Impacts of Future Climate Change and Effects of Biogenic Emissions on Surface Ozone and Particulate Matter Concentrations in Us

Atmospheric Chemistry and Physics Discussions This discussion paper is/has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP if available. Abstract Simulations of present and future average regional ozone and PM 2.5 concentrations over the United States were performed to investigate the potential impacts of global climate change and emissions on regional air quality using CMAQ. Various emissions and climate conditions with different biogenic emissions and domain resolutions were 5 implemented to study the sensitivity of future air quality trends from the impacts of changing biogenic emissions. A comparison of GEOS-Chem and CMAQ was performed to investigate the effect of downscaling on the prediction of future air quality trends. For ozone, the impacts of global climate change are relatively smaller when compared to the impacts of anticipated future emissions reduction, except for 10 the Northeast area, where increasing biogenic emissions due to climate change have stronger positive effects (increases) to the regional ozone air quality. The combination effect from both climate change and emission reductions leads to approximately a 10% or 5 ppbv decrease of the maximum daily average eight-hour ozone (MDA8) over the Eastern United States. For PM 2.5 , the impacts of global climate change have 15 shown insignificant effect, where as the impacts of anticipated future emissions reduction account for the majority of overall PM 2.5 reductions. The annual average 24-h PM 2.5 of the future-year condition was found to be about 40% lower than the one from the present-year condition, of which 60% of its overall reductions are contributed to by the decrease of SO 4 and NO 3 particulate matters. Changing the biogenic emissions 20 model increases the MDA8 ozone by about 5–10% or 3–5 ppbv in the Northeast area. Conversely, it reduces the annual average PM 2.5 by 5% or 1.0 µg/m 3 in the Southeast region.


Introduction
Properly representing the transport and chemical transformation of air pollutants has always been one of the greatest challenges of simulating regional air quality in global climate/chemistry models.The accuracy of the results strongly depends on the selection of grid resolution (i.e., usually ≈1 • ×1 • or large), land use information, emissions input and temporal resolution (i.e., 3-h) (Chin et al., 2007;Civerolo et al., 2007;Ito et al., 2009;Knutti et al., 2008;Wu et al., 2007;Fiore et al., 2005).It has been observed that the coarse resolution used by global models may not be sufficient to represent appropriate meteorological characteristics of some regions (i.e., complex terrain regions) because of over-simplifying the vertical grid structure and land use information in the models.This issue has been reported in the regional model, as well when a relatively coarse resolution (i.e., 36 km) is used (Arunachalam et al., 2006;Kim et al., 2010).Nevertheless, global models have been widely recognized as a practical tool for predicting long-term climate and air quality trends, evaluating intercontinental long-range transport of air pollutants and large-scale climate and air quality impact studies, such as those on dust storms and the stratospheric ozone hole (Wu et al., 2008b;Chin et al., 2007;Vingarzan, 2004).To integrate useful information from global models into regional-scale models, downscaled global climate and chemistry outputs have been developed in recent years for resolving the issue of insufficient temporal and spatial resolutions (Lam and Fu, 2010).Various air quality studies have implemented the downscaling methodology for evaluating the influence of climate change, land-use modification, and different emissions projection scenarios on both anthropogenic and biogenic emissions on the regional scale in the United States (Civerolo et al., 2007;Xiaoyan et al., 2008;Jacobson and Streets, 2009;Zhang et al., 2008).
In the area of regional climate change and air quality, a wide range of temperature and ozone concentration changes have been reported from both global and regional model studies in the United States.Depending on the type of model used and emissions projection scenarios (i.e., the IPCC A1B) selected, the projected future ozone concentrations vary greatly.In the global model perspective, Wu et al. (2008b) have predicted a 1-3 • C increase of temperature in 2050, which would result in an extra 2-5 ppbv of surface ozone in the Northeast and the Mid-north of the United States and a reduction of ozone in the Southeast United States on a non-emission change scenario using GISS-GCM/GEOS-Chem coupling models.They also found that the anticipated emissions reductions (40% for NO x ) in the IPCC A1B scenario would have a greater effect (i.e., −2 to −15 ppbv) than the climate change (i.e., +2 to +5 ppbv) on the maximum daily 8-h ozone.Huang et al. (2008) simulated the future air quality in 2048-2052 (summer) using the Model for Ozone And Related chemical Tracers (MOZART) under the IPCC A1Fi (i.e., dirtiness) and the B1 (clearness) scenarios.
They found that the Southeast United States would have the largest sensitivity of surface ozone in response to the emission changes with +25% to −24% for the A1Fi and B1 scenarios in 2048-2052, while less sensitivity of surface ozone would be shown on the Midwest and the Northeast of the United States and Texas.They suggested that the future US air quality projected by MOZART is less sensitive to the emissions scenarios simulated by the Regional Air Quality Model (RAQM) in those locations.It is doubtful that they have found that the trend of surface ozone mixing ratio from MOZART is consistently higher than the RAQM, which is unlikely to occur at a coarse grid resolution.They commented that the overestimation of ozone in MOZART was caused by over-estimation of anthropogenic emissions.Their study revives the erroneous notion that consistent emissions input between the global and the regional models should be used when model comparisons are performed.
In the regional model perspective, the downscaled results on the impacts of climate change have also varied largely across the geospatial regions.Some studies have found that climate change has large adverse effects on future air quality.The large increase of temperature (i.e., 1-2 K) has encouraged the formation of ozone and resulted in an extra 5-10 ppbv compared to the present air quality condition.Bell et al. (2007), Nolte et al. (2008) and Dawson et al. (2008) found that the sensitivity of temperature change in the regional ozone averages 0.34 ppbv K −1 (i.e., 1-3 ppbv for a 2. increase) for the Eastern United States.They also suggested that a 2.5 K increase of temperature leads to a 30% increase of exceedance on the maximum daily average 8-h ozone (MDA8) standard.Bell et al. (2007) found that the climate change alone contributed an increase of 4.8 ppbv on average ozone across the United States, with the largest increase at 9.6 ppbv, which corresponds to an additional 68% of exceedances in the 8-h standard in 2050.Although the effect of climate change on temperature and stagnant air flow would encourage the formation of ozone, most researchers have found that the anticipated emissions reduction from IPCC cases (i.e.A1B) in the United States tends to compensate for the effect of climate change on ozone formation with or without considering the positive feedback from Biogenic Volatile Organic Compounds (BVOC) and yields an overall ozone reduction of −4 to −15% in 2050.It is suggested that effects of anthropogenic emissions account for more overall change of ozone formation than the climate change (Tagaris et al., 2007;Jacob and Winner, 2009;Nolte et al., 2008;Zhang et al., 2008).The accuracy of these studies has been tied strongly to the methodology used for downscaling, the choice of resolution, and selection of projection emission scenarios.It is observed that most of the climate studies mentioned above have used the Biogenic Emissions Inventory System (BEIS) for estimating BVOC emissions (Weaver et al., 2009).While recent studies showing that BEIS may have underestimated isoprene emission compared to the Model of Emissions of Gases and Aerosols from Nature (MEGAN), these studies may also lead to underestimating the effect of climate change in the VOC-limited region, such as in the Northeast region of the United States (Sakulyanontvittaya et al., 2008;Guenther et al., 2006;Fiore et al., 2005;Kunkel et al., 2008).The estimates of biogenic isoprene emission from MEGAN are about 50% more than the estimates from BEIS (Pouliot, 2008;Pouliot and Pierce, 2009).Therefore, it is possible that the additional BVOC from MEGAN may lead to a large increase of ozone and further alter the relationship found between the effect of climate change and the effect of change of anthropogenic emissions found in previous studies.Furthermore, the majority of these climate change studies have used grid resolutions of 30 km or larger (i.e., except for Hogrefe et al., 2007), with recent studies suggesting that 12 km resolution may be the better choice for studying regional air quality, and that the grid resolutions of 30 km or larger may produce an additional bias to climate change studies and may result in underestimation of ozone formation in regional-scale studies (Hogrefe et al., 2007a,b;Kim et al., 2010).Since the sensitivities of scalability and the effects of BVOC on the climate change scenarios have not been studied, revisiting the future air quality with the implementation of those concepts is important to further investigate the effect of climate change on a regional scale.In this study, three years of air quality with present/future climate conditions were simulated at 36 km resolution using the Community Multi-scale Air Quality Modeling System (CMAQ) to examine the effect of climate change on regional air quality under IPCC A1B emissions scenarios.We downscaled GISS General Circulation Model (GISS GCM III) and GEOS-Chem model outputs according to the framework of Global Change and Air Pollution (GCAP) to obtain a proper present-future climate and chemical boundary conditions for the simulations (Jacob et al., 2009).In the manuscript, unless specified otherwise, the present/future climate in here refers to 1999-2001 for the present climate and 2049-2051 for the future climate.Due to the concern of the effects of biogenic emission in the regional climate study, additional air quality simulations of present/future climate conditions (2000 and 2050) with MEGAN and BEIS biogenic emissions scenarios at 12 km resolution were performed to investigate the effect of changing of biogenic emissions.
Overall, we concentrated on three aspects of climate change/air quality studies: (1) The regional impacts on air quality from global climate change (i.e., Southeastern United States).Since very limited studies have documented fine resolution results in climate change/air quality studies, these results provide additional insight into the effect of model resolution selection to the future climate and air quality predictions; (2) the comparison of global model results (i.e., 4 • ×5 • resolution) with regional outputs results (i.e., 36 km and 12 km resolution) to identify the discrepancy in the prediction of future regional air quality trends between the global model and the regional model; and (3) the impacts of using different biogenic emissions inventories (i.e., BIES and MEGAN on fine resolution CMAQ) on the future air quality studies and the role of BVOC in the future climate studies.In the study, ozone (O 3 ) and fine particulates (PM 2.5 ) were the focus since they have significant impacts on human health.Eight scenarios were performed, which include various combinations of emissions scenarios within present and future meteorology.We do not include the impacts of future land cover changes, which is highly uncertain in the future climate.It is expected that this study will provide a broader understanding of the discrepancy between global and regional outputs for air quality application in the area of future climate change scenarios.

Methodology -GCAP modeling system
The GCAP modeling system consists of four models, spanning from global to regional scales.In the global perspective, the GEOS-Chem modeling system driven by the GISS III GCM was used to provide global air quality conditions in a coarse resolution.Details of the global chemical and meteorological models implemented in the present study can be found in Schmidt et al. (2006) and Wu et al. (2008a).In the regional perspective, the outputs of the GEOS-Chem were downscaled to provide chemical initial and boundary conditions for CMAQ, while the outputs of the GISS GCM III were used as the inputs for the Penn State/NCAR Mesoscale Model (MM5).Descriptions of the models' setup and emission scenarios are discussed below.

Global models
The GEOS-Chem Chemical Transport Model (CTM) driven by meteorological fields from the GISS GCM III (an updated version of the model described by Rind et al., 1999)  surface to 0.002 hPa (up to 85 km in altitude) was used to simulate the transient climate event (Rind et al., 2007).For meteorological consistency, the same temporal resolution was used in the GEOS-Chem CTM with 3-h meteorological data of mixing depths and surface variables (i.e., surface temperature; surface winds; precipitation and albedo; and solar radiation) and 6-h meteorological data (i.e., winds, convective mass fluxes, temperature, humidity, cloud optical depths, and cloud fractions) generated from the GISS GCM III.In this study, GEOS-Chem (v7.03.06) was used, which includes a fully coupled treatment of tropospheric ozone-NOx-VOC chemistry and aerosols to simulate both ozone and PM 2.5 concentrations in the US (Park et al., 2004).Four scenarios were evaluated: (1) present meteorology with present emissions, (2) present meteorology with future emissions, (3) future meteorology with present emissions, and (4) future meteorology with future emissions.The descriptions of the forecasted future emissions were described in the emissions section.Three years of simulations were conducted for each climate scenario (i.e., three years of present climate and three years of future climate), which were initialized on 1 September and continued for 40 months.The first four months served for proper initialization, and the following 36 months were used as the actual simulation results.Details of the global models' setup were described by Wu et al. (2007).

Regional models
The initial and boundary conditions of the regional models (both MM5 and CMAQ) were downscaled from the outputs of the global models' simulations (GISS GCM III and GEOS-Chem).Details of the downscaling methodology were described in Lam and Fu (2010).The CMAQ was driven by NCAR's fifth-generation Mesoscale Model v3.7 (MM5), with hourly resolution.The horizontal resolutions of 36 km and 12 km with 34 sigma vertical layers were used.All MM5 simulations were conducted using the one-way nested approach from 108 km over North America (140-40  et al., 2004).Afterward, we applied these monthly growth factors to different emission categories of present-day emissions files to generate future-year emissions for each day.It should be noted that the same methodology described above has been applied in both GEOS-Chem and CMAQ to maintain emissions consistency between the global and the regional models.We have estimated the differences in total anthropogenic NO x and VOC emissions between those two models at the present-year (2000) were at the levels of 10% or less for the Continental US.The calculated total NO x and VOC emissions were 19.4 and 15.7 Tg/year for the GEOS-Chem and were 21.0 and 17.2 Tg/year for the CMAQ, respectively.Table 2 lists the summary of annual anthropogenic emission growth rates used in this study.To simplify model comparisons, the same sub-domain definitions described in Wu et al. (2008b), were implemented, as shown in Fig. 1.The sub-domains include three areas: (1) Northeast, (2) Southeast, and (3) Midwest.The Northeast domain covers all the eastern states from Indiana to the Atlantic coast in an east-west direction, and from Kentucky to Michigan in a south-north direction (87.5-67.7 • W, 37.2-45.7 • N).The Southeast domain includes the majority of the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) states and, with half of  • W, 29.8-37.2• N) and the Midwest domain, contains all the mid-northern states and up to the middle of Wyoming (107.4-87.5 • W, 38.6-49.8• N).As shown in Table 2, a large increase of acetaldehyde (ALD2) and formaldehyde (FORM) were projected as a result of the increase of the biomass burning in the future.The projection values could be up to 2.5 times higher than the present-day emissions.In contrast, a huge reduction of sulfur dioxide (SO 2 ) was proposed due to the anticipated future fuel emissions controls.For nitrogen oxide (NO 2 ), an overall reduction of 60% was forecast across the Eastern US, with the largest reductions of 60 to 70% in the fossil fuel combustion sector.It should be noted that these NO 2 reductions in the US, have been compensated for by the increased emissions in Mexico and yield a smaller reduction factor (0.64) for the continental US domain.

Biogenic emissions
For biogenic emissions, two emission factor-based models, the Biogenic Emissions Inventory System (BEIS) v3.12 and the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.02 (http://bai.acd.ucar.edu/Megan/index.shtml),were used to generate the hourly biogenic emissions inventories for both present and future climate scenarios.Corresponding years of temperature and solar radiation data generated from the Meteorology-Chemistry Interface Processor (MCIP) were used to take into account the change of biogenic emissions from natural sources caused by the change in meteorological conditions.It should be noted that, in the study, two separate datasets were generated, which are: 1) BEIS dataset for 2000 and 2050, and 2) MEGAN dataset for both present/future conditions (1999-2001 and 2049-2051).A spatial resolution of 1 km land use and vegetation was employed in the 36 and 12 km domains on both biogenic models.We assumed the same land use and vegetation patterns as 2000 on all years and all scenarios.The main differences between MEGAN and BEIS are the method of estimating isoprene emission and the emission factors used in the models (Sakulyanontvittaya et al., 2008).In BEIS, the isoprene emission is calculated by empirical algorithms described in Guenther et al. (1993), which follows a mathematical function that depends on temperature and solar radiation.An increase in temperature causes an initial rise in isoprene emission trailed by a slow decline when the temperature reaches about 38 • C (Zhang et al., 2008).In MEGAN, isoprene is characterized by two separate emissions processes, the light-and-temperature-dependent direct emissions from chloroplasts without storage and purely temperature-dependent emissions from storage pools.Each process utilizes an individual dependence factor to adjust the total isoprene emission.MEGAN calculates the plant-specific isoprene emission by multiplying all those dependence factors with the base/standard emission factor for 2193 where ε is the base emission factor, γ LAI is the Leaf Area Index Factor, γ P is the PPFD Emission Activity Factor (light-dependence) and is a function of solar angle and above canopy Photosynthetic Photon Flux Density (PPFD), γ T is the Temperature Response Factor and γ age is the Leaf Age Factor.Sakulyanontvittaya et al. (2008) estimated the average hourly isoprene emissions in MEGAN are about 61% and 47% higher than the emissions generated by BEIS for July 2001 and January 2002, respectively.It should be noted that the isoprene emission factor used by BEIS is significantly lower than the factors used by other models, which may lead to underestimate the total isoprene emission (Arneth et al., 2007).In this study, the annual isoprene emission in MEGAN was about 53% higher than in BEIS in year 2000.Similar geospatial distributions of isoprene emissions were observed between the two models (not shown).Figure 2a,b shows the CONUS 36 km daily domain totals of isoprene and total BVOC emissions in BEIS and MEGA.The major isoprene emission difference occurred in the months of May-September when heat and solar radiation are significantly high.For total BVOC, similar magnitudes of emissions (7% difference in the CONUS domain) are found between the two models.However, significant geospatial disagreements were observed (not shown).For example, formaldehyde emissions in BEIS are distributed quite evenly throughout the United States, but the emissions in MEGAN are almost all centered in the Southeastern United States.These discrepancies of emission distributions potentially create differences in the predictions of air quality results between the two models.
Table 3 shows the emissions breakdown of the present year (2000) biogenic emissions from BEIS and MEGAN.In the Northeast domain, MEGAN shows much larger emission values than BEIS on ALD2, ETH, ISOP, and PAR.The total biogenic VOC emissions in MEGAN is about 60% higher than in BEIS.It is expected that the additional VOC emission in MEGAN may strongly affect the ozone production in the Northeast domain since the Northeast domain is considered as a VOC-limited area and is sensitive to an increase of BVOC.For the Midwest and Southeast domains, −8% and +20% of total VOC differences (MEGAN−BEIS) were found, respectively.To investigate the effect of climate change, the differences in VOC emissions between 2050 and 2000 were also calculated, which is shown in the right side of the Table 3.As resulting from surface warming (i.e., 1.0-2.5 • C) and enhancement of solar radiation, both MEGAN and BEIS showed an increase of total biogenic emission by 30% and 21%, respectively.These results (+40% increase in isoprene in MEGAN and +23% in BEIS) were comparable to the values reported in the literature, where BEIS's VOC emissions are increased by 10-90% in the future year (Zhang et al., 2008;Hogrefe et al., 2004).
It is observed that the emissions estimated by MEGAN were much more climate sensitive than by BEIS, with additional 3-5% increase for most of VOC species and 10% increase for total biogenic VOC.The increase of VOC emission strengthens the impact of climate change on ozone air quality in the United States.

Emissions scenarios
Overall, eight simulation scenarios were selected and summarized in

Comparison of present and future climate
Model performance of meteorological outputs was evaluated by comparing the global GCM outputs to the downscaled MM5 outputs.We have chosen the global GCM outputs as the bases of comparison, instead of observational data, for three reasons: (1) the primary focus of the study was to investigate the effects of downscaling, this type of comparison permitted one to quantify the relative air quality impacts from meteorological downscaling; (2) the global GCM outputs used for the comparisons have been extensively evaluated with observational data (Rind et al., 2007;Schmidt et al., 2006).This type of comparison should give sufficient understanding of MM5 performance to the present climate condition; (3) since no observed boundary conditions (i.e., FDDA technique or observation nudging in the GISS GCM) were used to constrain GCM simulations, the characteristics of MM5 outputs are unlikely to follow the hourly/daily trends with the observational data.If model performance was done on monthly averaging, comparing MM5 outputs to the GISS outputs would give sufficient meteorological validation -just as if the outputs had been compared with observational data.
For the purpose of air quality evaluation, several climatic variables were selected: ground temperature (T ), relative humidity (RH), precipitation (RAIN), shortwave radiation at the surface (SW), total cloud fraction (CFRACT), wind speed (WSP), wind direction (WDR) and Planetary Boundary Layer (PBL) height from present and future climate conditions.The main focus was placed on temperature since the rise in temperature is expected to worsen the regional air quality in the future by enhancing both biogenic emissions and photochemical reaction rates of gaseous precursors of ozone and low-volatile secondary PM 2.5 .In addition to temperature, the change of wind speed and PBL height were also expected to be important to the regional air quality since both affect the rates of horizontal and vertical dispersions.Thus, they are expected to have a significant impact on surface ozone and PM 2.5 concentrations if significant changes from these variables are observed (Aw and Kleeman, 2003;Gaza, 1998).
In response to the change of greenhouse gases, the future mean surface temperature was predicted to increase 1.0-2.0K when compared to the present, as shown in Table 5.The major changes of temperature occurred in May-September (MJJAS) for all three domains.The change of mean surface temperature between future and present climate was about 2.0 K for the entire continental US domain, with the maximum hourly temperature difference of 5-6 K within the 36 km 2 grid.It was observed that the one of the future year, 2049, had a relatively low temperature; The mean surface temperature during May-September in the Midwest was even comparable to the present climate condition.Overall, these values shown in Table 5 are similar in magnitudes to previous studies reported in the literature, where a larger increase in temperature was predicted for the Midwest and Southeast, with a smaller increase expected for the Northeast (i.e., average +1 K) (Bell et al., 2007;Nolte et al., 2008;Zhang et al., 2008).The increase in temperature across the United States potentially enhances the rates of radical production and photochemical reaction, thus worsen the ozone and PM 2.5 air quality in the future (Aw and Kleeman, 2003;Tai et al., 2010).The comparison of the GISS outputs to the MM5-36 km have shown that the Root Mean Square Error (RMSE) is about +0.3 K or less for the CONUS domain, with ±0.6 K of winter bias and ±0.2 K summer bias on the defined domains.Based on the value reported by Dawson et al. (2008), the difference of 0.2 K would translate into about 0.1-0.2ppbv increase of surface ozone.With a 0.3 K difference found between the GISS and MM5 outputs, the effect of downscaling would contribute an additional 0.2-0.3ppbv of surface ozone in the Northeast domain for the future scenario.For downscaling from the MM5-36 km to the MM5-12 km, no significant changes were found on the average and maximum domain-wide temperatures for the Southeast.
The higher future temperature may promote higher ozone and PM 2.5 concentrations.The possible changes of PBL height and surface wind speed may also affect the regional air circulations and cause changes of ozone and PM 2.5 , which need further investigation.From MM5 comparison, the mean surface wind speeds between present and future climate conditions were similar for all domains, with the maximum difference of 0.4 m/s occurring in the Southeast during MJJAS.The overall annual RMSE was about 0.2 m/s across the CONUS domain.The mean values of wind speeds during MJJAS were 2.6 m/s, 3.0 m/s and 2.7 m/s for the Midwest, Northeast and Southeast, respectively.Although similar mean values of wind speeds between present and future climate conditions were observed, a clear indication of intensification of horizontal dispersion at the high wind speed portion (i.e., 6 m/s or above) were also found in the cumulative distribution curve (CDF) in the Northeast and Midwest domains for the future.It is believed that these phenomena would not likely increase the ozone and PM 2.5 concentrations in the future since ozone and PM 2.5 are formed at a low wind speed condition.Therefore, it is concluded that the change of wind speed between present and future climate conditions has a minor effect on the ozone and PM 2.5 air quality on the three domains.For the downscaling perspective, a large difference (i.e., 0.6 m/s) was found between the GISS and MM5-36 km outputs in the Midwest.The difference was caused by the manner in which topographical variables are implemented by the GISS GCM and MM5 models in the Rocky Mountain area where significant elevation changes within the modeling grids.This difference in wind speed may introduce significant biases to the future air quality in the Midwest when comparing GEOS-Chem outputs to CMAQ outputs.Figure 3a-c  In the study domains, no significant change of PBL height (±5% difference) was found to be attributable to climate change.These findings are consistent with the GISS's results, where only ±10% PBL changed for the future year scenario (Mickley et al., 2006;Wu et al., 2008a).In addition to wind speed and PBL height, other meteorological parameters such as solar radiation, humidity, and precipitation may also affect the ozone and PM 2.5 air qualities.Early findings show that the future temperature will increase by at least 2 K.This increase in temperature may be linked to the increase of solar radiation at the surface (a direct proportional relationship between temperature and solar radiation is generally expected).In the Midwest, more solar radiation is predicted reaching the surface due to the decrease of cloud cover.The increase in temperature with less cloud cover in the Midwest may potentially result in a significant increase of ozone under the future climate condition.In contrast, in the Northeast and Southeast, the solar radiation will decrease by 10% due to an increase of cloud cover in the future.Although the average temperatures are increased by 1.0 to 2.0 K, the increase of cloud cover may limit the amount of solar radiation reaching the surface and possibly result in less ozone formation in these two regions.For precipitation, a slight change was found for the three regions.The seasonal averages of precipitation (JFMA, MJJAS, and OND) are within a 0.01 cm rainfall difference (Gustafson Jr. and Leung, 2007).From geospatial plots (not shown), a slight increase in precipitation was observed in both Northeast and Southeast regions and a slight decrease in precipitation was observed in the Midwest.For relative humidity (RH), the overall changes are about ±5% from present to future climate conditions among different time periods and domains.A slight increase of moisture was observed in the Northeast, while slight decreases were found in the Midwest and Southeast.As expected, the average relative humidity in the Southeast was much higher than in the Midwest and Northeast.On average, it was about 10 and 15% higher.The average RH in the future condition during MJJAS was about 80, 75, and 55% for the Southeast, Northeast, and Midwest, respectively.The high RH possibly enhances chemical deposition rates of SO 2 and also promotes precipitation (Sakamoto et al., 2004) For the downscaling perspective, a large difference of RH is observed between the GISS and MM5-36 km outputs.We have estimated an average of 10% increase of moisture across different domains from downscaling the global model into the regional model.For the MM5-36 km to MM5-12 km outputs, only less than a 1.0% in difference of RH is observed.It was believed that the large difference in RH observed between the GISS and MM5-36 km outputs was introduced by the inconsistence of advection schemes and vertical layer structures used by those two meteorological models.The additional RH in MM5 may help the formation of clouds by causing air to increase their elevation and promote more precipitation (Gustafson Jr. and Leung, 2007;Gilliam et al., 2006;Queen et al., 2008).

Comparisons of present climate air quality using MEGAN emissions
The qualitative evaluation of CMAQ chemical predictions for the present climate condition was conducted by comparing the average observed quantities of ozone and PM 2.5 from the Clean Air Status and Trends Network (CASTNET) http://www.epa.gov/CASTNET/) and the Speciation Trends Network (STN).The results provided some level of agreement between the observed and our simulated values to justify the use of CMAQ results in representing the future air quality.Due to the difference in meteorological inputs, the hourly comparison was not performed, instead average monthly values were used.Figure 5 shows the comparison of monthly average PM 2.5 from CMAQ outputs and the STN observational network.Identical labeling conventions were used in Fig. 5, as was used in Fig. 4. Once again, the average PM 2.5 concentration in CMAQ was slightly under predicted for most of the months.As expected, the peak values of PM 2.5 between simulated and observed values do not match well due to the fact that conservative emissions have been used in the simulation where no special event (such as an extreme fire or volcanic eruption) was included in the present emissions.Since the maximum PM 2.5 value is either lower or close to the maximum observed value, the CMAQ outputs reproduce reasonably well on the present PM 2.5 level.For the underestimate of PM 2.5 , Zhang et al. (2008) and Tagaris et al. (2007) suggest that the under-prediction was caused by low aerosol yields, higher vapor pressures, and a lack of isoprene second organic aerosol (SOA) treatment in CMAQ, in which the isoprene SOA accounts for about 0.01-1.52µg/m 3 of PM 2.5 .

Comparisons of CMAQ simulated outputs (MEGAN versus BEIS inventories)
As mentioned earlier, the MEGAN biogenic model estimated about 50% higher isoprene emission than the BEIS biogenic model.However, due to the fact that the BEIS model estimated higher emissions on other biogenic emissions such as terprene and formaldehyde, the resulting difference of total annual biogenic emissions between those two models has turned into about 5%.In summer, isoprene emission contributed a large portion of overall biogenic emissions and resulted in higher overall biogenic emissions in MEGAN.Conversely, the influence of isoprene emission was diminishing when winter approached which resulted in lower overall emissions in MEGAN.To investigate the impacts of using different biogenic models in the climate change study, both MEGAN and BEIS biogenic emissions were used to simulate both 2000 and 2050 using CMAQ.Figures 6a-c  MEGAN biogenic emissions, where as the CMAQ-BEIS denotes the CMAQ simulation using BEIS biogenic emissions.Both Midwest and Southeast show only a minor difference in MDA8 ozone between MEGAN and BEIS.The slopes of those two best-fit curves are close to one, which signifies that the Midwest and Southeast are insensitive to the increase of VOC emissions.
Table 6 shows the percentage change of MDA8 ozone and PM 2.5 in the present (2000) and future (2050) climate conditions.For ozone, the differences between 2000 and 2050 on the Midwest and Southeast were less than 1.0% (e.g., |(−1.4)-(−0.6)|=−0.8),which implied that the impacts of change of biogenic emissions are independent from the selection of simulation year since both years of CMAQ simulations responded similarly.In the Northeast, 10% increase (based on the best-fit line) of MDA8 ozone is observed (shown in Fig. 6b).The increase of MDA8 ozone implies that the Northeast region is perhaps made up from multiple VOC-limited sub-regions.As discussed by Duncan et al. (2009), the Northeastern region of the US, such as New York and other metropolitan areas, was a typical radical-limited/VOC-limited region (Kleinman et al., 2000).There is no doubt that the majority of places in the Northeast are more radicallimited/VOC-limited conditions due to a large portion of urban land (Milford et al., 1994(Milford et al., , 1989)).As with the increase of biogenic emissions in the Northeast domain, the VOClimited sub-regions within the domain have led to the increase of MDA8 ozone.In this study, it was observed that the average changes of MDA8 ozone on the Northeast domain in 2000 and 2050 are 5.4% and 6.0%, respectively, as shown in Table 6.
For PM 2.5 , Fig. 7 shows the chemical breakdown of annual average PM 2.5 .The left side of the figure shows the constituent of PM 2.5 and the right side of the figure shows the organic carbon (OC) portion of PM 2.5 .The suffix of "-B" and "-M" indicate the BEIS and MEGAN inventories were used in the CMAQ simulations, respectively.
As expected, the change of PM 2.5 concentration is limited to only organic aerosol from the biogenic VOC.The overall changes of PM 2.5 between the MEGAN and BEIS emissions were estimated to be about −5, −3, and −6% for the Midwest, Northeast the Southeast domain was much larger than the Midwest and Northeast due to a large difference in isoprene emission between those two biogenic models in the Southeast.
To investigate the seasonal impacts of PM 2.5 , the annual CMAQ outputs have been divided into JFMA, MJJAS, and OND.As shown in Table 6 (last two columns), large changes of PM 2.5 were observed in the months of JFMA and OND for all three domains, while insignificant change of PM 2.5 was found in MJJAS.The largest change of slope, with the value of 0.93, was observed in the Southeast in the months of OND.This value indicates the PM 2.5 estimates of CMAQ-MEGAN are about 7% lower than the estimates of CMAQ-BEIS.This −7% difference translates into about −2 µg/m 3 on average.It is believed that the lower PM 2.5 in CMAQ-MEGAN was mainly contributed by the lower terprene emission from MEGAN inventories; since terprene emission undergoes oxidation to form condensable gases and eventually converts into secondary organic aerosols (SOAs).In the CMAQ simulations, we are aware of the fact that parts of the SOAs pathway for isoprene was missing in the present CMAQ configuration, which might result in lower isoprene SOAs on both CMAQ-MEGAN and CMAQ-BEIS.It is expected that the difference in isoprene emissions between CMAQ-MEGAN and CMAQ-BEIS in the months of JFMA and OND was fairly small, so the impacts of isoprene pathway were neglectable.However, for MJJAS, a larger impact from the missing isoprene pathway was expected due to the fact that isoprene emission is the dominant species in the biogenic VOC and large differences of VOC emissions were observed between CMAQ-MEGAN and CMAQ-BEIS.Zhang et al. (2008) and Boylan (2005) suggested the maximum impact of lacking of isoprene pathway in CMAQ was about 1.52 µg/m 3 and 2.2 µg/m 3 of SOAs, respectively.Nevertheless, since the focus of the PM 2.5 discussion has been placed on the months of JFMA and OND, the impact of SOAs from isoprene may be ignored.For different climate conditions, very minor differences (i.e., less than 1.0%) were observed between 2000 and 2050 as shown in the last two columns of Table 6.Once again, this indicates that the impact of change of biogenic emissions is independent from climate conditions since the CMAQ simulation results responded in the same way on both years.

Future ozone air quality and comparison of CMAQ vs. GEOS-Chem
To better understand future air quality, both CMAQ and GEOS-Chem outputs were analyzed to investigate the future air quality trends.As mentioned earlier, both models used the same US NEI inventories, future emissions projection factors, and meteorological fields from GISS'III GCM.Although the inputs from those models were kept consistently throughout implementations, it was expected that the model outputs might still give an inconsistent prediction of future air quality due to the differences in resolutions, chemical mechanisms, and model sensitivity to climate change.Table 7 shows the summary of MDA8 ozone outputs from CMAQ and the concentration differences between CMAQ and GEOS-Chem.The four scenarios used in the simula-  2050E).It should be noted that all simulations presented in this section are the simulations using MEGAN biogenic emissions and the same notation will be used throughout this manuscript.As reported by Wu et al. (2008b), the GEOS-Chem predicted a 2.0-5.0 ppbv increase of domain-averaged MDA8 ozone over the Midwest and Northeast domains, while little change over the Southeast domain from climate change.For CMAQ, an increase of domain-averaged MDA8 ozone by about 1.0-3.0ppbv (i.e., calculated by taking the average difference between 2049-2051 (2050M) and 1999-2001 (2000M)) were predicted from climate change for all domains.These results are similar to the findings reported by Zhang et al. ( 2008), Hogrefe et al. (2004), and Racherla and Adams (2008).It is expected that our results may predict less increase of the MDA8 ozone than the other findings since the selected IPCC scenario (i.e., A1B) predicts less future warming than the A2 scenario from Hogrefe et al. and Racherla et al.Large discrepancies of domain-averaged MDA8 ozone between CMAQ and GEOS-Chem were observed in the Northeast and Southeast domains, where the CMAQ values were consistently lower than the GEOS-Chem (see in Table 7 at the column CMAQ-GC*).In the comparison of GEOS-Chem and CMAQ outputs, we observed that GEOS-Chem predicted higher minimum ozone than CMAQ.Conversely, it also predicted lower maximum ozone than CMAQ due to the restriction of grid resolution (4 • ×5 • ).The minimum and maximum ozone concentrations in GEOS-Chem were at the range of 15-20 ppbv and 75-125 ppbv, whereas the maximum and minimum values in CMAQ were at 3-5 ppbv and 130-180 ppbv, respectively.It is believed that these discrepancies may be partially related to the lack of lightning emissions in CMAQ since we did not implement lightning as a source of NOx in the upper troposphere for either the present or future climate condition.Furthermore, the difference in the sensitivity of ozone under the coarse grid resolution and the different chemical mechanisms used in the models may also contribute to the discrepancies.It is predicted that increasing the grid resolution in GEOS-Chem may reduce a portion of the discrepancy of MDA8 ozone between GEOS-Chem and CMAQ.
For the perspective of the climate change, both models consistently predicted an increasing response of surface MDA8 ozone from climate change on the Northeast and Midwest domains.The average effects on climate change are about +1.0-2.5 ppbv and +2.0-2.5 ppbv for GEOS-Chem and CMAQ, respectively, whereas the average effects from reducing emissions are +4.0-7.0 ppbv and +5.0-7.0 ppbv.It is clear that emissions have stronger impacts than the climate change in the regional air quality.On the Southeast domain, inconsistence domain-averaged MDA8 ozone results between GEOS-Chem and CMAQ were observed, where GEOS-Chem results was insensitive to climate change and CMAQ shows a minor increase of the MDA8 ozone (e.g., future ozone subtracted by present ozone).It is believed that the treatment of isoprene nitrate between the models is not major contributor of such differences since both models did not implemented recycling OH − from photo-decomposition of isoprene nitrate.Instead, the differences in implemented chemical mechanisms and grid resolution between the To further investigate the difference between CMAQ and GEOS-Chem on the MDA8 ozone, the Cumulative Distribution Functions were constructed for all four simulated scenarios.These are shown in Fig. 8.The black, green, red, and blue colors represent the scenarios of 2000M 2000E, 2000M 2050E, 2050M 2000E, and 2050M 2050E, respectively.It is observed that CMAQ and GEOS-Chem performed quite similarly in the Northeast and Midwest domains, where the order of the color lines were identical.Distinct separation between the colored lines found in Fig. a,b,d,e demonstrates a discrete relationship was developed among the scenarios.The non-linearity (skew) distribution (e.g., Fig. 8d) indicates a small value of high ozone concentration was found in the CDF.It should be noted when a line is far more up and left, it implied a higher MDA8 ozone distribution has been found.As expected, the order of lines were red, black, blue, and green, and the worst MDA8 ozone air quality occurs in the red line, which corresponds to the future scenario (2049-2051 meteorological conditions with 1999-2001 present emissions) where higher overall temperature with no emissions control.
Since the reduction of emissions was a stronger factor than the increase of temperature from climate change, we would expect that the red and black lines should be more in the up and left position.In the Southeast domain, shown in Fig. 8c and f, the order of the colored lines is somewhat different between GEOS-Chem and CMAQ.In GEOS-Chem (Fig. 8c), the colored lines (red vs. black and green vs. blue) are virtually overlapping and consequently not able to demonstrate the effect of climate change.Conversely, in CMAQ (Fig. 8f), clear separations were found among those lines and the effect of climate change was observed.As mentioned earlier, the inconsistency of the results between GEOS-Chem and CMAQ may relate to differences in chemical mechanism and resolution ( 4• ×5 • vs. 36 km×36 km).Nevertheless, the future climate and air quality predictions in the Southeast have been controversial.
For the comparison between 36 km and 12 km CMAQ simulations in the Southeast, 4-5 ppbv of differences in average MDA8 ozone were found in present and future climate conditions.Since both climate conditions exhibited the same amount of differences, the relationship between the present and future climate on average MDA8 ozone remained the same.On the other hand, significant changes of maximum MDA8 ozone between 36 km and 12 km CMAQ were observed, where the average differences were 15 ppbv for the present climate and 36 ppbv for the future climate.Overall, the results suggested that it is important to use a finer resolution when local maximum MDA8 is concerned.Otherwise, the 36 km resolution should be sufficient for evaluating the future climate trends if the average MDA8 ozone is used.

Future PM 2.5 air quality
For PM 2.5 , since the GEOS-Chem v7.03.06 did not incorporate sufficient PM 2.5 species at the moment, no PM 2.5 comparison between GEOS-Chem and CMAQ will be presented.The maximum and average PM 2.5 from CMAQ were ranged from 96.1 to 127 µg/m 3 and 4.5 to 11.7 µg/m 3 , respectively.It was observed that the effect of climate change had only a minor impact on the future PM 2.5 concentration, whereas the reduction of emissions contributed a significant reduction of PM 2.5 .The total PM 2.5 reductions from present to future was estimated to be about 40 to 50%, in which the average PM 2.5 concentrations from the present climate (average of 2000M 2000E and 2000M 2050E) and the future climate (average of 2050M 2000E and 2050M 2050E) are 8.5-11.5 µg/m 3 and 4.5-7.0µg/m 3 , respectively.For the comparison between 36 km and 12 km CMAQ simulations, no difference in PM 2.5 was found on the future climate trends (not shown).Figure 9 shows the chemical breakdown of PM 2.5 .It was expected that a large portion of PM 2.5 in CMAQ simulations were coming from sulfate aerosols (SA) and organic aerosols (OA).For organic aerosol, no significant change of OA in the future scenario (T4 or 2050M 2050E) was observed.Although researchers have suggested that the increase of temperature might discourage the formation of aerosols by increasing the rate of vaporization (Zhang et al., 2008), a 5% (1 µg/m 3 ) increase of organic aerosols were still found.For sulfate aerosols, a significant reduction of SO 2− 4 was observed in the future scenario due to the large anticipated reduction of SO 2 /SO 4 emissions.The total reduction of sulfate aerosols were around 50%. is believed that the reduction of SO 2− 4 aerosols allows more radicals to be used for the formation of NO − 3 aerosols.However, since the emission of nitrogen oxides was also reduced significantly, the effect from extra radicals have been diminished by the reduction of NO x and yielded an overall 5% reduction of nitrate aerosols.As a result, the overall change of PM 2.5 from present condition (T1, 2000M 2000E) to future condition (T4, 2050M 2050E) maintained at about −40% to −50% and the effect of climate change contributed about 10% change of PM 2.5 , whereas the emissions accounted for about 90% of the change of overall PM 2.5 .

Conclusions
The CMAQ simulation comparisons of using MEGAN and BEIS biogenic emissions on the climate change scenarios were performed in this study.We found that there was a general increase of MDA8 ozone by about 10 to 12% in the Northeast domain when using MEGAN biogenic emissions.No significant effect was found in the Midwest and Southeast domains.The change of MDA8 ozone in the Northeast domain was mainly triggered by the nature of the VOC-limited region of the domain.For PM 2.5 , as expected, all three domains showed an increase of organic aerosols by 15% from using MEGAN biogenic emissions.Since the CMAQ version used in this study did not include the pathway of isoprene aerosols, it was expected that the PM 2.5 results may have been 1-2 µg/m 3 lower than if the isoprene chemistry had been present.Moreover, since a strong increase of isoprene emission was observed in MEGAN in the future climate condition while it was absent from BEIS, it might had also underestimated the impact of PM 2.5 when comparing the difference between MEGAN and BEIS simulations.Nevertheless, the change of biogenic emissions was not strong enough to alter the relationship among different climate scenarios on both ozone and PM 2.5 .Therefore, it is concluded that the relationships among different climate change scenarios is unlikely to change regardless of which biogenic emissions were used.For downscaling, both GEOS-Chem and CMAQ showed an increase of MDA8 ozone in the Midwest and Northeast domains due to climate change.However, disagreement of the ozone results was found in the Southeast domain, where the GEOS-Chem results showed insignificant changes, while CMAQ showed a small increase of MDA8 ozone.It is believed that the coarse resolution used in GEOS-Chem on the study was insufficient to represent the geospatial relationship in the complex terrain region.Moreover, the differences in chemical mechanism and lack of lightning emissions in CMAQ may also contribute the differences.For CMAQ 36 km and CMAQ 12 km study, no significant difference of output results (i.e., the difference between present and future conditions in domain-averaged MDA8 ozone and PM 2.5 ) in the regional average was observed between those two resolutions.For the future climate condition, MDA8 ozone and average PM 2.5 were strongly affected by both climate and emissions.Also, the emissions reduction had stronger effects on MDA8 ozone and average PM 2.5 than the effects from climate change for all three domains.For ozone, the effect from climate change increased the MDA8 ozone by about +2.0-2.5 ppbv, while the emissions reduction decreased the MDA8 ozone by about +5.0-7.0 ppbv.For PM 2.5 , 90% of the reduction in the future concentration was contributed by the emission reduction, where the climate change was only contributed by about 10%.

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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | was used to simulate the present and future air quality in the United States.The GISS GCM III simulation was initialized on 1 June 1950 and continuously simulated to the end of 2050.The resolution of 4 • ×5 • with 23 vertical layers extending from the 2189 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Figure 4a,b show the statistical distributions of maximum daily 1-h and 8-h average O 3 concentrations simulated for the months of MJJAS in 1999-2001.The black and red colors correspond to the 1999-2001 CMAQ simulated value and the CASTNET observed value from 1998-2002, respectively.The dashed lines at the top and bottom of each box plot show the maximum and minimum values for the data.The square box specifies the O 3 values of 75, 50, and 25% tiles and the cross mark shows the monthly mean value.The maximum 1-h and 8-h O 3 concentrations are well reproduced with the mean ozone values slightly under prediction.The average monthly value of O 3 is about 50 to 60 ppbv.The good agreement of O 3 suggests that the CO and NO x emissions used in this study were relatively close to the actual measured emissions from those five years.However, the underestimate also suggests the uncertainty of MM5 meteorological and emissions in CMAQ were derived from our present climate conditions.The O Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | show the MDA8 ozone of CMAQ-MEGAN vs. CMAQ-BEIS for the months of May-September in the year 2000 on the Midwest, Northeast, and Southeast, respectively.The CMAQ-MEGAN represents the CMAQ simulation using 2201 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , and Southeast, respectively (shown on the right side of the figure).The impact of PM 2.5 in Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

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2222Figure 1 .
Figure 1.The CONUS domain with the selected study areas boxed in red.

Figure 2 .
Figure 2. CONUS 36km daily domain totals of average biogenic emissions in 2000: a) 5 Biogenic isoprene and b) total biogenic VOC.

Fig. 1 .Figure 1 .
Fig. 1.The CONUS domain with the selected study areas boxed in red.

Figure 2 .
Figure 2. CONUS 36km daily domain totals of average biogenic emissions in 2000: a) 5 Biogenic isoprene and b) total biogenic VOC.

Figure 1 .
Figure 1.The CONUS domain with the selected study areas boxed in red.

Figure 2 .
Figure 2. CONUS 36km daily domain totals of average biogenic emissions in 2000: a) 5 Biogenic isoprene and b) total biogenic VOC.

Figure 4 .Figure 5 .
Figure 4. Statistical distributions of ozone concentrations for the months of MJJAS in 1999-2001: a) maximum 1-hr (MDA1), and b) 8-hr average ozone (MDA1).The black color corresponds to the 1999-2001 CMAQ simulated value, where as the red color represents the CASTNET observed values from 1998 to 2002. 5

Fig. 4 .
Fig. 4. Statistical distributions of ozone concentrations for the months of MJJAS in 1999-2001: (a) maximum 1-h (MDA1), and (b) 8-h average ozone (MDA1).The black color corresponds to the 1999-2001 CMAQ simulated value, where as the red color represents the CASTNET observed values from 1998 to 2002.

Fig. 6 .
Fig. 6.Scatter plots of MEGAN-MDA8 ozone versus BEIS-MDA8 ozone for the months of May-September in the year 2000 on: (a) Midwest, (b) Northeast, and (c) Southeast.

Figure 6 . 5 Figure7.
Figure 6.Scatter plots of MEGAN-MDA8 ozone versus BEIS-MDA8 ozone for the months of May-September in the year 2000 on: a) Midwest, b) Northeast, and c) Southeast.5

Fig. 7 .
Fig. 7.The annual average of PM 2.5 in the CONUS domain (left), and the annual average organic carbon of PM 2.5 for the Midwest, Northeast, and Southeast.

Figure 8 .
Figure 8.The cumulative probability function of MDA8 ozone for GEOS-Chem and CMAQ: a) Midwest for GEOS-Chem, b) Northeast for GEOS-Chem, c) Southeast for GEOS-Chem, d) Midwest for CMAQ, e) Northeast for CMAQ, and f) Southeast for CMAQ. 5

Figure 8 .Figure 9 .Fig. 9 .
Figure 8.The cumulative probability function of MDA8 ozone for GEOS-Chem and CMAQ: a) Midwest for GEOS-Chem, b) Northeast for GEOS-Chem, c) Southeast for GEOS-Chem, d) Midwest for CMAQ, e) Northeast for CMAQ, and f) Southeast for CMAQ. 5

Table 4 .
Wu et al. (2008b)enarios, marked with the dash line, were intended to investigate the effects of downscaling and the future air quality in the United States.These scenarios are (1) present meteorology with present emissions, (2) present meteorology with future emissions, (3) future meteorology with present emissions and (4) future meteorology with future emissions, which are identical to the scenarios used inWu et al. (2008b), for GEOS-Chem.While the eight scenarios, filled with grey color, were used to study the impacts of change of biogenic emissions (MEGAN vs. BEIS) in the future climate scenarios(2000 and 2050).

Table 1 .
MM5 and CMAQ model configurations for present and future simulations.

Table 4 .
Summary of CMAQ simulations conducted in this study.

Table 5 .
Average zonal temperatures of GISS and MM5 outputs for the present and future climate.JFMA is the average value from Jan., Feb., Mar., and Apr.; MJJAS is the average value from May, Jun., Jul., Aug., and Sep.; OND is the average value from Oct., Nov., and Dec. + Resolution of GISS output is 4 • ×5 •, ++ Only 2000 and 2050 are simulated.

Table 6 .
The percentage change of MDA8 ozone (in ppbv) and PM 2.5 (in µg/m 3 ) for 2000 and 2050.JFMA is the average value from Jan., Feb., Mar., and Apr.; MJJAS is the average value from May, Jun., Jul., Aug., and Sep.; OND is the average value from Oct., Nov., and Dec.

Table 7 .
Summary of MDA8 ozone (in ppbv) from CMAQ outputs and the concentration differences between CMAQ and GEOS-Chem for the present and future climate.