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Following a comprehensive model evaluation in part 1, this part 2 paper describes results from 1 year process analysis and a number of sensitivity simulations using the Community Multiscale Air Quality (CMAQ) modeling system aimed to understand the formation mechanisms of O3 and PM2.5, their impacts on global environment, and implications for pollution control policies. Process analyses show that the most influential processes for O3 in the planetary boundary layer (PBL) are vertical and horizontal transport, gas‐phase chemistry, and dry deposition and those for PM2.5 are primary PM emissions, horizontal transport, PM processes, and cloud processes. Exports of O3 and Ox from the U.S. PBL to free troposphere occur primarily in summer and at a rate of 0.16 and 0.65 Gmoles day−1, respectively. In contrast, export of PM2.5 is found to occur during all seasons and at rates of 25.68–34.18 Ggrams day−1, indicating a need to monitor and control PM2.5 throughout the year. Among nine photochemical indicators examined, the most robust include PH2O2/PHNO3, HCHO/NOy, and HCHO/NOz in winter and summer, H2O2/(O3 + NO2) in winter, and NOy in summer. They indicate a VOC‐limited O3 chemistry in most areas in winter, but a NOx‐limited O3 chemistry in most areas except for major cities in April–November, providing a rationale for nationwide NOx emission control and integrated control of NOx and VOCs emissions for large cities during high O3 seasons (May–September). For sensitivity of PM2.5 to its precursors, the adjusted gas ratio provides a more robust indicator than that without adjustment, especially for areas with insufficient sulfate neutralization in winter. NH4NO3 can be formed in most of the domain. Integrated control of emissions of PM precursors such as SO2, NOx, and NH3 are necessary for PM2.5 attainment. Among four types of VOCs examined, O3 formation is primarily affected by isoprene and low molecular weight anthropogenic VOCs, and PM2.5 formation is affected largely by terpenes and isoprene. Under future emission scenarios, surface O3 may increase in summer; surface PM2.5 may increase or decrease. With 0.71°C increase in future surface temperatures in summer, surface O3 may increase in most of the domain and surface PM2.5 may decrease in the eastern U.S. but increase in the western U.S.

[1] As part 1 in a series of papers describing long-term simulations using the Community Multiscale Air Quality (CMAQ) modeling system and subsequent process analyses and sensitivity simulations, this paper presents a comprehensive model evaluation for the full year of 2001 over the continental U.S. using both ground-based and satellite measurements. CMAQ is assessed for its ability to reproduce concentrations and long-term trends of major criteria pollutants such as surface ozone (O 3 ) and fine particulate matter (PM 2.5 ) and related variables such as indicator species, wet deposition fluxes, and column mass abundances of carbon monoxide (CO), nitrogen oxides (NO 2 ), tropospheric ozone residuals (TORs), and aerosol optical depths (AODs). The domain-wide and site-specific evaluation of surface predictions shows an overall satisfactory performance in terms of normalized mean biases for annual mean maximum 1 h and 8 h average O 3 mixing ratios (À11.6 to 0.1% and À4.6 to 3.0%, respectively), 24 h average concentrations of PM 2.5 (4.2-35.3%), sulfate (À13.0 to 43.5%), and organic carbon (OC) (À37.6 to 24.8%), and wet deposition fluxes (À13.3 to 31.6%). Larger biases, however, occur in the concentrations and wet deposition fluxes of ammonium and nitrate domain-wide and in the concentrations of PM 2.5 , sulfate, black carbon, and OC at some urban/suburban sites. The reasons for such model biases may be errors in emissions, chemistry, aerosol processes, or meteorology. The evaluation of column mass predictions shows a good model performance in capturing the seasonal variations and magnitudes of column CO and NO 2 , but relatively poor performance in reproducing observed spatial distributions and magnitudes of TORs for winter and spring and those of AODs in all seasons. Possible reasons for the poor column predictions include the underestimates of emissions, inaccurate upper layer boundary conditions, lack of model treatments of sea salt and dust, and limitations and uncertainties in satellite data.Citation: Zhang, Y., K. Vijayaraghavan, X.-Y. Wen, H. E. Snell, and M. Z. Jacobson (2009), Probing into regional ozone and particulate matter pollution in the United States: 1. A 1 year CMAQ simulation and evaluation using surface and satellite data,

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