Simulating the spatial distribution of pollutant loads from pig farming using an agent-based modeling approach

Ngo, A.T., Nguyen, G.T.H., Nong, D.H., & See, L. ORCID: (2022). Simulating the spatial distribution of pollutant loads from pig farming using an agent-based modeling approach. Environmental Science and Pollution Research 29 42037-42054. 10.1007/s11356-021-17112-2.

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This research developed an agent-based model (ABM) for simulating pollutant loads from pig farming. The behavior of farmer agents was captured using concepts from the theory of planned behavior. The ABM has three basic components: the household or farmer agent, the land patches, and global parameters that capture the environmental context. The model was evaluated using a sensitivity analysis and then validated using data from a household survey, which showed that the predictive ability of the model was good. The ABM was then used in three scenarios: a baseline scenario, a positive scenario in which the number of pigs was assumed to remain stable but supporting policies for environmental management were increased, and a negative scenario, which assumed the number of pigs increases but management measures did not improve relative to the baseline. The positive scenario showed reductions in the discharged loads for many sub-basins of the study area while the negative scenario indicated that increased loads will be discharged to the environment. The scenario results suggest that to maintain the development of pig production while ensuring environmental protection for the district, financial, and technical support must be provided to the pig producers. The experience and education level of the farmers were significant factors influencing behaviors related to manure reuse and treatment, so awareness raising through environmental communication is needed in addition to technical measures.

Item Type: Article
Uncontrolled Keywords: Agent-based model; Livestock waste; Pig farming; Planned behavior; Pollutant load; Water pollution
Research Programs: Advancing Systems Analysis (ASA)
Advancing Systems Analysis (ASA) > Novel Data Ecosystems for Sustainability (NODES)
Depositing User: Luke Kirwan
Date Deposited: 09 Nov 2021 14:16
Last Modified: 07 Jun 2022 12:54

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