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Additive manufacturing (AM) holds great potential for improving materials efficiency, reducing life-cycle impacts, and enabling greater engineering functionality compared to conventional manufacturing (CM), and AM has been increasingly adopted by aircraft component manufacturers for lightweight, cost-effective designs. This study estimates the net changes in life-cycle primary energy and greenhouse gas emissions associated with AM technologies for lightweight metallic aircraft components through the year 2050, to shed light on the environmental benefits of a shift from CM to AM processes in the U.S. aircraft industry. A systems modeling framework is presented, with integrates engineering criteria, life-cycle environmental data, aircraft fleet stock and fuel use models under different AM adoption scenarios. Estimated fleet-wide life-cycle primary energy savings at most reach 70-173 million GJ/year in 2050, with cumulative savings of 1.2-2.8 billion GJ. Associated cumulative GHG emission reductions were estimated at 92.1-215.0 million metric tons. In addition, thousands of tons of aluminum, titanium and nickel alloys could be potentially saved per year in 2050. The results indicate a significant role of AM technologies in helping society meet its long-term energy use and GHG emissions reduction goals, and highlight barriers and opportunities for AM adoption for the aircraft industry.

Development of reliable source emission inventories is particularly needed to advance the understanding of the origin of Arctic haze using chemical transport modeling. This study develops a regional anthropogenic black carbon (BC) emission inventory for the Russian Federation, the largest country by land area in the Arctic Council. Activity data from combination of local Russia information and international resources, emission factors based on either Russian documents or adjusted values for local conditions, and other emission source data are used to approximate the BC emissions. Emissions are gridded at a resolution of 0.1° × 0.1° and developed into a monthly temporal profile. Total anthropogenic BC emission of Russia in 2010 is estimated to be around 224 Gg. Gas flaring, a commonly ignored black carbon source, contributes a significant fraction of 36.2% to Russia's total anthropogenic BC emissions. Other sectors, i.e., residential, transportation, industry, and power plants, contribute 25.0%, 20.3%, 13.1%, and 5.4%, respectively. Three major BC hot spot regions are identified: the European part of Russia, the southern central part of Russia where human population densities are relatively high, and the Urals Federal District where Russia's major oil and gas fields are located but with sparse human population. BC simulations are conducted using the hemispheric version of Community Multi‐scale Air Quality Model with emission inputs from a global emission database EDGAR (Emissions Database for Global Atmospheric Research)‐HTAPv2 (Hemispheric Transport of Air Pollution) and EDGAR‐HTAPv2 with its Russian part replaced by the newly developed Russian BC emissions, respectively. The simulation using the new Russian BC emission inventory could improve 30–65% of absorption aerosol optical depth measured at the AERONET sites in Russia throughout the whole year as compared to that using the default HTAPv2 emissions. At the four ground monitoring sites (Zeppelin, Barrow, Alert, and Tiksi) in the Arctic Circle, surface BC simulations are improved the most during the Arctic haze periods (October–March). The poor performance of Arctic BC simulations in previous studies may be partly ascribed to the Russian BC emissions built on out‐of‐date and/or missing information, which could result in biases to both emission rates and the spatial distribution of emissions. This study highlights that the impact of Russian emissions on the Arctic haze has likely been underestimated, and its role in the Arctic climate system needs to be reassessed. The Russian black carbon emission source data generated in this study can be obtained via http://abci.ornl.gov/download.shtml or http://acs.engr.utk.edu/Data.php.

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. K E Y W O R D Searly stage technology assessment, environmental impacts, industrial ecology, life cycle assessment (LCA), research and development (R&D), unintended consequences

SummaryAdditive manufacturing (AM) holds great potentials in enabling superior engineering functionality, streamlining supply chains, and reducing life cycle impacts compared to conventional manufacturing (CM). This study estimates the net changes in supply-chain lead time, life cycle primary energy consumption, greenhouse gas (GHG) emissions, and life cycle costs (LCC) associated with AM technologies for the case of injection molding, to shed light on the environmental and economic advantages of a shift from international or onshore CM to AM in the United States. A systems modeling framework is developed, with integrations of lead-time analysis, life cycle inventory analysis, LCC model, and scenarios considering design differences, supply-chain options, productions, maintenance, and AM technological developments. AM yields a reduction potential of 3% to 5% primary energy, 4% to 7% GHG emissions, 12% to 60% lead time, and 15% to 35% cost over 1 million cycles of the injection molding production depending on the AM technology advancement in future. The economic advantages indicate the significant role of AM technology in raising global manufacturing competitiveness of local producers, while the relatively small environmental benefits highlight the necessity of considering trade-offs and balance techniques between environmental and economic performances when AM is adopted in the tooling industry. The results also help pinpoint the technological innovations in AM that could lead to broader benefits in future. Keywords:additive manufacturing industrial ecology injection molding life cycle assessment (LCA) life cycle costing (LCC) supply chain management Supporting information is linked to this article on the JIE website