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At least 919 records · Page 51

Urban NO x emissions around the world declined faster than anticipated between 2005 and 2019

Emission inventory development for air pollutants, by compiling records from individual emission sources, takes many years and involves extensive multi-national effort. A complementary method to estimate air pollution emissions is in the use of satellite remote sensing. In this study, NO 2 observations from the Ozone Monitoring Instrument are combined with re-analysis meteorology to estimate urban nitrogen oxide (NO X ) emissions for 80 global cities between 2005 and 2019. The global average downward trend in satellite-derived urban NO X emissions was 3.1%–4.0% yr -1 between 2009 and 2018 while inventories show a 0%–2.2% yr -1 drop over the same timeframe. This difference is primarily driven by discrepancies between satellite-derived urban NO X emissions and inventories in Africa, China, India, Latin America, and the Middle East. In North America, Europe, Korea, Japan, and Australasia, NO X emissions dropped similarly as reported in the inventories. In Europe, Korea, and Japan only, the temporal trends match the inventories well, but the satellite estimate is consistently larger over time. While many of the discrepancies between satellite-based and inventory emissions estimates represent real differences, some of the discrepancies might be related to the assumptions made to compare the satellite-based estimates with inventory estimates, such as the spatial disaggregation of emissions inventories. Overall, our work identifies that the three largest uncertainties in the satellite estimate are the tropospheric column measurements, wind speed and direction, and spatial definition of each city.

54 ENVIRONMENTAL SCIENCES↗

Greenhouse gas emissions embodied in the U.S. solar photovoltaic supply chain

Abstract Solar photovoltaic (PV) electricity is considered to be an important source of electricity generation in the quest for net-zero carbon emissions. However, the growth of solar electricity is creating both increased material demands and increased greenhouse gas (GHG) emissions from silicon and PV manufacturing (also referred to as embodied GHG emissions of solar electricity). Here we analyze the silicon and solar PV supply chain for the United States (U.S.) market and find that the embodied GHG emissions of solar PV panel materials (such as silicon), manufacture, logistics, and installation in the U.S. given the current supply chain are 36 g CO 2 e kWh −1 of solar electricity generated. Eighty-five percent of the embodied GHG emissions are from PV panel production processes in China and other Asia–Pacific countries. Moving the silicon and PV manufacturing to the U.S. would reduce the embodied GHG emissions of solar electricity by 16% from its current level, primarily because of the lower GHG emission intensity of the U.S. electrical grid and the lower GHG emissions for aluminum electrolysis in North America. Future scenario analysis shows that by 2030, with the U.S. PV domestic supply chain and its decarbonized grid electricity and aluminum production, as well as improving PV conversion efficiency, the embodied GHG emissions of solar electricity in the U.S. will be reduced to 21 g CO 2 e kWh −1 .

14 SOLAR ENERGY↗

Implications of an emission trading scheme for India’s net-zero strategy: a modelling-based assessment

To help meet its near-term NDC goals and long-term net-zero 2070 target, the Government of India has planned to establish a Carbon Credit Trading Scheme (CCTS), i.e. a domestic emission trading scheme (ETS). An ETS is an inherently cost-effective policy instrument for emission reduction, providing the greatest flexibility to reduce emissions from within and across sectors. An effective ETS requires design features that consider country-specific challenges and reflect its role within the larger policy package to achieve long-term emission reduction. Within the Indian context and in this study we therefore investigate—(i) what might be the role of the ETS in achieving India’s long-term mitigation targets? (ii) How might the various sectors interact under an emissions cap? (iii) How might the ETS interact with existing energy and climate policies? We do this analysis by running four main scenarios using the integrated assessment model GCAM (v6.0), adapted to India-specific assumptions and expectations. These scenarios are—(i) NZ (net-zero), (ii) NZ + ETS, (iii) NZ + CC (command and control), and (iv) NZ + RPO (renewables purchase obligations) + ETS. The NZ scenario assumes India’s near-term and long-term climate commitments of net zero by 2070. Scenarios with ETS (ii) and (iv) apply an emissions cap on four sectors—electricity, iron and steel, cement, and fertilizer. The scenario with CC applies a homogenous emission cap on each of the chosen sectors but does not allow cross-sectoral trading. The last scenario includes renewables purchase obligations (RPOs along with an ETS. We show that under a specific ETS emissions cap: (i) the electricity sector emerges as the largest source of cost-effective greenhouse gas (GHG) reduction options; (ii) ETS with trading across sectors is around 24% more cost-effective than ETS with trading only within sectors, (iii) RPOs can be complementary to an ETS although the impact of RPOs on GHG reductions in the electricity sector would need to be considered when setting the level of the ETS cap (or emissions intensity targets) or the RPO targets to avoid low carbon prices, and (iv) the direction and volume of financial transfers across sectors depends on allocation targets set by the government. Based on these results we provide design recommendations for India’s ETS.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Observation of Seeded Mn K β Stimulated X-Ray Emission Using Two-Color X-Ray Free-Electron Laser Pulses

Kβ x-ray emission spectroscopy is a powerful probe for electronic structure analysis of 3d transition metal systems and their ultrafast dynamics. Selectively enhancing specific spectral regions would increase this sensitivity and provide fundamentally new insights. Recently we reported the observation and analysis of Kα amplified spontaneous x-ray emission from Mn solutions using an x-ray free-electron laser to create the 1s core-hole population inversion [Kroll et al., Phys. Rev. Lett. 120, 133203 (2018)]. To apply this new approach to the chemically more sensitive but much weaker Kβ x-ray emission lines requires a mechanism to outcompete the dominant amplification of the Kα emission. Here we report the observation of seeded amplified Kβ x-ray emission from a NaMnO 4 solution using two colors of x-ray free-electron laser pulses, one to create the 1s core-hole population inversion and the other to seed the amplified Kβ emission. Comparing the observed seeded amplified Kβ emission signal with that from conventional Kβ emission into the same solid angle, we obtain a signal enhancement of more than 10 5 . Finally, our findings are the first important step of enhancing and controlling the emission of selected final states of the Kβ spectrum with applications in chemical and materials science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Computational study on the impact of gasoline-ethanol blending on autoignition and soot/NO x emissions under low-load gasoline compression ignition conditions

Here, in the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine are performed to investigate the impact of gasoline-ethanol blending on autoignition, nitrogen oxide (NO x ), and soot emissions under low-load conditions. In order to represent the test gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF)+ethanol (ETPRF) surrogate (with 10% ethanol by volume; E10) is employed. A three-dimensional (3D) engine CFD model employing finite-rate chemistry with a skeletal kinetic mechanism (including NO x sub-mechanism), adaptive mesh refinement (AMR), and hybrid method of moments (HMOM) is adopted to capture the in-cylinder combustion phenomena and soot/NO x emissions. The engine CFD model is validated against experimental data for three gasoline-ethanol blends: E10, E30 and E100, with varying ethanol content by volume. Model validation is carried out for a broad range of start-of-injection (SOI) timings (−21, −27, −36, and −45 crank angle degrees (°CA) after top-dead-center (aTDC)) with respect to in-cylinder pressure, heat release rate, combustion phasing, NO x and soot emissions. For relatively later injection timings (−21 and −27 °CA aTDC), E30 yields higher amount of soot than E10; while the trend reverses for early injection cases (−36 and −45 °CA aTDC ). On the other hand, E100 yields the lowest amount of soot among all fuels irrespective of SOI timing. Further, E10 shows a non-monotonic trend in soot emissions with SOI timing: SOI-36>SOI-45>SOI-21>SOI-27, while soot emissions from E30 exhibit monotonic decrease with advancing SOI timing. NO x emissions from various fuels follow a trend of E10>E30>E100. On the other hand, NO x emissions increase as SOI timing is advanced for all fuels, with an anomaly for E10 and E100 where NO x decreases when SOI is advanced beyond −36 °CA aTDC. Detailed analysis of the numerical results is performed to investigate the soot/NO x emission trends and elucidate the impact of chemical composition and physical properties on autoignition and emissions characteristics.

Computational fluid dynamics↗

Comparison of methane emission estimates from multiple measurement techniques at natural gas production pads

This study presents the results of a campaign that estimated methane emissions at 268 gas production facilities in the Fayetteville shale gas play using onsite measurements (261 facilities) and two downwind methods - the dual tracer flux ratio method (Tracer Facility Estimate - TFE, 17 facilities) and the EPA Other Test Method 33a (OTM33A Facility Estimate - OFE, 50 facilities). A study onsite estimate (SOE) for each facility was developed by combining direct measurements and simulation of unmeasured emission sources, using operator activity data and emission data from literature. The SOE spans 0-403 kg/h and simulated methane emissions from liquid unloadings account for 88% of total emissions estimated by the SOE, with 76% (95% CI [51%-92%]) contributed by liquid unloading at two facilities. TFE and SOE show overlapping 95% CI between individual estimates at 15 of 16 (94%) facilities where the measurements were paired, while OFE and SOE show overlapping 95% CI between individual estimates at 28 of 43 (65%) facilities. However, variance-weighted least-squares (VWLS) regressions performed on sets of paired estimates indicate statistically significant differences between methods. The SOE represents a lower bound of emissions at facilities where onsite direct measurements of continuously emitting sources are the primary contributor to the SOE, a sub-selection of facilities which minimizes expected inter-method differences for intermittent pneumatic controllers and the impact of episodically-emitting unloadings. At 9 such facilities, VWLS indicates that TFE estimates systematically higher emissions than SOE (TFE-to-SOE ratio = 1.6, 95% CI [1.2 to 2.1]). At 20 such facilities, VWLS indicates that OFE estimates systematically lower emissions than SOE (OFE-to-SOE ratio of 0.41 [0.26 to 0.90]). Given that SOE at these facilities is a lower limit on emissions, these results indicate that OFE is likely a less accurate method than SOE or TFE for this type of facility.

03 NATURAL GAS↗

Hestia SW-IFL Onroad Fossil Fuel Carbon Dioxide (FFCO2) product: Road segment-level annual FFCO2 emissions across Arizona (2017-2022), version 1.1

The SW-IFL onroad fossil fuel carbon dioxide (FFCO2) emissions data product represents CO2 emissions from the combustion of fossil fuels by motor vehicles (e.g., passenger cars, trucks, buses, motorcycles) traveling on designated roadways. The emissions are represented geographically on each road segment within the state of Arizona spanning the 2017 to 2022 time period. This data product was developed as part of the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL) project, which aims to provide new knowledge and tools that address urban environmental issues by integrating high-resolution observations, modeling, and civic engagement. The emissions data are provided in CSV (input data, ONR_FFCO2_AZ_county.csv) and GeoPackage form (output polyline objects - about 786,000 road segments, XXXX_AZ_v1.1.gpkg) designated by road class (interstates, arterials, collectors, local). The metadata file (Metadata_SW-IFL_Onroad_annualFFCO2_v1.1.docx) provides details about attributes and data formats. The GeoPackage emissions data are provided separately for local roads and nonlocal roads (interstates, arterials, collectors). The method file (Methods_SW-IFL_Onroad_annualFFCO2_v1.1.docx) describes the data processing flow and data sources. Update on 2024-04-17: Updates were made to both the input emission data file (.csv) and output segment-level emission file (.gpkg). There was an update in county-level emission input data (ONR_FFCO2_AZ_county.csv) and the entire road segments were reprocessed to reflect this update.Update on 2024-04-29: Update was made to one output segment-level emission file (Nonlocal_AZ_v1.0.gpkg). There was an error in the AADT values and the data were reprocessed to reflect this update.Update on 2024-10-22: Temporal coverage was extended to include 2022. VMT values were recalculated using new AADT data and the entire road segments were reprocessed to reflect these updates.

54 ENVIRONMENTAL SCIENCES↗

Pacific Northwest National Laboratory Facility Radionuclide Emissions Units and Sampling Systems

Battelle–Pacific Northwest Division operates numerous research and development (R&D) laboratories in Richland, WA, including those associated with Pacific Northwest National Laboratory (PNNL) on the U.S. Department of Energy (DOE)’s Hanford Site and PNNL Site that have the potential for radionuclide air emissions. The National Emission Standard for Hazardous Air Pollutants (NESHAP 40 CFR 61, Subparts H and I) requires an assessment of all emission units that have the potential for radionuclide air emissions. Potential emissions are assessed annually by PNNL staff members. Sampling, monitoring, and other regulatory compliance requirements are designated based upon the potential-to-emit dose criteria found in the regulations. The purpose of this document is to describe the facility radionuclide air emission sampling program and provide current and historical facility emission unit system performance, operation, and design information. For sampled systems, a description of the buildings, exhaust units, control technologies, and sample extraction details is provided for each registered emission unit. Additionally, applicable stack sampler configuration drawings, figures, and photographs are provided. Deregistered emission unit details are provided as necessary for up to 5 years post closure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Long-Term Methane Emissions Rate Quantification and Alert System for Natural Gas Storage Wells and Fields

The Department of Energy (DOE) National Energy Technology Laboratory (NETL) and other critical stakeholders (e.g., U.S. Environmental Protection Agency (USEPA), state regulators, and industry) seek to more accurately characterize and quantify methane emissions from natural gas storage wells. These efforts will reduce uncertainties in estimates of these emissions in USEPA’s current Green House Gas Inventory (GHGI) under their Greenhouse Gas Reporting Program (GHGRP; EPA, 2016). Emission factors currently used to estimate methane emissions from gas storage wells are the same factors used for onshore natural gas production wells (USEPA, 2016). This study has developed a robust and representative dataset of emissions from disaggregated gas station wellhead components and related emission factors that will inform future enhancements to the GHGI and GHGRP. Extensive methane emissions measurements and meteorological data were collected from three active storage facilities representing two of the three types of storage facilities (i.e., depleted gas reservoir and salt cavern) to support development of emissions factors specifically for gas storage wells and associated components. Methane emissions were quantified from both above-ground components (e.g., pipe fittings and valves) and seepage from the ground surface in proximity to gas storage wellheads.

03 NATURAL GAS↗

Updating and Evaluating Anthropogenic Emissions for NOAA’s Global Ensemble Forecast Systems for Aerosols (GEFS-Aerosols): Application of an SO 2 Bias-Scaling Method

We updated the anthropogenic emissions inventory in NOAA’s operational Global Ensemble Forecast for Aerosols (GEFS-Aerosols) to improve the model’s prediction of aerosol optical depth (AOD). We used a methodology to quickly update the pivotal global anthropogenic sulfur dioxide (SO 2 ) emissions using a speciated AOD bias-scaling method. The AOD bias-scaling method is based on the latest model predictions compared to NASA’s Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2). The model bias was subsequently applied to the CEDS 2019 SO 2 emissions for adjustment. The monthly mean GEFS-Aerosols AOD predictions were evaluated against a suite of satellite observations (e.g., MISR, VIIRS, and MODIS), ground-based AERONET observations, and the International Cooperative for Aerosol Prediction (ICAP) ensemble results. The results show that transitioning from CEDS 2014 to CEDS 2019 emissions data led to a significant improvement in the operational GEFS-Aerosols model performance, and applying the bias-scaled SO 2 emissions could further improve global AOD distributions. The biases of the simulated AODs against the observed AODs varied with observation type and seasons by a factor of 3~13 and 2~10, respectively. The global AOD distributions showed that the differences in the simulations against ICAP, MISR, VIIRS, and MODIS were the largest in March–May (MAM) and the smallest in December–February (DJF). When evaluating against the ground-truth AERONET data, the bias-scaling methods improved the global seasonal correlation (r), Index of Agreement (IOA), and mean biases, except for the MAM season, when the negative regional biases were exacerbated compared to the positive regional biases. The effect of bias-scaling had the most beneficial impact on model performance in the regions dominated by anthropogenic emissions, such as East Asia. However, it showed less improvement in other areas impacted by the greater relative transport of natural emissions sources, such as India. The accuracies of the reference observation or assimilation data for the adjusted inputs and the model physics for outputs, and the selection of regions with less seasonal emissions of natural aerosols determine the success of the bias-scaling methods. A companion study on emission scaling of anthropogenic absorbing aerosols needs further improved aerosol prediction.

54 ENVIRONMENTAL SCIENCES↗

Using Atmospheric Inverse Modelling of Methane Budgets with Copernicus Land Water and Wetness Data to Detect Land Use-Related Emissions

Climate change mitigation requires countries to report their annual greenhouse gas (GHG) emissions and sinks, including those from land use, land use change, and forestry (LULUCF). In Finland, the LULUCF sector plays a crucial role in achieving net-zero GHG emissions, as the sector is expected to be a net sink. However, accurate estimates of LULUCF-related GHG emissions, such as methane (CH 4 ), remain challenging. We estimated LULUCF-related CH 4 emissions in Finland in 2013–2020 by combining national land cover and remote-sensed surface wetness data with CH 4 emissions estimated by an inversion model. According to our inversion model, most of Finland’s CH 4 emissions were attributed to natural sources such as open pristine peatlands. However, our research indicated that forests with thin tree cover surrounding open peatlands may also be a significant source of CH 4 . Unlike open pristine peatlands and pristine peatlands with thin tree cover, surrounding transient forests are included in the Finnish GHG inventory if they meet the criteria used for forest land. The current Finnish national GHG inventory may therefore underestimate CH 4 emissions from forested organic soils surrounding open peatlands, although more precise methods and data are needed to verify this. Given the potential impact on net GHG emissions, CH 4 emissions from transitional forests on organic soils should be further investigated. Furthermore, the results demonstrate the potential of combining atmospheric inversion modelling of GHGs with diverse data sources and highlight the need for methods to more easily combine atmospheric inversions with national GHG inventories.

54 ENVIRONMENTAL SCIENCES↗

CO 2 is dominant greenhouse gas emitted from six hydropower reservoirs in southeastern United States during peak summer emissions

During August-September 2012, we sampled six hydropower reservoirs in southeastern United States. for CO 2 and CH 4 emissions via three pathways: diffusive emissions from water surface; ebullition in the water column; and losses from dam tailwaters during power generation. Average total emission rates of CO 2 for the six reservoirs ranged from 1,127 to 2,051 mg m -2 d -1 , which is low to moderate compared to CO 2 emissions rates reported for tropical hydropower reservoirs and boreal ponds and lakes, and similar to rates reported for other temperate reservoirs. Similar average rates for CH 4 were also relatively low, ranging from 5 to 83 mg m -2 d -1 . On a whole-reservoir basis, total emissions of CO 2 ranged nearly 10-fold, from ~51,000 kg per day for Fontana to ~486,000 kg per day for Guntersville, and total emissions of CH 4 ranged nearly 20-fold, from ~5 kg per day for Fontana to ~83 kg per day for Allatoona. Emissions through the tailwater pathway varied among reservoirs, comprising from 20 to 50% of total CO 2 emissions and 0 to 90% of CH 4 emissions, depending on the reservoir. Furthermore, several explanatory factors related to reservoir morphology and water quality were considered for observed differences among reservoirs.

13 HYDRO ENERGY↗

WHAT IS THE SOURCE OF QUIET SUN TRANSITION REGION EMISSION?

Dating back to the first observations of the on-disk corona, there has been a qualitative link between the photosphere’s magnetic network and enhanced transition-temperature plasma emission. These observations led to the development of a general model that describes emission structures through the partitioning of the atmospheric volume with different magnetic loop geometries that exhibit different energetic equilibria. Does the internetwork produce transition-temperature emission? What fraction of network flux connects to the corona? How does quiet Sun emission compare with low-activity Sun-like stars? In this work, we revisit the canonical model of the quiet Sun, with high-resolution observations from the Interface Region Imaging Spectrograph ( IRIS ) and HMI in hand, to address those questions. We use over 900 deep exposures of Si iv 1393 Å from IRIS along with nearly simultaneous HMI magnetograms to quantify the correlation between transition-temperature emission structures and magnetic field concentrations through a number of novel statistics. Our observational results are coupled with analysis of the Bifrost MHD model and a large-scale potential field model. Our results paint a complex portrait of the quiet Sun. We measure an emission signature in the distant internetwork that cannot be attributed to network contribution. We find that the dimmest regions of emission are not linked to the local vertical magnetic field. Using the MHD simulation, we categorize the emission contribution from cool mid-altitude loops and high-altitude coronal loops and discuss the potential emission contribution of spicules. Our results provide new constraints on the coupled solar atmosphere so that we can build on our understanding of how dynamic thermal and magnetic structures generate the observed phenomena in the transition region.

79 ASTRONOMY AND ASTROPHYSICS↗

Origin of X-Ray and Gamma-Ray Emission from the Galactic Central Region

We study a possible connection between different non-thermal emissions from the inner few parsecs of the Galaxy. We analyze the origin of the gamma-ray source 2FGL J1745.6−2858 (or 3FGL J1745.6−2859c) in the Galactic Center (GC) and the diffuse hard X-ray component recently found by the Nuclear Spectroscopic Telescope Array , as well as the radio emission and processes of hydrogen ionization from this area. We assume that a source in the GC injected energetic particles with power-law spectrum into the surrounding medium in the past or continues to inject until now. The energetic particles may be protons, electrons, or a combination of both. These particles diffuse to the surrounding medium and interact with gas, magnetic field, and background photons to produce non-thermal emissions. We study the spectral and spatial features of the hard X-ray emission and gamma-ray emission by the particles from the central source. Our goal is to examine whether the hard X-ray and gamma-ray emissions have a common origin. Our estimations show that, in the case of pure hadronic models, the expected flux of hard X-ray emission is too low. Despite the fact that protons can produce a non-zero contribution in gamma-ray emission, it is unlikely that they and their secondary electrons can make a significant contribution in hard X-ray flux. In the case of pure leptonic models, it is possible to reproduce both X-ray and gamma-ray emissions for both transient and continuous supply models. However, in the case of the continuous supply model, the ionization rate of molecular hydrogen may significantly exceed the observed value.

79 ASTRONOMY AND ASTROPHYSICS↗

On the Origin of the Flare Emission in IRIS ’ SJI 2832 Filter:Balmer Continuum or Spectral Lines?

Continuum (“white-light,” WL) emission dominates the energetics of flares. Filter-based observations, such as the IRIS SJI 2832 filter, show WL-like brightenings during flares, but it is unclear whether the emission arises from real continuum emission or enhanced spectral lines, possibly turning into emission. The difficulty in filter-based observations, contrary to spectral observations, is to determine which processes contribute to the observed brightening during flares. Here we determine the contribution of the Balmer continuum and the spectral line emission to IRIS ’ SJI 2832 emission by analyzing the appropriate passband in simultaneous IRIS NUV spectra. We find that spectral line emission can contribute up to 100% to the observed slitjaw images (SJI) emission, that the relative contributions usually temporally vary, and that the highest SJI enhancements that are observed are most likely because of the Balmer continuum. We conclude that care should be taken when calling SJI 2832 a continuum filter during flares, because the influence of the lines on the emission can be significant.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparison of GFED3, QFED2 and FEER1 Biomass Burning Emissions Datasets in a Global Model

Biomass burning contributes about 40% of the global loading of carbonaceous aerosols, significantly affecting air quality and the climate system by modulating solar radiation and cloud properties. However, fire emissions are poorly constrained in models on global and regional levels. In this study, we investigate 3 global biomass burning emission datasets in NASA GEOS5, namely: (1) GFEDv3.1 (Global Fire Emissions Database version 3.1); (2) QFEDv2.4 (Quick Fire Emissions Dataset version 2.4); (3) FEERv1 (Fire Energetics and Emissions Research version 1.0). The simulated aerosol optical depth (AOD), absorption AOD (AAOD), angstrom exponent and surface concentrations of aerosol plumes dominated by fire emissions are evaluated and compared to MODIS, OMI, AERONET, and IMPROVE data over different regions. In general, the spatial patterns of biomass burning emissions from these inventories are similar, although the strength of the emissions can be noticeably different. The emissions estimates from QFED are generally larger than those of FEER, which are in turn larger than those of GFED. AOD simulated with all these 3 databases are lower than the corresponding observations in Southern Africa and South America, two of the major biomass burning regions in the world.

biomass burning↗

Impact of Regional Northern Hemisphere Mid-latitude Anthropogenic Sulfur Dioxide Emissions on Local and Remote Tropospheric Oxidants

The unintended consequences of reductions in regional anthropogenic sulfur dioxide (SO2) emissions implemented to protect human health are poorly understood. SO2 decreases began in the 1970s in the US and Europe and are expected to continue into the future, while recent emissions decreases in China are also projected to continue. In addition to the well-documented climate effects (warming) from reducing aerosols, tropospheric oxidation is impacted via aerosol modification of photolysis rates and radical sinks. Impacts on the hydroxyl radical and other trace constituents directly affect climate and air quality metrics such as surface ozone levels. We use the Geophysical Fluid Dynamics Laboratory Atmospheric Model version 3 nudged towards National Centers for Environmental Prediction (NCEP) reanalysis wind velocities to estimate the impact of SO2 emissions from the US, Europe, and China by differencing a control simulation with an otherwise identical simulation in which 2015 anthropogenic SO2 emissions are set to zero over one of the regions. Springtime sulfate aerosol changes occur both locally to the emission region and also throughout the Northern Hemispheric troposphere, including remote oceanic regions and the Arctic. Hydroperoxy (HO2) radicals are directly removed via heterogeneous chemistry on aerosol surfaces, including sulfate, in the model, and we find that sulfate aerosol produced by SO2 emissions from the three individual northern mid-latitude regions strongly reduces both HO2 and hydroxyl (OH) by up to 10 % year-round throughout most of the troposphere north of 30∘ N latitude. Regional SO2 emissions significantly increase nitrogen oxides (NOx) by about 5 %–8 % throughout most of the free troposphere in the Northern Hemisphere by increasing the NOx lifetime as the heterogeneous sink of HO2 on sulfate aerosol declines. Despite the NOx increases, tropospheric ozone decreases at northern mid-latitudes by 1 %–4 % zonally averaged and by up to 5 ppbv in summertime surface air over China, where the decreases in HO2 and OH suppress O3 production. Since 2015 anthropogenic SO2 emissions in China exceed those in the US or Europe, the oxidative response is greatest for the China perturbation simulation. Chemical effects of aerosols on oxidation (reactive uptake) dominate over radiative effects (photolysis rates), the latter of which are only statistically significant locally for the large perturbation over China. We find that the SO2 emissions decrease in China, which has yet to be fully realized, will have the largest impact on oxidants and related species in the Northern Hemisphere free troposphere compared to future decreases in Europe or the US. Our results bolster previous calls for a multipollutant strategy for air pollution mitigation to avoid the unintended consequence of aerosol removal leading to surface ozone increases that offset or mask surface ozone gains achieved by regulation of other pollutants, especially in countries where current usage of high-sulfur emitting fuels may be phased out in the future.

anthropogenic sulfur dioxide emissions↗

Improved Assessment of Recent Trends in NOx and VOC Emissions and Ozone Production Sensitivity Regimes Using Satellite Data

This presentation highlights results from a NASA Aura Science Team and Atmospheric Composition Modeling and Analysis Program (ACMAP) project which study the capability to observe and model trends in ozone (O3) production regimes using spaceborne sensors. Ultraviolet– visible (UV–Vis) tropospheric column satellite retrievals of formaldehyde (HCHO) (a proxy for volatile organic compound [VOC] reactivity) and nitrogen dioxide (NO2) (a proxy for nitrogen oxides [NOx]) are frequently used to investigate the sensitivity of O3 production to emissions of NOx and VOCs. There are challenges that come from using satellite-derived ratios of HCHO and NO2 (FNR) to study O3 production sensitivity with the largest uncertainties associated with specific spaceborne sensor’s retrieval biases and errors. This study quantifies the differences and improvements in satellite retrievals of O3 production sensitivity regimes using FNRs when moving from legacy polar orbiting satellites such as the Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite and Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) onboard the NASA/NOAA Suomi-NPP platform to newer, higher spatiotemporal resolution satellite sensors TROPOspheric Monitoring Instrument (TROPOMI) and eventually the recently launched NASA geostationary sensor Tropospheric Emissions: Monitoring of Pollution (TEMPO). Furthermore, we investigate how using retrievals of NO2 and HCHO from these different satellites to constrain model predictions impacts the ability to accurately simulate O3 chemistry including chemical production regimes. To this end, we have conducted inverse model simulations, using the WRF-CMAQ-DDM data assimilation system at 12 km × 12 km, to constrain emissions of NOx and VOCs over the contiguous United States (CONUS) when assimilating OMI and TROPOMI retrievals of NO2 and HCHO. Two advantages of this are that we a) account for each satellite’s errors/biases in the emission estimation and b) update the prior profile to ensure that only radiance information is used for optimizing the emissions. This presentation will demonstrate: a) the varying accuracy of different satellite retrieved FNRs and ability to capture known sub-annual emission trends (e.g., seasonal, weekend/weekday) and emission anomalies during the COVID-19 lockdown of 2020, b) the differences and improvements in top-down emission estimates of NOx and VOCs when constrained by newer satellite sensors compared to legacy systems, and c) multi-sensor optimized emission estimates of summer-time NOx and VOCs between 2019-2021.

Data↗