CEMPD/SMOKE: SMOKE v4.8.1 Public Release (January 29, 2021)

Baek, Bok H.; Seppanen, Catherine

doi:10.5281/zenodo.4480334

Cited by 4 publications

(2 citation statements)

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“…Detailed estimates of capacity and generation for each modeled scenario from IPM are presented in figure S1. The core of the emissions processing methodology is based on the 2016 National Emissions Inventory (NEI) modeling platform and the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System (Baek and Seppanen 2021) with a new interface that links the two models (IPM-SMOKE) and maintains consistent inventory assumptions between them (i.e. consistent active and retired plants with stack information; for details see supplementary information section 1.2 and figure S1) using the National Electric Energy Data System and other proprietary databases.…”

Section: Domain and Modelsmentioning

confidence: 99%

Assessing the tradeoffs in emissions, air quality and health benefits from excess power generation due to climate-related policies for the transportation sector

Efstathiou,

Arunachalam,

Arter

et al. 2024

Environ. Res. Lett.

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As the transportation sector continues to decarbonize through electrification, there is growing interest in quantifying potential tradeoffs in air pollution and health impacts due to potential excess emissions from the power sector. This study investigates air pollution and health impacts of policy-driven changes in the transportation sector and the associated power generation demand in the Northeast and Mid-Atlantic United States. Five illustrative scenarios were designed to capture the effects of different policies under the first mandatory market-based program to reduce greenhouse gases in the US power sector (Regional Greenhouse Gas Initiative – RGGI) and the Transportation and Climate Initiative (TCI). Considering future power generation with new renewable energy investments to meet demands from decarbonized transportation, the scenarios were framed using: 1. 2030 reference cases for both sectors and a hybrid TCI portfolio, 2. Departure from the reference cases defined by Pennsylvania included or not in RGGI, and 3. Power grid emissions estimated under Clean Energy Standard (CES) policy and hybrid TCI portfolio. While the cross-sectoral policy effect on domain-wide concentrations is modest (max ΔPM2.5~0.06μg/m3, ΔNO2~0.3ppbv, ΔO3~0.15ppbv), substantial increases in Ohio and WestVirginia were attributed to Pennsylvania joining RGGI. With CES enacted and Pennsylvania in RGGI, significant reductions are seen in average concentrations (max ΔPM2.5~1.2 μg/m3, ΔNO2~1.1ppbv, ΔO3~1.7ppbv) except for Louisiana and Mississippi with corresponding disbenefits. When focusing exclusively on emissions reductions from transportation, the hybrid TCI portfolio had health benefits of 530 avoided adult deaths, and 46,000 avoided asthma exacerbations. With a “business as usual” power grid, these benefits remain comparable and are mainly driven by NO2, followed by PM2.5 and O3. However, if Pennsylvania joins RGGI, total health benefits and spatial distribution change substantially, with a large portion of adverse health impacts moving from TCI states to Ohio and West Virginia. The overall monetized impact of a CES scenario can substantially exceed the estimated average range of 66-69 Billion US$, depending on the interaction with transportation decarbonization strategies and other drivers of exposure.

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Section: Domain and Modelsmentioning

confidence: 99%

Assessing the tradeoffs in emissions, air quality and health benefits from excess power generation due to climate-related policies for the transportation sector

Efstathiou,

Arunachalam,

Arter

et al. 2024

Environ. Res. Lett.

View full text Add to dashboard Cite

show abstract

“…The WRF model was configured with Thompson graupel microphysics scheme, RRTMG long and short-wave radiation scheme, Mellor-Yamada-Janjic PBL scheme, unified Noah land-surface model, and Tiedtke cumulus parameterization option. The emission input was provided using a hybrid emission modeling system that utilized the SMOKE model version 4.8.1 (Baek and Seppanen, 2021) to process anthropogenic emissions, and a suite of emission models to estimate emissions from intermittent and/or meteorology-dependent sources. Anthropogenic emissions were taken from US EPA 2017 NEI.…”

Section: Modeling Configurationmentioning

confidence: 99%

Dynamic Meteorology-Induced Emissions Coupler (MetEmis) development in the Community Multiscale Air Quality (CMAQ): CMAQ-MetEmis

Baek

Coats

et al. 2023

Preprint

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Abstract. The main focus of this study is to develop a dynamic-coupling “inline” air quality modeling system for the meteorology-induced emissions with simulated meteorological data. To improve the spatiotemporal representations and accuracy of onroad vehicle emissions, which are largely senstivie to local meteorology, we developed the “inline” coupler module called “MetEmis” for Meteorology-Induced Emission sources within the Community Multiscale Air Quality (CMAQ) version 5.3.2 modeling system. It can dynamically estimate meteorology-induced hourly gridded emissions within the CMAQ modeling system using modeled meteorology. The CMAQ air quality modeling system is applied over the continental U.S. for two months (January and July 2019) for two emissions scenarios: a) current “offline” based onroad vehicle emissions, and b) “inline” CMAQ-MetEmis onroad vehicle emissions. Overall, the “MetEmis” coupler allows us to dynamically simulate onroad vehicle emissions from the MOVES onroad emission model for CMAQ with a better spatio-temporal representation compared to the “offline” scenario based on static temporal profiles. With an instance interpolation calculation approach, the new “inline” approach significantly enhances the computational efficiency and accuracy of estimating mobile source emissions, compared to the existing “offline” approach that yields almost identical hourly emission estimation. The domain total of daily VOC emissions from the “inline” scenario shows the largest impacts from the local meteorology, which is approximately 10 % lower than the ones from the “offline” scenario. Especially, the major difference of VOC estimates was shown over the California region. These local meteorology impacts on onroad vehicle emissions via CMAQ-MetEmis revealed an improvement in hourly NO2, daily maximum ozone, and daily average PM2.5 patterns with a higher agreement and correlation with daily ground observations.

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Impacts of On‐Road Vehicular Emissions on U.S. Air Quality: A Comparison of Two Mobile Emission Models (MOVES and FIVE)

Ma,

Tong,

Harkins

et al. 2024

JGR Atmospheres

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On‐road vehicles are significant contributors to air pollution globally, particularly to nitrogen oxides (NOx) and ozone (O3). Quantifying their contribution to air quality is crucial to understanding the trends of vehicle emissions as low‐ and “zero” emission vehicles join the fleet. Modeling on‐road emissions is complex due to various factors like fleet activities, traffic patterns, and meteorological conditions. We compare on‐road emissions from two mobile models: the National Oceanic and Atmospheric Administration Fuel‐based Inventory of Vehicle Emission (FIVE) and the US Environmental Protection Agency Motor Vehicle Emission Simulator (MOVES), finding they contribute 4%–33% to volatile organic compounds (VOCs), NOx, and fine particulate matter (PM2.5) in the contiguous United States (CONUS). Using a regional chemical transport model, we assess air quality effects under different emission scenarios. Both emission data sets yield satisfactory performance, with MOVES showing lower biases in ozone (O3) and PM2.5 over CONUS, while FIVE performs better at city scales due to higher urban NOx emissions. In January, on‐road emissions increased surface O3 over western and southern US by up to 9.1%–13.1% but decreased by 2.5% over the northeastern US, while PM2.5 predictions vary across the US (−85% to 24%). In July, on‐road emissions elevate O3 and PM2.5 concentrations by 15%–20% across CONUS, except in some west coast cities. They also greatly contribute to nitrogen dioxide (NO2) by more than 80% near roads and in urban areas. This study highlights the significant impact of on‐road emissions on urban air quality and provides insights for improving air quality forecasting and management.

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CEMPD/SMOKE: SMOKE v4.8.1 Public Release (January 29, 2021)

Cited by 4 publications

References 0 publications

Assessing the tradeoffs in emissions, air quality and health benefits from excess power generation due to climate-related policies for the transportation sector

Assessing the tradeoffs in emissions, air quality and health benefits from excess power generation due to climate-related policies for the transportation sector

Dynamic Meteorology-Induced Emissions Coupler (MetEmis) development in the Community Multiscale Air Quality (CMAQ): CMAQ-MetEmis

Impacts of On‐Road Vehicular Emissions on U.S. Air Quality: A Comparison of Two Mobile Emission Models (MOVES and FIVE)

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