Academic literature on the topic 'Greenhouse gas mitigation – Mathematical models'
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Journal articles on the topic "Greenhouse gas mitigation – Mathematical models"
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Zhou, C. Y., G. H. Huang, J. P. Chen, and X. Y. Zhang. "Inexact Fuzzy Chance-Constrained Fractional Programming for Sustainable Management of Electric Power Systems." Mathematical Problems in Engineering 2018 (November 19, 2018): 1–13. http://dx.doi.org/10.1155/2018/5794016.
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An inexact fuzzy chance-constrained fractional programming model is developed and applied to the planning of electric power systems management under uncertainty. An electric power system management system involves several processes with socioeconomic and environmental influenced. Due to the multiobjective, multilayer and multiperiod features, associated with these various factors and their interactions extensive uncertainties, may exist in the study system. As an extension of the existing fractional programming approach, the inexact fuzzy chance-constrained fractional programming can explicitly address system uncertainties with complex presentations. The approach can not only deal with multiple uncertainties presented as random variables, fuzzy sets, interval values, and their combinations but also reflect the tradeoff in conflicting objectives between greenhouse gas mitigation and system economic profit. Different from using least-cost models, a more sustainable management approach is to maximize the ratio between clean energy power generation and system cost. Results of the case study indicate that useful solutions for planning electric power systems management practices can be generated.
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Shaw, Jacob T., Adil Shah, Han Yong, and Grant Allen. "Methods for quantifying methane emissions using unmanned aerial vehicles: a review." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 379, no. 2210 (September 27, 2021): 20200450. http://dx.doi.org/10.1098/rsta.2020.0450.
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Methane is an important greenhouse gas, emissions of which have vital consequences for global climate change. Understanding and quantifying the sources (and sinks) of atmospheric methane is integral for climate change mitigation and emission reduction strategies, such as those outlined in the 2015 UN Paris Agreement on Climate Change. There are ongoing international efforts to constrain the global methane budget, using a wide variety of measurement platforms across a range of spatial and temporal scales. The advancements in unmanned aerial vehicle (UAV) technology over the past decade have opened up a new avenue for methane emission quantification. UAVs can be uniquely equipped to monitor natural and anthropogenic emissions at local scales, displaying clear advantages in versatility and manoeuvrability relative to other platforms. Their use is not without challenge, however: further miniaturization of high-performance methane instrumentation is needed to fully use the benefits UAVs afford. Developments in the models used to simulate atmospheric transport and dispersion across small, local scales are also crucial to improved flux accuracy and precision. This paper aims to provide an overview of currently available UAV-based technologies and sampling methodologies which can be used to quantify methane emission fluxes at local scales. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.
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Kebreab, E., K. Clark, C. Wagner-Riddle, and J. France. "Methane and nitrous oxide emissions from Canadian animal agriculture: A review." Canadian Journal of Animal Science 86, no. 2 (June 1, 2006): 135–57. http://dx.doi.org/10.4141/a05-010.
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Considerable evidence of climate change associated with emissions of greenhouse gases (GHG) has resulted in international efforts to reduce GHG emissions. The agriculture sector contributes about 8% of GHG emissions in Canada mostly through methane (CH4) and nitrous oxide (N2O). The objective of this paper was to compile an integrative review of CH4 and N2O emissions from livestock by taking a whole cycle approach from enteric fermentation to manure treatment and storage, and field application of manure. Basic microbial processes that result in CH4 production in the rumen and hindgut of animals were reviewed. An overview of CH4 and N2O production processes in manure, and controlling factors are presented. Most of the studies conducted in relation to enteric fermentation were in dairy and beef cattle. To date, research has focussed on GHG emissions from the stored manures of dairy, beef cattle and swine; therefore, we focus our review on these. Several methods used to measure GHG emissions from livestock and stored manure were reviewed. A comparison of methods showed that there were agreements between most of the techniques but some systematic differences were also observed. Additional studies with comprehensive comparisons of methodologies are needed in order to allow for comparison of results obtained from studies using contrasting methodologies. The need to standardize measurement methods and reporting to facilitate comparison of results and data integration was identified. Prediction equations are often used to calculate GHG emissions. Various types of mathematical approaches, such as statistical models, mechanistic models and estimates calculated from emission factors, and studies that compare various types of models are discussed herein. A lack of process-based models describing GHG emissions from manure during storage was identified. A brief description of mitigation strategies focussing on recent studies is given. Reduction in CH4 emissions from ruminants through the addition of fats in diets and the use of more starch was achieved and a transient beneficial effect of ionophores was reported. Grazing management and genetic selection also hold promise. Studies focussed on manure treatment options that thave been suggested to reduce gas fluxes from manure storage, composting, anaerobic digestion (AD), diet manipulation, covers and solid-liquid separation, were reviewed. While some of these options have been shown to decrease GHG emissions from stored manure, different studies have obtained conflicting results, and additional research is needed to identify the most promising options. GHG emissions from pasture and croplands after manure application have been the subject of several experimental and modelling studies, but few of these have linked field emissions to diet manipulation or manure treatments. Further work focussing on the entire cycle of GHG formation from feed formulation, animal metabolism, excreta treatment and storage, to field application of manure needs to be conducted. Key words: Greenhouse gases, enteric methane, nitrous oxide, manure management
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Stainforth, David A., Thomas E. Downing, Richard Washington, Ana Lopez, and Mark New. "Issues in the interpretation of climate model ensembles to inform decisions." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 365, no. 1857 (June 14, 2007): 2163–77. http://dx.doi.org/10.1098/rsta.2007.2073.
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There is a scientific consensus regarding the reality of anthropogenic climate change. This has led to substantial efforts to reduce atmospheric greenhouse gas emissions and thereby mitigate the impacts of climate change on a global scale. Despite these efforts, we are committed to substantial further changes over at least the next few decades. Societies will therefore have to adapt to changes in climate. Both adaptation and mitigation require action on scales ranging from local to global, but adaptation could directly benefit from climate predictions on regional scales while mitigation could be driven solely by awareness of the global problem; regional projections being principally of motivational value. We discuss how recent developments of large ensembles of climate model simulations can be interpreted to provide information on these scales and to inform societal decisions. Adaptation is most relevant as an influence on decisions which exist irrespective of climate change, but which have consequences on decadal time-scales. Even in such situations, climate change is often only a minor influence; perhaps helping to restrict the choice of ‘no regrets’ strategies. Nevertheless, if climate models are to provide inputs to societal decisions, it is important to interpret them appropriately. We take climate ensembles exploring model uncertainty as potentially providing a lower bound on the maximum range of uncertainty and thus a non-discountable climate change envelope. An analysis pathway is presented, describing how this information may provide an input to decisions, sometimes via a number of other analysis procedures and thus a cascade of uncertainty. An initial screening is seen as a valuable component of this process, potentially avoiding unnecessary effort while guiding decision makers through issues of confidence and robustness in climate modelling information. Our focus is the usage of decadal to centennial time-scale climate change simulations as inputs to decision making, but we acknowledge that robust adaptation to the variability of present day climate encourages the development of less vulnerable systems as well as building critical experience in how to respond to climatic uncertainty.
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Betts, Richard A., Matthew Collins, Deborah L. Hemming, Chris D. Jones, Jason A. Lowe, and Michael G. Sanderson. "When could global warming reach 4°C?" Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1934 (January 13, 2011): 67–84. http://dx.doi.org/10.1098/rsta.2010.0292.
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The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) assessed a range of scenarios of future greenhouse-gas emissions without policies to specifically reduce emissions, and concluded that these would lead to an increase in global mean temperatures of between 1.6°C and 6.9°C by the end of the twenty-first century, relative to pre-industrial. While much political attention is focused on the potential for global warming of 2°C relative to pre-industrial, the AR4 projections clearly suggest that much greater levels of warming are possible by the end of the twenty-first century in the absence of mitigation. The centre of the range of AR4-projected global warming was approximately 4°C. The higher end of the projected warming was associated with the higher emissions scenarios and models, which included stronger carbon-cycle feedbacks. The highest emissions scenario considered in the AR4 (scenario A1FI) was not examined with complex general circulation models (GCMs) in the AR4, and similarly the uncertainties in climate–carbon-cycle feedbacks were not included in the main set of GCMs. Consequently, the projections of warming for A1FI and/or with different strengths of carbon-cycle feedbacks are often not included in a wider discussion of the AR4 conclusions. While it is still too early to say whether any particular scenario is being tracked by current emissions, A1FI is considered to be as plausible as other non-mitigation scenarios and cannot be ruled out. (A1FI is a part of the A1 family of scenarios, with ‘FI’ standing for ‘fossil intensive’. This is sometimes erroneously written as A1F1, with number 1 instead of letter I.) This paper presents simulations of climate change with an ensemble of GCMs driven by the A1FI scenario, and also assesses the implications of carbon-cycle feedbacks for the climate-change projections. Using these GCM projections along with simple climate-model projections, including uncertainties in carbon-cycle feedbacks, and also comparing against other model projections from the IPCC, our best estimate is that the A1FI emissions scenario would lead to a warming of 4°C relative to pre-industrial during the 2070s. If carbon-cycle feedbacks are stronger, which appears less likely but still credible, then 4°C warming could be reached by the early 2060s in projections that are consistent with the IPCC’s ‘likely range’.
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Barker, Terry. "Use of energy-environment-economy models to inform greenhouse gas mitigation policy." Impact Assessment and Project Appraisal 16, no. 2 (June 1998): 123–31. http://dx.doi.org/10.1080/14615517.1998.10590197.
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Rashid, Shahzada Mudasir. "Impact of Livestock Enteric Emission on Climate and its Mitigation." Indian Journal of Pure & Applied Biosciences 9, no. 3 (June 30, 2021): 247–56. http://dx.doi.org/10.18782/2582-2845.8737.
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The increase in production of greenhouse gases is a major cause of global warming for which livestock holds a big share in total greenhouse gas emission annually. The greenhouse gases produced by livestock include carbon dioxide, methane, nitrous oxide etc. Cattle and buffalo are the major contributors responsible for 90% emission of GHG followed by sheep and goat. Increase in carbon dioxide emission by livestock, decaying of dung in absence of oxygen, enteric fermentations are the major sources of greenhouse gas production by livestock species. Owing to greenhouse effect, the elevated greenhouse gases cause global warming resulting in the increase of surface temperature of earth, decreased precipitation, and huge damage to environment and affect the flora and fauna turning the conditions on earth unfavorable for survival of living forms. The major impacts are loss of biodiversity, loss of habitat for animals and plants, uncertainty in climate, increase in livestock diseases, damage to feed sources (plants), decrease in productivity of livestock species and many more. Mitigation measures needed to be focused on decreasing the global meat consumption, implementing carbon tax, feeding dietary oils/nitrates, manure management and its biodigestion, genetic manipulations besides strengthening of global livestock environmental assessment models.
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Wei, Dan, Noah Dormady, and Adam Rose. "Development of Reduced-Form Models to Evaluate Macroeconomic Impacts of Greenhouse Gas Mitigation." Journal of Sustainable Energy Engineering 2, no. 4 (April 7, 2015): 377–97. http://dx.doi.org/10.7569/jsee.2015.629503.
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Boehlert, Brent, Ellen Fitzgerald, James E. Neumann, Kenneth M. Strzepek, and Jeremy Martinich. "Effects of Greenhouse Gas Mitigation on Drought Impacts in the United States." Weather, Climate, and Society 7, no. 3 (July 1, 2015): 255–72. http://dx.doi.org/10.1175/wcas-d-14-00020.1.
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Abstract The authors present a method for analyzing the economic benefits to the United States resulting from changes in drought frequency and severity due to global greenhouse gas (GHG) mitigation. The method begins by constructing reduced-form models of the effect of drought on agriculture and reservoir recreation in the contiguous United States. These relationships are then applied to drought projections based on two climate stabilization scenarios and two twenty-first-century time periods. Drought indices are sector specific and include both the standardized precipitation index and the Palmer drought severity index. It is found that the modeled regional effects of drought on each sector are negative, almost always statistically significant, and often large in magnitude. These results confirm that drought has been an important driver of historical reductions in economic activity in these sectors. Comparing a reference climate scenario to two GHG mitigation scenarios in 2050 and 2100, the authors find that, for the agricultural sector, mitigation reduces both drought incidence and damages through its effects on temperature and precipitation, despite regional differences in the sign and magnitude of effects under certain model scenarios. The current annual damages of drought across all sectors have been estimated at $6–$8 billion (U.S. dollars), but this analysis shows that average annual benefits of GHG mitigation to the U.S. agricultural sector alone reach $980 million by 2050 and upward of $2.2 billion by 2100. Benefits to reservoir recreation depend on reservoir location and data availability. Economic benefits of GHG mitigation are highest in the southwestern United States, where drought frequency is projected to increase most dramatically in the absence of GHG mitigation policies.
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Cayambe, Jhenny, and Ana Iglesias. "The cost of mitigating greenhouse gas emissions in farms in Central Andes of Ecuador." Spanish Journal of Agricultural Research 18, no. 1 (April 22, 2020): e0101. http://dx.doi.org/10.5424/sjar/2020181-13807.
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Aim of study: Reduction of the greenhouse gas (GHG) emissions derived from food production is imperative to meet climate change mitigation targets. Sustainable mitigation strategies also combine improvements in soil fertility and structure, nutrient recycling, and the use more efficient use of water. Many of these strategies are based on agricultural know-how, with proven benefits for farmers and the environment. This paper considers measures that could contribute to emissions reduction in subsistence farming systems and evaluation of management alternatives in the Central Andes of Ecuador. We focused on potato and milk production because they represent two primary employment and income sources in the region’s rural areas and are staple foods in Latin America.Area of study: Central Andes of Ecuador: Carchi, Chimborazo, Cañar provincesMaterial and methods: Our approach to explore the cost and the effectiveness of mitigation measures combines optimisation models with participatory methods.Main results: Results show the difference of mitigation costs between regions which should be taken into account when designing of any potential support given to farmers. They also show that there is a big mitigation potential from applying the studied measures which also lead to increased soil fertility and soil structure improvements due to the increased soil organic carbon.Research highlights: This study shows that marginal abatement cost curves derived for different agro-climatic regions are helpful tools for the development of realistic regional mitigation options for the agricultural sector.
Dissertations / Theses on the topic "Greenhouse gas mitigation – Mathematical models"
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Lee, Yu-tao, and 李裕韜。. "A study on greenhouse gases in Hong Kong: sources and mitigation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31254317.
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Enzinger, Sharn Emma 1973. "The economic impact of greenhouse policy upon the Australian electricity industry : an applied general equilibrium analysis." Monash University, Centre of Policy Studies, 2001. http://arrow.monash.edu.au/hdl/1959.1/8383.
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D'AMMARO, DANIELE. "From environmental concerns toward sustainable agro-food production. Mathematical models, indicators to achieve the sustainability of the wine sector." Doctoral thesis, Università Cattolica del Sacro Cuore, 2022. http://hdl.handle.net/10280/115286.
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Il sistema alimentare è sempre più interconnesso con il nostro futuro, il quale include un'ampia varietà di preoccupazioni della società che vanno dalla sicurezza alimentare, alla nutrizione, alle disuguaglianze sociali ed economiche, al cambiamento climatico, alla biodiversità e ai servizi generati dagli ecosistemi oceanici. In particolare, la filiera agroalimentare del vino emerge come una tra le filiere più analizzate data la sua importante rilevanza nel mercato economico produttivo e distributivo mondiale. In accordo con le disposizioni del New Green Deal dell'Unione Europea e dell'Agenda 2030 delle Nazioni Unite, il settore vitivinicolo deve indirizzarsi verso sistemi di gestione economicamente e ambientalmente sostenibili, legati a produzioni di qualità e ad un contesto riconosciuto e remunerato di conservazione della biodiversità. Una corretta scelta dei metodi e delle linee di azione per migliorare la sostenibilità del settore vitivinicolo deve iniziare con un'analisi obiettiva e accurata delle prestazioni di sostenibilità dei suoi prodotti e delle procedure. In questo contesto, la presente tesi mira a una più profonda comprensione delle strategie applicate nel settore vitivinicolo e dei loro risultati. A tal fine, sono state condotte numerose valutazioni, con diversi indicatori impiegati per misurare, monitorare e migliare le prestazioni di sostenibilità.The food system is increasingly interlinked with our future, which includes a wide variety of societal concerns ranging from food security, nutrition, social and economic inequities to climate change, biodiversity, and ocean ecosystem services. In particular, the wine chain emerges as one of the most examined areas given its significant relevance in economic production and global distribution market. In accordance with the provisions of the European Union's New Green Deal and the United Nations Agenda 2030, the wine sector must strive to transition to economically and environmentally sustainable management systems, linked to premium quality production and a recognized and remunerated context of biodiversity conservation. A proper determination of the methods and courses of action to enhance the wine industry's sustainability must begin with an objective and accurate analysis of its products and procedures' sustainability performance. Within this framework, the present thesis aims at a deeper understanding of the strategies applied in the wine sector and of their outcomes. For this purpose, numerous assessments have been conducted, with different indicators used to measure, monitor and improve sustainability performance.
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CESAR, Herman S. J. "The comedy and the tragedy of the commons : control and game models of economic policy regarding the Greenhouse effect." Doctoral thesis, 1993. http://hdl.handle.net/1814/4880.
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Defence date: 29 November 1993Examining board: Prof. Carlo Carraro, University of Venice ; Prof. Aart de Zeeuw, University of Tilburg, co-supervisor ; Prof. Louis Phlips, E.U.I. ; Prof. Mark Salmon, E.U.I., supervisor ; Prof. Alistair Ulph, University of Southampton
PDF of thesis uploaded from the Library digitised archive of EUI PhD theses completed between 2013 and 2017
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Gruber, Douglas S. "Modeling to reduce oil consumption and emissions of greenhouse gases, hydrocarbons, and particulates for the passenger land transport sector of Bangkok." Thesis, 2007. http://hdl.handle.net/10125/20602.
Full textBooks on the topic "Greenhouse gas mitigation – Mathematical models"
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F, Javier Hanna. Aplicación del modelo markal macro en Bolivia: Pirmera fase. La Paz, Bolvia: Programa Nacional de Cambios Climaticos, 2003.
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Environmental and Water Resources Institute (U.S.), ed. Climate change modeling, mitigation, and adaptation. Reston, Virginia: American Society of Civil Engineers, 2013.
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Schneider, Uwe A. Greenhouse gas mitigation through energy crops in the United States with implications for Asian-Pacific countries. Ames, IA: Center for Agricultural and Rural Development, Iowa State University, 2001.
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Peter, Markewitz, and Forschungszentrum Jülich Programmgruppe Technologiefolgenforschung, eds. Modelle für die Analyse energiebedingter Klimagasreduktionsstrategien. Jülich: Forschungszentrum Jülich, 1998.
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Strategic bargaining and cooperation in greenhouse gas mitigations: An integrated assessment modeling approach. Cambridge, MA: MIT Press, 2008.
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National Research Council (U.S.). Division on Engineering and Physical Sciences, ed. Modeling the economics of greenhouse gas mitigation: Summary of a workshop. Washington, D.C: National Academies Press, 2011.
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Taylor, Richard. Impacts of greenhouse gas emission regulations on the U.S. sugar industry. Fargo, N.D: Center for Agricultural Policy and Trade Studies, Dept. of Agribusiness and Applied Economics, North Dakota State University, 2010.
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National Research Council (U.S.). Transportation Research Board, National Cooperative Freight Research Program, and United States. Dept. of Transportation. Research and Innovative Technology Administration, eds. Representing freight in air quality and greenhouse gas models. Washington, D.C: Transportation Research Board, 2010.
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E, Schlesinger M., and Workshop on Greenhouse-Gas-induced Climatic Change: A Critical Appraisal of Simulations and Observations (1989 : University of Massachusetts, Amherst), eds. Greenhouse-gas-induced climatic change: A critical appraisal of simulations and observations. Amsterdam: Elsevier, 1991.
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1950-, Berck Peter, California Energy Commission. Public Interest Energy Research., and University of California, Berkeley. Dept. of Agricultural and Resource Economics., eds. Policy options for greenhouse gas mitigation in California: Preliminary results from a new social accounting matrix and computable general equilibrium (CGE) model : PIER final project report. [Sacramento, Calif.]: California Energy Commission, 2008.
Find full textBook chapters on the topic "Greenhouse gas mitigation – Mathematical models"
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Mannina, G., and A. Cosenza. "Comparison of Two Mathematical Models for Greenhouse Gas Emission from Membrane Bioreactors." In Lecture Notes in Civil Engineering, 662–67. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58421-8_104.
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Hillier, Jon, Mohammed Abdalla, Jessica Bellarby, Fabrizio Albanito, Arindam Datta, Marta Dondini, Nuala Fitton, et al. "Mathematical Modeling of Greenhouse Gas Emissions from Agriculture for Different End Users." In Synthesis and Modeling of Greenhouse Gas Emissions and Carbon Storage in Agricultural and Forest Systems to Guide Mitigation and Adaptation, 197–227. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/advagricsystmodel6.2013.0038.
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Leemans, R. "Determining the Global Significance of Local and Regional Mitigation Strategies: Setting the Scene with Global Integrated Assessment Models." In African Greenhouse Gas Emission Inventories and Mitigation Options: Forestry, Land-Use Change, and Agriculture, 99–110. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-009-1637-1_7.
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Unluturk, Burcu, and Anna Krook-Riekkola. "Energy System Models for City Climate Mitigation Plans—Challenges and Recommendations." In Smart and Sustainable Planning for Cities and Regions, 15–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-57764-3_2.
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AbstractMany cities around the world have adopted climate neutrality targets, and, to reduce their greenhouse gas emissions, they need climate action plans. Energy system optimization models (ESOMs) can be used as tools to support their energy transitions. ESOMs have been in use at the national level for several years and also have recently been used at the city level. Even though several researchers have focused on how city ESOMs can be developed, the literature lacks a discussion of the challenges that are faced in data collection during model development. In this paper, we share the challenges encountered in the model development, as well as in the scenario development and recommend practical solutions for overcoming these challenges. The following three challenges were identified and discussed in the model development process: (a) data availability and quality; (b) communication; and (c) knowledge and background of civil servants and researchers. The main challenges in the scenario development were: (a) parameter selection and (b) complexity. It was found that explanation of the terminology used in ESOMs, presentation of the model structure and preliminary base-year results were crucial actions for overcoming challenges during model development. During the scenario development, collaboration between modelers and civil servants when reviewing parameter combinations and working with preliminary scenario results were decisive strategies for improving the civil servants’ understanding of ESOMs. Complementarily, it was found that continuous communication between the researcher and the civil servant and good comprehension of the model on the municipality's side helped improve the usefulness of ESOMs in cities’ energy transitions.
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Maire, Juliette, Peter Alexander, Peter Anthoni, Chris Huntingford, Thomas A. M. Pugh, Sam Rabin, Mark Rounsevell, and Almut Arneth. "A New Modelling Approach to Adaptation-Mitigation in the Land System." In Springer Climate, 133–40. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86211-4_16.
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AbstractClimate change, growing populations and economic shocks are adding pressure on the global agricultural system’s ability to feed the world. In addition to curbing the emissions from fossil fuel use, land-based actions are seen as essential in the effort to mitigate climate change, but these tend to reduce areas available for food production, thereby further increasing this pressure. The actors of the food system have the capacity to respond and adapt to changes in climate, and thereby reduce the negative consequences, while potentially creating additional challenges, including further greenhouse gas emissions. The food system actors may respond autonomously based on economic drivers and other factors to adapt to climate change, whereas policy measures are usually needed for mitigation actions to be implemented. Much research and policy focus has been given to land-based climate change mitigation, but far less emphasis has to date been given to the understanding of adaptation, or the interaction between adaptation and mitigation in the land use and food system. Here, we present an approach to better understand and plan these interactions through modelling. Climate change adaptation and mitigation strategies and the impacts on the global food system and socio-economic development can be simulated over long-term predictions, thanks to the new combination of multiple models into the Land System Modular Model (LandSyMM). LandSyMM takes into account the impacts in changes in climate (i.e. temperature, precipitation, atmospheric greenhouse gas concentrations) and land management on crop yields with its implications for land allocation, food security and trade. This new coupled model integrates, over fine spatial scale, the interactions between commodities consumption, land use management, vegetation and climate into a worldwide dynamic economic system. This study offers an outline description of the LandSyMM as well as the perspectives of uses for climate adaptation assessment.
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Grant, Brian B., Ward N. Smith, Con A. Campbell, Raymond L. Desjardins, Reynald L. Lemke, Roland Kröbel, Brian G. McConkey, Elwin G. Smith, and Guy P. Lafond. "Comparison of DayCent and DNDC Models: Case Studies Using Data from Long-Term Experiments on the Canadian Prairies." In Synthesis and Modeling of Greenhouse Gas Emissions and Carbon Storage in Agricultural and Forest Systems to Guide Mitigation and Adaptation, 21–57. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/advagricsystmodel6.2013.0035.
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"Using biogeochemical process models to quantify greenhouse gas mitigation from agricultural management: Lydia P. Olander." In Climate Change Mitigation and Agriculture, 255–69. Routledge, 2013. http://dx.doi.org/10.4324/9780203144510-30.
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N., Manyowa, James R., Kathrine D., Meghan N. Pawlowski, and Susan E. "The Role of Simulation Models in Monitoring Soil Organic Carbon Storage and Greenhouse Gas Mitigation Potential in Bioenergy Cropping Systems." In CO2 Sequestration and Valorization. InTech, 2014. http://dx.doi.org/10.5772/57177.
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Cosmi, C., S. Di Leo, S. Loperte, F. Pietrapertosa, M. Salvia, M. Macchiato, and V. Cuomo. "Comprehensive Energy Systems Analysis Support Tools for Decision Making." In Green Technologies, 493–514. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-472-1.ch307.
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Sustainability of energy systems is a common priority that involves key issues such as security of energy supply, mitigation of environmental impacts - the energy sector is currently responsible for 80% of all EU greenhouse gas emissions (European Environment Agency, 2007), contributing heavily to the overall emissions of local air pollutants - and energy affordability. In this framework, energy planning and decision making processes can be supported at different stages and spatial scales (regional, national, pan-European, etc.) by the use of comprehensive models in order to manage the large complexity of energy systems and to define multi-objective strategies on the medium-long term. This Chapter is aimed to outline the value of model-based decision support systems in addressing current challenges aimed to carry out sustainable energy systems and to diffuse the use of strategic energy-environmental planning methods based on the use of partial equilibrium models. The proposed methodology, aimed to derive cost-effective strategies for a sustainable resource management, is based on the experiences gathered in the framework of the IEA-ETSAP program and under several national and international projects.
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ur Rehman, Obaid, Nor Erniza Mohammad Rozali, and Marappa Gounder Ramasamy. "Fouling and Mechanism." In Heat Transfer [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.105878.
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Fouling is the deposition of material on the heat transfer surface which reduces the film heat transfer coefficient. The impact of fouling on the heat exchanger is manifested as the reduction of thermal and hydraulic performance, in which the latter has a minor effect. This factor needs to be considered when calculating the effectiveness of the heat exchanger. During the design of heat exchangers, the fouling factor increases the required heat transfer area, which adds extra manufacturing costs. With less efficient heat exchangers, the economic cost of fouling is related to excess fuel consumption, loss of production, and maintenance or cleaning. The extra fuel consumption also damages the environment by increasing greenhouse gas production. Although much of the research work has been done on modeling and predicting fouling, it is still a poorly understood phenomenon representing the complexity of its mechanism. The common fouling mitigation action after the onset of fouling is to optimize the operating condition, e.g., increase the bulk flow velocity or decrease surface temperature. However, many quantitative and semi-empirical models have been developed to predict the fouling rate for preventive actions and optimizing cleaning schedules.
Conference papers on the topic "Greenhouse gas mitigation – Mathematical models"
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Chidambram, Siva Kumaran, Jin An Tan, Mohd Amaluddin Yusoff, and June Janesby Roy Jihok. "Predictive Analytics for Gas Turbine Driven Trains to Achieve Optimum Performance, Economics and Greenhouse Gas Emissions." In Offshore Technology Conference Asia. OTC, 2022. http://dx.doi.org/10.4043/31489-ms.
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Abstract The current gas turbine performance monitoring infrastructure in Shell Malaysia yields inaccuracies of ±15% with no links towards emissions and fuel economics. This has resulted in severe limitations towards the ability to improve greenhouse gas (GHG) performance and generate value. This paper describes a novel, data centric approach to derive meaningful insights and economics/carbon savings from existing data on Plant Information (PI) and SMART CONNECT, a Shell in house performance management IT tool. This project applies advanced analytics techniques based on historical data, supplemented by engineering performance models to derive robust outcomes. First, gas turbine and compressor modelling principles are programmed in Python and validated with engineering software such as UNISIM based on available operating data via PI. This yields a multivariate dataset tabulating the historical efficiency, power and fuel gas consumption of the fleet. The model is then utilized in a mathematical optimization algorithm and the optimized data used for training and validation of a Random Forest Regressor model. The performance model in Python is able to achieve accuracies of <1% absolute error when validated with UMSFM on the key performance parameters. Through parametric optimization, the Mean Squared Error (MSE) of the gas turbine and compressor powers is reduced to 0.55MW2 from its original 4.94MW2. The Heat Rate, Shaft Power, and gas generator exit pressures are also identified as the variables most correlated with efficiency. Lastly, the trained machine learning model demonstrated agreement with the dataset during testing, with a R2 value of 0.86 reflecting a strong correlation. With a predictive digital model in place, production programmers can accurately identify the key levers to optimize the machine operating point for optimum fuel gas consumption. Optimizing Gumusut Kakap's high pressure compressors can yield 62,400 USD in savings per annum from increased sales gas and and 880 tCO2e per annum of reduction in GHG emissions, for every 1% increase in efficiency. This approach is a novel concept, leveraging on expertise from both engineering and data science to enhance equipment performance, and can be replicated towards other types of equipment to achieve efficiency, economic and emissions improvements at scale.
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Di, Lei, Gaurav Manish Shah, Yiran Yang, and Cuicui Wei. "Greenhouse Gas Emission Analysis of Integrated Production-Inventory-Transportation Supply Chain Enabled by Additive Manufacturing." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-63822.
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Abstract The manufacturing industry is a major source of greenhouse gas emissions (GHG). Additive manufacturing, owing to its multiple advantages, plays a critical role in innovating the current manufacturing industry, especially from a supply chain perspective. Currently, the majority of research on GHG emissions in the manufacturing industry is focused on traditional manufacturing, either single processes in the supply chain or specific case studies, indicating the lack of models on GHG emissions in additive manufacturing-enabled supply chain structures. In this work, a mathematical model is established to estimate the GHG emissions in both traditional manufacturing and additive manufacturing-enabled supply chains. To explore the advantages of additive manufacturing in terms of fast production and reduced or even eliminated the need for assembly and labor involvement, a unique integrated production-inventory-transportation structure is investigated in additive manufacturing case studies. The results indicate that a potential reduction of 26.43% of GHG emissions can be achieved by adopting the additive manufacturing technique in the supply chain. Also, the impacts of rush order rate, emission intensity, and vehicle GHG emission constant rate on the overall GHG emissions are investigated in the sensitivity analysis. Results indicate that a 20% variation in GHG emission intensity (the amount of CO2eq emissions caused by generating a unit of electricity) can lead to a 6.26% change in the total GHG emissions in additive manufacturing.
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Gu¨len, S. Can. "A Simple Parametric Model for the Analysis of Cooled Gas Turbines." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-22160.
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A natural gas fired gas turbine combined cycle power plant is the most efficient option for fossil fuel based electric power generation that is commercially available. Trade publications report that currently available technology is rated near 60% thermal efficiency. Research and development efforts are in place targeting even higher efficiencies in the next two decades. In the face of diminishing natural resources and increasing carbon dioxide emissions, leading to greenhouse gas effect and global warming, these efforts are even more critical today than in the last century. The main performance driver in a combined cycle power plant is the gas turbine. The basic thermodynamics of the gas turbine, described by the well-known Brayton cycle, dictates the key design parameters that determine the gas turbine performance are the cycle pressure ratio and maximum cycle temperature at the turbine inlet. While performance calculations for an ideal gas turbine are straightforward with compact mathematical formulations, detailed engineering analysis of real machines with turbine hot gas path cooling requires complex models. Such models, requisite for detailed engineering design work, involve highly empirical heat transfer formulations embedded in a complex system of equations that are amenable only to numerical solutions. A cooled turbine modeling system incorporating all pertinent physical phenomena into compact formulations is developed and presented in this paper. The model is fully physics-based and amenable to simple spreadsheet calculations while illustrating the basic principles with sufficient accuracy and extreme qualitative rigor. This model is valuable not only as a teaching and training tool it is also suitable to preliminary gas turbine combined cycle design calculations in narrowing down the field of feasible design options.
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Roy, Arjun, Sangeeta Nundy, Okja Kim, and Godine Chan. "Emission Source Detection and Leak Rate Estimation Using Point Measurements of Concentration." In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22377-ea.
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Abstract Introduction With the advent of global climate change, it has become incumbent on governments and industries to monitor and limit greenhouse gas emissions to prevent a catastrophic rise in the average global temperature. The Paris agreement [Paris 2015] aims to lower global greenhouse gas emissions by 40% (in comparison to greenhouse gas levels observed in 1990) by 2030. Methane is a greenhouse gas whose 100- year global warming potential is 25 times that of carbon dioxide [GWP] and whose atmospheric concentration has been increasing since 2007 [Nisbet 2016, Theo Stein, et al. 2021]. Thus, there is an increased requirement on industries from government regulators to detect, localize, quantify and mitigate both fugitive and vented emissions of methane. There are several different technologies that are available for automated methane emissions management. These include arial and ground-based mobile sensing units that are based on optical-gas imaging, satellite-based imagery [Jacob et al. 2016] and stationary metal-oxide based sensors. A key criterion that often needs to be satisfied is continuous monitoring for early detection and mitigation of fugitive leaks. Fixed metal-oxide based sensors [Yuliarto et al. (2015), Zeng et al. (2019), Yunusa et al. (2014), Potyrailo et al. (2020), Wang et al. (2010) and Feng et al. (2019)] are low-cost sensors that can be used for continuous monitoring of a site and are typically used for detection of leaks and alerting. The main challenge is to extend utility of these sensors to not only detect presence of fugitive and vented emissions, but also be able to estimate the number of leak sources and their probable locations and the total volume of hydrocarbon leaked over a period. This paper describes an approach used for detecting anomalies in emission data, identifying possible emission sources, and estimating emission leak rates using point measurements of concentration collected over a period along with measurements of wind speed and direction. This involves multiple analytics that combine concentration and wind-condition time-series data with physics models to predict the different outcomes.
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Tokarev, Denis, Dmitry Tailakov, and Anton Ablaev. "Digital platform for E&P Assets Business Process Optimization with a Module for Estimation and Optimizing of Greenhouse Gases Emissions. Case Study." In SPE Russian Petroleum Technology Conference. SPE, 2021. http://dx.doi.org/10.2118/206607-ms.
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Resume Due to the increasing requirements for reducing the carbon footprint on the part of end users of hydrocarbons, there is a need to develop a system for automated analysis of the main business processes of oil and gas field development to assess greenhouse gas emissions, as well as for optimization in order to improve environmental safety. The paper describes a prototype of a platform that was developed for decarbonization of oil and gas enterprises using modern optimization tools and up-to-date methods for inventory of greenhouse gas emissions. The platform is based on the following models: – simulation model (IM) – simulates the company's business processes, identifying weaknesses and areas of potential development, is a set of mathematical algorithms for solving direct problems; – optimization model (OM) – allows to conduct a comprehensive analysis with a large number of parameters, excluding manual data processing and using automated information exchange between various software that is used in the oil and gas industry for modeling and monitoring of various processes, as well as developing various development options (taking into account geological conditions, geophysical interpretation, etc.). The initial conditions and the specified criteria related to economic indicators allow to solve the problem of finding the optimal parameters for the development of the selected asset. This paper shows the economic effect of implementing software based on a digital twin, implemented as a platform with the ability to build a model of an oil and gas asset, using various data (SAP, 1C, IPM GAP, Repos, Eclipse, etc.) and targets for the development. In the same way, the possible losses of the oil and gas industry from the introduction of additional carbon taxation and the potential for optimizing processes to minimize these costs are considered. IPCC methods are used to calculate greenhouse gas emissions, and direct, indirect, and fugitive emissions are considered in the calculation. The main conclusion is the need to reduce the costs for oil and gas companies and prepare modern automated digital solutions for accounting for greenhouse gas emissions in advance to achieve a zero-carbon footprint and maintain the competitiveness of the Russian oil and gas industry. As a result of the work done, the feasibility was justified, and the result was demonstrated to the customer for calculating greenhouse gas emissions based on digital twins of key business processes of oil and gas enterprises. The use of automated systems makes it possible to reduce the potential economic risks associated with the introduction of a carbon fee from large oil and gas consumers.
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Tewari, Raj Deo, Chee Phuat Tan, and M. ohd Faizal Sedaralit. "A Toolkit for Carbon Capture and Storage in Offshore Depleted Gas Field." In Offshore Technology Conference Asia. OTC, 2022. http://dx.doi.org/10.4043/31651-ms.
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Abstract Carbon dioxide (CO2) capture, utilization, and storage is the best option for mitigating atmospheric emissions of CO2 and thereby controlling the greenhouse gas concentrations in the atmosphere. Despite the benefits, there have been a limited number of projects solely for CO2 sequestration being implemented. The industry is well-versed in gas injection in reservoir formation for pressure maintenance and improving oil recovery. However, there are striking differences between the injection of CO2 into depleted hydrocarbon reservoirs and the engineered storage of CO2. The differences and challenges are compounded when the storage site is karstified carbonate in offshore and bulk storage volume. It is paramount to know upfront that CO2 can be stored at a potential storage site and demonstrate that the site can meet required storage performance safety criteria. Comprehensive screening for site selection has been carried out for suitable CO2 storage sites in offshore Sarawak, Malaysia using geographical, geological, geophysical, geomechanical and reservoir engineering data and techniques for evaluating storage volume, container architecture, pressure, and temperature conditions. The site-specific input data are integrated into static and dynamic models for characterization and generating performance scenarios of the site. In addition, the geochemical interaction of CO2 with reservoir rock has been studied to understand possible changes that may occur during/after injection and their impact on injection processes/mechanisms. Novel 3-way coupled modelling of dynamic-geochemistry-geomechanics processes were carried out to study long-term dynamic behaviour and fate of CO2 in the formation. The 3-way coupled modelling helped to understand the likely state of injectant in future and the storage mechanism, i.e., structural, solubility, residual, and mineralized trapping. It also provided realistic storage capacity estimation, incorporating reservoir compaction and porosity/permeability changes. The study indicates deficient localized plastic shear strain in overburden flank fault whilst all the other flaws remained stable. The potential threat of leakage is minimal as target injection pressure is set at initial reservoir pressure, which is much lower than caprock breaching pressure during injection. Furthermore, it was found that the geochemical reaction impact is shallow and localized at the top of the reservoir, making the storage safe in the long term. The integrity of existing wells was evaluated for potential leakage and planned for a proper mitigation plan. Comprehensive measurement, monitoring, and verification (MMV) were also designed using state-of-art tools and dynamic simulation results. The understanding gaps are closed with additional technical work to improve technologies application and decrease the uncertainties. A comprehensive study for offshore CO2 storage projects identifying critical impacting elements is crucial for estimation, injection, containment, and monitoring CO2 plume. The information and workflow may be adopted to evaluate other CO2 projects in both carbonate and clastic reservoirs for long-term problem-free storage of greenhouse gas worldwide.
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Patel, Shreyas M., Paul T. Freeman, and John R. Wagner. "An Electrical Microgrid: Integration of Solar Panels, Compressed Air Storage, and a Micro-Cap Gas Turbine." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-6058.
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Non-renewable energy sources such as coal, oil, and natural gas are being consumed at a brisk pace while greenhouse gases contribute to atmospheric pollution. A global shift is underway toward the inclusion of renewable energy sources, such as solar and wind, for generating electrical and mechanical power. To meet this emerging demand, a solar based electrical microgrid study is underway at Clemson University. Solar energy is harvested from photovoltaic panels capable of producing 15 kW of DC power. Compressed air energy storage has been evaluated using the generated solar power to operate an electric motor driven piston compressor. The compressed air is then stored under pressure and supplied to a natural gas driven Capstone C30 MicroTurbine with attached electric power generator. The compressed air facilitates the turbine’s rotor-blade operated compression stage resulting in direct energy savings. A series of mathematical models have been developed. To evaluate the feasibility and energy efficiency improvements, the experimental and simulation results indicated that 127.8 watts of peak power was delivered at 17.5 Volts and 7.3 Amps from each solar panel. The average power generation over a 24-hour time period from 115 panels was 15 kW DC or 6 kW of AC power at 208/240 VAC and 25 Amps from the inverter. This electrical power could run a 5.2 kW reciprocating compressor for approximately 5 hours storing 1,108 kg of air at a 1.2 MPa pressure. A case study indicated that the microturbine, when operated without compressed air storage, consumed 11.2 kg of gaseous propane for 30 kW·hr of energy generation. In contrast, the microturbine operated in conjunction with solar supplied air storage could generate 50.8 kW·hr of electrical energy for a similar amount of fuel consumption. The study indicated an 8.1% efficiency improvement in energy generated by the system which utilized compressed air energy storage over the traditional approach.
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Choudhury, Shiny, Vincent G. McDonell, and Scott Samuelsen. "Performance of Low-NOx and Conventional Storage Water Heaters Operated on Biogas and Natural Gas." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-69702.
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Abstract The U.S. has high renewable methane potential. Biogas can be obtained from many organic sources like landfills, wastewater, animal manure, industrial, institutional, and commercial organic waste. Biogas can also be produced from lignocellulosic biomass; also, there is attention in biofuel and biogas production from various kinds of algae. In the U.S., 5% of the natural gas utilized in the electric power sector and 56% of the natural gas in transportation can be directly replaced with biogas. In a typical Californian household, around 50% of the 354 therms Natural Gas energy supplied goes to water heating. Hence, a large amount of emission from residential spaces is due to water heating units. Introducing renewable natural gas (RNG) or biomethane to natural gas pipelines has shown great potential for greenhouse gas mitigation. However, the upgrade process is energy and cost intensive. Assuming primary biogas composition as methane (CH4) and carbon dioxide (CO2), an understanding of the tolerance for residential appliances (significant pipeline delivery point use) to biogas addition could save cleaning/upgrading costs. Focusing on the combustion performance of two representative models of storage water heaters (low-NOx and conventional) in California, this research addresses how much CO2 in natural gas can be tolerated without losing critical performance parameters for reliable operation. Characteristics like blow-off, ignition time, flame structure, efficiency, and emissions (NOx, NO, N2O, CO, CO2, UHC, CH4, and NH3) at different concentrations of CO2 in natural gas are investigated. The pilot operation becomes unstable for the low-NOx water heater beyond 10% CO2, and the probability of blow-off increases. At both 5% and 10% CO2 addition, a stable though the increasingly flat flame is observed, and pilot operation is stable both during idling and while the main burner relights. For the conventional gas storage water heater, a stable flame is established up to 25% CO2 addition, with the flame becoming increasingly shorter beyond 30% CO2 addition. On the other hand, the stable pilot operation could not be established even at 5% CO2 addition, which proved to be the limiting factor for the operation of this device. A similar trend of NOx/NO decrease and CO/UHC increase with increasing CO2 percentage was observed for both water heaters. Further, methane emissions from water heaters during active and idle operations and pilot light’s role were quantified. The present study show 10% CO2 can be added to natural gas without any significant loss of efficiency for the low-NOx storage water heater. We found that both the water heaters emit CH4 during active and idle operation, of which more CH4 is emitted during the idle process. This study can inform policymakers on allowing higher composition variability for the pipeline gas and research into modifying water heater burners for increased tolerance to biogas with reliable performance and a simultaneous decrease in pollutant emissions.
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Patil, Parimal A., Prasanna Chidambaram, M. Syafeeq Bin Ebining Amir, Pankaj K. Tiwari, Debasis P. Das, Mahesh S. Picha, M. Khaidhir B A Hamid, and Raj Deo Tewari. "FEP Based Model Development for Assessing Well Integrity Risk Related to CO2 Storage in Central Luconia Gas Fields in Sarawak." In International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21472-ms.
Full textAbstract:
Abstract Underground storage of CO2 in depleted gas reservoirs is a greenhouse gas reduction technique that significantly reduces CO2 released into the atmosphere. Three major depleted gas reservoirs in Central Luconia gas field, located offshore Sarawak, possess good geological characteristics needed to ensure long-term security for CO2 stored deep underground. Long-term integrity of all the wells drilled in these gas fields must be ensured in order to successfully keep the CO2 stored for decades/centuries into the future. Well integrity is often defined as the ability to contain fluids without significant leakage through the project lifecycle. In order to analyze the risk associated with all 38 drilled wells, that includes 11 plugged and abandoned (P&A) wells and 27 active wells, probabilistic risk assessment approach has been developed. This approach uses various leakage scenarios, that includes features, events, and processes (FEP). A P&A well in a depleted reservoir is a very complex system in order to assess the loss of containment as several scenarios and parameters associated to those scenarios are difficult to estimate. Based on the available data of P&A wells, a well has been selected for this study. All the barriers in the example well have been identified and properties associated with those barriers are defined in order to estimate the possible leakage pathways through the identified barriers within that well. Detailed mathematical models are provided for estimating CO2 leakage from reservoir to the surface through all possible leakage pathways. Sensitivity analysis has been carried out for critical parameters such as cement permeability, and length of cement plug, in order to assess the containment ability of that well and understand its impact on overall well integrity. Sensitivity analysis shows that permeability of the cement in the annulus, and length of cement plug in the wellbore along with pressure differential can be used as critical set of parameters to assess the risk associated with all wells in these three fields. Well integrity is defined as the ability of the composite system (cemented casings string) in the well to contain fluids without significant leakage from underground reservoir up to surface. It has been recognized as a key performance factor determining the viability of any CCS project. This is the first attempt in assessing Well Integrity risk related to CO2 storage in Central Luconia Gas Fields in Sarawak. The wells have been looked individually in order to make sure that integrity is maintained, and CO2 is contained underground for years to come.
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Tewari, Raj Deo, Chee Phuat Tan, and M. Faizal Sedaralit. "A Toolkit for Offshore Carbon Capture and Storage CCS." In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22307-ms.
Full textAbstract:
Abstract Carbon dioxide (CO2) capture, utilization, and storage is the best option for mitigating atmospheric emissions of CO2 and thereby controlling the greenhouse gas concentrations in the atmosphere. Despite the benefits, there have been a limited number of projects solely for CO2 sequestration being implemented. The industry is well-versed in gas injection in reservoir formation for pressure maintenance and improving oil recovery. However, there are striking differences between the injection of CO2 into depleted hydrocarbon reservoirs and the engineered storage of CO2. The differences and challenges are compounded when the storage site is karstified carbonate in offshore and bulk storage volume. It is paramount to know upfront that CO2 can be stored at a potential storage site and demonstrate that the site can meet required storage performance safety criteria. Comprehensive screening for site selection has been carried out for suitable CO2 storage sites in offshore Sarawak, Malaysia using geographical, geological, geophysical, geomechanical and reservoir engineering data and techniques for evaluating storage volume, container architecture, pressure, and temperature conditions. The site-specific input data are integrated into static and dynamic models for characterization and generating performance scenarios of the site. In addition, the geochemical interaction of CO2 with reservoir rock has been studied to understand possible changes that may occur during/after injection and their impact on injection processes/mechanisms. Novel 3-way coupled modelling of dynamic-geochemistry-geomechanics processes were carried out to study long-term dynamic behaviour and fate of CO2 in the formation. The 3-way coupled modelling helped to understand the likely state of injectant in future and the storage mechanism, i.e., structural, solubility, residual, and mineralized trapping. It also provided realistic storage capacity estimation, incorporating reservoir compaction and porosity/permeability changes. The study indicates deficient localized plastic shear strain in overburden flank fault whilst all the other flaws remained stable. The potential threat of leakage is minimal as target injection pressure is set at initial reservoir pressure, which is much lower than caprock breaching pressure during injection. Furthermore, it was found that the geochemical reaction impact is shallow and localized at the top of the reservoir, making the storage safe in the long term. The integrity of existing wells was evaluated for potential leakage and planned for a proper mitigation plan. Comprehensive measurement, monitoring, and verification (MMV) were also designed using state-of-art tools and dynamic simulation results. The understanding gaps are closed with additional technical work to improve technologies application and decrease the uncertainties. A comprehensive study for offshore CO2 storage projects identifying critical impacting elements is crucial for estimation, injection, containment, and monitoring CO2 plume. The information and workflow may be adopted to evaluate other CO2 projects in both carbonate and clastic reservoirs for long-term problem-free storage of greenhouse gas worldwide.
Reports on the topic "Greenhouse gas mitigation – Mathematical models"
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Alexander, Serena E., Mariela Alfonzo, and Kevin Lee. Safeguarding Equity in Off-Site Vehicle Miles Traveled (VMT) Mitigation in California. Mineta Transportation Institute, November 2021. http://dx.doi.org/10.31979/mti.2021.2027.
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Historically, the State of California assessed the environmental impacts of proposed developments based on how it was projected to affect an area’s level of service (LOS). However, as LOS focused on traffic delays, many agencies simply widened roads, which was an ineffective way to reduce greenhouse gas emissions (GHGs). With the passage of Senate Bill (SB)743 in 2013, LOS was replaced by Vehicle Miles Traveled (VMT) as a more appropriate metric by which to gauge the environmental impacts of proposed development. Additionally, SB 743 presented an opportunity for off-site VMT mitigation strategies through banking and exchanges– allowing multiple development projects to fund a variety of strategies to reduce VMT elsewhere in the city or region. While the shift from LOS to VMT has generally been lauded, concerns remain about how to apply SB 743 effectively and equitably. This study aimed to: 1) understand how local governments are addressing this shift toward VMT while ensuring equity, including its approaches to off-site VMT mitigation; and 2) evaluate the various built environment factors that impact VMT, which should be considered by local governments, using both qualitative and quantitative research designs. The study posited that both micro and macro level aspects of the built environment needed to be considered when evaluating the impacts of proposed development on VMT, not only to ensure higher accuracy VMT models, but also because of the potential equity implications of off-site mitigation measures. Using multiple linear regression, the study shows that macroscale built environment features such as land use, density, housing, and employment access have a statistically significant impact on reducing VMT (35%), along with transit access (15%), microscale features such as sidewalks, benches, and trees (13%), and income (6%). More notably, a four-way interaction was detected, indicating that VMT is dependent on the combination of macro and micro level built environment features, public transit access, and income. Additionally, qualitative interviews indicate that transportation practitioners deal with three types of challenges in the transition to VMT impact mitigation: the lack of reliable, standardized VMT measure and evaluation tools; the lack of a strong legal foundation for VMT as a component of the California Environmental Quality Act (CEQA); and the challenge of distributing off-site VMT mitigation equitably. Overall, findings support a nuanced, multi-factor understanding of the context in which new developments are being proposed, both in terms of modeling VMT, but also when considering whether offsite mitigation would be appropriate. The results of this study can help California ensure equitable VMT mitigation that better aligns with the state’s climate goals.
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Aalto, Juha, and Ari Venäläinen, eds. Climate change and forest management affect forest fire risk in Fennoscandia. Finnish Meteorological Institute, June 2021. http://dx.doi.org/10.35614/isbn.9789523361355.
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Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.