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

Evaluation of the effect of accounting method, IPCC v. LCA, on grass-based and confinement dairy systems’ greenhouse gas emissions

The influence of strain of Holstein-Friesian cow and feeding system on greenhouse gas emissions from pastoral dairy farms

Making sense of methods to audit emissions – various audit methods to estimate dairy production carbon footprint

Comparison of greenhouse gas emission accounting methods for steel production in China

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).

Using a revised Intergovernmental Panel on Climate Change (IPCC) methodology and the process-based model DeNitrification and DeComposition (DNDC), we estimated N2O emissions from agroecosystems in Canada for each census year from 1981 to 2001. Based on the IPCC methodology, direct emissions of N2O ranged from 12.9 to 17.3 with an average of 15.1 Tg CO2 equivalents, while the DNDC model predicted values from 16.0 to 24.3 with an average of 20.8 Tg CO2 equivalents over the same period, and showed a large interannual variation reflecting weather variability. On a provincial basis, emissions estimated by IPCC and DNDC methods were highest in Alberta, Saskatchewan and Ontario, intermediate for Manitoba and Quebec and lowest in British Columbia and the Atlantic provinces. The greatest source of emissions estimated by the IPCC method was from N fertilizer (avg. 6.32 Tg CO2 equiv. in Canada), followed by crop residues (4.24), pasture range and paddocks (PRP) (2.77), and manure (1.65). All sources of emissions, but especially those from fertilizers, increased moderately over time. Monte Carlo Simulation was used to determine the uncertainty associated with the 2001 emission estimates for both IPCC and DNDC methodologies. The simulation generated most likely values of 19.2 and 16.0 Tg CO2 equivalents for IPCC and DNDC, respectively, with uncertainties of 37 and 41%, respectively. Values for the IPCC estimates varied between 28% for PRP and manure and 50% for N fertilizer and crop residues. At the provincial level, uncertainty ranged between 15 and 47% with higher values on the prairies. Sensitivity analyses for IPCC estimates showed crop residues as the most important source of uncertainty followed by synthetic N-fertilizers. Our analysis demonstrated that N2O emissions can be effectively estimated by both the DNDC and IPCC methods and that their uncertainties can be effectively estimated by Monte Carlo Simulation. Key words: Nitrous oxide, IPCC, DNDC model, Uncertainty analysis, Monte Carlo Simulation

Oil and gas (O&G) production activities emits greenhouse gases (GHG) which must be well estimated to improve accountability and formulating efficient mitigation. The Indonesia’s GHG emission reported thru Nationally Determined Contribution (NDC) was estimated by Tier-1 Intergovernmental Panel on Climate Change (IPCC) method, while the O&G company adopts different methodology. This leads to asynchronous GHG emission contribution of this industry to national GHG emission. This paper aims to estimate the GHG inventory from O&G offshore production facility by using American Petroleum Institute (API) Compendium Methodology and compare it with Tier-1 IPCC Methodology. It found that GHG emission estimated by API method is significantly lower than IPCC method. Both methods shown fuel combustion sources are the dominant. GHG emission sources from fuel combustion and flaring have been well identified, but emission sources from venting and fugitive need to be improved. Moreover this study identified that to have more accurate national GHG inventory, the GHG calculation method might be different for each industry segment. This evaluation could improve the future national GHG inventory and as reference for the industry. National emission factors database for O&G industry segment is highly suggested to be developed.

Animal production is a significant source of greenhouse gas (GHG) emissions. One of the major challenges in sustainable management is to mitigate the effects of climate change by reducing GHG emissions. The diversity of animal production systems and accompanying diversification of technological processes, mean that specific production effects can be obtained at different levels of GHG emissions. The aim of the study was to determine the carbon footprint (CF) of beef cattle grown in a conventional system (i.e. indoor confinement). The research was carried out on the beef cattle farm belonging to a large-area enterprise, Długie Stare Ltd. The beef cattle production system consisted of the following subsystems: a basic breeding herd (consisting of suckler cows, replacement heifers and calves up to 6.5 months), breeding heifers, breeding bulls and fattening bulls. The method of life cycle analysis (LCA) in the stages from "cradle-to-farmgate" was used to assess the GHG emissions associated with the production of beef cattle. The average CF in the entire beef cattle production system was 25.43 kg of CO2 kg-1 of live weight of marketed cattle, while in the individual subsystems of basic breeding herd, breeding heifers, breeding bulls and fattening bulls, the CF (after GHG allocation) was: 11.0 kg CO2 eq., 34.30 kg CO2 eq., 27.32 and 25.40 kg CO2 eq., respectively. GHG emissions associated with young calves staying in the cow-calf pairs until weaning (in the period from 0-6.5 months), had a decisive influence on the final CF in each of the subsystems of beef cattle production. The second important factor directly affecting the CF was GHG emissions related to methane (CH4) enteric fermentation and manure management. Knowledge of factors affecting the CF structure allows better identification of critical areas in production processes with high GHG emission potential. Information on the CF of beef cattle and beef meat responds to a wider societal demand for the ecological characteristics of market products, which ultimately contributes to improving their market competitiveness.

Life-cycle analysis (LCA) is an important tool used to assess the energy and environmental impacts of biofuels. Here, we review biofuel LCA methodology and its application in transportation fuel regulations in the United States, the European Union, and the United Kingdom. We examine the application of LCA to the production of ethanol from corn, sugarcane, corn stover, switchgrass, and miscanthus. A discussion of methodological choices such as co-product handling techniques in biofuel LCA is also provided. Further, we discuss the estimation of greenhouse gas (GHG) emissions of land use changes (LUC) potentially caused by biofuels, which can significantly influence LCA results. Finally, we provide results from LCAs of ethanol from various sources. Regardless of feedstock, bioethanol offers reduced GHG emissions over fossil-derived gasoline, even when LUC GHG emissions are included. This is mainly caused by displacement of fossil carbon in gasoline with biogenic carbon in ethanol. Of the ethanol pathways examined, corn ethanol has the greatest life-cycle GHG emissions and offers 30% reduction in life-cycle GHG emissions as compared to gasoline when LUC GHG emissions are included. Miscanthus ethanol demonstrates the highest life-cycle GHG emissions reductions compared to gasoline, 109%, when LUC GHG emissions are included.

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

ABSTRACTThis study was meant to determine environmental aspects of hospital waste management scenarios using a life cycle analysis approach. The survey for this study was conducted at the largest hospital in a major city of Pakistan. The hospital was thoroughly analyzed from November 2014 to January 2015 to quantify its wastes by category. The functional unit of the study was selected as 1 tonne of disposable solid hospital waste. System boundaries included transportation of hospital solid waste and its treatment and disposal by landfilling, incineration, composting, and material recycling methods. These methods were evaluated based on their greenhouse gas emissions. Landfilling and incineration turned out to be the worst final disposal alternatives, whereas composting and material recovery displayed savings in emissions. An integrated system (composting, incineration, and material recycling) was found as the best solution among the evaluated scenarios. This study can be used by policymakers for the formulation of an integrated hospital waste management plan.Implications: This study deals with environmental aspects of hospital waste management scenarios. It is an increasing area of concern in many developing and resource-constrained countries of the world. The life cycle analysis (LCA) approach is a useful tool for estimation of greenhouse gas emissions from different waste management activities. There is a shortage of information in existing literature regarding LCA of hospital wastes. To the best knowledge of the authors this work is the first attempt at quantifying the environmental footprint of hospital waste in Pakistan.

Does increasing milk yield per cow reduce greenhouse gas emissions? A system approach

Quantifying urban wastewater treatment sector's greenhouse gas emissions using a hybrid life cycle analysis method – An application on Shenzhen city in China

The challenge of agricultural sector is to reduce greenhouse gas (GHG) emissions while increasing food, fiber and energy production without jeopardizing environmental integrity. In the Andean zone of Colombia, there is a growing need to develop GHG mitigation techniques associated with milk production. The present study focuses on GHG emissions and potential sinks associated with milk production scenarios in the Andean zone of Colombia. The scenarios considered were as follows: conventional agriculture of Pennisetum clandestinum in rotation with potatoes (PRP), improved pastures of Lolium multiflorum (IP) and silvopastoral system of P. clandestinum in association with Acacia decurrens and Trifolium repens (SPS). Based on the IPCC (Guidelines for national greenhouse gas inventories. The intergovernmental panel on climate change, Institute for Global Environmental Strategies, Kanagawa, 2006. http://www.ipcc-nggip.iges.or.jp/support/Primer_2006GLs.pdf ) methodologies, the annual GHG emissions considering a 6-year production cycle included agricultural sources and gasoline consumption related to the most important agricultural phases in the field, and a potential for soil carbon accumulation and biomass carbon fixation in all the studied scenarios. The lowest GHG emissions were estimated in PRP scenario (3684 kg CO2-eq ha−1 year−1), which also presented additional emissions because of soil carbon losses beyond the lower milk productivity. Highest GHG emissions were observed in IP scenario (7711 kg CO2-eq ha−1 year−1), which exhibited the highest milk productivity and a considerable potential for soil carbon accumulation that could help to offset its emissions. Nevertheless, SPS scenario, which had milk productivity close to that of IP, presented the highest potential to offset the total GHG emission (4878 kg CO2-eq ha−1 year−1) because of soil carbon accumulation and biomass carbon fixation in trees. This study contributed to indicate management strategies that should be prioritized to mitigate the main sources of GHG emission in the extensive and intensive dairy cattle production in the Andean region of Colombia.

Objectives:The study was undertaken to investigate the greenhouse gas (GHG) emission from livestock in Bangladesh.Materials and Methods:The GHG emission inventory of livestock in Bangladesh was estimated according to the tier 1 approach of the Intergovernmental Panel on Climate Change (IPCC) using livestock population data from 2005 to 2018. It was also extrapolated for the next three decades, according to the growth of the livestock population.Results:According to the calculation, the GHG emission from livestock was 66,586 Gg/year CO2 equivalent (CO2e) in 2018. This emission may rise to 69,869, 80,618, 94,638, and 113,098 Gg/year CO2e in 2020, 2030, 2040, and 2050, respectively. The share of enteric methane, manure methane, direct nitrous oxide emission, and indirect nitrous oxide emission in the total GHG emissions represented 44.0%, 3.6%, 51.5%, and 0.9%, respectively, in 2018. It may arise at a rate of 1.54%–1.74% annually until 2050.Conclusion:The GHG inventory may guide professionals to formulate and undertake the effective mitigation measures of GHG emissions from livestock in Bangladesh. However, this inventory can be amended following the tier 2 approach recommended by the IPCC if necessary data are available at the national level.