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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Study of vacuum ultraviolet emission in helium and helium/nitrogen mixtures

Helium is frequently used as a working medium for the generation of plasmas and is capable of energetic photon emissions. These energetic photon emissions are often attributed to the formation of helium excimer and subsequent photon emission. When the plasma device is exposed to another gas, such as nitrogen, this energetic photon emission can cause photoionization and further ionization wave penetration into the additional gas. Often ignored are the helium resonance emissions that are assumed to be radiation trapped and therefore not pertinent to photoionization. Here, experimental evidence for the presence of helium atomic emission in a pulsed discharge at ten’s of Torr is shown. Simulations of a discharge in similar conditions agree with the experimental measurements. In this context, the role of atomic and molecular helium light emission on photoionization of molecular nitrogen in an ionization wave is studied using a kinetic modeling approach that accounts for radiation dynamics in a developing low-temperature plasma. Three different mixtures of helium at a total pressure of 250 Torr are studied in simulation. Photoionization of the nitrogen molecule by vacuum ultraviolet helium emission is used as the only seed source ahead of the ionization front. It is found that even though radiation trapped, the atomic helium emission lines are the significant source of photoionization of nitrogen. The significant effect of radiation trapped photon emission on ionization wave dynamics demonstrates the need to consider these radiation dynamics in plasma reactors where self-absorbed radiation is ignored.

42 ENGINEERING↗
DOE OSTI2023

The Sustainability Index: a new tool to breed for reduced greenhouse-gas emissions intensity in Australian dairy cattle

Context The Australian dairy industry has a target to reduce greenhouse-gas (GHG) emissions intensity by 30% between 2015 and 2030. At the animal level, apart from nutritional modifications and other management practices, selecting animals that emit less GHG can be a cost-effective and long-term strategy. Given the world’s demand for protein is increasing, selecting for animals with lower GHG emissions per unit of production, i.e. emissions intensity, is a realistic approach that addresses the key issue of emissions reduction while maintaining farm productivity. Aim To develop a selection index for Australian dairy cattle to breed for reduced emissions intensity. Methods The Sustainability Index was built based on the existing Balanced Performance Index (BPI) but placed greater emphasis on production, survival, health and feed efficiency. Key results In August 2022, DataGene released the Sustainability Index that can be used by dairy farmers to select animals with lower environmental footprints. Compared with BPI, the weights for protein, fat, survival, mastitis resistance and feed efficiency increased by 2.6-, 1.4-, 2.8-, 1.3- and 3.8-fold respectively. It is expected that with the use of the Sustainability Index, emissions intensity will be reduced by 7.64%, 8.96% and 5.52% respectively in Holstein, Jersey and Red breeds by 2050, compared with the 2015 level. The corresponding values when selecting for BPI were 6.34%, 7.91% and 5.23% respectively. However, the trade-off in BPI when using the Sustainability Index will be AUD0.79, AUD0.83, AUD0.22 per cow per year for Holstein, Jersey and Red breeds respectively. Conclusions The current profit index BPI has contributed to reduction in emissions intensity. To enhance the rate of improvement in emissions intensity, the Sustainability Index can be used with minimal impacts on profit. Implications To breed for lower emissions intensity, farmers can select animals with high Sustainability Index values that are published on DataVat (datavat.com.au) and the Good Bulls App. To lower gross emissions, combinations of additional measures such as management of diet, adjustment to animal numbers, management of stored manure, and appropriate use of carbon neutral fertiliser, renewable fuels and energy, will need to be adopted on farms.

Agriculture↗
DOE OSTI2018

Search for C II emission on cosmological scales at redshift Z ~ 2.6

We present a search for C II emission over cosmological scales at high redshifts. The C II line is a prime candidate to be a tracer of star formation over large-scale structure since it is one of the brightest emission lines from galaxies. Redshifted C II emission appears in the submillimeter regime, which means it could potentially be present in the higher frequency intensity data from the Planck satellite is used to measure the cosmic infrared background (CIB). We search for C II emission over redshifts z = 2–3.2 in the Planck 545 GHz intensity map by cross-correlating the three highest frequency Planck maps with spectroscopic quasars and CMASS galaxies from the Sloan Digital Sky Survey III, which we then use to jointly fit C II intensity, CIB parameters, and thermal Sunyaev–Zeldovich (SZ) emission. We report a measurement of an anomalous emission I ν = 6.6 +5.0 –4.8 × 10 4 Jy sr –1 at 95 percent confidence, which could be explained by C II emission, favouring collisional excitation models of C II emission that tend to be more optimistic than models based on C II luminosity scaling relations from local measurements; however, a comparison of Bayesian information criteria reveals that this model and the CIB & SZ model are equally plausible. Thus, more sensitive measurements will be needed to confirm the existence of a large-scale C II emission at high redshifts. Lastly, we forecast that intensity maps from Planck cross-correlated with quasars from the Dark Energy Spectroscopic Instrument would increase our sensitivity to C II emission by a factor of 5, while the proposed Primordial Inflation Explorer could increase the sensitivity further.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Core collapse supernova gravitational wave emission for progenitors of 9.6, 15, and 25 M ⊙

Here, we present gravitational wave emission predictions based on three core collapse supernova simulations corresponding to three different progenitor masses. The masses span a large range, between 9.6 and 25M ⊙ , are all initially nonrotating, and are of two metallicities: zero and solar. We compute both the temporal evolution of the gravitational wave strains for both the plus and the cross polarizations, as well as their spectral decomposition and characteristic strains. The temporal evolution of our zero metallicity 9.6M ⊙ progenitor model is distinct from the temporal evolution of our solar metallicity 15M ⊙ progenitor model and our zero metallicity 25M ⊙ progenitor model. In the former case, the high-frequency gravitational wave emission is largely confined to a brief time period ~75 ms after bounce, whereas in the latter two cases high-frequency emission does not commence until ~125 ms after bounce or later. The excitation mechanisms of the high-frequency emission in all three cases correspond to proto-neutron star convection and accretion onto the proto-neutron star from the convective gain layer above it, with the former playing the dominant role for most of the evolution. The low-frequency emission in all three models exhibits very similar behavior. At frequencies below ~250 Hz, gravitational waves are emitted by neutrino-driven convection and the standing accretion shock instability (SASI). This emission extends throughout the simulations when a gain region is present. In all three models, explosion is observed at ~125, ~500, and ~250 ms after bounce in the 9.6, 15, and 25M ⊙ progenitor models, respectively. At these times, the low-frequency gravitational wave emission is joined by very low-frequency emission, below ~10 Hz. These very low-frequency episodes are the result of explosion and begin at the above designated explosion times in each of our models. Our characteristic strains tell us that, in principle, all three gravitational wave signals would be detectable by current-generation detectors for a supernova at a distance of 10 kpc. However, our 9.6M ⊙ progenitor model is a significantly weaker source of gravitational waves, with strain amplitudes approximately 5–10 times less than in our other two models. The characteristic strain for this model tells us that such a supernova would be detectable only within a much more narrow frequency range around the maximum sensitivity of today’s detectors. Finally, in our 9.6M ⊙ progenitor model, we see very high-frequency gravitational radiation, extending up to ~2000 Hz. This feature results from the interaction of shock- and deleptonization-induced convection with perturbations introduced in the progenitor by nuclear burning during core collapse. While unique to the 9.6M ⊙ progenitor model analyzed here, this very high-frequency emission may, in fact, be a generic feature of the predictions for the gravitational wave emission from all core collapse supernova models when simulations are performed with three-dimensional progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The role of shale gas in shaping the U.S. long-run CO 2 emissions

The shale gas boom in the U.S. has lowered the U.S. CO 2 emissions in recent years mainly through substitution of gas for coal in power generation. Will the shale gas boom reduce the emissions in the long-run as well? To study this, we consider a counterfactual without the shale gas boom based on a general equilibrium modeling for the 2011 U.S. economy. To enhance the power sector modeling, the supply responses of coal-fired and gas-fired generations are calibrated to existing research. We find that if gas prices remain at 2007 levels in 2011, only a model setting that allows very little reduction in electricity demand, reflecting a short-run demand response, generates an increase in economy-wide emissions. For all other cases, the higher gas price under the counterfactual will have a dampening effect on economic activities and consequently lowers economy-wide emissions, even though the power sector emissions may increase due to the gas-to-coal switch. In other words, without any policy intervention, although the shale gas boom could reduce emissions in the short run, it may lead to higher emissions in the long run if the low gas prices persist. Our finding suggests that extrapolating the current decline in emissions due to the shale gas boom to the distant future could be misleading. Instead, if curbing emissions is the goal, rather than depending upon the cheap gas, policies and measures for cutting emissions remain imperative.

Chen, Y. -H. Henry↗
DOE OSTI2011

A Greenhouse-Gas Information System: Monitoring and Validating Emissions Reporting and Mitigation

Current GHG-mitigating regimes, whether internationally agreed or self-imposed, rely on the aggregation of self-reported data, with limited checks for consistency and accuracy, for monitoring. As nations commit to more stringent GHG emissions-mitigation actions and as economic rewards or penalties are attached to emission levels, self-reported data will require independent confirmation that they are accurate and reliable, if they are to provide the basis for critical choices and actions that may be required. Supporting emissions-mitigation efforts and agreements, as well as monitoring energy- and fossil-fuel intensive national and global activities would be best achieved by a process of: (1) monitoring of emissions and emission-mitigation actions, based, in part, on, (2) (self-) reporting of pertinent bottom-up inventory data, (3) verification that reported data derive from and are consistent with agreed-upon processes and procedures, and (4) validation that reported emissions and emissions-mitigation action data are correct, based on independent measurements (top-down) derived from a suite of sensors in space, air, land, and, possibly, sea, used to deduce and attribute anthropogenic emissions. These data would be assessed and used to deduce and attribute measured GHG concentrations to anthropogenic emissions, attributed geographically and, to the extent possible, by economic sector. The validation element is needed to provide independent assurance that emissions are in accord with reported values, and should be considered as an important addition to the accepted MRV process, leading to a MRV&V process. This study and report focus on attributes of a greenhouse-gas information system (GHGIS) needed to support MRV&V needs. These needs set the function of such a system apart from scientific/research monitoring of GHGs and carbon-cycle systems, and include (not exclusively): the need for a GHGIS that is operational, as required for decision-support; the need for a system that meets specifications derived from imposed requirements; the need for rigorous calibration, verification, and validation (CV&V) standards, processes, and records for all measurement and modeling/data-inversion data; the need to develop and adopt an uncertainty-quantification (UQ) regimen for all measurement and modeling data; and the requirement that GHGIS products can be subjected to third-party questioning and scientific scrutiny. This report examines and assesses presently available capabilities that could contribute to a future GHGIS. These capabilities include sensors and measurement technologies; data analysis and data uncertainty quantification (UQ) practices and methods; and model-based data-inversion practices, methods, and their associated UQ. The report further examines the need for traceable calibration, verification, and validation processes and attached metadata; differences between present science-/research-oriented needs and those that would be required for an operational GHGIS; the development, operation, and maintenance of a GHGIS missions-operations center (GMOC); and the complex systems engineering and integration that would be required to develop, operate, and evolve a future GHGIS. Present monitoring systems would be heavily relied on in any GHGIS implementation at the outset and would likely continue to provide valuable future contributions to GHGIS. However, present monitoring systems were developed to serve science/research purposes. This study concludes that no component or capability presently available is at the level of technological maturity and readiness required for implementation in an operational GHGIS today. However, purpose-designed and -built components could be developed and implemented in support of a future GHGIS. The study concludes that it is possible to develop and provide a capability-driven prototype GHGIS, as part of a Phase-1 effort, within three years from project-funding start, that would make use of and integrate existing sensing and system capabilities. As part of a Phase-2 effort, a requirements-driven, operational GHGIS could be developed, within ten years from project funding start. That schedule is driven by the development and long lead-times for some system components. The two efforts would be focused on different deliverables but could commence concurrently, to save time, if that was deemed desirable. We note that, developing and supporting an operational GHGIS will require a new approach and management, sustained funding and other support, as well as technical advances and development of purpose-built components that meet the requisite specifications. A functioning GHGIS will provide the basis for reasoned choices on how best to respond to rising GHG levels, especially when proposed U.S. actions are compared with or conditioned on the actions of other nations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Updated Greenhouse Gas and Criteria Air Pollutant Emission Factors and Their Probability Distribution Functions for Electricity Generating Units

Greenhouse gas (CO 2 , CH 4 and N 2 O, hereinafter GHG) and criteria air pollutant (CO, NO x , VOC, PM 10 , PM 2.5 and SO x , hereinafter CAP) emission factors for various types of power plants burning various fuels with different technologies are important upstream parameters for estimating life-cycle emissions associated with alternative vehicle/fuel systems in the transportation sector, especially electric vehicles. The emission factors are typically expressed in grams of GHG or CAP per kWh of electricity generated by a specific power generation technology. This document describes our approach for updating and expanding GHG and CAP emission factors in the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model developed at Argonne National Laboratory (see Wang 1999 and the GREET website at http://greet.es.anl.gov/main) for various power generation technologies. These GHG and CAP emissions are used to estimate the impact of electricity use by stationary and transportation applications on their fuel-cycle emissions. The electricity generation mixes and the fuel shares attributable to various combustion technologies at the national, regional and state levels are also updated in this document. The energy conversion efficiencies of electric generating units (EGUs) by fuel type and combustion technology are calculated on the basis of the lower heating values of each fuel, to be consistent with the basis used in GREET for transportation fuels. On the basis of the updated GHG and CAP emission factors and energy efficiencies of EGUs, the probability distribution functions (PDFs), which are functions that describe the relative likelihood for the emission factors and energy efficiencies as random variables to take on a given value by the integral of their own probability distributions, are updated using best-fit statistical curves to characterize the uncertainties associated with GHG and CAP emissions in life-cycle modeling with GREET.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Low Emissions Burner Technology for Metal Processing Industry using Byproducts and Biomass Derived Liquid Fuels (Final Report)

This research and development efforts produced low-emission burner technology capable of operating on natural gas as well as crude glycerin and/or fatty acids generated in biodiesel plants. The research was conducted in three stages (1) Concept definition leading to the design and development of a small laboratory scale burner, (2) Scale-up to prototype burner design and development, and (3) Technology demonstration with field vefiication. The burner design relies upon the Flow Blurring (FB) fuel injection based on aerodynamically creating two-phase flow near the injector exit. The fuel tube and discharge orifice both of inside diameter D are separated by gap H. For H < 0.25D, the atomizing air bubbles into liquid fuel to create a two-phase flow near the tip of the fuel tube. Pressurized two-phase fuel-air mixture exits through the discharge orifice, which results in expansion and breakup of air bubbles yielding a spray with fine droplets. First, low-emission combustion of diesel, biodiesel and straight VO (soybean oil) was achieved by utilizing FB injector to yield fine sprays for these fuels with significantly different physical properties. Visual images for these baseline experiments conducted with heat release rate (HRR) of about 8 kW illustrate clean blue flames indicating premixed combustion for all three fuels. Radial profiles of the product gas temperature at the combustor exit overlap each other signifying that the combustion efficiency is independent of the fuel. At the combustor exit, the NOx emissions are within the measurement uncertainties, while CO emissions are slightly higher for straight VO as compared to diesel and biodiesel. Considering the large variations in physical and chemical properties of fuels considered, the small differences observed in CO and NOx emissions show promise for fuel-flexible, clean combustion systems. FB injector has proven to be very effective in atomizing fuels with very different physical properties, and it offers a path forward to utilize both fossil and alternative liquid fuels in the same combustion system. In particular, experiments show that straight VO can be cleanly combusted without the need for chemical processing or preheating steps, which can result in significant economic and environmental benefits. Next, low-emission combustion of glycerol/methane was achieved by utilizing FB injector to yield fine droplets of highly viscous glycerol. Heat released from methane combustion further improves glycerol pre-vaporization and thus its clean combustion. Methane addition results in an intensified reaction zone with locally high temperatures near the injector exit. Reduction in methane flow rate elongates the reaction zone, which leads to higher CO emissions and lower NOx emissions. Similarly, higher air to liquid (ALR) mass ratio improves atomization and fuel pre-vaporization and shifts the flame closer to the injector exit. In spite of these internal variations, all fuel mixes of glycerol with methane produced similar CO and NOx emissions at the combustor exit. Results show that FB concept provides low emissions with the flexibility to utilize gaseous and highly viscous liquid fuels, straight VO and glycerol, without preheating or preprocessing the fuels. Following these initial experiments in quartz combustor, we demonstrated that glycerol combustion can be stably sustained in a metal combustor. Phase Doppler Particle Analyzer (PDPA) measurements in glycerol/methane flames resulted in flow-weighted Sauter Mean Diameter (SMD) of 35 to 40 μm, depending upon the methane percentage. This study verified that lab-scale dual-fuel burner using FB injector can successfully atomize and combust glycerol and presumably other highly viscous liquid fuels at relatively low HRR (<10 kW). For industrial applications, a scaled-up glycerol burner design thus seemed feasible.

03 NATURAL GAS↗
DOE OSTI2020

Automated, Unmanned Detection and Quantification of Fugitive Methane Emissions

Compressor stations used to move natural gas are one of the largest sources of fugitive methane emissions in the midstream sector, accounting for approximately 50% of all fugitive emissions (Zimmerle et al., 2015). This problem is most widespread at reciprocating compressors (Subramanian et al., 2015) where faulty seals are a key contributor to methane emissions (Johnson et al., 2015). As such, there is a significant need for a robust technology that could provide an early indication of an unexpected emission. Equally important, the technology needs to be able to account for biogenic versus anthropogenic sources of methane. One means of indirectly making this determination, is to leverage optical technologies that can autonomously pinpoint the source of such leaks. This presentation discusses recent work funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), focused on the development of an innovative remote sensing technology that can reliably and autonomously detect fugitive methane emissions in near real-time, using computer vision and deep learning. The technology called the Smart Methane Leak Detection (SLED/M) system was initially developed to monitor facilities such as compressor stations in a stationary, pan-tilt-zoom configuration. The system has recently been adapted to monitor facilities from an unmanned aerial system (UAS). The speed and maneuverability of UAS platforms are attractive to leak detection and repair program operators, but introduce several challenges. Many existing methane detection algorithms rely on mostly static backgrounds becoming unusable with motion. In addition, top-down views of fugitive methane emissions present differently in Optical Gas Imagers (OGI) compared to looking across the plume. Our work has focused on overcoming these challenges, enhancing the operators ability to detect methane emissions, and pinpoint their sources. Another recent adaptation to SLED/M is the ability to quantify methane emissions using passive sensors (OGI, thermal camera), environmental conditions, plume modeling, and deep learning. SLED/M advances the state-of-the-art for methane emission detection and quantification by focusing on three key critical criteria for effective methane emission mitigation: (1) autonomy (no need for a human to be in the loop), (2) high reliability (low false alarm rates), and (3) real-time performance. Results from this work will be presented.

03 NATURAL GAS↗
DOE OSTI2024

Adoption of Plug-in Electric Vehicles: Local Fuel Use and Greenhouse Gas Emissions Reductions Across the U.S.

The dependence on gasoline-powered light-duty automobiles has made U.S. households vulnerable to the burden of fuel costs. Tailpipe emissions from these vehicles constitute 58% of greenhouse gas (GHG) emissions in the U.S., which are damaging to the environment (EPA, 2023). The adoption of plug-in electric vehicles (PEVs) has been shown to effectively reduce fuel costs and GHG emissions. However, local effects on these benefits are not well understood by American consumers, potentially limiting adoption and therefore the realization of PEV benefits at scale (MacInnis & Krosnick, 2020; EY Americas, 2023). To fill this research gap, this study estimates the fuel cost savings and GHG emission reductions at the state and ZIP code levels by considering local fuel prices, vehicle class preference, average vehicle model year, fuel efficiencies, and driving intensities. The study's findings reveal that the adoption of PEVs can yield substantial benefits in terms of fuel cost savings and GHG emission reductions nationwide. Specifically, driving a battery electric vehicle (BEV) is estimated to result in annual savings of up to $\$2,200$, while driving a plug-in hybrid electric vehicle (PHEV) can lead to savings up to $\$1,500$, when compared to an internal combustion engine vehicle (ICEV) of equivalent size. Moreover, using population-weighted averages by ZIP code, BEVs and PHEVs show the potential to save 400 and 200 grams of carbon dioxide equivalent per mile, respectively, compared to a representative ICEV of the same class. The magnitude of fuel cost savings and emissions reduction vary by region due to various factors. Generally, regions with high gasoline prices, low electricity prices, preferences for larger vehicles, and high driving intensities tend to see relatively large fuel savings. The emissions reductions are more pronounced in areas with clean grids where consumer preferences lie with large vehicles. This regional variability underscores the importance of considering local contextual factors when assessing the potential benefits of PEV adoption. In more than 99% of U.S. ZIP codes, PEVs result in overall savings in fuel use (and subsequent costs) and GHG emissions. While not a central focus of this analysis, reductions in GHG tailpipe emissions from PEV adoption would also come with reductions in criteria pollutant emissions, contributing to improved local air quality depending on the PEV penetration, population density, and electricity generation infrastructure in the locality.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

42 ENGINEERING↗
DOE OSTI2021

Mitigation of Acute Ammonia Emissions With Biochar During Swine Manure Agitation Before Pump-Out: Proof-of-the-Concept

Ammonia (NH 3 ) emissions from animal agriculture can cause eutrophication of water ecosystems and are precursors to secondary particulate matter (PM 2 .5 ). NH 3 emissions from stored swine manure represent nutrient loss affecting the fertilizing value of manure. The short-term emission bursts occur when farmers agitate manure before emptying storage and fertilizing fields. There is no proven technology to mitigate gaseous emissions during agitation, while the hazards of acute releases (e.g., H 2 S) are well-known. Biochar mitigates NH 3 emissions from manure over the long-term. The objective of this research was to evaluate the mitigation of acute NH 3 emissions during/after agitation. Two biochars, highly alkaline and porous (HAP from corn stover) and red oak (RO), were tested. The 6 and 12 mm-thick layers of biochar powder were surficial applied followed by 3 min agitation. NH 3 concentrations were measured before/during/after agitation. Mitigation was assessed by comparing: (i) the maximum (peak) flux, (ii) total emission (from agitation start till NH 3 concentration returned to the before-agitation), and (iii) the total emissions during agitation. The 12 mm HAP significantly ( p < 0.05) reduced (i–iii) by 63, 70, and 85%, respectively. The 6 mm HAP significantly reduced (i–iii) by 76, 75, and 78%, respectively. The 12 mm RO significantly reduced (i–iii) by 9, 53, and 57%, respectively. The 6 mm RO significantly reduced (i–iii) by 61, 86, and 63%, respectively. The NH 3 emission kinetics model confirmed that a 6 mm dose was just as effective as the larger dose. More research is needed to optimize and scale-up mitigating emissions and retention of nutrients in manure with biochar.

Chen, Baitong↗
DOE OSTI2011

Impacts of urban transportation mode split on CO{sub 2} emissions in Jinan, China.

As the world's largest developing country, China currently is undergoing rapid urbanization and motorization, which will result in far-reaching impacts on energy and the environment. According to estimates, energy use and carbon emissions in the transportation sector will comprise roughly 30% of total emissions by 2030. Since the late 1990s, transportation-related issues such as energy, consumption, and carbon emissions have become a policy focus in China. To date, most research and policies have centered on vehicle technologies that promote vehicle efficiency and reduced emissions. Limited research exists on the control of greenhouse gases through mode shifts in urban transportation - in particular, through the promotion of public transit. The purpose of this study is to establish a methodology to analyze carbon emissions from the urban transportation sector at the Chinese city level. By using Jinan, the capital of China's Shandong Province, as an example, we have developed an analytical model to simulate energy consumption and carbon emissions based on the number of trips, the transportation mode split, and the trip distance. This model has enabled us to assess the impacts of the transportation mode split on energy consumption and carbon emissions. Furthermore, this paper reviews a set of methods for data collection, estimation, and processing for situations where statistical data are scarce in China. This paper also describes the simulation of three transportation system development scenarios. The results of this study illustrate that if no policy intervention is implemented for the transportation mode split (the business-as-usual (BAU) case), then emissions from Chinese urban transportation systems will quadruple by 2030. However, a dense, mixed land-use pattern, as well as transportation policies that encourage public transportation, would result in the elimination of 1.93 million tons of carbon emissions - approximately 50% of the BAU scenario emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Impacts of seasonal and regional variability in biogenic VOC emissions on surface ozone in the Pearl River Delta region, China

In this study, the BVOC emissions in November 2010 over the Pearl River Delta (PRD) region in southern China have been estimated by the latest version of a Biogenic Volatile Organic Compound (BVOC) emission model (MEGAN v2.1). The evaluation of MEGAN performance at a representative forest site within this region indicates MEGAN can estimate BVOC emissions reasonably well in this region except overestimating isoprene emission in autumn for reasons that are discussed in this manuscript. Along with the output from MEGAN, the Weather Research and Forecasting model with chemistry (WRF-Chem) is used to estimate the impacts of BVOC emissions on surface ozone in the PRD region. The results show BVOC emissions increase the daytime ozone peak by *3 ppb on average, and the max hourly impacts of BVOC emissions on the daytime ozone peak is 24.8 ppb. Surface ozone mixing ratios in the central area of Guangzhou- Foshan and the western Jiangmen are most sensitive to BVOC emissions BVOCs from outside and central PRD influence the central area of Guangzhou-Foshan and the western Jiangmen significantly while BVOCs from rural PRD mainly influence the western Jiangmen. The impacts of BVOC emissions on surface ozone differ in different PRD cities, and the impact varies in different seasons. Foshan and Jiangmen being most affected in autumn, result in 6.0 ppb and 5.5 ppb increases in surface ozone concentrations, while Guangzhou and Huizhou become more affected in summer. Three additional experiments concerning the sensitivity of surface ozone to MEGAN input variables show that surface ozone is more sensitive to landcover change, followed by emission factors and meteorology.

Situ, S.↗
DOE OSTI2014

Improved Model of Isoprene Emissions in Africa using Ozone Monitoring Instrument (OMI) Satellite Observations of Formaldehyde: Implications for Oxidants and Particulate Matter

We use a 2005-2009 record of isoprene emissions over Africa derived from OMI satellite observations of formaldehyde (HCHO) to better understand the factors controlling isoprene emission on the scale of the continent and evaluate the impact of isoprene emissions on atmospheric composition in Africa. OMI-derived isoprene emissions show large seasonality over savannas driven by temperature and leaf area index (LAI), and much weaker seasonality over equatorial forests driven by temperature. The commonly used MEGAN (version 2.1) global 31 isoprene emission model reproduces this seasonality but is biased high, particularly for 32 equatorial forests, when compared to OMI and relaxed-eddy accumulation measurements. 33 Isoprene emissions in MEGAN are computed as the product of an emission factor Eo, LAI, and 34 activity factors dependent on environmental variables. We use the OMI-derived emissions to 35 provide improved estimates of Eo that are in good agreement with direct leaf measurements from 36 field campaigns (r = 0.55, bias = -19%). The largest downward corrections to MEGAN Eo values are for equatorial forests and semi-arid environments, and this is consistent with latitudinal transects of isoprene over West Africa from the AMMA aircraft campaign. Total emission of isoprene in Africa is estimated to be 77 Tg C a-1, compared to 104 Tg C a-1 in MEGAN. Simulations with the GEOS-Chem oxidant-aerosol model suggest that isoprene emissions increase mean surface ozone in West Africa by up to 8 ppbv, and particulate matter by up to 1.5 42 μg m-3, due to coupling with anthropogenic influences.

Marais, E. A.↗
DOE OSTI2016

Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?

Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60° N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range of 496.4–511.5 Tg yr –1 , and pan-Arctic methane emissions were in the range of 11.9–28.5 Tg yr –1 . Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2 Tg yr –1 , respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.

58 GEOSCIENCES↗
DOE OSTI2016

Network design for quantifying urban CO<sub>2</sub> emissions: assessing trade-offs between precision and network density

The majority of anthropogenic CO 2 emissions are attributable to urban areas. While the emissions from urban electricity generation often occur in locations remote from consumption, many of the other emissions occur within the city limits. Evaluating the effectiveness of strategies for controlling these emissions depends on our ability to observe urban CO 2 emissions and attribute them to specific activities. Cost-effective strategies for doing so have yet to be described. Here we characterize the ability of a prototype measurement network, modeled after the Berkeley Atmospheric CO 2 Observation Network (BEACO 2 N) in California's Bay Area, in combination with an inverse model based on the coupled Weather Research and Forecasting/Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) to improve our understanding of urban emissions. The pseudo-measurement network includes 34 sites at roughly 2 km spacing covering an area of roughly 400 km 2 . The model uses an hourly 1 × 1 km 2 emission inventory and 1 × 1 km 2 meteorological calculations. We perform an ensemble of Bayesian atmospheric inversions to sample the combined effects of uncertainties of the pseudo-measurements and the model. We vary the estimates of the combined uncertainty of the pseudo-observations and model over a range of 20 to 0.005 ppm and vary the number of sites from 1 to 34. We use these inversions to develop statistical models that estimate the efficacy of the combined model–observing system in reducing uncertainty in CO 2 emissions. We examine uncertainty in estimated CO 2 fluxes on the urban scale, as well as for sources embedded within the city such as a line source (e.g., a highway) or a point source (e.g., emissions from the stacks of small industrial facilities). Using our inversion framework, we find that a dense network with moderate precision is the preferred setup for estimating area, line, and point sources from a combined uncertainty and cost perspective. The dense network considered here (modeled after the BEACO 2 N network with an assumed mismatch error of 1 ppm at an hourly temporal resolution) could estimate weekly CO 2 emissions from an urban region with less than 5 % error, given our characterization of the combined observation and model uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP

Here, the MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO 2 , 52.1 Tg NO x , 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH 3 , 31.7 Tg PM 10 , 22.7 Tg PM 2.5 , 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO 2 . Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: –8.1 % for SO 2 , +19.2 % for NO x , +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH 3 , –3.4 % for PM 10 , –1.6 % for PM 2.5 , +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO 2 . Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach.

54 ENVIRONMENTAL SCIENCES↗