Policy support for mitigating agricultural pollution and GHGs emissions

The goal
The goal of this project is to develop innovative methodologically sound approaches and modeling tools that would enable to analyze and design robust technical and financial measures to reduce pollution and emissions of greenhouse gases (GHGs) coming from agriculture.

Introduction
Growing demands for agricultural products (4F - food, feed, fuel, fiber) boost the development of industrial input-intensive agriculture, which in many countries of the world is running into resource and environmental limits impacting water, land, air, often causing livestock related disease outbreaks. Agriculture is responsible for a large part of global environmental pollution and GHGs emissions. The emissions comprise primarily of methane (CH4) from grazing livestock, waste and manure management and nitrous oxide (N2O) from nutrient cycles in agricultural soils. Agriculture contributes many pollutants to water and soil such as phosphates, herbicides, pesticides, nitrates and bacteria. Nitrates and pesticides are common contaminants of groundwater derived from agriculture. Nitrate is a particular concern because of the health effects related to consumption of nitrate in drinking water. Nitrate in water can potentially cause many health problems, among the most known are elevated levels of nitrate (blue baby syndrome) and cancer. Nitrate can also contribute to hormonal and endocrine dysfunction by disrupting the thyroid, the gland responsible for these functions.

Preserving resource quality requires sustainable approaches to production expansion and intensification as well as diversification of various production systems. There is a need for integrated multi-disciplinary approaches demonstrating that explicit treatment of social, environmental, and health risks reduces costs to achieve food and water security and environmental quality.

Methodology
Approaches to planning agricultural production expansion traditionally have been classified along two separate lines. One approach deals with estimation of physical production potential of land, usually without too much concern of socioeconomic and demographic driving forces and constraints.

A second approach concentrates more on socioeconomic and behavioral aspects of producers and consumers. Here, resources like land or water are only generally described. However, within the limits of natural resources, effective land performance is largely determined by anthropogenic factors, i.e. the availability of infrastructure, market access and complex interaction of behavioral, socioeconomic, cultural and technological factors.

We propose a modeling framework that integrates the two lines. Contrary to traditional Keynesian economics, it accounts for supply limiting factors as land and water resources, adequate infrastructure and advise on robust production expansion relying on such social, environmental and health risk indicators as, for example, quality of water, air, soil, health, etc., no matter whether these indicators can be measures in monetary terms or in terms of proxy variables. The explicit treatment of uncertainties and risks is an essential component of the framework as it leads to a welfare maximizing solution.

Applications
Major projects CATSEI and INMIC demonstrate promising results of the methodology.

CATSEI
Detailed studies of agriculture developments “Policy Decision Support for Sustainable Adaptation of China’s Agriculture to Globalization” (hence the CHINAGRO project) and Chinese Agricultural Transition: Trade, Social and Environmental Impacts (CATSEI), estimate current and future potential (N-P-K)-nutrient loads  from livestock and crop production in China quantified in the context of highly plausible economic, demographic and urbanization scenario assumptions. The project highlights negative impacts of production intensification trends, critical locations of nutrients output in excess of uptake capacity of available cultivated land, identifies main factors contributing to the increase of health risks to humans. More

INMIC
Collaborative project between APD-LUC-FOR carried out under the umbrella of IIASA’s “Greenhouse Gas Initiative” (GGI) integrates LUC (CATSEI) and APD (GAINS) methodologies to investigates and estimates indicators describing the most important flows of reactive nitrogen compounds from major agricultural activities (excessive crop fertilization and intensive livestock production) to different pools in the environment. In the INMIC (Integrated Nitrogen Management in China) project, the environmental indicators used to reflect the impacts of agricultural production comprise of fluxes to air (emissions of ammonia and nitrous oxide) and water (nitrate leaching). Alternative mitigation scenarios reducing the impacts are compared in terms of human exposure to risk, i.e. the number of people in different risk classes. The assessment is useful for policy advice regarding enforcement mechanisms for pollution control. It supports integrated planning of allocation and production regimes of crops and livestock accounting for multifold economic and environmental factors. report. More

Relevant publications:

1. Fischer, G., Ermolieva, T., Ermoliev, Y., van Velthuizen, H. (2006). Livestock production planning under environmental risks and uncertainties. Journal of Systems Science and System Engineering, 15(4), 385-399.
2. Ermolieva T., G. Fischer, and H. van Velthuizen (2005). Livestock Production and Environmental Risks in China: Scenarios to 2030”, FAO/IIASA Research Report, International Institute for Applied Systems Analysis, Laxenburg, Austria.
3. Ermolieva, T., Winiwarter, W., Fischer, G., Cao, G.-Y., Klimont, Z., Schöpp, W., Li, Y., Asman, W.A.H. (2009). Integrated nitrogen management in China. IIASA Interim Report IR-09-005, International Institute for Applied Systems Analysis, Laxenburg, Austria.
4. Fischer G., Ermolieva, T., Cao, G.Y., Zheng, X.Y., Wiberg, D., Winiwarter, W., Klimont, Z., Toth, E. (2008a). Measuring and Mitigating Environmental Risks from Agriculture, submitted to the special issues of peer reviewed papers presented at IIASA-Peking University Symposium on Urbanization and Environment
5. Fischer G,  Ermolieva T,  Ermoliev Y,  Sun L  (2008b). Risk-adjusted approaches for planning sustainable agricultural development. Stochastic Environmental Research and Risk Assessment, 1-10.
6. Fischer G,  Ermolieva T,  Ermoliev Y,  Sun L  (2007). Integrated risk management approaches for planning sustainable agriculture. In C. Huang, C. Frey, J. Feng (Eds.), Advances in Studies on Risk Analysis and Crisis Response. Atlantis Press, Paris, France.
7. Fischer, G., Ermolieva, T., Ermoliev, Y., and van Velthuizen, H. (2006) Sequential downscaling methods for Estimation from Aggregate Data. In K. Marti, Y. Ermoliev, M. Makowski, G. Pflug (Eds.), Coping with Uncertainty: Modeling and Policy Issue. Springer Verlag, Berlin, New York.
8. Fischer, G. and B.C. O’Neill (2004). Global and case-based modeling of population and land-use change. Paper prepared for the NRC workshop on New Research on Population and Environment. Irvine, CA. (peer reviewed).
9. Fischer G, van Velthuizen H, Mahendra S and Nachtergaele FO (2002). Global agro-ecological assessment for agriculture in the 21st century: methodology and results. International Institute for Applied Systems Analysis (IIASA). Research report RR-02-02, IIASA, Laxenburg, Austria. Laxenburg, Austria, FAO/IIASA.

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Last updated: 05 Oct 2011