Atmos. Chem. Phys. Discuss., 13, 14141-14161, 2013
www.atmos-chem-phys-discuss.net/13/14141/2013/
doi:10.5194/acpd-13-14141-2013
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review Status
This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Air quality resolution for health impacts assessment: influence of regional characteristics
T. M. Thompson1,*, R. K. Saari1, and N. E. Selin2
1Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, 77 Massachusetts, Ave., Bldg E19-411, Cambridge, MA 02139, USA
2Engineering Systems Division and Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, USA
*now at: Cooperative Institute for Research in the Atmosphere, Colorado State University, 1375 Campus Delivery, Fort Collins, CO 80523, USA

Abstract. We evaluate how regional characteristics of weather, population, and background pollution might impact the selection of optimal model resolution when calculating the human health impacts of changes to air quality. Using an approach consistent with air quality policy evaluation, we use a regional chemical transport model (CAMx) and a health benefits mapping program (BenMAP) to calculate the human health impacts associated with changes in ozone and fine particulate matter resulting from an emissions reduction scenario. We evaluate this same scenario at 36, 12 and 4 km resolution for nine regions in the Eastern US representing varied characteristics. We find that the human health benefits associated with changes in ozone concentrations are sensitive to resolution, especially in urban areas where we estimate that benefits calculated using coarse resolution results are on average two times greater than benefits calculated using finer scale results. In three urban areas we analyzed, results calculated using 36 km resolution modeling fell outside the uncertainty range of results calculated using finer scale modeling. In rural areas the influence of resolution is less pronounced with only an 8% increase in the estimated health impacts when using 36 km resolution over finer scales. In contrast, health benefits associated with changes in PM2.5 concentrations were not sensitive to resolution and did not follow a pattern based on any regional characteristics evaluated. The largest difference between the health impacts estimated using 36 km modeling results and either 12 or 4 km results was at most ±10% in any region. Several regions showed increases in estimated benefits as resolution increased (opposite the impact seen with ozone modeling) due to a higher contribution of primary PM in those regions, while some regions showed decreases in estimated benefits as resolution increased due to a higher contribution of secondary PM. Given that changes in PM2.5 dominate the human health impacts we conclude that human health benefits associated with decreases in ozone plus PM2.5, when calculated at 36 km resolution are indistinguishable from the benefits calculated using fine (12 km or finer) resolution modeling in the context of policy decisions.

Citation: Thompson, T. M., Saari, R. K., and Selin, N. E.: Air quality resolution for health impacts assessment: influence of regional characteristics, Atmos. Chem. Phys. Discuss., 13, 14141-14161, doi:10.5194/acpd-13-14141-2013, 2013.
 
Search ACPD
Discussion Paper
XML
Citation
Final Revised Paper
Share