Energy and GHG reductions considering embodied impacts of retrofitting existing dwelling stock in Greater Melbourne

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Assessing the effectiveness of building retrofits in reducing GHG emissions: A Canadian school case study

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

SummaryFuel economy has been an effective indicator of vehicle greenhouse gas (GHG) emissions for conventional gasoline‐powered vehicles due to the strong relationship between fuel economy and vehicle life cycle emissions. However, fuel economy is not as accurate an indicator of vehicle GHG emissions for plug‐in hybrid (PHEVs) and pure battery electric vehicles (EVs). Current vehicle labeling efforts by the U.S. Environmental Protection Agency (EPA) and Department of Transportation have been focused on providing energy and environmental information to consumers based on U.S. national average data. This article explores the effects of variations in regional grids and regional daily vehicle miles traveled (VMT) on the total vehicle life cycle energy and GHG emissions of electrified vehicles and compare these results with information reported on the label and on the EPA's fuel economy Web site. The model results suggest that only 25% of the life cycle emissions from a representative PHEV are reflected on current vehicle labeling. The results show great variation in total vehicle life cycle emissions due to regional grid differences, including an approximately 100 gram per mile life cycle GHG emissions difference between the lowest and highest electric grid regions and up to a 100% difference between the state‐specific emission values within the same electric grid regions. Unexpectedly, for two regional grids the life cycle GHG emissions were higher in electric mode than in gasoline mode. We recommend that labels include stronger language on their deficiencies and provide ranges for GHG emissions from vehicle charging in regional electricity grids to better inform consumers.

Aluminum production is a major energy consumer and important source of greenhouse gas (GHG) emissions globally. Estimation of the energy consumption and GHG emissions caused by aluminum production in China has attracted widespread attention because China produces more than half of the global aluminum. This paper conducted life cycle (LC) energy consumption and GHG emissions analysis of primary and recycled aluminum in China for the year 2020, considering the provincial differences on both the scale of self-generated electricity consumed in primary aluminum production and the generation source of grid electricity. Potentials for energy saving and GHG emissions reductions were also investigated. The results indicate that there are 157,207 MJ of primary fossil energy (PE) consumption and 15,947 kg CO2-eq of GHG emissions per ton of primary aluminum ingot production in China, with the LC GHG emissions as high as 1.5–3.5 times that of developed economies. The LC PE consumption and GHG emissions of recycled aluminum are very low, only 7.5% and 5.3% that of primary aluminum, respectively. Provincial-level results indicate that the LC PE and GHG emissions intensities of primary aluminum in the main production areas are generally higher while those of recycled aluminum are lower in the main production areas. LC PE consumption and GHG emissions can be significantly reduced by decreasing electricity consumption, self-generated electricity management, low-carbon grid electricity development, and industrial relocation. Based on this study, policy suggestions for China’s aluminum industry are proposed. Recycled aluminum industry development, restriction of self-generated electricity, low-carbon electricity utilization, and industrial relocation should be promoted as they are highly helpful for reducing the LC PE consumption and GHG emissions of the aluminum industry. In addition, it is recommended that the central government considers the differences among provinces when designing and implementing policies.

Plug-in hybrid electric vehicles (PHEVs) have potential to reduce greenhouse gas (GHG) emissions in the U.S. light-duty vehicle fleet. GHG emissions from PHEVs and other vehicles depend on both vehicle design and driver behavior. We pose a twice-differentiable, factorable mixed-integer nonlinear programming model utilizing vehicle physics simulation, battery degradation data, and U.S. driving data to determine optimal vehicle design and allocation for minimizing lifecycle greenhouse gas (GHG) emissions. The resulting nonconvex optimization problem is solved using a convexification-based branch-and-reduce algorithm, which achieves global solutions. In contrast, a randomized multistart approach with local search algorithms finds global solutions in 59% of trials for the two-vehicle case and 18% of trials for the three-vehicle case. Results indicate that minimum GHG emissions is achieved with a mix of PHEVs sized for around 35 miles of electric travel. Larger battery packs allow longer travel on electric power, but additional battery production and weight result in higher GHG emissions, unless significant grid decarbonization is achieved. PHEVs offer a nearly 50% reduction in life cycle GHG emissions relative to equivalent conventional vehicles and about 5% improvement over ordinary hybrid electric vehicles. Optimal allocation of different vehicles to different drivers turns out to be of second order importance for minimizing net life cycle GHGs.

Taking Stock of Strategies on Climate Change and the Way Forward: A Strategic Climate Change Framework for Australia

Vehicle lightweighting vs. electrification: Life cycle energy and GHG emissions results for diverse powertrain vehicles

Life cycle assessment of primary energy demand and greenhouse gas (GHG) emissions of four propylene production pathways in China

Electrified vehicles, including plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs), have the potential to reduce greenhouse gas (GHG) emissions from personal transportation by shifting energy demand from gasoline to electricity. GHG reduction potential depends on vehicle design, adoption, driving and charging patterns, charging infrastructure, and electricity generation mix. We construct an optimization model to study these factors by determining optimal design of conventional vehicles (CVs), hybrid electric vehicles (HEVs), PHEVs, and BEVs and optimal allocation of vehicle designs and charging infrastructure in the fleet for minimum lifecycle GHG emissions over a range of scenarios. We focus on vehicles with similar size and acceleration to a Toyota Prius under urban EPA driving conditions. We find that under today’s U.S. average grid mix, the vehicle fleet allocated for minimum GHG emissions includes HEVs and PHEVs with ~30 miles (48 km) of electric range. Allocating only CVs, HEVs, PHEVs, or BEVs will produce 86%, 1%, 0%, or 13+% more life cycle GHG emissions, respectively. Unlike BEVs, PHEVs do consume some gasoline; however, PHEVs can power a large portion of vehicle miles on electrical energy while accommodating infrequent long trips without need for a large battery pack, with its corresponding production and weight implications. Availability of workplace charging for 90% of vehicles optimistically reduces optimized GHG emissions by 0.5%. Under decarbonized grid scenarios, larger battery packs are more competitive and reduce life cycle GHG emissions significantly. Future work will relax modeling assumptions and address life cycle cost and cost-effectiveness of GHG reductions.

Impacts of alternative fuel combustion in cement manufacturing: Life cycle greenhouse gas, biogenic carbon, and criteria air contaminant emissions

Introducing demand to supply ratio as a new metric for understanding life cycle greenhouse gas (GHG) emissions from rainwater harvesting systems

The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One example of the latter approach was published in Science by Farrell and colleagues (2006) clarifying the net energy and greenhouse gas (GHG) emissions of ethanol, in which adjustments included the addition of coproduct credit, the addition and subtraction of processes within the system boundary, and a reconciliation of differences in the definition of net energy metrics. Such adjustments therefore provide an even playing field on which all studies can be considered and at the same time specify the conditions of the playing field itself. Understanding the conditions under which a meta-analysis was conducted is important for proper interpretation of both the magnitude and variability in results. This special supplemental issue of the Journal of Industrial Ecology includes 12 high-quality metaanalyses and critical reviews of LCAs that advance understanding of the life cycle environmental impacts of different technologies, processes, products, and materials. Also published are three contributions on methodology and related discussions of the role of meta-analysis in LCA. The goal of this special supplemental issue is to contribute to the state of the science in LCA beyond the core practice of producing independent studies on specific products or technologies by highlighting the ability of meta-analysis of LCAs to advance understanding in areas of extensive existing literature. The inspiration for the issue came from a series of meta-analyses of life cycle GHG emissions from electricity generation technologies based on research from the LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a laboratory of the U.S. Department of Energy, which also provided financial support for this special supplemental issue. (See the editorial from this special supplemental issue [Lifset 2012], which introduces this supplemental issue and discusses the origins, funding, peer review, and other aspects.) The first article on reporting considerations for meta-analyses/critical reviews for LCA is from Heath and Mann (2012), who describe the methods used and experience gained in NREL's LCA Harmonization Project, which produced six of the studies in this special supplemental issue. Their harmonization approach adapts key features of systematic review to identify and screen published LCAs followed by a meta-analytical procedure to adjust published estimates to ones based on a consistent set of methods and assumptions to allow interstudy comparisons and conclusions to be made. In a second study on methods, Zumsteg and colleagues (2012) propose a checklist for a standardized technique to assist in conducting and reporting systematic reviews of LCAs, including meta-analysis, that is based on a framework used in evidence-based medicine. Widespread use of such a checklist would facilitate planning successful reviews, improve the ability to identify systematic reviews in literature searches, ease the ability to update content in future reviews, and allow more transparency of methods to ease peer review and more appropriately generalize findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired by a meta-analysis, for categorizing main methodological topics, reconciling diverging methodological developments, and identifying future research directions in LCA. Their procedure involves the carrying out of a literature review on articles selected according to predefined criteria.« less

Embodied GHG emissions of buildings – The hidden challenge for effective climate change mitigation

_ Maritime transport accounts for around 3% of global anthropogenic greenhouse gas (GHG) emissions (Well-to-Wake). These GHG emissions must be reduced by at least 50% in absolute values by 2050 to contribute to the ambitions of the Paris Agreement signed in 2015. Switching to zero-carbon fuels made from renewable sources (hydro, wind, or solar) is seen by many as the most promising option to deliver the desired GHG reductions. However, renewable energy is a scarce resource that gives a much larger GHG reduction spent within other sectors. This study explores how to reach the IMO 2050 GHG targets exclusively through energy efficiency measures. The results indicate that by combining wind-assisted ship propulsion (WASP) with a slender hull form, fuel consumption and GHG emissions can be reduced by 30–35%, at a negative abatement cost for speeds exceeding 8 knots. Where the cost saving increases with the speed because at higher speeds, the fuel accounts for a higher share of the total cost, which implies that the cost saving goes from zero at 8 knots, to 5% reduction at 11 knots average speed to 14% reduction of total cost with 15 knots average speed. In comparison, GHG reductions through zero-carbon fuels will increase transport costs by 50–200%. Introduction From the first days of our civilization, sea transport has enabled regional and global trades. Today, sea transport accounts for 80% of the global trade measured in ton-miles (UNCTAD 2021) and 3% of greenhouse gas (GHG) emissions measured Well-to-Wake (Lindstad et al. 2021). More than 40% of this sea trade is performed by dry bulkers, making them the real workhorses of the sea. Even though sea transport is energy efficient compared to other transport modes, all sectors need to reduce their GHG emissions by at least 50% in absolute values by 2050 to contribute to the Paris Agreement (UNFCCC 2015). According to Bouman et al. (2017), the desired energy and GHG reductions can be achieved through: Design and other technical improvements of ships; Operational improvements; Fuels with zero or low GHG footprints; or a combination of these.