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Coupling crop and bio-economic farm modelling to evaluate the revised fertilization regulations in Germany

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  • Kuhn, T.
  • Enders, A.
  • Gaiser, T.
  • Schäfer, D.
  • Srivastava, A.K.
  • Britz, W.

Abstract

The German Fertilization Ordinance, implementing mainly the EU Nitrates Directive, was revised in 2017. We couple the bio-economic farm model FarmDyn and the crop system modelling framework SIMPLACE to assess the environmental and economic impact of the revised ordinance. The analysis focuses on specialized pig fattening and arable farms in the federal state of North Rhine-Westphalia. Most dominant farm types are derived from a farm typology based on the German Farm Structure Survey 2016. Following the revised ordinance, a farm type representing pig farms with a high stocking density lowers its emissions from 50 to 38 kg nitrate (NO3−) nitrogen ha−1 and 18 to 8 kg ammonia (NH3) nitrogen ha−1 from manure application. Compliance costs are 2.32 Euro (€) pig−1 and are mainly caused by the need to export manure to meet the stricter nutrient surplus thresholds. A pig farm type with lower stocking density mainly adapts to the compulsory use of low-emission manure application techniques, resulting in almost constant NO3− leaching, a NH3 reduction from manure application of 13 to 9 kg NH3- nitrogen ha−1, and compliance costs of 0.42 € pig−1. The two assessed arable farm types, which start to import manure under the revised ordinance, can lower costs by 109 and 118 € ha−1. However, manure import increases NO3− leaching and NH3 volatilization. Our results show that intensive pig farms realize a high emission reduction and lose a relevant share of their standard gross margin when complying with the revised ordinance. However, farm types with low stocking density, representing a high share of the pig farms in the study area, show little or no changes in costs and emissions. These findings are relevant for efficient enforcement and targeted support measures. Furthermore, the import of manure on arable farms comprises the danger of regional pollution swapping, which policymakers should address by complementary measures. Future research should focus on improving the data base for crop modelling and on scaling-up the farm model to the regional scale to directly link emission changes and environmental targets.

Suggested Citation

  • Kuhn, T. & Enders, A. & Gaiser, T. & Schäfer, D. & Srivastava, A.K. & Britz, W., 2020. "Coupling crop and bio-economic farm modelling to evaluate the revised fertilization regulations in Germany," Agricultural Systems, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:agisys:v:177:y:2020:i:c:s0308521x19303257
    DOI: 10.1016/j.agsy.2019.102687
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    2. Britz, Wolfgang & Ciaian, Pavel & Gocht, Alexander & Kanellopoulos, Argyris & Kremmydas, Dimitrios & Müller, Marc & Petsakos, Athanasios & Reidsma, Pytrik, 2021. "A design for a generic and modular bio-economic farm model," Agricultural Systems, Elsevier, vol. 191(C).
    3. Seidel, Claudia & Shang, Linmei & Britz, Wolfgang, 2023. "A critical assessment of neural networks as meta-model of a farm optimization model," Discussion Papers 338200, University of Bonn, Institute for Food and Resource Economics.
    4. Kanthilanka, H. & Ramilan, T. & Farquharson, R.J. & Weerahewa, J., 2023. "Optimal nitrogen fertilizer decisions for rice farming in a cascaded tank system in Sri Lanka: An analysis using an integrated crop, hydro-nutrient and economic model," Agricultural Systems, Elsevier, vol. 207(C).
    5. Julia Jouan & Julia Heinrichs & Wolfgang Britz & Christoph Pahmeyer, 2019. "Integrated assessment of legume production challenged by European policy interaction: a case-study approach from French and German dairy farms," Working Papers hal-02501428, HAL.
    6. Shang, Linmei & Wang, Jifeng & Schäfer, David & Heckelei, Thomas & Gall, Juergen & Appel, Franziska & Storm, Hugo, 2024. "Surrogate modelling of a detailed farm‐level model using deep learning," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 75(1), pages 235-260.
    7. Ombretta Paladino & Marco Massabò & Edoardo Gandoglia, 2020. "Assessment of Nitrate Hazards in Umbria Region (Italy) Using Field Datasets: Good Agriculture Practices and Farms Sustainability," Sustainability, MDPI, vol. 12(22), pages 1-26, November.

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