Impact of climate change on PM 2.5 air quality inferred from a multi-model analysis of meteorological modes

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Lionel Barton
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Impact of 2000-2050 climate change on PM 2.5 air quality inferred from a multi-model analysis of meteorological modes Loretta J. Mickley Co-Is: Am

1 Impact of climate change on PM 2.5 air quality inferred from a multi-model analysis of meteorological modes Loretta J. Mickley Co-Is: Amos P.K.A. Tai and Daniel J. Jacob School of Engineering and Applied Sciences Harvard University June 13-15, 2012 AQ Management Contacts: Susan Anenberg and Carey Jang, EPA/OAQPS 1

, 2009 µg m -3 These model results are computationally expensive. How well do models capture variability in present-day PM 2.5?

2 Climate change will likely affect PM2.5 concentrations. Models disagree on the sign and the magnitude of the impacts. Racherla and Adams, 2006 Response of sulfate PM 2.5 at the surface to climate change. A2 Pye et al., 2009 µg m -3 These model results are computationally expensive. How well do models capture variability in present-day PM 2.5? A1 We need a simple tool that will allow AQ managers to readily calculate the climate consequences for PM2.5 air quality across a range of models and scenarios. µg m -3 2

3 The dependence of PM 2.5 on meteorological variables is complex. Different components have different sensitivities. Climate change over US?? Temperature Relative humidity Precipitation PM 2.5 dependence on met variables Model projections have uncertainties.? Stagnation Mixing depth AQ management tool CMIP3 archive of daily meteorology: 15 IPCC models Apply observed relationships between PM 2.5 and met fields AQ response to climate change 3

1998-2008 meteorology + EPA-AQS observations Multiple linear regression coefficients for total PM 2.

4 Stagnation is strongly correlated with high PM 2.5. Observed correlations of PM 2.5 with temperature and precipitation meteorology + EPA-AQS observations Multiple linear regression coefficients for total PM 2.5 on meteorological variables. Units: μg m -3 D -1 (p-value < 0.05) Increases in total PM 2.5 on a stagnant day vs. a non-stagnant day. Mean PM 2.5 is 2.6 μg m -3 greater on a stagnant day Tai et al

driving day-to-day PM 2.5 variability by region: Transport modes for PM 2.

5 Dominant meteorological modes driving PM 2.5 variability. Principal component analysis (PCA) of 8 meteorological variables identifies the dominant meteorological mode driving day-to-day PM 2.5 variability by region: Transport modes for PM 2.5 : Eastern US: mid-latitude cyclone and cold front passage Pacific coast: synoptic-scale maritime inflow Midwest, Jan 2006 Jan 28 Jan 30 PC R = Observed PM 2.5 (µg m -3 ) Tai et al.,

6 Fluctuations in the period of the dominant meteorological modes can largely explain interannual variability of PM 2.5. In each region, we identify the dominant meteorological mode whose mean period T is most strongly correlated with annual mean PM 2.5. In the Midwest: sensitivity dpm 2.5 /dτ = ~1 µg m -3 d -1 Annual mean PM 2.5 (µg m -3 ) cyclone period T PM 2.5 R = 0.76 Period Τ (d) Tai et al., 2012 Anomalies of annual mean PM 2.5 and period of dominant meteorological mode (cyclone passage) for US Midwest

2000-2050 climate change leads to increases in annual mean PM 2.5 across much of the Eastern US, but decreases across the West.

7 climate change leads to increases in annual mean PM 2.5 across much of the Eastern US, but decreases across the West. T period, day Increased maritime inflow Change in period T of dominant meteorological modes, weighted average for 15 models. Increased stagnation PM2.5, µg m -3 We apply observed sensitivity dpm 2.5 /dτ to model change in period T in each grid box. Corresponding change in annual mean PM 2.5 concentrations There is large variation among model projections. 7

Models disagree on the sign and magnitude of projected change in annual mean PM2.5, but some patterns emerge. 2000-2050 change in annual mean PM 2.

8 Models disagree on the sign and magnitude of projected change in annual mean PM2.5, but some patterns emerge change in annual mean PM 2.5 (µg m -3 ) Eastern US Northwest Likely responses: Increase of ~0.1 µg m -3 in eastern US due to increased stagnation Decrease of ~0.3 µg m -3 in Northwest due to more frequent maritime inflows 8

Response of PM 2.5 to 2000-2050 climate change Overall climate effect on annual PM 2.5 is likely to be less than ±0.5 µg m -3. Effect of fires on PM 2.

9 Response of PM 2.5 to climate change Overall climate effect on annual PM 2.5 is likely to be less than ±0.5 µg m -3. Effect of fires on PM 2.5 may be most important impact in future atmosphere, especially on a daily basis. Circulation Tai et al., this work Temperature Heald et al, 2008; Pye et al., 2009; Tai et al., 2012a Vegetation Wu et al., 2012 Wildfires Spracklen et al., 2009; Yue et al., 2012 Southeast (OC) Northwest (OC + BC) Northwest East Southeast (nitrate) Midwest + West (OC) Tai et al., change in annual mean PM 2.5 (µg m -3 ) 9

10 Next steps: Investigate health impacts of trends in PM 2.5 air quality amd compare to impacts from heatwaves. Proposal submitted to NIH; PI is Francesca Dominici, Harvard. Develop similar tool for assessing climate impact on U.S. ozone air quality, across multiple models and scenarios. Tai, A.P.K., L.J. Mickley, D.J. Jacob, E.M. Leibensperger, L. Zhang, J.A. Fisher, and H.O.T. Pye, Meteorological modes of variability for fine particulate matter (PM 2.5 ) air quality the United States: implications for PM2.5 sensitivity, Atmos. Chem. Phys., 2012a. Tai, A. P. K., L. J. Mickley, and D. J. Jacob, Impact of climate change on fine particulate matter (PM 2.5 ) air quality inferred from a multi-model analysis of meteorological modes, submitted to Atmos. Chem. Phys., 2012b. 10

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5 /dτ Τ (d) Weighted average 2000-2050 change in T (15 IPCC AR4

12 Multi-model Projection of Synoptic Period and PM 2.5 dpm 2.5 /dτ (µg m -3 d -1 ) Climatological observation of dpm 2.5 /dτ Τ (d) Weighted average change in T (15 IPCC AR4 GCMs) = PM 2.5 (µg m -3 ) Resulting change in PM 2.5 [Tai et al., in prep]

13 Project Roadmap: 1. Identify the main meteorological modes controlling observed PM2.5 across the United States (Tai et al., 2010; 2011) 2. Calculate the sensitivity of PM2.5 to the frequency of the dominant meteorological mode. (Tai et al., 2011) Tai, A.P.K., L.J. Mickley, D.J. Jacob, E.M. Leibensperger, L. Zhang, J.A. Fisher, and H.O.T. Pye, Meteorological modes of variability for fine particulate matter (PM2.5) air quality the United States: implications for PM2.5 sensitivity to climate change, submitted to Atmos. Chem. Phys., Track the changes in these modes using the IPCC AR4 archive of climate projections. 4. Estimate the change in surface PM2.5 concentrations due to climate penalty (or climate benefit). AQ management tool IPCC archive of daily meteorology Main meteorological modes driving observed PM2.5 AQ response to climate change 13

14 Evaluation of present-day meteorological modes in AR4 climate models reveals differences among models. N42 W87.5 Observed Frequency (d -1 ) model s Modeled (2 IPCC models) and observed (NCEP/NCAR) time series of frequency of dominant meteorological mode for PM 2.5 in U.S. Midwest Some models capture both the long-term mean and variability of meteorological mode frequency well. As a first step, we use only those models that capture present-day mean and variability of frequency to predict future PM

Estimating the impact of climate change on fine particulate matter across the United States:

Estimating the impact of climate change on fine particulate matter across the United States: Use of principal component analysis as a quick gauge across models and scenarios Loretta J. Mickley Co-Is: Amos