Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.414
IF5.414
IF 5-year value: 5.958
IF 5-year
5.958
CiteScore value: 9.7
CiteScore
9.7
SNIP value: 1.517
SNIP1.517
IPP value: 5.61
IPP5.61
SJR value: 2.601
SJR2.601
Scimago H <br class='widget-line-break'>index value: 191
Scimago H
index
191
h5-index value: 89
h5-index89
Volume 15, issue 6
Atmos. Chem. Phys., 15, 3445–3461, 2015
https://doi.org/10.5194/acp-15-3445-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 15, 3445–3461, 2015
https://doi.org/10.5194/acp-15-3445-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 30 Mar 2015

Research article | 30 Mar 2015

Long-term particulate matter modeling for health effect studies in California – Part 1: Model performance on temporal and spatial variations

J. Hu1, H. Zhang1, Q. Ying2, S.-H. Chen3, F. Vandenberghe4, and M. J. Kleeman1 J. Hu et al.
  • 1Department of Civil and Environmental Engineering, University of California, Davis, One Shields Avenue, Davis, CA, USA
  • 2Zachry Department of Civil Engineering, Texas A{&}M University, College Station, TX, USA
  • 3Department of Land, Air, and Water Resources, University of California, Davis, One Shields Avenue, Davis, CA, USA
  • 4Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, USA

Abstract. For the first time, a ~ decadal (9 years from 2000 to 2008) air quality model simulation with 4 km horizontal resolution over populated regions and daily time resolution has been conducted for California to provide air quality data for health effect studies. Model predictions are compared to measurements to evaluate the accuracy of the simulation with an emphasis on spatial and temporal variations that could be used in epidemiology studies. Better model performance is found at longer averaging times, suggesting that model results with averaging times ≥ 1 month should be the first to be considered in epidemiological studies. The UCD/CIT model predicts spatial and temporal variations in the concentrations of O3, PM2.5, elemental carbon (EC), organic carbon (OC), nitrate, and ammonium that meet standard modeling performance criteria when compared to monthly-averaged measurements. Predicted sulfate concentrations do not meet target performance metrics due to missing sulfur sources in the emissions. Predicted seasonal and annual variations of PM2.5, EC, OC, nitrate, and ammonium have mean fractional biases that meet the model performance criteria in 95, 100, 71, 73, and 92% of the simulated months, respectively. The base data set provides an improvement for predicted population exposure to PM concentrations in California compared to exposures estimated by central site monitors operated 1 day out of every 3 days at a few urban locations.

Uncertainties in the model predictions arise from several issues. Incomplete understanding of secondary organic aerosol formation mechanisms leads to OC bias in the model results in summertime but does not affect OC predictions in winter when concentrations are typically highest. The CO and NO (species dominated by mobile emissions) results reveal temporal and spatial uncertainties associated with the mobile emissions generated by the EMFAC 2007 model. The WRF model tends to overpredict wind speed during stagnation events, leading to underpredictions of high PM concentrations, usually in winter months. The WRF model also generally underpredicts relative humidity, resulting in less particulate nitrate formation, especially during winter months. These limitations must be recognized when using data in health studies. All model results included in the current manuscript can be downloaded free of charge at http://faculty.engineering.ucdavis.edu/kleeman/ .

Publications Copernicus
Short summary
Air quality model simulations have been conducted for California from 2000 to 2009 with 4km spatial resolution to provide exposure data for health effect studies. Comprehensive analysis shows that predicted concentrations for many pollutants are in agreement with measurements at monitoring stations, building confidence that the fields may be useful at times and locations where measurements are not available. Data can be downloaded for free at http://faculty.engineering.ucdavis.edu/kleeman/.
Air quality model simulations have been conducted for California from 2000 to 2009 with 4km...
Citation
Altmetrics
Final-revised paper
Preprint