Modeling greenhouse gas emissions from livestock farming in Poland with the use of stepwise multiple regression

• Autorzy: Kolasa-Więcek A.

Warianty tytułu

PL

Modelowanie emisji gazów cieplarnianych uwalnianych z chowu zwierząt gospodarskich w Polsce z wykorzystaniem regresji krokowej wielorakiej

• Języki publikacji: EN

Abstrakty

EN

Primarily methane (CH4) and nitrous oxide (N2O) are greenhouse gases emitted by agriculture. It is estimated that 18% of global greenhouse gas emissions originates from livestock farming. This paper presents the results of the regression modeling of methane and nitrous oxide from livestock farming in Poland. The study was conducted for the emissions released from animal enteric fermentation (CH4) and manure management (CH4 and N2O). Modeling stepwise allowed a precise determination of the share of livestock population in the emissions. And so, in the case of CH4 emissions from enteric fermentation Beta coefficients obtained values: for cows - 0.667 and 0.339 for rest of cattle. Modeling CH4 emissions from manure management pointed to participation of the following variables, in order of importance: pigs population (Beta coefficient equal to 0.986), goats (-0.61), poultry chicken (0.421) and sheep population (0.312). In the case of N2O emissions released from manure management a high rate has been recorded for cows population (0.812), and significantly lower for pigs (0.227). In each of considered cases a high fitting of the model to the data has been obtained.

PL

Gazy cieplarniane emitowane przez rolnictwo to przede wszystkim metan (CH4) i podtlenek azotu (N2O). Szacuje się, iż 18% światowej emisji gazów cieplarnianych pochodzi z chowu zwierząt gospodarskich. W artykule zaprezentowano wyniki modelowania regresyjnego w emisji metanu i podtlenku azotu z chowu zwierząt gospodarskich w Polsce. Badania przeprowadzono dla emisji uwalnianych z fermentacji jelitowej zwierząt (CH4) oraz zarządzania obornikiem (CH4 i N2O). Modelowanie krokowe wsteczne umożliwiło dokładne określenie wielkości udziału pogłowia zwierząt w emisjach. I tak w przypadku emisji CH4 z fermentacji jelitowej otrzymano współczynniki Beta o wartościach: dla krów - 0,667 oraz pozostałego bydła 0,339. Modelowanie emisji CH4 z zarządzania obornikiem wskazało na udział w kolejności znaczenia następujących zmiennych: pogłowia trzody chlewnej (współczynnik Beta równy 0,986), kóz (-0,61), drobiu kurzego (0,421) oraz owiec (0,312). W przypadku emisji N2O uwalnianych z zarządzania obornikiem wysoki współczynnik odnotowano dla zmiennej pogłowie krów (0,812) oraz znaczniej niższy dla trzody chlewnej (0,227). W każdym z rozpatrywanych przypadków uzyskano wysokie dopasowanie modelu do danych.

Słowa kluczowe

EN

Multiple Regression; backward stepwise regression; modeling; methane; nitrous oxide; livestock

PL

regresja wieloraka; regresja krokowa wsteczna; modelowanie; metan; podtlenek azotu; zwierzęta gospodarskie

• Wydawca: Sieć Badawcza Łukasiewicz - Poznański Instytut Technologiczny
• Czasopismo: Journal of Research and Applications in Agricultural Engineering
• Rocznik: 2013
• Tom: Vol. 58, nr 1
• Strony: 78--85
• Opis fizyczny: BIbliogr. 27 poz., tab., wykr.

Twórcy

autor

Kolasa-Więcek A.

• Opole University of Technology, Department of Economics and Regional Research, Faculty of Economy and Management Waryńskiego 4, 45-047 Opole

Bibliografia

• [1] Amon B., Amon T., Boxberger J., Alt Ch.: Emissions of NH3, N2O and CH4 from dairy cows housed in a farm yard manure tying stall (housing, manure storage, manure spreading). Nutrient Cycling in Agroecosystems, 2001, 60, 103–113.
• [2] Asman W.A.H., Klimont Z., Winiwarter W.: A simplified model of nitrogen flows from manure management. Interim Report IR-11-030, IIASA, Laxenburg, 2011.
• [3] Bebkiewicz K., Cieślińska J., Dębski B., Jędrysiak P., Kanafa M., Kargulewicz I., Olecka A., Olendrzyński K., Rutkowski J., Sędziwa M., Skośkiewicz J., Sowińska K., Żaczek M.: National Inventory Report 2012, Stocktaking of greenhouse gases for the years 1988-2010, KOBiZE, Warszawa, 2012 [in polish].
• [4] van Eekert M.H.A., van Dooren H.J., Lexmond M., Zeeman G.: Wastewater and Manure, in: Methane and Climate Change. Ed. by: Dave Reay, Pete Smith, André van Amstel, Earthscan, 2010.
• [5] Food and Agricultural Organization: http://faostat.fao.org/site/567/DesktopDefault.aspx?PageID=567#ancor, [Accessed: 25.11.2012].
• [6] Gibbons J. M., Ramsden S. J., Blake A.: Modelling uncertainty in greenhouse gas emissions from UK agriculture at the farm level. Agriculture, Ecosystems and Environment, 2007, 112, 3, 240-251.
• [7] Giltrap D. L., Li Ch., Saggar S.: DNDC: A process-based model of greenhouse gas fluxes from agricultural soils. Agriculture, Ecosystems and Environment, 2010, 136, 292–300.
• [8] Greenhouse Gas Mitigation Potential in U.S. Forestry and Agriculture, United States Environmental Protection Agency Office of Atmospheric Programs, Washington, 2005.
• [9] IPCC: Climate change 2007: impacts, adaptation and vulnerability. In: Parry, M., Canziani, O., Palutikof, J., Van der Linden, P., Hanson, C. (Eds.), Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USA, 2007.
• [10] Jugowar J.L.: Methods for the analysis of the emission and spread of harmful gases from livestock buildings for the example of ammonia, Dissertations habilitation No. 5, Agricultural Engineering, Warszawa, 2001, [in polish].
• [11] Jun P., Gibbs M., Gaffney K.: Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories, CH4 and N2O Emissions from Livestock Manure, 2002, 321-338.
• [12] Miatkowski Z., Turbiak J., Burczyk P., Myczko A., Karłowski J.: Forecasts of change of activity in the agricultural sector, including information necessary to calculate an estimate of magnitude of the greenhouse gases emissions. Institute of Technology and Life Sciences in Falenty, 2010, [in polish].
• [13] Myczko A., Karłowski J., Szulc R.: Detailed Investigations of Methane and Dinitrogen Oxide Emissions from Enteric Fermantation and from Animal Excreta, in: Elimination of Agricultural risks to health and Environmental. Ed. by A. Myczko, Scienfic Network Agrorisks, IBMER Poznań, 2003, 9-126.
• [14] Niżewski P., Dach J., Boniecki P.: Artificial neural networks for model ling ammonia emission from field applied slurry manure, Agricultural Engineering, 2007, 2, 90, 235-242, [in polish].
• [15] OECD: Environmental Indicators for Agriculture, Methods and Results, Agriculture and Food, Volume 3, OECD 2001.
• [16] Pietrzak S., Sapek A., Oenema O.: Assessment of the emission of nitrous oxide (N2O) emissions from agricultural sources in Poland. Falenty, IMUZ. Educational Papers, 2002, 8, 23–36, [in polish].
• [17] Rosegrant M. W., Ewing M., Yohe G., Burton I., Huq S., Valmonte-Santos R.: Climate Change and Agriculture, Threats and Opportunities, Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ) GmbH Climate Protection Programme for Developing Countries, Eschborn, 2008.
• [18] Roszkowski A.: Livestock production technologies and greenhouse gas emissions. Problems of Agricultural Engineering, 2011, 2, 83-97, [in polish].
• [19] Salomon E., Rodhe L.: Losses of N2O, CH4 and NH3 from a grass sward used for overwintering beef heifers. Animal Feed Science and Technology, 2011, 166– 167, 147– 154.
• [20] Sidiropoulos Ch., Tsilingiridis G.: Trends of Livestockrelated NH3, CH4, N2O and PM Emissions in Greece. Water, Air and Soil Pollutio, 2009, 199:277–289.
• [21] Steinfeld H., Gerber P., Wassenaar T., Castel V., Rosales M., de Haan C.: Livestock’s long shadow - Environmental issues and options. Food and Agriculture Organization of the United Nations, Rome, 2006.
• [22] Stanisz A.: Approachable course statistics using STATISTICA PL on the examples of medicine. Volume 2 Linear and non-linear models, StatSoft Polska, Kraków, 2007, [in polish].
• [23] US EPA: Global Mitigation of Non-CO2 Greenhouse Gas, United States Enironmental Protection Agency, Washington DC, 2006.
• [24] United Nations Framework Convention on Climate Change: http://unfccc.int/di/DetailedByGas/Event.do?event=go, [Accessed: 25.11.2012].
• [25] Land use, crop area and livestock in 2011. Statistical information and studies, Central Statistical Office, Warszawa, 2011, [in polish].
• [26] Verburg R., Woltjer G., Tabeau A., Eickhout B., Stehfest E.: Agricultural trade liberalisation and greenhouse gas emissions, A simulation study using the GTAP-IMAGE modeling Framework, The Hague, LEI, Report 3.08.02; 2008.
• [27] Yamaji K., Ohara T., Akimoto H.: Regional-specific emission inventory for NH3, N2O, and CH4 via animal farming in South, Southeast, and East Asia, Atmospheric Environment, 2004, 38, 7111–7121.