In recent literature, prospective application of life cycle assessment (LCA) at low technology readiness levels (TRL) has gained immense interest for its potential to enable development of emerging ...technologies with improved environmental performances. However, limited data, uncertain functionality, scale up issues and uncertainties make it very challenging for the standard LCA guidelines to evaluate emerging technologies and requires methodological advances in the current LCA framework. In this paper, we review published literature to identify major methodological challenges and key research efforts to resolve these issues with a focus on recent developments in five major areas: cross‐study comparability, data availability and quality, scale‐up issues, uncertainty and uncertainty communication, and assessment time. We also provide a number of recommendations for future research to support the evaluation of emerging technologies at low technology readiness levels: (a) the development of a consistent framework and reporting methods for LCA of emerging technologies; (b) the integration of other tools with LCA, such as multicriteria decision analysis, risk analysis, technoeconomic analysis; and (c) the development of a data repository for emerging materials, processes, and technologies.
Life cycle assessment (LCA) analysts are increasingly being asked to conduct life cycle‐based systems level analysis at the earliest stages of technology development. While early assessments provide ...the greatest opportunity to influence design and ultimately environmental performance, it is the stage with the least available data, greatest uncertainty, and a paucity of analytic tools for addressing these challenges. While the fundamental approach to conducting an LCA of emerging technologies is akin to that of LCA of existing technologies, emerging technologies pose additional challenges. In this paper, we present a broad set of market and technology characteristics that typically influence an LCA of emerging technologies and identify questions that researchers must address to account for the most important aspects of the systems they are studying. The paper presents: (a) guidance to identify the specific technology characteristics and dynamic market context that are most relevant and unique to a particular study, (b) an overview of the challenges faced by early stage assessments that are unique because of these conditions, (c) questions that researchers should ask themselves for such a study to be conducted, and (d) illustrative examples from the transportation sector to demonstrate the factors to consider when conducting LCAs of emerging technologies. The paper is intended to be used as an organizing platform to synthesize existing methods, procedures and insights and guide researchers, analysts and technology developer to better recognize key study design elements and to manage expectations of study outcomes.
We developed a physically-based environmental account of US food production systems and integrated these data into the environmental-input-output life cycle assessment (EIO-LCA) model. The extended ...model was used to characterize the food, energy, and water (FEW) intensities of every US economic sector. The model was then applied to every Bureau of Economic Analysis metropolitan statistical area (MSA) to determine their FEW usages. The extended EIO-LCA model can determine the water resource use (kGal), energy resource use (TJ), and food resource use in units of mass (kg) or energy content (kcal) of any economic activity within the United States. We analyzed every economic sector to determine its FEW intensities per dollar of economic output. This data was applied to each of the 382 MSAs to determine their total and per dollar of GDP FEW usages by allocating MSA economic production to the corresponding FEW intensities of US economic sectors. Additionally, a longitudinal study was performed for the Los Angeles-Long Beach-Anaheim, CA, metropolitan statistical area to examine trends from this singular MSA and compare it to the overall results. Results show a strong correlation between GDP and energy use, and between food and water use across MSAs. There is also a correlation between GDP and greenhouse gas emissions. The longitudinal study indicates that these correlations can shift alongside a shifting industrial composition. Comparing MSAs on a per GDP basis reveals that central and southern California tend to be more resource intensive than many other parts of the country, while much of Florida has abnormally low resource requirements. Results of this study enable a more complete understanding of food, energy, and water as key ingredients to a functioning economy. With the addition of the food data to the EIO-LCA framework, researchers will be able to better study the food-energy-water nexus and gain insight into how these three vital resources are interconnected. Applying this extended model to MSAs has demonstrated that all three resources are important to a MSA's vitality, though the exact proportion of each resource may differ across urban areas.
For sustainable design, technology developers need to consider not only technical and economic aspects but also potential environmental impacts while developing new technologies. Techno economic ...analysis (TEA) evaluates the technical performance and economic feasibility of a technology. Life cycle assessment (LCA) evaluates the potential environmental impacts associated with a product system throughout its life cycle from raw material extraction to disposal. Generally, TEA and LCA performed separately for technology assessment. Understanding of the trade-off between economic and environmental performance is crucial for sustainable process design, which is not fully available if TEA and LCA is performed separately. In contrast, integration of TEA and LCA enables systematic analysis of the relationships between technical, economic, and environmental performance and provides more information to technology developers for trade-off analysis. Integrated TEA-LCA tool can also reduce inconsistency between system boundaries, functional units, and assumptions that can arise from using standalone TEA and LCA findings in decision making. There is also growing interest of prospective application of integrated TEA-LCA tool to evaluate emerging technologies at early technology readiness level (TRL). Integration of TEA and LCA is still an evolving area and requires further exploration to develop a consistent methodological guideline. The goal of this study is to review the current state-of-the-art in TEA and LCA to identify the methodological challenges of TEA-LCA integration approaches. This study also identifies major challenges to perform integrated TEA-LCA analysis of emerging technologies at low TRLs. Lack of consistent methodological guidelines and compatible software tools, inconsistent system boundary and functional unit selection, limited data availability and uncertainty are key methodological challenges for integration of LCA and TEA. Future research should focus on developing integrated TEA-LCA tool, formulating approach to incorporate optimization method with integrated TEA-LCA tool, and developing strategy of proper communication of results from integrated LCA-TEA tool to broad range of stakeholders.
•Integration of TEA and LCA is crucial for sustainable process design.•Ex-ante application of integrated TEA-LCA tool can guide development of emerging technologies.•Integrated TEA-LCA tool enables simultaneous economic and environmental evaluation.•Alignment of goal, scope, data, and system elements are key to integrate TEA and LCA.
To respond to anthropogenic effects on the global climate system, higher education institutions are assessing and aiming to reduce their greenhouse gas emissions. The objective of this paper was to ...evaluate the carbon footprint of Clemson University’s campus using a streamlined life cycle assessment approach. The carbon footprint sets a baseline for source specific evaluation and future mitigation efforts at Clemson University. Greenhouse gas emission sources presented in this carbon footprint include steam generation, refrigerants, electricity generation, electricity life cycle, various forms of transportation, wastewater treatment, and paper usage. This case study describes the approach used to quantify each greenhouse gas emission source, and discusses data assumptions and life cycles phases included to improve carbon footprint comparison with other higher education institutions. Results show that Clemson University’s carbon footprint for 2014 is approximately 95,000 metric tons CO2-equivalent, and 4.4 metric tons CO2-equivalent per student. Scope 1 emissions accounted for about 19% of the carbon footprint, while Scope 2 and 3 emissions each contributed nearly 41%. The largest sources of greenhouse gas emissions were electricity generation (41%), automotive commuting (18%), and steam generation (16%). Electricity generation from coal was 29% of the electricity generation resource mix and accounted for three-quarters of Clemson University’s GHG emissions associated with electricity.
•A case study of Clemson University presents a streamlined life cycle assessment approach to quantify the campus’s carbon footprint.•Life cycle phases and data assumptions for each greenhouse gas emission source are discussed to provide a basis for comparison to other higher education institutions.•Scope 1 emissions accounted for about 19% of the carbon footprint, while Scope 2 and 3 emissions each contributed nearly 41% to the carbon footprint.•Applying the electricity provider’s specific electricity generation resource mix has a significant impact on the final carbon footprint.
Habitat heterogeneity influences pathogen ecology by affecting vector abundance and the reservoir host communities. We investigated spatial patterns of disease risk for two human pathogens in the ...Borrelia genus-B. burgdorferi and B. miyamotoi-that are transmitted by the western black-legged tick, Ixodes pacificus. We collected ticks (349 nymphs, 273 adults) at 20 sites in the San Francisco Bay Area, California, USA. Tick abundance, pathogen prevalence and density of infected nymphs varied widely across sites and habitat type, though nymphal western black-legged ticks were more frequently found, and were more abundant in coast live oak forest and desert/semi-desert scrub (dominated by California sagebrush) habitats. We observed Borrelia infections in ticks at all sites where we able to collect >10 ticks. The recently recognized human pathogen, B. miyamotoi, was observed at a higher prevalence (13/349 nymphs = 3.7%, 95% CI = 2.0-6.3; 5/273 adults = 1.8%, 95% CI = 0.6-4.2) than recent studies from nearby locations (Alameda County, east of the San Francisco Bay), demonstrating that tick-borne disease risk and ecology can vary substantially at small geographic scales, with consequences for public health and disease diagnosis.
Future energy systems will inevitably rely much more on variable renewable energy. This transition has implications for capital equipment in the energy gathering, processing, and end-use sectors. We ...define a “flexible energy strategy” (FES) as an energy capital investment and associated operating strategy that can increase usage of variable renewable energy. The literature on FES options is vast and many options have been explored, such as electrochemical storage, demand management, or flexible manufacturing. However, FESs have been difficult to compare to date because of large variation in the details of technology characteristics and possible operating strategies. We develop a purposely simplified framework for consistent inter-comparison of FESs that uses the levelized cost of peak energy (LCPE) – energy provided at times of high electricity prices. We show that various FESs which differ in many details can be represented at a more abstract level with a small number of common terms (e.g., $ per W). We develop analytical solutions for LCPE for four broad classes of FESs. We evaluate these equations for four template variability cycles with empirical FES data. Our simple framework recreates intuitive and oft-cited results from the literature (i.e., challenges of seasonal-scale variability) and points to concrete targets for energy storage technologies.
•Building flexible energy systems will require new approaches to capital allocation.•Simple models with few parameters can be used to compare different flexible energy solutions.•Flexibility solutions differ drastically for different forms of variability (e.g., daily vs. seasonal).
Generating electricity by co-combusting biomass and coal, known as biomass cofiring, is shown to be an economically attractive option for coal-fired power plants to comply with emission regulations. ...However, the total carbon footprint of the associated supply chain still needs to be carefully investigated. In this study we propose a stochastic biobjective optimization model to analyze the economic and environmental impacts of biopower supply chains. We use a life cycle assessment approach to derive the emission factors used in the environmental objective function. We use chance constraints to capture the uncertain nature of energy content of biomass feedstocks. We propose a cutting plane algorithm which uses the sample average approximation method to model the chance constraints and finds high confidence feasible solutions. In order to find Pareto optimal solutions we propose a heuristic approach which integrates the
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-constraint method with the cutting plane algorithm. We show that the developed approach provides a set of local Pareto optimal solutions with high confidence and reasonable computational time. We develop a case study using data about biomass and coal plants in North and South Carolina. The results indicate that, cofiring of biomass in these states can reduce emissions by up to 8%. Increasing the amount of biomass cofired will not result in lower emissions due to biomass delivery.
Supermarkets in Port Harcourt (PH) city, Nigeria, predominantly rely on diesel electricity generation due to grid instability, leading to high electricity prices. Although solar photovoltaic (PV) ...systems have been proposed as an alternative, these supermarkets have yet to adopt them, mainly due to high investment costs and a lack of awareness of the long-term financial and environmental benefits. This paper examines the technical and economic practicality of a PV system for these supermarkets using the PVsyst software and a spreadsheet model. Solar resources showed that PH has a daily average solar radiation and temperature of 4.21 kWh/m2/day and 25.73 °C, respectively. Market Square, the supermarket with the highest peak power demand of 59.8 kW and a 561 kWh/day load profile, was chosen as a case study. A proposed PV system with a power capacity of 232 kW, battery storage capacity of 34,021 Ah, a charge controller size of 100 A/560 V, and an inverter with a power rating of 60 V/75 kW has been designed to meet the load demand. The economic analysis showed a $266,936 life cycle cost, $0.14 per kWh levelized cost of electricity (LCOE), a 4-year simple payback time, and a 20.5% internal rate of return (IRR). The PV system is feasible due to its positive net present value (NPV) of $165,322 and carbon savings of 582 tCO2/year.
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