Country-specific Emission Factors Research Articles

Assessing the Additional Benefits of Thailand’s Approaches to Reduce Motor Vehicle Emissions

Air pollutants and greenhouse gases (GHGs) represent major challenges in our era, contributing to climate change and global health issues. These problems arise from a variety of well-known sources, including motor vehicles. Almost all nations, Thailand included, have formulated and implemented policies to curb greenhouse gas (GHG) emissions in line with the requirements and commitments of the Paris Agreement. The evaluation of specific air pollutants and GHG emissions originating from road vehicles utilises the Thailand database, referencing the year 2019. Data intersections from 2019 to 2022 are grounded in actual data collected from relevant departments in Thailand, while projections for 2023–2030 are forecasted based on the baseline year. The secondary database used in the International Vehicle Emission model is adjusted according to real-world driving data to accurately reflect country-specific emission factors. Dynamic emission factors for specific air pollutants and GHGs are evaluated and integrated with the average Vehicle Kilometres Travelled (VKT) for each vehicle category. The Business-As-Usual (BAU) scenario is then examined, based on existing policies aimed at reducing air pollutants and GHG emissions in Thailand’s transport sector. These policies include strategies for the adoption of electric vehicles and the promotion of public transport to reduce VKT. Under the BAU scenario, the overall number of road vehicles in Thailand, including passenger cars, motorcycles, pickups, vans, trucks, and buses, is expected to increase by approximately 6.58% by 2030, leading to a rise in specific air pollutants and GHG emissions compared to the 2019 baseline. However, by adhering to Thailand’s strategies and transitioning to new electric passenger cars and buses, greenhouse gas emissions and specific air pollutants from the road transport sector will be significantly reduced.

Ṇitrogen footprint of Korean beef cattle farms: Scenarios toward more sustainable production

AbstractNitrogen (N) lost during beef cattle production accompanies various environmental risks and has become a rising concern among agricultural stakeholders. The objective of this study was to quantify the N footprint of producing Hanwoo beef cattle, which is a Korean indigenous breed of cattle, in Korea at the farm gate through a life cycle assessment approach. Field surveys were conducted on 106 farms across 9 provinces to identify regional distinctions in farming systems and evaluate total N losses from beef production. N losses were calculated using emission factors from the refined IPCC guidelines, which were then expressed as N footprint (g N/kg of live body weight (LBW)). Uncertainty and sensitivity analyses were deployed to evaluate the precision of the results and identify factors that contributed to the output. The N footprint averaged 132.7(± 61.8) g N/kg LBW and varied between provinces according to animal categories, manure management systems, land use and fertilizer application rates. Volatilization was the highest contributing factor, followed by leaching and denitrification, each representing 68.5, 21.4, and 10.1 percent of the N footprint, respectively. The uncertainty of the result was found to be 46.6 percent and was highly associated with emission factor uncertainties. We devised five mitigation scenarios that are cost effective and do not penalize productivity and evaluated their capacity for reducing N footprint: (i) dietary modifications to decrease animal N excretion rate; (ii) microorganism additives to reduce volatilization from housing; (iii) manure storages recycling manure within the farm to replace synthetic fertilizers; (iv) distributing biochar to the field after fertilizer application to curtail losses from crop production; (v) combination of i, ii, iii, and iv. Combining these scenarios demonstrated the potential to reduce 12.1 percent of the total N footprint. The extents of mitigation scenarios varied across provinces (ranging from 5.2 to 21.7 percent) and were shown to be contingent on feeding practices and type of crop cultivated. Overall, our study provides a national metric that can be utilized to communicate the environmental impacts of Korean beef production. The analyses indicate that more precise results could be achieved with future endeavors towards developing country-specific emission factors. The mitigation potentials of the presented scenarios propose possibilities for feasible and sustainable beef production in Korea.

Study on morphological composition of waste and the estimation of greenhouse gases from waste landfilling from the Republic of Moldova

The paper summarizes the research results on the development country country-specific emissions factors for the Greenhouse Gas Inventory (GHGI) for Source Category “5A Solid Waste Disposal on Land”, namely the degradable organic carbon (DOC), fraction of degradable organic carbon which decomposes (DOCf) and fraction of methane. The factors are determined based on the results of the survey on the composition of municipal solid waste, which was investigated during one year in the Republic of Moldova: from spring 2023 to 2024. The obtained morphological composition and results refer to three seasons: spring, summer and autumn and offer the opportunity to observe the variations among the seasons. After finalizing the survey on morphological composition, the final results will be used for estimation of country specific emission factors, which will allow to estimate accurately the emissions of methane from landfilling of waste in the Republic of Moldova, necessary for the development of a policy framework and tracking the progress in achievement of NDC. It will also improve the Intergovernmental Panel for Climate Change (IPCC) methodologies and Emission Factors for assessing the GHG emissions originating from the waste sector.

Emission inventory of inorganic trace gases from solid residential fuels over the National Capital Territory of India.

In developing nations, solid residential fuels are the major sources of primary energy for various domestic activities. To date, the emission inventory of inorganic trace gases over National Capital Territory (NCT) was prepared using either default or country-specific emission factors. In this paper, we report (for the first time) the spatial variation of emission factors (EFs) of inorganic trace gases (SO2, NO, NO2, CO, CO2, and CH4) from the residential fuels used in slums and rural areas of NCT determined using dilution chamber in the laboratory. 147 residential fuel samples, including fuelwood, dung cake, crop residues, coal, etc., were collected at 149 NCT locations out of 675 slum clusters and 146 rural villages. The range of EF(s) of SO2 (0.02 ± 0.01 to 0.04 ± 0.01gkg-1), CH4 (0.10 to 0.34gkg-1), NO2 (0.01 to 0.02gkg-1) is lower than the CO (3.55 ± 1.72 to 6.07 ± 1.53gkg-1) and CO2 (0 to 129.45 ± 46.94gkg-1). The north and north west districts of NCT are emission hotspots for CH4, NO, and NO2 emissions, whereas, the southern and northern areas of NCT are for CO2. These citywide emission inventories (0.05° × 0.05°) of inorganic trace gases are prepared using laboratory-determined EFs and available consumption data determined by recent survey information. Among solid residential fuels, fuel wood, and dung cake are two major contributors to inorganic trace gases in NCT.

PSXI-28 Nitrogen Footprint Assessment of Korean Native Beef Cattle Farms: Uncertainty Analysis and Mitigation Scenarios

Abstract Nitrogen (N) lost during beef cattle production accompanies various environmental impacts and has become an increasing concern among agricultural stakeholders. The objective of this study was to quantify the N footprint (NF) of Hanwoo beef cattle production in Korea at the farm gate through a life cycle assessment methodology. Field surveys were conducted on 106 farms across nine provinces to evaluate the NF of Hanwoo beef farms. N losses were calculated using emission factors using the refined Intergovernmental Panel on Climate Change (IPCC) guideline and expressed as NF [g N lost/kg of live body weight (LBW)]. Uncertainty and sensitivity analyses were deployed to evaluate the precision of the results and to quantify the variability of the input data. The NF was averaged 132.8 (±61.9) g N/kg LBW. Volatilization was the greatest contributing factor, followed by leaching and denitrification, each representing 68.4, 21.4, and 10.1 percent of the NF, respectively. The uncertainty of the output data was found to be 46.6 percent and was highly associated with emission factors uncertainties. We simulated four feasible mitigation scenarios that are cost effective and do not penalize productivity, and evaluated their capacity for reducing NF of meat: dietary modifications to decrease animal N excretion rates by adjusting the CP and rumen undegradable protein content for steers and fattening cows (A), microorganism additives to reduce volatilization from housing and manure storages through processing excess ammonium to synthesize microbial protein (B), using manure as land fertilizer instead of synthetic fertilizers to decrease denitrification from rice cultivation, and leaching and volatilization from all field types(C), and distributing straw-derived biochar (10 to 20 ton/ha) to the field after fertilizer application to reduce losses from crop production (D).Combining these scenarios demonstrated the potential to reduce NF by 12.3 percent. Overall, our study provides a national metric that can be used to communicate the N uses impact of Korean beef production. The analyses indicate that more precise results could be achieved with future endeavors toward developing country-specific emission factors. Integrating all four scenarios was shown to be the most effective approach to reducing the NF of beef production.

Allocation of carbon dioxide emissions to the by-products of combined heat and power plants: A methodological guidance

Cogeneration has higher efficiency than separate heat and power generation. Since both are generated in a single process, it is necessary to allocate the emissions to by-products for comparing their environmental performance. Numerous methods exist resulting in very different allocations. There is no consensus regarding the method choice. The main objective of this article is the development and implementation of an evaluation scheme allowing the choice of an appropriate method for specific applications. This scheme consists of nine criteria in the categories “Applicability”, “Environmental relevance”, and “Systematic approach” allowing a rating. The Finnish method performs best for a standard use case resulting in emission factors of 322 g CO2 / kWhel and 192 g CO2 / kWhth. Both are associated with less emissions per unit then the electricity and district heating mix of Germany in 2020 that were 375 g CO2 / kWhel and 270 g CO2 / kWhth. Therefore, cogeneration electricity and heat could contribute to climate protection in the short- to mid-term. The implementation of two sensitivity analyses shows that the location and country-specific emission factors can have a great influence on the results and the contribution to climate protection. Depending on use case and individual importance of certain criteria the Energy, the Exergy or the Greenhouse Gas method can be preferable. Each scored with one point less than the Finnish method. In contrast to existing publications, this study supports decision-makers in transparently selecting an appropriate allocation method when assessing the products of cogeneration by considering different criteria.

Methane release from enteric fermentation and manure management of domestic water buffalo in Nepal

Methane (CH4) emission in livestock arises from enteric fermentation (EnF) and manure management (MM). This study develops the country-specific CH4 emission factors (EFs) in both EnF and MM for domestic water buffalo (Bubalus bubalis) and estimates total CH4 emission in Nepal using Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology. Seasonal field data were collected on morphological characteristics, feed characteristics, and manure management practices of the buffalo. The buffalo population was divided into five age groups, and at least 35 buffalo individuals were measured from each age group in the Hilly and Plain regions of Nepal in the winter and summer seasons. Buffalo adult male (BAM) had the highest body weight of 530 ± 53kg in the plain region and 514 ± 65kg in the Hill region. Similarly, the weight of buffalo calf (BC) was 91 ± 25kg in the plain region and 77 ± 26kg in the Hill region. For different age groups of buffalo, EnF EFs ranged from 34 ± 8 to 90 ± 10kg CH4 head-1year-1 and MM EFs ranged from 2.5 ± 0.5 to 7.5 ± 0.5kg CH4 head-1year-1. The estimated EnF and MM EFs of buffalo were not statistically different by region (p > 0 .05). The total CH4 flux from buffalo was 347.8 Gg year-1 in Nepal, contributing 322.2 Gg year-1 from EnF and 25.6 Gg year-1 from MM. The country-specific EFs are highly recommended for precise computing of the national emissions and carrying out mitigation action.

바이오중유 발전소의 Non-CO2 배출계수 개발 및 비교

This study studied a specific power plant that changed fuels from B-C oil to bio-fuel oil. Carbon dioxide emitted by bio-fuel oil combustion is not included in total greenhouse gas emissions due to the application of the carbon neutral concept and is to be reported separately. Therefore, total greenhouse gas emissions for bio-fuel oil are calculated based on non-CO₂ emissions. To reliably calculate emissions, it is necessary to develop a country-specific emission factor that reflects national characteristics.BR Currently, there is no country-specific emission factor for bio-fuel oil. This study identified and analyzed non-CO₂ emission factors for bio-fuel oil. In total, non-CO₂ emission factors of this study are observed 0.671 kgCH4/TJ and 0.171 kgN₂O/TJ.

Measurement of greenhouse gas emissions from a dairy cattle barn in Korea.

Korea is currently developing country-specific emission factors to support the 2050 zero-carbon campaign. Dairy cattle represent one of the largest livestock industries in Korea, and the industry is estimated to continue increasing because of an increase in milk demand. However, country-specific emission factors for dairy cattle are currently only available for calculating methane (CH4) emissions from enteric fermentation. Two experiments were conducted to evaluate CH4 and nitrous oxide (N2O) fluxes from sawdust-bedded barn in dairy cow and steer, as well as dairy cattle manure composting lots. The greenhouse gas (GHG) fluxes were quantified using the open-chamber method and gas chromatography. CH4 fluxes from steer, dairy cow, and manure compost were 27.88 ± 5.84, 36.12 ± 10.85, and 259.44 ± 61.78 µg/head/s, respectively. N2O fluxes from steer, dairy cow, and manure compost were 14.04 ± 1.27, 4.11 ± 1.57, and 3.97 ± 1.08 µg/head/s, respectively. The result of this study can be used to construct country-specific data for GHG emissions from manure management. Thus, the application of mitigation strategies can be prioritized based on the GHG profile and targeted source.

우리나라 산림지부문 입목바이오매스 탄소저장량의 불확도 평가

The Paris Agreement recommends its member parties to enhance transparency in Greenhouse Gas (GHG) inventory by sector. IPCC guidelines provide recommendations for reducing uncertainties of GHG emissions and removals for the accurate assessment. Thus, this study aimed to assess the uncertainties of estimated carbon stocks for living biomass in the forestry sector. Living biomass is an essential indicator for monitoring GHG removals in the LULUCF sector. This study made a comparative assessment of the uncertainty by applying error propagation methods (simple multiplication, addition and subtraction) and the Monte Carlo Simulation (MCS) suggested in the IPCC guidelines. The findings showed that the overall uncertainty for the simple multiplication in the error propagation was found to be as high as ±28.0% due to higher uncertainties of country-specific emission factors. In contrast, the overall uncertainty was as low as ±3.6% for the addition and subtraction considering the sensitiveness of activity data and emission factors as explanatory variables, while that for the MCS was at around ±6.0%. Despite the slightly higher uncertainty for MCS compared with addition and subtraction, it is reasonable to apply uncertainty assessment using MCS considering the international reliability and comparability. Additionally, since living biomass causes various error sources including measurement error and volume equations by tree species, there is a need for research to assessing different error sources for uncertainty.

Determination of country-specific greenhouse gas emission factors for South African liquid and gaseous fuels

Higher-tier methods for greenhouse gas reporting require country-specific emission factors for a range of liquid and gaseous fuels for both stationary and mobile fuel combustion activities. Samples of selected liquid fuels used in South Africa were collected over the summer and winter seasons in the Gauteng, Mpumalanga, Free State, KwaZulu-Natal and Western Cape provinces of South Africa, primarily from large retail stations along major traffic routes (unleaded petrol – ULP93 and ULP95 – and diesel). Liquid fuels used in smaller volumes (bio-ethanol, paraffin, jet kerosene, aviation gasoline and heavy fuel oil) were also sampled at appropriate locations. Samples (343 in total) were analysed for carbon content using standard methods at an accredited commercial laboratory. Calorific values of the fuels were also determined, to allow for the calculation of methane and nitrous oxide emission factors. Results were statistically analysed to determine mean values and their uncertainties, to identify outliers, and to determine correlations between variables. Results for ULP93 and ULP95 were weighted by their respective 2021 annual average sales volumes to obtain an average value for all petrol of 2 263 g CO2/L. Based on sales data from the years 2018–2021, summer and winter results were equally weighted to obtain annual average emission factors for ULP93 (2255 g CO2/L), ULP95 (2 265 g CO2/L) and diesel (2 650 g CO2/L), reflecting a slight decrease from the values contained in the 2017 Department of Environmental Affairs Technical guidelines for monitoring, reporting and verification of greenhouse gas emissions by industry. A calculation-based liquefied petroleum gas emission factor, confirmed by analysis certificates from a number of local suppliers, was found to be 3002 g CO2/kg.

Open-data based carbon emission intensity signals for electricity generation in European countries – top down vs. bottom up approach

Dynamic grid emission factors provide a temporally resolved signal about the carbon intensity of electricity generation in the power system. Since actual carbon dioxide emission measurements are usually lacking, such a signal must be derived from system-specific emission factors combined with power generation time series. We present a bottom-up method that allows deriving per country and per technology emission factors for European countries based on plant specific power generation time series and reported emissions from the European emissions trading mechanism. We have matched, 595 fossil generation units and their respective annual emissions. In 2018, these power plants supplied 717 TWh of electricity to the grid, representing approximately 50% of power generation from fossil fuels. Based on this dataset, 42 individual technology and country-specific emission factors are derived. The resulting values for historical per country carbon intensity of electricity generation are compared with corresponding results from a top-down approach, which uses statistical data on emissions and power generation on national scales. All calculations are based on publicly available data, such that the analysis is transparent and the method can be replicated, adjusted and expanded in a flexible way.

Applying a neural network-based approach for estimating instantaneous emissions of the heavy-duty buses: A case study

ABSTRACT The lack of a chassis and a transient engine dynamometer for heavy-duty vehicles in Vietnam is a significant impediment to develop the country-specific emission factors. This study presents a novel approach for modeling the emission rate of heavy-duty bus engines based on the artificial neural network (ANN) to overcome the above limitation while ensuring emission prediction’s accuracy and minimizing test costs. The ANN-based models with high reliability (R2 > 0.98 and MAPE <20%) were built based on the experimental data collected from the engine emission measurement on the steady-state engine dynamometer. The developed models were used to estimate the bus’s emission rate according to the real-world driving characteristic that was taken into the typical transient engine cycle. The estimated average emission factors in terms of distance-based ones for buses in Hanoi according the ANN-based models were close to those measured.

Can nitrogen input mapping from aerial imagery improve nitrous oxide emissions estimates from grazed grassland?

Most nitrogen (N) lost to the environment from grazed grassland is produced as a result of N excreted by livestock, released in the form of nitrous oxide (N2O) emissions, nitrate leaching and ammonia volatilisation. In addition to the N fertiliser applied, excreta deposited by grazing livestock constitute a heterogeneous excess of N, creating spatial hotspots of N losses. This study presents a yearlong N2O emissions map from a typical intensively managed temperate grassland, grazed periodically by a dairy herd. The excreta deposition mapping was undertaken using high-resolution RGB images captured with a remotely piloted aircraft system combined with N2O emissions measurements using closed statics chambers. The annual N2O emissions were estimated to be 3.36 ± 0.30 kg N2O–N ha−1 after a total N applied from fertiliser and excreta of 608 ± 40 kg N ha−1 yr−1. Emissions of N2O were 1.9, 3.6 and 4.4 times lower than that estimated using the default IPCC 2019, 2006 or country-specific emission factors, respectively. The spatial distribution and size of excreta deposits was non-uniform, and in each grazing period, an average of 15.1% of the field was covered by urine patches and 1.0% by dung deposits. Some areas of the field repeatedly received urine deposits, accounting for an estimated total of 2410 kg N ha−1. The method reported in this study can provide better estimates of how management practices can mitigate N2O emissions, to develop more efficient selective approaches to fertiliser application, targeted nitrification inhibitor application and improvements in the current N2O inventory estimation.

A high-resolution gridded inventory of coal mine methane emissions for India and Australia

Coal mines are globally an important source of methane and also one of the largest point sources of methane. We present a high-resolution 0.1° × 0.1° bottom-up gridded emission inventory for methane emissions from coal mines in India and Australia, which are among the top 5 coal producing countries in 2018. The aim is to reduce the uncertainty in local coal mine methane emissions and to improve the spatial localization to support monitoring and mitigation of these emissions. For India, we improve the spatial allocation of the emissions (CH4 emissions: 825 [min: 166 – max: 1484] Gg yr−1) by identifying the exact location of surface and underground coal mines and we use a Tier-2 Intergovernmental Panel on Climate Change (IPCC) methodology to estimate the emissions from each coal mine using country-specific emission factors. For Australia (CH4 emissions: 972 [min: 863 – max: 1081] Gg yr−1), we estimate the emission for each coal mine by distributing the state-level reported total emissions using proxies of coal production and the coal basin-specific gas content profile of underground mines. Comparison of our total coal mine methane emission from India with existing global inventories showed our estimates are about a factor 3 lower, but well within range of the national Indian estimate reported to United Nations Framework Convention on Climate Change. For both the countries, the new spatial distribution of the emissions show large difference from the current global inventories. Our improved emissions dataset will be useful for air quality or climate modeling and while assessing the satellite methane observations.

Comprehensive Assessment of Greenhouse Gas Emissions From Thai Beef Cattle Production and the Effect of Rice Straw Amendment on the Manure Microbiome

We measured the greenhouse gas (GHG) emissions following beef cattle feeding and evaluated the manure management in northeast Thailand (Khon Kaen) to obtain the country-specific emission factor (EF) and replace the Intergovernmental Panel on Climate Change (IPCC) default value. We fed four Thai native cattle their typical diet of the region and then used the head-cage and dynamic chamber methods to measure the enteric methane (CH4) and GHG emissions during manure storage, respectively. The effect of amending the cattle manure with rice straw on the manure’s GHG emission was evaluated. The manure microbiome was monitored by 16S rRNA gene amplicon sequencing and qPCR assay of the functional genes that are required for the methanogenesis and nitrification/denitrification process. The estimated CH4conversion factor (Ym: 6.87 ± 0.11% gloss energy intake (GEI)) was slightly higher than the IPCC default value. The CH4emission from the manure accounted for 0.69 ± 0.26% GEI. The addition of rice straw slightly lowered the CH4emission from the manure, but the manure microbiome analysis results showed that it significantly reduced the relative abundance of methanogens (Methanobacteriales), and the functional estimation of manure microbiome agreed with this inhibition effect. The addition of rice straw also showed potential mitigation of the N2O emission with lowered nitrification activity and lower nitrifier abundance, but the results were not consistent between runs. Together these findings will be useful for the higher-tier approach to GHG emissions from beef cattle production systems in tropical regions.

Life cycle assessment of pasture-based dairy production systems: Current and future performance

To overcome the environmental challenges faced by the global agricultural sector while also ensuring economic viability, dairy farmers must improve the efficiency of their systems. To improve system efficiency, the performance of an average production system must be determined, as it establishes a benchmark from which the efficacy of proposed management practices and mitigation strategies can be assessed. Identified management practices and mitigation strategies can then be compiled to create ambitious but realistic targets for the sector to strive toward. Therefore the objective of this study was to calculate the environmental performance of an average spring-calving pasture-based dairy system and an ambitious target dairy system. Life cycle assessment (LCA) of 2 pasture-based dairy systems were conducted: (1) current average spring-calving pasture-based dairy system (current), and (2) a spring-calving pasture-based dairy system that has achieved key performance targets set by the most efficient dairy systems (target). An existing dairy LCA model was updated with country-specific emission factors, life cycle inventory data, and recommended methodologies. The environmental impact categories assessed were global warming potential, nonrenewable energy depletion, acidification potential, and eutrophication potential (marine and freshwater). Two functional units were used: per kilogram of fat- and protein-corrected milk (FPCM), and per hectare. To assess the effects of the model updates, the current dairy system was simulated twice, once with the previous version of the dairy LCA model, and second with the updated LCA model. The addition of country-specific emission factors, updated inventory data, and implementation of recommended methods has resulted in global warming potential and nonrenewable energy depletion being reduced by 10.4% and 10.9%, respectively. The updates had negligible effects on acidification and eutrophication potential. The inclusion of assumptions around carbon sequestration in grassland further reduced global warming potential by 16.4%. Moving from the current dairy system to the target dairy system was reported to reduce the environmental impact per kilogram of FPCM across all impact categories investigated. When expressed per hectare, transitioning toward the target dairy system reduced acidification, freshwater eutrophication, and nonrenewable energy depletion by 2.0%, 8.8%, and 13.8%, respectively. In contrast, transitioning toward the target dairy system increased global warming per hectare and, to a lesser degree, marine eutrophication potential per hectare. The increase in global warming and marine eutrophication potential per hectare was attributed to the increase in stocking rate and subsequently milk production per hectare (9,950 vs. 14,100 kg of FPCM/ha). This study demonstrates that the adoption of management practices that improve system efficiency will reduce the environmental impact per kilogram of FPCM and can contribute to the future sustainability of pasture-based dairy systems. However, improved system efficiency can be offset by the associated increase in productivity, highlighting the importance of reporting multiple environmental impact categories and functional units to prevent pollution swapping. New research and mitigation strategies will be required to improve the environmental sustainability of dairy systems beyond the target system in the future.

Estimation of greenhouse gases emission from domestic wastewater in Nepal: A scenario-based analysis applicable for developing countries

Domestic wastewater and wastewater treatment plants (WWTPs) are key emitters of greenhouse gases (GHGs). Quantifying these emissions in the present and future is crucial to tackle global climate change issues. As a developing country with few rural and urban wastewater treatment facilities, Nepal may have a unique opportunity to reduce future GHGs emissions by a proper selection of wastewater treatment technology. In this paper, the authors used Python programming to estimate the GHGs emissions from the domestic wastewater sector in Nepal under various technological development scenarios for 2020 to 2040 using the refined 2019 estimation methodology developed by Inter-governmental Panel on Climate Change (IPCC). Results show total equivalent CO2 emission of 3829.43 and 4523.65 Gigagrams in 2020 and 2040, respectively. The 2020 value is seven times greater than Nepal's 2017 national estimates because this study considered rural population and updated methodology. Comparing the technology development scenarios with the Business as Usual scenario, the highest GHGs reduction could be achieved by hybrid constructed wetlands (69.20%) followed by a combined anaerobic and aerobic system with biogas recovery for energy generation (61.72%). Further accuracy may be attained only through the actual measurement of WWTPs emissions and country-specific emission factors. Thus, this paper proposes GHGs estimation of future scenarios portraying urban and rural populations may be invaluable to policymakers of GHGs mitigation for selection of feasible WWTPs, especially in developing countries with limited wastewater treatment facilities and wastewater activity data.

농업환경 보전 프로그램 중 토양탄소 저장 증진 영농활동의 효과 정량화 방법론

Soil carbon storage is considered an important climate change mitigation strategy as it represents a major carbon storage reservoir in the global carbon cycle. Ministry for Food, Agriculture, Forestry and Fisheries (MIFAFF) set up the Agricultural Environment Conservation Program and agricultural practices to promote soil carbon storage are included as important activities. However, there is no established methodology to quantify the performance of agricultural practices that can enhance soil carbon storage. In this study, a methodology and tool were developed to quantify changes in soil carbon storage related to conservation actions. First, cropland was divided into rice paddies, agricultural fields, and perennial/tree crops, and agricultural activities were systematized considering domestic agricultural circumstances. No-till farming, cultivation of green manure, crop residue return, compost application, and biochar input were considered. Next, default factors of IPCC (Intergovernmental Panel on Climate Change) guideline and domestic research papers were reviewed to find the relevant effects of different activities on soil carbon storage. Finally, a spreadsheet for calculating changes in soil organic carbon stock was built using Microsoft Excel. The developed method was applied to Sangju-si and Boryeong-si, which joined the Agricultural Environment Conservation program, and the total increase in soil carbon storage in 20 years was calculated as 255.0 ton C and 356.8 ton C, respectively. The methodology and soil carbon stock calculator established in this study will be able to more accurately reflect the domestic situation if country-specific emission factors are incorporated in the future.

Country-specific emission factor for developing a tier 3 system of Indonesia’s seagrass carbon inventory

Climate action regarding carbon inventory requires baseline assessment, data regarding annual changes, and evaluation of reductions in carbon emissions. However, many studies of seagrass ecosystems have focused only on carbon stock and sequestration, neglecting the importance of the carbon emission factor. It is known that emission factors for land-use change, including those in seagrass ecosystems, can be derived from biomass and sediment carbon stock. Since currently Indonesia only has data for biomass carbon stock, we propose the measurement of province-based emission factors. This study combines the available carbon stock data reported in national or international publications and conducts a meta-analysis to obtain emission factor values. The results show that the biomass standing carbon stock of Indonesia’s seagrass meadows ranges from 0.30 tC/ha (i.e., Special Region of Yogyakarta) to 16.51 tC/ha (i.e., Gorontalo province), while emission factor ranges from 0.012 tC/ha/yr to 0.661 tC/ha/yr (equal to 0.05 t CO2/ha/yr to 2.42 t CO2/ha/yr). These findings will be beneficial for developing Tier 3 carbon inventory since they allow country-specific emission factor for the seagrass ecosystem to be measured.