Application, Evaluation, and Process Analysis of the US EPA’s 2002 Multiple-Pollutant Air Quality Modeling Platform

Abstract

A multiple-pollutant version of CMAQ v4.6 (i.e., CMAQ-MP) has been applied by the US EPA over continental US in 2002 to demonstrate the model's capability in reproducing the long-term trends of ambient criteria and hazardous air pollutants (CAPs and HAPs, respectively) in support of regulatory analysis for air quality management. In this study, a comprehensive model performance evaluation for the full year of 2002 is performed for the first time for CMAQ-MP using the surface networks and satellite measurements. CMAQ-MP shows a comparable and improved performance for most CAPs species as compared to an older version of CMAQ that did not treat HAPs and used older versions of national emission inventories. CMAQ-MP generally gives better performance for CAPs than for HAPs. Max 8-h ozone (O 3 ) mixing ratios are well reproduced in the O 3 season. The seasonal-mean performance is fairly good for fine particulate matter (PM 2.5 ), sulfate , and mercury (Hg) wet deposition and worse for other CAPs and HAPs species.The reasons for the model biases may be attributed to uncertainties in emissions for some species (e.g., ammonia (NH 3 ), elemental carbon (EC), primary organic aerosol (POA), HAPs), gas/aerosol chemistry treatments (e.g., secondary organic aerosol formation, meteorology (e.g., overestimate in summer precipitation), measurements (e.g.,, and the use of a coarse grid resolution. CMAQ cannot well reproduce spatial and seasonal variations of column variables except for nitrogen dioxide (NO 2 ) and the ratio of column mass of HCHO/NO 2 . Possible reasons include inaccurate seasonal allocation or underestimation of emissions, inaccurate BCONs at higher altitudes, lack of model treatments such as mineral dust or plume-in-grid process, and limitations and errors in satellite data retrievals. The process analysis results show that in addition to transport, gas chemistry or aerosol/emissions play the most important roles for O 3 or PM 2.5 , respectively. For most HAPs, emissions are important sources and cloud processes are a major sink. Simulated 2 2 3 H O HNO P P and HCHO/NO 2 indicate VOC-limited chemistry in major urban areas throughout the year and in other non-urban areas in winter, but NO X -limited chemistry in most areas in summer.

Sensitivity of simulated chemical concentrations and aerosol‐meteorology interactions to aerosol treatments and biogenic organic emissions in WRF/Chem

“…Underpredictions in volatile organic compounds (VOCs) may also be possible (although no VOCs observations are available), as O 3 chemistry is VOC limited over most areas in winter [ Zhang et al ., , ]. Using a similar emission inventory for 2002 simulations over CONUS, Wang and Zhang [] showed an underprediction of both surface concentrations and column abundances for HCHO, supporting possible underestimates in VOCs emissions used in this work. Other possible reasons for O 3 underpredictions may be the uncertainties in the magnitudes and vertical allocations of emissions of precursors such as CO and NO x and predicted vertical mixing.…”

“…The overpredictions in surface NO 2 concentrations but underpredictions in column NO 2 abundances indicate possible uncertainties in the vertical allocations of NO 2 emissions and vertical mixing of NO 2 . Wang and Zhang [] showed large underpredictions in surface HCHO concentrations but large overpredictions in column HCHO abundance, also indicating possible uncertainties in the vertical allocation of HCHO and other anthropogenic VOCs emissions. HNO 3 concentrations are moderately‐to‐significantly overpredicted at the SEARCH sites.…”

Simulation of ozone formation at different elevations in mountainous area of Hong Kong using WRF-CMAQ model

“…In this study, in order to understand the mechanisms of O 3 formation, the contribution of each controlling process to the formation and destruction of O 3 at the two sites was calculated using the IPR tool by quantifying the net effect of each atmospheric process, i.e., horizontal transport including advection and diffusion, vertical transport including advection and diffusion, dry deposition and gasphase chemistry. Details of IPR analysis can be found in Wang et al (2006); Wang and Zhang (2012).…”

Modeling regional air quality and climate: improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1

“…While both OC and TC from IM-PROVE are used for model evaluation, only TC data from STN are used, as STN uses the thermo-optical transmittance protocol for OC that is different from the one used by IM-PROVE . In addition, the measurements for STN OC are not blank corrected for carbon on the background filter (Wang and Zhang, 2012). The OA / OC ratios vary across locations in the continental US (CONUS) depending on whether the OA is dominated by secondary formation (Aitken et al, 2008) or it contains more aliphatic hydrocarbons (Turpin and Lim, 2001).…”