Journal of Natural Environment

Environmental impacts assessment of compost plants using a Bayesian approach: case study Golestan province

Document Type : Research Paper

Authors

1 MSc. graduated in Environment-Evaluation and Land Planning, Agriculture and Natural Resources Gorgan University

2 Associate Prof. Environment Department, Faculty of Agriculture and Natural Resources Gorgan University

3 Associate Prof. Watershed Department, Faculty of Agriculture and Natural Resources Gorgan University

Abstract

Composting as one of the municipal solid waste management strategies aims to reduce size and weight of excreted substances, to abate odor and leachate, increase resource recovery and reduce the cost of disposal. Environmental impact assessment (EIA) of compost plants is required for compliance with laws and regulations. EIA is one of the effective methods to protect environment. The aim of this study is environmental impact assessment of five candidate locations for compost plant and landfill in east and west of the Golestan Province. Considering new comprehensive and more objective methods of EIA can help improve the environment. In this study, the effects of compost plants on the environment of Golestan Province are evaluated in five sites. In the first step, the sites were visited and a GIS data base was compiled. Then, the maps of the potential environmental pollutions were generated in GIS for each site and relevant data extracted. The results of this part were entered into conditional probability table (CPT) of Bayesian network. Bayesian Belief Network is used in this study and is based on Bayes theory. The result of Bayesian network in each site was weighted with analytical hierarchy process (AHP) method. Then, technique for ordered preference of similarity to ideal solution (Topsis) was used to prioritize the sites. The results of this study showed that in eastern part of Golestan Province, site 2 and in the western part site 4 are the best. The results of this study confirm those of fuzzy matrix with compensating factor. Bayesian Belief network was found useful in EIA for entry of expert knowledge and display of the uncertainty in the status.

Keywords

 

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Journal of Natural Environment
Volume 68, Issue 2 - Serial Number 2
September 2015
Pages 305-319