Suitability evaluation of rural sewage treatment facilities in China considering lifcycle environmental impacts and regional differences

Jiang，Jiping1; Hu，Xiao1; Gu，Yang1; Wang，Wenzhao2; Bi，Zhaoshun2; Yao，Changsong2; Liang，Xiao4; Wen，Qingzhi1; Luo，Meiyu3; Zheng，Yi1; Xia，Xunfeng5

2023-10-15

10.1016/j.jenvman.2023.118516

Journal of Environmental Management   Impact Factor & Quartile

0301-4797

1095-8630

Centralized vs. decentralized sewage treatment is one of the key issues in the planning of rural sewage treatment (RST) in China due to the country's diverse regional characteristics. There are very limited comprehensive evaluation models for selecting regionally suitable schemes and facilities, particularly for national or provisional scale planning. As a scenario-based multi-attribute decision-making (MADM) issue, this paper develops a novel RST suitability evaluation model by integrating the multi-attribute analytic hierarchy process (AHP) with the technique for order preference by similarity to an ideal solution (TOPSIS). The suitability evaluation model sets up 3 small-centralized and 4 decentralized RST facilities as candidates and includes 12 evaluation indicators that cover economic cost, life cycle environmental impacts, technical features and operations management. Eight generic scenarios are classified for Chinese rural areas based on differences in three major characteristic factors, i.e., population density (PD), the economic development level (EDL), and topographic slope (TS). The universal evaluation results show that a centralized sewage treatment scheme is more suitable for areas with a high PD/high EDL/low TS, while a decentralized scheme is more suitable for areas with a low PD/low EDL/high TS. Sensitivity analysis shows that in regions with a high PD/low EDL, the indicator weight of the construction investment cost in the model has a great influence on the facility suitability ranking. However, in regions with a high PD/high EDL, the ranking is the most sensitive to the indicator weights of the global warming potential and sewage treatment effect. Furthermore, as a spatial decision issue, an RST suitability map of Hunan Province in China is produced at the county level of resolution, and the map is generally consistent with our field knowledge of several counties in Hunan Province. The presented evaluation framework can be integrated into environmental decision support systems in the future to help local and central governments, water utilities, design institutes and other stakeholders scientifically plan RST projects.

AHP China Life cycle assessment Rural sewage treatment facilities Sensitivity analysis TOPSIS

SCI

English

First ; Corresponding

National Natural Science Foundation of China[51979136];

Environmental Sciences & Ecology

Environmental Sciences

WOS:001033761800001

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD

ENVIRONMENT/ECOLOGY

2-s2.0-85164239400

Scopus

1.School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
2.Forigin Research Center,Fairylands Environmental Sci-Tech (Shenzhen) Co.,Ltd.,Shenzhen,518055,China
3.Shenzhen Zhishu Environmental Technology Co.,Ltd.,Shenzhen,518055,China
4.School of Economics,Shenzhen University,Shenzhen,518055,China
5.Technical Centre for Soil,Agriculture and Rural Ecology and Environment,Ministry of Ecology and Environment,Beijing,100012,China

Jiang，Jiping,Hu，Xiao,Gu，Yang,et al. Suitability evaluation of rural sewage treatment facilities in China considering lifcycle environmental impacts and regional differences[J]. Journal of Environmental Management,2023,344.

Jiang，Jiping.,Hu，Xiao.,Gu，Yang.,Wang，Wenzhao.,Bi，Zhaoshun.,...&Xia，Xunfeng.(2023).Suitability evaluation of rural sewage treatment facilities in China considering lifcycle environmental impacts and regional differences.Journal of Environmental Management,344.

Jiang，Jiping,et al."Suitability evaluation of rural sewage treatment facilities in China considering lifcycle environmental impacts and regional differences".Journal of Environmental Management 344(2023).