Severe Air Pollution Episodes Research Articles

In-vitro human lung cell injuries induced by urban PM2.5 during a severe air pollution episode: Variations associated with particle components

Environmental air pollutants pose significant threats to public health, especially the toxicity and diseases caused by the atmospheric fine particulate matters (PM2.5). Since the health risks vary with both the concentrations and compositions of PM2.5 which are determined by aerosol sources, how are their toxic effects relevant to the pollution level becomes an important issue, such as the haze episodes covering clean and polluted days. With the transition from non-pollution to pollution stage, daily PM2.5 samples were collected from both the urban and industrial areas of Nanjing city, eastern China, covering a typical haze event in autumn-winter. Their unpropitious effects on human lung epithelial cells (A549) were compared by in vitro toxicity assays and chemical component analysis. Both air levels and cytotoxic effects of PM2.5 varied with the transition of haze event. Although the concentration of PM2.5 in air is of course the highest in pollution stage driven by local stable meteorological condition, unit mass of them posed higher toxicity (lower cell viability and higher IL-6) but induced lower cell oxidative (evidences of ROS and NQO1 mRNA expression) and inflammatory cytokine TNF-α responses than those particles during non-pollution stage. These patterns were explained by the metals and water-soluble components decreased with the haze development. Non-soluble particulate carbonaceous aerosol compositions might play a significant role in inducing cytotoxicity. Moreover, the regional pattern of episode pollution weakened the spatial variation within a city scale. Since the haze development intensified both the quantity and toxicity of PM2.5 in air, the health risks of overall aerosol exposure were synthetically amplified during haze weather, so the increased air particles with higher toxic components from fuel combustion sources should be key targets of pollution control.

Future liasing of the lockdown during COVID-19 pandemic: The dawn is expected at hand from the darkest hour

The lockdown during COVID-19 pandemic has converted the world into new experimental laboratories, which may reveal temporal or spatial comparative analysis data. However, some startling information is gathered in terms of reduced premature mortality cases associated with air and water quality improvement, enhanced e-learning on a broader platform, work from home, and successful e-health. The decline in vehicular density on roads and congestion leads to reduced energy consumption and associated greenhouse gases (GHG) and other pollutants emission. The lockdown has also been identified as a possible emergency measure to combat severe air pollution episodes. Similarly, industrial pollution has been recognized as one of the primary causes of water resource pollution and would, therefore, bring change in policy vis-à-vis groundwater pollution control. Our findings suggest that the results of successful e-learning and work from home would be a permanent shift from conventional modes in the near future due to a drastic reduction in socio-economic cost. Our critical analysis also highlights that with such temporary lockdown measures acute/chronic ill-effects of anthropogenic perturbations on planet earth can be effectively estimated through sociocultural, socioeconomical and socio-political/sociotechnological nexus.

Daytime air pollution transport mechanisms in stable atmospheres of narrow versus wide urban valleys

Transport of air pollutants emitted from urban valleys can be strongly restricted by interactions between static and dynamic factors including topographic forcing, low-level atmospheric stability related to temperature inversions, and urban heat island-induced circulations. Interplay between these processes has a complex and dynamic nature, and is determinant for the evolution of different ventilation mechanisms and the associated impacts on air quality. Here we investigate these transport mechanisms through large eddy simulations using EULAG, an established model for multiscale flows, to simulate an idealized atmospheric environment in narrow versus wide urban valleys during critical conditions for air quality (high atmospheric stability). Our results show how the ventilation of valleys depends on a dynamic (variable during the daytime) balance between interacting and sometimes competing processes related to thermally-driven slope flows, urban heat island-induced flows, and the trapping effect of atmospheric stability; and how valley width affects this balance. Particularly important is that the time-space distribution of pollutants (a passive tracer) varies greatly between both valleys despite having the same urban area and emission rates. These variations lead to pollutants being mostly concentrated in different areas of the narrow and wide valleys. We discuss the mechanisms behind these results and their potential implications for real urban valleys. Further understanding of these mechanisms is crucial for explaining the occurrence of severe air pollution episodes and informing related decision-making processes in urban valleys.

Sources and atmospheric dynamics of organic aerosol in New Delhi, India: insights from receptor modeling

Abstract. Delhi, India, is the second most populated city in the world and routinely experiences some of the highest particulate matter concentrations of any megacity on the planet, posing acute challenges to public health (World Health Organization, 2018). However, the current understanding of the sources and dynamics of PM pollution in Delhi is limited. Measurements at the Delhi Aerosol Supersite (DAS) provide long-term chemical characterization of ambient submicron aerosol in Delhi, with near-continuous online measurements of aerosol composition. Here we report on source apportionment based on positive matrix factorization (PMF), conducted on 15 months of highly time-resolved speciated submicron non-refractory PM1 (NR-PM1) between January 2017 and March 2018. We report on seasonal variability across four seasons of 2017 and interannual variability using data from the two winters and springs of 2017 and 2018. We show that a modified tracer-based organic component analysis provides an opportunity for a real-time source apportionment approach for organics in Delhi. Phase equilibrium modeling of aerosols using the extended aerosol inorganics model (E-AIM) predicts equilibrium gas-phase concentrations and allows evaluation of the importance of the ventilation coefficient (VC) and temperature in controlling primary and secondary organic aerosol. We also find that primary aerosol dominates severe air pollution episodes, and secondary aerosol dominates seasonal averages.

Exploring spatial and temporal distributions of air quality in China from 2013 to 2017

In recent years, severe and persistent air pollution episodes in China have drawn wide public concern. It is necessary to analyse and evaluate the current status of air quality of China, which is significant for sustainable urbanization and environment protection. In this study, we investigate the air quality of the key 74 cities in China from 2013 to 2017 based on the data from the Ministry of Environmental Protection of the People’s Republic of China. With the use of ArcGIS and Stata, we identify the spatial correlation and agglomeration of the air quality. The significant value of Moran’s I test shows positive autocorrelation between the cities and verifies the spatial spill over effect of the air pollution. From the temporal dimension, we find the seasonal variations and an overall better-off trend of air quality. This improvement over the past year benefits from the strict regulations and governance from both central and local government. Our research provides an updated measurement and detailed illustration of the air condition in China. With the exploration of spatial and temporal distributions of air quality, the research findings facilitate the future governance and guidelines for sustainable environmental development.

What caused severe air pollution episode of November 2016 in New Delhi?

In recent years, South Asia is experiencing severely degraded air quality, with particulate matter less than 2.5 μm (PM2.5) reaching unprecedented high levels. Here, we investigate a severe air pollution episode (SAPE) witnessed in New Delhi during 1–7 November 2016. This was a very unusual air pollution episode wherein air quality index exceeded >500 and was persistent for about a week encapsulating the entire Indo-Gangetic Plain (IGP). We demonstrate that a stagnant weather condition was the dominant cause of the SAPE. Mean concentration of PM2.5 in New Delhi before, during, and after the SAPE were 142 μg/m3, 563 μg/m3, and 240 μg/m3, respectively. Satellite-based aerosol optical depth (AOD), ultraviolet-aerosol index (UV-AI) and surface carbon monoxide (CO) concentrations also showed significant enhancements over large locale spatially by about 50–70% during the SAPE. A large and simultaneous increase in UV-AI and CO downwind of a large number of fire hotspots (Punjab and Haryana) is a clear indication of biomass burning aerosols. Analysis of absorption Ångström exponent further substantiates this finding, showing a large fraction of light absorbing carbonaceous-type aerosols. Radiosonde observations clearly showed that stagnant atmospheric conditions led to SAPE in New Delhi by allowing pollution to accumulate and persist in the near-surface environment. As a result new particle formation was suppressed due to very high pre-existing aerosol concentrations during the SAPE. The heating rate induced by light absorbing aerosols into an atmospheric layer during SAPE was also very high (3.1 ± 0.7 K/day). These findings will help in understanding air quality and climate effects, as well as in formulating policies to mitigate these complex pollution episodes in an anthropogenic future.

Can Data Assimilation of Surface PM2.5 and Satellite AOD Improve WRF-Chem Forecasting? A Case Study for Two Scenarios of Particulate Air Pollution Episodes in Poland

Based on the Weather Research and Forecasting model with Chemistry (WRF-Chem) model and Gridpoint Statistical Interpolation (GSI) assimilation tool, a forecasting system was used for two selected episodes (winter and summer) over Eastern Europe. During the winter episode, very high particular matter (PM2.5, diameter less than 2.5 µm) concentrations, related to low air temperatures and increased emission from residential heating, were measured at many stations in Poland. During the summer episode, elevated aerosol optical depth (AOD), likely related to the transport of pollution from biomass fires, was observed in Southern Poland. Our aim is to verify if there is a relevant positive impact of surface and satellite data assimilation (DA) on modeled PM2.5 concentrations, and to assess whether there are significant differences in the DA’s impact on concentrations between the two seasons. The results show a significant difference in the impact of surface and satellite DA on the model results between the summer and winter episode, which to a large degree is related to the availability of the satellite data. For example, the application of satellite DA raises the factor of two statistic from 0.18 to 0.78 for the summer episode, whereas this statistic remains unchanged (0.71) for the winter. The study suggests that severe winter air pollution episodes in Poland and Eastern Europe in general, often related to the dense cover of low clouds, will benefit from the assimilation of surface observations rather than satellite data, which can be very sparse in such meteorological situations. In contrast, the assimilation of satellite data can have a greater positive impact on the model results during summer than the assimilation of surface data for the same period.

Development of an APP as alert system for severe air pollution episodes

TPS 641: Policies, interventions, communication, Exhibition Hall, Ground floor, August 28, 2019, 3:00 PM - 4:30 PM Background/Aim: Severe Air Pollution Episodes (SAPE) are often observed in areas in Europe where high anthropic pressure (e.g. highly populated urban areas with a high traffic load) and emission levels in combination with meteorological air stagnation can increase air pollution concentrations above EU limits for several consecutive days. Methods: The Interreg Central Europe AWAIR project (“EnvironmentAl integrated, multilevel knoWledge and approaches to counteract critical AIR pollution events, improving vulnerable citizens quality of life in Central Europe Functional Urban Areas”) addresses the issue of air quality, specifically SAPEs, in three functional urban areas: The city of Parma, Italy; Zugló in the Budapest metropolitan area, Hungary and Katowice in the Upper Silesia Metropolitan Area, Poland. Within this project we are going to develop a joint forecasting system for SAPEs that is linked to an APP for mobile devices to alert citizens and give advice for individual adaptation and mitigation measures. Results: While a joint forecasting system is planned, each area will have their own individual limits for triggering alerts to account for varying characteristics such as regional meteorology or alert regulations and air pollution levels. Susceptible subgroups e.g. children or asthmatics will get specially tailored advice. In addition, mitigation measures will be promoted such as the use of public transport or refraining from using small scale furnaces. Also, local political actions for example driving bans or free use of public transport can be disseminated via the APP. Conclusions: Through the alert system the AWAIR APP can contribute not only to better health by informing (susceptible) individuals about the best behaviour in case of SAPEs but ideally also to decrease the length and severity of a SAPE.

The high-resolution estimation of sulfur dioxide (SO2) concentration, health effect and monetary costs in Beijing.

Severe air pollution episodes with high SO2 loading have been frequently observed during the last decades in Beijing and have caused a noticeable damage to human health. To advance the spatiotemporal prediction of SO2 exposure in Beijing, we developed the monthly land use regression (LUR) models using daily SO2 concentration data collected from 34 monitoring stations during 2016 and 7 categories of potential independent variables (socio-economic factors, traffic and transport, emission source, land use, meteorological data, building morphology and Geographic location) in Beijing. The average adjusted R2 of 12 final LUR models was 0.62, and the root-mean-squared error (RMSE) was 4.12 μg/m3. The LOOCV R2 and RMSE of LUR models reached 0.56 and 5.43 μg/m3, respectively, suggesting that the LUR models achieved the satisfactory performance. The prediction results suggested that the average SO2 level in Beijing was 11.06 μg/m3 with the highest one up to 22.49 μg/m3 but the lowest one down to 3.86 μg/m3. The SO2 exposure showed strong spatial heterogeneity, which was much higher in the southern area than that in the northern in Beijing. The mortality and morbidity due to the excessive SO2 concentration were estimated to be 73 (95% CI:(38-125)) and 27854 (95% CI:(13852-41659)) cases per year in Beijing, leading to economic cost of 35.76 (95% CI:(16.45-54.06)) and 441.47 (95% CI:(318.31-562.04)) million RMB Yuan in 2016, respectively. This study clarified the intra- and inter-regional transport modeling of the SO2 pollution in Beijing and supplied an important support for the future air-quality and public health management strategies.

Large‐scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over China

AbstractThe frequent episodes of severe air pollution over China during recent years have posed serious health threats to densely populated eastern China. Although several studies investigated the linkage between enhanced severity and frequency of air pollution and the large‐scale weather patterns over China, the day‐to‐day covariability between them, as well as its local and remote mechanisms, has not been systematically documented. The wintertime synoptic covariability between PM2.5 and large‐scale meteorological fields is studied using surface observations of PM2.5 in 2013/2014–2016/2017 and ERA‐Interim meteorological fields through maximum covariance analysis (MCA). The first MCA mode (MCA1) suggests a consistent accumulation of ambient PM2.5 as a result of weakened winds that block the pollutant removal passage in heavily polluted areas of eastern China, as well as moist air from southeast coast favoring haze formation. A northeast–southwest belt that extends into northeastern China and central China on each end is more sensitive to MCA1. The second MCA mode (MCA2) shows a north–south dipole in PM2.5 linked to the contrast of boundary layer height and surface wind speed between northern and southern regions of China. Spatial patterns of both modes are supported by the GEOS‐Chem chemistry transport model with realistic emission inventory. The spatial patterns of the two modes are robust on the interannual time scales. Based on that, we investigate the variability of the first two modes of the identified modes on the multidecadal scale by projecting GPM_500 pattern to 1981–2010. Correlation analysis of the projected time series and climate indices over 30 years indicates the possible linkage of Arctic oscillation, ENSO indices, Pacific decadal oscillation and east Atlantic/western Russia to regional air pollution patterns over China.

Characteristics of six criteria air pollutants before, during, and after a severe air pollution episode caused by biomass burning in the southern Sichuan Basin, China

Biomass burning (BB) seriously affect air pollution, human health and global climate. A severe pollution episode (PE) caused by BB was investigated in the southern Sichuan Basin (SSB), one of the most polluted areas in China. Hourly variations in criteria air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3), chemical components, and sources of PM2.5 before, during, and after the severe regional air PE were characterized at three sites, namely Neijiang (NJ), Zigong (ZG), and Yibin (YB). The results showed that combination of intensive pollution from BB, stable meteorological conditions, and the basin topography caused this severe regional PE in the SSB. The average daily concentrations of PM2.5 during the PE were 1.8–6 times those measured during the periods before and after the PE, and 4.0–7.4 times that of World Health Organization air quality guidelines in the SSB. The highest PM levels occurred in ZG, where the peak values of PM2.5 and PM10 reached 536 μg m−3 and 578 μg m−3 at night, respectively. PM10, NO2, and CO also increased dramatically at night in the SSB. O3 formation was affected by BB, showing lower levels at night but higher levels in the day during the PE than before and after the PE, whereas SO2 levels were not affected. Sulfate–nitrate–ammonium in PM2.5 was the main chemical compositions before the PE, whereas organic matter (OM) and K+ became characteristics compositions during and after the PE. Higher OC/EC and Kexcess/EC ratios were observed during the PE and Kexcess/EC ratio was a better indicator of BB in the SSB than OC/EC ratio. The results of a positive matrix factorization model indicated that BB was the most significant contributor to PM2.5 during the PE, accounting for 58% in NJ, 65% in ZG, and 56% in YB. Backward trajectory analysis confirmed that the SSB is susceptible to pollutants from Chongqing and other surrounding cities, especially in ZG and NJ, due to the unique topography of the basin. Our findings suggest that BB in the basin topography can cause severe regional air pollution events at night, thus supporting the critical need for BB control in the basin to improve regional air quality.

Analysis of a severe air pollution episode in India during Diwali festival – a nationwide approach

Air pollution events have been a subject of major concern worldwide in recent years, since their frequency and intensity is increasing with time. An alarmingly high air pollution episode was observed in some parts of India during late October to the end of November in the year 2016. The Air Quality Index was observed to vary from poor to severe in northern and western parts of India, while it was satisfactory to moderate in the east and south of the country. The causes of this observed high pollution episode are examined in this paper. Apart from the Diwali effect on air pollution the study findings indicated the importance of biomass burning over India.

Secondary organic aerosol enhanced by increasing atmospheric oxidizing capacity in Beijing–Tianjin–Hebei (BTH), China

Abstract. The implementation of the Air Pollution Prevention and Control Action Plan in China since 2013 has profoundly altered the ambient pollutants in the Beijing–Tianjin–Hebei (BTH) region. Here we show observations of substantially increased O3 concentrations (about 30 %) and a remarkable increase in the ratio of organic carbon (OC) to elemental carbon (EC) in BTH during the autumn from 2013 to 2015, revealing an enhancement in atmospheric oxidizing capacity (AOC) and secondary organic aerosol (SOA) formation. To explore the impacts of increasing AOC on the SOA formation, a severe air pollution episode from 3 to 8 October 2015 with high O3 and PM2.5 concentrations is simulated using the WRF-Chem model. The model performs reasonably well in simulating the spatial distributions of PM2.5 and O3 concentrations over BTH and the temporal variations in PM2.5, O3, NO2, OC, and EC concentrations in Beijing compared to measurements. Sensitivity studies show that the change in AOC substantially influences the SOA formation in BTH. A sensitivity case characterized by a 31 % O3 decrease (or 36 % OH decrease) reduces the SOA level by about 30 % and the SOA fraction in total organic aerosol by 17 % (from 0.52 to 0.43, dimensionless). Spatially, the SOA decrease caused by reduced AOC is ubiquitous in BTH, but the spatial relationship between SOA concentrations and the AOC is dependent on the SOA precursor distribution. Studies on SOA formation pathways further show that when the AOC is reduced, the SOA from oxidation and partitioning of semivolatile primary organic aerosol (POA) and co-emitted intermediate volatile organic compounds (IVOCs) decreases remarkably, followed by those from anthropogenic and biogenic volatile organic compounds (VOCs). Meanwhile, the SOA decrease in the irreversible uptake of glyoxal and methylglyoxal on the aerosol surfaces is negligible.

Assessment of Emission Reduction Scenarios with a Focus on the Impact of Vehicle Fleets on Tehran Air Quality: Case Study

In recent years, the city of Tehran has frequently experienced severe air pollution episodes, and the increase in the use of vehicles has exacerbated this critical situation. It is unclear to what extent each vehicle category contributes to the production of pollution during a pollution event. For this purpose, a combination of the weather research and forecasting (WRF) and the Comprehensive Air Quality Model with Extensions (CAMx) modeling systems was used to simulate the distributions of pollutant concentrations over Tehran in a pollution episode from December 3 to 23, 2017. First, the performance of the modeling system was evaluated with respect to the simulation outputs against observations. Results showed satisfactory performance by the models in predicting meteorological parameters and pollutant concentrations. There were some discrepancies between measured and simulated pollutant levels that might have several causes, including, for example, not considering dust emissions in the system. The second step focused on the assessment of different emission scenarios to quantify the impact of each vehicle fleet in producing pollution during such severe episodes. For this reason, eight different scenarios were considered in which the emissions of each vehicle category were entirely eliminated from the corresponding scenario. The results show that the removal of passenger cars and motorcycles could have the most significant impact on PM2.5 reduction, with a maximum drop of 32% and 30%, respectively. In addition, the NO2 concentrations could be reduced by about 20% and 10% as a result of the removal of passenger cars and motorcycles, respectively. Finally, two traffic schemes with a main focus on the role of motorcycles on the degradation of Tehran’s air quality were also examined for the same episode.

CAUSES AND CONTROL MEASURES OF URBAN AIR POLLUTION IN CHINA

Air pollution is continuously increasing severe health problems in all over the world conscientious for copious diseases and deaths. Extensive economic growth, especially in urban areas of China, has led to escalating episodes of severe air pollution. In the past few decades, continuous industrialization and urbanization in China improved the living standards of their people but also increase the air pollution, which badly affected on health. In early 2002, China has carried out certain steps for the management and control of air pollution, but unfortunately there approaches towards implementation and governance is unsatisfied, after passing the so many years still have haze and other serious air pollution issues, which not only damage the environment but also destroy the people health. Recent, development, industrialization, and urbanization, air pollution has become one of the major and critical problems. Thus, it is very important to examine the cause and source of air pollution, treatment and effectively resolve the problems. Based on the causes and treatment of urban air pollution, this short communication would be a guideline for further control measures and technology development.

Relationships between the planetary boundary layer height and surface pollutants derived from lidar observations over China: regional pattern and influencing factors

Abstract. The frequent occurrence of severe air pollution episodes in China has been a great concern and thus the focus of intensive studies. Planetary boundary layer height (PBLH) is a key factor in the vertical mixing and dilution of near-surface pollutants. However, the relationship between PBLH and surface pollutants, especially particulate matter (PM) concentration across China, is not yet well understood. We investigate this issue at ∼1600 surface stations using PBLH derived from space-borne and ground-based lidar, and discuss the influence of topography and meteorological variables on the PBLH–PM relationship. Albeit the PBLH–PM correlations are roughly negative for most cases, their magnitude, significance, and even sign vary considerably with location, season, and meteorological conditions. Weak or even uncorrelated PBLH–PM relationships are found over clean regions (e.g., Pearl River Delta), whereas nonlinearly negative responses of PM to PBLH evolution are found over polluted regions (e.g., North China Plain). Relatively strong PBLH–PM interactions are found when the PBLH is shallow and PM concentration is high, which typically corresponds to wintertime cases. Correlations are much weaker over the highlands than the plains regions, which may be associated with lighter pollution loading at higher elevations and contributions from mountain breezes. The influence of horizontal transport on surface PM is considered as well, manifested as a negative correlation between surface PM and wind speed over the whole nation. Strong wind with clean upwind air plays a dominant role in removing pollutants, and leads to obscure PBLH–PM relationships. A ventilation rate is used to jointly consider horizontal and vertical dispersion, which has the largest impact on surface pollutant accumulation over the North China Plain. As such, this study contributes to improved understanding of aerosol–planetary boundary layer (PBL) interactions and thus our ability to forecast surface air pollution.

Exploring the most influential part of atmospheric circulation in the formation of severe air pollution episodes in the Greater Tehran

Availability of long-term data, information, and weather charts are essential parts of providing an accurate weather forecast by the synoptic method. The availability of air pollution data and information indicators from 1999 have imposed limitations in precise recognition of influential weather conditions on the formation of acute air pollution episodes, timely implementation of pollution control measures, and its management. One way of resolving those problems is to find out more similar synoptic circulation patterns in the past. To do that, two statistical methods, i.e., wavelet transform and bootstrap significance test, have been employed to identify more important and significant features of atmospheric circulation that provide suitable conditions for the formation of those episodes. The method has been used to extend the data and information availability to 30 years. Those methods not only helped us to find more synoptic circulation patterns associated with intense air pollution episodes but also made the process of finding them simple, fast, and precise. By this study, we have found that the transient weather systems that passes over the north of Europe and Russia, cutoff lows over the eastern Mediterranean Sea, deflection of high-speed atmospheric currents (jet streams) over the Scandinavian region towards the south, presence of a pressure ridge over the west of the region of study, appearance of a low center above the north of the Caspian Sea, and low-pressure areas over the Arabian Sea and North Indian Ocean (especially during the Monsoon season) have been the most influential parts of atmospheric circulation in the formation of highly polluted episodes in Tehran.

Ambient PM2.5 Human Health Effects—Findings in China and Research Directions

Exposure to fine particulate matter (PM) results in adverse health outcomes. Although this is a global concern, residents of China may be particularly vulnerable due to frequent severe air pollution episodes associated with economic growth, industrialization, and urbanization. Until 2012, PM2.5 was not regulated and monitored in China and annual average concentrations far exceeded the World Health Organizations guidelines of 10 μg/m3. Since the establishment of PM2.5 Ambient Air Quality Criteria in 2012, concentrations have decreased, but still pose significant health risks. A review of ambient PM2.5 health effect studies is warranted to evaluate the current state of knowledge and to prioritize future research efforts. Our review found that recent literature has confirmed associations between PM2.5 exposure and total mortality, cardiovascular mortality, respiratory mortality, hypertension, lung cancer, influenza and other adverse health outcomes. Future studies should take a long-term approach to verify associations between exposure to PM2.5 and health effects. In order to obtain adequate exposure assessment at finer spatial resolutions, high density sampling, satellite remote sensing, or models should be employed. Personal monitoring should also be conducted to validate the use of outdoor concentrations as proxies for exposure. More research efforts should be devoted to seasonal patterns, sub-population susceptibility, and the mechanism by which exposure causes health effects. Submicron and ultrafine PM should also be monitored and regulated.

Exploring atmospheric stagnation during a severe particulate matter air pollution episode over complex terrain in Santiago, Chile

A severe air quality degradation event occurred in the Santiago Metropolitan Area (SMA), Chile, in June 2014. Meteorological and air quality measurements from 11 stations in the area as well as numerical simulations using the Weather and Research Forecasting (WRF) model were used to explain the main reasons for the occurrence of elevated particulate matter (PM) concentrations. The conditions were characterized with formation of a coastal low in central Chile between the southeastern anticyclone and a high-pressure system over Argentina. At a local scale, these conditions generated a depression at the base of the inversion layer, an increase in the vertical thermal stability, lower humidity and low-wind conditions, which were conducive to a decrease in pollutant dispersion and insufficient ventilation of the polluted air. Measurements and simulations using the WRF model revealed a vertical structure of the boundary layer during these stagnant conditions and provided a basis for a trajectory analysis. The back-trajectory calculation showed that the transport of air parcels was contained in the valley during the highest concentrations. The analysis also enabled the definition of the threshold values of a simple indicator of air pollution (ventilation coefficient, VC), which confirmed the evolution of the episode and divided the observed daily concentrations into two groups, with one including values above the limits prescribed by the national air quality standards (NAQS) and the other including values below these limits. For the SMA, the daily PM concentrations above the NASQ limits were associated with an overall mean threshold value of VC below 500 m2 s−1 (for PM2.5) and 300 m2 s−1 (for PM10). To apply the VC analysis to other pollutants and different geographic locations, different threshold values should be evaluated.

NO<sub>2</sub>-initiated multiphase oxidation of SO<sub>2</sub> by O<sub>2</sub> on CaCO<sub>3</sub> particles

Abstract. The reaction of SO2 with NO2 on the surface of aerosol particles has been suggested to be important in sulfate formation during severe air pollution episodes in China. However, we found that the direct oxidation of SO2 by NO2 was slow and might not be the main reason for sulfate formation in ambient air. In this study, we investigated the multiphase reaction of SO2 with an O2 ∕ NO2 mixture on single CaCO3 particles using Micro-Raman spectroscopy. The reaction converted the CaCO3 particle to a Ca(NO3)2 droplet, with CaSO4 ⚫ 2H2O solid particles embedded in it, which constituted a significant fraction of the droplet volume at the end of the reaction. The reactive uptake coefficient of SO2 for sulfate formation was on the order of 10−5, which was higher than that for the multiphase reaction of SO2 directly with NO2 by 2–3 orders of magnitude. According to our observations and the literature, we found that in the multiphase reaction of SO2 with the O2 ∕ NO2 mixture, O2 was the main oxidant of SO2 and was necessary for radical chain propagation. NO2 acted as the initiator of radical formation, but not as the main oxidant. The synergy of NO2 and O2 resulted in much faster sulfate formation than the sum of the reaction rates with NO2 and with O2 alone. We estimated that the multiphase oxidation of SO2 by O2 initiated by NO2 could be an important source of sulfate and a sink of SO2, based on the calculated lifetime of SO2 regarding the loss through the multiphase reaction versus the loss through the gas-phase reaction with OH radicals. Parameterization of the reactive uptake coefficient of the reaction observed in our laboratory for further model simulation is needed, as well as an integrated assessment based on field observations, laboratory study results, and model simulations to evaluate the importance of the reaction in ambient air during severe air pollution episodes, especially in China.