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PR, IFPRI3; ISI; CRP2; 1 Fostering Climate-Resilient and Sustainable Food Supply; DCA; CRP3.4; CRP3.5; CRP7; Global Futures and Strategic Foresight, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM); CGIAR Research Program on Grain Legumes; CGIAR Research Program on Dryland Systems; CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Groundnut is one of the significant sources of oil, food, and fodder in India. It is grown in marginal arid and semi-arid agro-ecosystems with wide yield fluctuations due to spatial variability of rainfall and soil. Climate change, which is predicted to increase the intra- and inter-annual rainfall variability will further constrain the groundnut economy in India besides the global and domestic economic, social and policy changes. Through this study we aim to examine the biophysical and social economic impacts of climate change on groundnut production and prices to provide a comprehensive analysis of how agriculture and the food system will be affected. Using projected climate data for India, we estimated the biophysical impacts of climate change on groundnut during mid-century using representative concentration pathway (RCP 8.5) scenario. We examined the impacts of changes in population and income besides environmental factors on groundnut productivity. This is to highlight the importance of holistic assessment of biophysical and socioeconomic factors to better understand climate change impacts. Modelled projections show that by 2050, climate change under an optimistic scenario will result in -2.3 to 43.2 percent change in groundnut yields across various regions in India when climate alone was factored in. But the change in groundnut yields ranged from -0.9 percent to 16.2 percent when economic (population and income) and market variables (elasticities, trade, etc.) were also considered. Similarly, under pessimistic climate change scenario, the percent change in groundnut yields would be -33.7 to 3.4 with only the climate factored in and -11.2 to 4.3 with the additional economic and market variables included. This indicates the sensitivity of climate change impacts to differences in socioeconomic factors. This study highlights the need to take into account market effects to gain a holistic understanding of how economic and environmental factors impact agricultural

This paper presents a new framework for the modeling of coal-fired boiler furnaces. The input required for the model is the ultimate analysis of a coal sample. The model accounts for devolatilization followed by gas-phase combustion. The devolatilization model used in this work is taken from published literature with slight modifications to match the numerical predictions with experimental measurements. This work also develops a reactor network model for simulating the performance of boiler furnaces. For the seamless integration of kinetic models of coal devolatilization and combustion with furnace numerical model, the thermochemistry data of several hypothetical and intermediate species involved in devolatilization chemistry are evaluated in the form of 14 coefficient National Aeronautics and Space Administration polynomials. The capability of the model for predicting the furnace temperature and product composition is demonstrated by simulating a single-zone model.

This paper presents a new framework for the modeling of coal-fired boiler furnaces. The input required for the model is the ultimate analysis of a coal sample. The model accounts for devolatilization followed by gas-phase combustion. The devolatilization model used in this work is taken from published literature with slight modifications to match the numerical predictions with experimental measurements. This work also develops a reactor network model for simulating the performance of boiler furnaces. For the seamless integration of kinetic models of coal devolatilization and combustion with furnace numerical model, the thermochemistry data of several hypothetical and intermediate species involved in devolatilization chemistry are evaluated in the form of 14 coefficient National Aeronautics and Space Administration polynomials. The capability of the model for predicting the furnace temperature and product composition is demonstrated by simulating a single-zone model.

This paper presents a new framework for the modeling of coal-fired boiler furnaces. The input required for the model is the ultimate analysis of a coal sample. The model accounts for devolatilization followed by gas-phase combustion. The devolatilization model used in this work is taken from published literature with slight modifications to match the numerical predictions with experimental measurements. This work also develops a reactor network model for simulating the performance of boiler furnaces. For the seamless integration of kinetic models of coal devolatilization and combustion with furnace numerical model, the thermochemistry data of several hypothetical and intermediate species involved in devolatilization chemistry are evaluated in the form of 14 coefficient National Aeronautics and Space Administration polynomials. The capability of the model for predicting the furnace temperature and product composition is demonstrated by simulating a single-zone model.

This paper presents a new framework for the modeling of coal-fired boiler furnaces. The input required for the model is the ultimate analysis of a coal sample. The model accounts for devolatilization followed by gas-phase combustion. The devolatilization model used in this work is taken from published literature with slight modifications to match the numerical predictions with experimental measurements. This work also develops a reactor network model for simulating the performance of boiler furnaces. For the seamless integration of kinetic models of coal devolatilization and combustion with furnace numerical model, the thermochemistry data of several hypothetical and intermediate species involved in devolatilization chemistry are evaluated in the form of 14 coefficient National Aeronautics and Space Administration polynomials. The capability of the model for predicting the furnace temperature and product composition is demonstrated by simulating a single-zone model.