Multiple-pollutant cost-effectiveness of greenhouse gas mitigation measures in the UK agriculture

V Eory, CFE Topp, D Moran

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

This paper develops multiple-pollutant marginal abatement cost curve analysis to identify an optimal set of greenhouse gas (GHG) mitigation measures considering the trade-offs and synergies with other environmental pollutants. The analysis is applied to UK agriculture, a sector expected to make a contribution to the national GHG mitigation effort. Previous analyses using marginal abatement cost curves (MACCs) have determined the sector’s GHG abatement potential based on the cost-effectiveness of a variety of technically feasible mitigation mea- sures. Most of these measures have external effects on other pollution loads arising from agricultural activities. Here the monetary values of four of the most important impacts to water and air (specifically ammonia, nitrate, phosphorous and sediment) are included in the cost- effectiveness analysis. The resulting multiple-pollutant marginal abatement cost curve (MP MACC) informs the design of sustainable climate change policies by showing how the MP MACC for the UK agriculture can differ from the GHG MACC. The analysis also highlights research gaps, and suggests a need to understand the wider environmental effects of GHG mitigation options and to reduce the uncertainty in pollutant damage cost estimates. # 2012 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)55 - 67
Number of pages13
JournalEnvironmental Science and Policy
Volume27
DOIs
Publication statusPrint publication - Mar 2013

Bibliographical note

1023326
1023353
1023407

Keywords

  • Co-effects
  • Cost-effectiveness
  • Greenhouse gases
  • Marginal abatement costs curves
  • Nitrogen
  • Phosphorus

Fingerprint Dive into the research topics of 'Multiple-pollutant cost-effectiveness of greenhouse gas mitigation measures in the UK agriculture'. Together they form a unique fingerprint.

Cite this