Photochemical model assessment of single source NO2 and O3 plumes using field study data.

Single source contribution to ambient O3 and PM2.5 has been estimated with photochemical grid models to support policy demonstrations for National Ambient Air Quality Standards, regional haze, and permit related programs. Limited field data exists to evaluate model representation of the spatial extent and chemical composition of plumes emitted by specific facilities. New tropospheric column measurements of NO2 and in-plume chemical measurements downwind of specific facilities allows for photochemical model evaluation of downwind plume extent, grid resolution impacts on plume concentration gradients, and source attribution methods. Here, photochemical models were applied with source sensitivity and source apportionment approaches to differentiate single source impacts on NO2 and O3 and compare with field study measurements. Source sensitivity approaches (e.g., brute-force difference method and decoupled direct method (DDM)) captured the spatial extent of NO2 plumes downwind of three facilities and the transition of near-source O3 titration to downwind production. Source apportionment approaches showed variability in terms of attributing the spatial extent of NO2 plumes and downwind O3 production. Each of the Community Multiscale Air Quality (CMAQ) source apportionment options predicted large O3 contribution from a large industrial facility in the flight transects nearest the facility when measurements and source sensitivity approaches suggest titration was outpacing production. In general, CMAQ DDM tends to attribute more O3 to boundary inflow and less to within-domain NOX and VOC sources compared to CMAQ source apportionment. The photochemical modeling system was able to capture single source plumes using 1 to 12 km grid resolution with best representation of plume extent and magnitude at the finer resolutions. When modeled at 1 to 12 km grid resolution, primary and secondary PM2.5 impacts were highest at the source location and decrease as distance increases downwind. The use of coarser grid resolution for single source attribution resulted in predicted impacts highest near the source but lower peak source specific concentrations compared to finer grid resolution simulations because impacts were spread out over a larger area.

Summertime tropospheric ozone source apportionment study in the Madrid region (Spain).

The design of emission abatement measures to effectively reduce high ground-level ozone (O3) concentrations in urban areas is very complex. In addition to the strongly non-linear chemistry of this secondary pollutant, precursors can be released by a variety of sources in different regions, and locally produced O3 is mixed with that transported from the regional or continental scales. All of these processes depend also on the specific meteorological conditions and topography of the study area. Consequently, high-resolution comprehensive modeling tools are needed to understand the drivers of photochemical pollution and to assess the potential of local strategies to reduce adverse impacts from high tropospheric O3 levels. In this study, we apply the Integrated Source Apportionment Method (ISAM) implemented in the Community Multiscale Air Quality (CMAQ v5.3.2) model to investigate the origin of summertime O3 in the Madrid region (Spain). Consistent with previous studies, our results confirm that O3 levels are dominated by non-local contributions, representing around 70 % of mean values across the region. Nonetheless, precursors emitted by local sources, mainly road traffic, play a more important role during O3 peaks, with contributions as high as 25 ppb. The potential impact of local measures is higher under unfavorable meteorological conditions associated with regional accumulation patterns. These findings suggest that this modeling system may be used in the future to simulate the potential outcomes of specific emission abatement measures to prevent high-O3 episodes in the Madrid metropolitan area.

How have Divergent Global Emission Trends Influenced Long-range Transported Ozone to North America?

Several locations across the United States in non-compliance with the national standard for ground-level ozone (O3) are thought to have sizeable influences from distant extra-regional emission sources or natural stratospheric O3, which complicates design of local emission control measures. To quantify the amount of long-range transported O3 (LRT O3), its origin, and change over time, we conduct and analyze detailed sensitivity calculations characterizing the response of O3 to emissions from different source regions across the Northern Hemisphere in conjunction with multi-decadal simulations of tropospheric O3 distributions and changes. Model calculations show that the amount of O3 at any location attributable to sources outside North America varies both spatially and seasonally. On a seasonal-mean basis, during 1990-2010, LRT O3 attributable to international sources steadily increased by 0.06-0.2 ppb yr-1 at locations across the United States and arose from superposition of unequal and contrasting trends in individual source-region contributions, which help inform attribution of the trend evident in O3 measurements. Contributions of emissions from Europe steadily declined through 2010, while those from Asian emissions increased and remained dominant. Steadily rising NOx emissions from international shipping resulted in increasing contributions to LRT O3, comparable to those from Asian emissions in recent years. Central American emissions contribute a significant fraction of LRT O3 in southwestern United States. In addition to the LRT O3 attributable to emissions outside of North America, background O3 across the continental United States is comprised of a sizeable and spatially variable fraction that is of stratospheric origin (29-78%).

The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation.

The Community Multiscale Air Quality (CMAQ) model version 5.3 (CMAQ53), released to the public in August 2019 and followed by version 5.3.1 (CMAQ531) in December 2019, contains numerous science updates, enhanced functionality, and improved computation efficiency relative to the previous version of the model, 5.2.1 (CMAQ521). Major science advances in the new model include a new aerosol module (AERO7) with significant updates to secondary organic aerosol (SOA) chemistry, updated chlorine chemistry, updated detailed bromine and iodine chemistry, updated simple halogen chemistry, the addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism, updated M3Dry bidirectional deposition model, and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model's hybrid vertical coordinate (HVC) was added to CMAQ53 and the Meteorology-Chemistry Interface Processor (MCIP) version 5.0 (MCIP50). Enhanced functionality in CMAQ53 includes the new Detailed Emissions Scaling, Isolation and Diagnostic (DESID) system for scaling incoming emissions to CMAQ and reading multiple gridded input emission files. Evaluation of CMAQ531 was performed by comparing monthly and seasonal mean daily 8 h average (MDA8) O3 and daily PM2.5 values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O3, CMAQ531 has higher O3 in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O3 bias (2-4 ppbv monthly average). MDA8 O3 is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O3 from the lateral boundary conditions (BCs), which generally increases MDA8 O3 bias in spring and fall ( 0.5 µg m-3). For daily 24 h average PM2.5, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter to CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons were also performed to isolate updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used. Transitioning from a hemispheric CMAQ (HCMAQ) version 5.2.1 simulation to a HCMAQ version 5.3 simulation to provide lateral BCs contributes to higher O3 mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O3 dry deposition to snow in CMAQ53) and lower O3 mixing ratios in middle and lower latitudes year-round (due to reduced O3 over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC resulted in consistently higher (1.0-1.5 ppbv) MDA8 O3 mixing ratios and higher PM2.5 concentrations (0.1-0.25 µg m-3) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O3 is generally higher with M3Dry outside of summer, while PM2.5 is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to non-vegetated surfaces and land use with short vegetation (e.g., grasslands) between the two models. For ambient NH3, STAGE has slightly higher concentrations and smaller bias in the winter, spring, and fall, while M3Dry has higher concentrations and smaller bias but larger error and lower correlation in the summer.

The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) modeling system version 5.3.2.

Air quality modeling for research and regulatory applications often involves executing many emissions sensitivity cases to quantify impacts of hypothetical scenarios, estimate source contributions, or quantify uncertainties. Despite the prevalence of this task, conventional approaches for perturbing emissions in chemical transport models like the Community Multiscale Air Quality (CMAQ) model require extensive offline creation and finalization of alternative emissions input files. This workflow is often time-consuming, error-prone, inconsistent among model users, difficult to document, and dependent on increased hard disk resources. The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module, a component of CMAQv5.3 and beyond, addresses these limitations by performing these modifications online during the air quality simulation. Further, the model contains an Emission Control Interface which allows users to prescribe both simple and highly complex emissions scaling operations with control over individual or multiple chemical species, emissions sources, and spatial areas of interest. DESID further enhances the transparency of its operations with extensive error-checking and optional gridded output of processed emission fields. These new features are of high value to many air quality applications including routine perturbation studies, atmospheric chemistry research, and coupling with external models (e.g., energy system models, reduced-form models).

Incorporation of volcanic SO2 emissions in the Hemispheric CMAQ (H-CMAQ) version 5.2 modeling system and assessing their impacts on sulfate aerosol over the Northern Hemisphere.

The state-of-the-science Community Multiscale Air Quality (CMAQ) Modeling System has recently been extended for hemispheric-scale modeling applications (referred to as H-CMAQ). In this study, satellite-constrained estimation of the degassing SO2 emissions from 50 volcanoes over the Northern Hemisphere is incorporated into H-CMAQ, and their impact on tropospheric sulfate aerosol ( SO 4 2 - ) levels is assessed for 2010. The volcanic degassing improves predictions of observations from the Acid Deposition Monitoring Network in East Asia (EANET), the United States Clean Air Status and Trends Network (CASTNET), and the United States Integrated Monitoring of Protected Visual Environments (IMPROVE). Over Asia, the increased SO 4 2 - concentrations were seen to correspond to the locations of volcanoes, especially over Japan and Indonesia. Over the USA, the largest impacts that occurred over the central Pacific were caused by including the Hawaiian Kilauea volcano, while the impacts on the continental USA were limited to the western portion during summertime. The emissions of the Soufrière Hills volcano located on the island of Montserrat in the Caribbean Sea affected the southeastern USA during the winter season. The analysis at specific sites in Hawaii and Florida also confirmed improvements in regional performance for modeled SO 4 2 - by including volcanoes SO2 emissions. At the edge of the western USA, monthly averaged SO 4 2 - enhancements greater than 0.1µgm-3 were noted within the boundary layer (defined as surface to 750hPa) during June- September. Investigating the change on SO 4 2 - concentration throughout the free troposphere revealed that although the considered volcanic SO2 emissions occurred at or below the middle of free troposphere (500hPa), compared to the simulation without the volcanic source, SO 4 2 - enhancements of more than 10% were detected up to the top of the free troposphere (250hPa). Our model simulations and comparisons with measurements across the Northern Hemisphere indicate that the degassing volcanic SO2 emissions are an important source and should be considered in air quality model simulations assessing background SO 4 2 - levels and their source attribution.

A multiphase CMAQ version 5.0 adjoint.

We present the development of a multiphase adjoint for the Community Multiscale Air Quality (CMAQ) model, a widely used chemical transport model. The adjoint model provides location- and time-specific gradients that can be used in various applications such as backward sensitivity analysis, source attribution, optimal pollution control, data assimilation, and inverse modeling. The science processes of the CMAQ model include gas-phase chemistry, aerosol dynamics and thermodynamics, cloud chemistry and dynamics, diffusion, and advection. Discrete adjoints are implemented for all the science processes, with an additional continuous adjoint for advection. The development of discrete adjoints is assisted with algorithmic differentiation (AD) tools. Particularly, the Kinetic PreProcessor (KPP) is implemented for gas-phase and aqueous chemistry, and two different automatic differentiation tools are used for other processes such as clouds, aerosols, diffusion, and advection. The continuous adjoint of advection is developed manually. For adjoint validation, the brute-force or finite-difference method (FDM) is implemented process by process with box- or column-model simulations. Due to the inherent limitations of the FDM caused by numerical round-off errors, the complex variable method (CVM) is adopted where necessary. The adjoint model often shows better agreement with the CVM than with the FDM. The adjoints of all science processes compare favorably with the FDM and CVM. In an example application of the full multiphase adjoint model, we provide the first estimates of how emissions of particulate matter (PM2.5) affect public health across the US.

Modeling stratospheric intrusion and trans-Pacific transport on tropospheric ozone using hemispheric CMAQ during April 2010 - Part 2: Examination of emission impacts based on the higher-order decoupled direct method.

The state-of-the-science Community Multiscale Air Quality (CMAQ) modeling system, which has recently been extended for hemispheric-scale modeling applications (referred to as H-CMAQ), is applied to study the trans-Pacific transport, a phenomenon recognized as a potential source of air pollution in the US, during April 2010. The results of this analysis are presented in two parts. In the previous paper (Part 1), model evaluation for tropospheric ozone (O3) was presented and an air mass characterization method was developed. Results from applying this newly established method pointed to the importance of emissions as the factor to enhance the surface O3 mixing ratio over the US. In this subsequent paper (Part 2), emission impacts are examined based on mathematically rigorous sensitivity analysis using the higher-order decoupled direct method (HDDM) implemented in H-CMAQ. The HDDM sensitivity coefficients indicate the presence of a NO x -sensitive regime during April 2010 over most of the Northern Hemisphere. By defining emission source regions over the US and east Asia, impacts from these emission sources are examined. At the surface, during April 2010, the emission impacts of the US and east Asia are comparable over the western US with a magnitude of about 3ppbv impacts on monthly mean O3 all-hour basis, whereas the impact of domestic emissions dominates over the eastern US with a magnitude of about 10ppbv impacts on monthly mean O3. The positive correlation (r = 0.63) between surface O3 mixing ratios and domestic emission impacts is confirmed. In contrast, the relationship between surface O3 mixing ratios and emission impacts from east Asia exhibits a flat slope when considering the entire US. However, this relationship has strong regional differences between the western and eastern US; the western region exhibits a positive correlation (r = 0.36-0.38), whereas the latter exhibits a flat slope (r <0.1). Based on the comprehensive evaluation of H-CMAQ, we extend the sensitivity analysis for O3 aloft. The results reveal the significant impacts of emissions from east Asia on the free troposphere (defined as 750 to 250hPa) over the US (impacts of more than 5ppbv) and the dominance of stratospheric air mass on upper model layer (defined as 250 to 50hPa) over the US (impacts greater than 10ppbv). Finally, we estimate changes of trans-Pacific transport by taking into account recent emission trends from 2010 to 2015 assuming the same meteorological condition. The analysis suggests that the impact of recent emission changes on changes in the contribution of trans-Pacific transport to US O3 levels was insignificant at the surface level and was small (less than 1ppbv) over the free troposphere.

Ozone source apportionment during peak summer events over southwestern Europe.

It is well established that in Europe, high O3 concentrations are most pronounced in southern/Mediterranean countries due to the more favourable climatological conditions for its formation. However, the contribution of the different sources of precursors to O3 formation within each country relative to the imported (regional and hemispheric) O3 is poorly quantified. This lack of quantitative knowledge prevents local authorities from effectively designing plans that reduce the exceedances of the O3 target value set by the European air quality directive. O3 source attribution is a challenge because the concentration at each location and time results not only from local biogenic and anthropogenic precursors, but also from the transport of O3 and precursors from neighbouring regions, O3 regional and hemispheric transport and stratospheric O3 injections. The main goal of this study is to provide a first quantitative estimation of the contribution of the main anthropogenic activity sectors to peak O3 events in Spain relative to the contribution of imported (regional and hemispheric) O3. We also assess the potential of our source apportionment method to improve O3 modelling. Our study applies and thoroughly evaluates a countrywide O3 source apportionment method implemented in the CALIOPE air quality forecast system for Spain at high resolution (4 × 4 km2) over a 10-day period characterized by typical summer conditions in the Iberian Peninsula (IP). The method tags both O3 and its gas precursor emissions from source sectors within one simulation, and each tagged species is subject to the typical physico-chemical processes (advection, vertical mixing, deposition, emission and chemistry) as the actual conditions remain unperturbed. We quantify the individual contributions of the largest NO x local sources to high O3 concentrations compared with the contribution of imported O3. We show, for the first time, that imported O3 is the largest input to the ground-level O3 concentration in the IP, accounting for 46 %-68 % of the daily mean O3 concentration during exceedances of the European target value. The hourly imported O3 increases during typical northwestern advections (70 %-90 %, 60-80 µg m-3), and decreases during typical stagnant conditions (30 %-40 %, 30-60 µg m-3) due to the local NO titration. During stagnant conditions, the local anthropogenic precursors control the O3 peaks in areas downwind of the main urban and industrial regions (up to 40 % in hourly peaks). We also show that ground-level O3 concentrations are strongly affected by vertical mixing of O3-rich layers present in the free troposphere, which result from local/regional layering and accumulation, and continental/hemispheric transport. Indeed, vertical mixing largely explains the presence of imported O3 at ground level in the IP. Our results demonstrate the need for detailed quantification of the local and remote contributions to high O3 concentrations for local O3 management, and show O3 source apportionment to be an essential analysis prior to the design of O3 mitigation plans in any non-attainment area. Achieving the European O3 objectives in southern Europe requires not only ad hoc local actions but also decided national and European-wide strategies.

The impact of air pollutant deposition on solar energy system efficiency: An approach to estimate PV soiling effects with the Community Multiscale Air Quality (CMAQ) model.

Deposition and accumulation of aerosol particles on photovoltaics (PV) panels, which is commonly referred to as "soiling of PV panels," impacts the performance of the PV energy system. It is desirable to estimate the soiling effect at different locations and times for modeling the PV system performance and devising cost-effective mitigation. This study presents an approach to estimate the soiling effect by utilizing particulate matter (PM) dry deposition estimates from air quality model simulations. The Community Multiscale Air Quality (CMAQ) modeling system used in this study was developed by the U.S. Environmental Protection Agency (U.S. EPA) for air quality assessments, rule-making, and research. Three deposition estimates based on different surface roughness length parameters assumed in CMAQ were used to illustrate the soling effect in different land-use types. The results were analyzed for three locations in the U.S. for year 2011. One urban and one suburban location in Colorado were selected because there have been field measurements of particle deposition on solar panels and analysis on the consequent soiling effect performed at these locations. The third location is a coastal city in Texas, the City of Brownsville. These three locations have distinct ambient environments. CMAQ underestimates particle deposition by 40% to 80% when compared to the field measurements at the two sites in Colorado due to the underestimations in both the ambient PM10 concentration and deposition velocity. The estimated panel transmittance sensitivity due to the deposited particles is higher than the sensitivity obtained from the measurements in Colorado. The final soiling effect, which is transmittance loss, is estimated as 3.17 ±â€¯4.20% for the Texas site, 0.45 ±â€¯0.33%, and 0.31 ±â€¯0.25% for the Colorado sites. Although the numbers are lower compared to the measurements in Colorado, the results are comparable with the soiling effects observed in U.S.

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport.

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment in the Pacific Northwest focused on cropland residue burning was used to evaluate model performance in capturing surface and aloft impacts from the burning events. The Community Multiscale Air Quality (CMAQ) model was used to simulate multiple crop residue burns with 2 km grid spacing using field-specific information and also more general assumptions traditionally used to support National Emission Inventory based assessments. Field study specific information, which includes area burned, fuel consumption, and combustion completeness, resulted in increased biomass consumption by 123 tons (60% increase) on average compared to consumption estimated with default methods in the National Emission Inventory (NEI) process. Buoyancy heat flux, a key parameter for model predicted fire plume rise, estimated from fuel loading obtained from field measurements can be 30% to 200% more than when estimated using default field information. The increased buoyancy heat flux resulted in higher plume rise by 30% to 80%. This evaluation indicates that the regulatory air quality modeling system can replicate intensity and transport (horizontal and vertical) features for crop residue burning in this region when region-specific information is used to inform emissions and plume rise calculations. Further, previous vertical emissions allocation treatment of putting all cropland residue burning in the surface layer does not compare well with measured plume structure and these types of burns should be modeled more similarly to prescribed fires such that plume rise is based on an estimate of buoyancy.

Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin.

The Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models were used to simulate a 10 day high-ozone episode observed during the 2013 Uinta Basin Winter Ozone Study (UBWOS). The baseline model had a large negative bias when compared to ozone (O3) and volatile organic compound (VOC) measurements across the basin. Contrary to other wintertime Uinta Basin studies, predicted nitrogen oxides (NO x ) were typically low compared to measurements. Increases to oil and gas VOC emissions resulted in O3 predictions closer to observations, and nighttime O3 improved when reducing the deposition velocity for all chemical species. Vertical structures of these pollutants were similar to observations on multiple days. However, the predicted surface layer VOC mixing ratios were generally found to be underestimated during the day and overestimated at night. While temperature profiles compared well to observations, WRF was found to have a warm temperature bias and too low nighttime mixing heights. Analyses of more realistic snow heat capacity in WRF to account for the warm bias and vertical mixing resulted in improved temperature profiles, although the improved temperature profiles seldom resulted in improved O3 profiles. While additional work is needed to investigate meteorological impacts, results suggest that the uncertainty in the oil and gas emissions contributes more to the underestimation of O3. Further, model adjustments based on a single site may not be suitable across all sites within the basin.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1.

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM2.5 bias (PM2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O3 and PM2.5 on average in January and July. Overall, the seasonal variation in simulated PM2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM2.5 concentrations decrease in the winter (when PM2.5 is generally overestimated by CMAQ) and increase in the summer (when PM2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O3 mean bias, as O3 tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O3 is low); however, O3 correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO x (NO + NO2), VOC and SO x (SO2 + SO4) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O3 due to large, widespread reductions in observed emissions.

Differences between magnitudes and health impacts of BC emissions across the United States using 12 km scale seasonal source apportionment.

Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, which provides source-receptor relationships at highly resolved sectoral, spatial, and temporal scales. While damage resulting from anthropogenic emissions of BC is strongly correlated with population and premature death, we found little correlation between damage and emission magnitude, suggesting that controls on the largest emissions may not be the most efficient means of reducing damage resulting from anthropogenic BC emissions. Rather, the best proxy for locations with damaging BC emissions is locations where premature deaths occur. Onroad diesel and nonroad vehicle emissions are the largest contributors to premature deaths attributed to exposure to BC, while onroad gasoline emissions cause the highest deaths per amount emitted. Emissions in fall and winter contribute to more premature deaths (and more per amount emitted) than emissions in spring and summer. Overall, these results show the value of the high-resolution source attribution for determining the locations, seasons, and sectors for which BC emission controls have the most effective health benefits.

Diagnostic air quality model evaluation of source-specific primary and secondary fine particulate carbon.

Ambient measurements of 78 source-specific tracers of primary and secondary carbonaceous fine particulate matter collected at four midwestern United States locations over a full year (March 2004-February 2005) provided an unprecedented opportunity to diagnostically evaluate the results of a numerical air quality model. Previous analyses of these measurements demonstrated excellent mass closure for the variety of contributing sources. In this study, a carbon-apportionment version of the Community Multiscale Air Quality (CMAQ) model was used to track primary organic and elemental carbon emissions from 15 independent sources such as mobile sources and biomass burning in addition to four precursor-specific classes of secondary organic aerosol (SOA) originating from isoprene, terpenes, aromatics, and sesquiterpenes. Conversion of the source-resolved model output into organic tracer concentrations yielded a total of 2416 data pairs for comparison with observations. While emission source contributions to the total model bias varied by season and measurement location, the largest absolute bias of -0.55 µgC/m(3) was attributed to insufficient isoprene SOA in the summertime CMAQ simulation. Biomass combustion was responsible for the second largest summertime model bias (-0.46 µgC/m(3) on average). Several instances of compensating errors were also evident; model underpredictions in some sectors were masked by overpredictions in others.

A direct sensitivity approach to predict hourly ozone resulting from compliance with the National Ambient Air Quality Standard.

In setting primary ambient air quality standards, the EPA's responsibility under the law is to establish standards that protect public health. As part of the current review of the ozone National Ambient Air Quality Standard (NAAQS), the US EPA evaluated the health exposure and risks associated with ambient ozone pollution using a statistical approach to adjust recent air quality to simulate just meeting the current standard level, without specifying emission control strategies. One drawback of this purely statistical concentration rollback approach is that it does not take into account spatial and temporal heterogeneity of ozone response to emissions changes. The application of the higher-order decoupled direct method (HDDM) in the community multiscale air quality (CMAQ) model is discussed here to provide an example of a methodology that could incorporate this variability into the risk assessment analyses. Because this approach includes a full representation of the chemical production and physical transport of ozone in the atmosphere, it does not require assumed background concentrations, which have been applied to constrain estimates from past statistical techniques. The CMAQ-HDDM adjustment approach is extended to measured ozone concentrations by determining typical sensitivities at each monitor location and hour of the day based on a linear relationship between first-order sensitivities and hourly ozone values. This approach is demonstrated by modeling ozone responses for monitor locations in Detroit and Charlotte to domain-wide reductions in anthropogenic NOx and VOCs emissions. As seen in previous studies, ozone response calculated using HDDM compared well to brute-force emissions changes up to approximately a 50% reduction in emissions. A new stepwise approach is developed here to apply this method to emissions reductions beyond 50% allowing for the simulation of more stringent reductions in ozone concentrations. Compared to previous rollback methods, this application of modeled sensitivities to ambient ozone concentrations provides a more realistic spatial response of ozone concentrations at monitors inside and outside the urban core and at hours of both high and low ozone concentrations.

Extreme value analysis for evaluating ozone control strategies.

Tropospheric ozone is one of six criteria pollutants regulated by the US EPA, and has been linked to respiratory and cardiovascular endpoints and adverse effects on vegetation and ecosystems. Regional photochemical models have been developed to study the impacts of emission reductions on ozone levels. The standard approach is to run the deterministic model under new emission levels and attribute the change in ozone concentration to the emission control strategy. However, running the deterministic model requires substantial computing time, and this approach does not provide a measure of uncertainty for the change in ozone levels. Recently, a reduced form model (RFM) has been proposed to approximate the complex model as a simple function of a few relevant inputs. In this paper, we develop a new statistical approach to make full use of the RFM to study the effects of various control strategies on the probability and magnitude of extreme ozone events. We fuse the model output with monitoring data to calibrate the RFM by modeling the conditional distribution of monitoring data given the RFM using a combination of flexible semiparametric quantile regression for the center of the distribution where data are abundant and a parametric extreme value distribution for the tail where data are sparse. Selected parameters in the conditional distribution are allowed to vary by the RFM value and the spatial location. Also, due to the simplicity of the RFM, we are able to embed the RFM in our Bayesian hierarchical framework to obtain a full posterior for the model input parameters, and propagate this uncertainty to the estimation of the effects of the control strategies. We use the new framework to evaluate three potential control strategies, and find that reducing mobile-source emissions has a larger impact than reducing point-source emissions or a combination of several emission sources.

Bayesian analysis of a reduced-form air quality model.

Numerical air quality models are being used for assessing emission control strategies for improving ambient pollution levels across the globe. This paper applies probabilistic modeling to evaluate the effectiveness of emission reduction scenarios aimed at lowering ground-level ozone concentrations. A Bayesian hierarchical model is used to combine air quality model output and monitoring data in order to characterize the impact of emissions reductions while accounting for different degrees of uncertainty in the modeled emissions inputs. The probabilistic model predictions are weighted based on population density in order to better quantify the societal benefits/disbenefits of four hypothetical emission reduction scenarios in which domain-wide NO(x) emissions from various sectors are reduced individually and then simultaneously. Cross validation analysis shows the statistical model performs well compared to observed ozone levels. Accounting for the variability and uncertainty in the emissions and atmospheric systems being modeled is shown to impact how emission reduction scenarios would be ranked, compared to standard methodology.

Model representation of secondary organic aerosol in CMAQv4.7.

Numerous scientific upgrades to the representation of secondary organic aerosol (SOA) are incorporated into the Community Multiscale Air Quality (CMAQ) modeling system. Additions include several recently identified SOA precursors: benzene, isoprene, and sesquiterpenes; and pathways: in-cloud oxidation of glyoxal and methylglyoxal, particle-phase oligomerization, and acid enhancement of isoprene SOA. NO(x)-dependent aromatic SOA yields are also added along with new empirical measurements of the enthalpies of vaporization and organic mass-to-carbon ratios. For the first time, these SOA precursors, pathways and empirical parameters are included simultaneously in an air quality model for an annual simulation spanning the continental U.S. Comparisons of CMAQ-modeled secondary organic carbon (OC(sec)) with semiempirical estimates screened from 165 routine monitoring sites across the U.S. indicate the new SOA module substantially improves model performance. The most notable improvement occurs in the central and southeastern U.S. where the regionally averaged temporal correlations (r) between modeled and semiempirical OC(sec) increase from 0.5 to 0.8 and 0.3 to 0.8, respectively, when the new SOA module is employed. Wintertime OC(sec) results improve in all regions of the continental U.S. and the seasonal and regional patterns of biogenic SOA are better represented.

Uncertainty analysis of ozone formation and response to emission controls using higher-order sensitivities.

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this study, a high ozone episode in the southeastern United States is simulated using the Community Multiscale Air Quality (CMAQ) model. Uncertainties in ozone formation and response to emissions controls due to uncertainties in emission rates are quantified using the Monte Carlo method. Instead of propagating emissions uncertainties through the original CMAQ a reduced form of CMAQ is formulated using directly calculated first- and second-order sensitivities that capture the nonlinear ozone concentration-emission responses. This modification greatly reduces the associated computational cost. Quantified uncertainties in modeled ozone concentrations and responses to various emissions controls are much less than the uncertainties in emissions inputs. Average uncertainties in modeled ozone concentrations for the Atlanta area are less than 10% (as measured by the inferred coefficient of variance [ICOV]) even when emissions uncertainties are assumed to vary between a factor of 1.5 and 2. Uncertainties in the ozone responses generally decrease with increased emission controls. Average uncertainties (ICOV) in emission-normalized ozone responses range from 4 to 22%, with the smaller being associated with controlling of the relatively certain point nitrogen oxide (NOx) emissions and the larger resulting from controlling of the less certain mobile NOx emissions. These small uncertainties provide confidence in the model applications, such as in performance evaluation, attainment demonstration, and control strategy development.