An estimation of greenhouse gas emission from livestock in Bangladesh

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

While actions for addressing global climate change should not be delayed,an open and compatible method for quantifying the greenhouse gas(GHG) emissions of cities or local regions is critical required to support policies.Urban GHG inventory is fundamental for accounting GHG emissions in cities.In general,it reflects both emission structure and trend.Compiling GHG inventories at urban scale is a basic demand of low-carbon city construction in China,and also a foundation for China′s future development. Although use the methods of national GHG inventories as reference,GHG inventories for cities have their own characteristics on principles and methodology systems.The present urban GHG inventory usually uses the experiences of GHG inventory methodologies developed by IPCC(The Intergovernmental Panel on Climate Change),ICLEI(International Council for Local Environmental Initiatives) and Draft International Standard for Determining Greenhouse Gas Emissions for Cities.However,there are still no systemic and standardized methods and indexes for urban GHG inventories,because different organizations have established different approaches for inventorying urban GHG emissions.Though unified framework,such as IPCC or ICLEI,is used,treatments on some emission sources(electricity and cross-boundary transport) or divisions of sub-sectors are different.Due to these issues,it is unsuitable for comparison between cities.At the same time,the calculation results of China′s urban GHG emissions have little comparability with those of western cities,owing to differences of definitions and scales. China′s urban GHG emission inventory research is just at the beginning and achievements need to be extended and the performance of urban GHG emission inventory still has a long way to go.Based on present methodologies of compiling urban GHG emission inventories and typical case studies,both domestic and international,we were willing to establish a common standard by which inventory of urban emissions should be followed.Considering the special characteristics of China′s urban structure,and the problems which would be faced during the accounting progress,China′s urban GHG inventories should take its administrative area as spatial boundary and three main gases,carbon dioxide,methane and nitrous oxide,should be concluded.Consumption-based mode should be chose in order to reflect emission amount and structure more truly and more comprehensive.The most recent IPCC guidelines can be used for determining emissions from four aspects,energy(stationary and mobile sources),industrial processes and product use(IPPU),agriculture,forestry and other land use(AFOLU;where significant),and waste.While it is impractical to quantify all of the emissions associated with the indirect ways of urban GHG emissions,such as myriad of goods and materials consumed in cities,urban GHG inventories should also include out-of-boundary emissions from the generation of electricity and district heating which are consumed in cities(including transmission and distribution losses),emissions from aviation and marine vessels carrying passengers or freight away from cities,out-of-boundary emissions from waste that is generated in cities.The GHG emissions embodied in the food,water,fuels and building materials consumed in cities should also be reported as additional information items if possible.Uncertainty assessment and quality assurance are encouraged and should follow IPCC guidelines.

The Global Fire Emissions Database (GFED3) and the FAOSTAT Emissions database, containing estimates of greenhouse gas (GHG) emissions from biomass burning and peat fires, are compared. The two datasets formed the basis for several analyses in the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5), and thus represent a critical source of information for emissions inventories at national, regional and global level. The two databases differ in their level of computational complexity in estimating emissions. While both use the same burned area information from remote sensing, estimates of available biomass are computed in GFED3 at tier 3 using a complex dynamic vegetation model, while they are computed in FAOSTAT using default, tier 1 parameters from the Intergovernmental Panel on Climate Change (IPCC). Over the analysis period 1997–2011, the two methods were found to produce very similar global GHG emissions estimates for each of the five GFED aggregated biomass fire classes: i) Savanna; ii) Woodland; iii) Forest; iv) Deforestation; v) Peatlands; with total emissions ranging 6–8 Gt CO2eq yr-1. The main differences between the two datasets were found with respect to peat fires, with FAOSTAT showing a lower 1997–1998 peak in emissions compared with GFED3, within an otherwise good agreement for the rest of the study period, when limited to the three tropical countries covered by GFED. Conversely, FAOSTAT global emissions from peat fires, including both boreal and tropical regions, were several times larger than those currently estimated by GFED3. Results show that FAOSTAT activity data and emission estimates for biomass fires offer a robust alternative to the more sophisticated GFED data, representing a valuable resource for national GHG inventory experts, especially in countries where technical and institutional constraints may limit access, generation and maintenance of more complex methodologies and data.

The effect of methodology on estimates of greenhouse gas emissions from grass-based dairy systems

The waste that loaded to the Talang Gulo Landfill in 2018 is 1,012.234 m3/day and is predicted to produce Greenhouse Gas (GHG) emissions such as CH4 and N2O. The purpose of this study was to create a waste management layout, to determine the generation data and composition of waste in Jambi city and calculate the estimated amount of Greenhouse Gas (GHG). The calculation of Greenhouse Gas (GHG) emissions in this study used from Intergovernmental Panel On Climate Change (IPCC) 2006 method. Sampling results show that the average waste generation in Jambi City is 0.207 kg/person/day. Food waste, plastics, and paper were the dominant components from the composition of waste in landfill by 47,381%, 20.565%, and 13.096%. CH4 emissions generated from landfill zone VI in 2019 amounted to 4,695×10-2 Gg and would increase to 16,608×10-2 Gg in 2030. Greenhouse gas emissions generated from the composting zone consisted of 8,6×10-4 Gg CH4 and 5,16×10-5 Gg N2O in 2019 and 9,5×10-4 Gg CH4 and 5,7×10-5 Gg N2O in 2030. Emissions from heavy equipment activity in 2019 amounted to 1,065 Gg CO2. Estimates of greenhouse gas emissions are useful for taking steps to mitigate greenhouse gas emissions.

Abstract. To track progress towards keeping global warming well below 2 ∘C or even 1.5 ∘C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO2 emissions, CH4 emissions, N2O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF6, NF3) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (∼ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO2 eq. consisting of CO2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO2, CO2-LULUCF 5.7 ± 4.0 GtCO2, CH4 10 ± 3.1 GtCO2 eq., N2O 2.6 ± 1.6 GtCO2 eq., and F-gases 1.3 ± 0.40 GtCO2 eq. Initial estimates suggest further growth of 1.3 GtCO2 eq. in GHG emissions to reach 59 ± 6.6 GtCO2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr−1) compared to 2000–2009 (2.4 % yr−1), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

The overexploitation of natural resources and increasing dependence on these sources have caused an increase in solid waste generation, aggravating environmental impacts and contributing significantly to climate change through enhanced greenhouse gas (GHG) emissions. This scenario highlights the urgent need for circular economy strategies focused on reducing carbon emissions and mitigating environmental impacts. Continuous monitoring is crucial to evaluate current conditions and guide effective measures in the transition toward a sustainable waste management model. This study quantifies the total potential methane (CH4) emissions and analyzes the variation in CH4 production over time within a solid waste treatment and disposal facility. Emissions were estimated using three methodologies: the standard Intergovernmental Panel on Climate Change (IPCC) approach, the LandGEM® model (V3.02) provided by the U.S. Environmental Protection Agency (EPA), and the triangular gas production model. The results indicate peak emissions of approximately 72,82 and 2,30E-3 Gg for the IPCC and triangular models, respectively, while the LandGEM® model predicted a substantially higher peak of 8,31 Gg, suggesting emissions could persist for up to 124 years post-closure. In this study, the results are not directly comparable, as the estimates are strongly dependent on the assumptions and parameters adopted, reinforcing the inherent limitations of the available models when applied to realities different from those for which they were originally developed. Therefore, they should be interpreted as extreme envelopes of behavior intended to support the planning of strategies aimed at mitigating environmental impacts. Implications: The results presented in this study contribute significantly to the improvement of environmental management strategies in urban solid waste management complexes. The estimation of greenhouse gas (GHG) emissions allows the identification of critical points of methane and carbon dioxide release, supporting the adoption of more efficient control and mitigation technologies. In addition, the data obtained can be used by public managers and policymakers to develop action plans aimed at reducing emissions in the waste sector, aligning with the climate commitments assumed by Brazil under the Paris Agreement and promoting the transition to more sustainable circular economy practices.

Abstract. Conferences, meetings and congresses are an important part of today's economic and scientific world. But the environmental impact, especially from greenhouse gas emissions associated with travel, can be extensive. Anthropogenic greenhouse gas (GHG) emissions account for the warming of the atmosphere and oceans. This study draws on the need to quantify and reduce greenhouse gas emissions associated with travel activities and aims to give suggestions for organizers and participants on possible ways to reduce greenhouse gas emissions, demonstrated on the example of the European Geography Association (EGEA) Annual Congress 2013 in Wasilkow, Poland. The lack of a comprehensive methodology for the estimation of greenhouse gas emissions from travel led to an outline of a methodology that uses geographic information systems (GIS) to calculate travel distances. The calculation of travel distances in GIS is adapted from actual transportation infrastructure, derived from the open-source platform OpenStreetMap. The methodology also aims to assess the possibilities to reduce GHG emissions by choosing different means of transportation and a more central conference location. The results of the participants of the EGEA congress, who shared their travel data for this study, show that the total travel distance adds up to 238 000 km, with average travel distance of 2429 km per participant. The travel activities of the participants in the study result in total GHG emissions of 39 300 kg CO2-eq including both outward and return trip. On average a participant caused GHG emissions of 401 kg CO2-eq. In addition, the analysis of the travel data showed differences in travel behaviour depending on the distance between conference site and point of origin. The findings on travel behaviour have then been used to give an estimation of total greenhouse gas emissions from travel for all participants of the conference, which result in a total amount of 79 711 kg CO2-eq. The potential for reducing greenhouse gas emissions by substituting short flights with train rides and car rides with bus and train rides is limited. Only 6 % of greenhouse gas emissions could be saved by applying these measures. Further considerable savings could only be made by substituting longer flights (32.6 %) or choosing a more central conference location (26.3 %).

ABSTRACTWaste production increases with the increase in population, urbanization rate and people’s income. Solid waste is a contributor to greenhouse gas (GHG) emissions which can cause global warming. At the Conference of Parties 25 (COP 25) in Madrid 2019, the Indonesian government is still commited to reducing GHG emissions and working to reduce/limit the increase in temperature below 1.50C. Karangasem regency is an area located in the eastern part of Bali Island, which administratively is one of the regency in Bali Province. The population of Karangasem regency in 2018 based on results of population registration was 414,800 people. The population is spread across 8 sub-districs with the population growth rate in Karangasem averaging 0.88% per year. The distribution of the population will be directly proportional to the distribution of solid waste produced. The method for calculating municipal solid waste will be carried out using the First Order Decay method contained in the IPCC (Intergovernmental Panel on Climate Change) Guidelines. From the calculation results, GHG emission have been obtained in each sub-district in Karangasem regency. Total GHG emission in 2019 amounted to 11,764 tonnes of CO2-e. Mapping the area in Karangasem district to determine the amount of waste produced by each district is deemed necessary as a mitigation effort to be implemented. In this study, a mapping of each sub-district was carried out on the basis of Geographical Information System (GIS). It is necessary to carry out a GHG inventory at the district level, to determine how much GHG emission are generated from the waste sector. After the GHG emission in known, a mapping of each sub-district will be made to determine the level of emission produced, so that this GHG emission reduction mitigation action will focus more on the sub-districts that produce the most emission first followed by other sub-districts.Keywords: Waste, GHG Inventory, First Order Decay, Geographic Information System.ABSTRAKProduksi limbah meningkat seiring dengan meningkatnya jumlah penduduk, tingkat urbanisasi dan pendapatan masyarakat. Sampah merupakan salah satu penyumbang emisi gas rumah kaca (GRK) yang dapat menyebabkan adanya pemanasan global (global warming). Pada Conference of Parties 25 (COP 25) di Madrid tahun 2019, pemerintah Indonesia masih berkomitmen untuk dapat menurunkan emisi gas rumah kaca dan berupaya untuk mengurangi/membatasi peningkatan suhu dibawah 1,50C. Kabupaten Karangasem, merupakan daerah yang berada di belahan timur Pulau Bali, yang secara administratif merupakan salah satu kabupaten dalam wilayah Provinsi Bali. Jumlah penduduk Kabupaten Karangasem pada tahun 2018 berdasarkan hasil registrasi penduduk adalah 414.800 jiwa. Jumlah penduduk tersebut tersebar dalam 8 kecamatan dengan angka pertambahan penduduk di Karangasem rata-rata 0,88% per tahun. Sebaran jumlah penduduk akan berbanding lurus dengan sebaran limbah padat yang dihasilkan. Metode penghitungan limbah padat kota akan dilakukan dengan menggunakan metode First Order Decay yang terdapat pada IPCC (Intergovernmental Panel on Climate Change) Guidelines. Dari hasil perhitungan telah didapatkan emisi GRK di tiap-tiap kecamatan yang ada di Kabupaten Karangasem. Total emisi GRK pada tahun 2019 yaitu sebesar 11.764 ton CO2-e. Pemetaan wilayah di kabupaten392 Jurnal Teknologi Informasi dan Komputer, Volume 6, Nomor 3, Oktober 2020Karangasem untuk mengetahui jumlah sampah yang dihasilkan tiap kecamatan dipandang perlu dilaksanakan sebagai upaya mitigasi yang akan dilaksanakan. Pada penelitian ini dilaksanakan pemetaan tiap-tiap kecamatan dengan basis Sistem Informasi Geografis (SIG). Inventarisasi GRK di tingkat kabupaten ini perlu dilakukan, untuk mengetahui sampai berapa besar emisi GRK yang dihasilkan dari sektor limbah tersebut. Setelah emisi GRK sudah diketahui, maka akan dibuat sebuah pemetaan tiap-tiap kecamatan untuk mengetahui tingkat emisi yang dihasilkan, sehingga aksi mitigasi penurunan emisi GRK ini akan lebih fokus pada kecamatan-kecamatan yang menghasilkan emisi paling besar terlebih dahulu dilanjutkan dengan kecamatan yang lainnya.Kata Kunci : Limbah, Inventarisasi GRK, First Order Decay, Sistem Informasi Geografis.

Simple SummaryLivestock manure management is one of the main sources of greenhouse gas (GHG) emissions in South Africa producing mainly methane and nitrous oxide. The emissions from this sub-category are dependent on how manure is stored. Liquid-stored manure predominantly produces methane while dry-based manure enhances mainly production of nitrous oxide. Intergovernmental Panel on Climate Change (IPCC) guidelines were utilized at different tier levels in estimating GHG emissions from manure management. The results show that methane emissions are relatively higher than nitrous oxide emissions with 3104 Gg and 2272 Gg respectively in carbon dioxide global warming equivalent.Manure management in livestock makes a significant contribution towards greenhouse gas emissions in the Agriculture; Forestry and Other Land Use category in South Africa. Methane and nitrous oxide emissions are prevalent in contrasting manure management systems; promoting anaerobic and aerobic conditions respectively. In this paper; both Tier 1 and modified Tier 2 approaches of the IPCC guidelines are utilized to estimate the emissions from South African livestock manure management. Activity data (animal population, animal weights, manure management systems, etc.) were sourced from various resources for estimation of both emissions factors and emissions of methane and nitrous oxide. The results show relatively high methane emissions factors from manure management for mature female dairy cattle (40.98 kg/year/animal), sows (25.23 kg/year/animal) and boars (25.23 kg/year/animal). Hence, contributions for pig farming and dairy cattle are the highest at 54.50 Gg and 32.01 Gg respectively, with total emissions of 134.97 Gg (3104 Gg CO2 Equivalent). Total nitrous oxide emissions are estimated at 7.10 Gg (2272 Gg CO2 Equivalent) and the three main contributors are commercial beef cattle; poultry and small-scale beef farming at 1.80 Gg; 1.72 Gg and 1.69 Gg respectively. Mitigation options from manure management must be taken with care due to divergent conducive requirements of methane and nitrous oxide emissions requirements.

Bioenergy from perennial grasses mitigates climate change via displacing fossil fuels and storing atmospheric CO2 belowground as soil carbon. Here, we conduct a critical review to examine whether increasing plant diversity in bioenergy grassland systems can further increase their climate change mitigation potential. We find that compared with highly productive monocultures, diverse mixtures tend to produce as great or greater yields. In particular, there is strong evidence that legume addition improves yield, in some cases equivalent to mineral nitrogen fertilization at 33–150 kg per ha. Plant diversity can also promote soil carbon storage in the long term, reduce soil N2O emissions by 30%–40%, and suppress weed invasion, hence reducing herbicide use. These potential benefits of plant diversity translate to 50%–65% greater life-cycle greenhouse gas savings for biofuels from more diverse grassland biomass grown on degraded soils. In addition, there is growing evidence that plant diversity can accelerate land restoration. Bioenergy from perennial grasses mitigates climate change via displacing fossil fuels and storing atmospheric CO2 belowground as soil carbon. Here, we conduct a critical review to examine whether increasing plant diversity in bioenergy grassland systems can further increase their climate change mitigation potential. We find that compared with highly productive monocultures, diverse mixtures tend to produce as great or greater yields. In particular, there is strong evidence that legume addition improves yield, in some cases equivalent to mineral nitrogen fertilization at 33–150 kg per ha. Plant diversity can also promote soil carbon storage in the long term, reduce soil N2O emissions by 30%–40%, and suppress weed invasion, hence reducing herbicide use. These potential benefits of plant diversity translate to 50%–65% greater life-cycle greenhouse gas savings for biofuels from more diverse grassland biomass grown on degraded soils. In addition, there is growing evidence that plant diversity can accelerate land restoration.

Accuracy in national greenhouse gas (GHG) emissions estimation is a key element for outlining best strategies to reduce GHG emissions from various source sectors of the economy. In this study, an initial attempt has been made to estimate GHG emissions from waste sector in Rawal Town - an urban city of Rawalpindi district in Pakistan. Tier 1 approach of Revised 1996 Intergovernmental Panel on Climate Change (IPCC) Guidelines and the best available primary activity data collected for the study area were applied for the fiscal year June 2014-May 2015. Emissions of three GHGs - carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) under three waste management practices i.e. solid waste disposal sites, wastewater handling, and waste incineration were assessed. Out of the total 417.84 Gg CO2 equivalent emissions, the share of each gas (CH4, CO2 and N2O) in total emissions was found as 11.31, 0.53, and 0.58 Gg respectively. Solid waste disposal sites are identified as the largest source of CH4 emissions (10.73 Gg). To make the country's GHG emissions estimates more robust for waste sector, such type of local area based studies established on primary activity data could be advantageous for reducing uncertainties in national emission estimates.

Land-use changes are one of the three major sources of greenhouse gas (GHG) emissions due to human activity, along with fossil fuel combustion and cement production. Because road construction is the foremost cause of land-use changes, it is crucial to quantify the GHG emissions from road construction. However, the effect of GHG emissions attributed to land-use change for a single road construction project has not yet been fully investigated. This study quantified GHG emissions and sequestration from land-use changes due to road construction. Following the guidelines of the Intergovernmental Panel on Climate Change (IPCC), this study developed a framework to estimate GHG emissions for land-use changes. Eighteen cases involving a typical highway construction project in the Republic of Korea were selected for this study. The net GHG emissions from road construction were estimated to be within the range of 24–105 tons of carbon (tC)/lane-km, with an average of 66 tC/lane-km. Practical methods are sug...

A cradle-to-farm gate life cycle assessment was conducted following international standards (ISO 14040, 2006) to estimate sources of greenhouse gas emissions of an extensive alpaca production system in the Peruvian Andes with a focus on carbon footprint. The assessment encompasses all supply chain processes involved with the production of alpaca fiber and meat. Direct (i.e., enteric fermentation, manure, and manure management) and indirect emissions (i.e., electricity, fuel, and fertilizer) of carbon dioxide, nitrous oxide, and methane were estimated according to the (IPCC (Intergovernmental Panel on Climate Change). 2006. IPCC 2006 for National Greenhouse Gas Inventories. Volume 2, Chapter 3. Mobile Combustion. Volume 4, Chapter 10. Emissions from livestock and manure management. Chapter 11. N2O emissions from managed soils and CO2 emissions derived from the application of lime and urea. https://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html ). Carbon footprint was calculated based on a mass, economic, and biophysical allocation. The functional unit of the economic and mass allocations was 1kg of LW as the main product and 1kg of white or colored fiber as co-products. The functional unit of the biophysical allocation was 1kg of live weight and 1kg of fiber. The largest source of greenhouse gas emissions came from enteric fermentation (67%), followed by direct and indirect nitrous oxide emissions (29%). The estimated carbon footprint of the extensive alpaca production system, considering a 20% offtake rate, was 24.0 and 29.5kg of carbon dioxide equivalents per kg of live weight for the economic and mass allocations, respectively, while for the biophysical allocation was 22.6 and 53.0kg of carbon dioxide equivalents per kg of alpaca live weight and alpaca fiber, respectively. The carbon footprint per area was 88.6kg carbon dioxide equivalents per ha.

Estimating greenhouse gas emissions from Iran's domestic wastewater sector and modeling the emission scenarios by 2030