - 848 EP - 856 SN - 2352-5401 UR - https://doi.org/10.2991/icseee-16.2016.152 DO - 10.2991/icseee-16.2016.152 ID - Dong2016/12 ER -