Greenhouse gas emission mapping and quantification based on 3D transport modeling and Bayesian state estimation

Animal manure is an important source of anthropogenic GHG (greenhouse gas): methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2). The livestock contributes with 37% of global CH4 emission. The sources of GHG (CO2 and CH4) are the liquid manure or slurry storage and the compact solid manure. Measurement systems of GHG emission are important for the selection of the appropriate technology. By using the closed chamber method for soil, landfills, volcanoes etc., the present study evaluates the estimation of total emissions of methane and carbon dioxide from an experimental farm in Cluj County, Romania. The investigated area covered with sheep solid manure was about 579 m2 and ~5 cm thick, for cattle was about 12 m2 and 5 m thick and for swine was about 1.5 m5 and 0.5 m thick. The total methane emission measured for sheep manure was 0.83 t CH4/year and for cattle manure was 0.185 t CH4/year. The total carbon dioxide emission measured for sheep manure was 61.3 t CO2/year and for cattle manure was 4.7 t CO2/year. The measurement for pigs manure was high and this could be due to the freshness of the manure. The estimated emissions showed that a considerable amount of CH4 and CO2 is produced also by an experimental farm and an appropriate management of manure is important for reducing greenhouse gas. In this respect, we believe that the future solution for a green economy is to use manure in biogas plants.

Recent studies suggest that hypolimnetic respiration may be responsible for greenhouse gas (GHG) emissions from deep reservoirs. Currently, quantitative evaluation of aerobic vs. anaerobic processes and priming (enhanced processing of organic matter due to the addition of labile carbon) in regulating GHG production and emissions across the reservoir‐downstream continuum remains largely unknown. High‐resolution, annual time‐series observations in a large, subtropical reservoir (Shuikou) experiencing seasonal hypoxia in southeast China indicate that aerobic hypolimnetic CO2 production dominated in most periods of the stratified spring/summer with higher rates at higher temperatures. In addition, anaerobic production of hypolimnetic CO2 occurred in the late stratified spring/summer period, which stimulated hypolimnetic production of CH4 and N2O. Incubation experiments showed that priming in spring enhanced both aerobic and anaerobic production of excess GHGs. A late spring flood event generated the highest daily efflux of CO2 through the flushing of GHG‐enriched hypolimnion waters. Turbine degassing contributed 59%, 93%, and 63% of annual CO2, CH4, and N2O effluxes, respectively. Moreover, annual downstream GHG emissions were similar to those in the transition/lacustrine zone of the Shuikou reservoir. Diurnal variation observations revealed net CO2 emissions even during algal bloom seasons. The reservoir‐downstream river continuum was a year‐round source of GHGs (218.5 ± 18.9 Gg CO2‐equivalent yr−1; CO2 contributed 91%). However, the loss of oxygen also leads to increased production and storage of recalcitrant dissolved organic carbon (RDOC). Thus, identifying mechanisms controlling both GHG emissions and RDOC production is crucial to constrain the carbon neutrality issue of hydroelectric reservoirs in the context of climate change mitigation strategies.

Greenhouse gas emission profiles of European livestock sectors

Methane (CH4), carbon dioxide (CO2) and nitrous oxide (N2)O) are greenhouse gases (GHGs) which cause global warming. Natural sources of GHGs include wetlands and termites. Previous studies have quantified GHG emissions from upland termites and no study has reported GHG emissions from seasonal wetlands (dambo) located termite mounds. The objective of this study was to evaluate the effect of dambo catena position on termite mound distribution and GHG emissions. It was hypothesized that mound density and GHG emissions from Odontotermes transvaalensis mounds, vary with catena position. The evaluated catena positions were margin, mid-slope, lower slope and bottom. Mound density was significantly lower in the bottom when compared to the other catena positions. The mean GHG fluxes were 88 μg m2 hr-1, 0.78 mg m2 hr-1 and 1361 mg m2 hr-1 for N2) O, CH4 and CO2 respectively. Fluxes varied with catena position and were 0.48, 0.72, 1.35 and 0.79 mg m-2 hr-1 for CH4 , and 1173.7, 1440.7, 1798.7 and 922.8 mg m-2 hr-1 for CO2 in the margin, mid-slope, lower slope and the bottom catena position respectively. For N2) O, there were no significant differences between catena positions. It was concluded that dambo located Odontotermes transvaalensis termite mounds are an important source of GHGs, and emissions varied with catena position for CO2 and CH4.

Most of the electricity generation and transportation industries are based on fossil fuels in the present scenario but these fossil fuels are the main source of Green House Gas (GHG) emissions and global warming increment. CO2 is the key component in GHG emissions. These emissions can be reduced by using a renewable energy source like solar for electricity generation and using Fuel Cell Electric Vehicle (FCEV) technology for transportation. Total CO2 emission from 87,470 cars and 7,44,678 two-wheelers of Smart City Udaipur is calculated as 52 tonnes per km of driving distance. 100 vehicles (50 cars and 50 two-wheelers) are selected for pilot project calculation of required solar PV Plant size and required fuel for FCEV. 16,669.16 kWh electricity and 3,310 litres of water will be required per day for the electrolysis process to produce 331 kg hydrogen. Solar PV plant of 4 MW capacity will be required for enough electricity generation. MATLAB simulations of 6 kW (for bikes) and 50 kW (for cars) PEM Fuel Cell is done and some graphs are plotted in this paper with the help of simulation outputs like- power, efficiency, utilization etc.

Impacts of dissolved oxygen control on different greenhouse gas emission sources in wastewater treatment process

Agriculture is a significant source of anthropogenic greenhouse gas (GHG) emissions, and beef cattle are particularly emissions intensive. GHG emissions are typically expressed as a carbon dioxide equivalent (CO2e) ‘carbon footprint’ per unit output. The 100-year Global Warming Potential (GWP100) is the most commonly used CO2e metric, but others have also been proposed, and there is no universal reason to prefer GWP100 over alternative metrics. The weightings assigned to non-CO2 GHGs can differ significantly depending on the metric used, and relying upon a single metric can obscure important differences in the climate impacts of different GHGs. This loss of detail is especially relevant to beef production systems, as the majority of GHG emissions (as conventionally reported) are in the form of methane (CH4) and nitrous oxide (N2O), rather than CO2. This paper presents a systematic literature review of harmonised cradle to farm-gate beef carbon footprints from bottom-up studies on individual or representative systems, collecting the emissions data for each separate GHG, rather than a single CO2e value. Disaggregated GHG emissions could not be obtained for the majority of studies, highlighting the loss of information resulting from the standard reporting of total GWP100 CO2e alone. Where individual GHG compositions were available, significant variation was found for all gases. A comparison of grass fed and non-grass fed beef production systems was used to illustrate dynamics that are not sufficiently captured through a single CO2e footprint. Few clear trends emerged between the two dietary groups, but there was a non-significant indication that under GWP100 non-grass fed systems generally appear more emissions efficient, but under an alternative metric, the 100-year global temperature potential (GTP100), grass-fed beef had lower footprints. Despite recent focus on agricultural emissions, this review concludes there are insufficient data available to fully address important questions regarding the climate impacts of agricultural production, and calls for researchers to include separate GHG emissions in addition to aggregated CO2e footprints.

Canadian agriculture is a source of greenhouse gases (GHG) and agroforestry has the potential to sequester carbon (C), and mitigate agricultural GHG emissions. Agroforestry systems are common features in Canada’s agricultural landscape; however, there are limited empirical data to support implementation of agroforestry practices for GHG mitigation. This shortfall of data may be a contributing factor to the lack of policy that supports the use of agroforestry for GHG mitigation in the Canadian agricultural landscape. We reviewed published studies that compared C stocks in vegetation and soils, and/or GHG emissions in agroforestry systems to traditional agriculture across Canada, with the aims of assessing the benefit of adopting agroforestry for GHG reduction. We then identified data gaps and obstacles that could direct future research. We found that most studies reported increases in vegetation and soil organic C storage in areas with woody species compared to herbaceous crops. Agroforestry systems also reduced the emission of CH4and N2O, and increased CO2respiration from soil, but few studies have examined these gases. The small set of studies we reviewed demonstrated the potential of agroforestry to store terrestrial C and mitigate GHG emissions. However, additional research is required to verify this pattern across geographic regions, determine the regional potential for development of agroforestry systems, and assess the potential atmospheric GHG reduction at regional and national scales.

Greenhouse gas emissions from integrated urban drainage systems: Where do we stand?

The combustion of woodfuel for residential use is often not considered to be a source of greenhouse gas (GHG) emissions in households since emissions from woodfuel combustion can be offset by the CO2 absorbed by the growth of the forest as a carbon sink (IPCC, 2006). However, this only applies to wood that is harvested in a renewable way, i.e., at a rate not exceeding the regrowth rate of the forest from which it is harvested (Drigo et al., 2002). This paper estimates the share of GHG emissions attributable to non-renewable woodfuel harvesting for use in residential food activities. It adds to a growing research base estimating GHG emissions from across the entire agri-food value chain, from the manufacture of farm inputs, through food supply chains, and finally to waste disposal (Tubiello et al., 2021). Country-level information is generated from United Nations Statistics Division (UNSD) and International Energy Agency (IEA) data on woodfuel use in households. We find that, in 2019, annual emissions from non-renewable woodfuel use in household food consumption were about 745 million tonnes (Mt CO2eq yr−1), with uncertainty ranging from −20 % to + 22 %, having increased 6 % from 1990. Overall, global trends were a result of counterbalancing effects: the emission increases were largely fuelled from countries in Sub-Saharan Africa, Southern Asia, and Latin America while significant decreases were seen in countries in Eastern Asia and South-eastern Asia. The Food and Agriculture Organisation of the United Nations (FAO) has developed and regularly maintains a database covering GHG emissions from the various components of the agri-food sector, including pre- and post-production activities, by country and world regions. The dataset is developed according to International Panel on Climate Change guidelines (IPCC, 2006), which avoids overlaps across AFOLU and energy components. It relies mainly on UNSD Energy Statistics data, which are used as activity data for the calculation of the GHG emissions (Tubiello et al., 2022). The information used in this work is available as open data with DOI https://doi.org/10.5281/zenodo.7310932 (Flammini et al., 2022).

Livestock agriculture is a major source of anthropogenic greenhouse gas (GHG) emissions, with a substantial proportion of emissions derived from manure management. Accurate estimates of emissions related to management practices and climate are needed for identifying the best approaches to minimize, and potentially mitigate, GHG emissions. Current emissions models such as those of the IPCC, however, are based on emissions factors that have not been broadly tested against field-scale measurements, due to a lack of data. We used a diverse set of measurements over 22months across a range of substrate conditions on a working dairy to determine patterns and controls on soil-based GHG fluxes. Although dairy soils and substrates differed by management unit, GHG fluxes were poorly predicted by these or climate variables. The manure pile had the greatest GHG emissions, and though temperature increased and O2 concentration decreased following mixing, we detected almost no change in GHG fluxes due to mixing. Corral fluxes were characterized by hotspots and hot moments driven by patterns in deposition. Annual scraping kept the soil and accumulated manure pack thin, producing drier conditions, particularly in the warm dry season. Summed over area, corral fluxes had the greatest non-CO2 global warming potential. The field had net CH4 consumption, but CH4 uptake was insufficient to offset N2 O emissions on an area basis. All sites emitted N2 O with a similar or greater climate impact than CH4 . Our results highlight the importance of N2 O emissions, a less commonly measured GHG, from manure management and present potential opportunities for GHG emissions reductions.

This chapter outlines the role of livestock in the production of greenhouse gases (GHGs) that contributes to climate change. Livestock contribute both di‐ rectly and indirectly to climate change through the emissions of GHGs such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). As animal production systems are vulnerable to climate change and are large contribu‐ tors to potential global warming, it is vital to understand in detail enteric CH4 emission and manure management in different livestock species. Methane emissions from livestock are estimated to be approximately 2.2 billion tonnes of CO2 equivalents, accounting for about 80% of agricultural CH4 and 35% of the total anthropogenic CH4 emissions. Furthermore, the global livestock sec‐ tor contributes about 75% of the agricultural N2O emissions. Other sources of GHG emission from livestock and related activities are fossil fuels used for as‐ sociated farm activities, N2O emissions from fertilizer use, CH4 release from the breakdown of fertilizers and from animal manure, and land-use changes for feed production. There are several techniques available to quantify CH4 emission, and simulation models offer a scope to predict accurately the GHG emission from a livestock enterprise as a whole. Quantifying GHG emission from livestock may pave the way for understanding the role of livestock to climate change and this will help in designing appropriate mitigation strat‐ egies to reduce livestock-related GHGs.

Vegetation loss and plant diversity decline in wetlands affect carbon and nitrogen cycling and consequently influence gas fluxes. Although extensive grazing by livestock and climate change have caused significant physical degradation of wetlands on the Qinghai-Tibet Plateau (QTP), and created a clear drainage gradient, the impact on greenhouse gas (GHG) emissions associated with this change has rarely been reported. A 3-year study (2013–2015) was conducted to examine the effect of vegetation change and seasonality on ecosystem respiration, methane (CH4) and nitrous oxide (N2O) fluxes in four classes of wetlands with distinct magnitudes of vegetation degradation: healthy vegetation (HV), slightly degraded (SD), moderately degraded, and heavily degraded (HD). We used the dark static chamber-chromatography method to measure the gas fluxes. Highly degraded wetlands were larger C and GHG sources than HV, despite lower methane emissions, due to the loss of gross primary production. SD and HD exhibited the highest cumulative mean annual ecosystem respiration and N2O emissions, respectively. Ecosystem respiration and CH4 fluxes were much higher during the growing seasons than in the non-growing seasons. Ecosystem respiration and N2O fluxes were positively correlated with soil and air temperatures. This points at a potential effect of global warming on GHG emissions from the QTP wetlands. Top soil (0–20 cm) moisture content significantly correlated positively with CH4 fluxes. Vegetation loss led to a reduced C uptake and increased global warming potential. Therefore, we recommend soil conservation measures and reduced livestock grazing in the wetlands in order to conserve their role as carbon sinks.

In the current context of the international climate agenda, understanding both the sources of greenhouse gas (GHG) emissions and the mechanisms for their mitigation is a fundamental requirement for low-carbon development strategies. Kazakhstan has pledged to reduce its GHG emissions by 15–25% by 2030, relative to 1990 levels, and to achieve carbon neutrality by 2060. However, there is no unified methodology for comprehensively assessing the national carbon balance, particularly at the regional scale. This study addresses this gap by analyzing GHG emissions and carbon sequestration capacities across Kazakhstan’s regions using a sectoral disaggregation approach and scenario-based modeling aligned with IPCC methods. Emission hotspots were identified in the energy sector (328 MtCO2-eq), agriculture (118 MtCO2-eq—primarily from pasturelands), and transport (7 MtCO2-eq). In contrast, current carbon sinks—mainly forest ecosystems and abandoned pasturelands—account for only 3.97 and 13.9 MtCO2-eq, respectively. The research evaluates the technical potential for emissions reduction through the best available technologies (BAT), livestock management, partial transition to gas-powered vehicles, and reforestation. A geoengineering scenario combining all measures suggests that Kazakhstan could meet its 2030 climate targets, although full carbon neutrality by 2060 would remain out of reach under current policy trajectories. The Akmola region is examined as a representative case study, demonstrating a possible 35% reduction in net emissions by 2035. This work contributes a regionally nuanced, data-driven framework for integrating ecosystem services into national climate policy and identifies nature-based solutions—especially forest management—as essential components of Kazakhstan’s decarbonization pathway, offering insights for other carbon-intensive economies.

Estimating the pre-harvest greenhouse gas costs of energy crop production