- Current research grants
- Finished research grants
- Current Dissertation Projects
- Finalized Dissertations
The relation between indicators for the crediting of emission rights and abatement costs - a systematic modelling approach for dairy farms
If Greenhouse Gases (GHGs) are to be effectively reduced, agriculture as a non negligible emitter will have to contribute to abatement efforts. Accordingly, for some years already, the inclusion of agriculture, and especially dairy production as a main agricultural emitter in temperate climates, into an emission trading system or its exposure to a climate tax is discussed. However, most agricultural GHG emissions stem from non-point sources and cannot be measured directly.
Therefore, GHG related economic instruments for agriculture must be based on accounting rules which estimate CO2, CH4 and N2O emissions, more or less correctly, from observable farm attributes (herd sizes, milk yields, feed use etc.). In the following we term such a system of accounting rules an emission indicator. Confronted with for example an emission tax agents will select their abatement strategy not based on actual emissions, but on the chosen indicator. The latter hence determines abatement strategies and related costs for a given emission target or tax. Against this background, we want to determine how the choice of indicator impacts on efficiency of abatement, distributional effects and the allocation flexibility of different farms and thus contribute to the discussion about the best policy design for an inclusion of agriculture into climate policy.
FARMDYN - a flexible, full dynamic Mixed Integer Programming model for German farms
In order to analyze the impact of different GHG indicators and GHG emission ceilings on German dairy farm, a highly detailed single farm programming model was developed, with features such as dairy cow herds differentiated by milk yield potential, different feeding periods, monthly work restrictions linked to available field working days and a detailed machinery park.
The model documentation can be found here: Britz, W., Lengers B., Kuhn T., Schaefer D. (2015): A highly detailed template model for dynamic optimization of farms - FARMDYN, Institute for Food and Resource Economics, University Bonn, 110 pages
Publications and conference contributions related to the project
Lengers, B., Britz, W., Holm-Müller, K. (2014):What drives marginal abatement costs of greenhouse gases on dairy farms? A meta-modelling approach, Journal of Agricultural Economics 65(2) , Link....
Lengers, B., Schiefler, I. & W. Büscher (2013): A comparison of emission calculations using different modeled indicators with 1-year online measurements. Journal of Environmental Monitoring and Assessment, 185:9751-9762. doi:10.1007/s10661-013-3288-y
Lengers, B., Britz, W. and Holm-Müller, K. (2013): Comparison of GHG-emission indicators for dairy farms with respect to induced abatement costs, accuracy and feasibility, Applied Economic Perspectives and Policy, 35(3):451-475. doi:10.1093/aepp/ppt013
Lengers, B. and Britz, W. (2012).
The choice of emission indicators in environmental policy design: an analysis of GHG abatement in different dairy farms based on a bio-economic model approach. Review of Agricultural and Environmental Studies, 93(2), 117-144.
Budde, Johanna: Ökonomische Auswirkungen von Poltiken zur Umsetzung der Wasserrahmenrichtlinie auf die Schweinehaltung im Münsterland
Lengers, Bernd: The relation between indicators for the crediting of emission rights and abatement costs - a systematic modelling approach for dairy farms
Contributions to conferences and lecture series:
Lengers, B., Britz, W. & K. Holm-Müller (2013): What drives marginal abatement costs of greenhouse gases on dairy farms – a meta-modelling approach. Paper presented at the 2012 AURÖ-Workshop, Frankfurt (Oder), Germany, February 18-19.
Britz, W. and Lengers, B. (2012):
Abatement options for GHG emissions in a dynamic bio-economic model for dairy farms – DAIRYDYN -. Presentation contributed to the CIDRe lecture series “modelling across scales and disciplines”. University of Bonn, 09.10.2012, Bonn. Download
Lengers, B. and Britz, W. (2011):
Farm specific marginal abatement costs for dairy GHG emissions which base upon different emission indicators – a bio-economic model approach , selected paper presented at the 2011 EAAE PhD Workshop, April 27-29, 2011, Nitra (Slovak Republic)
Discussion and technical papers:
Lengers, B., Britz, W. and Holm-Müller, K. (2013): Trade-off of feasibility against accuracy and cost efficiency in choosing indicators for the abatement of GHG-emissions in dairy farming, Discussion Paper 2013: Download
Lengers, B.(2012): Construction of different GHG accounting schemes for approximation of dairy farm emissions. Technical paper referring to DFG-project HO 3780/2-1. Download
Lengers, B. (2012): Up to date relevant GHG abatement options in German agricultural dairy production systems. Technical Paper referring to DFG-project HO 3780/2-1. Institute for Food and Resource Economics, University of Bonn. Download
Lengers, B. (2011): GHG survey of German agriculture -specific view on dairy production systems. Technical paper referring to DFG-project HO 3780/2-1. Download
Last updated: Thursday, January 05, 2017
- Research meetings must be more sustainable, Sanz-Cobena, A., Alessandrini, R., Bodirsky, B. L., Springmann, M., Aguilera, E., Amon, B., Bartolini, F., Geupel, M., Grizzetti, B., Kugelberg, S., Latka, C., Liang, X., Milford, A. B., Musinguzi, P., Ng, E. L., Suter, H., Leip, A. (2020): Nature Food 1: 187-189.Modelling food security: Bridging the gap between the micro and the macro scale, Müller, B., Hoffmann, F., Heckelei, T., Müller, C., Hertel, T. W., Polhill, J. G., van Wijk, M., Achterbosch, T., Alexander, P., Brown, C., Kreuer, D., Ewert, F., Ge, J., Millington, J. D. A., Seppelt, R., Verburg, P. H., Webber, H. (2020): Global Environmental Change 63: 16 pages.Forecasting International Sugar Prices: A Bayesian Model Average Analysis, Amrouk, E. M., Heckelei, T. (2020): Sugar Tech: 11 pages.Brexit: an economy-wide impact assessment on trade, immigration, and foreign direct investment, Jafari, Y., Britz, W. (2020): Empirica 47(1): 17-52.Efficiency differentials in resource-use among smallholder cassava farmers in southwestern Cameroon, Molua, E. L., Tabe-Ojong, M. P., Meliko, M. O., Nkenglefac, M. F., Akamin, A. (2019): Development in Practice: 11 pages.New insights on efficiency and productivity analysis: Evidence from vegetable-poultry integration in rural Tanzania, Habiyaremye, N., Tabe-Ojong, M. P., Ochieng, J., Chagomoka, T. (2019): Scientific African 6(e00190): 11 pages.Explaining farm structural change in the European agriculture: a novel analytical framework, Neuenfeldt, S., Gocht, A., Heckelei, T., Ciaian, P. (2019): European Review of Agricultural Economics 46(5): 713-768.Machine learning in agricultural and applied economics Storm, H., Baylis, K., Heckelei, T. (2019): European Review of Agricultural Economics, jbz033: 44 pagesInterdependence between cash crop and staple food international prices across periods of varying financial market stress Amrouk, E. M., Grosche, S., Heckelei, T. (2019): Applied Economics: 16 pages.