Joe Cresko

Russian anthropogenic black carbon: Emission reconstruction and Arctic black carbon simulation

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 Russias 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 Russias 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performance of Arctic BC simulations in previous studies may be partly ascribed to the Russian BC emissions built on out-of-date and/or missing information, which could result in biases to both emission rates and the spatial distribution of emissions.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.

Understanding Variability To Reduce the Energy and GHG Footprints of U.S. Ethylene Production

Recent growth in U.S. ethylene production due to the shale gas boom is affecting the U.S. chemical industrys energy and greenhouse gas (GHG) emissions footprints. To evaluate these effects, a systematic, first-principles model of the cradle-to-gate ethylene production system was developed and applied. The variances associated with estimating the energy consumption and GHG emission intensities of U.S. ethylene production, both from conventional natural gas and from shale gas, are explicitly analyzed. A sensitivity analysis illustrates that the large variances in energy intensity are due to process parameters (e.g., compressor efficiency), and that large variances in GHG emissions intensity are due to fugitive emissions from upstream natural gas production. On the basis of these results, the opportunities with the greatest leverage for reducing the energy and GHG footprints are presented. The model and analysis provide energy analysts and policy makers with a better understanding of the drivers of energy use and GHG emissions associated with U.S. ethylene production. They also constitute a rich data resource that can be used to evaluate options for managing the industrys footprints moving forward.

Environmental and Economic Implications of Distributed Additive Manufacturing: The Case of Injection Mold Tooling

Summary Additive 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.

Volume 1: Survey of Available Information in Support of the Energy-Water Bandwidth Study of Desalination Systems:

Author(s): Rao, Prakash; Aghajanzadeh, Arian; Sheaffer, Paul; Morrow, William R.; Brueske, Sabine; Dollinger, Caroline; Price, Kevin; Sarker, Prateeti; Ward, Nicholas; Cresko, Joe

Energy Impacts of Wide Band Gap Semiconductors in U.S. Light-Duty Electric Vehicle Fleet

Silicon carbide and gallium nitride, two leading wide band gap semiconductors with significant potential in electric vehicle power electronics, are examined from a life cycle energy perspective and compared with incumbent silicon in U.S. light-duty electric vehicle fleet. Cradle-to-gate, silicon carbide is estimated to require more than twice the energy as silicon. However, the magnitude of vehicle use phase fuel savings potential is comparatively several orders of magnitude higher than the marginal increase in cradle-to-gate energy. Gallium nitride cradle-to-gate energy requirements are estimated to be similar to silicon, with use phase savings potential similar to or exceeding that of silicon carbide. Potential energy reductions in the United States vehicle fleet are examined through several scenarios that consider the market adoption potential of electric vehicles themselves, as well as the market adoption potential of wide band gap semiconductors in electric vehicles. For the 2015-2050 time frame, cumulative energy savings associated with the deployment of wide band gap semiconductors are estimated to range from 2-20 billion GJ depending on market adoption dynamics.