Quantification of the Lifecycle Greenhouse Gas Emissions from Nuclear Power Generation Systems

This paper statistically quantifies the lifecycle greenhouse gas (GHG) emissions from six distinct reactor-based (boiling water reactor (BWR), pressurized water reactor (PWR), light water reactor (LWR), heavy-water-moderated reactor (HWR), gas-cooled reactor (GCR), fast breeder reactor (FBR)) nuclear power generation systems by following a two-step approach that included (a) performing a review of the lifecycle assessment (LCA) studies on the reactor-based nuclear power generation systems; and (b) statistically evaluating the lifecycle GHG emissions (expressed in grams of carbon dioxide equivalent per kilowatt hour, gCO2e/kWh) for each of the reactor-based nuclear power generation systems to assess the role of different types of nuclear reactors in the reduction of the lifecycle GHG emissions. Additionally, this study quantified the impacts of fuel enrichment methods (centrifuge, gaseous diffusion) on GHG emissions. The mean lifecycle GHG emissions resulting from the use of BWR (sample size, N = 15), PWR (N = 21), LWR (N = 7), HWR (N = 3), GCR (N = 1), and FBR (N = 2) in nuclear power generation systems are 14.52 gCO2e/kWh, 11.87 gCO2e/kWh, 20.5 gCO2e/kWh, 28.2 gCO2e/kWh, 8.35 gCO2e/kWh, and 6.26 gCO2e/kWh, respectively. The FBR nuclear power generation systems produced the minimum lifecycle GHGs. The centrifuge enrichment method produced lower GHG emissions than the gaseous diffusion enrichment method

An Examination of the Sensitivity of Sulfur Dioxide, Nitric Oxide, and Nitrogen Dioxide Concentrations to the Important Factors Affecting Air Quality Inside a Public Transportation Bus

The present study examined the sensitivity of sulfur dioxide (SO<sub>2</sub>), nitric oxide (NO), and nitrogen dioxide (NO<sub>2</sub>) concentrations to the important factors affecting air quality inside a public transportation bus. Additionally, this study quantified the in-bus contaminant concentrations in relation to the ranked statistically significant variables. The independent variables to which the monitored contaminant concentrations are the most sensitive to were determined using regression trees and the analysis of variance. A comprehensive one-year database, of the monitored contaminant concentrations and the independent factors that affect an indoor microenvironment (meteorology, monitoring periods, outdoor sources, and ventilation settings) was developed to study the sensitivity of monitored in-bus contaminants. SO<sub>2</sub> concentrations were extremely sensitive to the month, weather conditions, and heavy vehicles. NO concentrations were sensitive to the month/season, ventilation, and ambient temperature; while NO<sub>2</sub> concentrations were additionally sensitive to the monitoring period and the ambient mixing ratio. Quantified in-bus relationships revealed NO and NO<sub>2</sub> concentrations to be less than 0.6 ppm and 0.1 ppm, respectively. SO<sub>2</sub> concentrations of 0.4 ppm were observed in the fall-winter months, when the lead heavy vehicles were at a minimum density of 56 per hour; < 0.4 ppm SO<sub>2</sub> concentrations remained for the rest of the year

Evaluation of the Life Cycle Greenhouse Gas Emissions from Hydroelectricity Generation Systems

This study evaluated the life cycle greenhouse gas (GHG) emissions from different hydroelectricity generation systems by first performing a comprehensive review of the hydroelectricity generation system life cycle assessment (LCA) studies and then subsequent computation of statistical metrics to quantify the life cycle GHG emissions (expressed in grams of carbon dioxide equivalent per kilowatt hour, gCO2e/kWh). A categorization index (with unique category codes, formatted as “facility type-electric power generation capacity”) was developed and used in this study to evaluate the life cycle GHG emissions from the reviewed hydroelectricity generation systems. The unique category codes were labeled by integrating the names of the two hydro power sub-classifications, i.e., the facility type (impoundment (I), diversion (D), pumped storage (PS), miscellaneous hydropower works (MHPW)) and the electric power generation capacity (micro (µ), small (S), large (L)). The characterized hydroelectricity generation systems were statistically evaluated to determine the reduction in corresponding life cycle GHG emissions. A total of eight unique categorization codes (I-S, I-L, D-µ, D-S, D-L, PS-L, MHPW-µ, MHPW-S) were designated to the 19 hydroelectricity generation LCA studies (representing 178 hydropower cases) using the proposed categorization index. The mean life cycle GHG emissions resulting from the use of I-S (N = 24), I-L (N = 8), D-µ (N = 3), D-S (N = 133), D-L (N = 3), PS-L (N = 3), MHPW-µ (N = 3), and MHPW-S (N = 1) hydroelectricity generation systems are 21.05 gCO2e/kWh, 40.63 gCO2e/kWh, 47.82 gCO2e/kWh, 27.18 gCO2e/kWh, 3.45 gCO2e/kWh, 256.63 gCO2e/kWh, 19.73 gCO2e/kWh, and 2.78 gCO2e/kWh, respectively. D-L hydroelectricity generation systems produced the minimum life cycle GHGs (considering the hydroelectricity generation system categories with a representation of at least two cases)

Evaluation of the Life Cycle Greenhouse Gas Emissions from Different Biomass Feedstock Electricity Generation Systems

This paper evaluates life cycle greenhouse gas (GHG) emissions from the use of different biomass feedstock categories (agriculture residues, dedicated energy crops, forestry, industry, parks and gardens, wastes) independently on biomass-only (biomass as a standalone fuel) and cofiring (biomass used in combination with coal) electricity generation systems. The statistical evaluation of the life cycle GHG emissions (expressed in grams of carbon dioxide equivalent per kilowatt hour, gCO2e/kWh) for biomass electricity generation systems was based on the review of 19 life cycle assessment studies (representing 66 biomass cases). The mean life cycle GHG emissions resulting from the use of agriculture residues (N = 4), dedicated energy crops (N = 19), forestry (N = 6), industry (N = 4), and wastes (N = 2) in biomass-only electricity generation systems are 291.25 gCO2e/kWh, 208.41 gCO2e/kWh, 43 gCO2e/kWh, 45.93 gCO2e/kWh, and 1731.36 gCO2e/kWh, respectively. The mean life cycle GHG emissions for cofiring electricity generation systems using agriculture residues (N = 10), dedicated energy crops (N = 9), forestry (N = 9), industry (N = 2), and parks and gardens (N = 1) are 1039.92 gCO2e/kWh, 1001.38 gCO2e/kWh, 961.45 gCO2e/kWh, 926.1 gCO2e/kWh, and 1065.92 gCO2e/kWh, respectively. Forestry and industry (avoiding the impacts of biomass production and emissions from waste management) contribute the least amount of GHGs, irrespective of the biomass electricity generation system

Review of the Life Cycle Greenhouse Gas Emissions from Different Photovoltaic and Concentrating Solar Power Electricity Generation Systems

This paper contains an extensive review of life cycle assessment (LCA) studies on greenhouse gas emissions (GHG) from different material-based photovoltaic (PV) and working mechanism-based concentrating solar power (CSP) electricity generation systems. Statistical evaluation of the life cycle GHG emissions is conducted to assess the role of different PVs and CSPs in reducing GHG emissions. The widely-used parabolic trough and central receiver CSP electricity generation systems emitted approximately 50% more GHGs than the paraboloidal dish, solar chimney, and solar pond CSP electricity generation systems. The cadmium telluride PVs and solar pond CSPs contributed to minimum life cycle GHGs. Thin-film PVs are also suitable for wider implementation, due to their lower Energy Pay-Back Time (EPBT) periods, in addition to lower GHG emission, in comparison with c-Si PVs