Articles | Volume 19, issue 23
https://doi.org/10.5194/acp-19-15157-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-15157-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluating wildfire emissions projection methods in comparisons of simulated and observed air quality
Uma Shankar
Department of Environmental Sciences and Engineering, University of
North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431, USA
Donald McKenzie
School of Environmental and Forest Sciences, University of
Washington, Seattle, WA 98195, USA
Jeffrey P. Prestemon
USDA Forest Service, Southern Research Station, Research Triangle
Park, NC 27709, USA
Bok Haeng Baek
University of North Carolina at Chapel Hill – Institute for the
Environment, Chapel Hill, NC 27517, USA
Mohammed Omary
University of North Carolina at Chapel Hill – Institute for the
Environment, Chapel Hill, NC 27517, USA
Dongmei Yang
University of North Carolina at Chapel Hill – Institute for the
Environment, Chapel Hill, NC 27517, USA
Aijun Xiu
University of North Carolina at Chapel Hill – Institute for the
Environment, Chapel Hill, NC 27517, USA
Kevin Talgo
CSRA Incorporated, Research Triangle Park, NC 27709, USA
Department of Environmental Sciences and Engineering, University of
North Carolina at Chapel Hill, Chapel Hill, NC 27599-7431, USA
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Timur Cinay, Dickon Young, Nazaret Narváez Jimenez, Cristina Vintimilla-Palacios, Ariel Pila Alonso, Paul B. Krummel, William Vizuete, and Andrew R. Babbin
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Sara L. Farrell, Havala O. T. Pye, Robert Gilliam, George Pouliot, Deanna Huff, Golam Sarwar, William Vizuete, Nicole Briggs, Fengkui Duan, Tao Ma, Shuping Zhang, and Kathleen Fahey
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Bok H. Baek, Carlie Coats, Siqi Ma, Chi-Tsan Wang, Yunyao Li, Jia Xing, Daniel Tong, Soontae Kim, and Jung-Hun Woo
Geosci. Model Dev., 16, 4659–4676, https://doi.org/10.5194/gmd-16-4659-2023, https://doi.org/10.5194/gmd-16-4659-2023, 2023
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Wendell W. Walters, Madeline Karod, Emma Willcocks, Bok H. Baek, Danielle E. Blum, and Meredith G. Hastings
Atmos. Chem. Phys., 22, 13431–13448, https://doi.org/10.5194/acp-22-13431-2022, https://doi.org/10.5194/acp-22-13431-2022, 2022
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Atmospheric ammonia and its products are a significant source of urban haze and nitrogen deposition. We have investigated the seasonal source contributions to a mid-sized city in the northeastern US megalopolis utilizing geospatial statistical analysis and novel isotopic constraints, which indicate that vehicle emissions were significant components of the urban-reduced nitrogen budget. Reducing vehicle ammonia emissions should be considered to improve ecosystems and human health.
Bok H. Baek, Rizzieri Pedruzzi, Minwoo Park, Chi-Tsan Wang, Younha Kim, Chul-Han Song, and Jung-Hun Woo
Geosci. Model Dev., 15, 4757–4781, https://doi.org/10.5194/gmd-15-4757-2022, https://doi.org/10.5194/gmd-15-4757-2022, 2022
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The Comprehensive Automobile Research System (CARS) is an open-source Python-based automobile emissions inventory model designed to efficiently estimate high-quality emissions. The CARS is designed to utilize the local vehicle activity database, such as vehicle travel distance, road-link-level network information, and vehicle-specific average speed by road type, to generate a temporally and spatially enhanced inventory for policymakers, stakeholders, and the air quality modeling community.
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Short summary
We evaluate two wildfire emissions estimates for the southeastern US, based on projected annual areas burned in 2011–2060, against a benchmark wildfire inventory in air quality (AQ) simulations for 2010 and AQ network observations. Our emissions estimates compare well with the benchmark but all three simulations have large biases compared to observations. We find our methods suitable to assess current and future wildfire AQ impacts but also identify areas for AQ model improvements.
We evaluate two wildfire emissions estimates for the southeastern US, based on projected annual...
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