DOI: 10.3303/CET23107120 Paper Received: 25 August 2023; Revised: 07 October 2023; Accepted: 05 December 2023 Please cite this article as: Sondakh D.S.I., Tulungen F.R., Kampilong J.K., Rumondor F.S.J., Kawuwung Y.S., 2023, Greenhouse Gas Profiling to Increase Agricultural Mitigation Program Effectiveness in Indonesia, Chemical Engineering Transactions, 107, 715-720 DOI:10.3303/CET23107120 CHEMICAL ENGINEERING TRANSACTIONS VOL. 107, 2023 A publication of The Italian Association of Chemical Engineering Online at www.cetjournal.it Guest Editors: Petar S. Varbanov, Bohong Wang, Petro Kapustenko Copyright © 2023, AIDIC Servizi S.r.l. ISBN 979-12-81206-07-6; ISSN 2283-9216 Greenhouse Gas Profiling to Increase Agricultural Mitigation Program Effectiveness in Indonesia Daniel S. I. Sondakh*, Franky R. Tulungen, Jon K. Kampilong, Fadly S. J. Rumondor, Yolla S. Kawuwung Universitas Kristen Indonesia Tomohon, Indonesia dsisondakh@gmail.com This study aims to provide an inventory of greenhouse gas emissions in the agricultural sector, map the distribution of greenhouse gas emissions, and formulate effective mitigation strategies in Minahasa District. Primary data on rice field types, land processing systems, and fertilizer doses were obtained from the respondents. The method is the interview, and the instrument is the questionnaire. Secondary data is in the form of planting area and emission factor data. Data processing uses the Tier-1 method to obtain the amount of CO2, CH4, and N2O emissions. Spatial mapping of greenhouse gas emissions is done with the help of ArcMap. After that, the greenhouse gas mitigation strategy was formulated. Total agricultural greenhouse gas emissions: 3,578,093.27 t CO2-eq/y, consists of emissions CH4: 71,711.87 t CO2-eq/y; CO2 Fertilizer: 1,828,235.40 t/y; N20 Land Managed: 1,665,299.66 t CO2-eq/y; and emission N2O Indirect: 12,846.33 t CO2-eq/y. The largest gas emissions are CO2 (51.10 %) and N2O Land Managed (46.54 %). The largest GHG-contributing is West Langowan District (285,165.25 t CO2-eq/y). Various adaptation efforts are to adjust planting time and patterns and reduce the use of inorganic fertilizers. In contrast, mitigation efforts are implementing organic farming, regulating intermittent irrigation systems (dry and wet), using low-emission rice varieties, and utilizing soil improvement materials such as biochar. 1. Introduction Greenhouse gas is a term used to describe the Earth's condition with a greenhouse effect. Global warming is a form of ecosystem imbalance on Earth due to the process of increasing the average temperature of the atmosphere, sea, and land on Earth so that there is a phenomenon of global average temperature on the surface of the Earth which has soared 0.74 ± 0.18 °C (1.33 ± 0.32 °F) in the last hundred years (Abbass et al., 2022). Today, climate change is one of humanity's most serious global problems. Climate change occurs due to human activities constantly affecting atmospheric composition and land use. The use of fossil fuels (Lee et al., 2021), deforestation (Erb et al., 2018), decay by microbes, waste, burning of plant litter, soil organic matter, and uncontrolled land conversion (Akram & Ali, 2021), Decomposition of organic matter that occurs in rice cultivation systems in wet (flooded) rice fields also contributes to the increase in CH4 and N2O production (da Cruz Corrêa et al., 2021), and natural factors such as volcanic eruptions and variations in solar radiation (Li et al., 2020). Although CH4 and N2O are emitted in smaller amounts than CO2, they can potentially result in 21 and 310 times greater global warming, respectively (Paul et al., 2022). GHG production from the agricultural sector is less than from the energy sector. Still, the GHGs it releases have tremendous potential, so they need to be managed and even reduced. Minahasa Regency, North Sulawesi Province, Indonesia, is one of the largest suppliers of agricultural production. With a planting area of around 44.2 thousand hectares, it has supplied its superior products in the form of rice, corn, tomatoes, and cloves throughout North Sulawesi Province (BPS-Statistics of Minahasa Regency, 2023). It even became one of the suppliers of cloves for the national cigarette industry. Anthropogenic activities in the agricultural sector produce a large number of significant greenhouse gases (GHG), namely carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), which are gases whose concentrations are increasing globally (Charkovska, 2019). This sector accounts for almost 14 % of global anthropogenic GHG emissions (Balafoutis et al., 2017;). Although many GHG emission studies have been 715 conducted in various places, there is still a gap in the availability of comprehensive academic information on agricultural GHG emissions in Minahasa District, where this study is ongoing. Based on literature searches, only two studies were found on this, and they were limited to CH4 gas from rice plants. Those are conducted by (Mambu, 2012) and (Langi, 2007). This gap has implications for the difficulty of academic information for policymaking related to GHG mitigation efforts. Determining agricultural GHG mitigation requires spatial analysis in mapping the distribution of CH4, CO2, and N2O by region to determine the type and origin of emission sources. Therefore, this research must be carried out to bridge or fill the existing gaps. This study aims to estimate GHG emissions in the Agricultural sector, map the distribution of GHG emissions, and formulate practical mitigation efforts to reduce emissions in Minahasa District, Indonesia. 2. Method and Material 2.1 Research Design This study uses a mixed research method, combining quantitative and qualitative methods in analytical descriptive studies. It then continues spatial analysis based on GIS (Geographic Information System) to map the distribution of GHG emissions in all districts in Minahasa Regency. The respondents were farmers and agricultural extension workers spread across 25 districts in Minahasa Regency. Primary data acquisition uses interview and questionnaire methods as instruments. The criteria for respondents are those who manage the largest land area (the five largest). The data collected is in the form of data on the type of paddy field, water regime, type and dose of fertilizer, planting frequency, and harvest frequency. Secondary data in the form of agricultural activities are land area data and Emission Factor data. Data processing uses the Tier method (from IPCC 2006 and 2019 Refinement to 2006) to obtain GHG emissions (IPCC, 2006)(IPCC, 2006). After that, they mapped the distribution of GHG emissions using ArcMap, a GIS-based application, to determine how big the distribution of greenhouse gas emissions was in each sub-district in Minahasa Regency. Furthermore, GHG inventory and GHG mitigation formulation involved respondents through FGD methods and interviews. 2.2 GHG Emission Calculation The GHG calculation method is based on IPCC guidelines, namely the Tier-1 method, based on global or regional emissions/removals factor defaults. The equation is: 1. CH4 emissions of paddy fields: calculated using the equation (1). −=∑ 6 4Emission of . . .10RiceCH Ef T A (1) Where: Emission of CH4Rice = CH4 emissions manage rice fields (Gg CH4/y); Ef = CH4 emission factor of paddy fields = 1.61 kg CH4/ha/d (MEFRI = Ministry of Environment and Forestry Republic of Indonesia, 2019); A = Area of rice fields (Ha); T = Rice planting period. 2. CO2 Emissions from Fertilizer Use: is calculated using the equation (2). =Rice2Emission of .Fertilizer FertilizerCO M EF (2) Where: Emission CO2 = C emissions fertilizer use (t CO2/y); EFfertilizer = Fertilizer emission factor. EF value of urea fertilizer = 0.20 t C/y (IPCC, 2006); Mfertilizer = The amount of fertilizer used (t/y). This value is obtained from the planting area multiplied by the recommended dose. 3. Direct N2O emissions: calculated using the equation (3). ( )[ ] ( )[ ]= + + +Direct 1 12Emission of -N . .SN on SN on FRN O F F Ef F F Ef (3) Where: Emission of N2ODirect = N2O directly land management (kg N2O-N/y); FSN = Sum of synthetic N fertilizer applied (kg N/y). The N in Urea/ZA/NPK is 46 %, 21 %, and 15 % (MEFRI, 2019); Fon = Sum of compost, manure, and other organic N is applied (kg N/y). The N in manure, compost, and crop residue is each 16 %, 0.5 %, and 0.5 % (MEFRI, 2019); Ef1 = N2O emission factor of N inputs for dryland (kg N2O-N (kg N input) is default 0.010 (MEFRI, 2019); Ef1FR = Emission factors N2O dari N input on irrigated rice fields (kg N2O-N (kg N input) is default 0.003 (MEFRI, 2019). 4. Indirect N2O emissions: calculated using the equation (4). ( ) (( ) )= + + + × ×   42Emission of - SN Gasf ON PRP GasmN O F Frac F Indirect F Frac EF (4) Where: Emission of N2O- = Indirect N2O land management (kg N2O-N/y); FSN =Sum of synthetic fertilizer N applied (kg N/y). The N content in Urea/ZA/NPK is 46 %, 21 %, and 15 % (MEFRI, 2019); FON =Sum of compost, livestock excretions, and other organic N is applied (kg N/y). The N content in manure, compost, and crop residue is respectively 16 %, 0.5 %, and 0.5 % (MEFRI, 2019); FPRP = Sum of urine and feces N (kg N/y); FracGasf = synthetic N fertilizer fractions that volatilize as NH3 and NOX is default 0,011 (MEFRI, 2019); FracGasm = organic fertilizer fraction N (FON) and livestock manure deposited by livestock (FPRP) which 716 is volatilized as NH3 and NOX (kg N volatilized per kg N given or deposited), is default 0.021 (MEFRI, 2019); EF4 = N2O emission factor from N deposits on the water surface and soil [kg N–N2O per (kg NH3–N + NOX– N volatilized)], is default 0.01 (MEFRI, 2019). An emission unit is a unit of gas type (t CH4, N2O, CO2/y) converted into CO2-equivalent using global warming potential (GWP) values. 3. Results and Discussion 3.1 Research Location This research is conducted in Minahasa Regency, North Sulawesi Province, Indonesia (See Figure1), with an area of 121,043.31 ha and 25 districts. The population of Minahasa Regency is 350,317 people, consisting of 178,730 men and 171,587 women. The population growth rate in 2011-2022 was 0.47%. The rice harvest area in 2021 reached around 44.18 thousand ha, a decrease compared to 2020, which was 61.83 thousand ha. Horticultural crops and tomato plants are the flagship of Minahasa Regency. As for plantation crops in 2022, they are cloves. The planting area of clove plants is 17,044.63 ha (Central Bureau of Statistics Minahasa Regency, 2023). 3.2 Emission Calculation Results of CH4, CO2 and N2O GHG emissions in the agricultural sector come from emissions: (1) methane (CH4) rice cultivation, (2) carbon dioxide (CO2) urea fertilizer use, (3) soil nitrous oxide (N2O), including indirect N2O emissions from adding N to the soil due to evaporation/precipitation and leaching. Calculating the emission burden of the agricultural sector requires secondary data on the area harvested per type of land and the type of fertilizer in rice cultivation, as described in Table 1. Table 1: Data on Agricultural Land Area and Fertilizer application in Minahasa Regency Districts Agriland Area (Ha) Fertilizer Paddy Dry land Corn Horti culture Plntation Land area UREA (kg) NPK (kg) Eris 97.4 100 1,000 744 1,795.0 1,196 197,299 306,465 Kakas 397.9 1,000 1,500 737 1,980.0 2,599 590,400 327,810 West Kakas 1,200.7 600 2,500 635 1,446.0 1,015 209,399 310,759 Kawangkoan 360.6 100 1,000 410 398.6 1,287 319,548 339,532 West Kawangkoan 112.7 100 900 64 766.0 1,857 455,750 478,250 North Kawangkoan 43.1 100 800 80 517.5 573 164,200 191,978 Kombi 0.0 3,600 1,100 182 7,257.3 2,341 587,250 567,045 West Langowan 357.5 50 1,550 81 63.8 5,124 736,070 1,166,025 South Langowan 141.6 100 650 30 1,676.0 1,321 237,740 170,567 East Langowan 646.8 50 110 165 97.5 1,993 526,702 390,772 North Langowan 206.2 50 100 795 10.8 3,619 560,667 794,462 East Lembean 0.0 2,500 1,500 650 5,515.5 680 170,048 174,662 Mandolang 37.5 100 500 281 2,239.0 365 91,419 96,856 Pineleng 3.6 100 500 619 2,872.0 68 17,024 19,238 Remboken 694.9 100 900 211 143.8 1,877 435,169 621,079 Sonder 205.2 300 1,250 209 2,847.0 2,416 597,400 630,235 East Tombariri 29.4 2,000 2,000 487 3,052.0 1,259 306,750 269,474 Tombulu 19.0 1,000 1,750 470 4,335.3 473 118,375 142,050 Tompaso 749.1 50 750 605 127.8 3,001 442,165 659,457 West Tompaso 134.8 50 750 750 46.8 3,970 703,950 785,568 Tombariri 23.0 2,000 2,000 451 3,347.5 782 193,750 186,506 West Tondano 456.3 100 850 58 128.4 564 138,710 113,858 South Tondano 420.2 100 1,000 193 436.3 2,209 536,226 469,006 East Tondano 686.1 50 750 795 784.5 3,202 724,600 760,452 North Tondano 149.3 270 1,200 300 245.0 339 80,566 97,498 TOTAL 7,172.6 14,570 26,910 10,002 42,129 44,138 9,141,177 10,069,604 These GHG emissions are then calculated in each district based on the type of emissions and using data in (Table 1) and each emissions factor, and integrate into the equations (1) to (4), will result in the total emissions of the agricultural and plantation sector amounting to: 3,578,093.27 t CO2-eq/y. CH4 emissions contribute this 717 amount: 2.00 %, CO2: 51.10 %, and N2O: 46.54 % of total emissions. Based on result mapping (Figure2) dark green color showed that the highest GHG emissions were in the West Langowan District (285,165.25 t CO2- eq/y), followed by the East Tondano District (282,633.12 t CO2-eq/y), West Tompaso District (269,322.73 t CO2- eq/y) and Sonder District (230,396.37 t CO2-eq/y). The primary source of emissions is agricultural activities because these districts are rice granaries or rice production centers in North Sulawesi. In addition, the region is the largest producer of horticultural crops in the form of tomatoes, onions, and chilies. This high emission is caused by increased fertilizer use, not under the recommended dose. Total fertilizer use (see Table. 1) on all land types reached 736,070 kg/y (Urea), 1,166,025 kg/y (Phonska/NPK), and organic fertilizers 5,255,550 kg/y so that the highest emission contribution is generated from CO2 emissions (147,214.00 t/y) and emissions N2O (134,377.24 t CO2-eq/y). The high application of this fertilizer causes CO2 to be in excessive condition, which increases the greenhouse effect. Various factors have caused CO2 emissions to be high. Fertilization and water availability have a positive and significant relationship with CO2 emissions. Nitrogen fertilizers can lead to increased CO2 emissions from the soil because nitrogen fertilizers can stimulate microbial activity in the soil, increasing the Decomposition of organic matter and releasing CO2 (Kong et al., 2020). The interviews with farmers show that the time of application and fertilizer dose did not follow the recommended doses. Excessive application of fertilizers can cause nutrient imbalances in the soil, negatively impacting soil health and increasing CO2 emissions. In addition, most plants meet nitrogen requirements as inorganic nitrates from soil solutions. From the results of the calculation of N2O emissions, Land Managed produces 1,678,145.33 t CO2-eq/y or contributes 46.54 % to total agricultural emissions. Those are also due to the high and frequent application of urea fertilizer. Nitrogen fertilizer applications can undergo nitrification and denitrification processes to release N2O into the atmosphere. When large amounts of organic fertilizers with available nitrogen (N) and degradable carbon infiltrate the soil or settle on the surface, it will increase N2O (Hansen et al., 2019). Figure 2. GHG Emission Distribution Map in Minahasa Regency. 3.3 Agriculture GHG Emissions Profile The GHG inventory of Minahasa Regency (period 2005-2022) shows that the level of GHG emissions in 2022 is 3,578,093.27 t CO2-eq/y or an increase of 1,056,184.66 t CO2-eq/y compared to the level of emissions in 2005. Figure 3 shows fluctuating variations in agricultural GHG emissions over the five years from 2005 to 2022. For the first five years (2005-2010), there was an increase in GHG emissions of 39.03 %; period 2 (2010-2015) decreased by -17.39 %. A sharp rise occurred in 2015-2020, amounting to 83.88 %. Finally, in 2020-2022, there was another decrease in GHG emissions by -32.82 %. The variation in GHG emission figures is due to the influence of various factors such as the type of crops grown, the types of animals raised, waste management systems, land use, and many other factors. Changes in land use in Minahasa Regency, such as deforestation and conversion of natural ecosystems to agricultural land, can release excessive carbon dioxide (CO2), contributing to global warming. Soil moisture content plays an essential role in N2O and CH4 emissions. Excessive soil moisture can create anaerobic conditions, promote denitrification, and increase N2O emissions (Bianchi, 2021). Conversely, dry soil conditions can limit denitrification and reduce N2O emissions. In addition, soil type, soil conditions, temperature, rainfall, plant types, plant residues, sludge waste, N mineralization in soil organic matter through soil drainage/management, and land use changes in mineral soils also affect the rate of N2O emissions (Xu et al., 2020). At the same time, CH4 emissions are 71,711.87 t CO2-eq/y, relatively low or contribute 2.00 % of total Agricultural emissions. As a notice to the 2020-2022 period, CH4 emissions tend to decrease. As a notice to the 2020-2022 period, CH4 emissions tend to fall; on the other hand, CO2 and N2O emissions continue to rise. This phenomenon indicates that excessive use of urea fertilizer is occurring in 718 agriculture in Minahasa district. Meanwhile, rainfed rice cultivation, which experiences periods of drought during the growing season, can withstand the rate of CH4 emissions. Figure3. Agriculture GHG Emissions Profile (2005-2022) 3.4 Adaptation and Mitigation Efforts in Minahasa Regency Mitigation efforts in the agricultural sector are to implement organic farming, namely limiting the application of synthetic fertilizers, herbicides, pesticides, and fungicides contained therein, potentially reducing GHG emissions and the flow of nitrates and toxic chemicals. In addition, using cover crops, crop rotation, and compost in organic farming can play an essential role in maintaining optimal soil health, increasing carbon sequestration, and reducing GHG emissions. The rice varieties selection that produces lower emissions or varieties with good root oxidizing capacity can potentially mitigate CH4 emissions and utilize soil improvement materials such as biochar. Another mitigation effort is the management of rice field irrigation systems with semi- irrigation/intermittent irrigation inundation. In flooded conditions, CH4 gas is higher than in dry conditions. Intermittent irrigation is the most efficient irrigation system in reducing CH4 emissions and can reduce emissions by 41 % to 45 %, compared to continuous irrigation. This research still needs to be continued in future studies, especially to calculate the potential reduction in greenhouse gas emissions from several mitigation options based on proposals from all stakeholders. 4. Conclusions Total agricultural and plantation sector emissions are 3,578,093.27 t CO2-eq/y, which is contributed by emissions per type of gas: Emission CH4: 71,711.87 t CO2-eq/y; CO2 Fertilizer: 1,828,235.40 t/y; N2O Land Managed: 1,665,299.66 t CO2-eq/y; and N2O Indirect: 12,846.33 t CO2-eq/y. The most significant contributors in the agricultural sector are CO2 emissions (51.10 %) and land-managed N2O emissions (46.54 %) of total emissions. Adaptation and mitigation efforts that have been formulated need to be carried out simultaneously. This study still has the potential to be continued in future studies, explicitly calculating the potential reduction in greenhouse gas emissions from several mitigation options. Acknowledgments Thank you to the Minister of Education and Culture of the Republic of Indonesia, via the Director of Research, Technology, and Community Service, for funding this research through the PFR-Bima 2023. References Abbass, K. et al. (2022) ‘A review of the global climate change impacts, adaptation, and sustainable mitigation measures’, Environmental Science and Pollution Research, 29(28), pp. 42539–42559. doi:10.1007/s11356- 022-19718-6. Akram, V. and Ali, J. (2021) ‘Global disparities of greenhouse gas emissions in agriculture sector: panel club convergence analysis’, Environmental Science and Pollution Research [Preprint]. doi:10.1007/s11356-021- 14786-6. Arisandi, F.D. and Setyanto, P. (2019) ‘Rendah Emisi Gas Metana Heritability and Characteristics of Rice Plant’, Jurnal Produksi Tanaman, 6(6), pp. 1042–1047. Available at: http://protan.studentjournal.ub.ac.id/index.php/ protan/article/view/745. Balafoutis, A. et al. (2017) ‘Precision agriculture technologies positively contributing to ghg emissions mitigation, farm productivity and economics’, Sustainability (Switzerland), 9(8), pp. 1–28. doi:10.3390/su9081339. 719 Bianchi, A. (2021) ‘Review of Greenhouse Gas Emissions from Rewetted Agricultural Soils’, Wetlands, 41(8). doi:10.1007/s13157-021-01507-5. BPS-Statistics of Minahasa Regency (2023) Minahasa Regency in Figures, 2023, minahasakab.bps.go.id. Available at:https://minahasakab.bps.go.id/publication.html?Publikasi%5BtahunJudul%5D=2023&Publikasi% 5BkataKunci%5D=Minahasa+dalam+angka&Publikasi%5BcekJudul%5D=0&yt0=Tampilkan. Chai, R. et al. (2019) ‘Greenhouse gas emissions from synthetic nitrogen manufacture and fertilization for main upland crops in China’, Carbon Balance and Management, 14(1), p. 20. doi:10.1186/s13021-019-0133-9. Charkovska, N. (2019) ‘High-resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector’, Mitigation and Adaptation Strategies for Global Change, 24(6), pp. 881–905. doi:10.1007/s11027-017-9779-3. da Cruz Corrêa, D.C. et al. (2021) ‘Are ch4, co2, and n2 o emissions from soil affected by the sources and doses of n in warm-season pasture?’, Atmosphere, 12(6). doi:10.3390/atmos12060697. Erb, K.H. et al. (2018) ‘Unexpectedly large impact of forest management and grazing on global vegetation biomass’, Nature, 553(7686), pp. 73–76. doi:10.1038/nature25138. Hansen, S. et al. (2019) ‘Reviews and syntheses: Review of causes and sources of N2O emissions and NO3 leaching from organic arable crop rotations’, Biogeosciences, 16(14), pp. 2795–2819. Available at: https://bg.copernicus.org/articles/16/2795/2019/. IPCC (2006) ‘IPCC Guidelines for National Greenhouse Inventories’, Prepared by the National Greenhouse Gas Inventories Programme, p. 20. Available at: https://www.ipcc-nggip.iges.or.jp/support/Primer_2006GLs.pdf. Jacinthe, P.A. and Dick, W.A. (1997) ‘Soil management and nitrous oxide emissions from cultivated fields in southern Ohio’, Soil and Tillage Research, 41(3–4), pp. 221–235. doi:10.1016/S0167-1987(96)01094-X. Kong, D. et al. (2020) ‘Effect of nitrogen fertilizer on soil CO2 emission depends on crop rotation strategy’, Sustainability (Switzerland), 12(13). doi:10.3390/su12135271. Langi, Y.A.R. (2007) ‘Model Penduga Biomassa dan Karbon Pada Tegakan Hutan Rakyat Cempaka (Elmerrillia ovalis) dan Wasian (Elmerrrillia celebica) Di Kabupaten Minahasa - Sulawesi Utara’, Sekolah Pascasarjana Institut Pertanian Bogor, p. 10593. Available at: http://repository.ipb.ac.id/handle/123456789/10593. Lee, D.S. et al. (2021) ‘The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018’, Atmospheric Environment, 244(July 2020). doi:10.1016/j.atmosenv.2020.117834. Li, C. et al. (2020) ‘Impact of irrigation and fertilization regimes on greenhouse gas emissions from soil of mulching cultivated maize (Zea mays L.) field in the upper reaches of Yellow …’, Journal of Cleaner Production [Preprint]. Available at: https://www.sciencedirect.com/science/article/pii/S0959652620309203. Licite, I. and Lupikis, A. (2020) ‘Impact of land use practices on greenhouse gas emissions from agriculture land on organic soils’, Engineering for Rural Development, 19, pp. 1823–1830. doi:10.22616/ERDev.2020.19.TF492. Lister, B.C. and Garcia, A. (2018) ‘Climate-driven declines in arthropod abundance restructure a rainforest food web’, Proceedings of the National Academy of Sciences of the United States of America, 115(44), pp. E10397–E10406. doi:10.1073/pnas.1722477115. MEFRI (Ministry of Environment & Forest of the Republic of Indonesia) (2019) Report of Indonesia GHG Inventory and Monitoring, Reporting, Verification (MRV) - 2019, Kementrian Lingkungan Hidup dan Kehutanan RI. Jakarta. Available at: https://www.menlhk.go.id/. Paul, B.K. et al. (2022) ‘Crop-livestock integration provides opportunities to mitigate environmental trade-offs in transitioning smallholder agricultural systems of the Greater Mekong Subregion’, Agricultural Systems, 195, p. 103285. doi:10.1016/j.agsy.2021.103285. Rehman, A., Ozturk, I. and Zhang, D. (2019) ‘The causal connection between CO2 emissions and agricultural productivity in Pakistan: Empirical evidence from an autoregressive distributed lag bounds testing approach’, Applied Sciences (Switzerland), 9(8). doi:10.3390/app9081692. Styles, D. et al. (2018) ‘Climate mitigation by dairy intensification depends on intensive use of spared grassland’, Global change … [Preprint]. doi:10.1111/gcb.13868. Tahat, M.M. et al. (2020) ‘Soil health and sustainable agriculture’, Sustainability (Switzerland), 12(12), pp. 1– 26. doi:10.3390/SU12124859. Xu, X. et al. (2020) ‘The role of soil N2O emissions in agricultural green total factor productivity: An empirical study from China around 2006 when agricultural tax was abolished’, Agriculture (Switzerland), 10(5). doi:10.3390/agriculture10050150. Yahya, M.N. et al. (2021) ‘A study on the hydrolysis of urea contained in wastewater and continuous recovery of ammonia by an enzymatic membrane reactor’, Processes, 9(10). doi:10.3390/pr9101703. Yan, Q. et al. (2017) ‘Energy-related GHG emission in agriculture of the European countries: An application of the Generalized Divisia Index’, Journal of Cleaner Production, 164, pp. 686–694. doi: 10.1016/j.jclepro.2017.07.010. 720 265Sondakh-PAGATO..pdf Greenhouse Gas Profiling to Increase Agricultural Mitigation Program Effectiveness in Indonesia