Estimation of greenhouse gas emissions from agricultural activities in the Aburra valley Metropolitan Area - Colombia

The traditional upscaling approach to greenhouse gas (GHG) emission estimates of inland waters is imprecise, but more precise methods based on environmental drivers are a longstanding challenge. Mexico lacks GHG emission estimates for its inland waters, and only sparse but scientifically validated information is available. This study provides the first GHG emission estimates from Mexican inland waters using 4275 GHG flux measurements from 26 distinctive waterbodies and one local and another global surface area dataset (INEGI and HydroLAKES). GHG emission factors were calculated and subsequently upscaled to estimate total national GHG emissions from the inland waters and compare to other emission measures based on mean global emission factors or size-productivity weighted (SPW) models. Mean (standard error) annual fluxes from all inland waters were 2.2 (5.3) kg CO2 m−2 yr−1, 0.6 (1.14) kg CH4 m−2 yr−1, and 1.0 × 10−3 (6.0 × 10−4) kg N2O m−2 yr−1. Estimates for natural waterbodies are annual average release rates between 74 (87) and 139 (163.23) Tg CO2eq while artificial waterbodies reach between 32 (2) and 21 (21) Tg CO2eq according to INEGI and HydroLAKES datasets, respectively. Considerable uncertainty was determined in the calculated mean emission factor, mostly for anthropogenic emissions. Waterbody area and chlorophyll a concentration were used as proxies to model CO2 and CH4 fluxes through regression analysis. According to SPW and IPCC models, computed mean annual CH4 emission factors were close to our estimates and exhibited a strong influence from eutrophication. In a likely scenario of increased eutrophication in Mexico, an increase in total net emissions from inland waters could be expected.

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 %).

The calling on livestock is increasing fast because of the population and economic broadening. In recent years, the contribution of the livestock sector to greenhouse gas emissions and climate change has been a concern. This sector accounts for the second largest share of anthropogenic greenhouse gas emissions after the energy sector. The storage of animal manure is very important in this respect. Because gases such as nitrous oxide and methane, which are important greenhouse gases, are formed during storage. Therefore, it is very important to focus on this area to make manure management systems sustainable. In this study, greenhouse gas emissions that may occur in the provinces located in the region called Turkey's Lakes Region were estimated using the data on the number of different species of animals published in 2016-2020. Evolution by years has been evaluated on a provincial basis. The global warming potential created by greenhouse gas emissions has been determined. As an animal species in the study; dairy and beef cattle, buffalo, sheep, goat, donkey-mule, meat and laying chicken, turkey, duck, and goose were used. 1567000 tons of CH4 emission has occurred due to the total enteric fermentation of animal origin. The amount of CH4 calculated based on manure management is 22450 tons. The CO2 equivalent amount of CH4 emission due to manure management and enteric fermentation was calculated as 33380500 tons. The total amount of direct and indirect N2O emissions from manure management in 2016-2020 is 12566.10 tons. CO2 emission originating from N2O emission was obtained as 555743.46 tons.

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

Identity-based estimation of greenhouse gas emissions from crop production: Case study from Denmark

Diversity in reservoir surface morphology and climate limits ability to compare and upscale estimates of greenhouse gas emissions

Rank-order concordance among conflicting emissions estimates for informing flight choice

Porvair makes environmental improvements across its global operations

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.

Emissions of methane (CH4) and nitrous oxide (N2O) from agricultural activities currently comprise 10-12% of the world’s total anthropogenic greenhouse gas (GHG) emissions. They are also forecast to rise by 30% above current levels by 2050. At the Conference of the United Nations Framework Convention on Climate Change (UNFCCC) held in Paris in December 2015, more than 100 countries indicated that they would reduce agricultural GHG emissions as part of the global effort to keep warming to a maximum of 2°C. Emissions from ruminant livestock present a particular challenge as enteric CH4 emissions alone comprise ~40% of total agricultural emissions. Estimating emissions from animal agriculture can be done through simple estimates, generically available data on animal populations and regional-level fixed emission factors per animal. But these estimates are subject to very large uncertainties and their appropriateness for estimating emissions at the country level is questionable. More appropriate country-specific methods can be developed using local data and expert opinion in the first instance, even in the absence of country-specific emission factors. Reducing GHG emissions from ruminant livestock is challenging technically even if livestock production is constant, and is particularly challenging if the sector is increasing in size. Internationally the quantity of GHG produced per unit of product has been declining consistently and for both cattle meat and milk than 50 years ago. This decline is largely due to increased efficiency of production. Increasing efficiency is therefore a key component of agricultural GHG mitigation. Increasing efficiency,while essential, may not be enough on its own. New technologies are therefore needed and for ruminant livestock there are some promising products; compounds that inhibit enteric CH4, vaccines, low emitting sheep have been successfully bred and, a variety of low emitting feeds, and feed additives.

Municipal waste production in Indonesia is rapidly increasing due to population growth and economic development, contributing significantly to greenhouse gas (GHG) emissions. This research aims to develop effective waste management scenarios for Pekanbaru City, focusing on reducing GHG emissions through integrated treatment methods. Employing a comprehensive methodology, the study estimates GHG emissions from various waste management practices, including biological, thermal, and mixed methods. The research utilizes a basic model to calculate emissions based on activity data and emission factors, exploring current practices and innovative strategies like Black Soldier Fly (BSF) larvae for organic waste treatment. Findings reveal that the Mix scenario, which combines multiple waste management processes, results in the most significant reduction of GHG emissions, achieving a net emission of 112,985.89 tons of CO?-eq/year, compared to the existing scenario with 637,864.33 tons of CO?-eq/year. The study identifies key emission hotspots, emphasizing the need for improved management of organic waste through composting and recycling. The implications of this research highlight the importance of adopting integrated waste management strategies to mitigate GHG emissions effectively. The findings provide actionable insights for policymakers, promoting sustainable practices aligned with the 3R hierarchy (reduce, reuse, recycle) and supporting targeted interventions that can enhance environmental sustainability in urban settings.

Carbon footprint of a winter wheat-summer maize cropping system under straw and plastic film mulching in the Loess Plateau of China

Livestock sector contributes to the increase of global warming through gas released from enteric fermentation and manure management. National estimation still uses a manual calculation. The aim of this study was to estimate the contribution of greenhouse gas (GHG) emission from livestock sector by using ALU tool version 6.0.1, in West Java Province in year 2016 as the case study. The emission were calculated by using Tier-1 and Tier-2 methodologies. Data used were livestock population and emission factors (EF) of CH4 and N2O of any livestock. The results showed that emission from enteric fermentation was 94.754 Gg CH4/year or 2,368.850 Gg CO2e/year with the highest emission from sheep (50.194 Gg CH4/year or 1,254.850 Gg CO2/year). While emission of CH4 from manure was 6,767 Gg CH4/year or 169,175 Gg CO2e/year with the highest emission from dairy cattle (2,870 Gg CH4/year or 71,750 Gg CO2e/year) and direct N2O emission from manure was 0.366 Gg N2O/year or 109.138 Gg CO2e/year with the highest emission from sheep (0.189 Gg N2O/year or 56.212 Gg CO2e/year). As a conclusion, total emission from the livestock sector in West Java Province was 2,647.163 Gg CO2e/year with the largest emission was from enteric fermentation (2,368.850 Gg CO2e/year). This study suggests that ALU tool is applicable to estimate GHG emission for Livestock in Indonesia with limited data available.

ABSTRACTSouth Korea has the tenth highest greenhouse gas (GHG) emissions worldwide, of which 16% originates from the road sector. Existing estimation methods of road GHG emissions have various limitations, such as low accuracy or the ability to only estimate GHG emissions within a limited area. Therefore, this study aimed to develop a methodology to estimate GHG emissions while considering various geometric designs of roads, including both vertical and horizontal alignment. The developed method is more objective and reliable than existing methodologies that consider only vertical alignment. First, Lamm's theory on travel speed profiles was applied to predict GHG emissions. Then, this study attempted to overcome the limited spatial estimation capacity of existing methods by considering upstream and downstream geometric design parameters simultaneously. Second, this study used the GHG operation mode extracted from the MOtor Vehicle Emission Simulator (MOVES), a modeling system that estimates emissions for mobile sources at the national, county, and project levels for criteria air pollutants, GHGs, and air toxicity. The operation mode includes vehicle type, fuel, and other factors, and is designed to estimate GHG emissions at 1-s intervals. Based on the results of the analysis, the effectiveness of the new method was compared to existing methods using an economic analysis (e.g., cost–benefits from the reduced emissions). This study presents a method for performing sensitive estimations of GHG emissions according to the geometric design of roads, which can be used to collect more accurate data on GHG emissions.

Land use affects the structure and functioning of forest ecosystems, thus affecting greenhouse gas fluxes. Greenhouse gas emissions were assessed in the Wari-Maro Forest Reserve (FCWM) and its periphery between 2005 and 2020. To achieve this, the methodological approach applied is based on the use of activity data (AD) from 2005 and 2020 land use and land cover maps derived from satellite images and emission factors (EF) from forest inventory data conducted in 2005 and 2020. The analysis of the results shows that the peripheral zone has the highest emission factor evaluated at 87.22 t.eq-CO2 /ha/year against 47.37 t.eq-CO2/ha/year recorded in the Forest Reserve. The total CO2 emissions due to deforestation in the Forest Reserve are 5106.78 t.eq-CO2/ha/year against a global emission of 65402.23 t.eq-CO2/ha/year for the periphery. This high emission of the peripheral area is due to the result of the high anthropogenic pressure in this area. Those due to degradation are 2880.53 t.eq-CO2/ha/year in the Forest Reserve against 1049.67 t.eq-CO2/ha/year in the periphery. The amount of CH4 and N2O increases progressively from the Forest Reserve (319.49 t.eq-CO2/ha/year and 26.80 t.eq-CO2/ha/year) to the periphery (2658.08 t.eq-CO2ha/year and 222.99 t.eq-CO2/ha/year) probably due to the extent of agricultural and livestock production activities in this area.