Document Type : Research Article
Authors
1 Department of Management, Faculty of Economic and Business, Ahmad Dahlan Institute of Technology and Business, Indonesia.
2 Department of Information Technology, Faculty of Computer Science, Universitas Indonesia, Indonesia.
Abstract
The percentage of production and utilization of hydrocarbon resources from the livestock sector has raised concerns regarding the worldwide issue of global warming. A total of CH4 emissions from enteric fermentation and waste management has been estimated at 78.3 %. Meanwhile, N2O emissions are 75-80 % of total agricultural emissions. This raises questions about the extent of global warming due to increased CO2 resulting in changes in weather and global warming. This research aims to predict Green House Gas (GHG) emissions from manure management and present policy alternatives for Indonesian livestock development. Secondary data was taken from a related website (fao.org) with coverage throughout Indonesia from 1961 to 2021, containing 12,480 rows and 5 column features including item, Element, Year, Unit, and Value emission. LSTM and GRU are used to predict the trend of emission from manure management to provide alternative policies on greenhouse gas mitigation in Indonesia. The results showed that based on 15 types of livestock that emit GHG emissions, 3 types of livestock produce the highest emissions from 1961 to 2021: (a) cattle, (b) cattle and non-dairy, and (c) poultry. Significant reduction in the emission of carbon dioxide (CO2eq) in 2020 is indicated by reduced public consumption and hampered supply chains with large-scale social restrictions (covid-19 pandemic policy). Based on these results, fertilizer storage duration can be used as a policy to reduce CO2eq emissions, hence it is desired that fertilizer management techniques can be properly regulated. Mitigation can also be accomplished by utilizing livestock waste as biogas and upgrading animal feed additives with chitosan or potassium nitrate.
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- Ambazamkandi, P., Thyagarajan, G., Sambasivan, S., Davis, J.R., Sankaralingam, S., & Joseph, B.A. (2015). Shelter Design for Different Livestock from a Climate Change Perspective. Springer, (pp. 399-424). https://doi.org/10.1007/978-81-322-2265-1_23
- Anderson, T.R., Hawkins, E., & Jones, P.D. (2016). CO2, the greenhouse effect and global warming: from the pioneering work of Arrhenius and Callendar to today’s Earth System Models. Endeavour, 40(3), 178-187. https://doi.org/10.1016/j.endeavour.2016.07.002
- Broucek, J. (2014). Production of methane emissions from ruminant husbandry: A review. Journal of Environmental Protection, 05(15), 1482-1493. https://doi.org/10.4236/jep.2014.515141
- Chlingaryan, A., Sukkarieh, S., & Whelan, B. (2018). Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review. Computers and Electronics in Agriculture, 151(November 2017), 61-69. https://doi.org/10.1016/j.compag.2018.05.012
- Fang, G., Tian, L., Fu, M., Sun, M., Du, R., & Liu, M. (2016). Investigation of carbon tax pilot in YRD urban agglomerations-analysis and application of a novel ESER system with carbon tax constraints. Energy Procedia, 88(025), 290-296. https://doi.org/10.1016/j.egypro.2016.06.148
- FAOSTAT Agriculture Total Online Database. (2020). FAOSTAT Agriculture Total Online Database. Fao.Org. http://www.fao.org/faostat/en/#data/GT
- Hamrani, A., Akbarzadeh, A., & Madramootoo, C.A. (2020). Machine learning for predicting greenhouse gas emissions from agricultural soils. Science of the Total Environment, 741, 140338. https://doi.org/10.1016/j.scitotenv.2020.140338
- Harahap, R.P., Setiawana, D., Nahrowib, S., Suharti, S., Obitsud, T., & Jayanegara, A. (2020). Enteric methane emissions and rumen fermentation profile treated by dietary chitosan: A meta-analysis of in vitro experiments. Tropical Animal Science Journal, 43(3), 233-239. https://doi.org/10.5398/tasj.2020.43.3.233
- Herawati, T. (2012). Refleksi sosial dari mitigasi emisi gas rumah kaca pada sektor peternakan di Indonesia. Wartazoa, 22(1), 35-46. https://repository.pertanian.go.id/server/api/core/bitstreams/b45033a2-b954-4f14-b967-27827982475a/content
- Gitarskiy, M.L. (2019). The refinement to the 2006 ipcc guidelines for national greenhouse gas inventories. Fundamentalʹnaâ I Prikladnaâ Klimatologiâ, 2, 5-13. https://doi.org/10.21513/0207-2564-2019-2-05-13
- Mahardika, I.G., Suryani, N.N., Mariani, N.P., Suarna, I.W., Duarsa, M., & Mudita, I.M. (2011). Pemanfaatan limbah lidah buaya sebagai feed supplemet pakan sapi bali dalam upaya mengurangi emisi metan. Pastura : Jurnal Ilmu Tumbuhan Pakan Ternak, 1(2), 44-47. https://ojs.unud.ac.id/index.php/pastura/article/view/1596
- Jayanegara, A., Haryati, R.P., Nafisah, A., Suptijah, P., Ridla, M. & Laconi, E.B. (2020). Derivatization of chitin and chitosan from black soldier fly (hermetia illucens) and their use as feed additives: An in vitro Archives of Anesthesiology and Critical Care, 8(5), 472-477. http://dx.doi.org/10.17582/journal.aavs/2020/8.5.472.477
- Le Quéré, C., Jackson, R.B., Jones, M.W., Smith, A.J.P., Abernethy, S., Andrew, R.M., De-Gol, A.J., Willis, D.R., Shan, Y., Canadell, J.G., Friedlingstein, P., Creutzig, F., & Peters, G.P. (2020). Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement. Nature Climate Change, 10(7), 647-653. https://doi.org/10.1038/s41558-020-0797-x
- Limanseto, H. (2021, October). Kelola isu perubahan iklim, pemerintah manfaatkan strategi transformasi ekonomi melalui pembangunan hijau. Kementerian Koordinator Bidang Perekonomian. https://www.ekon.go.id/publikasi/detail/3386/kelola-isu-perubahan-iklim-pemerintah-manfaatkan-strategi-transformasi-ekonomi-melalui-pembangunan-hijau
- Masson Delmotte, V., Zhai, P., Pörtner, H.-O., Roberts, D., Skea, J., Shukla, P.R., Pirani, A., Moufouma-Okia, W., Péan, C., Pidcock, R., Connors, S., Matthews, J.B.R., Chen, Y., Zhou, X., Lonnoy, E., Maycock, T., & Tignor, M. (2018). Summary for Policymakers. https://www.ipcc.ch/sr15/chapter/spm/
- Miranti Ariani, M., & Ardiansyah, P.S. (2015). Inventarisasi emisi GRK lahan pertanian di kabupaten grobogan dan tanjung jabung timur dengan menggunakan metode IPCC 2006 dan modifikasinya. Jurnal Sumberdaya Lahan, 9(1), 15-2 https://www.neliti.com/id/publications/132900/inventarisasi-emisi-grk-lahan-pertanian-di-kabupaten-grobogan-dan-tanjung-jabung
- Missanjo, E., & Kadzuwa, H. (2021). Greenhouse gas emissions and mitigation measures within the forestry and other land use subsector in Malawi. International Journal of Forestry Research, 2021(i). https://doi.org/10.1155/2021/5561162
- Pachauri, R.K., & Leo Meyer, T.C.W.T. (2014). Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change [core writing team, R.K. Pachauri and L. Meyer (eds)], Intergovernmental panel on climate change (pp. 155), IPCC, Geneva, Switzerland,. https://www.ipcc.ch/report/ar5/syr/
- Peraturan Presiden Republik Indonesia No. 71 Tahun 2011 tentang Penyelenggaraan Inventarisasi Gas Rumah Kaca Nasional, (2011). https://peraturan.bpk.go.id/Home/Details/41187/perpres-no-71-tahun-2011.
- Peraturan Presiden Republik Indonesia No 61 Tahun 2011 tentang Rencana Aksi Nasional Penurunan Emisi Gas Rumah Kaca, (2011). https://peraturan.bpk.go.id/Home/Details/41199/perpres-no-61-tahun-2011
- Phuong T.B., Khang, D.N., & Preston, T.R. (2012). Effect of NPN source, level of added sulphur and source of cassava leaves on growth performance and methane emissions in cattle fed a basal diet of molasses. Livestock Research for Rural Development, 24(4). http://www.lrrd.org/lrrd24/4/phuong24070.htm
- Ratnawati, D. (2016). Carbon tax sebagai alternatif kebijakan untuk mengatasi eksternalitas negatif emisi karbon di indonesia. Indonesian Treasury Review Jurnal Perbendaharaan Keuangan Negara Dan Kebijakan Publik, 1(2), 53-67. https://doi.org/10.33105/itrev.v1i2.51
- Utaminingsih, W., & Hidayah, S. (2012). Mitigasi emisi gas rumah kaca melalui penerapan irigasi intermittent di lahan sawah beririgasi. Jurnal Irigasi, 7(2), 132. https://doi.org/10.31028/ji.v7.i2.132-141
- Van Houdt, G., Mosquera, C., & Nápoles, G. (2020). A review on the long short-term memory model. Artificial Intelligence Review, 53(8), 5929-5955. https://doi.org/10.1007/s10462-020-09838-1
- Whelan, B., Taylor, J., & Taylor, J.A.P. (2013). Precision agriculture for grain production systems. CSIRO. https://www.researchgate.net/publication/239731186_Precision_Agriculture_for_Grain_Production_Systems
- Widiawati, R.A.Y., Tiesnamurti, B., Hdayat, C., Nurhayati, I.S., Wahyono, T., Krisnan, R., Rofiq, M.N., Shiddique, M.I., Ramadhan, B.A., Krishna, N.H., Anggraeny, Y.N., Ginting, S.P., & Munawaroh, I.S. (2021c). Emisi gas rumah kaca dari peternakan di indonesia dengan TIER 2 IPCC. In Penerbit BRIN eBooks. https://doi.org/10.55981/brin.461
- World Meteorological Organization & Atmosphere Watch Global. (2017). Greenhouse gas. https://public.wmo.int/en/resources/library/wmo-greenhouse-gas-bulletin
- Zhao, G., Miao, Y., Wang, H., Su, M., Fan, M., Zhang, F., Jiang, R., Zhang, Z., Liu, C., Liu, P., & Ma, D. (2013). A preliminary precision rice management system for increasing both grain yield and nitrogen use efficiency. Field Crops Research, 154, 23-30. https://doi.org/10.1016/j.fcr.2013.07.019