Impact of Climate Change on Fine Particulate Matter \((PM_{2.5})\) Air Quality

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Impact of Climate Change on Fine Particulate Matter \((PM_{2.5})\) Air Quality

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Title: Impact of Climate Change on Fine Particulate Matter \((PM_{2.5})\) Air Quality
Author: Tai, Pui Kuen Amos P. K.
Citation: Tai, Pui Kuen Amos P. K. 2012. Impact of Climate Change on Fine Particulate Matter \((PM_{2.5})\) Air Quality. Doctoral dissertation, Harvard University.
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Abstract: This dissertation investigates the impact of 2000-2050 climate change on fine particulate matter \((PM_{2.5})\) air quality. We first applied a multiple linear regression model to study the correlations of total \(PM_{2.5}\) and its components with meteorological variables using the past decadal \(PM_{2.5}\) observations over the contiguous US. We find that daily variation in meteorology can explain up to 50% of \(PM_{2.5}\) variability. Temperature is positively correlated with sulfate and organic carbon (OC) almost everywhere. The correlation of nitrate with temperature is negative in the Southeast but positive in California and the Great Plains. Relative humidity (RH) is positively correlated with sulfate and nitrate, but negatively with OC. Precipitation is strongly negatively correlated with all \(PM_{2.5}\) components. We then compared the observed correlations of \(PM_{2.5}\) with meteorological variables with results from the GEOS-Chem chemical transport model. The results indicate that most of the correlations of \(PM_{2.5}\) with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling \(PM_{2.5}\) variability, and showed that 20-40% of the observed \(PM_{2.5}\) daily variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. From 1999-2010 observations we further showed that interannual variability of annual mean \(PM_{2.5}\) in most of the US is strongly correlated with the synoptic period T of the dominant meteorological mode as diagnosed from a spectral-autoregressive analysis. We then used the observed local \(PM_{2.5}\)-to-period sensitivity to project \(PM_{2.5}\) changes from the 2000-2050 changes in T simulated by fifteen IPCC AR4 GCMs following the SRES A1B scenario. We project a likely increase of \(\sim 0.1 \mu g m^{-3}\) in annual mean \(PM_{2.5}\) in the eastern US arising from less frequent frontal ventilation, and a likely decrease of \(\sim 0.3 \mu g m^{-3}\) in the northwestern US due to more frequent maritime inflows. These circulation-driven changes are relatively small, representing only a minor climate penalty or benefit for \(PM_{2.5}\) regulatory purpose.
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