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An air pollution process in Jiangsu Province on December 22–23, 2016 is discussed by analyzing various data set, including the meteorological observation data, the reanalysis data from National Centers for Environmental Prediction (NCEP), the Air Quality Index (AQI), the PM2.5 and PM10 concentrations data, and the airflow backward trajectory model of National Oceanic and Atmospheric Administration (NOAA). The results show that the air pollution episode was under the background of a medium cold front from the west of the Hetao area, and caused by regional transport of pollutants from North China. The primary pollutant was PM2.5 and PM10. The PM2.5 and PM10 concentrations increase significantly 4–6 h after the cold front passing and reached the peak in 13–24 h. The obvious lag phenomena of the rising period and the peak-moment of PM2.5 and PM10 concentrations were found at the Suzhou, Huai'an, Taizhou and Xuzhou stations, and the maximum of 3h-allobaric, the maximum and average values of the wind speed near the ground were larger one by one at the four stations respectively in the northwestern Jiangsu, north-central Jiangsu, along with the Yangtze river Jiangsu, and southeastern Jiangsu. The period of middle –heave level pollution in Suzhou was 7–9 h later than in Huai'an and Taizhou, and was 24 h later than in Xuzhou, because of the lower PM2.5 and PM10 concentrations at early December 21, the delay of pollutants from upstream, and the larger wind speed from the boundary layer to the surface in southeastern Jiangsu. WRF-Chem model can well reveal the pollutant transport process. The high-value zone has a close relationship with the position of cold front. At 1200 LST on December 22, the cold front reached Xuzhou accompanied by high PM2.5 concentration. At 1400 LST on December 22, the cold front advanced to Huai'an. The high PM2.5 concentration zone moved south alongside the cold front and covered Xuzhou and Huai'an. Suzhou, far away from the upstream, was less vulnerable to pollutant transport. The high-value did not fell until the northwest wind shifted to the north wind. The backward trajectory analysis of air pollution also indicated that regional transport of pollutants from North China led to the middle –heave level pollution weather.

The meteorology of air pollution in Los Angeles (LA) is studied via daily near-surface air chemistry, aerosol and weather data assimilated from insitu and satellite measurements in the period 2005–2016. Atmospheric fields are regressed onto seasonal air pollution indices and reveal that a ridge of high pressure north of California weakens the longshore circulation and reduces dispersion. A 10-case composite of atmospheric anomalies during winter air pollution episodes was analyzed. Periods of high nitrogen dioxide and carbon monoxide show increasing temperature gradients that induce the converging of land-seabreezes beneath a strengthened thermal inversion. The atmospheric environment of an air pollution episode in December 2005 reveals recirculating trajectories. Efforts to limit emissions have contributed to reductions of nitrogen dioxide, but other constituents remain a public health concern. Knowledge of weather conditions underlying air pollution episodes will improve warnings and the effectiveness of mitigating actions.

The Jianghuai area is an “important” region not only for its local pollutant accumulation but the belt for pollutant transportation between North China and the Yangtze River Delta during the winter half of the year (often from October to next February). In this study, a movable boundary layer conceptual model for the Jianghuai area in the winter half of the year is established based on the analyses of characteristics of atmospheric circulations and boundary layer dynamic conditions. This conceptual model can well explain the causes of air quality change and frequent fog-haze episodes. Variations of the intensity and range of the cold and warm fronts in the Jianghuai area in the winter half of the year lead to form a movable boundary in this area. When the southerly wind is strong, or affected by strong cold air mass, the air quality in the Jianghuai area may be excellent with a low air pollution index; Two atmospheric circulations provide favorable conditions for the fog-haze formation and maintenance in Jianghuai area: 1) When the shallow weak cold air mass is below the deep moist warm air mass, a stable temperature inversion occurs. The pollutants are transported to the Jianghuai area by the weak cold air mass, and local emissions also accumulate. As a result, a severe air pollution episode appears. 2) When the northerly cold air mass is as intense as the southerly moist warm air mass, the pollutants transported from North China as well as local emissions will continuously accumulate in the study area, which may lead to more severe air pollution. This conceptual model can help us analyze atmospheric diffusion capacity, and benefit the forecast and early warning of airflow stagnation area and fog-haze episode.

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.

International audience; 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.

We examined the impacts of aerosol-radiation interactions, including the effects of aerosol-photolysis interaction (API) and aerosol-radiation feedback (ARF), on surface-layer ozone (O3) concentrations during one multi-pollutant air pollution episode characterized by high O3 and PM2.5 levels from 28 July to 3 August 2014 in North China, by using the Weather Research and Forecasting with Chemistry (WRF-Chem) model embedded with an integrated process analysis scheme. Our results show that aerosol-radiation interactions decrease the daytime downward shortwave radiation at surface, 2 m temperature, 10 m wind speed, planetary boundary layer height, photolysis rates J[NO2] and J[O1D] by 115.8 W m−2, 0.56 °C, 0.12 m s−1, 129 m, 1.8 × 10−3 s−1 and 6.1 × 10−6 s−1, and increase relative humidity at 2 m and downward shortwave radiation in the atmosphere by 2.4 % and 72.8 W m−2. The weakened photolysis rates and changed meteorological conditions reduce surface-layer O3 concentrations by up to 11.4 ppb (13.5 %), with API and ARF contributing 74.6 % and 25.4 % of the O3 decrease, respectively. The combined impacts of API and ARF on surface O3 are further quantitatively characterized by the ratio of changed O3 concentration to local PM2.5 level. The ratio is calculated to be −0.14 ppb (µg m−3)−1 averaged over the multi-pollutant air pollution area in North China. Process analysis indicates that the weakened O3 chemical production makes the greatest contribution to API effect while the reduced vertical mixing is the key process for ARF effect. This study implies that future PM2.5 reductions will lead to O3 increases due to weakened aerosol-radiation interactions. Therefore, tighter controls of O3 precursors are needed to offset O3 increases caused by weakened aerosol-radiation interactions in the future.

After the 2020 Lunar New Year, the Chinese government implemented a strict nationwide lockdown to inhibit the spread of the Coronavirus Disease 2019 (COVID‐19). Despite the abrupt decreases in gaseous emissions caused by record‐low anthropogenic activities, severe haze pollution occurred in northern China during the COVID lockdown. This paradox has attracted the attention of both the public and the scientific community. By analyzing comprehensive measurements of air pollutants, planetary boundary layer (PBL) height, and surface meteorology, we show that the severe air pollution episode over northern China coincided with the abnormally low PBL height, which had reduced by 45%, triggering strong aerosol‐PBL interactions. After dynamical processes initiated the temperature inversion, the Beijing metropolitan area experienced a period with continuously shallow PBLs during the lockdown. This unprecedented event provided an experiment showcasing the role of meteorology, in particular, aerosol‐PBL interactions in affecting air quality., Key Points Based on nationwide observations, variations in air pollution and meteorology are discussed during the COVID lockdown.The severe air pollution during the lockdown coincided with abnormally shallow PBL triggering strong aerosol‐PBL interactions.Beijing experienced a period with continuously shallow PBLs initiated by dynamical processes, which warrant the formation of haze event.

Increasing air pollution levels in Delhi city is a major concern for regulators and stakeholders because of its associated critical and acute health impacts on human beings. During the onset of winter every year (in the months of October and November), people of Delhi were facing an increased level of pollutant concentrations from the last few years. The present study is an attempt to analyze the increased air pollution level episodic situation that occurred during 5–6th November 2016 in Delhi city. Four differently located air monitoring stations data on Air Quality Index, pollutant concentration, and meteorology from 25th October to 15th November 2016 are considered for the present analysis. The results indicate that PM2.5 concentrations exceeded 12–14 times whereas PM10 levels exceeded 8–17 times of NAAQS values of 60 µg/m3 and 100 µg/m3, respectively on 5–6th November 2016. The meteorological conditions were found worst for pollution dispersion on these two days which may be one of the reasons for high air pollution occurrence. However, NOx and SO2 concentration peaks were observed during Diwali days (Oct. 29–31, 2016). Critical analysis of the situation indicates that local sources are influencing the pollutant concentration significantly at the monitoring stations. Further, the qualitative evaluation of the graded response action plan (GRAP) indicates that the efficacy of a particular mitigation action on pollution reduction shall vary from site to site. Hence, in order to improve air quality in different zones, more emphasis needs to be given on regulating local activities as per suggested actions in addition to the regional level action plans.

Background: Physical exercise increases the absorbed dose of air pollutants, therefore it is commonly recommended to limit physical activity during air pollution episodes. Aim: To determine acute cardiorespiratory responses to ambient air pollution exposure during short controlled physical exercise in healthy males. Methods: 26 young adult males (age 22.8±2.2 years old) performed two 15-min. submaximal (70% HRmax) cycle-ergometer sessions: during air pollution episode (exposure trial) and when air quality was good (control trial). Data on air pollution was recorded in the study site (PM10) or provided by the closest monitoring station (PM2.5, NOx, SO2). Air pollutants concentrations during exposure trials were higher than during control trials (PM2.5: 80.3±35.6μg/m3 vs 28.4±14.9μg/m3, p Results: All results were within the normal values. There were no significant differences in spirometry between exposure and control trial. During exposure trial larger increase in diastolic blood pressure (DBP) was noted than during control trial directly after exercise (%change from baseline: 6.3±6.8% vs 1.7±7.1%, p=0.01) and at rest (4.2±6.3% vs -0.6±6.5%, p=0.005). Change in FeNO did not differ significantly between exposure and control trial after exercise, while at rest it was decreased only during control trial (0.0±11.8% vs -6.5±10.6%, p=0.03). Conclusions: In young and healthy males exposure to air pollution during exercise causes acute changes in FeNO and DBP.

Anthropogenic fossil fuel (FF) combustion, biomass burning (BB) and desert dust are main sources of air pollutants around the globe. The emission of the three sources in Asia are all very intensive and their influences on air quality is very important, especially in spring. In this study, we investigate the vertical distribution, transport characteristics, source contribution, and meteorological feedback of the dust, BB and FF aerosols in a unique pollution episode occurred in eastern Asia based on various measurement data and modelling methods. Ground-based observations indicated a persistent pollution episode dramatically changing from secondary fine particulate pollution to dust pollution in late March 2015 over the Yangtze River Delta (YRD) region, eastern China. The online-coupled meteorology–chemistry–aerosol modelling together with Lagrangian particle dispersion simulations were conducted to investigate the vertical structure, transport characteristics and mechanisms of the multi-scale, multi-source, and multi-day air pollution episode. The regional polluted continental aerosols mainly accumulated near surface by local anthropogenic emissions mixed with dust aerosols, downwash from the upper planetary boundary layer (PBL) and middle/lower troposphere (MLT), and further transported downwardly by large-scale cold fronts and warm conveyor belts. BB smoke from the Southeast Asia, mainly from forest burning in Indochina, were transported by westerlies around the altitude of 3 km from southern China to eastern China, further mixed with dust and FF aerosols in eastern China and experienced long-range transport over the subtropical Pacific Ocean. The three pollutant sources could all transport to eastern China, especially the YRD region around the latitude of 30° N, caused a structure of multi-layer pollutants and well mixed pollutants there. These solar absorption aerosols from FF, BB and dust could also cause significant feedback with MLT meteorology and then enhance local anthropogenic pollution. This study highlights the importance of intensive vertical measurement in the eastern China and the downwind Pacific Ocean with a focus of understanding the complex physical and chemical processes of various pollution sources, and also raises the needs of quantitative understanding of environmental and climate impacts of these pollution sources in regional even global scales.

Characteristics of two serious air pollution episodes (9-15 January, as the winter case; and 30 June to 1 July, as the summer case), which occurred in Beijing in 2013 were investigated and compared using multi-method observations and numerical simulations. During these two air pollution episodes, PM2.5 concentrations varied significantly within Beijing, with PM2.5 concentrations in southern parts of Beijing being significantly higher than in northern areas. Typically, heavy air pollution episodes begin in the southern parts and disperse towards the northern parts of Beijing. Clearly, synoptic patterns and the stability of atmospheric circulation patterns were the main factors controlling air pollution in Beijing. During the winter case, a warm center above 900hPa occurred over Beijing. Meanwhile, in the summer case, although there was only a weak inversion, the convective inhibition energy was strong (over 200J/kG). This clearly influenced the duration of the air pollution event. Except for the local accumulation and secondary atmospheric reactions in both cases, regional straw burnings contributed a lot to the PM2.5 concentrations in summer case. Using the CAMx model, we established that regional transport contributed almost 59% to the PM2.5 averaged concentration in Beijing in the winter case, but only 31% in the summer case. Thus, the winter case was a typical regional air pollution episode, while the summer case resulted from local accumulation straw burnings transportation and strong secondary atmospheric reactions. Given that air pollution is a regional problem in China, consistent and simultaneous implementation of regional prevention and control strategies is necessary to improve regional air quality.

Previous studies have suggested that pollutant concentrations have the characteristics of initially rising and later falling in the main impact area of a typhoon. Whether this occurs in the typhoon's periphery or in zones even further away is still unknown. Based on ground observations of pollutant concentrations, meteorological parameters, aerosol optical depth, and WRF-Chem simulation, an aerosol air pollution episode affected by binary typhoons were analyzed over different regions in inland China. Before the typhoons made landfall, the weak surface winds and downdrafts were the crucial factors triggering the severe aerosol air pollution in east and central China. After landing, in the main impact area, aerosols were effectively removed due to precipitation scavenging and strong winds. However, beyond that area, the impact of the typhoons on pollution weakened with the increasing distance. Wuhan was at the edge of the typhoon impact zone, the changes of pollutant concentrations were similar to the main impact area, but the pollutants dispersed only due to the gales. Weinan site was farthest away from the typhoons, typhoons hardly affected the air quality. The results provide a scientific basis for understanding the mechanism between binary typhoons and aerosol air pollution and enable more accurate pollution alerts to be made during typhoons.

The utmost important task for air pollution prevention and control is to identify the source of pollution such that targeted management and governance can be greatly enhanced. In this paper, we have develoepd an air quality forecasting system called “the national air quality high-resolution forecast and pollution control decision support system (NARS)”, which integrates atmospheric environment monitoring and analysis, meteorological numerical forecasting, emission source inversion, air quality forecasting, meteorological and atmospheric chemical data assimilation, emission sources tracing, profit and loss assessment together with dynamic optimal control. The system could be applied to perform the closed-loop prevention and control for atmospheric pollution by monitoring, forecasting, assimilation, traceability, emission source inversion and optimal control, and the system stands a great promise of providing a solution for current air pollution prevention and control strategy. In the NARS, a CAMx based adjoint model was developed, and was further demonstrated to perform dynamic inversion and grid-based quantitative emission source tracing. Our results show that the system can trace quickly and quantitatively both spatial and temporal distributions of emission sources and their contribution rates resulting from severe air pollution for certain target area for the coming 7 days. As an application of the NARS, the emission inversion, meteorological field simulation, air quality forecasting and grid traceability were studied for the time period from September 2016 to March 2017 in Beijing. Compared with the observation of national control station in Beijing-Tianjin-Hebei region (BTH), the results showed that the forecast accuracies of the pollution processes, the pollution level and the pollutant concentration are close to 100%, 88.8% and 84.7%, respectively, and the correlation coefficient between the modeling and observation is 0.81. The results of grid traceability showed that the emissions of PM2.5 pollution in the main urban area of Beijing are mainly from the air pollutant transmission channel in the southwest of. The emission contributions of BTH plus the surrounding areas are respectively 66%, 29% and 5%. The 19% PM2.5 emissions of BTH have resulted in 80% Beijing PM2.5 concentration in heavily polluted and severely polluted days. Among them, 9% Beijing local emissions account for 63% PM2.5, and 10% Hebei emissions accounted for 17%. The 26% BTH emissions have resulted in 80% PM2.5 in Beijing’s main city for slightly or heavily polluted days. Furthermore, Beijing emissions accounting for 9% of BTH emissions have contributed 61%; meanwhile, Hebei emissions accounting for 15% of BTH emissions have contributed the 18% of the pollution; finally, Tianjin 2% accouts for the leaving 1%. The emissions leading to the PM2.5 pollution in Beijing main city mainly distribute in the city zone and the sourthern of Beijing, some districts or counties of Baoding and Shijiazhuang. The top six districts or counties accounting for 48% pollutants are located in Beijing, while the top 20 districts or counties contribute 73%. Here, using the the adjoint model developed, we are able to analyze synchronously the emisison apportionment of the modeling results through combining the dynamic inversion and the monitoring emission inventories. Using both profit-loss assessment and natural cybernetics, the NARS is able to locate the emisison sources for optimal emisison control during a heavy air pollution episode.

A severe, prolonged and harmful regional heavy air pollution episode occurred in eastern China from December 2016 to January 2017. In this paper, the pollutant characteristics and the meteorological formation mechanism of this pollution event, including climate anomalies, surface weather conditions, planetary boundary layer structure and large-scale circulation features, were analysed based on observational pollution data, surface meteorological data, sounding data and ERA-Interim reanalysis data. The results are as follows. (1) Five pollution stages were identified in eastern China. The two most severe episodes occurred from December 27, 2016 to January 4, 2017 and from January 8 to 12 2017. During these two pollution episodes, fine mode particles were major contributors, and hourly PM2.5 concentrations often exceeded 150 μg/m3, reaching a maximum of 333 μg/m3 at Fuyang station. Gaseous pollutants were transformed into secondary aerosols through heterogeneous reactions on the surface of PM2.5. (2) Compared with the same period over the years 2000–2016, 2017 presented meteorological field climate anomalies in conjunction with unfavourable surface conditions (weak winds, high relative humidity, fewer hours of sunshine, high cloud cover) and adverse atmospheric circulation (weak East Asian winter monsoon and an abnormal geopotential height of 500 hPa), which caused poorer visibility in 2017 than in the other analysed years. (3) During the development of heavy pollution event, unfavourable surface weather conditions, including poorer visibility, weaker pressure, higher relative humidity, lower wind speed with unfavourable wind direction and less precipitation suppressed the horizontal diffusion ability of air pollutants. Furthermore, the unfavourable structure of the atmospheric boundary layer was the key cause of the rapid PM2.5 increase. The deep, strong temperature inversion layer and weak vertical wind velocity could have suppressed vertical motion and enhanced the stability of the near-surface atmosphere, causing the air pollutants to accumulate at low levels and exacerbating the air pollution problem. Finally, a persistent stagnant weather system with a weak geopotential height field of 1000 hPa and warm air advection at 850 hPa was the main feature of atmospheric circulation associated with the heavy pollution.

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.

To investigate the impact of the Western Pacific subtropical high (WPSH) on the air pollution episode of Xiamen, a coastal city in Southeastern China, this study focused on formation processes and influencing mechanisms of an air pollution episode from 17th to 23rd September 2017. The results showed that the WPSH fluctuated in this period and intensified this air pollution with local emissions. The episode was divided into four stages according to WPSH center locations to diagnose the air pollution. Visibility declined below 10 km twice while fine particulate matte (PM2.5) concentration was up to 89.05 μg/m3 during this episode. As a consequence of high temperature (28.33 ± 1.25 °C) resulted from WPSH, atmospheric oxidation at high level (140.81 ± 56.49 μg/m3) was the driving force of secondary aerosols generations. Oxidation determined photo-chemical reactions with the pathways of gas-phase and heterogeneous formation. Sulfate was formed from gas-phase oxidation by SO2 in daytime while heterogeneous reaction occurred at night. Nitrate generation was dominated by not only excess ammonium but also intense oxidation. Reconstruction light extinction results coupling with trajectories revealed that (NH4)2SO4, NH4NO3 and OM were the priority factors to the reduction of atmospheric visibility. These findings provided new insights of air pollution episode diagnosis and indicative function of WPSH impacts on local air quality in Southeast China.

Egypt is suffering from acute air pollution episodes as a result of Egyptian farmers’ continuous burning of rice straw after harvest. The Egyptian government issued strict legislations and took measurements to prevent the burning processes and counter its pollution. Still the problem persists constituting a major public health issue. The paper introduces a proposed Internet of Things “IOT-Based conceptual Framework for the prevention of acute air pollution episodes caused by rice straw burning which negatively impacts the environment and public health. The proposed IOT-Based conceptual framework considers environmental and related healthcare dimensions and parameters. It argues that IOT technologies can efficiently solve this problem by preventing and controlling the fire counts and monitoring the black cloud movement to react or pro-act in dealing with health consequences. The paper starts explaining IOT definition, architecture, benefits and challenges. Then explains in details the acute air pollution episode and the black cloud, its reasons and consequences. It presents a proposed IOT-Based solution scenario and its corresponding phases. Finally, it contributes with a proposed general IOT-Based conceptual Framework to prevent and control the acute air pollution episode and limit its health-related problems in Egypt, concentrating on the proposed IOT layers and components used.

Urbanization significantly influences meteorological conditions and air quality. Statistically, air pollution in the megacity of Shanghai usually occurs with cold weather fronts. An air pollution episode during a cold front was simulated using weather research and forecasting and the Community Multi-scale Air Quality model system. In this study, we used two urban schemes, a simple bulk scheme (denoted BULK) and the single-layer urban canopy model (SLUCM), to check the effects of urban parameterization. Our results showed that SLUCM better predicted the arrival time and cooling process of the cold front and more realistically simulated the moving process of the cold front. The improvement in the temperature and relative humidity simulation achieved using SLUCM was more effective under higher urbanization levels, whereas the wind speed simulation was better in rural areas. The simulated concentrations at sites with high urbanization were obviously improved by urban parameterization. The barrier role of the urban canopy during a cold front was better represented and was shown to cause a wider polluted area and higher pollutant concentration using SLUCM than with BULK. Overall, accurate meteorological simulations in the atmospheric boundary layer using SLUCM are expected to provide good prediction of urban air quality.

Air quality in China is tending to improve, especially in urban areas. Nevertheless, rural areas and underdeveloped cities in northern China are still suffering from severe air pollution in winter due to large usage of coal and unfavorable meteorological conditions. In this study, size-segregated aerosol samples were collected from a typical coal-combustion rural site in Linfen, China during an extreme air pollution episode in winter 2017. The polycyclic aromatic hydrocarbons (PAHs), n-alkanes, hopanes and steranes were identified to better understand the emission sources of the organic compounds and the health effects of the PAHs in the ambient air here. The PAHs showed a bimodal mode with the major peak in the Aitken mode (

Conventional air pollutants (PM10, CO, NOx) gradually increased from fall to winter during 2015 in Istanbul. Several air pollution episodes were observed during this period. This study was made in order to determine polycyclic aromatic hydrocarbon (PAH) levels, identify the sources of air pollution, and make toxicity assessment based on Benzo(a)pyrene equivalent concentrations. The sampling took 14 sequential days during winter. High-pressure weather conditions prevailed at the start of the sampling. The conditions were then changed to low-pressure condition towards the end of the sampling. Strong inversion was effective on the onset of the sampling. Strong inversion was effective at the onset of the sampling. A high-volume sampler was used to collect gas and particle phase samples. Total suspended particle concentrations were between 27 and 252 μg m−3. Sixteen PAH species were investigated. Total (gas + particle) PAH concentrations were between 76.4 and 1280.3 ng m−3, with an average of 301.4 ng m−3. Individual PAH concentrations were between not detected (n.d.) and 99.2 ng m−3 in the gaseous phase, and between n.d. and 11.5 ng m−3 in the particle phase. Phenanthrene had the highest share among 16 PAH compounds. Benzo(a)pyrene was not detected in 8 days. On the remaining days, its concentration ranged between 5.5 and 14.8 ng m−3 with an average of 3.7 ng m−3. Low-molecular-weight PAHs dominated gaseous phase; inversely, high-molecular-weight PAHs dominated particle phase. Possible sources were identified by diagnostic ratios. These ratios suggested that coal combustion and diesel vehicle exhaust emissions had a substantial impact on ambient air quality. Benzo(a)pyrene equivalencies were calculated for each PAH compound in order to make toxicity assessment. Total benzo(a)pyrene equivalencies ranged between 0.4 and 30.0 ng m−3 with an average of 7.2 ng m−3.

A Single Particle Aerosol Mass Spectrometer (SPAMS), a Single Particle Soot Photometer (SP2) and various meteorological instruments were employed to investigate the chemical and physical properties of black carbon (BC) aerosols during a regional air pollution episode in urban Shanghai over a five-day period in December 2013. The average PM2.5 and BC mass concentrations were 221 and 3.2 μg m−3, respectively, with the PM2.5 peak value of 636 μg m−3 at noon of 6 December and the BC peak value of 12.1 μg m−3 at 04:26 LT on 7 December. The number size of BC cores was distributed over ~ 60–400 nm, with a peak around ~ 60 nm. The BC core mass size distribution was within ~ 70–500 nm, with a peak around ~ 200 nm. The number concentration of BC-containing particles captured by SPAMS in the size range 200–1200 nm agreed very well with that detected by SP2 (R2 = 0.87). A cluster analysis of the single particle mass spectra allowed for the separation of BC-containing particles into seven classes. Pure BC accounted for 0.53 % of BC-containing particles; BC attributed to biomass burning (BBBC) accounted for 22.60 %; K-rich BC-containing (KBC), NaK-rich BC-containing (NaKBC), BC internally-mixed with OC and ammonium sulfate (BCOC-SOx), BC internally-mixed with OC and ammonium nitrate (BCOC-NOx) were all attributed to traffic emissions and accounted for 73.24 %; unidentified particles accounted for 3.63 %. The size distribution of internally-mixed BC particles was bimodal. Detected by SP2, the condensation mode peaked around ~ 230 nm and droplet mode peaked around ~ 380 nm, with a clear valley in the size distribution around ~ 320 nm. The condensation mode mainly consisted of traffic emissions, with particles featuring a small BC core (~ 60–80 nm) and a relatively thin absolute coating thickness (ACT, ~ 50–130 nm). The droplet mode included highly aged traffic emission particles and biomass burning particles. The highly aged traffic emissions had a small core (~ 60–80 nm) and a very thick ACT (~ 130–300 nm), which is larger than reported in any previous literature. The biomass burning particles had a larger BC core (~ 80–130 nm) and a thick ACT (~ 110–300 nm). High concentration gaseous pollutants like NO2 were found to accelerate the aging process and resulted in a continuous size growth of BC-containing particles from traffic emission. The condensation of gaseous pollutants made a significant contribution to the extremely high particulate matter during heavy pollution episode in the urban area.

The aim of this paper is to study the wintertime physical properties of atmospheric aerosol particles on the basis of data observed at the K-puszta regional background station in Hungary. In Hungary wintertime smog episodes are linked to strong stable air (high pressure blocking events) with thermal inversion. These atmospheric conditions are frequently formed during winter months (November–February) due to the special geographical location of the country. The formation of smog events is highly probable in cases of thermal inversion periods sustaining for at least 4 days. We discuss in the paper the role of high-pressure blocking events in aerosol properties in terms of PM10 concentrations, aerosol size distributions, new particle formation and optical properties. We found that high-pressure blocking events have significant impacts on the size distribution and particle formation processes. At K-puszta the aerosol is in highly aged state with size distribution dominated by the accumulation mode. This is further supported by the optical properties, e.g., by high scattering Angstrom exponent and by relatively weak absorption. The most significant effect of extreme episodes is manifested in the changes in PM10 concentrations and, consequently, in aerosol optical properties. The PM10 concentrations, scattering coefficients and absorption coefficients considerably increase to extreme values that are characteristic of a heavily polluted atmosphere rather than rural air. Our results indicate that in winter, the air quality at Kpuszta is often influenced by regional air pollution as shown by spatial distribution of PM10 concentration. It is found that PM10 had almost the same concentration in regional background air and in different types of urban environments. The special meteorological conditions and the role of regional-scale transport can explain why local abatements in cities cannot lead to significant improvement of the air quality during smog events.

The paper focus is on the air pollution episode generated by a closed mining tailings dump located on Danube banks in historical Banat region, between Romania and Serbia. In this paper a new generation Gaussian plume air dispersion model was used, based on the hypothesis that the atmospheric boundary layer properties are characterized by the boundary layer depth and the Monin-Obukhov length rather than in terms of the single parameter Pasquill-Gifford class. The case-study focuses on a sensible case of Romania-Serbia cross-border case generated by the lack of maintenance of a closed mining tailings dump and the evaluation of an area type pollution source on the surrounding environment.

The Twain-Hu basin (THB), covering the lower plain of Hubei and Hunan provinces in Central China, has experienced severe air pollution in recent years. However, the terrain effects of such sub-basin on air quality over the THB have been incomprehensibly understood. A heavy PM2.5 pollution event occurred over the THB during 4&ndash, 10 January 2019. By using the observations and WRF-Chem simulations, we investigated the underlying mechanisms of sub-basin effects on the air pollution with several sensitivity experiments. Observationally, air pollution in the western THB urban area with an average PM2.5 concentration of 189.8 &mu, g m&minus, 3, which was more serious than the eastern urban area with the average PM2.5 concentration of 106.3 &mu, 3, reflecting a different influence of topography on air pollution over the THB. Simulation results revealed that the terrain effect can contribute 12.0 % to increasing the PM2.5 concentrations in the western THB, but slightly mitigate the pollution extent in the eastern THB with the contribution of &minus, 4.6 % to PM2.5 during the heavy pollution episode. In particular, the sub-basin terrain was conducive to the accumulation of PM2.5 by regional transport with the contribution of 39.1 %, and contrarily lowered its local pollution by &minus, 57.0 % via the enhanced atmospheric boundary layer height and ventilation coefficients. Given a heavy air pollution episode occurring over the THB, such inverse contribution of terrain effects reflected a unique importance of sub-basin topography in regional transport of air pollutants for air pollution in central China.

Coupled weather forecasting and chemical transport models are useful tools to evaluate air pollution episodes in big cities for the purpose of forecasting and air pollution abatement measures' evaluation. However, large set of accurate data of various sources and modeling calibrations are needed for such complex modeling system to be reliable. The problem becomes more obvious when the model is operated over a domain in which there is a general lack of accurate input data such as emission inventory data. The current study investigates the possibility of model tuning for more accurate prediction of air pollutant concentrations in the city of Tehran in an air pollution episode as a case study. In the last several years, Tehran has frequently experienced long episodes of air pollution, often resulted in forced holidays in the city. WRF/CAMx modeling system were used to simulate the spatial distribution of pollutants concentrations over the city of Tehran in a highly polluted episode during December 2017. In order to improve model performance, a methodology was developed and used to adjust the emission inventory of the system. Due to lack of national emission inventory and background data, effects of introducing a top-down national emission inventory to the modeling system was investigated. This emission inventory can also be used to prepare more accurate boundary concentrations for countries located near Iran. In addition, emission rates of the most dominant emission sources of the city of Tehran – mobile sources – were adjusted using the results from chassis dynamometer tests. Also, the hourly variations of emission were improved using measured ambient NO2 concentrations. Comparison of modeled and measured concentrations at air quality monitoring stations for various pollutant showed that emission adjustment was the most effective method which resulted in considerable model performance improvement over Tehran. Results showed that due to better and more realistic emission factors used in the model, bias error for CO, NO2, O3 and PM2.5 reduced by 0.36 ppm, 3.4 ppb, 0.19 ppb and 2.14 μg/m3, respectively and correlation coefficient for CO, O3 and PM2.5 increased by 0.13, 0.02 and 0.6. This proves the possibility of using such method to improve model performance when there is a general lack of accurate input data.

Unmanned aerial vehicle (UAV) experiments, multiple datasets from ground-based stations and satellite remote sensing platforms, and backward trajectory models were combined to investigate the characteristics and influential mechanisms of the air pollution episode that occurred in Nanjing during 3&ndash, 4 December 2017. Before the experiments, the position of the detector mounted on a UAV that was minimally disturbed by the rotation of the rotors was analyzed based on computational fluid dynamics (CFD) simulations. The combined analysis indicated that the surface meteorological conditions&mdash, high relative humidity, low wind speed, and low temperature&mdash, were conducive to the accumulation of PM2.5. Strongly intense temperature inversion layers and the low thickness of the atmospheric mixed layer could have resulted in elevated PM2.5 mass concentrations. In the early stage, air pollution was affected by the synoptic circulation of the homogenous pressure field and low wind speeds, and the pollutants mainly originated from emissions from surrounding areas. The aggravated pollution was mainly attributed to the cold front and strong northwesterly winds above 850 hPa, and the pollutants mostly originated from the long-distance transport of emissions with northwesterly winds, mainly from the Beijing‒Tianjin‒Hebei (BTH) region and its surrounding areas. This long-distance transport predominated during this event. The air pollution level and aerosol optical depth (AOD) were positively correlated with respect to their spatial distributions, they could reflect shifts in areas of serious pollution. Pollution was concentrated in Anhui Province when it was alleviated in Nanjing. Polluted dust, polluted continental and smoke aerosols were primarily observed during this process. In particular, polluted dust aerosols accounted for a major part of the transport stage, and existed between the surface and 4 km. Moreover, the average extinction coefficient at lower altitudes (&lt, 1 km) was higher for aerosol deposition.

An extremely high PM 2.5 pollution episode occurred over the eastern China in January 2013. In this paper, the particulate matter source apportionment technology (PSAT) method coupled within the Comprehensive air quality model with extensions (CAMx) is applied to study the source contributions to PM 2.5 and its major components at six receptors (Urban Shanghai, Chongming, Dianshan Lake, Urban Suzhou, Hangzhou and Zhoushan) in the Yangtze River Delta (YRD) region. Contributions from 4 source areas (including Shanghai, South Jiangsu, North Zhejiang and Super-region) and 9 emission sectors (including power plants, industrial boilers and kilns, industrial processing, mobile source, residential, volatile emissions, dust, agriculture and biogenic emissions) to PM 2.5 and its major components (sulfate, nitrate, ammonia, organic carbon and elemental carbon) at the six receptors in the YRD region are quantified. Results show that accumulation of local pollution was the largest contributor during this air pollution episode in urban Shanghai (55%) and Suzhou (46%), followed by long-range transport (37% contribution to Shanghai and 44% to Suzhou). Super-regional emissions play an important role in PM 2.5 formation at Hangzhou (48%) and Zhoushan site (68%). Among the emission sectors contributing to the high pollution episode, the major source categories include industrial processing (with contributions ranging between 12.7 and 38.7% at different receptors), combustion source (21.7–37.3%), mobile source (7.5–17.7%) and fugitive dust (8.4–27.3%). Agricultural contribution is also very significant at Zhoushan site (24.5%). In terms of the PM 2.5 major components, it is found that industrial boilers and kilns are the major source contributor to sulfate and nitrate. Volatile emission source and agriculture are the major contributors to ammonia; transport is the largest contributor to elemental carbon. Industrial processing, volatile emissions and mobile source are the most significant contributors to organic carbon. Results show that the Yangtze River Delta region should focus on the joint pollution control of industrial processing, combustion emissions, mobile source emissions, and fugitive dust. Regional transport of air pollution among the cities are prominent, and the implementation of regional joint prevention and control of air pollution will help to alleviate fine particulate matter concentrations under heavy pollution case significantly.

Air pollutant emissions from agricultural burning are observed every year after harvest in China. While agriculture is not the main contributor to air pollution in China, agricultural activities can cause severe pollution events. Recognizing the key mechanisms involved in this process offers an opportunity to minimize pollution events caused by agricultural burning. In this paper, we review the meteorological conditions present during a selected air pollution episode and discuss those conditions using standard meteorological observations. The spatio-temporal variations of PM2.5 concentrations following agricultural burning in Beijing were measured from October 4 to October 7, 2013. This time period coincides with a Chinese public holiday and was selected because the influence of other anthropogenic emissions on air quality was strongly reduced during those days. As a result, we were able to identify the key sources and progress of a severe air pollution event. On October 4, average PM_(2.5) concentration in Beijing continuously increased from 49.7 μg m^(-3) at 1:00 to 302.5 μg m^(-3) at 23:00. Heavily polluted air (＞ 300 μg m^(-3)) initially appeared in southeastern Beijing on the afternoon of October 4. On October 5 and in the early morning of October 6, heavily polluted air masses moved into central Beijing, the inner suburbs, and the suburbs. From 0:00 on October 6 to 15:00 on October 7, the average PM_(2.5) concentration in Beijing decreased from 291.6 μg m^(-3) to 19.2 μg m^(-3). Active fire information derived from the MODIS sensors and back trajectory analysis show that field burning of agricultural residues after a harvest triggered and massively contributed to this severe air pollution event. The results improve our understanding of PM_(2.5) air pollution development processes, and they provide scientific support for the Chinese government to accelerate emission reductions from the field burning of agricultural residues.

A winter air pollution episode was observed in Hangzhou, South China, during the Second World Internet Conference, 2015. To study the pollution characteristics and underlying causes, the Weather Research and Forecasting with Chemistry model was used to simulate the spatial and temporal evolution of the pollution episode from December 8 to 19, 2015. In addition to scenario simulations, analysis of the atmospheric trajectory and synoptic weather conditions were also performed. The results demonstrated that control measures implemented during the week preceding the conference reduced the fine particulate matter (PM2.5) pollution level to some extent, with a decline in the total PM2.5 concentration in Hangzhou of 15% (7%–25% daily). Pollutant long-range transport, which occurred due to a southward intrusion of strong cold air driven by the Siberia High, led to severe pollution in Hangzhou on December 15, 2015, accounting for 85% of the PM2.5 concentration. This study provides new insights into the challenge of winter pollution prevention in Hangzhou. For adequate pollution prevention, more regional collaborations should be fostered when creating policies for northern China.

The MM5-SMOKE-CMAQ model system, which was developed by the United States Environmental Protection Agency (US EPA) as the MODELS-3 system, has been used for daily air quality forecasts in the Beijing Municipal Environmental Monitoring Center (Beijing MEMC), as a part of the Ensemble air quality Modeling forecast System for Beijing (EMS-Beijing) since the 2008 Olympic Games. According to the daily forecast results for the entire duration of 2010, the model shows good performance in the PM10 forecast on most days but clearly underestimates PM10 concentration during some air pollution episodes. A typical air pollution episode from 11–20 January 2010 was chosen, in which the observed air pollution index of particulate matter (PM10-API) reached 180 while the forecast PM10-API was about 100. In this study, three numerical methods are used for model improvement: first, by enhancing the inner domain with 3 km resolution grids, and expanding the coverage from only Beijing to an area including Beijing and its surrounding cities; second, by adding more regional point source emissions located at Baoding, Landfang and Tangshan, to the south and east of Beijing; third, by updating the area source emissions, including the regional area source emissions in Baoding and Tangshan and the local village/town-level area source emissions in Beijing. The last two methods are combined as the updated emissions method. According to the model sensitivity testing results by the CMAQ model, the updated emissions method and expanded model domain method can both improve the model performance separately. But the expanded model domain method has better ability to capture the peak values of PM10 than the updated emissions method due to better reproduction of the pollution transport process in this episode. As a result, the hindcast results ("New(CMAQ)"), which are driven by the updated emissions in the expanded model domain, show a much better model performance in the national standard station-averaged PM10-API. The daily hindcast PM10-API reaches 180 and is much closer to the observed value, and has a high correlation coefficient of 0.93. The correlation coefficient of the PM10-API in all Beijing MEMC stations between the hindcast and observation is 0.82, clearly higher than the forecast 0.54. The FAC2 increases from 56% in the forecast to 84% in the hindcast, and the NMSE decreases from 0.886 to 0.196. The hindcast also has better model performance in PM10 hourly concentrations during the typical air pollution episode. The updated emissions method accompanied by a suitable domain in this study improved the model performance for the Beijing area significantly.

The first pan-European kilometre-scale atmospheric chemistry simulation is introduced. The continental-scale air pollution episode of January 2009 is modelled with the CHIMERE offline chemistry transport model with a massive grid of 2 million horizontal points, performed on 2000 CPU of a high-performance computing system hosted by the Research and Technology Computing Center at the French Alternative Energies and Atomic Energy Commission (CCRT/CEA). Besides the technical challenge, we find that model biases are significantly reduced, especially over urban areas. The high-resolution grid also allows revisiting of the contribution of individual city plumes to the European burden of pollution, providing new insights to target the appropriate geographical level of action when designing air pollution mitigation strategies.

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.

In January 2013, extremely high concentrations of fine particles (PM2.5) were observed around Beijing, China. In Japan, the health effects of transboundary air pollution have been a matter of concern. We examined the association between the levels of outdoor PM2.5 and other air pollutants with primary care visits (PCVs) at night due to asthma attack in Himeji City, western Japan. A case–crossover study was conducted in a primary care clinic in Himeji City, Japan, involving 112 subjects aged 0–80 years who visited the clinic due to an asthma attack between 9 p.m. and 6 a.m. during the period January–March, 2013. Daily concentrations of particulate matter, ozone, nitrogen dioxide, and some meteorological elements were measured, and a conditional logistic regression model was used to estimate the odds ratios (OR) of PCVs per unit increment in air pollutants or meteorological elements. Of the 112 subjects, 76 (68 %) were aged

We have evaluated the performance of operational versions of the numerical weather prediction (NWP) model HIRLAM and HARMONIE in severe air pollution atmospheric conditions in Istanbul in November 18–20 of 2009. During the episode, a high pressure system over northwest Turkey, including Istanbul, lead to the formation of an exceptional ground-based temperature inversion. The forecasts generated by HIRLAM and HARMONIE models were compared to observations at meteorological stations in the area. Both HIRLAM and HARMONIE 24 h's forecasts are successful to predict possible episode conditions due to meteorological circumstances, and thus both models provide reliable weather input to an air pollution warning system. Results of this study are important especially for those involved in NWP, in air pollution modeling and decision-making where high resolution NWP model outputs are becoming a valuable product.

Air pollutant emission factors produced by open burning of rice straw were estimated using the residual mass method which incorporated ambient air-quality and meteorological data of measured stations. The residual mass method regarded the residual mass of air pollutants as emissions caused by the open burning of rice straw. Lasting from November 27–28, 2002, the selected episode resulted in the most serious air pollution in the recent decade in terms of open burning of rice straw, significantly degrading air quality in central-south Taiwan. Emission factors from open burning of rice straw, as modeled by the residual mass method, were 30.3 ± 1.45, 5.14 ± 0.13, 3.44 ± 0.09, 6.28 ± 0.34, and 0.058 ± 0.003 g kg−1 for CO, NMHCs, NOx, PM10 and SO2, respectively. The maximum daily emissions of CO and PM10 were 1000 kg km−2 and located at central-south Taiwan. Additionally, emissions of CO and PM10 in EPS were 7.67 and 9.33 times higher than MON during the rice straw burning episode. The spatial emission of EPS and MON were also presented with the residual mass method. Comparing our results with those of other studies revealed that calculated emission factors in this study were in an acceptable range.

In this work we investigated an air pollution episode during the landfall process of a tropical cyclone (TC) in Hong Kong. TCs affect air condition and account for most air pollution episodes in summer of this region. In August 2008, TC Nuri made direct landfall in Hong Kong. Before its landfall, an air pollution episode occurred, where major pollutants like SO2 and PM10 increased eight and six times higher respectively. Rather than using single measurement method, we combined ground air sampling, lidar, sunphotometer and satellite lidar CALIPSO with focus on aerosol to study the episode mechanism, and some new phenomena were found. During the episode, it was found that heavy inland aerosol plumes existed in areas larger than urbanized regions and were elevated vertically and transported southward. During episode, planetary boundary layer (PBL) expansion and height increase were observed, which is different from previous reported PBL compression and height decrease. While vertical subsidence and horizontal stagnation and consequently local aerosol accumulation were attributed as the main episode cause in previous cases, our observation showed that transported aerosols dominated in this TC landfall event. This can be further confirmed by examining aerosol chemical composition, size distribution and single scattering albedo, where transported related species showed significantly change and local indicators remained relatively stable. Invigorated cloud droplets were found on the boundary layer top upon aerosol elevation. The results indicate that site difference and TC tracks should be considered for analyzing episode formation mechanism. They can cause difference in the strength of vertical subsidence and horizontal advection and affect pollution flow direction, which subsequently results in different pollution formation processes.

Numerous wildfires provoked by an unprecedented intensive heat wave caused continuous episodes of extreme air pollution in several Russian cities and densely populated regions, including the Moscow region. This paper analyzes the evolution of the surface concentrations of CO, PM10 and ozone over the Moscow region during the 2010 heat wave by integrating available ground based and satellite measurements with results of a mesoscale model. The CHIMERE chemistry transport model is used and modified to include the wildfire emissions of primary pollutants and the shielding effect of smoke aerosols on photolysis. The wildfire emissions are derived from satellite measurements of the fire radiative power and are optimized by assimilating data of ground measurements of carbon monoxide (CO) and particulate matter (PM10) into the model. It is demonstrated that the optimized simulations reproduce independent observations, which were withheld during the optimisation procedure, quite adequately (specifically, the correlation coefficient of daily time series of CO and PM10 exceeds 0.8) and that inclusion of the fire emissions into the model significantly improves its performance. The model results show that wildfires are the principal factor causing the observed air pollution episode associated with the extremely high levels of daily mean CO and PM10 concentrations (up to 10 mg m−3 and 700 μg m−3 in the averages over available monitoring sites, respectively), although accumulation of anthropogenic pollution was also favoured by a stagnant meteorological situation. Indeed, ozone concentrations were simulated to be episodically very large (>400 μg m−3) even when fire emissions were omitted in the model. It was found that fire emissions increased ozone production by providing precursors for ozone formation (mainly VOC), but also inhibited the photochemistry by absorbing and scattering solar radiation. In contrast, diagnostic model runs indicate that ozone concentrations could reach very high values even without fire emissions which provide "fuel" for ozone formation, but, at the same time, inhibit it as a result of absorption and scattering of solar radiation by smoke aerosols. A comparison of MOPITT CO measurements and corresponding simulations indicates that the observed episodes of extreme air pollution in Moscow were only a part of a very strong perturbation of the atmospheric composition, caused by wildfires, over European Russia. It is estimated that 2010 fires in this region emitted ~10 Tg CO, thus more than 85% of the total annual anthropogenic CO emissions. About 30% of total CO fire emissions in European Russia are identified as emissions from peat fires.

This study investigated the main causes of haze episodes in the northwestern Thailand to provide early warning and prediction. In an absence of emission input data required for chemical transport modeling to predict the haze, the climatological approach in combination with statistical analysis was used. An automatic meteorological classification scheme was developed using regional meteorological station data of 8years (2001-2008) which classified the prevailing synoptic patterns over Northern Thailand into 4 patterns. Pattern 2, occurring with high frequency in March, was found to associate with the highest levels of 24h PM(10) in Chiangmai, the largest city in Northern Thailand. Typical features of this pattern were the dominance of thermal lows over India, Western China and Northern Thailand with hot, dry and stagnant air in Northern Thailand. March 2007, the month with the most severe haze episode in Chiangmai, was found to have a high frequency of occurrence of pattern 2 coupled with the highest emission intensities from biomass open burning. Backward trajectories showed that, on haze episode days, air masses passed over the region of dense biomass fire hotspots before arriving at Chiangmai. A stepwise regression model was developed to predict 24h PM(10) for days of meteorology pattern 2 using February-April data of 2007-2009 and tested with 2004-2010 data. The model performed satisfactorily for the model development dataset (R(2)=87%) and test dataset (R(2)=81%), which appeared to be superior over a simple persistence regression of 24h PM(10) (R(2)=76%). Our developed model had an accuracy over 90% for the categorical forecast of PM(10)>120μg/m(3). The episode warning procedure would identify synoptic pattern 2 and predict 24h PM(10) in Chiangmai 24h in advance. This approach would be applicable for air pollution episode management in other areas with complex terrain where similar conditions exist.

Gaseous pollutants and PM 2.5 aerosol particles were investigated during a tropical storm and an air pollution episode in southern Taiwan. Field sampling and chemical analysis of particulate matter and gaseous pollutants were conducted in Daliao and Tzouying in the Kaohsiung area, using a denuder-filter pack system during the period of 22 October to 3 November 2004. Sulfate, nitrate and ammonium were the major ionic species in the PM 2.5 , accounting for 46 and 39% of the PM 2.5 for Daliao and Tzouying, respectively. Higher PM 2.5 , Cl − , NO 3 − and NH 4 + , HNO 2 and NH 3 concentrations were found at night in both stations, whereas higher HNO 3 was found during the day. In general, higher PM 2.5 , HCl, NH 3 , SO 2 , Cl − , NO 3 − , SO 4 2− and NH 4 + concentrations were found in Daliao. The synoptic weather during the experiment was first influenced by Typhoon NOCK-TEN, which resulted in the pollutant concentrations decreasing by about two-thirds. After the tropical thunderstorm system passed, the ambient air quality returned to the previous condition in 12 to 24 h. When there was a strong subsidence accompanied by a high-pressure system, a more stable environment with lower wind speed and mixing height resulted in higher PM 2.5 , as well as HNO 2 , NH 3 , SO 4 2− , Cl − , NO 3 − , NH 4 + and K + concentrations during the episode days. The rainfall is mainly a scavenger of air pollutants in this study, and the stable atmospheric system and the high emission loading are the major reasons for high air pollutant concentrations.

This study analyzed the air pollution episode which affected Taiwan on March 19 and 20, 2006, an event confirmed to have been caused by Asian dust (AD). During this AD event, the maximum hourly values of PM 2.5 and PM 2.5–10 particles at 136 and 218 µg m − 3 , respectively, were recorded at the Taipei aerosol supersite (TAS) located in northern Taiwan. Moreover, of Taiwan's 74 air quality monitoring stations, 65 (on March 19) and 29 stations (March 20) recorded daily average concentrations of PM 10 which exceeded Taiwan's air quality standard of 125 µg m − 3 . This AD event not only greatly increased the PM 2.5 and PM 2.5–10 concentrations, but the gaseous pollutants transported by the northeast monsoon were predicted to adversely affect Taiwan as well. In addition to ground measurements, an aerosol layer was detected in Taipei, the thickness of which was verified to be about 800 m through the light detection and ranging (LIDAR) method. During the AD-affected period (defined as the situation where the concentration of PM 2.5–10 maintains a high value), the black carbon (BC) fraction of PM 2.5 was reduced from 15.7 to 5.6%; sulfate fraction of PM 2.5 increased from 7.1 to 19.8%; and the nitrate fraction of PM 2.5 was reduced slightly from 10.3 to 8.1% at the TAS site. Moreover, the particles' number size spectra showed a decrease in the amount of particles with a diameter of less than 200 nm, indicating that the rise of the concentration of PM 2.5 increased along with the increase of PM 2.5 particles with diameters larger than 200 nm. This study demonstrates that anthropogenic pollutants from the Asian mainland including nitrates, sulfates, BC, gaseous pollutants (CO, SO 2 , and O 3 ), and other fractions of fine particles, would influence the downwind regions as the AD is transported.

Atmospheric particulate matter (PM1) was collected at an urban and a rural site in Switzerland during a hibernal high air pollution episode and was investigated for estrogenicity using an estrogen-sensitive reporter gene assay (ER-CALUX). All samples that were tested induced estrogen receptor-mediated gene expression in T47D human breast adenocarcinoma cells. Observed estrogenic activities corresponded to 17beta-estradiol (E2) CALUX equivalent concentrations ranging from 2 to 23 ng E2-CEQ per gram of PM1 (particulate matter ofor = 1 microm aerodynamic diameter) and from 0.07 to 1.25 pg E2-CEQ per m(3) of sampled air. There was a strong correlation between the PM1 estrogenicity of the urban and rural sites (r = 0.92). Five hydroxylated polycyclic aromatic hydrocarbons (hydroxy-PAHs), which show structural similarities to E2, were assessed for their estrogenic activity. The following order of estrogenic potency was found: 2-hydroxychrysene2-hydroxyphenanthrene1-hydroxypyrene2-hydroxynaphthalene1-hydroxynaphthalene. Three of these hydroxy-PAHs, namely 2-hydroxyphenanthrene, 2-hydroxynaphthalene and 1-hydroxynaphthalene, were detected in all PM1 extracts. However, they contributed only 0.01-0.2% to the overall estrogenic activity. Hence, mainly other estrogenic compounds not yet identified by chemical analysis must be responsible for the observed activity. The temporal trend of PM1 estrogenicity at the urban and rural site, respectively, was compared with the time course of several air pollutants (NO2, NO, SO2, O3, CO) and meteorological parameters (temperature, humidity, air pressure, solar irradiation, wind velocity). However, specific emission sources and formation processes of atmospheric xenoestrogens could not be elucidated. This study showed that ambient particulate matter contains compounds that are able to interact with estrogen receptors in vitro and potentially also interfere with estrogen-regulated pathways in vivo.

By utilizing the air quality monitoring data and the NCEP reanalysis data, the relationship between the PM10 air pollution episode and synoptic situation is analyzed in the Beijing area. It is interesting to find that PM10 air pollution episode in and around the Beijing area is correlated with the Western Pacific tropical cyclone track to some extent, namely when a tropical cyclone lands southward to the Changjiang River, PM10 air pollution episode is not easy to take place generally in the Beijing area; but when a tropical cyclone moves northward and finally lands at the Korea Peninsula or the Japanese mainland, and under this condition the Beijing area is generally controlled by weak high or weak low for several days, PM10 air pollution episode often takes place in one day or several days. Above findings indicate that predicting the Western Pacific tropical cyclone track can foretell whether or not PM10 air pollution episode takes place in the Beijing area, which can offer a technique for urban air quality prediction and air pollution source management in the Beijing area.

Summary Time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased hospitalizations, typically at a single lag of 0, 1 or 2 days after an air pollution episode. Two important scientific objectives are to understand better how the risk of hospitalization that is associated with a given day’s air pollution increase is distributed over multiple days in the future and to estimate the cumulative short-term health effect of an air pollution episode over the same multiday period. We propose a Bayesian hierarchical distributed lag model that integrates information from national health and air pollution databases with prior beliefs of the time course of risk of hospitalization after an air pollution episode. This model is applied to air pollution and health data on 6.3 million enrollees of the US Medicare system living in 94 counties covering the years 1999–2002. We obtain estimates of the distributed lag functions relating fine particulate matter pollution to hospitalizations for both ischaemic heart disease and acute exacerbation of chronic obstructive pulmonary disease, and we use our model to explore regional variation in the health risks across the USA.

The application of complex atmospheric transport and transformation mesoscale models is becoming more common for study complex environmental problems. In this contribution, we present a pollution episode occurred in the area of Stara Zagora (Bulgaria), where a large SO 2 industrial emitter is present. This industrial emitter accounts for more than 75% of the total SO 2 emissions in Bulgaria. Two monitoring stations located in Stara Zagora and Mogila observed high SO 2 concentration peaks for 7–11 July 2007. We have used the MM5–CMAQ air quality modelling system with CBM-IV chemical mechanism. We have used two different emission modelling tools such as SMOKE and EMIMO. In the first simulation SMOKE is used. In the second simulation, we have used EMIMO including biogenic and anthropogenic sources coming from traffic, domestic sources, etc. Additionally, in the second simulation we have used a so-called ON–OFF approach, which means that we have run two time the modelling system with and without the emissions of the large industrial plant “Maritza-Iztok”, located in the surrounding area of the two monitoring stations. The use of MM5–CMAQ air quality modelling system with two different approaches, parameterizations, spatial resolution, emission modelling systems and vertical grid levels produce two significantly different results. The results show that the parameterizations and approaches for using a complex air quality modelling system such as MM5–CMAQ, are crucial for obtaining some similarities between observed and modelled data.

The concentrations of fine particulate matter (PM) and ozone in Beijing often exceed healthful levels in recent years, therefore China is to taking steps to improve Beijing's air quality for the 2008 Olympic Games. In this paper, the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System was used to investigate a heavy air pollution episode in Beijing during 3–7 April 2005 to obtain the basic information of how heavy air pollution formed and the contributions of local sources and surround emissions. The modeling domain covered from East Asia with four nested grids with 81 to 3 km horizontal resolution focusing on urban Beijing. This was coupled with a regional emissions inventory with a 10 km resolution and a local 1 km Beijing emissions database. The trend of predicted concentrations of various pollutants agreed reasonably well with the observations and captured the main features of this heavy pollution episode. The simulated column concentration distribution of PM was correlated well with the MODIS remote sensing products. Control runs with and without Beijing emissions were conducted to quantify the contributions of non-Beijing sources (NBS) to the Beijing local air pollution. The contributions of NBS to each species differed spatially and temporally with the order of PM2.5>PM10>SO2> soil for this episode. The percentage contribution of NBS to fine particle (PM2.5) in Beijing was averaged about 39%, up to 53% at the northwest of urban Beijing and only 15% at southwest. The spatial distribution of NBS contributions for PM10 was similar to that for PM2.5, with a slightly less average percentage of about 30%. The average NBS contributions for SO2 and soil (diameter between 2.5 μm and 10 μm) were 18% and 10%. In addition, the pollutant transport flux was calculated and compared at different levels to investigate transport pathway and magnitude. It was found that the NBS contribution correlated with the transport flux, contributing 60% of PM10 concentration in Beijing at the time of transport flux peak during a strong episode with a transport path from southwest to northeast.

Introduction On 6-18 March 2014, a major episode of air pollution (PM10 concentrations exceeding 100 µg/m3 locally for several days) affected almost all France as well as other European countries, ...

Heavy air pollution episodes occurred in Beijing in January 2013 attracted intensively attention around the whole world. During this period, the authors conducted highly time-resolved measurements of water soluble ions associated with PM 2.5 at an urban site, and attempted to distinguish the ion chemistry and potential sources. In this study, hourly mean concentrations of Cl − , NO 3 − , SO 4 2− , Na + , NH 4 + , K + , Mg 2+ and Ca 2+ were measured during the air pollution episode in January 2013, and the ions were found to exist mainly in the form of (NH 4 ) 2 SO 4 , NH 4 NO 3 , NaCl and KCl in aerosol particles by correlation and linear analysis. SO 4 2− and NO 3 − were observed peak concentrations in 10–15, 18–20, 21–24, and 26–30 January during this monitoring campaign. The percentage of SO 4 2− and NH 4 + in total ions concentrations exhibited an increasing trend with the enhancement of PM 2.5 concentration, indicating high concentrations of SO 4 2− and NH 4 + had played important roles in the formation of air pollution episodes. Ratio of [NO 3 − ]/[SO 4 2− ] was calculated, finding the sources of SO 4 2− would contribute more to the formation of PM 2.5 than mobile sources. Diurnal variations of SO 4 2− , NO 3 − , NH 4 + were examined, and all of them exhibited similar pattern with high concentration in night and relative low level at daytime. Emission from coal combustion, remote transportation at night or impact of meteorological was likely to be responsible for the high level of SO 4 2− , NH 4 + andNO 3 − . Potential sources were identified by applying PMF. Secondary nitrate, secondary sulfate, coal combustion and biomass burning, as well as fugitive dust were considered as the major contributors to total ions.

Background: The dramatic increase in population and industrialization in Cairo has resulted in a significant deterioration in air quality. The serious impact of air pollution in Cairo was manifested since the last 8 year in the “black smoke phenomenon” which invaded its atmosphere during the months of October and November. Methods: This study evaluated the changing trends of air quality monitoring including sulphur dioxide [SO2], nitrogen dioxide [NO2], Particular matter less than 10 μm in aerodynamic diameter, [PM10], particulate matter less than 2.5 μm [PM2.5], meteorological parameters as wind stability and wind seed [W.S], in Cairo during the years 2002-2004 and their relation to respiratory health risks. Results: It was found that there was a significant association between air pollutants with the number of asthma admissions, [P 0.05]. There was negative correlation between wind speed and asthma admissions, [P

We examine the extent to which the sensitivity of ground-level ozone concentrations to precursor emissions varies with grid resolution in a regional air quality model. Nested grids of 36-, 12- and 4-km resolution are applied to model an air pollution episode in Georgia. A direct sensitivity analysis method is used to compute the response of ozone to emissions of its precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs). All three grids predict that ozone production is limited primarily by the availability of NOx, and yield similar predictions of average ozone sensitivity to both regional and local emissions of NOx. However, in urban areas, the coarsest (36-km) resolution fails to capture the extent and magnitude of VOC sensitivity and underpredicts the nonlinearity of ozone response indicated by the finest resolution. Medium (12-km) resolution is sufficient to reproduce most features of ozone response, except for the texture of local variability. Despite the consistency of average results, discrepancies in wind fields at times lead to inconsistencies in the predicted location of ozone enhancements, especially for a power plant plume.