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The production of maple syrup from sap requires extensive processing, which has traditionally led to significant energy inputs and greenhouse gas (GHG) emissions per gallon produced. Technology advancements, e.g., vacuum tubing sap collection systems, reverse osmosis (RO), and electric evaporators have changed the way syrup is produced, resulting in widespread variability in processing equipment and sugar-making operational decisions. This paper evaluates these complex operations through a cradle-to-retail gate carbon footprinting model and by capturing variability in a series of producer archetypes. By isolating energy and emissions impacts, we find that implementing RO has the largest reduction effect on energy (54-77%) and emissions (57-82%), depending on both production size and evaporator fuel (wood, fuel-oil, or electricity). Results also demonstrate the effect of production scale on cumulative energy demand (CED) and emissions per gallon of syrup, with small producers ranging from 333-1,425 MJ/gal and 27-118 kg CO 2 e/gal (61-90% biogenic on-site) for wood-fired operations and 18-65 kg CO 2 e/gal for oil-fired operations. Large producers ranged from 90-131 MJ and 3.5-7 kg CO 2 e/gal (electricity to oil-fired operations). Producers of all scales with the highest rates of electrification in their operations have the lowest GHG emissions and energy use per gallon of syrup produced.

The United States Postal Service (USPS) plans to purchase 165,000 next-generation delivery vehicles (NGDVs) between 2023 and 2032. The USPS submitted an environmental impact statement (EIS) for two NGDV procurement scenarios: (1) 90% internal combustion engine vehicles (ICEVs) and 10% battery electric vehicles (BEVs) ("ICEV scenario") and (2) 100% BEVs ("BEV scenario"). To correct several significant deficiencies in the EIS, we conduct a cradle-to-grave life cycle greenhouse gas (GHG) assessment of these two scenarios. Our analysis improves upon the USPS's EIS by including vehicle production and end-of-life emissions, future grid decarbonization, and more accurate vehicle operating emissions. In our base case, we find that the ICEV and BEV scenarios would result in 15% greater and 8% fewer GHG emissions, respectively, than the USPS estimate. Favorable vehicle and grid development would result in 63% lower BEV scenario emissions than the USPS estimate. Consequently, we calculate a cumulative lifetime emission reduction of 57-82% (14.7-21.4 Mt CO 2 e) from procuring 100% BEVs instead of 10% BEVs, compared to the USPS's estimate of 10.3 Mt. Given the long NGDV lifetimes, committing to the ICEV scenario squanders an ideal use case for BEVs, jeopardizes meeting our climate goals, and forgoes potential climate and environmental justice co-benefits.

The COVID-19 pandemic has accelerated the growth of e-commerce and automated warehouses, vehicles, and robots and has created new options for grocery supply chains. We report and compare the greenhouse gas (GHG) emissions for a 36-item grocery basket transported along 72 unique paths from a centralized warehouse to the customer, including impacts of micro-fulfillment centers, refrigeration, vehicle automation, and last-mile transportation. Our base case is in-store shopping with last-mile transportation using an internal combustion engine (ICE) SUV (6.0 kg CO 2 e). The results indicate that emissions reductions could be achieved by e-commerce with micro-fulfillment centers (16-54%), customer vehicle electrification (18-42%), or grocery delivery (22-65%) compared to the base case. In-store shopping with an ICE pick-up truck has the highest emissions of all paths investigated (6.9 kg CO 2 e) while delivery using a sidewalk automated robot has the least (1.0 kg CO 2 e). Shopping frequency is an important factor for households to consider, e.g. halving shopping frequency can reduce GHG emissions by 44%. Trip chaining also offers an opportunity to reduce emissions with approximately 50% savings compared to the base case. Opportunities for grocers and households to reduce grocery supply chain carbon footprints are identified and discussed.

Estimates show that 6.2 gigatons of carbon dioxide (CO 2 ) can be captured and utilized across three pathways, concrete, chemical, and minerals, by 2050. However, it is difficult to compare the climate benefit across these three carbon capture and utilization (CCU) pathways to determine the most effective use of captured CO 2 . The life cycle assessment methods to evaluate the climate benefit of CCU chemicals should additionally account for the change in material properties of concrete due to CO 2 utilization. Furthermore, with most CO 2 utilization technologies being in the early stages of research and development, the uncertainty and variability in process and inventory data present a significant challenge in evaluating the climate benefit. We present a stochastically determined climate return on investment (ROI) metric to rank and prioritize CO 2 utilization across 20 concrete, chemical and mineral pathways based on the realized climate benefit. We show that two concrete pathways, which use CO 2 during concrete mixing, and two chemical pathways, which produce formic acid through hydrogenation of CO 2 and carbon monoxide through dry reforming of methane, generate the greatest climate ROI and are the only CCU pathways with a higher likelihood of generating a climate benefit than a climate burden.

Increased E-commerce and demand for contactless delivery during the COVID-19 pandemic have fueled interest in robotic package delivery. We evaluate life cycle greenhouse gas (GHG) emissions for automated suburban ground delivery systems consisting of a vehicle (last-mile) and a robot (final-50-feet). Small and large cargo vans (125 and 350 cubic feet; V125 and V350) with an internal combustion engine (ICEV) and battery electric (BEV) powertrains were assessed for three delivery scenarios: (i) conventional , human-driven vehicle with human delivery; (ii) partially automated , human-driven vehicle with robot delivery; and (iii) fully automated , connected automated vehicle (CAV) with robot delivery. The robot's contribution to life cycle GHG emissions is small (2-6%). Compared to the conventional scenario, full automation results in similar GHG emissions for the V350-ICEV but 10% higher for the V125-BEV. Conventional delivery with a V125-BEV provides the lowest GHG emissions, 167 g CO 2 e/package, while partially automated delivery with a V350-ICEV generates the most at 486 g CO 2 e/package. Fuel economy and delivery density are key parameters, and electrification of the vehicle and carbon intensity of the electricity have a large impact. CAV power requirements and efficiency benefits largely offset each other, and automation has a moderate impact on life cycle GHG emissions.

Electrification of delivery fleets has emerged as an important opportunity to reduce the transportation sector's environmental impact, including reducing greenhouse gas (GHG) emissions. When, where, and how vehicles are charged, however, impact the reduction potential. Not only does the carbon intensity of the grid vary across time and space, but charging decisions also influence battery degradation rates, resulting in more or less frequent battery replacement. Here, we propose a model that accounts for the spatial and temporal differences in charging emissions using marginal emission factors and degradation-induced differences in production emissions using a semi-empirical degradation model. We analyze four different charging strategies and demonstrate that a baseline charging scenario, in which a vehicle is fully charged immediately upon returning to a central depot, results in the highest emissions and employing alternative charging methods can reduce emissions by 8-37%. We show that when, where, and how batteries are charged also impact the total cost of ownership. Although the lowest cost and the lowest emitting charging strategies often align, the lowest cost deployment location for electric delivery vehicles may not be in the same location that maximizes environmental benefits.

Urine diversion has been proposed as an approach for producing renewable fertilizers and reducing nutrient loads to wastewater treatment plants. Life cycle assessment was used to compare environmental impacts of the operations phase of urine diversion and fertilizer processing systems [via (1) a urine concentration alternative and (2) a struvite precipitation and ion exchange alternative] at a city scale to conventional systems. Scenarios in Vermont, Michigan, and Virginia were modeled, along with additional sensitivity analyses to understand the importance of key parameters, such as the electricity grid and wastewater treatment method. Both urine diversion technologies had better environmental performance than the conventional system and led to reductions of 29-47% in greenhouse gas emissions, 26-41% in energy consumption, approximately half the freshwater use, and 25-64% in eutrophication potential, while acidification potential ranged between a 24% decrease to a 90% increase. In some situations, wastewater treatment chemical requirements were eliminated. The environmental performance improvement was usually dependent on offsetting the production of synthetic fertilizers. This study suggests that urine diversion could be applied broadly as a strategy for both improving wastewater management and decarbonization.

A large portion of life cycle transportation impacts occur during vehicle operation, and key improvement strategies include increasing powertrain efficiency, vehicle electrification, and lightweighting vehicles by reducing their mass. The potential energy benefits of vehicle lightweighting are large, given that 29.5 EJ was used in all modes of U.S. transportation in 2016, and roughly half of the energy spent in wheeled transportation and the majority of energy spent in aircraft is used to move vehicle mass. We collect and review previous work on lightweighting, identify key parameters affecting vehicle environmental performance (e.g., vehicle mode, fuel type, material type, and recyclability), and propose a set of 10 principles, with examples, to guide environmental improvement of vehicle systems through lightweighting. These principles, based on a life cycle perspective and taken as a set, allow a wide range of stakeholders (designers, policy-makers, and vehicle manufacturers and their material and component suppliers) to evaluate the trade-offs inherent in these complex systems. This set of principles can be used to evaluate trade-offs between impact categories and to help avoid shifting of burdens to other life cycle phases in the process of improving use-phase environmental performance.

Although recent studies of connected and automated vehicles (CAVs) have begun to explore the potential energy and greenhouse gas (GHG) emission impacts from an operational perspective, little is known about how the full life cycle of the vehicle will be impacted. We report the results of a life cycle assessment (LCA) of Level 4 CAV sensing and computing subsystems integrated into internal combustion engine vehicle (ICEV) and battery electric vehicle (BEV) platforms. The results indicate that CAV subsystems could increase vehicle primary energy use and GHG emissions by 3-20% due to increases in power consumption, weight, drag, and data transmission. However, when potential operational effects of CAVs are included (e.g., eco-driving, platooning, and intersection connectivity), the net result is up to a 9% reduction in energy and GHG emissions in the base case. Overall, this study highlights opportunities where CAVs can improve net energy and environmental performance.

Due to the complexity of power systems, tracking emissions attributable to a specific electrical load is a daunting challenge but essential for many environmental impact studies. Currently, no consensus exists on appropriate methods for quantifying emissions from particular electricity loads. This paper reviews a wide range of the existing methods, detailing their functionality, tractability, and appropriate use. We identified and reviewed 32 methods and models and classified them into two distinct categories: empirical data and relationship models and power system optimization models. To illustrate the impact of method selection, we calculate the CO2 combustion emissions factors associated with electric-vehicle charging using 10 methods at nine charging station locations around the United States. Across the methods, we found an up to 68% difference from the mean CO2 emissions factor for a given charging site among both marginal and average emissions factors and up to a 63% difference from the average across average emissions factors. Our results underscore the importance of method selection and the need for a consensus on approaches appropriate for particular loads and research questions being addressed in order to achieve results that are more consistent across studies and allow for soundly supported policy decisions. The paper addresses this issue by offering a set of recommendations for determining an appropriate model type on the basis of the load characteristics and study objectives.

The introduction of energy storage technologies to the grid could enable greater integration of renewables, improve system resilience and reliability, and offer cost effective alternatives to transmission and distribution upgrades. The integration of energy storage systems into the electrical grid can lead to different environmental outcomes based on the grid application, the existing generation mix, and the demand. Given this complexity, a framework is needed to systematically inform design and technology selection about the environmental impacts that emerge when considering energy storage options to improve sustainability performance of the grid. To achieve this, 12 fundamental principles specific to the design and grid application of energy storage systems are developed to inform policy makers, designers, and operators. The principles are grouped into three categories: (1) system integration for grid applications, (2) the maintenance and operation of energy storage, and (3) the design of energy storage systems. We illustrate the application of each principle through examples published in the academic literature, illustrative calculations, and a case study with an off-grid application of vanadium redox flow batteries (VRFBs). In addition, trade-offs that can emerge between principles are highlighted.

Lightweighting is a key strategy to improve vehicle fuel economy. Assessing the life-cycle benefits of lightweighting requires a quantitative description of the use-phase fuel consumption reduction associated with mass reduction. We present novel methods of estimating mass-induced fuel consumption (MIF) and fuel reduction values (FRVs) from fuel economy and dynamometer test data in the U.S. Environmental Protection Agency (EPA) database. In the past, FRVs have been measured using experimental testing. We demonstrate that FRVs can be mathematically derived from coast down coefficients in the EPA vehicle test database avoiding additional testing. MIF and FRVs calculated for 83 different 2013 MY vehicles are in the ranges 0.22-0.43 and 0.15-0.26 L/(100 km 100 kg), respectively, and increase to 0.27-0.53 L/(100 km 100 kg) with powertrain resizing to retain equivalent vehicle performance. We show how use-phase fuel consumption can be estimated using MIF and FRVs in life cycle assessments (LCAs) of vehicle lightweighting from total vehicle and vehicle component perspectives with, and without, powertrain resizing. The mass-induced fuel consumption model is illustrated by estimating lifecycle greenhouse gas (GHG) emission benefits from lightweighting a grille opening reinforcement component using magnesium or carbon fiber composite for 83 different vehicle models.

Emerging products and technologies pose unique challenges for the life cycle assessment (LCA) community, given the lack of data and inherent uncertainties regarding their development. An emerging technology that has the potential to be transformative and effect broad-scale change within society, as well as the underpinning assumptions associated with its life cycle, is particularly difficult to analyze. Despite the associated challenges, LCA methods must be developed for transformative technologies. The greatest improvement potential occurs at the early phases of technology development; therefore, prospective LCA results can be used to anticipate potential unintended consequences and develop design pathways that lead to preferential outcomes. This paper identifies and categorizes ten factors that influence the LCA results of transformative technologies in order to provide a formal structure for determining appropriate factors for inclusion within an LCA. Appropriate factors for an analysis should be selected according to the overall research questions of the study and are applicable to both attributional and consequential approaches to LCA.

Supplying adequate human nutrition within ecosystem carrying capacities is a key element in the global environmental sustainability challenge. Life cycle assessment (LCA) has been used effectively to evaluate the environmental impacts of food production value chains and to identify opportunities for targeted improvement strategies. Dietary choices and resulting consumption patterns are the drivers of production, however, and a consumption-oriented life cycle perspective is useful in understanding the environmental implications of diet choices. This review identifies 32 studies that use an LCA framework to evaluate the environmental impact of diets or meals. It highlights the state of the art, emerging methodological trends and current challenges and limitations to such diet-level LCA studies. A wide range of bases for analysis and comparison (i.e., functional units) have been employed in LCAs of foods and diet; we conceptually map appropriate functional unit choices to research aims and scope and argue for a need to move in the direction of a more sophisticated and comprehensive nutritional basis in order to link nutritional health and environmental objectives. Nutritional quality indices are reviewed as potential approaches, but refinement through ongoing collaborative research between environmental and nutritional sciences is necessary. Additional research needs include development of regionally specific life cycle inventory databases for food and agriculture and expansion of the scope of assessments beyond the current focus on greenhouse gas emissions.

Feed production constitutes a major portion of the energy and water resource inputs in modern livestock production. Schemes to reduce these inputs may include local sourcing of animal feed. However, in water stressed regions where irrigation of feed crops is necessary, a trade-off between local sourcing (with high water stress) and transport from less water stressed regions can occur. We demonstrate this trade-off in the U.S. by combining state-level irrigation water use and pumping energy demand from USDA surveys with fertilizer and transportation energy demands for producing major feed crops (corn grain, soybean, alfalfa hay, corn silage) in each state and delivering them to two hypothetical dairy farms located in Kersey, CO and Rosendale, WI. A back-up technology approach is employed to express freshwater resource depletion in units of energy, allowing direct comparison with other energy resource demands. Corn grain, soybean, and alfalfa hay delivered to CO demonstrate a clear trade-off between transportation energy (proportional to the distance between CO and the production state) and water stress. On the other hand, transportation burdens dominate for corn silage, making local production most attractive, even in water stressed regions. All crops delivered to WI (a region of low water stress and minimal irrigation) are dominated by transportation burdens, making local production preferable, but this is clearly not a universal principal, as other cases show. This paper quantitatively elucidates the water-energy trade-off in sourcing feed for livestock and the method is expected to be applicable in managing supply chain logistics of other farm commodities.

We conducted surveys of six hatcheries and 18 farms for data inputs to complete a cradle-to-farm-gate life cycle assessment (LCA) to evaluate the environmental performance for intensive (for export markets in Chicago) and semi-intensive (for domestic markets in Shanghai) shrimp farming systems in Hainan Province, China. The relative contribution to overall environmental performance of processing and distribution to final markets were also evaluated from a cradle-to-destination-port perspective. Environmental impact categories included global warming, acidification, eutrophication, cumulative energy use, and biotic resource use. Our results indicated that intensive farming had significantly higher environmental impacts per unit production than semi-intensive farming in all impact categories. The grow-out stage contributed between 96.4% and 99.6% of the cradle-to-farm-gate impacts. These impacts were mainly caused by feed production, electricity use, and farm-level effluents. By averaging over intensive (15%) and semi-intensive (85%) farming systems, 1 metric ton (t) live-weight of shrimp production in China required 38.3 ± 4.3 GJ of energy, as well as 40.4 ± 1.7 t of net primary productivity, and generated 23.1 ± 2.6 kg of SO(2) equiv, 36.9 ± 4.3 kg of PO(4) equiv, and 3.1 ± 0.4 t of CO(2) equiv. Processing made a higher contribution to cradle-to-destination-port impacts than distribution of processed shrimp from farm gate to final markets in both supply chains. In 2008, the estimated total electricity consumption, energy consumption, and greenhouse gas emissions from Chinese white-leg shrimp production would be 1.1 billion kW·h, 49 million GJ, and 4 million metric tons, respectively. Improvements suggested for Chinese shrimp aquaculture include changes in feed composition, farm management, electricity-generating sources, and effluent treatment before discharge. Our results can be used to optimize market-oriented shrimp supply chains and promote more sustainable shrimp production and consumption.

In order to manage strategies to curb climate change, systemic benchmarking at a variety of production scales and methods is needed. This study is the first life cycle assessment (LCA) of a large-scale, vertically integrated organic dairy in the United States. Data collected at Aurora Organic Dairy farms and processing facilities were used to build a LCA model for benchmarking the greenhouse gas (GHG) emissions and energy consumption across the entire milk production system, from organic feed production to post-consumer waste disposal. Energy consumption and greenhouse gas emissions for the entire system (averaged over two years of analysis) were 18.3 MJ per liter of packaged fluid milk and 2.3 kg CO(2 )equiv per liter of packaged fluid milk, respectively. Methane emissions from enteric fermentation and manure management account for 27% of total system GHG emissions. Transportation represents 29% of the total system energy use and 15% of the total GHG emissions. Utilization of renewable energy at the farms, processing plant, and major transport legs could lead to a 16% reduction in system energy use and 6.4% less GHG emissions. Sensitivity and uncertainty analysis reveal that alternative meat coproduct allocation methods can lead to a 2.2% and 7.5% increase in overall system energy and GHG, respectively. Feed inventory data source can influence system energy use by -1% to +10% and GHG emission by -4.6% to +9.2%, and uncertainties in diffuse emission factors contribute -13% to +25% to GHG emission.

Primary aluminum ingot is a globally traded commodity, and large regional differences in technology and electricity fuel mixes exist among the industry's smelters. A life cycle assessment model is developed to calculate absolute emissions and emissions intensities of greenhouse gases (GHGs) from the production, trade, and consumption of primary ingot in six world regions. Global production emissions are estimated at 283 (+/-18) Mt CO2-eq (14.7 (+/-0.95) kg CO2-eq/kg primary ingot) in 1990 and 468 (+/-26) Mt CO2-eq (14.7 (+/-0.80) kg CO2-eq/kg primary ingot) in 2005. In total, the production of primary aluminum accounts for 0.78 and 0.93% of world GHG emissions in 1990 and 2004, respectively. Regional production GHG intensities in 2005 range from 7.07 (+/-0.69) kg CO2-eq/kg primary ingot in Latin America to 21.9 (+/-3.0) kg CO2-eq/kg primary ingot in Asia. The GHG implications of expanding global trade of primary ingot are examined in terms of the emissions embodied in the imports and exports and the consumption-weighted emissions intensities of each region.

Models and frameworks to guide "sustainable mobility" of personal transportation lack definitive quantitative targets. This paper defines sustainable mobility targets for US light-duty vehicles (LDVs) to help stabilize atmospheric carbon dioxide concentrations at 450 or 550 ppm. The Intergovernmental Panel on Climate Change carbon stabilization pathways are used to equitably distribute future carbon dioxide emissions to the US. Allowable US emissions are then allocated to the LDV sector according to the current share of national emissions. Average on-road LDV well-to-wheel carbon emissions must be reduced from 160 g/mile (2002) to 20 g/mile by 2050 to contribute to a 450 ppm CO2 goal. Strategies to reduce LDV greenhouse gas emissions include reducing travel demand, improving average fuel economy, and utilizing low-carbon ethanol. Simulations using EIA modeling parameters indicate that average LDV fuel economy must reach 136 mpg, cellulosic ethanol must make up over 83% of fuel market share, or annual LDV travel demand must be reduced by about 53% by 2050 to help meet LDV greenhouse gas targets based on a 450 ppm CO2 stabilization goal. Recent federal energy security policy and plug-in hybrid technology programs may also help meet LDV carbon emission targets in the short term by reducing gasoline use, but an aggressive combination of strategies will be needed to keep vehicle CO2 in line with an emissions target to 2050.

Although recent progress in automotive technology has reduced exhaust emissions per mile for new cars, the continuing use of inefficient, higher-polluting old cars as well as increasing vehicle miles driven are undermining the benefits of this progress. As a way to address the "inefficient old vehicle" contribution to this problem, a novel life cycle optimization (LCO) model is introduced and applied to the automobile replacement policy question. The LCO model determines optimal vehicle lifetimes, accounting for technology improvements of new models while considering deteriorating efficiencies of existing models. Life cycle inventories for different vehicle models that represent materials production, manufacturing, use, maintenance, and end-of-life environmental burdens are required as inputs to the LCO model. As a demonstration, the LCO model was applied to mid-sized passenger car models between 1985 and 2020. An optimization was conducted to minimize cumulative carbon monoxide (CO), non-methane hydrocarbon (NMHC), oxides of nitrogen (NOx), carbon dioxide (CO2), and energy use over the time horizon (1985-2020). For CO, NMHC, and NOx pollutants with 12000 mi of annual mileage, automobile lifetimes ranging from 3 to 6 yr are optimal for the 1980s and early 1990s model years while the optimal lifetimes are expected to be 7-14 yr for model year 2000s and beyond. On the other hand, a lifetime of 18 yr minimizes cumulative energy and CO2 based on driving 12000 miles annually. Optimal lifetimes are inversely correlated to annual vehicle mileage, especially for CO, NMHC, and NOx emissions. On the basis of the optimization results, policies improving durability of emission controls, retiring high-emitting vehicles, and improving fuel economies are discussed.