Meteorology Feedbacks Research Articles

Wildfire aerosols and their impact on weather: A case study of the August 2021 fires in Greece using the WRF‐Chem model

AbstractWildfires are significant contributors to atmospheric gases and aerosols, impacting air quality and composition. This pollution from fires also affects radiative forcing, influencing short‐term weather patterns and climate dynamics. Our research employs the Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) to investigate the repercussions of wildfires on aerosol abundances and associated immediate weather responses. We examine the summer season of 2021, a period marked by severe wildfire events in the country during a heatwave period. We conducted sensitivity experiments including and excluding wildfire emissions to measure their effects on aerosol optical depth (AOD), radiative forcing, and weather features such as temperature, humidity, clouds, and atmospheric circulation. Our findings demonstrate that the radiative impacts of wildfires negatively influence the local temperature over the fire smoke plume‐affected areas. Conversely, neighbouring areas of continental Greece experience increases in temperature due to remote effects of wildfire emissions, caused by meteorological feedbacks that reduce atmospheric humidity. Crucially, including fire emissions significantly improves the simulated surface temperatures predicted by the model over the Greek domain. Our work demonstrates that wildfire‐generated aerosols can significantly impact weather conditions and highlights the importance of including both local radiative effects and remote feedback for achieving more accurate weather prediction.

Studying the Aerosol Effect on Deep Convective Clouds over the Global Oceans by Applying Machine Learning Techniques on Long-Term Satellite Observation

Long-term (1982–2019) satellite climate data records (CDRs) of aerosols and clouds, reanalysis data of meteorological fields, and machine learning techniques are used to study the aerosol effect on deep convective clouds (DCCs) over the global oceans from a climatological perspective. Our analyses are focused on three latitude belts where DCCs appear more frequently in the climatology: the northern middle latitude (NML), tropical latitude (TRL), and southern middle latitude (SML). It was found that the aerosol effect on marine DCCs may be detected only in NML from long-term averaged satellite aerosol and cloud observations. Specifically, cloud particle size is more susceptible to the aerosol effect compared to other cloud micro-physical variables (e.g., cloud optical depth). The signature of the aerosol effect on DCCs can be easily obscured by meteorological covariances for cloud macro-physical variables, such as cloud cover and cloud top temperature (CTT). From a machine learning analysis, we found that the primary aerosol effect (i.e., the aerosol effect without meteorological feedbacks and covariances) can partially explain the aerosol convective invigoration in CTT and that meteorological feedbacks and covariances need to be included to accurately capture the aerosol convective invigoration. From our singular value decomposition (SVD) analysis, we found the aerosol effects in the three leading principal components (PCs) may explain about one third of the variance of satellite-observed cloud variables and significant positive or negative trends are only observed in the lead PC1 of cloud and aerosol variables. The lead PC1 component is an effective mode for detecting the aerosol effect on DCCs. Our results are valuable for the evaluation and improvement of aerosol-cloud interactions in the long-term climate simulations of global climate models.

Study on visibility forecast optimization based on aerosol- meteorological feedbacks in wet conditions

Study on visibility forecast optimization based on aerosol- meteorological feedbacks in wet conditions

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry-meteorology feedbacks on air quality.

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry-meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O3) and fine particulate matter (PM2.5). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O3, sulfate, nitrate, ammonium, elemental carbon, tropospheric O3 residual, and column nitrogen dioxide (NO2). For example, the mean biases have been reduced by more than 10 W m-2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O3. However, relatively large biases still exist for cloud predictions, some PM2.5 species, and PM10 that warrant follow-up studies to better understand those issues. The impacts of chemistry-meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O3, nitrogen oxide (NO x ), volatile organic compounds (VOCs), and PM2.5 by 3.1% (up to 27.8%), 4.2% (up to 16.2%), 6.6% (up to 50.9%), 5.8% (up to 46.6%), and 8.6% (up to 49.1%), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

A study of the effect of aerosols on surface ozone through meteorology feedbacks over China

Abstract. Interactions between aerosols and gases in the atmosphere have been the focus of an increasing number of studies in recent years. Here, we focus on aerosol effects on tropospheric ozone that involve meteorological feedbacks induced by aerosol–radiation interactions. Specifically, we study the effects that involve aerosol influences on the transport of gaseous pollutants and on atmospheric moisture, both of which can impact ozone chemistry. For this purpose, we use the UK Earth System Model (UKESM1), with which we performed sensitivity simulations including and excluding the aerosol direct radiative effect (ADE) on atmospheric chemistry, and focused our analysis on an area with a high aerosol presence, namely China. By comparing the simulations, we found that ADE reduced shortwave radiation by 11 % in China and consequently led to lower turbulent kinetic energy, weaker horizontal winds and a shallower boundary layer (with a maximum of 102.28 m reduction in north China). On the one hand, the suppressed boundary layer limited the export and diffusion of pollutants and increased the concentration of CO, SO2, NO, NO2, PM2.5 and PM10 in the aerosol-rich regions. The NO/NO2 ratio generally increased and led to more ozone depletion. On the other hand, the boundary layer top acted as a barrier that trapped moisture at lower altitudes and reduced the moisture at higher altitudes (the specific humidity was reduced by 1.69 % at 1493 m on average in China). Due to reduced water vapour, fewer clouds were formed and more sunlight reached the surface, so the photolytical production of ozone increased. Under the combined effect of the two meteorology feedback methods, the annual average ozone concentration in China declined by 2.01 ppb (6.2 %), which was found to bring the model into closer agreement with surface ozone measurements from different parts of China.

Aerosol‐Radiation Interactions of Dust Storm Deteriorate Particle and Ozone Pollution in East China

AbstractEast Asia features frequent dust storms and intensive anthropogenic emissions. The mixing of natural dust and anthropogenic pollutants exerts complicated impacts on air pollution and regional climate. Studies have focused on chemical interactions of the mixed pollution, while the meteorological feedback and influences on atmospheric chemistry have not been fully investigated. Here, a comprehensive study on a widespread dust storm and its influence on the air quality downwind was conducted by combining multiple observations and modeling. We found that dust originated from Gobi Desert was mixed with anthropogenic pollutants after transported to the Yangtze River Delta (YRD). Through scattering and absorbing radiation, dust aerosol perturbed solar energy budget and led to a more stabilized planetary boundary layer (PBL). A reduction of 15% in PBL height (184 m) weakened the dispersion of locally emitted pollutants and increased primary pollution by 10% in YRD city clusters. Besides, the mixed plume over offshore areas warmed the entire lower atmosphere and increased surface evaporation. Accordingly, ozone formation was accelerated by ∼1 ppbv/h within PBL under higher temperature, and secondary aerosol was increased due to faster photochemical and heterogeneous oxidation. Such enhancements substantially contributed to air quality deterioration in YRD region. This work reveals the complexity of interactions between natural dust and anthropogenic pollutants through both atmospheric chemistry and meteorological feedbacks, which is of great importance in both regional air pollution and climate.

Modeling PM2.5 and O3 with aerosol feedbacks using WRF/Chem over the Sichuan Basin, southwestern China

With a large population and fast economic growth, the Sichuan Basin (SCB) has been suffering from air pollution in recent years. However, limited studies have estimated air pollution levels in consideration of the feedbacks of aerosols on meteorology in the SCB. In this study, simulation of fine particulate matter (PM2.5) and ozone (O3) over the SCB with a horizontal resolution of 36 km over China and 12 km was conducted for summer (July) and winter (January) in 2015 using the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem). The model well captured the variations of PM2.5 and daily maximum 8 h average (MDA8) O3 in the 18 cities, especially O3 in July and PM2.5 in January. From rim to center, averaged PM2.5 increased from 40 μg/m3 to 100 μg/m3 in January while averaged O3 ranged from 60 to 90 ppb in July. Aerosol radiation decreased surface temperature by 1–2 °C, wind speed (WS) by ∼ 0.3 m/s, planetary boundary layer (PBL) height by 10–20%, solar radiation (SR) by ∼30%, and precipitation by 0.02–0.2 mm, while increased relative humidity (RH) by up to 2–4% in January, which resulted in up to 10 μg/m3 increase of PM2.5 in January and 2 ppb decrease of O3 in July. The effect increased as the increase of PM2.5 concentration and can be up to 18% in January and 25% in July. This study highlights the importance of considering meteorology feedbacks in understanding and controlling air pollution in the SCB.

A multi-scale model analysis of ozone formation in the Bangkok Metropolitan Region, Thailand

Abstract Over the last three decades, Thailand's rapid industrialization and urbanization have led to an impact on urban air quality. A majority of the country's development has occurred within and around Bangkok (BKK), the capital city of Thailand, and the Bangkok Metropolitan Region (BMR). Since 1995, the BMR has experienced air quality degradation, in particular, enhanced ozone (O3) due to a combination of the local increase in emissions from accelerated growth in automotive and industrial activities, local meteorology including strong solar radiation, high temperature and high humidity, and potential long-range effects of regional transport from China. To investigate the O3 formation in the BMR due to the effects of long-range transport and local meteorology feedbacks, we perform a multi-scale simulation with the Weather Research and Forecasting model with Chemistry (WRF-Chem) during the O3 season (January to March), 2010; since O3 mixing ratio exceedances in the BMR occur primarily during this period The results in this study indicate the significance of China's emission reductions on the regional-scale and the local-scale pollution, as far as the BMR region and southern Thailand. Applying China's oxide of nitrogen (NOx)-only emission controls, generally, enhance the domain-wide monthly-average peroxyacetyl nitrate (PAN) and O3 in the regional scale, in the order of ~1–7% and ~1–5%, respectively, while those in the local scale are ~ 0.2–6% and ~0.1–5% compared with the baseline simulation. However, the increases in PAN and O3 are mitigated by 40% China's Volatile Organic Compound (VOC) reduction along with 40% NOx reduction. The results, supported by an indicator analysis, suggest that northern and eastern China, northern and central Thailand and the BMR, are likely VOC-limited during the O3 season. Since the BMR is VOC-limited regime, controlling anthropogenic VOC emissions will show more benefit to control O3 than controlling NOx-only emissions. Other factors that influence on O3 levels in the BMR are biogenic VOC emissions from the Tenasserim range and land- and sea-breeze circulations that recirculate and disperse pollutants along the coastal areas.

Investigating size-segregated sources of elemental composition of particulate matter in the South China Sea during the 2011 <i>Vasco</i> cruise

Abstract. The South China Sea (SCS) is a receptor of numerous natural and anthropogenic aerosol species from throughout greater Asia. A combination of several developing countries, archipelagic and peninsular terrain, a strong Asian monsoon climate, and a host of multi-scale meteorological phenomena make the SCS one of the most complex aerosol–meteorological systems in the world. However, aside from the well-known biomass burning emissions from Indonesia and Borneo, the current understanding of aerosol sources is limited, especially in remote marine environments. In September 2011, a 2-week research cruise was conducted near Palawan, Philippines, to sample the remote SCS environment. Size-segregated aerosol data were collected using a Davis Rotating Uniform size-cut Monitor (DRUM) sampler and analyzed for concentrations of 28 elements measured via X-ray fluorescence (XRF). Positive matrix factorization (PMF) was performed separately on the coarse, fine, and ultrafine size ranges to determine possible sources and their contributions to the total elemental particulate matter mass. The PMF analysis resolved six sources across the three size ranges: biomass burning, oil combustion, soil dust, a crustal–marine mixed source, sea spray, and fly ash. Additionally, size distribution plots, time series plots, back trajectories and satellite data were used in interpreting factors. The multi-technique source apportionment revealed the presence of biogenic sources such as soil dust, sea spray, and a crustal–marine mixed source. Anthropogenic sources were also identified: biomass burning, oil combustion, and fly ash. Mass size distributions showed elevated aerosol concentrations towards the end of the sampling period, which coincided with a shift of air mass back trajectories to southern Kalimantan. Covariance between coarse-mode soil dust and fine-mode biomass burning aerosols were observed. Agreement between the PMF and the linear regression analyses indicates that the PMF solution is robust. While biomass burning is indeed a key source of aerosol, this study shows the presence of other important sources in the SCS. Identifying these sources is not only key for characterizing the chemical profile of the SCS but, by improving our picture of aerosol sources in the region, also a step forward in developing our understanding of aerosol–meteorology feedbacks in this complex environment.

Retrospective analysis of 2015–2017 wintertime PM<sub>2.5</sub> in China: response to emission regulations and the role of meteorology

Abstract. To better characterize anthropogenic emission-relevant aerosol species, the Gridpoint Statistical Interpolation (GSI) and Weather Research and Forecasting with Chemistry (WRF/Chem) data assimilation system was updated from the GOCART aerosol scheme to the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) 4-bin (MOSAIC-4BIN) aerosol scheme. Three years (2015–2017) of wintertime (January) surface PM2.5 (fine particulate matter with an aerodynamic diameter smaller than 2.5 µm) observations from more than 1600 sites were assimilated hourly using the updated three-dimensional variational (3DVAR) system. In the control experiment (without assimilation) using Multi-resolution Emission Inventory for China 2010 (MEIC_2010) emissions, the modeled January averaged PM2.5 concentrations were severely overestimated in the Sichuan Basin, central China, the Yangtze River Delta and the Pearl River Delta by 98–134, 46–101, 32–59 and 19–60 µg m−3, respectively, indicating that the emissions for 2010 are not appropriate for 2015–2017, as strict emission control strategies were implemented in recent years. Meanwhile, underestimations of 11–12, 53–96 and 22–40 µg m−3 were observed in northeastern China, Xinjiang and the Energy Golden Triangle, respectively. The assimilation experiment significantly reduced both high and low biases to within ±5 µg m−3. The observations and the reanalysis data from the assimilation experiment were used to investigate the year-to-year changes and the driving factors. The role of emissions was obtained by subtracting the meteorological impacts (by control experiments) from the total combined differences (by assimilation experiments). The results show a reduction in PM2.5 of approximately 15 µg m−3 for the month of January from 2015 to 2016 in the North China Plain (NCP), but meteorology played the dominant role (contributing a reduction of approximately 12 µg m−3). The change (for January) from 2016 to 2017 in NCP was different; meteorology caused an increase in PM2.5 of approximately 23 µg m−3, while emission control measures caused a decrease of 8 µg m−3, and the combined effects still showed a PM2.5 increase for that region. The analysis confirmed that emission control strategies were indeed implemented and emissions were reduced in both years. Using a data assimilation approach, this study helps identify the reasons why emission control strategies may or may not have an immediately visible impact. There are still large uncertainties in this approach, especially the inaccurate emission inputs, and neglecting aerosol–meteorology feedbacks in the model can generate large uncertainties in the analysis as well.

Effects of ozone–vegetation coupling on surface ozone air quality via biogeochemical and meteorological feedbacks

Abstract. Tropospheric ozone is one of the most hazardous air pollutants as it harms both human health and plant productivity. Foliage uptake of ozone via dry deposition damages photosynthesis and causes stomatal closure. These foliage changes could lead to a cascade of biogeochemical and biogeophysical effects that not only modulate the carbon cycle, regional hydrometeorology and climate, but also cause feedbacks onto surface ozone concentration itself. In this study, we implement a semi-empirical parameterization of ozone damage on vegetation in the Community Earth System Model to enable online ozone–vegetation coupling, so that for the first time ecosystem structure and ozone concentration can coevolve in fully coupled land–atmosphere simulations. With ozone–vegetation coupling, present-day surface ozone is simulated to be higher by up to 4–6 ppbv over Europe, North America and China. Reduced dry deposition velocity following ozone damage contributes to ∼ 40–100 % of those increases, constituting a significant positive biogeochemical feedback on ozone air quality. Enhanced biogenic isoprene emission is found to contribute to most of the remaining increases, and is driven mainly by higher vegetation temperature that results from lower transpiration rate. This isoprene-driven pathway represents an indirect, positive meteorological feedback. The reduction in both dry deposition and transpiration is mostly associated with reduced stomatal conductance following ozone damage, whereas the modification of photosynthesis and further changes in ecosystem productivity are found to play a smaller role in contributing to the ozone–vegetation feedbacks. Our results highlight the need to consider two-way ozone–vegetation coupling in Earth system models to derive a more complete understanding and yield more reliable future predictions of ozone air quality.

Application of WRF/Chem over North America under the AQMEII Phase 2 – Part 2: Evaluation of 2010 application and responses of air quality and meteorology–chemistry interactions to changes in emissions and meteorology from 2006 to 2010

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) simulation with the 2005 Carbon Bond (CB05) gas-phase mechanism coupled to the Modal for Aerosol Dynamics for Europe (MADE) and the volatility basis set approach for secondary organic aerosol (SOA) are conducted over a domain in North America for 2006 and 2010 as part of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 project. Following the Part 1 paper that focuses on the evaluation of the 2006 simulations, this Part 2 paper focuses on a comparison of model performance in 2006 and 2010 as well as analysis of the responses of air quality and meteorology–chemistry interactions to changes in emissions and meteorology from 2006 to 2010. In general, emissions for gaseous and aerosol species decrease from 2006 to 2010, leading to a reduction in gaseous and aerosol concentrations and associated changes in radiation and cloud variables due to various feedback mechanisms. WRF/Chem is able to reproduce most observations and the observed variation trends from 2006 to 2010, despite its slightly worse performance than WRF that is likely due to inaccurate chemistry feedbacks resulting from less accurate emissions and chemical boundary conditions (BCONs) in 2010. Compared to 2006, the performance for most meteorological variables in 2010 gives lower normalized mean biases but higher normalized mean errors and lower correlation coefficients. The model also shows poorer performance for most chemical variables in 2010. This could be attributed to underestimations in emissions of some species, such as primary organic aerosol in some areas of the US in 2010, and inaccurate chemical BCONs and meteorological predictions. The inclusion of chemical feedbacks in WRF/Chem reduces biases in meteorological predictions in 2010; however, it increases errors and weakens correlations comparing to WRF simulations. Sensitivity simulations show that the net changes in meteorological variables from 2006 to 2010 are mostly influenced by changes in meteorology and those of ozone and fine particulate matter are influenced to a large extent by emissions and/or chemical BCONs and to a lesser extent by changes in meteorology. Using a different set of emissions and/or chemical BCONs helps improve the performance of individual variables, although it does not improve the degree of agreement with observed interannual trends. These results indicate a need to further improve the accuracy and consistency of emissions and chemical BCONs, the representations of SOA and chemistry–meteorology feedbacks in the online-coupled models.

Investigating impacts of forest fires in Alaska and western Canada on regional weather over the northeastern United States using CAM5 global simulations to constrain transport to a WRF-Chem regional domain

An aerosol-enabled globally driven regional modeling system has been developed by coupling the National Center for Atmospheric Research's Community Atmosphere Model version 5 (CAM5) with the Weather Research and Forecasting model with chemistry (WRF-Chem). In this modeling system, aerosol-enabled CAM5, a state-of-the-art global climate model is downscaled to provide coherent meteorological and chemical boundary conditions for regional WRF-Chem simulations. Aerosol particle emissions originating outside the WRF-Chem domain can be a potentially important nonlocal aerosol source. As a test case, the potential impacts of nonlocal forest fire aerosols on regional precipitation and radiation were investigated over the northeastern United States during the summer of 2004. During this period, forest fires in Alaska and western Canada lofted aerosol particles into the midtroposphere, which were advected across the United States. WRF-Chem simulations that included nonlocal biomass burning aerosols had domain-mean aerosol optical depths that were nearly three times higher than those without, which reduced peak downwelling domain-mean shortwave radiation at the surface by ~25 W m-2. In this classic twin experiment design, adding nonlocal fire plume led to near-surface cooling and changes in cloud vertical distribution, while variations in domain-mean cloud liquid water path were negligible. The higher aerosol concentrations in the simulation with the fire plume resulted in a ~10% reduction in domain-mean precipitation coincident with an ~8% decrease in domain-mean CAPE. A suite of simulations was also conducted to explore sensitivities of meteorological feedbacks to the ratio of black carbon to total plume aerosols, as well as to overall plume concentrations. Results from this ensemble revealed that plume-induced near-surface cooling and CAPE reduction occur in a wide range of conditions. The response of moist convection was very complex because of strong thermodynamic internal variability. Key Points Nonlocal fire emissions resulted in ~10% precipitation reduction Nonlocal fire emissions reduced peak surface shortwave radiation at by 25 W m-2 An aerosol-enabled globally driven regional modeling system is developed ©2014. American Geophysical Union. All Rights Reserved.

Projections of future summertime ozone over the U.S.

AbstractWe use a regional coupled chemistry‐transport model to assess changes in surface ozone over the summertime U.S. between present and a 2050 future time period at high spatial resolution under the A2 climate and Representative Concentration Pathway (RCP) 8.5 anthropogenic precursor emission scenarios. Predicted changes in regional climate and globally enhanced ozone are estimated to increase surface ozone over most of the U.S.; the 95th percentile for daily 8 h maximum surface ozone increases from 79 ppb to 87 ppb. The analysis suggests that changes in meteorological drivers likely will add to increasing ozone, but the simulations do not allow separating meteorological feedbacks from that due to enhanced global ozone. Stringent emission controls can counteract these feedbacks; if implemented as in RCP8.5, the 95th percentile for surface ozone is reduced to 55 ppb. A comparison of regional to global model projections shows that the global model is biased high in surface ozone compared to the regional model and compared to observations. On average, both the global and the regional model predict similar future changes but reveal pronounced differences in urban and rural regimes that cannot be resolved at the coarse resolution of the considered global model. This study confirms the key role of emission control strategies in future air quality projections and demonstrates the need for considering degradation of air quality with future climate change in policy making. It also illustrates the need for high‐resolution modeling when the objective is to address regional and local air quality or establish links to human health and society.

Development of a source oriented version of the WRF/Chem model and its application to the California regional PM<sub>10</sub> / PM<sub>2.5</sub> air quality study

Abstract. A source-oriented version of the Weather Research and Forecasting model with chemistry (SOWC, hereinafter) was developed. SOWC separately tracks primary particles with different hygroscopic properties rather than instantaneously combining them into an internal mixture. This approach avoids artificially mixing light absorbing black + brown carbon particles with materials such as sulfate that would encourage the formation of additional coatings. Source-oriented particles undergo coagulation and gas-particle conversion, but these processes are considered in a dynamic framework that realistically "ages" primary particles over hours and days in the atmosphere. SOWC more realistically predicts radiative feedbacks from anthropogenic aerosols compared to models that make internal mixing or other artificial mixing assumptions. A three-week stagnation episode (15 December 2000 to 6 January 2001) in the San Joaquin Valley (SJV) during the California Regional PM10 / PM2.5 Air Quality Study (CRPAQS) was chosen for the initial application of the new modeling system. Primary particles emitted from diesel engines, wood smoke, high-sulfur fuel combustion, food cooking, and other anthropogenic sources were tracked separately throughout the simulation as they aged in the atmosphere. Differences were identified between predictions from the source oriented vs. the internally mixed representation of particles with meteorological feedbacks in WRF/Chem for a number of meteorological parameters: aerosol extinction coefficients, downward shortwave flux, planetary boundary layer depth, and primary and secondary particulate matter concentrations. Comparisons with observations show that SOWC predicts particle scattering coefficients more accurately than the internally mixed model. Downward shortwave radiation predicted by SOWC is enhanced by ~1% at ground level chiefly because diesel engine particles in the source-oriented mixture are not artificially coated with material that increases their absorption efficiency. The extinction coefficient predicted by SOWC is reduced by an average of 0.012 km−1 (4.8%) in the SJV with a maximum reduction of ~0.2 km−1. Planetary boundary layer (PBL) height is increased by an average of 5.2 m (1.5%) with a~maximum of ~100 m in the SJV. Particulate matter concentrations predicted by SOWC are 2.23 μg m−3 (3.8%) lower than the average by the internally mixed version of the same model in the SJV because increased solar radiation at the ground increases atmospheric mixing. The changes in predicted meteorological parameters and particle concentrations identified in the current study stem from the mixing state of black carbon. The source-oriented model representation with realistic aging processes predicts that hydrophobic diesel engine particles remain largely uncoated over the +7 day simulation period, while the internal mixture model representation predicts significant accumulation of secondary nitrate and water on diesel engine particles. Similar results will likely be found in any air pollution stagnation episode that is characterized by significant particulate nitrate production. Future work should consider episodes where coatings are predominantly sulfate and/or secondary organic aerosol.