Estimation of Energy Balance and Greenhouse Gas Emissions in Dairy Farms (Case study: Qazvin Province)

Document Type : Original Article

Authors

1 Faculty Member, Department of Agricultural Machinery, Sari College of Agricultural, Technical and Vocation University, Mazandaran Province, Iran.

2 Faculty Member, Department of Animal Sciences, Sari College of Agricultural, Technical and Vocational University, Mazandaran Province, Iran.

Abstract

Investigation of energy consumption and its management in industrial and semi-industrial units of livestock breeding is one of the most important issues in economy and energy of these units. The present study was conducted to investigate the energy flow and greenhouse gas emissions in dairy farms in Qazvin Province. Data was collected through questionnaires and face-to-face interviews with 62 dairy farm managers . The results showed that the total energy input to produce one liter of milk was 27.8 MJ. In addition, livestock and fuel feeders with 48% and 29% share were the most energy consuming units. Energy efficiency in this study was estimated to be 0.25. Greenhouse gas emissions were calculated to be 0.65 kg of carbon dioxide per liter of milk and among the inputs used, machinery and fuel accounted for 72% and 24% of greenhouse gas emissions, respectively,. Based on the results obtained, it is possible to increase energy efficiency and reduce environmental impacts by replacing low performance machines and equipment with higher performance ones and by consuming natural gas fuel instead of diesel fuel. It is also possible to reduce energy consumption by appropriately managing diets and using optimal nutritional patterns and suitable nutrition.

Keywords

References

[1] Moitzi, G., Damm, D., Weingartmann, H., & Boxberger, J. (2010). Analysis of Energy Intensity in Selected Austrian Dairy Farms with Focus on Concentrate Level in Feeding. Bulletin UASVM Agriculture, 67(1), 1843-5386. https://doi.org/10.15835 /buasvmcn-agr:5032

[2] Basarir, A., & Gillespie, J. M. (2003, February 1-5). Goals of Beef Cattle and Dairy Producers: A Comparison of the Fuzzy Pair-Wise Method and Simple Ranking Procedure. . https://ideas.repec.org/p/ags/saeatm/35163.html

[3] Meul, M., Nevens, F., Reheul, D., & Hofman, G. (2007). Energy use efficiency of specialised dairy, arable and pig farms in Flanders. Agriculture, Ecosystems & Environment, 119(1-2), 135-144. https://doi.org/10.1016/j.agee.2006.07.002

[4] Sefeedpari, P., Rafiee, S., Akram, A., & Pishgar-Komleh, S. H. (2014). Modeling output energy based on fossil fuels and electricity energy consumption on dairy farms of Iran: Application of adaptive neural-fuzzy inference system technique. Computers and electronics in agriculture, 109, 80-85. https://doi.org/10.1016/j.compag.2014.09.010

[5] Lundie, S., Feitz, A., Changsiri, A., Jones, M., Dennien, G., & Morain, M. (2003). Evaluation of the environmental performance of the Australian dairy processing industry using life cycle assessment. T. U. o. N. S. W. Centre for Water and Waste Technology, Sydney.

[6] Gollnow, S., Lundie, S., Moore, A. D., McLaren, J., van Buuren, N., Stahle, P., Christie, K., Thylmann, D., & Rehl, T. (2014). Carbon footprint of milk production from dairy cows in Australia. International Dairy Journal, 37(1), 31-38. https://doi.org/ 10.1016/j.idairyj.2014.02.005

[7] Robert Kiefer, L., Menzel, F., & Bahrs, E. (2015). Integration of ecosystem services into the carbon footprint of milk of South German dairy farms. Journal of Environmental Management, 152, 11-18. https://doi.org/10.1016/j.jenvman.2015.01.017

[8] Sadeghi Aghdam, F., & Maki, S. (2017- July). Abstract of the results of the census of the country's industrial livestock-2016. M. o. C. Statistics and Strategic Information Center, Labor and Social Welfare.

[9] Cochran, W. G. (1991, January). Sampling Techniques (3rd ed.). Wiley. https://www. wiley.com/en-us/Sampling+Techniques%2C+3rd+Edition-p-9780471162407

[10] Nabavi-Pelesaraei, A., Abdi, R., & Rafiee, S. (2016). Neural network modeling of energy use and greenhouse gas emissions of watermelon production systems. Journal of the Saudi Society of Agricultural Sciences, 15(1), 38-47. https://doi.org/ 10.1016/j.jssas.2014.05.001

[11] CIGR International Commission of Agricultural and Biosystems Engineering. (1999). CIGR Handbook of Agricultural Engineering: Energy & biomass engineering (O. Kitani, Ed.). American Society of Agricultural Engineers. https://books.google. com/books?id=430fAQAAMAAJ

[12] Ozkan, B., Akcaoz, H., & Fert, C. (2004). Energy input–output analysis in Turkish agriculture. Renewable Energy, 29(1), 39-51. https://doi.org/10.1016/S0960-1481 (03)00135-6

[13] Frorip, J., Kokin, E., Praks, J., Poikalainen, V., Ruus, A., Veermäe, I., Lepasalu, L., Schäfer, W., Mikkola, H., & Ahoka, J. (2012). Energy consumption in animal production - Case farm study. Biosystems Engineering, 10(Special Issue 1), 39-48. https://agronomy.emu.ee/vol10Spec1/p10s105.pdf

[14] Wells, C. (2001, August ). Total energy indicators of agricultural sustainability: dairy farming case study (1171-4662). M. o. A. a. F. MAF Policy. https://citeseerx.ist. psu.edu/viewdoc/download?doi=10.1.1.15.692&rep=rep1&type=pdf

[15] Sainz, R. D. (2003). Framework for calculating fossil fuel use in livestock systems. T. F. a. A. O. o. t. U. N. (FAO). https://www.fao.org/documents/pub_dett.asp?lang=ar& pub_id=154286

[16] Coley, D. A., Goodliffe, E., & Macdiarmid, J. (1998). The embodied energy of food: the role of diet. Energy policy, 26(6), 455-460. https://abdn.pure.elsevier.com/en/ publications/the-embodied-energy-of-food-the-role-of-diet

[17] Dyer, J., & Desjardins, R. (2003). Simulated Farm Fieldwork, Energy Consumption and Related Greenhouse Gas Emissions in Canada. Biosystems Engineering, 85(4), 503-513. https://doi.org/10.1016/S1537-5110(03)00072-2

[18] Liang, S., Xu, M., & Zhang, T. (2013). Life cycle assessment of biodiesel production in China. Bioresource Technology 129, 72-77. https://doi.org/10.1016/j.biortech.2012.11.037

[19] Uzmay, A., Koyubenbe, N., & Armagan, G. (2009). Measurement of Efficiency Using Data Envelopment Analysis (DEA) and Social Factors Affecting the Technical Efficiency in Dairy Cattle Farms within the Province of Izmir, Turkey. Journal of Animal and Veterinary Advances. 8(6), 1110-1115. http://www.medwelljournals. com/abstract/?doi=javaa.2009.1110.1115

[20] Soltan Ali, H., Naskhah, A., Rouhani, A., & Ki Dashti, M. (2014, March 13). Emission Analysis of Consumption Inputs in a Dairy Cattle Breeding Unit The first national conference on engineering and management of agriculture, environment and sustainable natural resources, Permanent Conference Secretariat, Hamedan, Iran.  https://civilica.com/doc/253459

[21] Hasani, A., Hir, M., & Farhang, S. (2013). Measuring Iranian provinces efficiency in meaty poultry production by use of Data Envelopment Analysis. International Research Journal of Applied and Basic Sciences, 4(11), 3338-3346. https://www. semanticscholar.org/paper/Measuring-Iranian-provinces-efficiency-in-meaty-by-H asani-Hir/161fde4d8d2c850fdbc6c1ab0b84a070f41df043

[22] Sefeedpari, P., Ghahderijani, M., & Pishgar-Komleh, S. (2013). Assessment the effect of wheat farm sizes on energy consumption and CO2 emission. Journal of Renewable and Sustainable Energy, 5(2), 023131-023115. https://doi.org/10.1063/1.4800207

References

References
[1] Moitzi, G., Damm, D., Weingartmann, H., & Boxberger, J. (2010). Analysis of Energy Intensity in Selected Austrian Dairy Farms with Focus on Concentrate Level in Feeding. Bulletin UASVM Agriculture, 67(1), 1843-5386. https://doi.org/10.15835 /buasvmcn-agr:5032
[2] Basarir, A., & Gillespie, J. M. (2003, February 1-5). Goals of Beef Cattle and Dairy Producers: A Comparison of the Fuzzy Pair-Wise Method and Simple Ranking Procedure. . https://ideas.repec.org/p/ags/saeatm/35163.html
[3] Meul, M., Nevens, F., Reheul, D., & Hofman, G. (2007). Energy use efficiency of specialised dairy, arable and pig farms in Flanders. Agriculture, Ecosystems & Environment, 119(1-2), 135-144. https://doi.org/10.1016/j.agee.2006.07.002
[4] Sefeedpari, P., Rafiee, S., Akram, A., & Pishgar-Komleh, S. H. (2014). Modeling output energy based on fossil fuels and electricity energy consumption on dairy farms of Iran: Application of adaptive neural-fuzzy inference system technique. Computers and electronics in agriculture, 109, 80-85. https://doi.org/10.1016/j.compag.2014.09.010
[5] Lundie, S., Feitz, A., Changsiri, A., Jones, M., Dennien, G., & Morain, M. (2003). Evaluation of the environmental performance of the Australian dairy processing industry using life cycle assessment. T. U. o. N. S. W. Centre for Water and Waste Technology, Sydney.
[6] Gollnow, S., Lundie, S., Moore, A. D., McLaren, J., van Buuren, N., Stahle, P., Christie, K., Thylmann, D., & Rehl, T. (2014). Carbon footprint of milk production from dairy cows in Australia. International Dairy Journal, 37(1), 31-38. https://doi.org/ 10.1016/j.idairyj.2014.02.005
[7] Robert Kiefer, L., Menzel, F., & Bahrs, E. (2015). Integration of ecosystem services into the carbon footprint of milk of South German dairy farms. Journal of Environmental Management, 152, 11-18. https://doi.org/10.1016/j.jenvman.2015.01.017
[8] Sadeghi Aghdam, F., & Maki, S. (2017- July). Abstract of the results of the census of the country's industrial livestock-2016. M. o. C. Statistics and Strategic Information Center, Labor and Social Welfare.
[9] Cochran, W. G. (1991, January). Sampling Techniques (3rd ed.). Wiley. https://www. wiley.com/en-us/Sampling+Techniques%2C+3rd+Edition-p-9780471162407
[10] Nabavi-Pelesaraei, A., Abdi, R., & Rafiee, S. (2016). Neural network modeling of energy use and greenhouse gas emissions of watermelon production systems. Journal of the Saudi Society of Agricultural Sciences, 15(1), 38-47. https://doi.org/ 10.1016/j.jssas.2014.05.001
[11] CIGR International Commission of Agricultural and Biosystems Engineering. (1999). CIGR Handbook of Agricultural Engineering: Energy & biomass engineering (O. Kitani, Ed.). American Society of Agricultural Engineers. https://books.google. com/books?id=430fAQAAMAAJ
[12] Ozkan, B., Akcaoz, H., & Fert, C. (2004). Energy input–output analysis in Turkish agriculture. Renewable Energy, 29(1), 39-51. https://doi.org/10.1016/S0960-1481 (03)00135-6
[13] Frorip, J., Kokin, E., Praks, J., Poikalainen, V., Ruus, A., Veermäe, I., Lepasalu, L., Schäfer, W., Mikkola, H., & Ahoka, J. (2012). Energy consumption in animal production - Case farm study. Biosystems Engineering, 10(Special Issue 1), 39-48. https://agronomy.emu.ee/vol10Spec1/p10s105.pdf
[14] Wells, C. (2001, August ). Total energy indicators of agricultural sustainability: dairy farming case study (1171-4662). M. o. A. a. F. MAF Policy. https://citeseerx.ist. psu.edu/viewdoc/download?doi=10.1.1.15.692&rep=rep1&type=pdf
[15] Sainz, R. D. (2003). Framework for calculating fossil fuel use in livestock systems. T. F. a. A. O. o. t. U. N. (FAO). https://www.fao.org/documents/pub_dett.asp?lang=ar& pub_id=154286
[16] Coley, D. A., Goodliffe, E., & Macdiarmid, J. (1998). The embodied energy of food: the role of diet. Energy policy, 26(6), 455-460. https://abdn.pure.elsevier.com/en/ publications/the-embodied-energy-of-food-the-role-of-diet
[17] Dyer, J., & Desjardins, R. (2003). Simulated Farm Fieldwork, Energy Consumption and Related Greenhouse Gas Emissions in Canada. Biosystems Engineering, 85(4), 503-513. https://doi.org/10.1016/S1537-5110(03)00072-2
[18] Liang, S., Xu, M., & Zhang, T. (2013). Life cycle assessment of biodiesel production in China. Bioresource Technology 129, 72-77. https://doi.org/10.1016/j.biortech.2012.11.037
[19] Uzmay, A., Koyubenbe, N., & Armagan, G. (2009). Measurement of Efficiency Using Data Envelopment Analysis (DEA) and Social Factors Affecting the Technical Efficiency in Dairy Cattle Farms within the Province of Izmir, Turkey. Journal of Animal and Veterinary Advances. 8(6), 1110-1115. http://www.medwelljournals. com/abstract/?doi=javaa.2009.1110.1115
[20] Soltan Ali, H., Naskhah, A., Rouhani, A., & Ki Dashti, M. (2014, March 13). Emission Analysis of Consumption Inputs in a Dairy Cattle Breeding Unit The first national conference on engineering and management of agriculture, environment and sustainable natural resources, Permanent Conference Secretariat, Hamedan, Iran.  https://civilica.com/doc/253459
[21] Hasani, A., Hir, M., & Farhang, S. (2013). Measuring Iranian provinces efficiency in meaty poultry production by use of Data Envelopment Analysis. International Research Journal of Applied and Basic Sciences, 4(11), 3338-3346. https://www. semanticscholar.org/paper/Measuring-Iranian-provinces-efficiency-in-meaty-by-H asani-Hir/161fde4d8d2c850fdbc6c1ab0b84a070f41df043
[22] Sefeedpari, P., Ghahderijani, M., & Pishgar-Komleh, S. (2013). Assessment the effect of wheat farm sizes on energy consumption and CO2 emission. Journal of Renewable and Sustainable Energy, 5(2), 023131-023115. https://doi.org/10.1063/1.4800207
Karafan Quarterly Scientific Journal
Volume 17, Issue 2 - Serial Number 48
Agriculture
September 2020
Pages 13-21

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History

  • Receive Date: 26 April 2020
  • Revise Date: 23 August 2020
  • Accept Date: 12 September 2020

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