Estimation of Greenhouse Gas Emissions from Land-Use Changes due to Road Construction in the Republic of Korea

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).

The estimation of greenhouse gas (GHG) emissions from a change in land‐use and management resulting from growing biofuel feedstocks has undergone extensive – and often contentious – scientific and policy debate. Emergent renewable fuel policies require life cycle GHG emission accounting that includes biofuel‐induced global land‐use change (LUC) GHG emissions. However, the science of LUC generally, and biofuels‐induced LUC specifically, is nascent and underpinned with great uncertainty. We critically review modeling approaches employed to estimate biofuel‐induced LUC and identify major challenges, important research gaps, and limitations of LUC studies for transportation fuels. We found LUC modeling philosophies and model structures and features (e.g. dynamic vs. static model) significantly differ among studies. Variations in estimated GHG emissions from biofuel‐induced LUC are also driven by differences in scenarios assessed, varying assumptions, inconsistent definitions (e.g. LUC), subjective selection of reference scenarios against which (marginal) LUC is quantified, and disparities in data availability and quality. The lack of thorough sensitivity and uncertainty analysis hinders the evaluation of plausible ranges of estimates of GHG emissions from LUC. The relatively limited fuel coverage in the literature precludes a complete set of direct comparisons across alternative and conventional fuels sought by regulatory bodies and researchers.Improved modeling approaches, consistent definitions and classifications, availability of high‐resolution data on LUC over time, development of standardized reference and future scenarios, incorporation of non‐economic drivers of LUC, and more rigorous treatment of uncertainty can help improve LUC estimates in effectively achieving policy goals. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

Wastewater treatment plants (WWTPs) using membrane bioreactor (MBR) technology have been considered a significant source of greenhouse gas (GHG) emissions. This study chose a small-scale wastewater treatment plant using MBR technology to estimate its potential for GHG emissions. The total GHG emissions from this wastewater treatment plant ranged from 2,802 to 11,946kg CO2 -eq/month within the 4-year study period, and they were mainly attributable to electricity consumption (79.94%) followed by chemical usages (17.13%) and on-site GHG emissions (2.93%). The on-site GHG emissions varied monthly, but most of them ranged from 80 to 160kg CO2 -eq/month. The aeration tank was an important operating unit for GHG emissions. Off-site GHG emissions mainly came from carbon dioxide (CO2 ) emissions resulting from electricity consumption. The results of this study provide useful information about the potential of GHG emissions from WWTPs using MBR technology and indicate that WWTPs can be sustainably managed. PRACTITIONER POINTS: Wastewater treatment plants have been considered a source of greenhouse gas emissions. Total greenhouse gas emissions from the wastewater treatment plants using membrane bioreactor were mainly attributable to electricity consumption. On-site greenhouse gas emissions were relatively insignificant in this study.

The environmental sustainability of food production systems, including net greenhouse gas (GHG) emissions, is of increasing importance. In Norwegian pork production, animal performance is high in terms of reproduction, growth, and health. The development and use of an IPCC methodology-based model for estimating GHG emissions from pork production could be helpful in identifying the effects of progress in genetics and management. The objective was to investigate whether an IPCC methodology-based model was able to reflect the effects of the progress in genetics and management in pork production on the GHG emissions per kg carcass weight (CW). It is hypothesized that this progress has led to low GHG emissions intensities in Norwegian pork compared to global levels and that expected improvements will give a lasting reduction in GHG emissions intensities. A model ‘HolosNorPork’ for estimating net farm gate GHG emissions intensities was developed, including allocation procedures, at the pig production unit level. The model was run with pig production data from in average 632 farms from 2014 to 2019. The estimates include emissions of enteric and manure storage methane, manure storage nitrous oxide emissions, as well as GHG emissions from production and transportation of purchased feeds, and direct and indirect GHG emissions caused by energy use in pig-barns. The model was able to estimate the effects on net GHG emissions intensities from pork production on the basis of production characteristics. The estimated net GHG emissions intensity was found to have decreased from on average 2.49 to 2.34 kg CO2 eq. kg−1 CW over the investigated period. For 2019 the net GHG emission for the one-third lower performing farms was estimated to 2.56 kg CO2 eq. kg−1 CW, whereas for the one-third medium and one-third best performing farms the estimates were 2.36 and 2.16 kg CO2 eq. kg−1 CW, respectively. The net GHG emissions intensity for pork carcasses from boars was estimated to be 2.07 kg CO2 eq. kg−1 CW. For the health regimes investigated, Conventional and Specific-Pathogen Free (SPF), the estimated GHG emissions intensities for 2019 were 2.37 and 2.24 kg CO2 eq. kg−1 CW, respectively. The effects on net GHG emissions intensities of breeding and management measures were estimated to be profound, and this progress in pig production systems contributes to an on-going strengthening of pork as a sustainable source for human food supply.

All material supplied via Jukuri is protected by copyright and other intellectual property rights. Duplication or sale, in electronic or print form, of any part of the repository collections is prohibited. Making electronic or print copies of the material is permitted only for your own personal use or for educational purposes. For other purposes, this article may be used in accordance with the publisher's terms. There may be differences between this version and the publisher's version. You are advised to cite the publisher's version. This is an electronic reprint of the original article. This reprint may differ from the original in pagination and typographic detail.

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

Industrial activities are one of the most important emission sources of greenhouse gases at a global level. The process of production, transportation, electricity consumption, and industrial wastewater are the four major components in producing greenhouse gases. Industrial wastewater management (collection, treatment, and disposal) results in direct emission of greenhouse gases (including carbon dioxide, methane, and nitrous oxide). Also, energy consumption in the wastewater treatment process causes indirect carbon dioxide emissions. The present study aimed to estimate the contribution of industrial wastewater treatment plants in Iran from this emission, in addition to identifying sources of greenhouse gas emissions in the industrial wastewater treatment plant and estimating greenhouse gas emissions from the industrial wastewater sector in Iran. In this research, the emission calculations were conducted by using the methodology of Intergovernmental Panel on Climate Change (IPCC) guidelines for calculating greenhouse gases emission. Based on the estimations performed in this study, 1,305.98 kt of CH4 were emitted directly from wastewater in 2017 in the entire industrial wastewater sector. Further, the results indicated that industrial wastewater treatment plants in Iran’s industrial parks generate 46.53 kt of CH4 directly and 259.5 kt of CO2 indirectly. According to the studies, the food industry, especially the industries involved in processing agricultural products (with 48.74 % of total methane emissions) has the highest greenhouse gas emissions in the country, followed by the paper production industry (with 27.46 % of total methane emissions) in the second place. One of the best strategies for reducing greenhouse gas emissions in industrial wastewater treatment plants is energy production from methane produced in large treatment plants and implementing necessary amendments in production processes to decrease wastewater production.

Land use change implications for large-scale cultivation of algae feedstocks in the United States Gulf Coast

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 %).

A comprehensive mathematical model was developed for this study to estimate on-site and off-site GHG emissions from wastewater treatment plants (WWTPs). The model was applied to three different hybrid WWTPs (S-WWTP, J-WWTP, and T-WWTP) including anaerobic, anoxic, and aerobic process, located in Seoul City, South Korea. Overall on-site and off-site GHG emissions from S-WWTP, J-WWTP, and T-WWTP were <TEX>$305,253kgCO_2e/d$</TEX>, <TEX>$282,682kgCO_2e/d$</TEX>, and <TEX>$117,942kgCO_2e/d$</TEX>, respectively. WWTP treating higher amounts of wastewater produced more on-site and off-site GHG emissions. On average, the percentage contribution of on-site and off-site emissions was 3.03% and 96.97%. The highest amount of on-site GHG emissions was generated from anoxic process and the primary on-site GHG was nitrous oxide (<TEX>$N_2O$</TEX>). Off-site GHG emissions related to electricity consumption for unit operation was much higher than that related to production of chemicals for on-site usage. Recovery and reuse of biogas significantly reduced the total GHG emissions from WWTPs. The results obtained from this study can provide basic knowledge to understand the source and amount of GHG emissions from WWTPs and strategies to establish lower GHG emitting WWTPs.

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.

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.

Intended nationally determined contributions (INDCs) are a new strategy for mitigating climate change. Many international organizations and scholars have assessed the possibility of holding the increase in global average temperature to well below 2°C based on INDCs. Although the conclusions of these assessments are consistent, there are still large differences among the assessment results. For example, the global greenhouse gas emissions in 2030 estimated by INDCs are between 47.1–66.5 GtCO2 eq, and the temperature increase at the end of the 21st century estimated by INDCs is between 2.4–4.0°C; the inconsistency represented by these ranges is not conducive to an accurate assessment of the contributions of the current INDCs to global warming mitigation or to the further development of emissions reduction programs. By summarizing the existing studies, we found that the main reasons for the differences in estimates of global greenhouse gas emissions in 2030 made using INDCs are as follows: (1) The studies interpreted INDCs differently, which is attributable to three reasons: The studies (a) made different assumptions for the unquantifiable INDCs; (b) ignored or used different methods to estimate the emissions not covered by INDCs; and (c) used different amounts of INDCs because the studies were performed at different times. (2) The studies used different databases that include different greenhouse gases, accounting methods and data sources to estimate historical greenhouse gas emissions. (3) The studies used different methods for estimating greenhouse gas emissions and removals related to land use, land-use change and forestry (LULUCF). (4) The studies used different values of the global warming potential. Additionally, the main reasons for the differences in the predictions of the temperature increase at the end of the 21st century based on INDCs are as follows: (1) Differences in the estimations of greenhouse gas emissions in 2030 based on INDCs and (2) different methods of extrapolating global greenhouse gas emissions to 2100. There are three main extrapolation methods: one is to maintain the net present value of the carbon price in 2030 and then extrapolate the greenhouse gas emissions to 2100; another is to maintain the decarbonization rate of a certain period of history and then extrapolate the greenhouse gas emissions to 2100; the third is to match the emissions reduction scenario with the current INDC emissions reduction scenario from the IPCC AR5 scenario database and then use the matching emissions reduction scenario as the current INDC emissions reduction scenario. The use of different methods of extrapolating carbon emissions is one of the main reasons for the differences in the prediction results. (3) Differences in the methods for predicting the effects of greenhouse gas emissions on temperature. Statistical methods and simulation methods are the two main prediction methods; they use different calculation methods, which led to the difference in the prediction results. Therefore, the following points are worth noting: (1) Most importantly, to the extent possible, countries should submit absolute emissions reduction targets as much as possible; nonquantifiable INDCs without detailed methods descriptions and data introductions should not be submitted; (2) authorities should recommend certain data sets that are the most suitable for INDC accounting; (3) a global warming potential should be designated to avoid differences in greenhouse gas estimates due to the use of different criteria; and (4) to the extent possible, future research should adopt simulation methods for predicting the impact of global greenhouse gas emissions on temperature.

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.

Carbon Footprint of Rubber/Sugarcane Intercropping System in Sri Lanka: A Case Study