Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Emissivity”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Aircraft-based inversions quantify the importance of wetlands and livestock for Upper Midwest methane emissions

Abstract. We apply airborne measurements across three seasons (summer, winter and spring 2017–2018) in a multi-inversion framework to quantify methane emissions from the US Corn Belt and Upper Midwest, a key agricultural and wetland source region. Combing our seasonal results with prior fall values we find that wetlands are the largest regional methane source (32 %, 20 [16–23] Gg/d), while livestock (enteric/manure; 25 %, 15 [14–17] Gg/d) are the largest anthropogenic source. Natural gas/petroleum, waste/landfills, and coal mines collectively make up the remainder. Optimized fluxes improve model agreement with independent datasets within and beyond the study timeframe. Inversions reveal coherent and seasonally dependent spatial errors in the WetCHARTs ensemble mean wetland emissions, with an underestimate for the Prairie Pothole region but an overestimate for Great Lakes coastal wetlands. Wetland extent and emission temperature dependence have the largest influence on prediction accuracy; better representation of coupled soil temperature–hydrology effects is therefore needed. Our optimized regional livestock emissions agree well with the Gridded EPA estimates during spring (to within 7 %) but are ∼ 25 % higher during summer and winter. Spatial analysis further shows good top-down and bottom-up agreement for beef facilities (with mainly enteric emissions) but larger (∼ 30 %) seasonal discrepancies for dairies and hog farms (with > 40 % manure emissions). Findings thus support bottom-up enteric emission estimates but suggest errors for manure; we propose that the latter reflects inadequate treatment of management factors including field application. Overall, our results confirm the importance of intensive animal agriculture for regional methane emissions, implying substantial mitigation opportunities through improved management.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A new method for inferring city emissions and lifetimes of nitrogen oxides from high-resolution nitrogen dioxide observations: a model study

We present a new method to infer emissions and lifetimes of nitrogen oxides (NO x ) based on tropospheric nitrogen dioxide (NO 2 ) observations together with reanalysis wind fields for cities located in polluted backgrounds. Since the accuracy of the method is difficult to assess due to lack of “true values” that can be used as a benchmark, we apply the method to synthetic NO 2 observations derived from the NASA-Unified Weather Research and Forecasting (NU-WRF) model at a high horizontal spatial resolution of 4 km × 4 km for cities over the continental United States. We compare the inferred emissions and lifetimes with the values given by the NU-WRF model to evaluate the method. The method is applicable to 26 US cities. The derived results are generally in good agreement with the values given by the model, with the relative differences of 2 % ± 17 % (mean ± standard deviation) and 15 % ± 25 % for lifetimes and emissions, respectively. Our investigation suggests that the use of wind data prior to the satellite overpass time improves the performance of the method. The correlation coefficients between inferred and NU-WRF lifetimes increase from 0.56 to 0.79 and for emissions increase from 0.88 to 0.96 when comparing results based on wind fields sampled simultaneously with satellite observations and averaged over 9 h data prior to satellite observations, respectively. We estimate that uncertainties in NO x lifetime and emissions arising from the method are approximately 15 % and 20 %, respectively, for typical (US) cities. The total uncertainties reach up to 43% (lifetimes) and 45% (emissions) by considering the additional uncertainties associated with satellite NO 2 observations and wind data. We expect this new method to be applicable to NO 2 observations from the TROPOspheric Monitoring Instrument (TROPOMI) and geostationary satellites, such as Geostationary Environment Monitoring Spectrometer (GEMS) or the Tropospheric Emissions: Monitoring Pollution (TEMPO) instrument, to estimate urban NO x emissions and lifetimes globally.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Strain–Activated Stimulated Emission from Multilayer MoSe 2 in a Narrow Operation Window

Herein, photoluminescence (PL) and fluorescence lifetime imaging (FLIM) in multilayer MoSe 2 are studied. Strain-activated stimulated emission via defect levels in multilayer MoSe 2 under laser excitation is observed, for the first time in defects of transition metal dichalcogenides. The stimulated emission is indicated by a threshold behavior of PL emission intensity with respect to laser intensity, strong polarization effects, achieved population inversion with a difference in lifetimes of two competing excited states, and localization of the stimulated emission zone as observed in FLIM. Here, the presented results not only demonstrate strain-activated stimulated emission and highlight the necessity of strain engineering in tailoring 2D layered materials for optoelectronic applications, but also shed light on the design of stimulated emission in transition metal dichalcogenide's defects to tailor for potential single-photon emission behavior.

enhanced emission↗
DOE OSTI2021

The effect of price-based demand response on carbon emissions in European electricity markets: The importance of adequate carbon prices

Price-based demand response (PBDR) has recently been attributed great economic but also environmental potential. However, the determination of its short-term effects on carbon emissions requires the knowledge of marginal emission factors (MEFs), which compared to grid mix emission factors (XEFs), are cumbersome to calculate due to the complex characteristics of national electricity markets. This study, therefore, proposes two merit order-based methods to approximate hourly MEFs and applies them to readily available datasets from 20 European countries for the years 2017–2019. Based on the calculated electricity prices, standardized daily load shifts were simulated which indicated that carbon emissions increased for 8 of the 20 countries and by 2.1% on average. Thus, under specific circumstances, PBDR leads to carbon emissions increases, mainly due to the economic advantage fuel sources such as lignite and coal have in the merit order. MEF-based load shifts reduced the mean resulting carbon emissions by 35%, albeit with 56% lower monetary cost savings compared to price-based load shifts. Finally, by repeating the load shift simulations for different carbon price levels, the impact of the carbon price on the resulting carbon emissions was analyzed. The Spearman correlation coefficient between carbon intensity and marginal cost along the German merit order substantially increased with increasing carbon price. The coefficients were -0.13 for the 2019 carbon price of 24.9 €/t, 0 for 42.6 €/t, and 0.4 for 100.0 €/t. Therefore, with adequate carbon prices, PBDR can be an effective tool for both economical and environmental improvement.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Wildland Urban Interface (WUI) Emissions: Laboratory Measurement of Aerosol and Trace Gas from Combustion of Manufactured Building Materials

Wildfires are increasing in intensity and more often threatening the wildland urban interface (WUI) where buildings and homes coexist with the natural environment. WUI emissions have not been as well-studied as emissions from vegetation. Thus, there is a need to quantify the emissions of building materials used in home construction under flaming and smoldering conditions to study their impacts to human health, visibility, air quality, and climate. Here, in a controlled laboratory setting, we quantify emissions of aerosols and trace gases including formaldehyde, particulate matter, and black carbon. We focus on the combustion of traditional single-source wood-based construction fuels. Our results indicate that, similar to natural fuels, the aerosol optical properties were more related to combustion conditions than the fuel type. Overall, we observed significant variability in the gas and particle emissions. Consistent trends include high formaldehyde (HCHO) and carbon monoxide (CO) emissions for smoldering conditions and higher carbon dioxide (CO 2 ), nitrogen oxides (NO x ), and black carbon for flaming conditions. Finally, these observations highlight the need to better characterize emissions for materials in the built environment to assess large-scale climate and human health impacts of fires at the WUI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Global, Regional, and National Fossil-Fuel CO2 Emissions: 1751-2017

This data product is a time series of Carbon Dioxide (CO2) emissions from fossil fuel combustion and cement manufacture. Estimates of CO2 emissions are included for the globe and by nation back to 1751, and include emissions from solid fuel consumption, liquid fuel consumption, gas fuel consumption, cement production, and gas flaring. Per capita CO2 emissions and emissions from international trade (bunker fuels) are included as well; bunker fuels are not included in country totals, but are assigned to the country in which loading took place. Estimates are generated using the United Nations Energy Statistics database and the United States Geologic Survey’s cement statistics. Datasets produced from this group at Appalachian State University are located here, and are also located at https://energy.appstate.edu/research/work-areas/cdiac-appstate. Historic CDIAC data from Oak Ridge National Laboratory are located here: https://data.ess-dive.lbl.gov/view/doi:10.3334/CDIAC/00001_V2017. This dataset is the foundational dataset for the annual global carbon budget and other carbon cycle analyses that need relevant fossil fuel CO2 data. Within this data package are spreadsheets (.csv) of global and national estimates of CO2 emissions as well as text files of the ranking of each country’s total CO2 emissions and per capita for that year.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The DREAM approach to demand-side emissions reductions in Indonesia, 2020–2060

Indonesia’s current energy system modeling is heavily focused on the supply side, but emissions reductions in the demand sector have a significant impact on advancing Indonesia’s ambitious emissions reductions goals. To address the gap, we develop a new modeling tool DREAM Indonesia based on a bottom-up, technology-rich demand side framework and formulate projections of demand-side emissions reductions in Indonesia in 2020–2060. We find that demand-side energy efficiency and electrification can halve the growth rate of final energy demand to 1.4% annually over 2020–2060 and reverse the growing trend of emissions. The feasibility of full electrification by 2060, coupled with rapid adoption of existing technologies, positions the building sector as a model for achievable decarbonization and a cornerstone of Indonesia’s emissions reductions ambitions. In the industrial sector, extensive emissions reductions of 87% by 2060 (compared to business-as-usual) are achievable through energy efficiency improvements, alongside enhanced material efficiency measures including optimized material usage, low-carbon substitutions, innovative technologies, and increased circularity. In the transportation sector, balancing final energy demand by incorporating energy efficiency improvements across all transport modes, along with electrification particularly in road transportation, could decrease the emissions by up to 82% in 2060 compared to business-as-usual. This study provides insights and modeling approaches for rapidly growing Asian economies as well as other developing countries facing combined development and decarbonization challenges.

DREAM Indonesia↗
DOE OSTI2022

Impact of landscape design on the greenhouse gas emissions of shrub willow bioenergy buffers in a US Midwest corn-production landscape

Previous studies have evaluated the economics and ecosystem services of perennial bioenergy crops when replacing grain crops on marginal (environmentally critical and/or underproductive) lands. This study used life-cycle analysis (LCA) to investigate the greenhouse gas (GHG) emissions of perennial crops when grown in targeted landscape positions and their impact in reducing nitrogen leaching. Specifically, LCA was performed to evaluate the GHG emissions of growing shrub willow on marginal lands in the Indian Creek watershed in Illinois to assess the sustainability of strategically planted willow buffer strips. Willow was grown as a short-rotation woody crop with a 21-year rotation under three scenarios including a business-as-usual (BAU) field-scale production with nitrogen fertilizer application and two unfertilized subfield buffer scenarios – landscape single subfield (LSSF) or landscape multiple subfields (LMSF) – grown alongside cornfields to reduce nitrate leaching. Each scenario also considers three field sizes, 2.0, 10.1, and 40.5 ha. The average annual GHG emissions from willow production and depot transportation were 0.32–0.77 Mg-CO 2 e ha-1 with the lowest emissions for the LSSF scenario and highest for the BAU. The GHG emissions for the LSSF and BAU scenarios are independent of field size, whereas LMSF emissions increase with increasing field size, 0.41 Mg-CO 2 e ha-1 at 2.0 ha and 0.76 Mg-CO 2 e ha-1 at 40.5 ha. Emission results were most sensitive to the willow yield, followed by fertilizer application rate (BAU only), harvest fuel consumption, and transportation distance.

09 BIOMASS FUELS↗
DOE OSTI2023

Cost and Life Cycle Analysis for Deep CO 2 Emissions Reduction for Steel Making: Direct Reduced Iron Technologies

Among heavy industrial sectors worldwide, the steel industry ranks first in carbon dioxide (CO 2 ) emissions. Technologies that produce direct reduced iron (DRI) enable the industry to reduce emissions or even approach net‐zero CO 2 emissions for steel production. Herein, comprehensive cradle‐to‐gate (CTG) life cycle analysis (LCA) and techno‐economic analysis (TEA) are used to evaluate the CO 2 emissions of three DRI technologies. Compared to the baseline of blast furnace and basic oxygen furnace (BF–BOF) technology for steel making, using natural gas (NG) to produce DRI has the potential to reduce CTG CO 2 emissions by 33%. When 83% or 100% renewable H 2 is used for DRI production, DRI technologies can potentially reduce CO 2 emissions by 57% and 67%, respectively, compared to baseline BF–BOF technology. However, the renewable H 2 application for DRI increases the levelized cost of steel (LCOS). When renewable natural gas (RNG) and clean electricity are used for steel production, the CTG CO 2 emissions of all the DRI technologies can potentially be reduced by more than 90% compared to the baseline BF–BOF technology, although the LCOS depends largely on the cost of RNG and clean electricity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Derivation and assessment of regional electricity generation emission factors in the USA

Electricity production is one of the largest sources of environmental emissions - especially greenhouse gases (GHGs) - in the USA. Emission factors (EFs) vary from region to region, which requires the use of spatially relevant EF data for electricity production while performing life cycle assessments (LCAs). Uncertainty information, which is sought by LCA practitioners, is rarely supplied with available life cycle inventories (LCIs). To address these challenges, we present a method for collecting data from different sources for electricity generation and environmental emissions; discuss the challenges involved in agglomerating such data; provide relevant suggestions and solutions to merge the information; and calculate EFs for electricity generation processes from various fuel sources for different spatial regions and spatial resolutions. The EFs from the US 2016 Electricity Life Cycle Inventory (eLCI) are analyzed and explored in this study. We also explore the method of uncertainty information derivation for the EFs. We explore the EFs from different technologies across Emissions & Generation Resource Integrated Database (eGRID) regions in the USA. We find that for certain eGRID regions, the same electricity production technology may have worse emissions. This may be a result of the age of the plants in the region, the quality of fuel used, or other underlying factors. Region-wise life cycle impact assessment (LCIA) ISO 14040 impacts for total generation mix activities provide an overview of the total sustainability profile of electricity production in a particular region, rather than only global warming potential (GWP). We also find that, for different LCIA impacts, several eGRID regions are consistently worse than the US average LCIA impact for every unit of electricity generated. Here this work describes the development of an electricity production LCI at different spatial resolutions by combining and harmonizing information from several databases. The inventory consists of emissions, fuel inputs, and electricity and steam outputs from different electricity production technologies located across various regions of the USA. This LCI for electricity production in the USA will prove to be an enormous resource for all LCA researchers - considering the detailed sources of the information and the breadth of emissions covered by it.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Causality guided machine learning model on wetland CH 4 emissions across global wetlands

Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Characterization and microbial mitigation of fugitive methane emissions from oil and gas wells: Example from Indiana, USA

Hydrocarbon gas emissions from active, inactive, and improperly sealed or abandoned oil/gas wells significantly contribute to anthropogenically emitted greenhouse gases, predominantly in the form of methane (CH 4 ). We explored the extent of hydrocarbon gas emissions from 20 active, inactive, plugged and abandoned oil/gas wells in Indiana (USA), where it is estimated that there are more than 80,000 well sites throughout the state. After this initial survey, using a static flux tent, we quantified fugitive CH4 emissions from an active gas well to approximately 2 L h -1 . To evaluate the potential for microbial mitigation of hydrocarbon emissions to the atmosphere, we conducted laboratory microcosm experiments to quantify the CH 4 oxidizing potential of soils collected from sites with varying distances to the leaking gas well. Soils in close proximity to the well (0.5 m) efficiently consumed nearly all (97 %) of the added CH 4 , while only 14 % of added CH 4 was consumed by soils that were more distant from the well (20 m). These results suggest that fugitive CH 4 emissions enrich methanotrophic bacteria in soils immediately adjacent to the well. Consistent with this view, we found that prolonged exposure of soils to elevated concentrations of CH 4 enhanced the methanotrophic activity. Together, these findings prompted us to design a “methanotrophic soil mound” to assess the feasibility of mitigating point sources of CH 4 by harnessing the natural methanotrophic capacity of soil microbial communities. We found that a methanotrophic soil mound from a landfill could sustainably mitigate the CH 4 emission from the artificial source, providing a promising low-cost solution to ameliorate fugitive CH 4 emissions from abandoned oil and gas wells to the atmosphere. Finally, the effectiveness of microbe-based remediation is limited in cold climates and arid environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Whole-building life-cycle analysis with a new GREET® tool: Embodied greenhouse gas emissions and payback period of a LEED-Certified library

Embodied greenhouse gas (GHG) emissions of building components and buildings operations need to be quantified to holistically address building sustainability. To evaluate embodied GHG emissions of buildings and to provide insights on building materials and building design decisions toward decarbonization, we have recently created a building life-cycle assessment (LCA) module in the widely used Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET (R)) LCA model. We applied the GREET building LCA module to examine embodied GHG impacts and the payback period of a LEED (Leadership in Energy and Environmental Design) certified public library in Chicago, USA. We developed localized, detailed life-cycle inventories to address individual building materials used in the library. We expanded the LCA system boundary to include the mechanical, electrical, and plumbing system, as well as refrigerant impacts, which are often ignored in previous studies. Results show that the total embodied GHG emissions are approximately 817 metric tons, or approximately 538 kg/m 2 . Sensitivity analysis highlights the positive role of increasing the use of recycled materials for reducing embodied GHG emissions. Sensitivity analysis on embodied GHG emissions payback periods shows the need to benchmark the embodied and operational carbon performance of buildings for comparison to alternative building designs and sustainability practices. Furthermore, this analysis demonstrates that building LCA models, such as the GREET building LCA module, which addresses embodied and operational GHG emission impacts of whole buildings holistically, could empower building architects, technology developers, manufacturers, and general contractors to address embodied and operational impacts holistically for building sustainability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

The path to 2060: Saudi Arabia's long-term pathway for GHG emission reduction

Saudi Arabia, as part of its Saudi Green Initiative, has announced its goal to achieve net zero green-house gas emissions by 2060. This ambitious target underscores the nation's dedication to address-ing climate change. However, there is a significant gap in comprehensive analysis regarding the long-term effects of Saudi Arabia's climate policies and their collective contribution towards the net-zero objective. This study endeavors to bridge this gap through a detailed examination using the GCAM-KSA, a specialized version of the Global Change Analysis Model tailored for Saudi Arabia, employing a multi-sectoral methodology that integrates economic, energy, and land use systems within a coherent framework to assess the impact of climate policies on GHG emissions. Our anal-ysis reveals that reaching net-zero GHG emissions by 2060 is a complex challenge requiring con-certed efforts across all sectors of the economy. While transitioning to low-carbon electricity and improving energy efficiency offer considerable emission reductions, fully decarbonizing the indus-trial and transportation sectors poses a significant hurdle. Our findings suggest that Saudi Arabia must triple its emission reduction commitments in its next Nationally Determined Contributions (NDCs) update to align with its 2060 net-zero goal. Early action and increased ambition could avoid the chances of getting locked into the high emission assets and give enough time to transform the energy system. Furthermore, the adoption and integration of Carbon Dioxide Removal (CDR) tech-nologies are identified as crucial for offsetting residual emissions, especially in sectors that might continue to rely on fossil fuels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Impact of grassland fire dynamics on particulate emission factors

Understanding particulate emission factors in grassland fires is critical for improving air quality assessments and refining emissions inventories. This study explores the dynamic and heterogeneous nature of fire processes and their influence on particulate emissions. Traditional emission factor inventories often rely on static values, overlooking the spatially and temporally variable dynamics of fire behavior. Through field experiments conducted at Konza Prairie Biological Station measuring emissions with uncrewed aerial vehicles, and computational modeling using HIGRAD/FIRETEC, this research highlights the dependency of emission production on localized fire dynamics, including ignition patterns, fuel properties, and atmospheric conditions. The results demonstrate a need for fire dynamic considerations to accurately capture emissions variability.

09 BIOMASS FUELS↗
DOE OSTI2020

Dicarboxylic acid emissions from a GDI engine equipped with a catalytic gasoline particulate filter

Dicarboxylic acids play an important role in atmospheric chemistry, yet their emissions from primary sources, such as internal combustion engines, has not been extensively studied. In this paper, KOH impregnated quartz filters were loaded with exhaust gases from a gasoline direct injection (GDI) engine equipped with a catalytic gasoline particulate filter (GPF). All filters were analyzed for carboxylic and dicarboxylic acids using a derivatized gas chromatography-mass spectroscopy method. Exhaust gas was sampled from pre-GPF and post-GPF locations to determine the performance of the GPF regarding acid conversion. Lean and stoichiometric engine modes were considered with non-oxygenated gasoline and 10% splash blended ethanol in gasoline (E10) to examine the impact of stoichiometry and fuel type. Acid emissions represented as much as 0.51% of total unburned hydrocarbon emissions for total monocarboxylic acids and as much as 0.40% for total dicarboxylic acids. Individual acid concentrations were as high as 38 mg/kg-fuel for monocarboxylic acids and as high as 29 mg/kg-fuel for dicarboxylic acids. Overall, the study found that fuel oxygenates had mixed impact on the acid emissions. Engine-out monocarboxylic acids were reduced when using the E10 fuel by approximately 30–45% for the stoichiometric condition and increased marginally for the lean condition. Dicarboxylic acid emissions were generally insensitive to ethanol content. However, the engine condition significantly affected the acid emissions. Lean operation produced a factor of two to an order of magnitude higher emissions rates of both monocarboxylic and dicarboxylic acids than the stoichiometric condition. The catalytic GPF eliminated between 80 and 92% of the acids emitted from the engine, allowing some acids to be emitted into the environment.

42 ENGINEERING↗
DOE OSTI2020

Investigating relationship between surface topography and emissivity of metallic additively manufactured parts

Due to the direct relationship between thermal history and mechanical behavior, in situ thermal monitoring is key in gauging quality of parts produced with additive manufacturing (AM). Accurate monitoring of temperatures in an AM process requires knowledge of environment and object parameters including object emissivity. The emissivity is dependent on several variables, including: wavelength, material composition, temperature, and surface topography. Researchers have been concerned with the thermal emissivity dependence on temperature since large ranges are seen in metal powder bed processes, but there is also an extensive range of surfaces produced by AM. This work focused on discovering what roughness characteristics control thermal emissivity through investigation of prototypic 316 stainless steel AM samples produced with a range of build conditions on a laser powder bed fusion machine. Through experimental measurements of emissivity using hemispherical directional reflectance (HDR), guided by simulations using a finite-difference time-domain (FDTD) Maxwell solver, it was found that combinations of existing roughness parameters describing both height and slope of the surface correlate well with emissivity changes. Furthermore, these parameters work well due to their apt description of surface features encouraging internal reflection, which is the phenomenon that increases emissivity when a surface falls under the geometric optical region conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Life cycle greenhouse gas emissions of different CO 2 supply options for an algal biorefinery

This paper characterizes the greenhouse gas (GHG) emissions from the provision of CO 2 for twelve hours of the day from a range of sources operating on a twenty-four-hour basis. Twelve CO 2 supply cases spanning from fossil fuel power plant stack gases to direct air capture (DAC) systems are modeled. The results are compared in a life cycle assessment (LCA) framework. The CO 2 supply from the combustion or gasification of biomass has GHG emissions of –1.62 gCO 2 eq./g CO 2 delivered and is the case with the lowest carbon footprint for supplied CO2. The emissions for all the CO 2 supply cases were found to be negative, either because of capturing more CO 2 from the atmosphere than is released from the CO 2 production process, or because of production of excess electricity that is exported to the grid (replacing emissions from grid electricity). A purpose-built Natural Gas Combined Cycle (NGCC) power plant CO 2 source has the highest GHG emissions of -0.40 gCO 2 eq./gCO 2 delivered of the cases considered because of nighttime emissions and natural gas supply chain losses. The impact of a diurnal cycle can be mitigated by using capture and refrigeration systems as part of the CO 2 management system. The results are sensitive to the GHG emissions of the grid electricity, which is imported or exported in different cases. The results provide a benchmark for the comparison of different CO 2 supply options for the establishment of a sustainable algal biorefinery.

42 ENGINEERING↗