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Feedbacks between Air Pollution and Weather, Part 2: Effects on Chemistry.
Citation:
Makar, P., W. Gong, C. Hogrefe, Y. Zhang, g. Curci, R. Žabkar, J. Milbrandt, U. Im, S. Galmarini, A. Balzarini, R. Baro, R. Bianconi, P. Cheung, R. Forkel, S. Gravel, M. Hirtl, L. Honzak, A. Hou, P. Jimenez-Guerrero, M. Langer, M. Moran, B. Pabla, J. Perez, G. Pirovano, R. San Jose, P. Tuccella, J. Werhahn, AND J. Zhang. Feedbacks between Air Pollution and Weather, Part 2: Effects on Chemistry. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 115:499-526, (2015).
Impact/Purpose:
The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation’s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
Fully-coupled air-quality models running in “feedback” and “no-feedback” configurations were compared against each other and observation network data as part of Phase 2 of the Air Quality Model Evaluation International Initiative. In the “no-feedback” mode, interactions between meteorology and chemistry through the aerosol direct and indirect effects were disabled, with the models reverting to climatologies of aerosol properties, or a no-aerosol weather simulation, while in the “feedback” mode, the model generated aerosols were allowed to modify the models’ radiative transfer and/or cloud formation processes. Annual simulations with and without feedbacks were conducted for domains in North America for the years 2006 and 2010, and for Europe for the year 2010. Comparisons against observations via annual statistics show model-to-model variation in performance is greater than the within-model variation associated with feedbacks. However, during the summer and during intense emission events such as the Russian forest fires of 2010, feedbacks have a significant impact on the chemical predictions of the models. The aerosol indirect effect was usually found to dominate feedbacks compared to the direct effect. The impacts of direct and indirect effects were often shown to be in competition, for predictions of ozone, particulate matter and other species. Feedbacks were shown to result in local and regional shifts of ozone-forming chemical regime, between NOx- and VOC-limited environments. Feedbacks were shown to have a substantial influence on biogenic hydrocarbon emissions and concentrations: North American simulations incorporating both feedbacks resulted in summer average isoprene concentration decreases of up to 10%, while European direct effect simulations during the Russian forest fire period resulted in grid average isoprene changes of -5 to +12.5%. The atmospheric transport and chemistry of large emitting sources such as plumes from forest fires and large cities were shown to be strongly impacted by the presence or absence of feedback mechanisms in the model simulations. Summertime model performance for ozone and other gases was improved through the inclusion of indirect effect feedbacks, while performance for particulate matter was degraded, suggesting that current parameterizations for in- and below cloud processes, once the cloud locations become more directly influenced by aerosols, may over or under-predict the strength of these processes. Process parameterization-level comparisons of fully coupled feedback models are therefore recommended for future work, as well as further studies using these models for the simulations of large scale urban/industrial and/or forest fire plumes.
URLs/Downloads:
MAKARETAL_PART2_ACCEPTED_FINAL.PDF (PDF, NA pp, 10167.561 KB, about PDF)Atmospheric Environment
