The last decade witnessed a quantum increase in wind energy contribution to the U.S. renewable electricity mix. Although the overall environmental impact of wind energy is miniscule in comparison to fossil-fuel energy, the early stages of the wind energy life cycle have potential for a higher environmental impact. This study attempts to quantify the relative contribution of individual stages toward life cycle impacts by conducting a life cycle assessment with SimaPro^® and the Impact 2002+ impact assessment method. A comparative analysis of individual stages at three locations, onshore, shallow-water, and deep-water, in Texas and the gulf coast indicates that material extraction/processing would be the dominant stage with an average impact contribution of 72% for onshore, 58% for shallow-water, and 82% for deep-water across the 15 midpoint impact categories. The payback times for CO₂ and energy consumption range from 6 to 14 and 6 to 17 months, respectively, with onshore farms having shorter payback times. The greenhouse gas emissions (GHG) were in the range of 5–7 gCO₂eq/kWh for the onshore location, 6–9 CO₂eq/kWh for the shallow-water location, and 6–8 CO₂eq/kWh for the deep-water location. A sensitivity analysis of the material extraction/processing stage to the electricity sourcing stage indicates that replacement of lignite coal with natural gas or wind would lead to marginal improvements in midpoint impact categories.

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.

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.

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).

This study characterized and evaluated the life cycle greenhouse gas (GHG) emissions from different wind electricity generation systems by (a) performing a comprehensive review of the wind electricity generation system life cycle assessment (LCA) studies and (b) statistically evaluating 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 ‘axis of rotation-installed location-power generation capacity’) was adopted for use in this study to characterize the reviewed wind electricity generation systems. The unique category codes were labeled by integrating the names from the three wind power sub-classifications, i.e., the axis of rotation of the wind turbine [horizontal axis wind turbine (HAWT), vertical axis wind turbine (VAWT)], the location of the installation [onshore (ON), offshore (OFF)], and the electricity production capacity [small (S), intermediate (I), large (L)]. The characterized wind electricity generation systems were statistically evaluated to assess the reduction in life cycle GHG emissions. A total of five unique categorization codes (HAWT-ON-S, HAWT-ON-I, HAWT-ON-L, HAWT-OFF-L, VAWT-ON-S) were designated to the 29 wind electricity generation LCA studies (representing 74 wind system cases) using the proposed categorization index. The mean life cycle GHG emissions resulting from the use of HAWT-ON-S (N = 3), HAWT-ON-I (N = 4), HAWT-ON-L (N = 58), HAWT-OFF-L (N = 8), and VAWT-ON-S (N = 1) wind electricity generation systems are 38.67, 11.75, 15.98, 12.9, and 46.4 gCO₂e/kWh, respectively. The HAWT-ON-I wind electricity generation systems produced the minimum life cycle GHGs than other wind electricity generation systems.

In order to solve the energy crisis and reduce emissions of greenhouse gases (GHG), renewable energy resources are exploited for power generation. Because lignocellulosic biomass resources are abundant and renewable, various technologies are applied to using lignocellulosic biomass to derive biofuel and electricity. This paper focuses on power generation from lignocellulosic biomass and comparison of the effects of different feedstocks, transportation, and power generation technologies evaluated through life cycle assessment (LCA). The inputs and boundaries of LCA vary with different feedstocks, such as forestry wood, agricultural residues, and fast-growing grass. For agricultural residues and fast-growing grass, the transportation cost from field to power plant is more critical. Three technologies for power generation are analyzed both with and without pelletization of lignocellulosic biomass. The GHG emissions also vary with different feedstocks and depend on burning technologies at different plant scales. The daily criteria pollutant emissions of power generation from different lignocellulosic biomass were evaluated with a life cycle assessment model of GREET.net 2014. It is concluded that bio-power generation is critical with the urgency of greenhouse effects.