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At least 55 records · Page 3

Much of zero emissions commitment occurs before reaching net zero emissions

Abstract We explore the response of the Earth’s coupled climate and carbon system to an idealized sequential addition and removal of CO 2 to the atmosphere, following a symmetric and continuous emissions pathway, in contrast to the discontinuous emissions pathways that have largely informed our understanding of the climate response to net zero and net negative emissions to date. We find, using both an Earth system model and an ensemble of simple climate model realizations, that warming during the emissions reduction and negative emissions phases is defined by a combination of a proportionality of warming to cumulative emissions characterized by the transient climate response to emissions (TCRE), and a deviation from that proportionality that is governed by the zero emissions commitment (ZEC). About half of the ZEC is realized before reaching zero emissions, and the ZEC thus also controls the timing between peak cumulative CO 2 emissions and peak temperature, such that peak temperature may occur before peak cumulative emissions if ZEC is negative, underscoring the importance of ZEC in climate policies aimed to limit peak warming. Thus we argue that ZEC is better defined as the committed warming relative to the expected TCRE proportionality, rather than as the additional committed warming that will occur after reaching net zero CO 2 emissions. Once established, the combined TCRE and ZEC relationship holds almost to complete removal of prior cumulative CO 2 emissions. As cumulative CO 2 emissions approach zero through negative CO 2 emissions, CO 2 concentrations drop below preindustrial values, while residual long-term climate change continues, governed by multicentennial dynamical processes.

54 ENVIRONMENTAL SCIENCES↗

A new process-based and scale-aware desert dust emission scheme for global climate models – Part I: Description and evaluation against inverse modeling emissions

Desert dust accounts for most of the atmosphere's aerosol burden by mass and produces numerous important impacts on the Earth system. However, current global climate models (GCMs) and land-surface models (LSMs) struggle to accurately represent key dust emission processes, in part because of inadequate representations of soil particle sizes that affect the dust emission threshold, surface roughness elements that absorb wind momentum, and boundary-layer characteristics that control wind fluctuations. Furthermore, because dust emission is driven by small-scale (~ 1 km or smaller) processes, simulating the global cycle of desert dust in GCMs with coarse horizontal resolutions (~ 100 km) presents a fundamental challenge. This representation problem is exacerbated by dust emission fluxes scaling nonlinearly with wind speed above a threshold wind speed that is sensitive to land-surface characteristics. Here, we address these fundamental problems underlying the simulation of dust emissions in GCMs and LSMs by developing improved descriptions of (1) the effect of soil texture on the dust emission threshold, (2) the effects of nonerodible roughness elements (both rocks and green vegetation) on the surface wind stress, and (3) the effects of boundary-layer turbulence on driving intermittent dust emissions. We then use the resulting revised dust emission parameterization to simulate global dust emissions in a standalone model forced by reanalysis meteorology and land-surface fields. We further propose (4) a simple methodology to rescale lower-resolution dust emission simulations to match the spatial variability of higher-resolution emission simulations in GCMs. The resulting dust emission simulation shows substantially improved agreement against regional dust emissions observationally constrained by inverse modeling. We thus find that our revised dust emission parameterization can substantially improve dust emission simulations in GCMs and LSMs.

54 ENVIRONMENTAL SCIENCES↗

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, “esm-flat10”, has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 – the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as “fast track” simulations.

Sanderson, Benjamin M↗

Assessing Uncertainties in Gridded Emissions: A Case Study for Fossil Fuel Carbon Dioxide (FFCO2) Emission Data

Fossil fuel carbon dioxide (CO2) emissions (FFCO2) are the largest input to the global carbon cycle on a decadal time scale. Because total emissions are assumed to be reasonably well constrained by fuel statistics, FFCO2 often serves as a reference in order to deduce carbon uptake by poorly understood terrestrial and ocean sinks. Conventional atmospheric CO2 flux inversions solve for spatially explicit regional sources and sinks and estimate land and ocean fluxes by subtracting FFCO2. Thus, errors in FFCO2 can propagate into the final inferred flux estimates. Gridded emissions are often based on disaggregation of emissions estimated at national or regional level. Although national and regional total FFCO2 are well known, gridded emission fields are subject to additional uncertainties due to the emission disaggregation. Assessing such uncertainties is often challenging because of the lack of physical measurements for evaluation. We first review difficulties in assessing uncertainties associated with gridded FFCO2 emission data and present several approaches for evaluation of such uncertainties at multiple scales. Given known limitations, inter-emission data differences are often used as a proxy for the uncertainty. The popular approach allows us to characterize differences in emissions, but does not allow us to fully quantify emission disaggregation biases. Our work aims to vicariously evaluate FFCO2 emission data using atmospheric models and measurements. We show a global simulation experiment where uncertainty estimates are propagated as an atmospheric tracer (uncertainty tracer) alongside CO2 in NASA's GEOS model and discuss implications of FFCO2 uncertainties in the context of flux inversions. We also demonstrate the use of high resolution urban CO2 simulations as a tool for objectively evaluating FFCO2 data over intense emission regions. Though this study focuses on FFCO2 emission data, the outcome of this study could also help improve the knowledge of similar gridded emissions data for non-CO2 compounds with similar emission characteristics.

FFCO↗

Predicting vehicular emissions in high spatial resolution using pervasively measured transportation data and microscopic emissions model

Air pollution related to traffic emissions pose an especially significant problem in cities; this is due to its adverse impact on human health and well-being. Previous studies which have aimed to quantify emissions from the transportation sector have been limited by either simulated or coarsely resolved traffic volume data. Emissions inventories form the basis of urban pollution models, therefore in this study, Global Positioning System (GPS) trajectory data from a taxi fleet of over 15,000 vehicles were analyzed with the aim of predicting air pollution emissions for Singapore. This novel approach enabled the quantification of instantaneous drive cycle parameters in high spatio-temporal resolution, which provided the basis for a microscopic emissions model. Carbon dioxide (CO2), nitrogen oxides (NOx), volatile organic compounds (VOCs) and particulate matter (PM) emissions were thus estimated. Highly localized areas of elevated emissions levels were identified, with a spatio-temporal precision not possible with previously used methods for estimating emissions. Relatively higher emissions areas were mainly concentrated in a few districts that were the Singapore Downtown Core area, to the north of the central urban region and to the east of it. Daily emissions quantified for the total motor vehicle population of Singapore were found to be comparable to another emissions dataset Results demonstrated that high resolution spatio-temporal vehicle traces detected using GPS in large taxi fleets could be used to infer highly localized areas of elevated acceleration and air pollution emissions in cities, and may become a complement to traditional emission estimates, especially in emerging cities and countries where reliable fine-grained urban air quality data is not easily available. This is the first study of its kind to investigate measured microscopic vehicle movement in tandem with microscopic emissions modeling for a substantial study domain.

54 ENVIRONMENTAL SCIENCES↗

Increasing methane emissions from natural land ecosystems due to sea-level rise

Because methane (CH4) is currently the second most important greenhouse gas, it is important to accurately quantify CH4 emissions from terrestrial ecosystems. Different from many current modelling studies which focus on how CH4 emissions respond to a variety of environmental factors in land ecosystems, we analyzed how methane emitted from lands responded to sea-level increase (SLR) in this study. To do so, a large-scale surface water routing module was incorporated into our existing CH4 model and we designed an efficient simulation protocol to capture small variations in inundation extent due to SLR. Both the annual maximum inundation extent and CH4 emissions showed a steadily growing trend, increasing 1.21 × 105 km2 and 3.13 Tg CH4 /yr globally, respectively, in a 22-year SLR experiment during 1993-2014. Most of new inundation and methane source areas were located near rivers’ deltas and along the downstream reaches of rivers. The increase in inundation extent is primarily influenced by precipitation, channel geomorphic characteristics and topography of riverside area. The growth of CH4 emissions due to the SLR is largely determined by inundation extent but other factors such as temperature and carbon storage also played the important roles. Although the current SLR-induced increases in inundation extent and CH4 emissions only accounted for 1.0% and 1.3% of their global totals, they took 7.0% and 17.3% of the mean annual variability in both, respectively, during the study period. Considering SLR has a long-term but stable increasing trend, future SLR under potential climate change could play a more important role in evaluating dynamic of CH4 emissions.

Lu, Xiaoliang↗

Spatially resolved X-ray emission measurements of the residual velocity during the stagnation phase of inertial confinement fusion implosion experiments

A technique for measuring residual motion during the stagnation phase of an indirectly driven inertial confinement experiment has been implemented. This method infers a velocity from spatially and temporally resolved images of the X-ray emission from two orthogonal lines of sight. This work investigates the accuracy of recovering spatially resolved velocities from the X-ray emission data. A detailed analytical and numerical modeling of the X-ray emission measurement shows that the accuracy of this method increases as the displacement that results from a residual velocity increase. For the typical experimental configuration, signal-to-noise ratios, and duration of X-ray emission, it is estimated that the fractional error in the inferred velocity rises above 50% as the velocity of emission falls below 24 μm/ns. By inputting measured parameters into this model, error estimates of the residual velocity as inferred from the X-ray emission measurements are now able to be generated for experimental data. Details of this analysis are presented for an implosion experiment conducted with an unintentional radiation flux asymmetry. The analysis shows a bright localized region of emission that moves through the larger emitting volume at a relatively higher velocity towards the location of the imposed flux deficit. This technique allows for the possibility of spatially resolving velocity flows within the so-called central hot spot of an implosion. This information would help to refine our interpretation of the thermal temperature inferred from the neutron time of flight detectors and the effect of localized hydrodynamic instabilities during the stagnation phase. Across several experiments, along a single line of sight, the average difference in magnitude and direction of the measured residual velocity as inferred from the X-ray and neutron time of flight detectors was found to be ∼13 μm/ns and ∼14°, respectively.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

TOWARD AN EMPIRICAL THEORY OF PULSAR EMISSION. X. ON THE PRECURSOR AND POSTCURSOR EMISSION

Precursors and postcursors (PPCs) are rare emission components, which appear beyond the main pulse emission, in some cases far away from it, and are detected in a handful of pulsar. In this paper we attempt to characterize the PPC emission in relation to the pulsar main pulse geometry. In our analysis we find that PPC components have properties very different from that of outer conal emission. The separation of the PPC components from the main pulse center remains constant with frequency. In addition the beam opening angles corresponding to the separation of PPC components from the pulsar center are much larger than the largest encountered in conal emission. Pulsar radio emission is believed to originate within the magnetic polar flux tubes due to the growth of instabilities in the outflowing relativistic plasma. Observationally, there is strong evidence that the main pulse emission originates at altitudes of about 50 neutron star radii for a canonical pulsar. Currently, the most plausible radio emission model that can explain main pulse emission is the coherent curvature radiation mechanism, wherein relativistic charged solitons are formed in a non-stationary electron-positron-pair plasma. The wider beam opening angles of PPC require the emission to emanate from larger altitudes as compared to the main pulse, if both these components originate by the same emission mechanism. We explore this possibility and find that this emission mechanism is probably inapplicable at the height of the PPC emission. We propose that the PPC emission represents a new type of radiation from pulsars with a mechanism different from that of the main pulse.

79 ASTRONOMY AND ASTROPHYSICS↗

Creating Accurate Methane Emission Inventories through Data-Driven Airborne Survey Strategies

Because natural gas emits less carbon than other fossil fuels, it holds promise as a green energy transition fuel. However, the overall carbon footprint of natural gas is significantly elevated by methane emissions that occur during its production and transmission (Cusworth et al. 2022). Methane “super-emitters,” while comprising only about 1% of sites, are responsible for the majority of oil- and gas-sourced methane emissions, making their detection and mitigation critical in reducing the climate impact of natural gas and in meeting national and global sustainability goals (Sherwin et al. 2024). Yet, despite advancements in detection, significant uncertainties remain regarding the size, frequency, and duration distributions of methane emissions (e.g., Frankenberg et al. 2016, Cusworth et al. 2022, Chen, Sherwin et al. 2022, Conrad et al. 2023, Johnson et al. 2023, Sherwin et al. 2024) underscoring the need for comprehensive emissions inventories segmented by basin across the US. Airborne surveys are well-suited for collecting data to build these comprehensive, basin-level inventories because they allow for extensive spatial coverage, and have the spatial resolution, and the sensitivity to pinpoint individual methane sources. As remote sensing technologies enable rapid basin-scale surveys, it is imperative to establish scientifically and statistically robust standards to generate reliable and actionable emissions inventories. Recent work has shown that differences in airborne sampling strategies, detection technologies, and analysis can lead to large differences between survey conclusions if not correctly accounted for (Chen et al. 2024). This elevates the importance of incorporating proper sampling and analysis techniques when designing a methane emissions monitoring campaign to produce accurate results and facilitate cross-study comparisons. In this paper, we describe a survey strategy designed using the latest conclusions from the literature to align results from different aerial surveys. We identify several sampling and analysis principles, including large sample sizes, balanced sampling across oil and gas production, careful survey area definition, and a unified protocol for analysis, to be vital to producing an unbiased estimate of basin-scale emissions. We present results from a Department of Energy-funded project that deployed this survey strategy in two understudied oil and gas- producing regions in the United States: the Haynesville Basin in Texas and Louisiana, and the Woodford Shale in the Anadarko Basin in Oklahoma.

03 NATURAL GAS↗

Land management change greatly impacts biofuels’ greenhouse gas emissions

Harvesting corn stover for biofuel production may decrease soil organic carbon (SOC) and increase greenhouse gas (GHG) emissions. Adding additional organic matter into soil or reducing tillage intensity, however, could potentially offset this SOC loss. Here, by using SOC and life cycle analysis (LCA) models, we evaluated the impacts of land management change (LMC), i.e., stover removal, organic matter addition, and tillage on spatially explicit SOC level and biofuels’ overall life-cycle GHG emissions in U.S. corn-soybean production systems. Results indicate that under conventional tillage (CT), 30% stover removal (dry weight) may reduce SOC by 0.04 t C ha-1yr-1 over a 30-year simulation period. Growing a cover crop during the fallow season or applying manure, on the other hand, could add to SOC and further reduce biofuels’ life-cycle GHG emissions. With 30% stover removal in a CT system, cover crop and manure application can increase SOC at the national level by about 0.06 and 0.02 t C ha-1yr-1, respectively, compared to cases without such measures. With contributions from this SOC increase, the life-cycle GHG emissions for stover ethanol are more than 80% lower than those of gasoline, exceeding the U.S. Renewable Fuel Standard mandate of 60% emissions reduction for cellulosic biofuels. Reducing tillage intensity while removing stover could also limit SOC loss or lead to SOC gain, which would lower stover ethanol life-cycle GHG emissions to near or under the mandated 60% reduction. Without these organic matter inputs or reduced tillage intensity, however, the emissions will not meet this mandate. More efforts are still required to further identify key practical LMCs, improve SOC modeling, and accounting for LMCs in biofuel LCAs that incorporate stover removal.

Qin, Zhangcai↗

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

Abstract. Future trends in air pollution and greenhouse gas (GHG)emissions for China are of great concern to the community. A set of globalscenarios regarding future socio-economic and climate developments, combiningshared socio-economic pathways (SSPs) with climate forcing outcomes asdescribed by the Representative Concentration Pathways (RCPs), was createdby the Intergovernmental Panel on Climate Change (IPCC). Chinese researchers have also developed various emission scenarios by considering detailed local environmental and climate policies. However, a comprehensive scenario set connecting SSP–RCP scenarios with local policies and representing dynamic emission changes under local policies is still missing. In this work, to fill this gap, we developed a dynamic projection model, the Dynamic Projection model for Emissions in China (DPEC), to explore China'sfuture anthropogenic emission pathways. The DPEC is designed tointegrate the energy system model, emission inventory model, dynamicprojection model, and parameterized scheme of Chinese policies. The modelcontains two main modules, an energy-model-driven activity rate projectionmodule and a sector-based emission projection module. The activity rateprojection module provides the standardized and unified future energyscenarios after reorganizing and refining the outputs from the energy systemmodel. Here we use a new China-focused version of the Global ChangeAssessment Model (GCAM-China) to project future energy demand and supply inChina under different SSP–RCP scenarios at the provincial level. Theemission projection module links a bottom-up emission inventory model, theMulti-resolution Emission Inventory for China (MEIC), to GCAM-China andaccurately tracks the evolution of future combustion and production technologiesand control measures under different environmental policies. We developedtechnology-based turnover models for several key emitting sectors (e.g.coal-fired power plants, key industries, and on-road transportationsectors), which can simulate the dynamic changes in the unit/vehicle fleetturnover process by tracking the lifespan of each unit/vehicle on an annualbasis. With the integrated modelling framework, we connected five SSP scenarios(SSP1–5), five RCP scenarios (RCP8.5, 7.0, 6.0, 4.5, and 2.6), and threepollution control scenarios (business as usual, BAU; enhanced controlpolicy, ECP; and best health effect, BHE) to produce six combined emissionscenarios. With those scenarios, we presented a wide range of China's futureemissions to 2050 under different development and policy pathways. We foundthat, with a combination of strong low-carbon policy and air pollutioncontrol policy (i.e. SSP1-26-BHE scenario), emissions of major airpollutants (i.e. SO 2 , NO x , PM 2.5 , and non-methane volatile organic compounds – NMVOCs) in China willbe reduced by 34%–66% in 2030 and 58%–87% in 2050 compared to 2015. End-of-pipe control measures are more effective for reducing air pollutant emissions before 2030, while low-carbon policy will play a more important rolein continuous emission reduction until 2050. In contrast, China's emissionswill remain at a high level until 2050 under a reference scenario without activeactions (i.e. SSP3-70-BAU). Compared to similar scenarios set from theCMIP6 (Coupled Model Intercomparison Project Phase 6), our estimates ofemission ranges are much lower than the estimates from the harmonized CMIP6 emissions dataset in2020–2030, but their emission ranges become similar in the year 2050.

54 ENVIRONMENTAL SCIENCES↗

Improved Rice Residue Burning Emissions Estimates: Accounting for Practice-Specific Emission Factors in Air Pollution Assessments of Vietnam

In Southeast Asia and Vietnam, rice residues are routinely burned after the harvest to prepare fields for the next season. Specific to Vietnam, the two prevalent burning practices include: a). piling the residues after hand harvesting; b). burning the residues without piling, after machine harvesting. In this study, we synthesized field and laboratory studies from the literature on rice residue burning emission factors for Particulate Matter less than 2.5 microns (PM2.5). We found significant differences in the resulting burning-practice specific emission factors, with 16.9 grams per square kilogram (plus or minus 6.9) for pile burning and 8.8 grams per square kilogram (plus or minus 3.5) for non-pile burning. We calculated burning practice specific emissions based on rice area data, region-specific fuel-loading factors, combined emission factors, and estimates of burning from the literature. Our results for year 2015 estimate 180 gigagrams of PM2.5 result from the pile burning method and 130 gigagrams result from non-pile burning method, with the most-likely current emission scenario of 150 gigagrams PM2.5 emissions for Vietnam. For comparison purposes, we calculated emissions using generalized agricultural emission factors employed in global biomass burning studies. These results estimate 80 gigagrams PM2.5, which is only 44 percent of the pile burning-based estimates, suggesting underestimation in previous studies. We compare our emissions to an existing all-combustion sources inventory, results show emissions account for 14-18 percent of Vietnam's total PM2.5 depending on burning practice. Within the highly-urbanized and cloud-covered Hanoi Capital region (HCR), we use rice area from Sentinel-1A to derive spatially-explicit emissions and indirectly estimate residue burning dates. Results from HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) back-trajectory analysis stratified by season show autumn has most emission trajectories originating in the North, while spring has most originating in the South, suggesting the latter may have bigger impact on air quality. From these results, we highlight locations where emission mitigation efforts could be focused and suggest measures for pollutant mitigation. Our study demonstrates the need to account for emissions variation due to different burning practices.

Air Pollution↗

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗

Using an explicit emission tagging method in global modeling of source‐receptor relationships for black carbon in the Arctic: Variations, sources, and transport pathways

Abstract We introduce an explicit emission tagging technique in the Community Atmosphere Model to quantify source‐region‐resolved characteristics of black carbon (BC), focusing on the Arctic. Explicit tagging of BC source regions without perturbing the emissions provides a physically consistent and computationally efficient approach to establish source‐receptor relationships and transport pathways. Our analysis shows that the contributions of major source regions to the global BC burden are not proportional to the respective emissions due to strong region‐dependent removal rates and lifetimes, while the contributions to BC direct radiative forcing show a near‐linear dependence on their respective contributions to the burden. Arctic BC concentrations, deposition, and source contributions all have strong seasonal variations. Eastern Asia contributes the most to the wintertime Arctic BC burden, but has much less impact on lower‐level concentrations and deposition. Northern Europe emissions are more important to both surface concentration and deposition in winter than in summer. The largest contribution to Arctic BC in the summer is from Northern Asia. Although local emissions contribute less than 10% to the annual mean BC burden and deposition within the Arctic, the per‐emission efficiency is much higher than for non‐Arctic sources. The interannual variability (1996–2005) due to meteorology is small in annual mean BC burden and radiative forcing but is significant in yearly seasonal means over the Arctic. When a slow aging treatment of BC is introduced, the increase of BC lifetime and burden is source dependent. Global BC forcing‐per‐burden efficiency also increases primarily due to changes in BC vertical distributions.

Wang, Hailong↗

Regional Influence of Aerosol Emissions from Wildfires Driven by Combustion Efficiency: Insights from the BBOP Campaign

Abstract Wildfires are important contributors to atmospheric aerosols and a large source of emissions that impact regional air quality and global climate. In this study, wildfire emissions in the Pacific Northwest region of the United States were characterized using real-time measurements near their sources using an aircraft, and farther downwind from a fixed ground site located at the Mt. Bachelor Observatory (~ 2700 m a.s.l.). The characteristics of aerosol emissions were found to depend strongly on the modified combustion efficiency (MCE), a qualitative index of the combustion processes of a fire. Organic aerosol emissions had negative correlations with MCE, whereas the carbon oxidation state of organic aerosol increased with MCE. The relationships between the aerosol properties and MCE were consistent between fresher emissions (~1 hour old) and emissions sampled after atmospheric transport (6 - 45 hours), suggesting that organic aerosol mass loading and chemical properties were strongly influenced by combustion processes at the source and conserved to a significant extent during regional transport. These results suggest that MCE can be a useful metric for describing aerosol properties of regionally transported wildfire emissions and their impacts on regional air quality and global climate.

54 ENVIRONMENTAL SCIENCES↗

FERMI-LAT OBSERVATIONS OF HIGH-ENERGY γ-RAY EMISSION TOWARD THE GALACTIC CENTER

The Fermi Large Area Telescope (LAT) has provided the most detailed view to date of the emission toward the Galactic center (GC) in high-energy γ-rays. This paper describes the analysis of data taken during the first 62 months of the mission in the energy range 1–100 GeV from a 15° × 15° region about the direction of the GC. Specialized interstellar emission models (IEMs) are constructed to enable the separation of the γ-ray emissions produced by cosmic ray particles interacting with the interstellar gas and radiation fields in the Milky Way into that from the inner ∼1 kpc surrounding the GC, and that from the rest of the Galaxy. A catalog of point sources for the 15° × 15° region is self-consistently constructed using these IEMs: the First Fermi-LAT Inner Galaxy Point Source Catalog (1FIG). The spatial locations, fluxes, and spectral properties of the 1FIG sources are presented, and compared with γ-ray point sources over the same region taken from existing catalogs. After subtracting the interstellar emission and point-source contributions a residual is found. If templates that peak toward the GC are used to model the positive residual the agreement with the data improves, but none of the additional templates tried account for all of its spatial structure. The spectrum of the positive residual modeled with these templates has a strong dependence on the choice of IEM.

79 ASTRONOMY AND ASTROPHYSICS↗

Locally Resolved Electron Emission Area and Unified View of Field Emission from Ultrananocrystalline Diamond Films

One of the common problems in case of field emission from polycrystalline diamond films, which typically have uniform surface morphology, is uncertainty in determining exact location of electron emission sites across the surface. Although several studies have suggested that grain boundaries are the main electron emission source, it is not particularly clear what makes some sites emit more than the others. It is also practically unclear how one could quantify the actual electron emission area and therefore field emission current per unit area. In this paper we study the effect of actual, locally resolved, field emission (FE) area on electron emission characteristics of uniform planar highly conductive nitrogen-incorporated ultrananocrystalline diamond ((N)UNCD) field emitters. It was routinely found that field emission from as-grown planar (N)UNCD films is always confined to a counted number of discrete emitting centers across the surface which varied in size and electron emissivity. It was established that the actual FE area critically depends on the applied electric field, as well as that the actual FE area and the overall electron emissivity improve with sp2 fraction present in the film irrespectively of the original substrate roughness and morphology. To quantify the actual FE area and its dependence on the applied electric field, imaging experiments were carried out in a vacuum system in a parallel-plate configuration with a specialty anode phosphor screen. Electron emission micrographs were taken concurrently with I-V characteristics measurements. In addition, a novel automated image processing algorithm was developed to process extensive imaging datasets and calculate emission area per image. By doing so, it was determined that the emitting area was always significantly smaller than the FE cathode surface area. Namely, the actual FE area would change from 5×10-3 % to 1.5 % of the total cathode area with the applied electric field increased. Finally and most importantly, it was shown that when I-E curves as measured in the experiment were normalized by the field-dependent emission area, the resulting j-E curves demonstrated a strong kink and significant deviation from Fowler-Nordheim (FN) law, and eventually saturated at a current density of ~100 mA/cm2 . This value was nearly identical for all (N)UNCD films measured in this study, regardless of the substrate.

36 MATERIALS SCIENCE↗

A New Global Anthropogenic SO2 Emission Inventory for the Last Decade: A Mosaic of Satellite-Derived and Bottom-Up Emissions

Sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor have been used to detect emissions from large point sources. Emissions from over 400 sources have been quantified individually based on OMI observations, accounting for about a half of total reported anthropogenic SO2 emissions. Here we report a newly developed emission inventory, OMI-HTAP, by combining these OMI-based emission estimates and the conventional bottom-up inventory, HTAP, for smaller sources that OMI is not able to detect. OMI-HTAP includes emissions from OMI-detected sources that are not captured in previous leading bottom-up inventories, enabling more accurate emission estimates for regions with such missing sources. In addition, our approach offers the possibility of rapid updates to emissions from large point sources that can be detected by satellites. Our methodology applied to OMI-HTAP can also be used to merge improved satellite-derived estimates with other multi-year bottom-up inventories, which may further improve the accuracy of the emission trends. OMI-HTAP SO2 emissions estimates for Persian Gulf, Mexico, and Russia are 59%, 65%, and 56% larger than HTAP estimates, respectively, in year 2010. We have evaluated the OMI-HTAP inventory by performing simulations with the Goddard Earth Observing System version 5 (GEOS-5) model. The GEOS-5 simulated SO2 concentrations driven by both HTAP and OMI-HTAP were compared against in situ measurements. We focus for the validation on year 2010 for which HTAP is most valid and for which a relatively large number of in situ measurements are available. Results show that the OMI-HTAP inventory improves the agreement between the model and observations, in particular over the US, with the normalized mean bias decreasing from 0.41 (HTAP) to -0.03 (OMI-HTAP) for year 2010. Simulations with the OMI-HTAP inventory capture the worldwide major trends of large anthropogenic SO2 emissions that are observed with OMI. Correlation coefficients of the observed and modelled surface SO2 in 2014 increase from 0.16 (HTAP) to 0.59 (OMI-HTAP) and the normalized mean bias dropped from 0.29 (HTAP) to 0.05 (OMI-HTAP), when we updated 2010 HTAP emissions with 2014 OMI-HTAP emissions in the model.

Sulfur dioxide (SO2)↗