Regional Air Quality Model Research Articles

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 1: Assessing the influence of constrained multi-generational ageing

Abstract. Multi-generational oxidation of volatile organic compound (VOC) oxidation products can significantly alter the mass, chemical composition and properties of secondary organic aerosol (SOA) compared to calculations that consider only the first few generations of oxidation reactions. However, the most commonly used state-of-the-science schemes in 3-D regional or global models that account for multi-generational oxidation (1) consider only functionalization reactions but do not consider fragmentation reactions, (2) have not been constrained to experimental data and (3) are added on top of existing parameterizations. The incomplete description of multi-generational oxidation in these models has the potential to bias source apportionment and control calculations for SOA. In this work, we used the statistical oxidation model (SOM) of Cappa and Wilson (2012), constrained by experimental laboratory chamber data, to evaluate the regional implications of multi-generational oxidation considering both functionalization and fragmentation reactions. SOM was implemented into the regional University of California at Davis / California Institute of Technology (UCD/CIT) air quality model and applied to air quality episodes in California and the eastern USA. The mass, composition and properties of SOA predicted using SOM were compared to SOA predictions generated by a traditional two-product model to fully investigate the impact of explicit and self-consistent accounting of multi-generational oxidation.Results show that SOA mass concentrations predicted by the UCD/CIT-SOM model are very similar to those predicted by a two-product model when both models use parameters that are derived from the same chamber data. Since the two-product model does not explicitly resolve multi-generational oxidation reactions, this finding suggests that the chamber data used to parameterize the models captures the majority of the SOA mass formation from multi-generational oxidation under the conditions tested. Consequently, the use of low and high NOx yields perturbs SOA concentrations by a factor of two and are probably a much stronger determinant in 3-D models than multi-generational oxidation. While total predicted SOA mass is similar for the SOM and two-product models, the SOM model predicts increased SOA contributions from anthropogenic (alkane, aromatic) and sesquiterpenes and decreased SOA contributions from isoprene and monoterpene relative to the two-product model calculations. The SOA predicted by SOM has a much lower volatility than that predicted by the traditional model, resulting in better qualitative agreement with volatility measurements of ambient OA. On account of its lower-volatility, the SOA mass produced by SOM does not appear to be as strongly influenced by the inclusion of oligomerization reactions, whereas the two-product model relies heavily on oligomerization to form low-volatility SOA products. Finally, an unconstrained contemporary hybrid scheme to model multi-generational oxidation within the framework of a two-product model in which ageing reactions are added on top of the existing two-product parameterization is considered. This hybrid scheme formed at least 3 times more SOA than the SOM during regional simulations as a result of excessive transformation of semi-volatile vapors into lower volatility material that strongly partitions to the particle phase. This finding suggests that these hybrid multi-generational schemes should be used with great caution in regional models.

High-resolution ammonia emissions inventories in China from 1980 to 2012

Abstract. Ammonia (NH3) can interact in the atmosphere with other trace chemical species, which can lead to detrimental environmental consequences, such as the formation of fine particulates and ultimately global climate change. China is a major agricultural country, and livestock numbers and nitrogen fertilizer use have increased drastically since 1978, following the rapid economic and industrial development experienced by the country. In this study, comprehensive NH3 emissions inventories were compiled for China for 1980–2012. In a previous study, we parameterized emissions factors (EFs) considering ambient temperature, soil acidity, and the method and rate of fertilizer application. In this study, we refined these EFs by adding the effects of wind speed and new data from field experiments of NH3 flux in cropland in northern China. We found that total NH3 emissions in China increased from 5.9 to 11.1 Tg from 1980 to 1996, and then decreased to 9.7 Tg in 2012. The two major contributors were livestock manure and synthetic fertilizer application, which contributed 80–90 % of the total emissions. Emissions from livestock manure rose from 2.86 Tg (1980) to 6.16 Tg (2005), and then decreased to 5.0 Tg (2012); beef cattle were the largest source followed by laying hens and pigs. The remarkable downward trend in livestock emissions that occurred in 2007 was attributed to a decrease in the numbers of various livestock animals, including beef cattle, goats, and sheep. Meanwhile, emissions from synthetic fertilizer ranged from 2.1 Tg (1980) to 4.7 Tg (1996), and then declined to 2.8 Tg (2012). Urea and ammonium bicarbonate (ABC) dominated this category of emissions, and a decline in ABC application led to the decrease in emissions that took place from the mid-1990s onwards. High emissions were concentrated in eastern and southwestern China. Seasonally, peak NH3 emissions occurred in spring and summer. The inventories had a monthly temporal resolution and a spatial resolution of 1000 m, and thus are suitable for global and regional air-quality modeling.

Simulated seasonal variations in nitrogen wet deposition over East Asia

The regional air quality modeling system Regional Atmospheric Modeling System–Community Multiscale Air Quality was applied to estimate the spatial distribution and seasonal variation in nitrogen wet deposition over East Asia in 2010. The simulated results were evaluated by comparing modeled precipitation rates and ion concentrations, such as ammonium (), nitrate (), and sulfate, in rainwater, against observations obtained from Acid Deposition Monitoring Network in East Asia and meteorological stations in China. Comparison of simulated and observed precipitation showed that the modeling system can reproduce seasonal precipitation patterns reasonably well. For major ion species, the simulated results in most cases were in good agreement with those observed. Analysis of the modeled wet deposition distributions indicated that China experiences noticeable variation in wet deposition patterns throughout the year. Nitrogen wet deposition () during summer and spring accounted for 71% of the annual total (3.9 Tg N yr−1), including 42.7% in summer. Precipitation plays a larger role in the seasonal variation of wet deposition; whereas, aerosol concentrations affect its distribution patterns. In China, the amount of annual nitrogen wet deposition ranged from 1 to 18 kg N ha−1. Nitrogen in wet deposition was mainly in the form of , accounting for 65.76% of the total amount, and the molar ratio of was mostly more than 1, indicating a relatively larger effect from agricultural activities.

Constraining NOx emissions using satellite NO2 measurements during 2013 DISCOVER-AQ Texas campaign

Reliable emission inventories are key to precisely model air pollutant concentrations. The relatively large reduction in NOx emissions that is well corroborated by satellite and in-situ observations over southeast Texas has resulted in discrepancies between observations and regional model simulations based on the National Emission Inventory (NEI) provided every three years in U.S. In this study, a Bayesian inversion of OMI tropospheric NO2 is conducted to update anthropogenic sources of NEI-2011 and soil-biogenic sources from BEIS3 (Biogenic Emission Inventory System version 3) over southeast Texas and west Louisiana during the 2013 DISCOVER-AQ Texas campaign. Results reveal that influences of the a priori profile used in OMI NO2 retrieval play a significant role in inconsistencies between model and satellite observations, which should be mitigated. A posteriori emissions are produced using the regional Community Multiscale Air Quality (CMAQ) model associated with Decoupled Direct Method (DDM) sensitivity analysis. The inverse estimate suggests a reduction in area (44%), mobile (30%), and point sources (60%) in high NOx areas (ENOx> 0.2 mol/s), and an increase in soil (∼52%) and area emissions (37%) in low NOx regions (ENOx< 0.02 mol/s). The reductions in anthropogenic sources in high NOx regions are attributed to both uncertainty of the priori and emissions policies, while increases in area and soil-biogenic emissions more likely resulted from under-estimation of ships emissions, and the Yienger- Levy scheme used in BEIS respectively. In order to validate the accuracy of updated NOx emissions, CMAQ simulation was performed and results were evaluated with independent surface NO2 measurements. Comparing to surface monitoring sites, we find improvements (before and after inverse modeling) for MB (1.95, −0.30 ppbv), MAB (3.65, 2.60 ppbv), RMSE (6.13, 4.37 ppbv), correlation (0.68, 0.69), and IOA (0.76, 0.82). The largest improvement is seen for morning time surface NO2 for which RMSE and MB are reduced considerably by ∼60% (5.05 to 2.07 ppbv) and 109% (3.49 to −0.3 ppbv). However, under-prediction of model NO2 in Houston on 09/25–09/26 likely resulting from unprecedented local NOx sources from the Houston Ship Channel (HSC) becomes more evident. Overall, results show that use of OMI tropospheric NO2 columns can substantially reduce the uncertainty of bottom-up emissions for a regional study which should be extended to larger domains (e.g. entire U.S. or North America).

Aramis un modelo regional para la gestión de la calidad del aire. Evaluación y validación

The aim of this research was to better understand the dynamics of air pollutants and to forecast the air quality over regional areas in order to develop emission abatement strategies for air pollution and adverse health effects. To accomplish this objective, we developed and applied a high resolution Eulerian system named ARAMIS (A Regional Air Quality Modelling Integrated System) over the north-east of Spain (Catalonia), where several pollutants exceed threshold values for the protection of human health. The results indicate that the model reproduced reasonably well observed concentrations, as statistical values fell within Environmental Protection Agency (EPA) recommendations and European (EU) regulations. Nevertheless, some hourly O3 exceedances in summer and hourly peaks of NO2 in winter were underestimated. Concerning PM10 concentrations less accurate model levels were obtained with a moderate trend towards underestimation during the day.

Emissions of hydrogen cyanide from on-road gasoline and diesel vehicles

Hydrogen cyanide (HCN) is considered a marker for biomass burning emissions and is a component of vehicle exhaust. Despite its potential health impacts, vehicular HCN emissions estimates and their contribution to regional budgets are highly uncertain. In the current study, Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) was used to measure HCN emission factors from the exhaust of individual diesel, biodiesel and gasoline vehicles. Laboratory emissions data as a function of fuel type and driving mode were combined with ambient measurement data and model predictions. The results indicate that gasoline vehicles have the highest emissions of HCN (relative to diesel fuel) and that biodiesel fuel has the potential to significantly reduce HCN emissions even at realistic 5% blend levels. The data further demonstrate that gasoline direct injection (GDI) engines emit more HCN than their port fuel injection (PFI) counterparts, suggesting that the expected full transition of vehicle fleets to GDI will increase HCN emissions. Ambient measurements of HCN in a traffic dominated area of Toronto, Canada were strongly correlated to vehicle emission markers and consistent with regional air quality model predictions of ambient air HCN, indicating that vehicle emissions of HCN are the dominant source of exposure in urban areas. The results further indicate that additional work is required to quantify HCN emissions from the modern vehicle fleet, particularly in light of continuously changing engine, fuel and after-treatment technologies.

수도권 대기질 모델링 정확도 향상을 위한 WRF모델링: 계절별 물리옵션 민감도 연구

In order to improve the prediction of the regional air quality modeling in the Seoul metropolitan area, a sensitivity analysis using two PBL and microphysics (MP) options of the WRF model was performed during four seasons. The results from four sets of the simulation experiments (EXPs) showed that meteorological variables (especially wind field) were highly sensitive to the choice of PBL options (YSU or MYJ) and no significant differences were found depending on MP options (WDM6 or Morrison) regardless of specific time periods, i.e. day and night, during four seasons. Consequently, the EXPs being composed of YSU PBL option were identified to produce better results for meteorological elements (especially wind field) regardless of seasons. On the other hand, the accuracy of all simulations for summer and winter was somewhat lower than those for spring and autumn and the effect according to physics options was highly volatile by geographical characteristics of the observation site.

Simulating reactive nitrogen, carbon monoxide, and ozone in California during ARCTAS-CARB 2008 with high wildfire activity

Predictions of O_3, CO, total NO_y and individual NO_y species (NO, NO_2, HNO_3, PAN, alkyl nitrates and aerosol nitrate) from a fine resolution regional air quality modeling system for the South Coast Air Basin (SoCAB) and San Joaquin Valley Air Basin (SJVAB) of California are presented and evaluated for the 2008 ARCTAS-CARB campaign. The measurements of the chemical compounds from the fire plumes during the field campaign allow for the evaluation of the model's ability to simulate fire-influenced air masses as well. In general, the model successfully simulated the broad spatial distribution of chemical compounds in both air basins as well as the variation within the basins. Using inventories that reflect 2008 emissions levels, the model performed well in simulating NO_x (NO + NO_2) in SoCAB. Therefore, the under prediction of O_3 over these areas is more likely caused by uncertainties with the VOC emissions, chemistry, or discrepancies in the meteorology. The model did not capture the relatively high levels of O_3, and some reactive nitrogen species that were measured off shore of the SoCAB, indicating potential missing sources or the transport from on shore to off shore was not successfully captured. In SJVAB, the model had good performance in simulating different chemical compounds in the Fresno and Arvin areas. However, enhanced concentrations of O_3, NO_x, HNO_3 and PAN near dairy farms were significantly underestimated in the model. Negative biases also exist for O_3 and HNO_3 near oil fields, suggesting larger uncertainties associated with these emission sources. While the model simulated the total NO_y mixing ratios reasonably well, the prediction for partitioning between individual compounds showed larger uncertainties in the model simulation. Although the fire emissions inventory was updated to include the latest emissions estimates and speciation profiles, our model shows limited improvement in simulating the enhancement of O_3, CO, and PAN under fire impact as compared to a previous version of the modeling system. Further improvements in simulating fire emissions, especially the timing and the plume injection heights, are desired in order to better simulate the impact of fires.

Evidence for an increase in the ozone photochemical lifetime in the eastern United States using a regional air quality model

AbstractMeasures to control surface ozone rely on quantifying production attributable to local versus regional (upwind) emissions. Here we simulate the relative contribution of local (i.e., within a particular state) and regional sources of surface ozone in the eastern United States (66–94°W longitude) for July 2002, 2011, and 2018 using the Comprehensive Air‐quality Model with Extensions (CAMx). To determine how emissions and chemistry within the domain affect the production, loss, lifetime, and transport of trace gases, we initialize our model with identical boundary conditions in each simulation. We find that the photochemical lifetime of ozone has increased as emissions have decreased. The contribution of ozone from outside the domain (boundary condition ozone, BCO3) to local surface mixing ratios increases in an absolute sense by 1–2 ppbv between 2002 and 2018 due to the longer lifetime of ozone. The photochemical lifetime of ozone lengthens because the two primary gas phase sinks for odd oxygen (Ox ≈ NO2 + O3)—attack by hydroperoxyl radicals (HO2) on ozone and formation of nitrate—weaken with decreasing pollutant emissions. The relative role of BCO3 will also increase. For example, BCO3 represents 34.5%, 38.8%, and 43.6% of surface ozone in the Baltimore, MD, region during July 2002, 2011, and 2018 means, respectively. This unintended consequence of air quality regulation impacts attainment of the National Ambient Air Quality Standard for surface ozone because the spatial and temporal scales of photochemical smog increase; the influence of pollutants transported between states and into the eastern U.S. will likely play a greater role in the future.

A modeling study of severe winter haze events in Beijing and its neighboring regions

A Regional Air Quality Model System (RAQMS) with a series of ground observations and satellite retrievals was utilized to investigate haze events in January 2013, in which the observed maximum daily mean surface PM2.5 concentrations in Beijing exceeded 400μgm−3. The model predicted a monthly mean PM2.5 concentration of 200–300μgm−3 over southern Beijing, Tianjin, and the southern Hebei province, with most aerosols restricted within 500m above ground. Meteorology played an important role in haze formation. Aerosols were transported into Beijing and Tianjin from the south to the north at altitudes below 1.5km during haze episodes. Sensitivity simulations revealed that nearly 44% of surface PM2.5 in Beijing was contributed by local emissions with the remaining 56% coming from surrounding sources in terms of monthly mean and the outside contribution increased to 62% during episode 2, suggesting the important influence of regional trans-boundary transport on Beijing haze pollution.

Quantitative DNA Analyses for Airborne Birch Pollen.

Birch trees produce large amounts of highly allergenic pollen grains that are distributed by wind and impact human health by causing seasonal hay fever, pollen-related asthma, and other allergic diseases. Traditionally, pollen forecasts are based on conventional microscopic counting techniques that are labor-intensive and limited in the reliable identification of species. Molecular biological techniques provide an alternative approach that is less labor-intensive and enables identification of any species by its genetic fingerprint. A particularly promising method is quantitative Real-Time polymerase chain reaction (qPCR), which can be used to determine the number of DNA copies and thus pollen grains in air filter samples. During the birch pollination season in 2010 in Mainz, Germany, we collected air filter samples of fine (<3 μm) and coarse air particulate matter. These were analyzed by qPCR using two different primer pairs: one for a single-copy gene (BP8) and the other for a multi-copy gene (ITS). The BP8 gene was better suitable for reliable qPCR results, and the qPCR results obtained for coarse particulate matter were well correlated with the birch pollen forecasting results of the regional air quality model COSMO-ART. As expected due to the size of birch pollen grains (~23 μm), the concentration of DNA in fine particulate matter was lower than in the coarse particle fraction. For the ITS region the factor was 64, while for the single-copy gene BP8 only 51. The possible presence of so-called sub-pollen particles in the fine particle fraction is, however, interesting even in low concentrations. These particles are known to be highly allergenic, reach deep into airways and cause often severe health problems. In conclusion, the results of this exploratory study open up the possibility of predicting and quantifying the pollen concentration in the atmosphere more precisely in the future.

Comparison of aerosol hygroscopicity and mixing state between winter and summer seasons in Pearl River Delta region, China

Hygroscopic properties of aerosol particles are important for determining aerosol size distributions, and thus determining scattering and absorption coefficients at ambient atmospheric conditions. In this study, hygroscopic properties of aerosol particles at an urban site in Guangzhou, China, were measured using a Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA) system during the winter and the summer. The results show that the urban aerosols were composed of more-hygroscopic, less-hygroscopic and non-hygroscopic particles. For less-hygroscopic particles of 40–200nm in diameter, the hygroscopic parameter κLH was around 0.15. For more-hygroscopic particles, the κMH was from 0.290 to 0.339 with a particle size from 40 to 200nm. For non-hygroscopic particles, the κNH was about 0.015. It was found that the number fraction of less-hygroscopic particles (NFLH) was correlated with the atmospheric oxidation which can be presented by OC/EC. This paper attributed the larger NFLH in winter to the higher value of OC/EC (3.0). Such conditions may lead to more formation of less-hygroscopic particles. Backward trajectories cluster analysis shows that there is a certain link between air mass origin and aerosol hygroscopicity, but it seems to be independent of the level of pollution. The difference of NFNH indicates that the mixing state of aerosol particles can also be affected by air mass origin. Diurnal variations in aerosol hygroscopic parameters in both seasons show that during daytime, aerosol particles tend to have a low degree of external mixing or quasi-internal mixing, resulting in a higher NFMH and a larger κmean; during nighttime and early mornings, they tend to be mixed externally, resulting in a lower NFMH and a smaller κmean. This can be attributed to atmospheric aging effect and evolution of mixing layer height and implies that soot (non-hygroscopic) particles present to a large extent as internal mixtures by the time they leave the urban environment. Hence, only assuming a constant mixing state of soot particles, such as pure external or internal for the regional climate model and air quality model is still not realistic and may lead to uncertainties for the Pearl River Delta (PRD) region which is one of the three major economic regions in China. Comparing the diurnal variation of NFNH in both seasons, it seems that such a diurnal cycle was mainly related to the differences in evolution of mixing layer between two seasons. Such quantitative hygroscopic properties of sub-micro particles are essential in assessing their impact on weather–climate effect and atmospheric visibility.

Toxic volatile organic air pollutants across Canada: multi-year concentration trends, regional air quality modelling and source apportionment

A Unified Regional Air-quality Modelling System, AURAMS, was expanded to predict six toxic volatile organic compounds (VOCs) within a continental domain and two nested domains covering eastern and western Canada. The model predictions were evaluated against Environment Canada’s National Air Pollution Surveillance (NAPS) data set to assess the predictive capability of the model at daily and seasonal time scales. The predictions were also evaluated with satellite-derived column total maps for formaldehyde, carbon monoxide, and nitrogen dioxide. In general, the model showed fair to good predictive skill in terms of both correlation (R) and normalized mean bias (NMB) for benzene (R = 0.53 NMB = 26 %), formaldehyde (R = 0.73, NMB = −15 %) and acetaldehyde (R = 0.55, NMB = 29 %). For the other toxics VOCs, the model showed less predictive skill in the order 1,2,4-trimethylbenzene (R = 0.50, NMB = −41 %), 1,3-butadiene (R = 0.26, NMB = 40 %) and acrolein (R = 0.052, NMB = −51 %). The goal of this study was to apply an air quality model to assess the contribution of mobile sources to ambient levels of toxic VOCs at urban locations across Canada. The mobile source contribution varied in a complex manner for each species for different regions. For benzene and 1,2,4-trimethylbenzene, the mobile source contribution was in the range 40–65 % for major Canadian cities. The model predicted considerably lower mobile source contributions for rural locations in the Canadian Prairies, where other area sources dominate, such as the petrochemical industry. Measured concentration trends in toxics are also presented from 2004 to 2010. The primary emitted toxics declined gradually (13–16 % over 6 yr) whereas the toxic aldehydes showed no trend.

Evaluation of modeled surface ozone biases as a function of cloud cover fraction

Abstract. A regional air-quality forecast system's model of surface ozone variability based on cloud coverage is evaluated using satellite-observed cloud fraction (CF) information and a surface air-quality monitoring system. We compared CF and daily maximum ozone from the National Oceanic and Atmospheric Administration's National Air Quality Forecast Capability (NOAA NAQFC) with CFs from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Environmental Protection Agency's AirNow surface ozone measurements during May to October 2014. We found that observed surface ozone shows a negative correlation with the MODIS CFs, showing around 1 ppb decrease for 10 % MODIS CF change over the contiguous United States, while the correlation of modeled surface ozone with the model CFs is much weaker, showing only −0.5 ppb per 10 % NAQFC CF change. Further, daytime CF differences between MODIS and NAQFC are correlated with modeled surface-ozone biases between AirNow and NAQFC, showing −1.05 ppb per 10 % CF change, implying that spatial and temporal misplacement of the modeled cloud field might have biased modeled surface ozone level. Current NAQFC cloud fields seem to have fewer CFs compared to MODIS cloud fields (mean NAQFC CF = 0.38 and mean MODIS CF = 0.55), contributing up to 35 % of surface-ozone bias in the current NAQFC system.

Use of high-order sensitivity analysis and reduced-form modeling to quantify uncertainty in particulate matter simulations in the presence of uncertain emissions rates: A case study in Houston

Abstract Regional air quality models are widely used to evaluate control strategy effectiveness. As such, it is important to understand the accuracy of model simulations to establish confidence in model performance and to guide further model development. Particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) is regulated as one of the criteria pollutants by the National Ambient Air Quality Standards (NAAQS), and PM2.5 concentrations have a complex dependence on the emissions of a number of precursors, including SO2, NOx, NH3, VOCs, and primary particulate matter (PM). This study quantifies how the emission-associated uncertainties affect modeled PM2.5 concentrations and sensitivities using a reduced-form approach. This approach is computationally efficient compared to the traditional Monte Carlo simulation. The reduced-form model represents the concentration-emission response and is constructed using first- and second-order sensitivities obtained from a single CMAQ/HDDM-PM simulation. A case study is conducted in the Houston-Galveston-Brazoria (HGB) area. The uncertainty of modeled, daily average PM2.5 concentrations due to uncertain emissions is estimated to fall between 42% and 52% for different simulated concentration levels, and the uncertainty is evenly distributed in the modeling domain. Emission-associated uncertainty can account for much of the difference between simulation and ground measurements as 60% of observed PM2.5 concentrations fall within the range of one standard deviation of corresponding simulated PM2.5 concentrations. Uncertainties in meteorological fields as well as the model representation of secondary organic aerosol formation are the other two key contributors to the uncertainty of modeled PM2.5. This study also investigates the uncertainties of the simulated first-order sensitivities, and found that the larger the first-order sensitivity, the lower its uncertainty associated with emissions. Sensitivity of PM2.5 to primary PM has the lowest uncertainty while sensitivity of PM2.5 to VOC has the highest uncertainty associated with emission inputs.

Estimate Mortality Attributable To PM2.5 Exposure In China With Assimilated PM2.5 Concentrations Based On Ground Monitoring Network And A Regional Air Quality Model

Background. Significant progresses have been made to estimate the health burden attributable to exposure to ambient air pollutants, such as retrieval surface PM2.5 concentration from satellite observed aerosol optical depth. While in China, surface monitoring network of air pollutants has been expanding drastically. Assimilating the concentrations of ground monitoring network with regional air quality model could provide surface concentration of PM2.5 with much higher spatial and temporal resolution. Methods. PM2.5 concentrations in 2013 were estimated with the Nested Air Quality Prediction Modeling System (NAQPMS) using measured concentrations of air pollutants from more than 300 monitoring stations, data assimilation method based on ensemble Kalman filter was used to improve surface PM2.5 simulation. The provincial permanent population and age-specific mortalities were obtained from statistical year book in China at both central and provincial levels. Attributable mortalities including ischemic heart disease (IHD), cerebrovascular disease (stroke), chronic obstructive pulmonary disease (COPD), and lung cancer (LC) in adults were estimated using the integrated exposure-response (IER) model. Results. In 2013 in China, exposure to PM2.5 was associated with 0.69, 0.35, 0.14 and 0.14 million of premature deaths from stroke, IHD, LC and COPD disease. All together, about 1.33 million premature deaths were attributed to PM2.5 exposure. Northern China and Yangtze River Delta have the highest mortality attributable to PM2.5. Conclusions. Assimilation results of PM2.5 concentration from monitoring network with regional air quality model has been successfully used to estimate mortality attributable to PM2.5, the results are comparable with that of the Global Burden of Disease Study 2010.

Observation and modeling of black soil wind-blown erosion from cropland in Northeastern China

Abstract As the nation’s bread basket, Northeastern China has experienced dramatic land use changes in the past decades, with much natural land being converted into cropland to feed the growing population. The long dormant season, coupled with frequent cold fronts and strong spring winds, makes the exposed cropland vulnerable to wind erosion. However, the rates and spatial–temporal characteristics of wind erosion in this particular soil type have been poorly studied. The present study aimed to measure and simulated the wind erosion characteristics from black soil cropland in the Dehui region of Northeastern China. Our results showed that wind-blown erosion was positively correlated with wind speed and negatively linked to soil moisture, vegetation and soil roughness in this region. The measured threshold friction velocity was 4.47 m/s at 2 m height, corresponding to 0.37 m/s at the surface ground. Based on WRF-CMAQ-FENGSHA model, we localized the parameters and simulated a significant wind erosion event in the Dehui region on May 31, 2013. The relationships between modeled dust flux and ground measurement were correlated (R2 = 0.78). In addition, the modeled aerosol optical depths were also captured by satellite observations (MODIS and CALIPSO). Our results indicate that the bare farmland areas over Northeastern China are important dust sources over this region, and should not be neglected in regional air quality models. The use of protective farming techniques, protection of grassland and plowing in autumn for cropland areas should be considered to combat dust emission.

Evaluating NOx emission inventories for regulatory air quality modeling using satellite and air quality model data

The purpose of this study was to assess the accuracy of NOx emissions in the Texas Commission on Environmental Quality's (TCEQ) State Implementation Plan (SIP) modeling inventories of the southeastern U.S. We used retrieved satellite tropospheric NO2 columns from the Ozone Monitoring Instrument (OMI) together with NO2 columns from the Comprehensive Air Quality Model with Extensions (CAMx) to make top–down NOx emissions estimates using the mass balance method. Two different top–down NOx emissions estimates were developed using the KNMI DOMINO v2.0 and NASA SP2 retrievals of OMI NO2 columns. Differences in the top–down NOx emissions estimates made with these two operational products derived from the same OMI radiance data were sufficiently large that they could not be used to constrain the TCEQ NOx emissions in the southeast. The fact that the two available operational NO2 column retrievals give such different top–down NOx emissions results is important because these retrievals are increasingly being used to diagnose air quality problems and to inform efforts to solve them. These results reflect the fact that NO2 column retrievals are a blend of measurements and modeled data and should be used with caution in analyses that will inform policy development. This study illustrates both benefits and challenges of using satellite NO2 data for air quality management applications. Comparison with OMI NO2 columns pointed the way toward improvements in the CAMx simulation of the upper troposphere, but further refinement of both regional air quality models and the NO2 column retrievals is needed before the mass balance and other emission inversion methods can be used to successfully constrain NOx emission inventories used in U.S. regulatory modeling.

Sources and formation pathways of organic aerosol in a subtropical metropolis during summer

A field campaign combined with numerical simulations was designed to better understand the emission sources and formation processes of organic aerosols (OA) in a subtropical environment. The field campaign measured total and water soluble organic carbon (OC) in aerosol, as well as its precursor gases in the Taipei metropolis and a nearby rural forest during the summer of 2011. A regional air-quality model modified with an additional secondary organic aerosol (SOA) formation pathway was used to decipher the observed variations in OA, with focus on various formation pathways and the relative contributions from anthropogenic and biogenic sources.According to the simulations, biogenic sources contributed to 60% and 72% of total OA production at the NTU (urban) and HL (rural) sites. The simulated fractions of SOA in total OA were 67% and 79% near the surface of NTU and HL, respectively, and these fractions increased with height and reach over 90% at the 1-km altitude. Estimated from the simulation results, aqueous-phase dicarbonyl uptake was responsible of 51% of OA production in the urban area, while the primary emissions, reversible partitioning of semi-volatile oxidation products, oligomerization of semi-volatile SOA in the particulate phase and acid-enhanced oxidation contributed to 33%, 10%, 5% and 1% respectively; in the rural area, the percentages were 59%, 21%, 13%, 7% and 1%, respectively. Meteorological factors, including large-scale wind direction, local circulation and planetary boundary layer height, all have strong influences on the source contributions and diurnal variations of OA concentration.

Numerical Simulation of CO 2 Concentrations in East Asia with RAMS-CMAQ

AbstractThe regional air quality modeling system RAMS-CMAQ (Regional Atmospheric Modeling System and Models-3 Community Multi-scale Air Quality) was developed by incorporating a vegetation photosynthesis and respiration module (VPRM) and used to simulate temporal-spatial variations in atmospheric CO2 concentrations in East Asia, with prescribed surface CO2 fluxes (i.e., fossil fuel emission, biomass burning, sea-air CO2 exchange, and terrestrial biosphere CO2 flux). Comparison of modeled CO2 mixing ratios with eight ground-based in-situ measurements demonstrated that the model was able to capture most observed CO2 temporal-spatial features. Simulated CO2 concentrations were generally in good agreement with observed concentrations. Results indicated that the accumulated impacts of anthropogenic emissions contributed more to increased CO2 concentrations in urban regions relative to remote locations. More-over, RAMS-CMAQ analysis demonstrates that surface CO2 concentrations in East Asia are strongly influenc...