Treatment of clouds and the associated response of atmospheric sulfur in the Community Multiscale Air Quality (CMAQ) modeling system

Mueller, Stephen F.; Bailey, Elizabeth M.; Cook, Toree M.; Mao, Qi

doi:10.1016/j.atmosenv.2006.05.069

Cited by 14 publications

(9 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, Wang et al () explored the source apportionment of PM 2.5 in three cities (SJZ, Xingtai, and Handan) in Southern Hebei province of China by using the Mesoscale Modeling System Generation 5 (MM5) and the Models‐3/Community Multiscale Air Quality (CMAQ) modeling system; Hu et al () used the source‐oriented CMAQ to determine the source sector/region's contributions to primary particulate matter in China; Liu et al () applied Weather Research and Forecasting (WRF)/Chem model to study the spatial and seasonal variations of several air pollutants (SO 2 , NOx, CO, VOCs, NH 3 , PM 2.5 , and PM 10 ) from anthropogenic sources in Henan province; a nested grid air quality model system (NAQPMS) was used to simulate PM 2.5 concentration changes in BTH region and Chengdu‐Chongqing urban cluster during 2013–2015 (Wang et al, ). Also, there are some studies which mainly focused on one single pollutant such as SO 2 (Itahashi et al, ; Mueller et al, ), NO x (Han et al, ), and O 3 (N. Wang, Gou, et al, ). However, previous studies primarily focused on conventional air pollutants, and none has investigated the spatial and temporal variations of TEs in BTH region, especially for modeling based on the localized emission inventory.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variations of Ambient Concentrations of Trace Elements in a Highly Polluted Region of China

et al. 2019

View full text Add to dashboard Cite

Anthropogenic emissions of trace elements (TEs) into the atmosphere have warranted global concern due to their adverse effects on human health and the ecosystem. We adapted the Weather Research and Forecasting (WRF) and Models‐3/Community Multiscale Air Quality (CMAQ) modeling system to predict the spatial and temporal concentrations of 11 TEs (arsenic, selenium, lead, cadmium, chromium, nickel, antimony, manganese, cobalt, copper, and zinc) in fine particulate matter (PM2.5) in January, April, July, and October of 2012 over Beijing, Tianjin, and Hebei (BTH) region of Northern China, one of the most polluted areas in China with frequent occurrences of haze episodes. A localized emission inventory that includes both conventional air pollutants and TEs established by our previous study was used in the model. Predicted concentrations of TEs were compared with observations collected at a site located in Beijing Normal University. The results show that arsenic, selenium, lead, copper, nickel, and zinc predictions better agree with observations made in both months. Manganese, antimony, and cobalt simulations display different abilities to reproduce observations between months. Chromium predictions have lower correlation coefficients. Cadmium predictions, similar to previous findings, show the least ability to reproduce observations. According to the model predictions, higher concentrations of TEs are primarily identified in the central and southern areas of the BTH region, and seasonally January sees the highest TEs. Potential causes for high concentrations of TEs were examined by evaluating emissions and contributions from major sources. Finally, specific countermeasures for emissions reduction of TEs were proposed.

show abstract

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variations of Ambient Concentrations of Trace Elements in a Highly Polluted Region of China

et al. 2019

View full text Add to dashboard Cite

show abstract

“…O 3 episodes in the eastern U.S. can extend well beyond the area of a single state [e.g., Gilliland et al , 2008; Logan , 1989; Ryan et al , 1998; Zhang and Rao , 1999]. Exchange of air between the PBL and lower free troposphere (LFT), especially as mediated by small‐scale cumulus clouds, has been suggested to play an important role in the temporal and spatial scales of smog events [ Ching et al , 1988; Hains , 2007; Hains et al , 2008; Mueller et al , 2006; Taubman et al , 2004, 2006]. Effective modeling for control of O 3 must adequately simulate this vertical transport.…”

Section: Introductionmentioning

confidence: 99%

Ozone, oxides of nitrogen, and carbon monoxide during pollution events over the eastern United States: An evaluation of emissions and vertical mixing

et al. 2011

View full text Add to dashboard Cite

[1] Chemical transport models such as the Community Multiscale Air Quality (CMAQ) model provide useful guidance on air pollution control strategies. We evaluate the performance of a 12 km resolution CMAQ simulation with surface and aircraft observations of CO, O 3 , and NO x during the summer of 2002. When all data are considered, on average, modeled and observed CO total column contents (surface to 3,000 m) agreed to within 14% in the morning and 22% in the afternoon. Reducing the deposition velocity for CO improves model-measurement agreement but did not eliminate the model bias. The majority of observed vertical profiles have a maximum near the surface. Although many observed spirals had a secondary maximum at the top of the boundary layer, indicating subgrid-scale shallow convection. The model was not able to replicate these vertical structures. Water vapor profiles likewise showed greater vertical variability in the observations than in the model. General conclusions from these model-measurement comparisons: total CO emissions estimates are either adequate or underestimated,

show abstract

“…Table 1 shows that the underestimate in GEOS-FP cloud fraction is mainly due to a lack of fair-weather cumulus. Climate models generally tend to underestimate low cloud cover (Zhang, 2005;Mueller et al, 2006;Chepfer et al, 2008; 15 Naud et al, 2010;Kay et al, 2012;Nam et al, 2012). The GEOS-Chem underestimate of sulfate aerosol production in SEAC 4 RS, previously attributed by Kim et al (2015) to a missing SO2 oxidation pathway involving Criegee biradicals, could instead be due to insufficient cloud processing.…”

Section: Relationship To Cloud Cover and Precipitationmentioning

confidence: 92%

Resolving ozone vertical gradients in air quality models

Travis

Jacob

Keller

et al. 2017

Preprint

View full text Add to dashboard Cite

Abstract. Models severely overestimate surface ozone in the Southeast US during summertime and this overestimation has implications for the design of air quality regulations. We use the GEOS-Chem model to interpret ozone observations from aircraft 15 (SEAC 4 RS), ozonesondes (SEACIONS), and surface sites (CASTNET) in August-September 2013. After correcting for a 30-50 % NOx emission overestimate in the US EPA National Emission Inventory, we find that the model is unbiased relative to aircraft observations below 1 km. However, surface observations of maximum daily 8-h average (MDA8) ozone are still biased high in the model (averaging 48 ± 9 ppb) compared to observations (40 ± 9 ppb). The low tail in the observations (MDA8 ozone < 25 ppb) is associated with rain and is not captured by the model. The model bias decreases by 3 ppb when accounting for the subgrid 20 vertical gradient between the lowest model level (centered 60 m above ground) and the measurement altitude (10 m). The model underestimates low cloud cover, but this underestimate is insufficient to explain the remaining surface ozone bias because the response of model ozone to cloud cover is weaker than observed. Midday ozonesondes at Huntsville, Alabama show mean decreases in ozone from 1 km to the surface of 4 ppb under clear-sky and 7 ppb under low cloud, whereas the model decreases by only 1 ppb under both conditions. By contrast, potential temperature below 1 km is well-mixed in both the observations and the 25 model. The observations thus imply a strong asymmetry between top-down and bottom-up mixing that is missing from GEOSChem and appears to be insufficiently represented in current air quality models. A sensitivity simulation reducing top-down eddy diffusion and removing top-down non-local vertical transport of ozone can reproduce the observed ozone gradients in the mixed layer.

show abstract

Treatment of clouds and the associated response of atmospheric sulfur in the Community Multiscale Air Quality (CMAQ) modeling system

Cited by 14 publications

References 13 publications

Spatiotemporal Variations of Ambient Concentrations of Trace Elements in a Highly Polluted Region of China

Spatiotemporal Variations of Ambient Concentrations of Trace Elements in a Highly Polluted Region of China

Ozone, oxides of nitrogen, and carbon monoxide during pollution events over the eastern United States: An evaluation of emissions and vertical mixing

Resolving ozone vertical gradients in air quality models

Contact Info

Product

Resources

About