Estimation of Green House Gas (GHG) emission at Telaga Punggur landfill using triangular, LandGEM, and IPCC methods

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.

Methane emissions along biomethane and biogas supply chains are underestimated

Greenhouse gas emissions during MSW landfilling in China: Influence of waste characteristics and LFG treatment measures

The MAGICC (Model for the Assessment of Greenhouse gas Induced Climate Change) model simulation has been carried out for the 2000–2100 period to investigate the impacts of future Indian greenhouse gas emission scenarios on the atmospheric concentrations of carbon dioxide, methane and nitrous oxide besides other parameters like radiative forcing and temperature. For this purpose, the default global GHG (Greenhouse Gases) inventory was modified by incorporation of Indian GHG emission inventories which have been developed using three different approaches namely (a) Business-As-Usual (BAU) approach, (b) Best Case Scenario (BCS) approach and (c) Economy approach (involving the country’s GDP). The model outputs obtained using these modified GHG inventories are compared with various default model scenarios such as A1B, A2, B1, B2 scenarios of AIM (Asia-Pacific Integrated Model) and P50 scenario (median of 35 scenarios given in MAGICC). The differences in the range of output values for the default case scenarios (i.e., using the GHG inventories built into the model) vis-a-vis modified approach which incorporated India-specific emission inventories for AIM and P50 are quite appreciable for most of the modeled parameters. A reduction of 7% and 9% in global carbon dioxide (CO2) emissions has been observed respectively for the years 2050 and 2100. Global methane (CH4) and global nitrous oxide (N2O) emissions indicate a reduction of 13% and 15% respectively for 2100. Correspondingly, global concentrations of CO2, CH4 and N2O are estimated to reduce by about 4%, 4% and 1% respectively. Radiative forcing of CO2, CH4 and N2O indicate reductions of 6%, 14% and 4% respectively for the year 2100. Global annual mean temperature change (incorporating aerosol effects) gets reduced by 4% in 2100. Global annual mean temperature change reduces by 5% in 2100 when aerosol effects have been excluded. In addition to the above, the Indian contributions in global CO2, CH4 and N2O emissions have also been assessed by India Excluded (IE) scenario. Indian contribution in global CO2 emissions was observed in the range of 10%–26%, 6%–36% and 10%–38% respectively for BCS, Economy and BAU approaches, for the years 2020, 2050 and 2100 for P50, A1B-AIM, A2-AIM, B1-AIM & B2-AIM scenarios. CH4 and N2O emissions indicate about 4%–10% and 2%–3% contributions respectively in the global CH4 and N2O emissions for the years 2020, 2050 and 2100. These Indian GHG emissions have significant influence on global GHG concentrations and consequently on climate parameters like RF and ∆T. The study reflects not only the importance of Indian emissions in the global context but also underlines the need of incorporation of country specific GHG emissions in modeling to reduce uncertainties in simulation of climate change parameters.

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

At present scenario, estimation of Greenhouse Gas (GHG) emission in the ambient air has becomes a major concern. Emission of GHG has the direct linkage with ambient air pollution and also poses global environmental threats and challenges. Though several scientists are working to mitigate the emission of GHGs but till date no mitigation/management plan has been implemented in global scale. The emission of GHGs are in general from multiple sectors like energy, industry, waste management plant, agricultural sector etc. The major GHGs are methane (CH4), carbon dioxide (CO2) and nitrous oxide (N2O). In the present study GHG (CH4, CO2 and N2O) fluxes have been reviewed from wastewater treatment plant (WWTP), constructed wetlands (CWs) and irrigated rice fields (IRF) in India and compared with other countries like Australia, Europe and China. The emission of CH4, CO2 and N2O fluxes from WWTP in Australian condition varied in an average from 0 to 111, 0 to 769 and 0 to 3 ton/year respectively whereas in Indian condition CH4 and N2O fluxes varied in an average from 0 to 6, and 0 to 0.01 ton/year. The higher emission of CH4 and N2O in Australia might be due to higher capacity of WWTP and advance biological treatment plant as compared to India. In Indian and China climatic condition the emission of CH4, CO2 and N2O fluxes from IRF varied from 107 × 104 to 110 × 104, 2116 × 104 to 6096 × 104 and 4 × 104 to 5 × 104, 644 × 104 to 1202 × 104, 205 × 104 to 1208 × 104 and 29 × 104 to 41 × 104 ton/year respectively. The higher fluxes of GHG w.r.t CH4 and N2O might be due to continuous flooding in China, application of nitrogen fertilizers in large scale in the rice field, and likely to be due to overburden pressure for production of rice as compared to India. CWs are the well-known natural CH4 producer in the atmosphere. The emission of CH4 from CWs in India and Europe varied from 46 to 1103 and negative to 38,000 mg/m2/day respectively. CH4 emission depends on tropical coastal wetland condition and type of surface flow in the wetland. India is fewer producers to GHGs as compared to other countries. Appropriate management plan will further reduce the emission of GHGs as well as ambient air pollution.

Global economic development has highlighted the issue of climate change, which is one of the most important environmental issues plaguing human beings. It is widely agreed that excessive greenhouse gas (GHG) emissions are important factors contributing to global warming. Many countries have formulated corresponding GHG emission reduction plans to deal with climate change issues. An important GHG emission source is released from sewage-sludge treatment systems. However, there has not been a comprehensive quantitative GHG emissions evaluation system in the case of sewage-sludge treatment systems, due to multiple emission sources, complex processes, and different standards. In previous studies, the Guidelines for National Greenhouse Gas Inventories (Intergovernmental Panel on Climate Change, IPCC, 2006) and Chinese Greenhouse Gas Inventory (National Center for Climate Change Strategy and International Cooperation, NCSC, 2005) were widely applied to estimate GHG emissions from sewage-sludge treatment. However, IPCC does not consider CO2 emissions from sewage treatment, and NCSC does not consider CO2 emissions from the sewage treatment and N2O emissions from sludge treatment. Therefore, the following have been conducted in this study: (1) A GHG estimation model basing on Life Cycle Thinking (LCT) was constructed, and the research objects were CH4, N2O, and CO2 that were produced by the sewage-sludge treatment system. The estimation model of CO2 and N2O, which were ignored in the IPCC report, were analyzed and discussed. The models of the GHG emission estimation were summarized and improved in the urban sewage-sludge treatment system under the different sewage-sludge treatment process scenarios. (2) The GHG emission load of major urban sewage-sludge treatment processes was analyzed, and the level and key links of environmental impacts generated by different processes were identified. This helps to understand and compare the environmental impacts of different treatment processes and provides suggestions for the sustainable development of wastewater treatment processes. (3) The GHG emission characteristics of nine scenarios of different sewage-sludge treatment processes were analyzed, and the environmental impacts caused by energy consumption and chemicals consumption were studied. Consequently, the sewage-sludge treatment process under low carbonization and low environment impact were proposed.

This chapter explains the importance of accurate estimation of greenhouse gas (GHG) emissions for effective promotion of mitigation policies at the national and regional levels. Between 2011 and 2014, the Ministry of Environment of Indonesia and Japan International Cooperation Agency (JICA) conducted a pilot project in the provinces of North Sumatra and South Sumatra to enhance the quality of their GHG inventory in the waste sector. Through the pilot project, methodologies for developing accurate activity data were developed, resulting in a decrease of GHG emissions from solid waste disposal sites (SWDSs) by approximately 30 %. Methane emissions from SWDSs in other provinces are also expected to decrease by approximately 30 % because their GHG estimation methods are similar to what had been the case in North Sumatra and South Sumatra before the pilot project started. This indicates the necessity of updating the national action plan for GHG emission reduction (RAN-GRK) along with the improvement of the GHG inventory.

Significant temporal variability leads to estimation bias in greenhouse gas emissions from aquaculture pond systems

Climate change mitigation requires countries to report their annual greenhouse gas (GHG) emissions and sinks, including those from land use, land use change, and forestry (LULUCF). In Finland, the LULUCF sector plays a crucial role in achieving net-zero GHG emissions, as the sector is expected to be a net sink. However, accurate estimates of LULUCF-related GHG emissions, such as methane (CH4), remain challenging. We estimated LULUCF-related CH4 emissions in Finland in 2013–2020 by combining national land cover and remote-sensed surface wetness data with CH4 emissions estimated by an inversion model. According to our inversion model, most of Finland’s CH4 emissions were attributed to natural sources such as open pristine peatlands. However, our research indicated that forests with thin tree cover surrounding open peatlands may also be a significant source of CH4. Unlike open pristine peatlands and pristine peatlands with thin tree cover, surrounding transient forests are included in the Finnish GHG inventory if they meet the criteria used for forest land. The current Finnish national GHG inventory may therefore underestimate CH4 emissions from forested organic soils surrounding open peatlands, although more precise methods and data are needed to verify this. Given the potential impact on net GHG emissions, CH4 emissions from transitional forests on organic soils should be further investigated. Furthermore, the results demonstrate the potential of combining atmospheric inversion modelling of GHGs with diverse data sources and highlight the need for methods to more easily combine atmospheric inversions with national GHG inventories.

A greenhouse gas (GHG) inventory is a systematic attempt to account for the production and release of certain gasses generated by an institution from various emission sources. The gasses of interest are those which have become identified by climate science as related to anthropogenic global climate change. This document presents an inventory of GHGs generated during fiscal year (FY) 2008 by Idaho National Laboratory (INL), a Department of Energy (DOE)-sponsored entity, located in southeastern Idaho. Concern about the environmental impact of GHGs has grown in recent years. This, together with a desire to decrease harmful environmental impacts, would be enough to encourage the calculation of a baseline estimate of total GHGs generated at the INL. Additionally, the INL has a desire to see how its emissions compare with similar institutions, including other DOE-sponsored national laboratories. Executive Order 13514 requires that federally-sponsored agencies and institutions document reductions in GHG emissions in the future, and such documentation will require knowledge of a baseline against which reductions can be measured. INL’s FY08 GHG inventory was calculated according to methodologies identified in Federal recommendations and an as-yet-unpublished Technical and Support Document (TSD) using operational control boundary. It measures emissions generated in three Scopes: (1)more » INL emissions produced directly by stationary or mobile combustion and by fugitive emissions, (2) the share of emissions generated by entities from which INL purchased electrical power, and (3) indirect or shared emissions generated by outsourced activities that benefit INL (occur outside INL’s organizational boundaries but are a consequence of INL’s activities). This inventory found that INL generated a total of 114,256 MT of CO2-equivalent emissions during fiscal year 2008 (FY08). The following conclusions were made from looking at the results of the individual contributors to INL’s baseline GHG inventory: • Electricity is the largest contributor to INL’s GHG inventory, with over 50% of the net anthropogenic CO2e emissions • Other sources with high emissions were stationary combustion, fugitive emissions from the onsite landfill, mobile combustion (fleet fuels) and the employee commute • Sources with low emissions were contracted waste disposal, wastewater treatment (onsite and contracted) and fugitive emissions from refrigerants. This report details the methods behind quantifying INL’s GHG inventory and discusses lessons learned on better practices by which information important to tracking GHGs can be tracked and recorded. It is important to stress that the methodology behind this inventory followed guidelines that have not yet been formally adopted. Thus, some modification of the conclusions may be necessary as additional guidance is received. Further, because this report differentiates between those portions of the INL that are managed and operated by the Battelle Energy Alliance (BEA) and those managed by other contractors, it includes only that large proportion of Laboratory activities overseen by BEA. It is assumed that other contractors will provide similar reporting for those activities they manage, where appropriate.« less

Central to any study of climate change is the development of an emission inventory that identifies and quantifies the State's primary anthropogenic sources and sinks of greenhouse gas (GHG) emissions. CO2 emissions from fossil fuel combustion accounted for 80 percent of California GHG emissions (CARB, 2007a). Even though these CO2 emissions are well characterized in the existing state inventory, there still exist significant sources of uncertainties regarding their accuracy. This report evaluates the CO2 emissions accounting based on the California Energy Balance database (CALEB) developed by Lawrence Berkeley National Laboratory (LBNL), in terms of what improvements are needed and where uncertainties lie. The estimated uncertainty for total CO2 emissions ranges between -21 and +37 million metric tons (Mt), or -6percent and +11percent of total CO2 emissions. The report also identifies where improvements are needed for the upcoming updates of CALEB. However, it is worth noting that the California Air Resources Board (CARB) GHG inventory did not use CALEB data for all combustion estimates. Therefore the range in uncertainty estimated in this report does not apply to the CARB's GHG inventory. As much as possible, additional data sources used by CARB in the development of its GHG inventory are summarized in this report for consideration in future updates to CALEB.

Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.

Climatic temperature controls the geographical patterns of coastal marshes greenhouse gases emissions over China

Dairy production systems represent a significant source of air pollutants such as greenhouse gases (GHG), that increase global warming, and ammonia (NH3), that leads to eutrophication and acidification of natural ecosystems. Greenhouse gases and ammonia are emitted both by conventional and organic dairy systems. Several studies have already been conducted to design practices that reduce greenhouse gas and ammonia emissions from dairy systems. However, those studies did not consider options specifically applied to organic farming, as well as the multiple trade-offs occurring between these air pollutants. This article reviews agricultural practices that mitigate greenhouse gas and ammonia emissions. Those practices can be applied to the most common organic dairy systems in northern Europe such as organic mixed crop-dairy systems. The following major points of mitigation options for animal production, crop production and grasslands are discussed. Animal production: the most promising options for reducing greenhouse gas emissions at the livestock management level involve either the improvement of animal production through dietary changes and genetic improvement or the reduction of the replacement rate. The control of the protein intake of animals is an effective means to reduce gaseous emissions of nitrogen, but it is difficult to implement in organic dairy farming systems. Considering the manure handling chain, mitigation options involve housing, storage and application. For housing, an increase in the amounts of straw used for bedding reduces NH3 emissions, while the limitation of CH4 emissions from deep litter is achieved by avoiding anaerobic conditions. During the storage of solid manure, composting could be an efficient mitigation option, depending on its management. Addition of straw to solid manure was shown to reduce CH4 and N2O emissions from the manure heaps. During the storage of liquid manure, emptying the slurry store before late spring is an efficient mitigation option to limit both CH4 and NH3 emissions. Addition of a wooden cover also reduces these emissions more efficiently than a natural surface crust alone, but may increase N2O emissions. Anaerobic digestion is the most promising way to reduce the overall greenhouse gas emissions from storage and land spreading, without increasing NH3 emissions. At the application stage, NH3 emissions may be reduced by spreading manure during the coolest part of the day, incorporating it quickly and in narrow bands. Crop production: the mitigation options for crop production focus on limiting CO2 and N2O emissions. The introduction of perennial crops or temporary leys of longer duration are promising options to limit CO2 emissions by storing carbon in plants or soils. Reduced tillage or no tillage as well as the incorporation of crop residues also favour carbon sequestration in soils, but these practices may enhance N2O emissions. Besides, the improvement of crop N-use efficiency through effective management of manure and slurry, by growing catch crops or by delaying the ploughing of leys, is of prime importance to reduce N2O emissions. Grassland: concerning grassland and grazing management, permanent conversion from arable to grassland provides high soil carbon sequestration while increasing or decreasing the livestock density seems not to be an appropriate mitigation option. From the study of the multiple interrelations between gases and between farm compartments, the following mitigation options are advised for organic mixed crop-dairy systems: (1) actions for increasing energy efficiency or fuel savings because they are beneficial in any case, (2) techniques improving efficiency of N management at field and farm levels because they affect not only N2O and NH3 emissions, but also nitrate leaching, and (3) biogas production through anaerobic digestion of manure because it is a promising efficient method to mitigate greenhouse gas emissions, even if the profitability of this expensive investment needs to be carefully studied. Finally, the way the farmer implements the mitigation options, i.e. his practices, will be a determining factor in the reduction of greenhouse gas and NH3 emissions.