Cyanobacterial risk prevention under global warming using an extended Bayesian network

Jiang，Peng1,2; Liu，Xiao3; Zhang，Jingjie4,5; Te，Shu Harn4; Gin，Karina Yew Hoong4,6; Fan，Yee Van7; Klemeš，Jiří Jaromír7; Shoemaker，Christine A.6,8

2021-08-20

10.1016/j.jclepro.2021.127729

Journal of Cleaner Production   影响因子和分区

0959-6526

1879-1786

Cyanobacterial blooms under global warming are increasing worldwide, producing emerging contaminants, which threaten the health of human beings and aquatic ecosystems. The health burdens warrant the development of a useful risk-assessment tool and a holistic preventive-control scheme to prevent cyanobacterial blooms. This paper aims to integrate cyanobacterial risk assessment and risk preventive control by investigating the relationships amongst cyanobacterial blooms and multi-dimensional influencing variables. Two challenges hinder such a task. First, the time-series variations in cyanobacteria and influencing variables are uncertain and nonlinear. Second, there rarely exists an explicit modelling framework for integrating cyanobacterial risk assessment and risk preventive control. This study builds an extended Bayesian network model and proposes an integrated framework with functions of assessment, inference, preventive control, and visualisation of the risk of cyanobacterial blooms. Field data from a tropical lake are used to evaluate the model and framework. The proposed model achieves better performance than the seven models in comparison. The cyanobacterial risk is anticipated to increase by 38.5% under global warming. On the contrary, guided by the model and framework, the risk could be reduced by about 60% by taking the identified risk preventive control scheme. The cyanobacterial risk prevention would reduce aquatic emerging contaminants in drinking and recreational water sources.

Bayesian networks Cyanobacterial risk Decision support Global warming Pollution reduction Risk management

SCI ; EI

英语

其他

Fundamental Research Funds for the Central Universities["YJ202138","2021ZY-SX14","SXYPY202139"] ; China Postdoctoral Science Foundation[2018M640397] ; National Natural Science Foundation of China[71673188] ; EU project Sustainable Process Integration Laboratory - SPIL[CZ.02.1.01/0.0/0.0/15_003/0000456]

Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology

Green & Sustainable Science & Technology ; Engineering, Environmental ; Environmental Sciences

WOS:000693419300003

ELSEVIER SCI LTD

20212310470621

Aquatic ecosystems ; Bayesian networks ; Decision support systems ; Global warming ; Pollution control ; Potable water ; Risk assessment

Atmospheric Properties:443.1 ; Water Resources:444 ; Ecology and Ecosystems:454.3 ; Computer Software, Data Handling and Applications:723 ; Management:912.2 ; Accidents and Accident Prevention:914.1 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4

2-s2.0-85107282189

Scopus

1.Department of Industrial Engineering and Engineering Management,Business School,Sichuan University,Chengdu,610064,China
2.Department of Industrial Engineering & Management,Shanghai Jiao Tong University,Shanghai,200240,China
3.China Institute for Urban Governance,Shanghai Jiao Tong University,Shanghai,200030,China
4.NUS Environmental Research Institute (NERI),National University of Singapore,Singapore,117411,Singapore
5.School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
6.Department of Civil and Environmental Engineering,National University of Singapore,Singapore,117576,Singapore
7.Sustainable Process Integration Laboratory – SPIL,NETME Centre,Faculty of Mechanical Engineering,Brno University of Technology - VUT Brno,Brno,Technická 2896/2,616 69,Czech Republic
8.Department of Industrial Systems Engineering & Management,National University of Singapore,Singapore,119260,Singapore

Jiang，Peng,Liu，Xiao,Zhang，Jingjie,et al. Cyanobacterial risk prevention under global warming using an extended Bayesian network[J]. Journal of Cleaner Production,2021,312.

Jiang，Peng.,Liu，Xiao.,Zhang，Jingjie.,Te，Shu Harn.,Gin，Karina Yew Hoong.,...&Shoemaker，Christine A..(2021).Cyanobacterial risk prevention under global warming using an extended Bayesian network.Journal of Cleaner Production,312.

Jiang，Peng,et al."Cyanobacterial risk prevention under global warming using an extended Bayesian network".Journal of Cleaner Production 312(2021).