Estimating Costs of Reducing Environmental Emissions From a Dairy Farm: Multi-objective epsilon-constraint Optimization Versus Single Objective Constrained Optimization

TR Number

Date

2020-07-08

Journal Title

Journal ISSN

Volume Title

Publisher

Virginia Tech

Abstract

Agricultural production is an important source of environmental emissions. While water quality concerns related to animal agriculture have been studied extensively, air quality issues have become an increasing concern. Due to the transfer of nutrients between air, water, and soil, emissions to air can harm water quality. We conduct a multi-objective optimization analysis for a representative dairy farm with two different approaches: nonlinear programming (NLP) and ϵ-constraint optimization to evaluate trade-offs among reduction of multiple pollutants including nitrogen (N), phosphorus (P), greenhouse gas (GHG), and ammonia. We evaluated twenty-six different scenar- ios in which we define incremental reductions of N, P, ammonia, and GHG from five to 25% relative to a baseline scenario. The farm entails crop production, livestock production (dairy and broiler), and manure management activities. Results from NLP optimization indicate that reducing P and ammonia emissions is relatively more expen- sive than N and GHG. This result is also confirmed by the ϵ-constraint optimization. However, the latter approach provides limited evidence of trade-offs among reduction of farm pollutants and net returns, while the former approach includes different re- duction scenarios that make trade-offs more evident. Results from both approaches indicate changes in crop rotation and land retirement are the best strategies to reduce N and P emissions while cow diet changes involving less forage represents the best strategy to reduce ammonia and GHG emissions.

Description

Keywords

Multi-objective Optimization, Nitrogen, Phosphorus, Ammonia, Green House Gas (GHG), ϵ-constraint Optimization, Farm Economics

Citation

Collections