Four dimensional data assimilation experiments with International Consortium for Atmospheric Research on Transport and Transformation ozone measurements

International audienceOzone measurements by various platforms during the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) operations in the summer of 2004 are assimilated into the STEM regional chemical transport model (CTM). Under the four-dimensional variational data assimilation (4D-Var) framework, the model forecast (background) error covariance matrix is constructed using both the so-called NMC (National Meteorological Center, now National Centers for Environmental Prediction) method and the observational (Hollingworth-Lönnberg) method. The inversion of the covariance matrix is implemented using truncated singular value decomposition (TSVD) approach. The TSVD approach is numerically stable even with severely ill conditioned vertical correlation covariance matrix and large horizontal correlation distances. Ozone observations by different platforms (aircraft, surface, and ozonesondes) are first assimilated separately. The impacts of the various measurements are evaluated on their ability to improve the predictions, defined as the information content of the observations under the current framework. In the end, all observations are assimilated into the CTM. The final analysis matches well with observations from all platforms. Assessed with all the observations throughout the boundary layer and midtroposphere, the model bias is reduced from 11.3 ppbv for the base case to −1.5 ppbv. A reduction of 10.3 ppbv in root mean square error is also seen. In addition, the potential of improving air quality forecasts by chemical data assimilation is demonstrated. The effect of assimilating ozone observations on model predictions of other species is also shown

Premature deaths attributed to source-specific BC emissions in six urban US regions

Recent studies have shown that exposure to particulate black carbon (BC) has significant adverse health effects and may be more detrimental to human health than exposure to PM2.5 as a whole. Mobile source BC emission controls, mostly on diesel-burning vehicles, have successfully decreased mobile source BC emissions to less than half of what they were 30 years ago. Quantification of the benefits of previous emissions controls conveys the value of these regulatory actions and provides a method by which future control alternatives could be evaluated. In this study we use the adjoint of the Community Multiscale Air Quality (CMAQ) model to estimate highly-resolved spatial distributions of benefits related to emission reductions for six urban regions within the continental US. Emissions from outside each of the six chosen regions account for between 7% and 27% of the premature deaths attributed to exposure to BC within the region. While we estimate that nonroad mobile and onroad diesel emissions account for the largest number of premature deaths attributable to exposure to BC, onroad gasoline is shown to have more than double the benefit per unit emission relative to that of nonroad mobile and onroad diesel. Within the region encompassing New York City and Philadelphia, reductions in emissions from large industrial combustion sources that are not classified as EGUs (i.e., non-EGU) are estimated to have up to triple the benefits per unit emission relative to reductions to onroad diesel sectors, and provide similar benefits per unit emission to that of onroad gasoline emissions in the region. While onroad mobile emissions have been decreasing in the past 30 years and a majority of vehicle emission controls that regulate PM focus on diesel emissions, our analysis shows the most efficient target for stricter controls is actually onroad gasoline emissions

Differences between magnitudes and health impacts of BC emissions across the United States using 12 km scale seasonal source apportionment

Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, which provides source-receptor relationships at highly resolved sectoral, spatial, and temporal scales. While damage resulting from anthropogenic emissions of BC is strongly correlated with population and premature death, we found little correlation between damage and emission magnitude, suggesting that controls on the largest emissions may not be the most efficient means of reducing damage resulting from anthropogenic BC emissions. Rather, the best proxy for locations with damaging BC emissions is locations where premature deaths occur. Onroad diesel and nonroad vehicle emissions are the largest contributors to premature deaths attributed to exposure to BC, while onroad gasoline emissions cause the highest deaths per amount emitted. Emissions in fall and winter contribute to more premature deaths (and more per amount emitted) than emissions in spring and summer. Overall, these results show the value of the high-resolution source attribution for determining the locations, seasons, and sectors for which BC emission controls have the most effective health benefits