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High-Mountain Asia (HMA) is a global hotspot of stratospheric intrusion, and elevated surface ozone were observed at ground monitoring sites. Still, links between the variability of surface ozone and stratospheric intrusion at regional scale remain unclear. This study synthesized ground measurements of surface ozone over the HMA and analyzed their seasonal variations. The monthly mean surface ozone concentrations peaked earlier in the south in April and later in the north in July over the HMA. The migration of monthly surface ozone peaks was coupled with the synchronous movement of tropopause folding and westerly jet that created a conducive conditions for stratospheric ozone intrusion. Such intrusion contributed ~65 % of surface ozone at three typical sites across the HMA. We demonstrated that surface ozone over the HMA is mainly controlled by stratospheric intrusion, which warrants a proper consideration in understanding atmospheric chemistry and impacts of ozone over this highland region and beyond.

Low-Cost Sensors (LCS) of fine particulate matter (PM2.5) have been widely used to supplement regular air quality monitoring stations. However, the sensor output is impacted by environmental factors, especially relative humidity, and must be calibrated to yield estimates of concentrations. In this study, we evaluate the performance of a linear model and a generalized additive model (GAM) to calibrate the output of LCS PM2.5 measurements in terms of different relative humidity levels. The method is based on co-located measurements from an LCS and a conventional reference monitor at two sites in an urban area in northern China. A stepwise variable selection of air pollutant concentrations and meteorological observations is used to select inputs to the model in order to improve the calibration ability. The results show that when relative humidity is below 75%, linear calibration of LCS PM2.5 observations can output PM2.5 mass concentrations close to the reference method with a correlation coefficient (R2) of 0.86. When relative humidity is above 75%, the GAM calibration model significantly outperforms the linear model, with an R2 of approximately 0.83. Overall, the linear model exhibits good fitness in dry conditions, while the GAM captures PM2.5 variations best in humid conditions. We conclude that low-cost PM2.5 sensors are sensitive to relative humidity and that therefore condition-specific calibration methods need to be used to improve the quality of the data as well as to improve the match with reference measurements. Copyright © 2021 American Association for Aerosol Research

The Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite is a valuable source of information to monitor the NOx emissions that adversely affect air quality. We conduct a series of experiments using a 4×4 km2 Comprehensive Air Quality Model with Extensions (CAMx) simulation during April–September 2019 in eastern Texas to evaluate the multiple challenges that arise from reconciling the NOx emissions in model simulations with TROPOMI. We find an increase in NO2 (+17 % in urban areas) when transitioning from the TROPOMI NO2 version 1.3 algorithm to the version 2.3.1 algorithm in eastern Texas, with the greatest difference (+25 %) in the city centers and smaller differences (+5 %) in less polluted areas. We find that lightning NOx emissions in the model simulation contribute up to 24 % of the column NO2 in the areas over the Gulf of Mexico and 8% in Texas urban areas. NOx emissions inventories, when using locally resolved inputs, agree with NOx emissions derived from TROPOMI NO2 version 2.3.1 to within 20 % in most circumstances, with a small NOx underestimate in Dallas–Fort Worth (−13 %) and Houston (−20 %). In the vicinity of large power plant plumes (e.g., Martin Lake and Limestone) we find larger disagreements, i.e., the satellite NO2 is consistently smaller by 40 %–60 % than the modeled NO2, which incorporates measured stack emissions. We find that TROPOMI is having difficulty distinguishing NO2 attributed to power plants from the background NO2 concentrations in Texas – an area with atmospheric conditions that cause short NO2 lifetimes. Second, the NOx/NO2 ratio in the model may be underestimated due to the 4 km grid cell size. To understand ozone formation regimes in the area, we combine NO2 column information with formaldehyde (HCHO) column information. We find modest low biases in the model relative to TROPOMI HCHO, with −9 % underestimate in eastern Texas and −21 % in areas of central Texas with lower biogenic volatile organic compound (VOC) emissions. Ozone formation regimes at the time of the early afternoon overpass are NOx limited almost everywhere in the domain, except along the Houston Ship Channel, near the Dallas/Fort Worth International airport, and in the presence of undiluted power plant plumes. There are likely NOx-saturated ozone formation conditions in the early morning hours that TROPOMI cannot observe and would be well-suited for analysis with NO2 and HCHO from the upcoming TEMPO (Tropospheric Emissions: Monitoring Pollution) mission. This study highlights that TROPOMI measurements offer a valuable means to validate emissions inventories and ozone formation regimes, with important limitations.

Each year, considerable levels of dust particles coming from arid regions of the earth contribute to the atmosphere. Because dust has serious environmental and human health effects, predictions of dust concentrations and their contribution to PM surface concentrations are essential for atmospheric research and the implementation of air quality programs and rules. This study aims to assess dust contributions to PM2.5 in Tehran in order to provide guidance for air quality management systems as well as validate the updated Dust Regional Atmospheric Model version 2 (BSC-DREAM8b) and the NMMB/BSC-Dust model using chemical speciation of ground-based measurements of PM2.5. Accurate and reliable measurements are necessary to determine the sources of pollutants as well as to confirm, validate, and improve models. For this purpose, dust concentration and contribution were calculated from chemical speciation of PM2.5 samples that were obtained on a 6 day basis for a whole year from February 2014 to February 2015. The comparison of the dust observations to the model products revealed that model outputs were in good agreement for the monthly averaged values. However, for the daily averaged values, models and ground observation showed a considerable difference. In order to understand possible reasons for the discrepancy, differences between neighboring grid cells were investigated, as well as the effect of sampling frequency. It is found that agreement between models and observations was sensitive to sampling duration and frequency but not to spatial variability between grid cells. This study is the first validation of model outputs with the calculated dust concentration from ground-based chemical speciation of PM2.5 rather than using total PM or aerosol optical depth measurements as a proxy for dust concentrations.

The Tibetan Plateau is generally considered to be a significantly clean area owing to its high altitude; however, the transport of atmospheric pollutants from the Indian subcontinent to the Tibetan Plateau has influenced the Tibetan environments. Nyingchi is located at the end of an important water vapor channel. In this study, continuous monitoring of gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particle-bound mercury (PBM) was conducted in Nyingchi from 30 March to 3 September 2019, to study the influence of the Indian summer monsoon (ISM) on the origin, transport, and behavior of Hg. The GEM and PBM during the preceding Indian summer monsoon (PISM) period (1.20±0.35 ng m−3 and 11.4±4.8 pg m−3 for GEM and PBM, respectively) were significantly higher than those during the ISM period (0.95±0.21 ng m−3, and 8.8±6.0 pg m−3); the GOM during the PISM period (13.5±7.3 pg m−3) was almost at the same level as that during the ISM period (12.7±14.3 pg m−3). The average GEM concentration in the Nyingchi region, obtained using passive sampler, was 1.12±0.28 ng m−3 (from 4 April 2019 to 31 March 2020). The GEM concentration showed that the sampling area was very clean compared to other high-altitude sites. The GEM has several patterns of diurnal variation during different periods. Stable high GEM concentrations occur at night and low concentrations occur in the afternoon during PISM, which may be related to the nocturnal boundary layer structure. High values occurring in the late afternoon during the ISM may be related to long-range transport. Low concentrations of GEM observed during the morning in the ISM may originate from vegetation effects. The results of the trajectory model demonstrate that the sources of pollutants at Nyingchi are different with different circulation patterns. During westerly circulation in the PISM period, pollutants mainly originate from central India, northeastern India, and central Tibet. During the ISM period, the pollutants mainly originate from the southern part of the SET site. The strong precipitation and vegetation effects on Hg species during the ISM resulted in low Hg concentrations transmitted to Nyingchi during this period. Further, principal component analysis showed that long-distance transport, local emissions, meteorological factors, and snowmelt factors are the main factors affecting the local Hg concentration in Nyingchi. Long-distance transport factor dominates during PISM and ISM3, while local emissions is the major contributor between PISM and ISM3. Our results reveal the Hg species distribution and possible sources of the most important water vapor channel in the Tibetan Plateau and could serve as a basis for further transboundary transport flux calculations.

This study investigated the sources and formation processes of particulate matter (PM) with an aerodynamic diameter ≤1 μm (PM

Air pollutants can be transported to the pristine regions such as the Tibetan Plateau, by monsoon and stratospheric intrusion. The Tibetan Plateau region has limited local anthropogenic emissions, while this region is influenced strongly by transport of heavy emissions mainly from South Asia. We conducted a comprehensive study on various air pollutants (PM2.5, total gaseous mercury, and surface ozone) at Nam Co Station in the inland Tibetan Plateau. Monthly mean PM2.5 concentration at Nam Co peaked in April before monsoon season, and decreased during the whole monsoon season (June–September). Monthly mean total gaseous mercury concentrations at Nam Co peaked in July and were in high levels during monsoon season. The Indian summer monsoon acted as a facilitator for transporting gaseous pollutants (total gaseous mercury) but a suppressor for particulate pollutants (PM2.5) during the monsoon season. Different from both PM2.5 and total gaseous mercury variabilities, surface ozone concentrations at Nam Co are primarily attributed to stratospheric intrusion of ozone and peaked in May. The effects of the Indian summer monsoon and stratospheric intrusion on air pollutants in the inland Tibetan Plateau are complex and require further studies.

The Tibetan Plateau is generally considered to be a significantly clean area owing to its high altitude; however, the transport of atmospheric pollutants from the Indian subcontinent to the Tibetan Plateau has infected the Tibetan environments. Nyingchi is located at the end of an important water vapor channel. In this study, continuous monitoring of gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particle-bound mercury (PBM) was conducted in Nyingchi from March 30 to September 3, 2019, to study the influence of the Indian summer monsoon (ISM) on the origin, transport and behavior of mercury. The atmospheric Hg concentrations during the preceding Indian summer monsoon (PISM) period (1.20 ± 0.35 ng m−3, 13.5 ± 7.3 pg m−3, and 11.4 ± 4.8 pg m−3 for GEM, GOM, and PBM, respectively) were relatively higher than those during the ISM period (0.95 ± 0.21 ng m−3, 12.7 ± 14.3 pg m−3 and 8.8 ± 6.0 pg m−3). The average annual total gaseous mercury concentration in the Nyingchi region was obtained using a passive sampler as 1.12 ± 0.28 ng m−3. The GEM concentration showed that the sampling area was very clean. The GEM has several patterns of daily variation during different periods. Stable high GEM concentrations occur at night during PISM, which may be related to the nocturnal boundary layer. High values occurring in the late afternoon during the ISM may be related to long-range transport. The results of the trajectory model demonstrate that the sources of pollutants at Nyingchi are different under the control of different airflow fields. During westerly circulation, pollutants mainly originate from northeast India or Nepal. During the ISM period, the pollutants mainly originate from northeast India, or the Bay of Bengal, and the Indian Ocean. The strong precipitation and vegetation effects on Hg during the ISM resulted in low Hg concentrations transmitted to Nyingchi during this period. Further, principal component analysis showed that long-distance transport, local emissions, meteorological factors, and snowmelt factors are the main factors affecting the local Hg concentration in Nyingchi.

Severe haze episodes occur frequently in the Seoul Metropolitan Area (SMA) and throughout East Asian countries, especially during the winter and early spring. We investigated the sources and chemistry of particulate matter (PM) during three winter haze episodes in Seoul that occurred between January 1st and February 10th in 2017 using a high resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and positive matrix factorization (PMF) analysis. The average concentration of sub-micrometer aerosol (PM1 = NR-PM1 + black carbon (BC)) was 32.6 μg/m3, which was composed of 42% organics, 27% nitrate, 11% sulfate, 13% ammonium and 4% BC by mass. Six distinct sources of organic aerosol (OA) were identified: vehicle emitted hydrocarbon-like OA (HOA), cooking OA (COA), biomass burning OA (BBOA), and 3 different types of secondary OA (SOA) with varying degrees of oxidation and temporal trends. The nitrate mass fraction increased during the three haze episodes, with nitrate accounting for 27-33% of PM1 mass. Enhanced nitrate concentrations and higher nitrate oxidation ratios (NOR), despite lower enhancement in relative humidity (RH) than the low PM loading period, suggest that regional transport of nitrate contributed to the nitrate mass during the haze periods. Lower HOA and COA concentrations during the high PM loading periods further confirm that local emissions or stagnant meteorological conditions were not the main reason for the severe haze. Residence time analysis (RTA), concentration field analysis (CFA), and column-CFA results from FLEXPART also showed that the measurement period was accompanied by atmospheric transport of nitrate, sulfate, and ammonium from eastern China. Nevertheless, we found that NO2, a precursor of nitrate, was predominantly from local emissions. These findings suggest that nitrate in Seoul is not only locally formed, but also transported from upwind areas.

The TROPOspheric Monitoring Instrument (TROPOMI) is used to derive top-down NOX emissions for two large power plants and three megacities in North America. We first re-process the vertical column N...

Two hundred sixty-three fine particulate matter (PM2.5) samples were collected over fourteen months in Fresno and Bakersfield, California. Samples were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and 160 organic molecular markers. Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) source apportionment models were applied to the results in order to understand monthly and seasonal source contributions to PM2.5 OC. Similar source categories were found from the results of the CMB and PMF models to PM2.5 OC across the sites. Six source categories with reasonably stable profiles, including biomass burning, mobile, food cooking, two different secondary organic aerosols (SOAs) (i.e., winter and summer), and forest fires were investigated. Both the CMB and the PMF models showed a strong seasonality in contributions of some sources, as well as dependence on wind transport for both sites. The overall relative source contributions to OC were 24% CMB wood smoke, 19% CMB mobile sources, 5% PMF food cooking, 2% CMB vegetative detritus, 17% PMF SOA summer, 22% PMF SOA winter, and 12% PMF forest fire. Back-trajectories using the Weather Research and Forecasting model combined with the FLEXible PARTicle dispersion model (WRF-FLEXPART) were used to further characterize wind transport. Clustering of the trajectories revealed dominant wind patterns associated with varying concentrations of the different source categories. The Comprehensive Air Quality Model with eXtensions (CAMx) was used to simulate aerosol transport from forest fires and thus confirm the impacts of individual fires, such as the Rough Fire, at the measurement sites.

In this work, we investigate the NOx emissions inventory in Seoul, South Korea, using a regional ozone monitoring instrument (OMI) NO2 product derived from the standard NASA product. We first develop a regional OMI NO2 product by recalculating the air mass factors using a high-resolution (4 km × 4 km) WRF-Chem model simulation, which better captures the NO2 profile shapes in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the subpixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 times larger in the Seoul metropolitan region and >2 times larger near substantial point sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the South Korea–United States Air Quality (KORUS-AQ) field campaign. NOx emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emissions inventory yields a NOx emissions rate of 227±94 kt yr −1 , while the bottom-up inventory itself within a 40 km radius of Seoul yields a NOx emissions rate of 198 kt yr −1 . Using the top-down approach on the regional OMI NO2 product, we derive the NOx emissions rate from Seoul to be 484±201 kt yr −1 , and a 353±146 kt yr −1 NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53 % and 36 % in the bottom-up inventory using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 and NOy simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate. When NOx emissions in the WRF-Chem model are increased by a factor of 2.13 in the Seoul metropolitan area, there is better agreement with KORUS-AQ aircraft observations and the recalculated OMI NO2 tropospheric columns. Finally, we show that by using a WRF-Chem simulation with an updated emissions inventory to recalculate the air mass factor (AMF), there are small differences ( ∼8 %) in OMI NO2 compared to using the original WRF-Chem simulation to derive the AMF. This suggests that changes in model resolution have a larger effect on the AMF calculation than modifications to the South Korean emissions inventory. Although the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NOx emissions estimates.

The severity of high atmospheric pollution has been a major social problem in northern China. To improve the air quality in the Beijing–Tianjin–Hebei (BTH) region and guarantee a suitable environment during the military parade and other celebrating activities for the 70th anniversary of the victory for anti-Fascist Warcraft in the year 2015, a series of strict air quality control policies were carried out. To analyze the reduction extents of PM2.5 and organic matter components during the control period and to examine the meteorological conditions in this region and their decisive influence on the air quality, PM2.5 samples were collected and the Lagrangian particle dispersion model FLEXPART was performed to calculate potential source locations within the BTH region. PM2.5, organic carbon (OC), elementary carbon (EC), and three species types were specifically analyzed. Although the results showed that PM2.5, OC, and EC reduced by 64.55%, 48.74%, and 60.75% during the control period, the air mass transport patterns showed great difference at certain periods, which altered the dominant transport direction of air mass and the potential source region of pollutants and organic matters. This alteration completely changed major atmospheric pollutants sources contribution and caused huge concentration changes. Parallel cases also showed that meteorological conditions could avoid massive atmospheric transported from a major emission source region to a receptor site. The meteorological conditions changed the main contribution source region in control and non-control periods and proved the air quality control measures were less necessary in some southern Hebei cities during special events periods.

Unprecedented travel restrictions due to the COVID-19 pandemic caused remarkable reductions in anthropogenic emissions, however, the Beijing area still experienced extreme haze pollution even under the strict COVID-19 controls. Generalized Additive Models (GAM) were developed with respect to inter-annual variations, seasonal cycles, holiday effects, diurnal profile, and the non-linear influences of meteorological factors to quantitatively differentiate the lockdown effects and meteorology impacts on concentrations of nitrogen dioxide (NO2) and fine particulate matters (PM2.5) at 34 sites in the Beijing area. The results revealed that lockdown measures caused large reductions while meteorology offset a large fraction of the decrease in surface concentrations. GAM estimates showed that in February, the control measures led to average NO2 reductions of 19 μg/m3 and average PM2.5 reductions of 12 μg/m3. At the same time, meteorology was estimated to contribute about 12 μg/m3 increase in NO2, thereby offsetting most of the reductions as well as an increase of 30 μg/m3 in PM2.5, thereby resulting in concentrations higher than the average PM2.5 concentrations during the lockdown. At the beginning of the lockdown period, the boundary layer height was the dominant factor contributing to a 17% increase in NO2 while humid condition was the dominant factor for PM2.5 concentrations leading to an increase of 65% relative to the baseline level. Estimated NO2 emissions declined by 42% at the start of the lockdown, after which the emissions gradually increased with the increase of traffic volumes. The diurnal patterns from the models showed that the peak of vehicular traffic occurred from about 12pm to 5pm daily during the strictest control periods. This study provides insights for quantifying the changes in air quality due to the lockdowns by accounting for meteorological variability and providing a reference in evaluating the effectiveness of control measures, thereby contributing to air quality mitigation policies., Graphical abstract Image 1

Speciated hourly measurements of fine aerosols were made for more than two years at an urban, an industrial and a port site in Busan, Korea. A Generalized Additive Model (GAM) was designed to deconvolve factors contributing to the pollutant concentrations at multiple scales. The model yields estimates of source contributions to pollution by separately identifying the signals in the time series due to meteorology, vertical mixing, horizontal wind transport and temporal variations such as diurnal, weekly, seasonal and annual trends. The GAM model was expanded to include FLEXPART back trajectory clusters generated using fuzzy c-means clustering. This made it possible to quantify the impact of long-range transport using the Trajectory Cluster Contribution Function (TCCF). TCCF provides a development of methods such as Concentration Field Analysis and Potential Source Contribution Function by providing numerical estimates of concentration changes associated with different air mass transport patterns while accounting for possible confounding factors from meteorology. The GAM simulations identified the importance of local transport for primary pollutants and long-range transport from China for secondary pollutants. Local factors accounted for up to 72% of the variance in concentrations of NO2 and elemental carbon whereas large-scale/seasonal factors accounted for up to 56% of PM2.5 and 80% of inorganic species. The algorithm further identified the importance of the weekend effect and the holiday effect at the different sites in Busan. The residual from the analysis was used to estimate the impact of the COVID-19 pandemic. The signature of the pandemic was different between the pollutants as well as from site to site. The model was able to distinguish small impacts from local pollutants at the residential site; short-lived acute impacts from industrial changes; and longer-term changes due to the early pandemic response in China.

The holiday effect is a useful tool to estimate the impact on air pollution due to changes in human activities. In this study, we assessed the variations in concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) during the holidays in the heating season from 2014 to 2018 based on daily surface air quality monitoring measurements in Beijing. A Generalized Additive Model (GAM) is used to analyze pollutant concentrations for 34 sites by comprehensively accounting for annual, monthly, and weekly cycles as well as the nonlinear impacts of meteorological factors. A Saturday effect was found in the downtown area, with about 4% decrease in PM2.5 and 3% decrease in NO2 relative to weekdays. On Sundays, the PM2.5 concentrations increased by about 5% whereas there were no clear changes for NO2. In contrast to the small effect of the weekend, there was a strong holiday effect throughout the region with average increases of about 22% in PM2.5 and average reductions of about 11% in NO2 concentrations. There was a clear geographical pattern in the strength of the holiday effect. In rural areas the increase in PM2.5 is related to the proportion of coal and biomass consumption for household heating. In the suburban areas between the Fifth Ring Road and Sixth Ring Road there were larger reductions in NO2 than downtown which might be due to decreased traffic as many people return to their hometown for the holidays. This study provides insights into the pattern of changes in air pollution due to human activities. By quantifying the changes, it also provides insights for improvements in air quality due to control policies implemented in Beijing during the heating season., Graphical abstract Unlabelled Image, Highlights • During the holidays, PM2.5 is about 22% higher and NO2 is about 11% lower in the greater Beijing area. • On Saturdays, PM2.5 is about 4% lower and NO2 is about 3% lower in downtown Beijing. • On Sundays, PM2.5 is about 5% higher but NO2 is similar to weekdays. • Holiday increases in PM2.5 are about 18.4% larger in the southwest and northeast than in other rural areas. • Suburban areas have larger holiday reductions in NO2 than downtown areas.

To illustrate the major sources responsible for the redox activity of ambient fine particles during the 2014 Asia-Pacific Economic Cooperation (APEC) conference in Beijing, 3 months of daytime (8:00-19:30 LST) and nighttime (20:00-7:30 LST) particulate kmatter (PM

Black and Brown Carbon (BC, BrC) are key parameters of climate forcing, yet significant challenges exist assigning emission source contributions to light-absorption by carbonaceous aerosols. Additionally, BC and BrC emissions add to extreme air pollution events in Chinese mega-cities, which harm human health and detract from the natural and built environment. To address these concerns, the ability to estimate atmospheric light absorption related to emission sources and global inventories is a highly valuable tool for climate modelers and policy makers. Three months of BC and BrC data was collected using an Aethalometer in parallel to PM2.5 filter sampling during a stringent emission controls period and post controls period, including during the regional heating season. In this study reconstructed 370 nm wavelength absorption was calculated by applying source specific Mass Absorption Cross-Sections to PMF apportioned EC and OC results. Reconstructed absorption showed good agreement with the ambient measured absorption for both BC and BrC. In Beijing, the major contributor to near-UV absorption was mobile sources, which accounted for 45–54% of absorption by BC and 14–18% by BrC. BrC absorption from secondary aerosols, biomass burning, and soil dust was also estimated, with these sources contributing from 1 to 9% individually. Meteorological cluster analysis showed that air mass origin did not impact the absorption reconstruction and that the highest regional contribution to near-UV light absorption originated primarily in areas south and east of Beijing. The study shows ambient near-UV light absorption can be predicted using BC and BrC MAC values from sources. However, the current number of multi-wavelength and source specific BrC MAC values reported in the literature is limited. The reconstruction approach allows for a more robust method of assigning light absorption to source categories, allowing the expansion of aethalometer derived BrC apportionment to multiple sources, including biomass burning.

Two hundred sixty-three fine particulate matter (PM2.5) samples collected on 3-day intervals over a 14-month period at two sites in the San Joaquin Valley (SJV) were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and organic molecular markers. A unique source profile library was applied to a chemical mass balance (CMB) source apportionment model to develop monthly and seasonally averaged source apportionment results. Five major OC sources were identified: mobile sources, biomass burning, meat smoke, vegetative detritus, and secondary organic carbon (SOC), as inferred from OC not apportioned by CMB. The SOC factor was the largest source contributor at Fresno and Bakersfield, contributing 44% and 51% of PM mass, respectively. Biomass burning was the only source with a statistically different average mass contribution (95% CI) between the two sites. Wintertime peaks of biomass burning, meat smoke, and total OC were observed at both sites, with SOC peaking during the summer months. Exceptionally strong seasonal variation in apportioned meat smoke mass could potentially be explained by oxidation of cholesterol between source and receptor and trends in wind transport outlined in a Residence Time Analysis (RTA). Fast moving nighttime winds prevalent during warmer months caused local emissions to be replaced by air mass transported from the San Francisco Bay Area, consisting of mostly diluted, oxidized concentrations of molecular markers. Good agreement was observed between SOC derived from the CMB model and from non-biomass burning WSOC mass, suggesting the CMB model is sufficiently accurate to assist in policy development. In general, uncertainty in monthly mass values derived from daily CMB apportionments were lower than that of CMB results produced with monthly marker composites, further validating daily sampling methodologies. Strong seasonal trends were observed for biomass and meat smoke OC apportionment, and monthly mass averages had lowest uncertainty when derived from daily CMB apportionments.

Control on emissions of nitrogen oxides (NOx) in the United States of America have led to reductions in concentrations in urban areas by up to a factor of two in the last decade. The Air Quality System monitoring network provides surface measurements of concentrations at hourly resolution over multiple years, revealing variations at the annual, seasonal, day of week and diurnal time scales. A multiple linear regression model was used to estimate the temporal profiles in the NOx concentrations as well as the impact of meteorology, ozone concentrations, and boundary layer heights. The model is applied to data from 2005 to 2016 available at 6 sites in Chicago, Illinois. Results confirm the 50% decrease in NOx over the length of the time series. The weekend effect is found to be stronger in more commercial areas, with 32% reductions on Saturdays and 45% on Sundays and holidays; and weaker in more residential areas with 20% reductions on Saturdays and 30% reductions on Sundays. Weekday diurnal profiles follow a double hump with emission peaks during the morning and afternoon rush hours, but only a shallow drop during the middle day. Difference in profiles from the 6 sites suggest that there are different emission profiles within the urban area. Diurnal profiles on Saturdays have less variation throughout the day and more emissions in the evening. Sundays are very different from both weekdays and Saturdays with a gradual increase until the early evening. The results suggest that in addition to vehicle type and vehicle miles traveled, vehicle speed and congestion must be taken into account to correctly quantify morning rush hour emissions and the weekend effect.

Unprecedented travel restrictions due to the COVID-19 pandemic caused remarkable reductions in anthropogenic emissions, however, the Beijing area still experienced extreme haze pollution even under the strict COVID-19 controls. Generalized Additive Models (GAM) were developed with respect to inter-annual variations, seasonal cycles, holiday effects, diurnal profile, and the non-linear influences of meteorological factors to quantitatively differentiate the lockdown effects and meteorology impacts on concentrations of nitrogen dioxide (NO2) and fine particulate matters (PM2.5) at 34 sites in the Beijing area. The results revealed that lockdown measures caused large reductions while meteorology offset a large fraction of the decrease in surface concentrations. GAM estimates showed that in February, the control measures led to average NO2 reductions of 19 µg/m3 and average PM2.5 reductions of 12 µg/m3. At the same time, meteorology was estimated to contribute about 12 µg/m3 increase in NO2, thereby offsetting most of the reductions as well as an increase of 30 µg/m3 in PM2.5, thereby resulting in concentrations higher than the average PM2.5 concentrations during the lockdown. At the beginning of the lockdown period, the boundary layer height was the dominant factor contributing to a 17% increase in NO2 while humid condition was the dominant factor for PM2.5 concentrations leading to an increase of 65% relative to the baseline level. Estimated NO2 emissions declined by 42% at the start of the lockdown, after which the emissions gradually increased with the increase of traffic volumes. The diurnal patterns from the models showed that the peak of vehicular traffic occurred from about 12pm to 5pm daily during the strictest control periods. This study provides insights for quantifying the changes in air quality due to the lockdowns by accounting for meteorological variability and providing a reference in evaluating the effectiveness of control measures, thereby contributing to air quality mitigation policies.

A multiple linear regression (MLR) chemical mass balance model was applied to data collected during an air quality field experiment in Yakima, WA during January, 2013to determine the relative contribution of residential wood combustion (RWC) and vehicle emissions to ambient pollutant levels. Acetonitrile was used as a chemical tracer for wood burning and nitrogen oxides (NOx) as a chemical tracer for mobile sources. RWC was found to be a substantial source of gas phase air toxics in winter time. The MLR model found RWC primarily responsible for emissions of formaldehyde (73%), acetaldehyde (69%), and black carbon (55%) and mobile sources primarily responsible for emissions of carbon monoxide (CO) (83%), toluene (81%), C2 – alkylbenzenes (81%), and benzene (64%). When compared with the EPA's 2011 winter emissions inventory, the MLR results suggest that the contribution of RWC to CO emissions was underestimated in the inventory by a factor of 2. Emission ratios to NOx from the MLR model agreed to within 25% with wintertime emission ratios predicted from the Motor Vehicle Emissions Simulator (MOVES) 2010b emission model for Yakima County for all pollutants modeled except for CO, C2 – alkylbenzenes, and black carbon. The MLR model results suggest that MOVES was over predicting mobile source emissions of CO relative to NOx by a factor of 1.33 and black carbon relative to NOx by about a factor of 3.

The San Joaquin Valley in California suffers from poor air quality due to a combination of local emissions and weak ventilation. Over the course of decades, there has been a concerted effort to control emissions from vehicles as well as from residential wood burning. A multiple linear regression model was used to evaluate the trends in air pollution over multiple time scales: by year, by season, by day of the week and by time of day. The model was applied to 18 years of measurements in Fresno including hourly mole fractions of NOx and concentrations of PM2.5; and daily measurements of speciated components of PM2.5. The analysis shows that there have been reductions in NOx, elemental carbon and ammonium nitrate of 4 to 6%/year. On weekends, NOx mole fractions are reduced by 15 to 30% due to fewer vehicle miles traveled and a smaller fraction of diesel traffic. These weekend reductions in NOx have not been accompanied by weekend reductions in PM2.5 however. In particular, elemental and organic carbon concentrations are higher on winter weekends. Analysis of diurnal profiles suggests that this is because of increased PM2.5 on Saturday and holiday evenings which are likely due to residential wood combustion. Furthermore, while organic carbon concentrations have decreased in the winter months, they have been variable but without a net decline in the summer, most likely as a result of forest fires offsetting other improvements in air quality. Fog was found to greatly enhance ammonium nitrate formation and was therefore associated with higher PM2.5 in the winter months. Overall the analysis shows that air quality controls have been effective at reducing NOx all year and PM2.5 in the winter, that continued reductions in emissions will further reduce pollutant concentrations, but that winter residential wood combustion and summer forest fires could offset some of the gains obtained.

The TROPOspheric Monitoring Instrument (TROPOMI) is used to derive top-down NO

In recent decades, most big cities in China have experienced severe air pollution accompanied by rapid economic and social development. Analysis of measurements of air pollutants form a fundamental basis for understanding the characteristics of air pollution and are important references for policy-making. In this study, five-year measurements of air pollutants at 6 sites in Lhasa, a typical high altitude big city in southwestern China, were analyzed from January 2013 to December 2017. Air pollutants at all the 6 sites in Lhasa generally displayed similar patterns of both diurnal and monthly variations, indicating the mixed atmospheric environment and the overall effect of the meteorological conditions in the city. Spatially, the air pollutant concentrations at the 6 sites were generally characterized by high concentrations of SO2, NO2, CO, PM10 and PM2.5 at urban sites and high O3 concentrations at suburban sites. In comparison with other provincial capital cities in China, Lhasa has low concentrations of air pollutants, except for O3, and thus, better air quality. Although Lhasa has experienced rapid urbanization and economic development, air pollution conditions have remained rather stable and even decreased slightly in term of particular air pollutants. We suggested that the relatively isolated location, low air pollutant emissions associated with its industrial structure and renewable energy consumption, and effective air pollution control measures, collectively contributed to the synchronous improvement of the economy and air quality in Lhasa. Such "Lhasa pattern" may serve as a positive example for other regional hub cities in China and beyond that experience socioeconomic development and simultaneously seek to improve air quality.

Among various gaseous oxidized mercury species, HgCl2 and HgBr2 are known to be more recalcitrant to direct photolysis under radiations. In this study, we examined a possible route to reduce HgCl2 and HgBr2 in the dry air under UV, visible and solar radiations with different levels of irradiances. Potential impact of O3 on the reductions of HgCl2 and HgBr2 were discussed. The laboratory results showed that if without any radiation, O3 would not influence the chemical conversions between HgCl2/HgBr2 and Hg0. However, if with involvement of radiation, a rapid reduction of HgCl2 and HgBr2 was observed, resulting in a significant production of Hg0 in the air. The magnitudes of reduction reactions heavily depended on the frequency of radiations as well as the irradiances. UV light had the strongest capacity to promote photoreduction of HgCl2 and HgBr2 even at relatively low irradiances. A relationship analysis indicated that the reduction of HgCl2 and HgBr2 was possibly related to the O3 concentrations in the air. We proposed that O3 might be involved in productions of the unstable intermediate HgIX (X = Br, Cl), which has a quicker photolysis rate than the HgIIX2. Our results suggest that the impacts of solar radiation and O3 on reductions of HgII species in the atmosphere are worth of being investigated theoretically and in both laboratory and field studies in the future, since it might be an important but lesser-known part in the atmospheric Hg chemistry.

The Ozone Monitoring Instrument (OMI) has been estimating NO2 columns from space for over 10 years, and these have been used to estimate emissions and emission trends for point and area sources all over the world. In this study we evaluate the trends in NO2 columns over 54 cities in the USA and Canada to identify the long term trends due to air quality policies, the impact of the Great Recession, and the weekday-weekend effect. A multiple linear regression model is used to fit annual, seasonal and weekly factors for individual swath retrievals along with the impact of temperature, wind speed and pixel size. For most cities, the correlation coefficients of the model fit ranges from 0.47 to 0.76. There have been strong reductions in NO2 columns, with annual decreases of up to 7% per year in most cities. During the years of the Great Recession, NO2 columns were as much as 30% lower than they would have been had they followed the linear annual trend. The analysis yielded insights into the timing of the reductions, with some cities in the northwest and in the east experiencing reductions in 2008 already, and most areas back to where they would have been based on the uniform trend by 2011. The analysis also finds that reductions in columns during the weekend vary significantly from city to city, with a range in reductions of 10%–30% on Saturdays, and 20%–50% on Sundays.

Hourly speciated measurements of atmospheric mercury made in a remote, high-altitude site in the Tibetan Plateau revealed the first field observations of the reduction of reactive mercury in the presence of sunlight in the atmosphere. Measurements were collected over four winter months on the shore of Nam Co Lake in the inland Tibetan Plateau. The data was analyzed to identify sources and atmospheric transformations of the speciated mercury compounds. The absence of local anthropogenic sources provided a unique opportunity to examine chemical transformations of mercury. An optimization algorithm was used to determine the parameters of a chemical box model that would match the measured reactive mercury concentrations. This required the presence of a photolytic reduction reaction previously observed in laboratory studies and in power plant plumes. In addition, the model estimated the role of vertical mixing in diluting reactive gaseous mercury during the day, and the role of bromine chemistry in oxidizing gaseous elemental mercury to produce reactive gaseous mercury. This work provides further evidence of the need to add the photolytic reduction reaction of oxidized mercury into atmospheric transport models in order to better simulate mercury deposition.

Significant progress has been made in reducing emissions of air pollutants in the San Joaquin Valley in California. Nevertheless, from May to October, the valley still experiences numerous exceedances of the ozone health standard. As the standards are tightened, it is becoming harder to design policies to attain them. To better understand historical emissions reductions in the context of necessary future control efforts, we analyze 25 years of hourly measurements of ozone and nitrogen oxides concentrations for the hottest one third of days in Fresno using multiple linear regression analysis. We then analyze the changing dynamics of the weekend effect over the years in order to evaluate the growing importance of day-to-day carryover on ozone concentrations. A simplified model of the day-of-week pattern of ozone concentrations is used to explore the impact of same-day and previous-day concentrations. In addition to ozone, Ox (O3 + NO2) is used to distinguish reductions of atmospheric oxidants from short-duration exchanges between O3 and NO2. The analysis shows that there has been a significant increase in the importance of day-to-day carryover on ozone levels, and that consequently the ozone weekend effect in Fresno has changed over the last 25 years. In the 1990s, lower NOx on the weekend led to increased ozone on Saturdays and Sundays but levels of Ox remained constant. In the 2010s, lower weekend NOx led to reduced ozone on Saturdays, Sundays and Mondays showing that reductions in primary pollutants are sufficient to yield immediate decreases in secondary pollutants. Overall, the photochemical regime in the atmosphere has evolved such that carryover and regional pollution will be increasingly important in determining local ozone concentrations. Policies will therefore need to pay greater attention to regional emissions as local reductions may not be sufficient to meet the health standard.

One year of online total gaseous mercury (TGM) measurements were carried out for the first time in Lanzhou, a city in northwest China that was once seriously polluted. Measurements were made from October 2016 to October 2017 using the Tekran 2537B instrument, and the annual mean concentration of TGM in Lanzhou was 4.48 ± 2.32 ng m−3 (mean ± standard deviation). TGM concentrations decreased during the measurement period, with autumn 2017 average concentrations 2.87 ng m−3 lower than autumn 2016 average concentrations. Similar diurnal variations of TGM were obtained in different seasons with low concentrations observed in the afternoon and high concentrations at night. The principal component analysis and conditional probability function results revealed that the sources of mercury were similar to the other atmospheric pollutants such as SO2, CO, NO2 and PM2.5, and were mainly from industrial combustion plants in urban districts. Concentration weighted trajectory analysis using backward trajectories demonstrated that higher mercury concentrations were related to air masses from adjacent regions, indicating the importance of influences from local-to-regional scale sources. A synthesis of multi-decadal atmospheric mercury measurements in Lanzhou and other Chinese megacities revealed that atmospheric mercury concentrations were either generally stable or experienced a slight decrease, during a time when China implemented control measures on atmospheric pollution. Long-term atmospheric mercury observations in urban and background sites in China are warranted to assess mercury pollution and the effectiveness of China's mercury control policies.

© 2019 Elsevier B.V. To alleviate air pollution in western China, experiencing rapid economic growth following national western development strategies, an accurate and compressive assessment of PM2.5 sources is critical. Here, we firstly investigated the spatiotemporal variation in PM2.5 and analyzed its association with weather conditions and emission changes. Then, WRF-Chem simulations were conducted for an entire year to obtain various emission sectors' contributions to the PM2.5 mass by a hybrid method, which considers both the proportions of various components as well as each sector contributing to these components. The results showed that residential emissions had the largest contribution to PM2.5 because of its dominating contribution for primary components of PM2.5 (BC and POA), which can explain >70% of PM2.5. Seasonally, the residential contributions to PM2.5 were higher in the non-monsoon period than in the monsoon period because of the higher contribution ratios to primary components. Regionally, as an essential source of the gaseous precursors, the industrial and transportation sectors were the second-largest contributors to PM2.5 in the highly populated urban (HP) and remote background (RM) regions, respectively. Further assessment of emission reduction measures indicated that eliminating 50% of residential emissions induced a 29.4% and 33.1% decrease in the annual PM2.5 mass of the HP and RM regions, respectively, with higher decrease proportions in non-monsoon. By comparison, eliminating 50% of industrial emissions caused a significantly lower decrease in PM2.5 for both HP (10%) and RM (4.6%). Eliminating 50% of transportation emissions led to PM2.5 concentrations to decline by 9.3% in RM, which was greater than the 4.6% reduction caused by eliminating 50% of industrial emissions. Therefore, in addition to focusing on the residential sector, especially in non-monsoon in western China, the transportation sector should be a focus to alleviate PM2.5 pollution on the Tibetan Plateau. The outcome of this study provides valuable information for policy-makers to make strategies to mitigate air pollution in western China.

Located in the world’s ‘Third Pole’ and a remote region connecting the Indian Ocean plate and the Eurasian plate, Qomolangma National Nature Preserve (QNNP) is an ideal region to study the long-range transport of atmospheric pollutants. In this study, gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) were continuously measured during the Indian monsoon transition period in QNNP. A slight increase in GEM concentration was observed from the period preceding the Indian Summer Monsoon (1.31±0.42 ng m−3) to the Indian Summer Monsoon period (1.44±0.36 ng m−3), while significant decreases were observed in GOM and PBM concentrations, decreasing from 35.2±18.7 to 19.1±11.0 pg m−3 and from 30.5±12.6 to 24.7±19.9 pg m−3, respectively. A unique daily pattern of GEM concentration in QNNP was observed, with a peak value before sunrise and a low value at noon. Unexpectedly, GOM concentrations (with a mean value of 21.3±13.5 pg m−3) in this region were considerably higher than the values in other clean or even polluted regions. A cluster analysis indicated that the air masses transported to QNNP changed significantly at different stages of the monsoon, and the major potential Hg sources shifted from north India and west Nepal to east Nepal and Bangladesh. With large coverage of glacier in QNNP, local glacier winds could enforce the transboundary transport of pollutants and transport the polluted air masses to the Tibetan Plateau. It should be noted that the atmospheric Hg concentrations in QNNP are higher than the reported values in some background regions, which addresses the need for a more specific identification of Hg sources in QNNP and the importance of international cooperation for global Hg controls.

In this work, we investigate the NOx emissions inventory in Seoul, South Korea, using a regional ozone monitoring instrument (OMI) NO2 product derived from the standard NASA product. We first develop a regional OMI NO2 product by recalculating the air mass factors using a high-resolution (4 km × 4 km) WRF-Chem model simulation, which better captures the NO2 profile shapes in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the subpixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 times larger in the Seoul metropolitan region and >2 times larger near substantial point sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the South Korea–United States Air Quality (KORUS-AQ) field campaign. NOx emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emissions inventory yields a NOx emissions rate of 227±94 kt yr−1, while the bottom-up inventory itself within a 40 km radius of Seoul yields a NOx emissions rate of 198 kt yr−1. Using the top-down approach on the regional OMI NO2 product, we derive the NOx emissions rate from Seoul to be 484±201 kt yr−1, and a 353±146 kt yr−1 NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53 % and 36 % in the bottom-up inventory using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 and NOy simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate. When NOx emissions in the WRF-Chem model are increased by a factor of 2.13 in the Seoul metropolitan area, there is better agreement with KORUS-AQ aircraft observations and the recalculated OMI NO2 tropospheric columns. Finally, we show that by using a WRF-Chem simulation with an updated emissions inventory to recalculate the air mass factor (AMF), there are small differences (∼8 %) in OMI NO2 compared to using the original WRF-Chem simulation to derive the AMF. This suggests that changes in model resolution have a larger effect on the AMF calculation than modifications to the South Korean emissions inventory. Although the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NOx emissions estimates.

Total gaseous mercury (TGM) concentrations were continuously measured at the Nam Co Station, a remote high altitude site (4730 m a.s.l.), in the inland Tibetan Plateau, China from January 2012 to October 2014 using a Tekran 2537B instrument. The mean concentration of TGM during the entire monitoring period was 1.33 ± 0.24 ng m−3 (mean ± standard deviation (SD)), ranking the lowest value among all continuous TGM measurements reported all over China, and was lower than most of sites in the Northern Hemisphere. This indicated the pristine atmospheric environment in the inland Tibetan Plateau. Long-term TGM at the Nam Co Station exhibited a slight decreasing trend especially for summer seasons. The seasonal variation of TGM was characterized by high levels during warm seasons and low levels during cold seasons. Diurnal variations of TGM exhibited uniform patterns in different seasons: the daily maximum was reached in the morning (around 2–4 hours after sunrise), followed by a decrease until sunset and a subsequent build-up at night, especially in the summer and the spring. Regional surface re-emission and vertical mixing were two major contributors to the temporal variations of TGM while long-range transported atmospheric mercury promoted elevated TGM during warm seasons. Results of multiple linear regression (MLR) revealed that humidity and temperature were the principal covariates of TGM. Potential source contribution function (PSCF) and FLEXible PARTicle dispersion model (WRF-FLEXPART) results indicated that the likely high potential source regions of TGM to the Nam Co are central and eastern Indo-Gangetic Plain (IGP) during the measurement period with high biomass burning and anthropogenic emissions. The seasonality of TGM at Nam Co was in phase with the Indian Monsoon Index, implying Indian Summer Monsoon as an important driver for transboundary transport of air pollution into the inland Tibetan Plateau. Our results provided atmospheric mercury baseline in the remote inland Tibetan Plateau and serve as new constraint for assessment of Asian mercury emission and pollution.

Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons.