Quantification of sustainable animal manure utilization strategies in Hangzhou, China

Abstract

ContextChina's livestock and poultry industries have been experiencing a transformation over recent decades, transitioning from family-size farms to larger, confined animal feeding operations. This development has significantly improved animal production capacity and reduced costs but has also created new challenges to manure management. One important concern is the conflicting interests of environmental protection and economic welfare between policymakers and manure utilization practitioners. ObjectiveIn this study, a regional manure utilization chain (RMUC) model was developed by recognizing optimal logistic configurations for manure and manure-based products between animal feeding operations, centralized processing facilities, and crop farms. We then use RMUC model to quantify the impact of management practices to the animal manure utilization chain of Hangzhou, China in the context of sustainable development. MethodThe RMUC model implemented an analytical target cascading structure with a multi-objective optimization algorithm to generate a set of Pareto-optimal configurations for discussing the regional economic costs and greenhouse gas (GHG) emission considering the practitioners' operational decisions to the designated manure management practices. Results and conclusionA comparative analysis quantified and prioritized the manure management practices (solid/liquid separation, manure reduction strategies); estimated economic and GHG emission credits of manure composition measurements; and indicated economic and GHG emission benefits of electric vehicles and the secondary infrastructures on manure distribution. The results showed sustainable metrics of the manure utilization improvement, including private costs, regional benefits, and the global impact of GHG emissions. SignificanceThe RMUC model demonstrated the compromise between practitioners' interests and public sustainability benefits given a certain level of constraints in decision process. Our analysis is an example of implementing computational models to deal with agricultural systematic problems with social, environmental, and economic concerns.