scholarly journals Modelling winter organic aerosol at the European scale with CAMx: evaluation and source apportionment with a VBS parameterization based on novel wood burning smog chamber experiments og

2016 ◽  
Author(s):  
Giancarlo Ciarelli ◽  
Sebnem Aksoyoglu ◽  
Imad El Haddad ◽  
Emily A. Bruns ◽  
Monica Crippa ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Basis Set ◽  
Formation Mechanisms ◽  
Smog Chamber ◽  
Air Quality Model ◽  
Quality Model ◽  
Residential Combustion ◽  
Wood Burning

Abstract. We evaluated a modified VBS (Volatility Basis Set) scheme to treat biomass burning-like organic aerosol (BBOA) implemented in CAMx (Comprehensive Air Quality Model with extensions). The updated scheme was parameterized with novel wood combustion smog chamber experiments using a hybrid VBS framework that accounts for a mixture of wood burning organic aerosol precursors and their further functionalization and fragmentation in the atmosphere. The new scheme was evaluated for one of the winter EMEP intensive campaigns (February-March 2009) against aerosol mass spectrometer (AMS) measurements performed at 11 sites in Europe. We found a considerable improvement for the modelled organic aerosol (OA) mass compared to our previous model application with the mean fractional bias (MFB) reduced from −61 % to −29 %. We performed model-based source apportionment studies and compared results against positive matrix factorization (PMF) analysis performed on OA AMS data. Both model and observations suggest that OA was mainly of secondary origin at almost all sites. Modelled secondary organic aerosol (SOA) contributions to total OA varied from 32 to 88 % (with an average contribution of 62 %) and absolute concentrations were generally under-predicted. Modelled primary hydrocarbon-like organic aerosol (HOA) and primary biomass burning-like aerosol (BBOA) fractions contributed to a lesser extent (HOA from 3 to 30 %, and BBOA from 1 to 39 %) with average contributions of 13 and 25 %, respectively. Modelled BBOA fractions was found to represent 12 to 64 % of the total residential heating related OA, with increasing contributions at stations located in the northern part of the domain. Source apportionment studies were performed to assess the contribution of residential and non-residential combustion precursors to the total SOA. Non-residential combustion and transportation precursors contributed about 30–40 % to SOA formation (with increasing contributions at urban and near industrialized sites) whereas residential combustion (mainly related to wood burning) contributed to a larger extent, around 60–70 %. Contributions to OA from residential combustion precursors in different volatility ranges were also assessed: our results indicate that residential combustion gas-phase precursors in the semi-volatile range contributed from 6 to 30 %, with higher contributions predicted at stations located in the southern part of the domain. On the other hand, higher volatility residential combustion precursors contributed from 15 to 38 % with no specific gradient among the stations. The new retrieved parameterization, although leading to a better agreement between model and observations, still under-predicts the SOA fraction suggesting remaining uncertainties in the new scheme or that other sources and/or formation mechanisms need to be elucidated.

scholarly journals Modelling winter organic aerosol at the European scale with CAMx: evaluation and source apportionment with a VBS parameterization based on novel wood burning smog chamber experiments

2017 ◽  
Vol 17 (12) ◽  
pp. 7653-7669 ◽  
Author(s):  
Giancarlo Ciarelli ◽  
Sebnem Aksoyoglu ◽  
Imad El Haddad ◽  
Emily A. Bruns ◽  
Monica Crippa ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Oxidation Products ◽  
Basis Set ◽  
Formation Mechanisms ◽  
Smog Chamber ◽  
Road Transportation ◽  
Residential Combustion ◽  
Wood Burning

Abstract. We evaluated a modified VBS (volatility basis set) scheme to treat biomass-burning-like organic aerosol (BBOA) implemented in CAMx (Comprehensive Air Quality Model with extensions). The updated scheme was parameterized with novel wood combustion smog chamber experiments using a hybrid VBS framework which accounts for a mixture of wood burning organic aerosol precursors and their further functionalization and fragmentation in the atmosphere. The new scheme was evaluated for one of the winter EMEP intensive campaigns (February–March 2009) against aerosol mass spectrometer (AMS) measurements performed at 11 sites in Europe. We found a considerable improvement for the modelled organic aerosol (OA) mass compared to our previous model application with the mean fractional bias (MFB) reduced from −61 to −29 %. We performed model-based source apportionment studies and compared results against positive matrix factorization (PMF) analysis performed on OA AMS data. Both model and observations suggest that OA was mainly of secondary origin at almost all sites. Modelled secondary organic aerosol (SOA) contributions to total OA varied from 32 to 88 % (with an average contribution of 62 %) and absolute concentrations were generally under-predicted. Modelled primary hydrocarbon-like organic aerosol (HOA) and primary biomass-burning-like aerosol (BBPOA) fractions contributed to a lesser extent (HOA from 3 to 30 %, and BBPOA from 1 to 39 %) with average contributions of 13 and 25 %, respectively. Modelled BBPOA fractions were found to represent 12 to 64 % of the total residential-heating-related OA, with increasing contributions at stations located in the northern part of the domain. Source apportionment studies were performed to assess the contribution of residential and non-residential combustion precursors to the total SOA. Non-residential combustion and road transportation sector contributed about 30–40 % to SOA formation (with increasing contributions at urban and near industrialized sites), whereas residential combustion (mainly related to wood burning) contributed to a larger extent, around 60–70 %. Contributions to OA from residential combustion precursors in different volatility ranges were also assessed: our results indicate that residential combustion gas-phase precursors in the semivolatile range (SVOC) contributed from 6 to 30 %, with higher contributions predicted at stations located in the southern part of the domain. On the other hand, the oxidation products of higher-volatility precursors (the sum of intermediate-volatility compounds (IVOCs) and volatile organic compounds (VOCs)) contribute from 15 to 38 % with no specific gradient among the stations. Although the new parameterization leads to a better agreement between model results and observations, it still under-predicts the SOA fraction, suggesting that uncertainties in the new scheme and other sources and/or formation mechanisms remain to be elucidated. Moreover, a more detailed characterization of the semivolatile components of the emissions is needed.

scholarly journals Sources of organic aerosols in Europe: A modelling study using CAMx with modified volatility basis set scheme

2019 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Basis Set ◽  
Anthropogenic Sources ◽  
Air Quality Model ◽  
Quality Model ◽  
Wood Burning ◽  
Gasoline Vehicles

Abstract. Source apportionment of organic aerosols (OA) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models act as potential tools to identify OA components and sources at high spatial and temporal resolution, however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional air quality model Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and contained more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modelled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in the previous studies which strengthens our confidence in our modelled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 μg m−3 to −0.4 μg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 %–42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %) while biogenic emissions contributed ~55 % to OA during summer in Europe on average. In both seasons, the other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (~5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modelling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.

scholarly journals Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

2021 ◽  
Vol 14 (3) ◽  
pp. 1681-1697
Author(s):  
Jianhui Jiang ◽  
Imad El Haddad ◽  
Sebnem Aksoyoglu ◽  
Giulia Stefenelli ◽  
Amelie Bertrand ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Experimental Studies ◽  
Organic Aerosol ◽  
Basis Set ◽  
Reference Scenario ◽  
Air Quality Model ◽  
Quality Model ◽  
The Balkans ◽  
Wall Loss

Abstract. Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models that use parameters obtained from chamber experiments. In this study, a box model with a volatility basis set (VBS) scheme was developed, and the secondary organic aerosol (SOA) yields with vapor wall loss correction were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9 and leads to better agreement with measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The model results from the VBS schemes with standard (VBS_BASE) and vapor-wall-loss-corrected parameters (VBS_WLS), as well as the traditional two-product approach, were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) stations in the winter of 2011. An additional reference scenario, VBS_noWLS, was also developed using the same parameterization as VBS_WLS except for the SOA yields, which were optimized by assuming there is no vapor wall loss. The VBS_WLS generally shows the best performance for predicting OA among all OA schemes and reduces the mean fractional bias from −72.9 % (VBS_BASE) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than VBS_BASE and VBS_noWLS, respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ∼80 % (in the Balkans). VBS_WLS also leads to better agreement between the modeled SOA fraction in OA (fSOA) and the estimated values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in parameterizations based on laboratory studies for a wider range of chamber conditions and field observations with higher spatial and temporal coverage.

scholarly journals Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

2020 ◽  
Author(s):  
Jianhui Jiang ◽  
Imad El-Haddad ◽  
Sebnem Aksoyoglu ◽  
Giulia Stefenelli ◽  
Amelie Bertrand ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Experimental Studies ◽  
Organic Aerosol ◽  
Basis Set ◽  
Reference Scenario ◽  
Air Quality Model ◽  
Quality Model ◽  
Wall Loss ◽  
Product Approach

Abstract. Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to the chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models which use parameters obtained from the chamber experiments. In this study, a box model with volatility basis set (VBS) scheme was developed and the secondary organic aerosol (SOA) yields with vapor wall loss corrected were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9, and leads to a better agreement with the measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The modeled results from the standard and vapor wall loss corrected VBS schemes, as well as the traditional two-product approach were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM)/aerosol mass spectrometer (AMS) stations in the winter of 2011. The vapor wall loss corrected VBS (VBS_WLS) generally shows the best performance for predicting OA among all OA schemes, and reduces the mean fractional bias from −72.9 % (with the standard VBS (VBS_BASE)) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than the standard VBS and the reference scenario (VBS_noWLS, same parameterization as VBS_WLS, except with the default yields without vapor wall loss correction), respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ~ 80 % in Romania. VBS_WLS also leads to a better agreement between the modeled SOA fraction in OA (fSOA) and the estimated measured values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in the parameterizations based on laboratory studies with a wider range of chamber conditions and field observations with higher spatial and temporal coverage.

scholarly journals Sources of organic aerosols in Europe: a modeling study using CAMx with modified volatility basis set scheme

2019 ◽  
Vol 19 (24) ◽  
pp. 15247-15270 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Agricultural Waste ◽  
Organic Aerosols ◽  
Basis Set ◽  
Anthropogenic Sources ◽  
Wood Burning ◽  
Gasoline Vehicles

Abstract. Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 to −0.4 µg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.

scholarly journals Changes in PM<sub>2.5</sub> concentrations and their sources in the US from 1990 to 2010

2021 ◽  
Vol 21 (22) ◽  
pp. 17115-17132
Author(s):  
Ksakousti Skyllakou ◽  
Pablo Garcia Rivera ◽  
Brian Dinkelacker ◽  
Eleni Karnezi ◽  
Ioannis Kioutsioukis ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Biomass Burning ◽  
Transport Model ◽  
Organic Aerosol ◽  
Road Transport ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Quality Model ◽  
So2 Emissions ◽  
The Us

Abstract. Significant reductions in emissions of SO2, NOx, volatile organic compounds (VOCs), and primary particulate matter (PM) took place in the US from 1990 to 2010. We evaluate here our understanding of the links between these emissions changes and corresponding changes in concentrations and health outcomes using a chemical transport model, the Particulate Matter Comprehensive Air Quality Model with Extensions (PMCAMx), for 1990, 2001, and 2010. The use of the Particle Source Apportionment Algorithm (PSAT) allows us to link the concentration reductions to the sources of the corresponding primary and secondary PM. The reductions in SO2 emissions (64 %, mainly from electric-generating units) during these 20 years have dominated the reductions in PM2.5, leading to a 45 % reduction in sulfate levels. The predicted sulfate reductions are in excellent agreement with the available measurements. Also, the reductions in elemental carbon (EC) emissions (mainly from transportation) have led to a 30 % reduction in EC concentrations. The most important source of organic aerosol (OA) through the years according to PMCAMx is biomass burning, followed by biogenic secondary organic aerosol (SOA). OA from on-road transport has been reduced by more than a factor of 3. On the other hand, changes in biomass burning OA and biogenic SOA have been modest. In 1990, about half of the US population was exposed to annual average PM2.5 concentrations above 20 µg m−3, but by 2010 this fraction had dropped to practically zero. The predicted changes in concentrations are evaluated against the observed changes for 1990, 2001, and 2010 in order to understand whether the model represents reasonably well the corresponding processes caused by the changes in emissions.

scholarly journals Organic aerosol concentration and composition over Europe: insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis

2014 ◽  
Vol 14 (17) ◽  
pp. 9061-9076 ◽  
Author(s):  
C. Fountoukis ◽  
A. G. Megaritis ◽  
K. Skyllakou ◽  
P. E. Charalampidis ◽  
C. Pilinis ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Biomass Burning ◽  
Transport Model ◽  
Three Dimensional ◽  
Organic Aerosol ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Wood Combustion ◽  
Quality Model ◽  
Average Mass

Abstract. A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3.

scholarly journals Simulation of the evolution of biomass burning organic aerosol with different volatility basis set schemes in PMCAMx-SRv1.0

2021 ◽  
Vol 14 (4) ◽  
pp. 2041-2055
Author(s):  
Georgia N. Theodoritsi ◽  
Giancarlo Ciarelli ◽  
Spyros N. Pandis
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Organic Aerosol ◽  
Basis Set ◽  
Base Case ◽  
Air Quality Model ◽  
Alternative Scheme ◽  
Average Maximum ◽  
Different Seasons ◽  
The Impact

Abstract. A source-resolved three-dimensional chemical transport model, PMCAMx-SR (Particulate Matter Comprehensive Air-quality Model with extensions – Source Resolved), was applied in the continental US to investigate the contribution of the various components (primary and secondary) of biomass burning organic aerosol (bbOA) to organic aerosol levels. Two different schemes based on the volatility basis set were used for the simulation of the bbOA during different seasons. The first is the default scheme of PMCAMx-SR, and the second is a recently developed scheme based on laboratory experiments of the bbOA evolution. The simulations with the alternative bbOA scheme predict much higher total bbOA concentrations when compared with the base case ones. This is mainly due to the high emissions of intermediate-volatility organic compounds (IVOCs) assumed in the alternative scheme. The oxidation of these compounds is predicted to be a significant source of secondary organic aerosol. The impact of the other parameters that differ in the two schemes is low to negligible. The monthly average maximum predicted concentrations of the alternative bbOA scheme were approximately an order of magnitude higher than those of the default scheme during all seasons. The performance of the two schemes was evaluated against observed total organic aerosol concentrations from several measurement sites across the US. The results were different for the different seasons examined. The default scheme performed better during July and September, while the alternative scheme performed a little better during April. These results illustrate the uncertainty of the corresponding predictions and the need to quantify the emissions and reactions of IVOCs from specific biomass sources and to better constrain the total (primary and secondary) bbOA levels.

scholarly journals Changes in PM<sub>2.5</sub> concentrations and their sources in the US from 1990 to 2010

2021 ◽  
Author(s):  
Ksakousti Skyllakou ◽  
Pablo Garcia Rivera ◽  
Brian Dinkelacker ◽  
Eleni Karnezi ◽  
Ioannis Kioutsioukis ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Biomass Burning ◽  
Transport Model ◽  
Organic Aerosol ◽  
Road Transport ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Quality Model ◽  
So2 Emissions ◽  
The Us

Abstract. Significant reductions of emissions of SO2, NOx, volatile organic compounds (VOCs) and primary particulate matter (PM) took place in the US from 1990 to 2010. We evaluate here our understanding of the links between these emissions changes and corresponding changes in concentrations and health outcomes using a chemical transport model, the Particulate Matter Comprehensive Air Quality Model with Extensions (PMCAMx) with the Particle Source Apportionment Algorithm (PSAT). Results for 1990, 2001 and 2010 are presented. The reductions in SO2 emissions (64 %, mainly from electric generating units) during these 20 years have dominated the reductions in PM2.5 leading to a 45 % reduction in sulfate levels. The predicted sulfate reductions are in excellent agreement with the available measurements. Also, the reductions in elemental carbon (EC) emissions (mainly from transportation) have led to a 30 % reduction of EC concentrations. The most important source of organic aerosol (OA) through the years according to PMCAMx is biomass burning, followed by biogenic secondary organic aerosol (SOA). OA from on-road transport has been reduced by more than a factor of three. On the other hand, changes in biomass burning OA and biogenic SOA have been modest. In 1990, about half of the US population was exposed to annual-average PM2.5 concentrations above 20 μg m−3, but by 2010 this fraction had dropped to practically zero. The predicted changes in concentrations are evaluated against the observed changes for 1990, 2001, and 2010, in order to understand if the model represents reasonably well the corresponding processes caused by the changes in emissions.

scholarly journals 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

2015 ◽  
Vol 8 (7) ◽  
pp. 2095-2117 ◽  
Author(s):  
K. Yahya ◽  
K. Wang ◽  
Y. Zhang ◽  
T. E. Kleindienst
Keyword(s):  
Air Quality ◽  
North America ◽  
Model Performance ◽  
Organic Aerosol ◽  
Basis Set ◽  
Meteorological Variables ◽  
Phase 2 ◽  
Air Quality Model ◽  
Quality Model ◽  
Coupled Models

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.

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