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Hydropower, which contributes to around 16% of global electricity and more than 72% of renewable electricity, is expected to play an important role in the deep decarbonization of the energy sector. However, the idea that hydropower is a carbon-neutral energy alternative on par with solar and wind is controversial. Research, mainly from limnology and climate modeling, shows that depending on the characteristics of the hydro project, it could be a significant source of GHG emissions. This aspect has been ignored in most life cycle assessment (LCA) studies, affecting the effective use of LCA results, especially in comparative assessments. This paper aims to provide a comprehensive and critical review on this topic by conducting a systematic literature review on hydropower LCA studies published since 2010. We found that there is inconsistency in how LCA is used for hydropower projects. While the emissions associated with the engineering work are well addressed, efforts to accurately estimate and model reservoir GHG emissions are constrained by limited data availability, difficulties in accurately quantifying highly variable carbon fluxes, and inconsistent modeling approaches. A huge range of emissions values is reported in the reviewed literature, from 1.5 to 3747.8 g CO 2 eq per kWh. Reservoir-based hydropower shows high variability, which is mainly dictated by reservoir-related GHG emissions. Reservoir GHG emissions could be more than 90% of the life cycle emissions, especially for hydropower in a tropical region. The regionalized aspect is a key factor to be considered in extrapolating reservoir GHG emissions. • There is inconsistency in how LCA is used for hydropower projects. • A wide range of emission intensities has been reported (1.5–3747.8 g CO 2 eq/kWh). • The high variability in the emissions is due to major differences in key reservoir characteristics. • Data limitations are the main cause for over- or underestimation of hydropower emissions. • Harmonization of data is vital to effectively conduct LCA and to generate useful results. [ABSTRACT FROM AUTHOR]

Hydrogen (H 2) can play a critical role in global greenhouse gas (GHG) mitigation. Photocatalytic water splitting using solar radiation is a promising H 2 technology. Titanium dioxide (TiO 2) and carbon nitride (g–C 3 N 4)–based photocatalysts are the most widely used photocatalytic materials because of their activity and abundance. Several attempts have been made to improve the photocatalytic performance of these materials in terms of their activity level, life span, response to visible radiation, and stability. However, the environmental impacts of these modifications are often not included in existing studies. This research, therefore, develops a cradle-to-grave life cycle assessment (LCA) framework to evaluate and compare the GHG footprints of four alternative pathways: TiO 2 nanorods and fluorine-doped carbon nitride quantum dots embedded with TiO 2 (CNF: TNR/TiO 2), g-C 3 N 4 , and g-C 3 N 4 /BiOI composite. Unlike most studies that focus only on certain stages such as laboratory-scale photocatalytic fabrication, this study includes utility-scale cell production, assembly, operation, and end of life to give a more accurate and precise environmental performance estimation. The results show that g-C 3 N 4 /BiOI has the lowest GHG footprint (0.38 kg CO 2 eq per kg of H 2) and CNF: TNR/TiO 2 has the lowest energy payback time (0.4 years). In every pathway, energy use in material extraction processes makes up the largest GHG contribution, between 83% and 89%. Sensitivity and uncertainty analyses were conducted under the impact of various input parameters on the life cycle GHG emissions of hydrogen production. Photocatalytic water splitting is highly feasible for adaptation as a mainstream hydrogen production pathway in the future. • LCA of H 2 production via photocatalytic water splitting is conducted. • GHG emissions range from 0.33 to 1.15 kg of CO 2 eq per kg of H 2 produced. • Material extraction has the largest GHG emissions; 56–67% of total emissions. • System is scaled up to produce 5 tonnes of H 2 per day. • H 2 produced has 95% less GHG emissions than steam methane reforming. [ABSTRACT FROM AUTHOR]

Jurisdictions are looking into mixing hydrogen into the natural gas (NG) system to reduce greenhouse gas (GHG) emissions. Earlier studies have focused on well-to-wheel analysis of H 2 fuel cell vehicles, using high-level estimates for transportation-based emissions. There is limited research on transportation emissions of hythane, a blend of H 2 and NG used for combustion. An in-depth analysis of the pipeline transportation system was performed for hythane and includes sensitivity and uncertainty analyses. When hythane with 15% H 2 is used, transportation GHG emissions (gCO2eq/GJ) increase by 8%, combustion GHG emissions (gCO2eq/GJ) decrease by 5%, and pipeline energy capacity (GJ/hr) decreases by 11% for 50–100 million m3/d pipelines. Well-to-combustion (WTC) emissions increase by 2.0% without CCS, stay the same with a 41% CCS rate, decrease by 2.8% for the 100% CCS scenario, and decrease by 3.6% in the optimal CO 2 -free scenario. While hythane contains 15% H 2 by volume only 5% of the gas' energy comes from H 2 , limiting its GHG benefit. [Display omitted] • A model is developed to assess well-to-combustion (WTC) greenhouse gas (GHG) emissions of hythane. • A hythane blend of 15% H 2 and 85% natural gas is assessed. • Transportation GHG emissions increase by 8% and combustion GHG emissions decrease by 4%. • Without carbon capture, WTC GHG emissions increase by 2%. • Steam methane reforming of hydrogen with 90% carbon capture will reduce WTC GHG emissions by 3%. [ABSTRACT FROM AUTHOR]

Many studies have calculated deterministic point estimates of well-to-combustion (WTC) emissions of transportation fuels from crude oil in an attempt to determine which crude oils have lower or higher emissions. However, there is considerable variation in the published results, resulting in uncertainty. The purpose of this study is to identify GHG emissions ranges for five conventional and two unconventional crudes by performing an uncertainty analysis using an improved version of the FUN damental E N gineering Principl E s-based Mode L for Estimation of G reen H ouse G ases (FUNNEL-GHG). Distributions for key inputs in the Monte Carlo simulation were determined based on values obtained from the literature. Eleven scenarios were developed, nine historical and two current, the former using life-long average production data from the oil fields studied and the latter using recent production data to illustrate how WTC emissions change as the fields age. The mean WTC emissions ranges for the eleven scenarios are 97.5–140 gCO 2 eq/MJ. The uncertainty in the WTC emissions ranges from ±3% to ±11%. The largest source of uncertainty in the WTC emissions is from the venting, fugitive, and flaring volumes, fluid injection rates, and refinery yields. [ABSTRACT FROM AUTHOR]

• Life cycle assessment of utility-scale solar energy is performed. • Upstream production and assembly are the most emission-intensive life cycle stages. • Energy use during production and plant lifetime are the most sensitive parameters. • The system shows a net energy production with a net energy ratio up to 6.6. • The life cycle GHG emissions range from 98.3 to 149.3 g CO 2 eq /kWh. Grid-connected utility-scale solar PV has emerged as a potential pathway to ensure deep decarbonization of electricity in regions with fossil fuel-dominated energy mixes. Research on utility-scale solar PV projects mainly focuses on assessing technical or economic feasibility. Environmental performance assessments of large-scale solar applications are scarce. There is limited information on the greenhouse gas (GHG) emissions and energy footprints of utility-scale solar energy systems. Earlier studies conducted on small-scale solar systems have limited application in the grid system. We developed a comprehensive bottom-up life cycle assessment model to evaluate the life cycle GHG emissions and energy profiles of utility-scale solar photovoltaic (PV) system with lithium-ion battery storage to provide a consistent electricity supply to the grid with peak load options. We conducted a case study for a fossil fuel-based energy jurisdiction, Alberta (a western province in Canada). The results of the energy assessment show that raw material extraction, production, and assembly of solar panels are the key drivers, accounting for 53% of the total consumption. Energy consumed during battery manufacturing is responsible for 28%. The system shows a net energy production with a mean net energy ratio as high as 6.6 for two-axis sun tracking orientation. The life cycle GHG emissions range from 98.3 to 149.3 g CO 2 eq /kWh with a mean value of 123.8 g CO 2 eq /kWh. The largest emissions contribution is due to the manufacturing of batteries, 54% of the total emissions. The solar PV system offers a mean energy payback time of 3.8 years (with a range of 3.3 to 4.2 years). The results are highly sensitive to the expected lifetime of the system, the panel's peak wattage, and process energy consumption at various life cycle stages. [ABSTRACT FROM AUTHOR]

A model – FUNNEL-GHG-OS ( FUN damental E N gineering Principl E s-based Mode L for Estimation of G reen H ouse G ases in the O il S ands) was developed to estimate project-specific energy consumption and greenhouse gas emissions (GHGs) in major recovery and extraction processes in the oil sands, namely surface mining and in␣situ production. This model estimates consumption of diesel (4.4–7.1 MJ/GJ of bitumen), natural gas (52.7–86.4 MJ/GJ of bitumen) and electricity (1.8–2.1 kW h/GJ of bitumen) as fuels in surface mining. The model also estimates the consumption of natural gas (123–462.7 MJ/GJ of bitumen) and electricity (1.2–3.5 kW h/GJ of bitumen) in steam assisted gravity drainage (SAGD), based on fundamental engineering principles. Cogeneration in the oil sands, with excess electricity exported to Alberta’s grid, was also explored. Natural gas consumption forms a major portion of the total energy consumption in surface mining and SAGD and thus is a main contributor to GHG emissions. Emissions in surface mining and SAGD range from 4.4 to 7.4 gCO 2 eq/MJ of bitumen and 8.0 to 34.0 gCO 2 eq/MJ of bitumen, respectively, representing a wide range of variability in oil sands projects. Depending upon the cogeneration technology and the efficiency of the process, emissions in oil sands recovery and extraction can be reduced by 16–25% in surface mining and 33–48% in SAGD. Further, a sensitivity analysis was performed to determine the effects of key parameters on the GHG emissions in surface mining and SAGD. Temperature and the consumption of warm water in surface mining and the steam-to-oil ratio (SOR) in SAGD are major parameters affecting GHG emissions. The developed model can predict the energy consumption and emissions for surface mining and SAGD for oil sands. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to develop a bottom-up life cycle assessment model to evaluate the greenhouse gas (GHG) emissions associated with the Canadian oil sands supply to China. Two pathways were considered. In pathway I, extracted bitumen is sent to Edmonton for upgrading and pipelined to the Westridge terminal near Vancouver, then shipped to a port in China. In pathway II, extracted bitumen is mixed with diluent, directly pipelined to the Westridge terminal, and shipped to China. The results from both the pipeline and the shipping models suggest that pathway I has better GHG emissions than pathway II on a per-barrel basis. GHG emissions are 2.4–3.5 times lower in pipelining synthetic crude oil (SCO) to Westridge than in pipelining dilbit, without and with a diluent return. The emissions range from 826 − 401 + 701 g CO 2 eq/bbl for SCO, 1819 − 719 + 1172 for dilbit without diluent return, and 2684 − 1065 + 1374 g CO 2 eq/bbl for dilbit with a diluent return. Shipping SCO has 15% fewer emissions than shipping dilbit. The shipping emissions are due to fuel use in the main engine. The emissions for shipping are 5536 − 914 + 966 g CO 2 /bbl for dilbit and 4034 − 822 + 899 g CO 2 /bbl for SCO. • GHG emission performances of Canadian oil sands supply to China were identified. • Pipeline GHG emissions range from 826 − 401 + 701 to 1819 − 719 + 1172 g CO 2 eq/bbl. • Shipping synthetic crude oil has 15% fewer GHG emissions than shipping dilbit. • Shipping GHG emissions ranges from 4034 − 822 + 899 to 5536 − 914 + 966 g CO 2 /bbl. • The synthetic crude oil supply pathway has a higher GHG performance than the dilbit. [ABSTRACT FROM AUTHOR]

• Bottom-up life cycle assessment models were developed for battery storage systems. • Life cycle greenhouse gas (GHG) emissions of five battery storage systems were evaluated. • Four different stationary applications of batteries were examined. • The Li-ion has the highest net energy ratio (NER) and lowest GHGs in all applications. Electro-chemical batteries are widely used in portable devices and transportation, but they can also be used in the electricity grid for various applications. The assessment of the environmental impacts of electro-chemical storage systems for stationary use has received little attention. In this study, data-intensive, bottom-up life cycle assessment models were developed to assess the life cycle net energy ratios (NERs) and greenhouse gas (GHG) emissions of utility-scale stationary applications of five electro-chemical energy storage systems: sodium-sulfur, lithium-ion, valve-regulated lead-acid, nickel–cadmium, and vanadium redox flow. Four stationary application scenarios were considered: bulk energy storage, transmission and distribution (T&D) investment deferral, frequency regulation, and support of voltage regulation. The Li-ion storage system has the highest NER and lowest GHG emissions in every scenario. The life cycle GHG emissions range from 715 to 784 kg-CO 2 eq for sodium-sulfur, 625–659 kg-CO 2 eq for lithium-ion, 749–803 kg-CO 2 eq for valve-regulated lead-acid, 742–806 kg-CO 2 eq for nickel–cadmium, and 800–963 kg-CO 2 eq for vanadium redox flow per MWh of electricity delivered, depending on the application scenario. The results are highly influenced by the operation phase that involves charging the batteries. Lithium-ion and sodium-sulfur storage systems are the most suitable for all the application scenarios because of their longer cycle lives and higher energy densities. [ABSTRACT FROM AUTHOR]