Regional Air Quality Modeling System Research Articles

Impacts of open biomass burning in Southeast Asia on atmospheric PM2.5 concentrations over south China from 2009 to 2018

Open biomass burning (BB) frequently occurs in spring over Southeast Asia (SEA). The concentration of fine particulate (PM2.5) produced by BB and its impacts on air quality in downwind aeras exhibit significant interannual variations, which are controlled by emission intensity and meteorological circulation. In this study, a regional air quality model system (RAQMS) was applied to investigate the contributions of BB emissions in SEA to atmospheric PM2.5 concentrations over South China in March (a spring month) during 2009–2018 and their interannual variations. Higher near-surface BB-PM2.5 (refers to the PM2.5 produced by BB in SEA) concentrations and contributions were mainly distributed in the source region and its vicinity, while the higher tropospheric BB-PM2.5 concentrations and contributions were characterized by a long belt extending from BB source regions to Yangtze River Delta (YRD) in South China. Combined with the vertical distribution of BB-PM2.5 on the transported path profile, it indicated that higher BB-PM2.5 concentrations were mainly concentrated in 0∼1500 m above the ground over source regions, while the maximum BB-PM2.5 concentrations in the downwind area were distributed in 1500∼3500 m above the ground. The monthly mean tropospheric BB-PM2.5 concentrations were higher in March 2009, 2010, 2012, and 2013, with evident correlation with interannual variation of BB emissions. Sensitivity experiments suggested that the near-surface and tropospheric BB-PM2.5 concentrations over South China had changed by-48.1%∼190.5% and −48.0%∼213.8%, respectively in March 2009–2018 by fixing BB emissions unchanged at the mean of the 10 years, being greater than the changes caused by meteorological conditions and other affecting factors (∼20%). In addition, the relative contributions of BB emission from various regions in SEA on the mean near-surface and tropospheric BB-PM2.5 concentrations over South China were further identified.

Impacts of Biomass Burning in Southeast Asia on Tropospheric CO2 Concentration Over South China

AbstractThe field observations imply that the long‐range transport of carbon dioxide (CO2) emitted by biomass burning (BB) in Southeast Asia might impact the atmospheric CO2 in South China, while the transboundary path and the contributions of long‐range transport on atmospheric CO2 concentrations in South China remain poorly understood. In this study, a regional air quality model system (RAQMS) was developed by incorporating the atmospheric process of CO2 to investigate the impacts of BB in Southeast Asia on tropospheric CO2 concentration over South China in spring during 2009–2018. CO2 emissions from BB in Southeast Asia in spring varied greatly from 2009 to 2018, and high monthly mean emissions were concentrated in the west of Myanmar, the border between Myanmar, Thailand and Laos, the north of Laos, and Cambodia, with the maximum reaching 1.0 g m−2 hr−1. Higher monthly mean concentrations of near surface CO2 and tropospheric CO2 produced by BB were mainly distributed in the source regions of Southeast Asia and South China. The monthly mean tropospheric CO2 concentrations produced by BB in Southeast Asia were higher in March 2010, 2014, and 2015, which were obviously related to the interannual variation of BB emission, and affected by the atmospheric circulation as well. The contribution of BB emission in Southeast Asia to the net change of tropospheric CO2 concentration in South China presented a belt distribution from the southwest to the northeast, with a domain average of 5.7%–38.6% over South China in March 2009–2018.

Numerical analysis of CH4 concentration distributions over East Asia with a regional chemical transport model

Atmospheric CH4 concentrations have increased rapidly and exhibited large spatiotemporal variations. But their values were generally fixed in regional air quality models, without considering the processes of emissions, transport, and diffusion. In this study, a regional air quality modeling system RAMS-CMAQ was developed by incorporating the emissions, transport, and diffusion processes of CH4 to produce CH4 concentration distributions. The developed model was applied to simulate CH4 concentrations over East Asia in 2020. As a result, the comparisons between the simulated CH4 vertical column densities (VCDS) and the observations derived from GOSAT showed that the developed model can reasonably reflect the crucial features in CH4 concentration variations with the correlation coefficients larger than 0.94. The temporal-spatial patterns of surface CH4 concentrations showed that concentrations were high (≥2.3 ppm) over Sichuan Basin, central-eastern China and South China as well as India, where the highest was in summer because of the largest agricultural emissions, and the lowest was in spring due to less emissions and stronger OH sinks compared to winter. The low surface CH4 concentrations (≤1.9 ppm) appeared over Northwest China with small seasonal variations (high in summer and low in winter and autumn) and less local emissions. The temporal-spatial patterns of CH4 VCDS showed that VCDS were high (3.6–4.5 × 1019 molec/cm2) over eastern China with significant seasonal variations (high in summer and autumn), and low (≤3.0 × 1019 molec/cm2) over Tibet Plateau and western Mongolia with slight variations.

Changes in summer biogenic volatile organic compound emission and secondary organic aerosols over the 2001–2018 period over China: Roles of leaf biomass, meteorology, and anthropogenic emission variability

A regional air quality model system (RAQMS), coupled with a biogenic emission model was applied to investigate the variations of summertime biogenic volatile organic compound (BVOC) emission and secondary organic aerosols (SOA) during 2001–2018 over China. During 2001–2018, evident land use changes occurred, especially in the Sichuan Basin, the Qinling Mountains, and the megacities over east China. Leaf aera index (LAI) increased significantly over the western parts of northeast China, the Qinling Mountains, the North China Plain (NCP), and most areas of south China. The domain-average LAI and BVOC emission increased by 0.2 m2 m−2 (19%) and 3.0 Tg (26%), respectively, over China during 2001–2018, mainly due to the increases in LAI and air temperature. It is found that near surface BSOA concentration increased apparently over China from 2001 to 2018, with the maximum increment exceeded 2 μg m−3 (75%) in the middle reaches of the Yangtze River. The domain-average surface BSOA concentration increased remarkably by 0.44 μg m−3 (41%) over China, resulting from the combined effect of LAI and anthropogenic emission increases, and meteorological change, in which the land use and LAI changes were the dominant driving factors, explaining over 50% of the BSOA increase, while the changes in meteorology and anthropogenic emission contributed almost equally to the remaining BSOA increase.

Emission, transport, deposition, chemical and radiative impacts of mineral dust during severe dust storm periods in March 2021 over East Asia

A Regional Air Quality Model System (named RAQMS) coupled with a developed dust model driven by WRF was applied to synthetically investigate the emission, transport, deposition, budget, and chemical and radiative effects of mineral dust during the severe dust storm periods of 10–31 March 2021. Model results were validated against a variety of ground, vertical and satellite observations, which demonstrated a generally good model ability in reproducing meteorological variables, particulate matter and compositions, and aerosol optical properties. The first dust storm (DS1), which was the severest one since 2010 was originated from the Gobi Desert in southern Mongolia on 14 March, with the dust emission flux reaching 2785 μg m−2 s−1 and the maximum dust concentration exceeding 18,000 μg m−3 in the dust deflation region. This dust storm resulted in remarkably high hourly PM10 observations up to 7506 μg m−3, 1887 μg m−3, and 2704 μg m−3 in Beijing, Tianjin, and Shijiazhuang on 15 March, respectively, and led to a maximum decrease in surface shortwave radiation up to 313.4 W m−2 (72 %) in Beijing. The second dust storm (DS2) broke out in the deserts of eastern Mongolia, with lower dust emission than the first one. The extinction of shortwave radiation by dust aerosols led to a reduction in photolysis rate and consequently decreases in O3 and secondary aerosol concentrations over the North China Plain (NCP), whereas total sulfate and nitrate concentrations consistently increased due to heterogeneous reactions on dust surfaces over the middle reaches of the Yellow River and the NCP region during DS1. Sulfate and nitrate formation through heterogeneous reactions were enhanced in the dust backflow on 16–17 March by approximately 18 % and 24 % on average in the NCP. Heterogeneous reactions and photolysis rate reduction by mineral dust jointly led to average changes in sulfate, nitrate, ammonium, and secondary organic aerosol (SOA) concentrations by 13.0 %, 13.5 %, −12.3 %, and −4.4 %, respectively, in the NCP region during DS1, larger than the changes in the Yangtze River Delta (YRD). The maximum dry deposition settled in the 7–11 μm size range in downwind land and ocean areas, while wet deposition peaked in the 4.7–7 μm size range in the entire domain. Wet deposition was approximately twice the dry deposition over mainland China except for dust source regions. During 10–31 March, the total dust emission, dry and wet depositions were estimated to be 31.4 Tg, 13.78 Tg and 4.75 Tg, respectively, with remaining 12.87 Tg of dust aerosols (41 % of the dust emission) suspending in the atmosphere or transporting to other continents and oceans.

Secondary organic aerosol formation and source contributions over east China in summertime

Various precursor emissions and chemical mechanisms for secondary organic aerosol (SOA) formation were incorporated into a regional air quality model system (RAQMS) and applied to investigate the distribution, composition, and source contribution of SOA over east China in summer 2018. Model comparison against a variety of observations at a national scale demonstrated that the model was able to reasonably reproduce meteorological variables, O3 and PM2.5 concentrations, and the model simulated SOA concentration generally agreed with observations, with the overall NMB of 7.0% and R of 0.4 in 10 cities over east China. The simulated period-mean SOA concentrations of 4–15 μg m−3 were mainly distributed over the North China Plain (NCP), the middle and lower reaches of the Yangtze River and Chongqing district. SOA dominated organic aerosol (OA) over China in summertime (90%). The percentage contributions to SOA from ASOA (SOA produced from anthropogenic volatile organic compounds (AVOC)), BSOA (SOA produced from biogenic volatile organic compounds (BVOC)), DSOA (SOA produced from aqueous uptake of glyoxal and methylglyoxal) and S/I-SOA (SOA produced from semi-volatile and intermediate volatile organic compounds) were estimated to be 48.3%, 28.6%, 14.3%, and 8.8% respectively, over east China in summertime. In terms of domain and period average, ASOA contributed most to SOA (59%) in north China, while BSOA contributed most to SOA (37.3%) in northeast China. The percentage contribution of DSOA to SOA reached 21.5% in southwest China. S/I-SOA accounted for approximately 10% of SOA in most areas of east China. This study reveals that while AVOC dominates SOA formation on average over east China, the SOA source contributions differ considerably in different regions of China. BVOC makes the same contribution to SOA formation as AVOC in northeast China and southwest China, where forest coverage and BVOC emission are higher and anthropogenic emissions are relatively low, highlighting the significant role of BVOC in summer SOA formation in China.

Investigation of the influence of mineral dust on airborne particulate matter during the COVID-19 epidemic in spring 2020 over China

A regional air quality model system (RAQMS) driven by the Weather Research and Forecasting model (WRF) is applied to investigate the distribution and evolution of mineral dust and anthropogenic aerosols over China in April 2020, when air quality was improved due to reduced human activity during the COVID-19 epidemic, whereas dust storms began to attack China and deteriorated air quality. A dust deflation model was developed and improved mineral dust prediction. Model validation demonstrated that RAQMS was able to reproduce PM10, PM2.5 and aerosol components reasonably well. China suffered from three dust events in April 2020, with the maximum hourly PM10 concentrations exceeding 700 μg m−3 in downwind cities over the North China Plain (NCP). Mineral dust dominated PM10 mass (>80%) over the Gobi deserts in north and west China, while it comprised approximately 30–50% of PM10 over wide areas of east China. The domain and monthly mean dust mass fractions in PM10 were estimated to be 47% and 43% over the North China Plain and east China, respectively. On average, mineral dust contributed up to 22% and 21% of PM2.5 mass over the North China Plain and east China in April 2020, respectively. Sulfate and nitrate produced by heterogeneous chemical reactions on dust surface accounted for approximately 9% and 13% of secondary inorganic aerosols (SIA) concentration over the North China Plain and east China, respectively. The results from this study demonstrated that mineral dust made an important contribution to particulate matter mass during the COVID-19 epidemic in spring 2020 over China.

Surface and aloft NO2 pollution over the greater Tokyo area observed by ground-based and MAX-DOAS measurements bridged by kilometer-scale regional air quality modeling

To advance our understanding of surface and aloft nitrogen dioxide (NO2) pollution, this study extensively evaluated NO2 concentrations simulated by the regional air quality modeling system with a 1.3 km horizontal grid resolution using the Atmospheric Environmental Regional Observation System ground-based observation network and aloft measurements by multi-axis differential optical absorption spectroscopy (MAX-DOAS) over the greater Tokyo area. Observations are usually limited to the surface level, and gaps remain in our understanding of the behavior of air pollutants above the near-surface layer, particularly within the planetary boundary layer (PBL). Therefore, MAX-DOAS measurement was used, which observes scattered sunlight in the ultraviolet/visible range at several elevation angles between the horizon and zenith to determine the aloft NO2 pollution averaged over 0–1 km. In total, four MAX-DOAS measurement systems at Chiba University (35.63°N, 140.10°E) systematically covered the north, east, west, and south directions to capture the aloft NO2 pollution over the greater Tokyo area. The target period was Chiba-Campaign 2015 conducted during 9–23 November 2015. The evaluations showed that the air quality modeling system can generally capture the observed behavior of both surface and aloft NO2 pollution in terms of spatial and temporal coverage. The diurnal variation, which typically showed an increase from evening to early morning without daylight and a decrease during the daytime, was also captured by the model. During Chiba-Campaign 2015, two cases of episodic higher NO2 concentration were identified: one during the nighttime and another during the daytime as different diurnal patterns. These were related to a stagnant wind field, with the latter also connected to a lower PBL height in cloudy conditions. Comparison of the modeled daily-averaged surface and aloft NO2 concentrations showed that aloft NO2 concentration exhibited a strong linear correlation with surface NO2 concentration, with the aloft (0–1 km) value scaled to 0.4–0.5-fold the surface value, irrespective of whether the day was clean or polluted. This scaling value was lower during the nighttime and higher during the daytime. Based on this synergetic analysis of surface and aloft observation bridged by a kilometer-scale fine-resolution modeling simulation, this study contributes to fostering understanding of aloft NO2 pollution.

Analysis of aerosol distribution variations over China for the period 2045–2050 under different Representative Concentration Pathway scenarios: 不同代表性浓度路径情景下 2045-2050 年中国气溶胶分布变化的分析

The regional air quality modeling system RAMS-CMAQ was applied to simulate the aerosol concentration for the period 2045–2050 over China based on the downscaled meteorological field of three RCP scenarios from CESM (NCAR's Community Earth System Model) in CMIP5. The downscaling simulation of the meteorological field of the three RCP scenarios showed that, compared with that under RCP2.6, the difference in near-surface temperature between North and South China is weakened and the wind speed increases over North and South China and decreases over central China under RCP4.5 and RCP8.5. Under RCP2.6, from 2045 to 2050, the modeled average PM2.5 concentration is highest, with a value of 40–50 µg m−3, over the North China Plain, part of the Yangtze River Delta, and the Sichuan Basin. Meanwhile, it is 30–40 µg m−3 over central China and part of the Pearl River Delta. Compared with RCP2.6, PM2.5 increases by 4–12 µg m−3 under both RCP4.5 and RCP8.5, of which the SO42− and NH4+ concentration increases under both RCP4.5 and RCP8.5; the NO3− concentration decreases under RCP4.5 and increases under RCP8.5; and the black carbon concentration changes very slightly, and organic carbon concentration decreases, under RCP4.5 and RCP8.5, with some increase over part of Southwest and Southeast China under RCP8.5. The difference between RCP4.5 and RCP2.6 and the difference between RCP8.5 and RCP2.6 have similar annual variation for different aerosol species, indicating that the impact of climate change on different species tends to be consistent.摘要基于来自于 CMIP5 中 CESM 模式的三种 RCP 情景下的气象场的降尺度模拟, 应用区域空气质量模式系统 RAMS-CMAQ 模拟 2045-2050 年中国地区气溶胶浓度.三种 RCP 情景下气象场的降尺度模拟表明, 与 RCP2.6 相比, 在 RCP4.5 和 RCP8.5 下, 华北和华南的近地表温度差减小, 风速在华北和华南地区增加, 在中部地区下降. RCP2.6 情景下, 模拟的 2045 年到 2050 年平均的 PM 2.5浓度在华北平原, 长三角的部分地区和四川盆地最高, 约为 40-50 µg m–3, 在中国中部和珠三角的部分地区约为 30-40 µg m–3. 与 RCP2.6 相比, 在 RCP4.5 和 RCP8.5 下, PM2.5增加了 4-12 µg m–3, 其中在 RCP4.5 和 RCP8.5 下, SO42–和 NH4+的浓度增加, 在 RCP4.5 下, NO3–浓度降低, 在 RCP8.5 下, NO3–浓度升高, 在 RCP4.5 和 RCP8.5 下, BC 浓度变化很小, 而 OC 浓度下降, 其中在 RCP8.5 下, 西南和东南部分地区的 OC 有所增加.不同的气溶胶物种浓度在 RCP4.5 和 RCP2.6 之间的差异以及 RCP8.5 和 RCP2.6 之间的差异具有相似的年度变化, 这表明气候变化对不同物种的影响趋于一致.

Chemical formation pathways of secondary organic aerosols in the Beijing-Tianjin-Hebei region in wintertime

A regional air quality model system (RAQMS) was developed by incorporating an aqueous reaction mechanism for secondary organic aerosol (SOA) formation and primary semi-volatile (SVOC) and intermediate volatile organic compounds (IVOC) precursors to investigate various chemical pathways for SOA formation in the Beijing-Tianjin-Hebei (BTH) region in wintertime. Model comparison against observations demonstrates that the model is able to well reproduce meteorological variables and major aerosol chemical components, and the model improves SOA simulation significantly by including primary S/IVOCs (SVOC + IVOC) and aqueous reactions into the model. SVOC and IVOC emissions were relatively higher over the regions from southern Hebei province to Beijing and Tianjin, with the emission rates up to 0.15 mg m−2 hr−1 and 0.3 mg m−2 hr−1, respectively. The glyoxal (GLY) and methylglyoxal (MGLY) emissions were similar in distribution to those of S/IVOC emissions, with the maximum of 0.08 mg m −2 hr−1. The simulated SOA concentrations exhibited a southwest-northeast belt extending from southern Hebei to Beijing, with the maximum of 35 μg m−3 in southern Hebei province. The average contributions from various precursors or chemical pathways to SOA formation during the study period were estimated, in which AVOCs (anthropogenic VOCs), SVOCs, IVOCs, BVOCs (biogenic VOCs), GLY and MGLY contributed 38.4%, 24.9%, 28.4%, 0.2% and 8.1% of SOA mass concentration, respectively, in the BTH region. The maximum average contribution of GLY and MGLY to SOA reached 16% in southern Hebei province during a severe haze episode. From the clean to haze periods, concentrations of all SOA components apparently increased along with increasing atmospheric stability and weakening dispersion, but the increasing rates of SOA concentration produced by AVOCs and aqueous reactions were larger than those by primary S/IVOCs due to different chemical processes, and the AVOC-produced SOA dominated over the other SOA components during the haze periods.

Air Quality Modeling Study on the Controlling Factors of Fine Particulate Matter (PM2.5) in Hanoi: A Case Study in December 2010

Meteorology and emission sources are the two main factors determining concentrations of air pollutants, including fine particulate matter. A regional air quality modeling system was used to analyze the sources of fine-particulate air pollution in Hanoi, Vietnam, in December 2010. The impacts of precipitation and winds on PM2.5 concentrations was investigated. Precipitation was negatively correlated with PM2.5 concentrations. However, winds showed both positive and negative correlations with PM2.5 concentrations, depending on wind direction (WD) and the level of upwind concentrations. Sensitivity simulations were conducted to investigate the contribution of local and non-local emissions sources on total PM2.5 by perturbing the emission inputs of the model. Overall, local and non-local sources contributed equally to the total PM2.5 in Hanoi. Local emission sources comprised 57% of the total PM2.5 concentrations for the high PM2.5 pollution levels, while only comprising 42% of the total PM2.5 for low levels of PM2.5 concentrations. In Hanoi’s urban areas, local sources contributed more to the total PM2.5 than non-local sources. In contrast, non-local sources were the main contributors to the PM2.5 in Hanoi’s rural areas. Additional sensitivity simulations were conducted to identify the main local emission sources of PM2.5 concentrations in December 2010. The industrial and residential sectors collectively comprised 79% of the total PM2.5 concentrations while the transport and power sectors comprised only 2% and 3%, respectively. This is the first case study which used a regional air quality modeling system to provide new and informative insights into PM2.5 air pollution in Hanoi by estimating the contributions of local and non-local emissions sources, as well as the contribution of local emission sectors to PM2.5 concentrations in Hanoi.

Impacts of post-harvest open biomass burning and burning ban policy on severe haze in the Northeastern China.

Open filed biomass burning is a major contributor to airborne particulate matter and reactive trace gases during the post-harvest season in the Northeastern China. Due to prevailing weather conditions and high emission density, this region is prone to the accumulation of air pollutants that often leads to severe haze events. In this study, we combined satellite and ground observations, and a regional air quality modeling system to quantify the contribution of open biomass burning to surface PM2.5 (particulate matter with diameter less than 2.5 µm) concentrations during a severe haze episode. During this period (November 1st - 4th, 2015), the average PM2.5 concentrations in Heilongjiang, Jilin, and Liaoning provinces reached 116.98μg/m3, 98.60μg/m3, and 70.17μg/m3 respectively. Model simulations showed that open biomass burning contributed to 52.7% of PM2.5 concentrations over Northeast China. Using the differences in active fire spots as detected by the Visible Infrared Imaging Radiometer Suites (VIIRS) aboard the Suomi-NPP, we estimated that the burning ban enforced in 2018 have caused the PM2.5 concentrations to decrease from the 2015 level by 67.10%, 53.23%, and 10.06% in the Heilongjiang, Jilin, and Liaoning provinces respectively. Over the region, the burning ban proved to be effective in reducing fire emissions and lowering region-wide PM2.5 concentration by 48.1% during the post-harvest season.

The formation and evolution of secondary organic aerosol during haze events in Beijing in wintertime

A regional air quality model system (RAQMS) with a volatility basis set approach for secondary organic aerosol (SOA) formation and an emission inventory of semi-volatile (SVOC) and intermediate volatile organic compounds (IVOC) are applied to investigate the distribution and evolution of organic aerosols over the Beijing-Tianjin-Hebei (BTH) region in winter 2014, with focus on Beijing. Model validation demonstrates the model is capable of reproducing meteorological variables and major aerosol components, and the model significantly improves SOA and organic aerosol (OA) simulations by taking S/IVOCs (SVOC + IVOC) and relevant aging processes into account. SVOC and IVOC emissions in the BTH region are estimated to be 0.47 Tg and in a range of 0.09–0.36 Tg, respectively, which are about 18% and 4–14% of the emission amounts of volatile organic compounds (VOCs). The distribution of mean organic aerosols is characterized by a high concentration belt oriented southwest-northeast from southern Hebei to Beijing, with the maximum concentration up to 50 μg m−3 in Beijing and Shijiazhuang. The simulated SOA concentration is comparable in magnitude to primary organic aerosol (POA) concentration, and the SOA/OA ratio is around 50% in most areas of the BTH region. In terms of domain average, the percentage contributions to SOA mass concentration from anthropogenic volatile organic compounds (AVOCs), SVOCs, IVOCs and biogenic VOCs are estimated to be 46.1%, 40.1%, 9.4% and 4.4%, respectively, in the BTH region during the study period, which indicates an important role of S/IVOCs in SOA formation. From clean to haze periods, both POA and SOA concentrations apparently increase, with an increasing (decreasing) trend of the SOA/OA (POA/OA) ratio. SOA dominates over POA in fine organic aerosols during the haze periods. The increase of POA in hazy days is mainly due to the weakened vertical diffusion and accumulation near the surface, whereas the increase of SOA is likely attributed to both the reduced diffusivity and a series of competing chemical processes, in which the decreased photolysis rate by aerosol attenuation tends to decrease SOA concentration by about 6% during the most severe haze day, whereas the lower surface air temperature and higher POA and S/IVOC concentrations in haze days both enhance gas to particle partition, and consequently lead to higher SOA concentration.

Assessment of dicarbonyl contributions to secondary organic aerosols over China using RAMS-CMAQ

Abstract. The concentration of secondary organic aerosol (SOA) is underestimated in current model studies. Recent research suggests that the reactive uptake of dicarbonyls contributes to the production of SOA, although few models have included this pathway. Glyoxal, an important representative component of dicarbonyls in models, is significantly underestimated. We therefore incorporated the reactive uptake of dicarbonyls into the regional air quality modeling system RAMS-CMAQ (the Regional Atmospheric Modeling System-Community Multiscale Air Quality) to evaluate the contribution of dicarbonyls to SOA, and we then assess the impact of the underestimation of glyoxal on the production of SOA in China during two time periods: 3 June to 11 July 2014 (episode 1) and 14 October to 14 November 2014 (episode 2). When the reactive uptake process was added, the modeled mean concentration of SOA in episode 1 increased by 3.65 µg m−3, which explained 34.8 % of the unaccounted-for source of SOA. Meanwhile the increase in the concentration of SOA in episode 2 was 1.82 µg m−3 as a result of the lower liquid water content and the lower amount of dicarbonyls produced from biogenic precursors in the fall. On this basis, when the glyoxal simulation was improved, the modeled mean dicarbonyl-derived SOA (AAQ) increased by more than a factor of 2 in both episodes relative to case 1. AAQ in episode 1 contributed, on average, 60.6 % of the total concentration of SOA and the increase in this contribution represented 69.1 % of the unaccounted-for concentration of SOA, whereas the mean AAQ in episode 2 accounted for 64.5 % of total concentration of SOA. Based on the results, the mean AAQ over China was generally higher in the east than in the west during the two episodes. The highest value (10–15 µg m−3) of episode 1 appeared in the areas around the lower reaches of the Yellow River, whereas the highest value of 5–10 µg m−3 in episode 2 was concentrated over regions from south of the lower reaches of the Yellow River to the south of Guangzhou Province as well as the Sichuan Basin. The contribution of AAQ to the concentration of SOA in episode 1 varied from 10 % to 90 % throughout China, with the highest contributions (70 %–90 %) in the coastal regions and offshore along the East China Sea to the South China Sea and in the southwestern regions. The fraction of AAQ to SOA in episode 2 was in the range of 10 %–80 % over China, with the fraction up to 80 % in a small portion of northeastern China.

A modeling study of the influence of sea salt on inorganic aerosol concentration, size distribution, and deposition in the western Pacific Ocean

A regional air quality model system (RAQMS) was developed by coupling the treatment of heterogeneous reactions between sea salt aerosols (SSAs) and trace gases and applied to the investigation of aerosol properties and evolutionary features in the western Pacific Ocean in the spring of 2014. Model results for meteorological variables, PM concentrations, and size-resolved water soluble inorganic aerosol (WSIA) concentrations were compared and analyzed with a variety of observations from in situ measurements and the research cruise Dongfanghong II. Model validation demonstrated that the model can simulate the spatial-temporal distribution and size distribution of aerosol inorganic components in the marine atmosphere over East Asia, and the inclusion of heterogeneous reactions on SSAs apparently improved the model simulation for WSIA concentration, especially for aerosol size distribution. In the western Pacific Ocean, the non-sea salt SO42− and NO3− formed on SSAs accounted for up to 30% and 90% of surface SO42− and NO3− concentrations on average, respectively. The atmospheric depositions of total inorganic sulfur and nitrogen were estimated to be 13184 × 103 kgS/d and 10728 × 103 kgN/d, respectively. Wet deposition was the dominant removal pathway, which accounted for 75% and 68% of sulfur and nitrogen depositions, respectively. The deposition of fine-mode SO42− exceeded that of coarse-mode SO42−, whereas the deposition of coarse-mode NO3− was comparable to that of fine-mode NO3−. The non-sea salt SO42− and NO3− formed on SSAs contributed 16% and 9% of total sulfur and nitrogen depositions on average, respectively. The above results revealed the important role of SSAs in both atmospheric chemistry and deposition in the western Pacific Ocean.

Assessment of the regional source contributions to PM2.5mass concentration in Beijing

A source apportionment tool, ISAM (Integrated Source Apportionment Method), coupled with a regional air quality modeling system, RAMS-CMAQ (Regional Atmospheric Modeling System and Community Multis...

Regional contributions to particulate matter concentration in the Seoul metropolitan area, South Korea: seasonal variation and sensitivity to meteorology and emissions inventory

Abstract. The impact of regional emissions (e.g., domestic and international) on surface particulate matter (PM) concentrations in the Seoul metropolitan area (SMA), South Korea, and its sensitivities to meteorology and emissions inventories are quantitatively estimated for 2014 using regional air quality modeling systems. Located on the downwind side of strong sources of anthropogenic emissions, South Korea bears the full impact of the regional transport of pollutants and their precursors. However, the impact of foreign emissions sources has not yet been fully documented. We utilized two regional air quality simulation systems: (1) a Weather Research and Forecasting and Community Multi-Scale Air Quality (CMAQ) system and (2) a United Kingdom Met Office Unified Model and CMAQ system. The following combinations of emissions inventories are used: the Intercontinental Chemical Transport Experiment-Phase B, the Inter-comparison Study for Asia 2010, and the National Institute of Environment Research Clean Air Policy Support System. Partial contributions of domestic and foreign emissions are estimated using a brute force approach, adjusting South Korean emissions to 50 %. Results show that foreign emissions contributed ∼ 60 % of SMA surface PM concentration in 2014. Estimated contributions display clear seasonal variation, with foreign emissions having a higher impact during the cold season (fall to spring), reaching ∼ 70 % in March, and making lower contributions in the summer, ∼ 45 % in September. We also found that simulated surface PM concentration is sensitive to meteorology, but estimated contributions are mostly consistent. Regional contributions are also found to be sensitive to the choice of emissions inventories.

Assessment of the impacts of aromatic VOC emissions and yields of SOA on SOA concentrations with the air quality model RAMS-CMAQ

The secondary organic aerosol (SOA) concentration is generally underestimated by models. Recent studies suggest that the underprediction is related to underestimations of aromatic volatile organic compound (VOC) emissions and SOA yields in current models. Here, the impacts of these two factors in China were investigated with the regional air quality modeling system RAMS-CMAQ, referring to field observations during the episode from October 14 to November 14, 2014. Comparisons between the observed and modeled SOA of four sensitivity simulation cases indicated the significant impacts of the two underestimated factors on the SOA output. By considering these two aspects, the simulated mean SOA concentrations significantly increased by nearly 4 times with a good representation of the intensively temporal variations of concentrations, which were largely controlled by photochemical processes rather than meteorological conditions. The improvement in SOA compensated for the underestimations by approximately 23.5% and contributed to the mean fraction of SOA to organic aerosol (OA) by increasing the fraction from less than 7% to more than 25%, which was closer to the observed result. These results suggested a more reasonable and more realistic representation of SOA formation in the model after allowing for the two factors. Due to the better simulation of SOA, predictions of OA were correspondingly improved when the correlation coefficient increased from 0.57 to 0.73 and other bias parameters were reduced, which indicated the improved ability of our model to trace the temporal variations of OA. Based on the improved simulation throughout the episode, the mean SOA concentration was obviously higher in eastern China than in the west. The highest concentration appeared in the Sichuan Basin and Pearl River Delta (PRD) areas, with values of 6–11 μg/m3 and 8–17 μg/m3, respectively. Over the wide regions of central and eastern China, the dominant component in SOA was formed from anthropogenic sources (ASOA), generally accounting for more than 60%.

Model analysis of secondary organic aerosol over China with a regional air quality modeling system (RAMS-CMAQ)

The regional air quality modeling system RAMS-CMAQ was updated to incorporate secondary organic aerosol (SOA) production from isoprene and sesquiterpene and to account for the SOA production rate dependence on NOx and SOA aging. The system was then used to simulate spatiotemporal distributions of SOA concentration and its major constituents over China in winter. Modeled monthly mean SOA concentrations were high in central and eastern China and low in western regions. The highest SOA appeared in regions from Beijing–Tianjin–Hebei (BTH) to the middle reaches of the Yangtze River and areas from Sichuan Basin to the southwest border of China, where SOA contributions were less than 10% of the organic aerosol (OA). The lowest concentration was in the Qinghai–Tibet Plateau, accounting for 20%–30% of OA. It is notable that contributions from anthropogenic precursors to SOA were significant in winter, especially the wide areas of central and eastern China with contributions generally varying from 50% to 80% of the total SOA. Beijing was used as an example location representative of the heavily polluted BTH area for analysis of major components of SOA. Though the modeled concentration of SOA was still underestimated compared to the observations, it still showed that xylene and toluene were the two greatest contributors to anthropogenic SOA, which was in agreement with the observations. SOA produced from monoterpene was the greatest contributor to biogenic SOA due to the high mass yield of monoterpene, followed by isoprene. More than 57% of SOAs were aged, which may increase the extinction effect of SOA.

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.