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Jakarta, as a megapolitan city, is always crowded with thousands of vehicles every day which results in decreased air quality due to combustion emissions and may have a significant impact on human health. Particulate matter (PM2.5) is a pollutant that has an aerodynamic diameter of fewer than 2.5 micrometers and is very easy to enter the human respiratory system so it can affect health. In the dry season, rain as the main natural mechanism for reducing PM2.5 occurs very rarely, causing an accumulation of PM2.5 concentrations in the atmosphere. The weather research and forecasting model coupled with the chemistry (WRF-Chem) model is a dynamic model that works with atmospheric chemistry combined with meteorological variables simultaneously. This study aims to simulate the concentration of PM2.5 in Jakarta during the high air pollution episode from 20 to 29 June 2019 with the WRF-Chem model based on the T1-MOZCART chemical scheme. Spatial analysis was conducted to determine the distribution of PM2.5 concentrations during high air pollution episodes in Jakarta. Validation of the simulation model was based on three observation sites, one in South Jakarta and two in Central Jakarta. The results showed that the highest correlation is 0.3 and the lowest root mean square error (RMSE) is 26.4, while the simulations still tend to overestimate the PM2.5 concentration.

The Indo-Gangetic Plain (IGP) experienced an intensive air pollution episode during November 2017. Weather Research and Forecasting model coupled to Chemistry (WRF-Chem), a coupled meteorology–chemistry model, was used to simulate this episode. In order to capture PM2.5 peaks, we modified input chemical boundary conditions and biomass burning emissions. The Community Atmosphere Model with Chemistry (CAM-chem) and Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) global models provided gaseous and aerosol chemical boundary conditions, respectively. We also incorporated Visible Infrared Imaging Radiometer Suite (VIIRS) active fire points to fill in missing fire emissions in the Fire INventory from NCAR (FINN) and scaled by a factor of 7 for an 8 d period. Evaluations against various observations indicated the model captured the temporal trend very well although missed the peaks on 7, 8, and 10 November. Modeled aerosol composition in Delhi showed secondary inorganic aerosols (SIAs) and secondary organic aerosols (SOAs) comprised 30 % and 27 % of total PM2.5 concentration, respectively, during November, with a modeled OC/BC ratio of 2.72. Back trajectories showed agricultural fires in Punjab were the major source for extremely polluted days in Delhi. Furthermore, high concentrations above the boundary layers in vertical profiles suggested either the plume rise in the model released the emissions too high or the model did not mix the smoke down fast enough. Results also showed long-range-transported dust did not affect Delhi's air quality during the episode. Spatial plots showed averaged aerosol optical depth (AOD) of 0.58 (±0.4) over November. The model AODs were biased high over central India and low over the eastern IGP, indicating improving emissions in the eastern IGP can significantly improve the air quality predictions. We also found high ozone concentrations over the domain, which indicates ozone should be considered in future air quality management strategies alongside particulate matter.

Northeastern China (NEC) has experienced serious environmental problems by energy consumption and domestic emission. This paper reviews an extreme haze event occurred in Shenyang, NEC, on 5–9 January 2017. The meteorological data, extinction coefficients from ground-based Lidar and aerosol optical products from Moderate Resolution Imaging Spectroradiometer (MODIS) were used to study this pollution evolution. The deterioration of visibility lasted for 57 h with a minimum value reached to 0.2 km. The SO2 decreased slightly to approximately 150 μg/m3 while the NO2 mass concentration increased to approximately 100 μg/m3. The northeastern wind (1–2 m/s) and higher relative humidity (RH) (90%) as well as increased pressure (1020 hPa) were conducive to particulate matter (PM) accumulation and degraded visibility. An inversion layer began to appear at 0.2 km and developed upward to 2.0 km with the development of heavy pollution, and the RH in the ground and upper air both increased significantly to 80%–90% to conducive larger aerosol extinction. The aerosol extinction coefficient increased to 1.7–1.8 km−1 during the serious pollution, and the average aerosol optical depth (AOD) increased to 1.5 with a larger Angstrom exponent (AE) increasing to 1.5 on 7 January. Five main clusters of air trajectories indicated that pollutants from the northwest, southwest, and local emissions affected Shenyang. These findings elucidate the coordinated variation in visibility, PM, and meteorology elements in the near and upper surfaces as well as the spatial distribution in aerosols from satellites during the special pollution episode in NEC.

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.

The planetary boundary-layer (PBL) structure was investigated using observations from single aerosol lidar, eddy covariance (EC) system, and automatic meteorological station (AWS) in the north of Nanjing city during an air pollution episode in 2016–2017 winter. Based on seven days’ observations under clear to polluted day, we present the temporal variations of the aerosol extinction profiles observed by lidar, and then inter-compare PBL depth retrieved from individual gradient methods. The results show that the gradient method (GM) generated the lowest PBL depth. In contrast to the cubic root gradient method (CRGM), which determined PBL depth ranging from 172 m to 1575 m during the observation period, the logarithm gradient method (LGM) and normalized gradient method (NGM) generated similar results and both tended to overestimate PBL depth on polluted days. The CRGM performed better than LGM and NGM in case of multiple backscatter layers and could detect low level layers, while the GM was biased at low heights probably due to the effect of lidar overlap function. Based on these measurements, the evolution of boundary layer structures and PBL depth over clean days and polluted days were compared. The results show that (1) on clean days, the strong surface turbulence exchange make the PBL depth fully developed and the PBL depth had obvious characteristics of diurnal variation; the maximum depth of PBL was 1560 m for CRGM; and (2) on polluted days, the high pressure system and lower wind was favorable to the accumulation of air pollutants, and thus generating less turbulence by reducing surface radiation. These conditions on polluted days led to smaller PBL depth than those on clean days, and the maximum depth of PBL was 660 m for CRGM. Besides, the diurnal variation of PBL depth on polluted days was weaker than those on clean days.

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.

The impact of chlorine (Cl) chemistry on the formation of secondary organic aerosol (SOA) during a severe wintertime air pollution episode is investigated in this study. The Community Multiscale Air Quality (CMAQ) model v5.0.1 with a modified SAPRC-11 gas-phase mechanism and heterogeneous reactions for reactive chlorine species is updated to include the formation of chlorine radical (Cl•)-initiated SOA (Cl-SOA) from aromatic compounds, terpenes, and isoprene. Reported SOA yield data on Cl-SOA formation from environmental chamber studies are used to derive the mass yield and volatility data for the two-product equilibrium-partitioning model. The heterogeneous reaction of particulate chloride (pCl-) leads to a significant increase in the Cl• and hydroxyl radical (OH) concentrations throughout the domain. Monthly Cl-SOA concentrations range from 0.7 to 3.0 μg m-3, with increasing anthropogenic Cl emissions leading to higher Cl-SOA concentrations. Indirectly, this also leads to an increase of monthly SOA by up to 2.5-3.0 g μm-3 from the traditional OH oxidation pathways as well as the surface uptake of glyoxal and methylglyoxal. Increased OH concentrations, however, do not always lead to higher overall SOA concentrations in the entire domain. High OH reduces the lifetime of glyoxal/methylglyoxal (GLY/MGLY), making them less available to form SOA. In the Sichuan Basin (SCB) and part of Southwest China where high O3 concentrations meet high pCl emissions, a higher Cl•/OH ratio leads to net O3 loss from the Cl• + O3 reaction, thus reducing SOA formation from the O3 oxidation of volatile organic compounds (VOCs). Also, the competition between Cl• and OH for VOCs could lead to lower overall SOA because the molar yields of the semivolatile products in Cl-VOC reactions are lower than their OH + VOC reaction counterparts. When Cl• concentrations are further increased with higher emissions of Cl, precursor gases can be depleted and become the limiting factor in SOA formation. This study reveals the direct and indirect impacts of chlorine chemistry on SOA in polluted winter conditions, which are greatly affected by the Cl emissions, the ambient O3 level, and the availability of SOA precursors.

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.

Based on the Weather Research and Forecasting model and the Models-3 community multi-scale air quality model (WRF-CMAQ), this study analyzes the impacts of meteorological conditions and changes in air pollutant emissions on the heavy air pollution episode occurred over North China around the 2020 Spring Festival (January to Februray 2020). Regional reductions in air pollutant emissions required to eliminate the PM2.5 heavy pollution episode are also quantified. Our results found that meteorological conditions for the Beijing-Tianjin-Hebei and surrounding “2+26” cities are the worst during the heavy pollution episode around the 2020 Spring Festival as compared with two other typical heavy pollution episodes that occurred after 2015. However, because of the substantial reductions in air pollutant emissions in the “2+26” cities in recent years, and the 32% extra reduction in emissions during January to February 2020 compared with the baseline emission levels of the autumn and winter of 2019 to 2020, the maximum PM2.5 level during this heavy pollution episode around the 2020 Spring Festival was much lower than that in the other two typical episodes. Yet, these emission reductions are still not enough to eliminate regional heavy pollution episodes. Compared with the actual emission levels during January to February 2020, a 20% extra reduction in air pollutant emissions in the “2+26” cities (or a 45% extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020) could help to generally eliminate regionwide severe pollution episodes, and avoid heavy pollution episodes that last three or more consecutive days in Beijing; a 40% extra reduction in emissions (or a 60% extra reduction compared with baseline emission levels of the autumn and winter of 2019 to 2020) could help to generally eliminate regionwide and continuous heavy pollution episodes. Our analysis finds that during the clean period after the heavy pollution episode around the 2020 Spring Festival, the regionwide heavy pollution episode would only occur with at least a 10-fold increase in air pollutant emissions.

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 Angstrom 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.

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.

In the present study, the WRF-Chem model is used to assess contributions of residential coal combustion (RCC) emissions to the air quality in Beijing–Tianjin–Hebei (BTH) during a persistent air pollution episode from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the mass concentrations of air pollutants are in good agreement with observations at monitoring sites in BTH. The WRF-Chem model also reasonably reproduces the temporal variations in aerosol species when compared with the aerosol mass spectrometer measurements in Beijing. The RCC emissions play an important role in the haze formation in BTH, contributing about 23.1 % of PM2.5 (fine particulate matter) and 42.6 % of SO2 during the simulation period on average. Organic aerosols dominate the PM2.5 from the RCC emissions in BTH, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emissions in BTH and the surrounding areas are excluded in model simulations, with a 30 % decrease in PM2.5 mass concentrations. However, if only the RCC emissions in Beijing are excluded, the local PM2.5 mass concentration is decreased by 18.0 % on average. Our results suggest that the implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the local air quality. Should residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies would need to consider uncertainties in the emission inventory and meteorological fields.

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.

During the Asian summer monsoon season, prevailing southeasterly–southwesterly winds are subject to delivering air pollutants from the North China Plain (NCP) to northeast and northwest China. In the present study, the WRF-CHEM model is used to evaluate contributions of trans-boundary transport of NCP emissions to the air quality in northeast and northwest China during a persistent air pollution episode from 22 to 28 May 2015. The WRF-CHEM model generally performs well in capturing the observed temporal variation and spatial distribution of fine particulate matter (PM2.5), ozone (O3), and NO2. The simulated temporal variation of aerosol species is also in good agreement with measurements in Beijing during the episode. Model simulations show that NCP emissions contribute substantially to the PM2.5 level in Liaoning and Shanxi provinces, the adjacent downwind areas of the NCP, with an average of 24.2 and 13.9 µg m−3 during the episode, respectively. The PM2.5 contributions in Jilin and Shaanxi provinces are also appreciable, with an average of 9.6 and 6.5 µg m−3, respectively. The average percentage contributions of NCP emissions to the PM2.5 level in Liaoning, Jilin, Shanxi, and Shaanxi provinces are 40.6, 27.5, 32.2, and 20.9 %, respectively. The NCP emissions contribute remarkably to the O3 level in Liaoning province, with an average of 46.5 µg m−3, varying from 23.9 to 69.5 µg m−3. The O3 level in Shanxi province is also influenced considerably by NCP emissions, with an average contribution of 35.1 µg m−3. The O3 level in Shanxi province is also influenced considerably by NCP emissions, with an average contribution of 35.1 µg m−3. The average O3 contributions of NCP emissions to Jilin and Shaanxi provinces are 28.7 and 20.7 µg m−3, respectively. The average percentage contributions of NCP emissions to the afternoon O3 level in Liaoning, Jilin, Shanxi, and Shaanxi provinces are 27.4, 19.5, 21.2, and 15.8 %, respectively. However, the effect of NCP emissions on the air quality in Inner Mongolia is generally insignificant. Therefore, effective mitigation of NCP emissions not only improves the local air quality, but is also beneficial to the air quality in northeast and northwest China during the Asian summer monsoon season.

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.

Traditionally, the atmospheric particle composition is analyzed using destructive methods. In general, the destructive methods lead to the destruction of the samples, higher cost of the analysis and larger analysis time. In view of aforesaid, in current work, we present a method for the non-destructive analysis of atmospheric particles using open path-Fourier transform infrared spectroscopy (OP-FTIR). The developed method has been used for the measurement of ammonium and sulfate in atmospheric particles without destroying the samples. Here, we targeted the said species because of their relative importance for air pollution episode formation. Particulate sulfate plays a major role in formation of haze. However; particulate acidity is an important factor in this process, which is governed by particulate ammonium concentration. Therefore, both SO42− and NH4+ are important as far as atmospheric chemistry of haze formation is concerned. In the present study, the qualitative and quantitative estimation of ammonium and sulfate ions in PM2.5 (particulate matter with aerodynamic diameter less than 2.5 µm) was carried out using OP-FTIR with the developed method. The seasonal average concentration of NH4+ and SO42− were measured to be 12.00 ± 5.80, 31.71 ± 12.71 µg/m3 respectively for winters, 3.00 ± 0.85 and 8.00 ± 2.28 µg/m3 respectively for summers and 2.60 ± 1.90 and 7.00 ± 5.21 µg/m3 respectively for monsoon season. The observed results are found to be in good agreement with that of other studies using destructive methods.

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.

Using ground-based data, meteorological observations, and atmospheric environmental monitoring data, a comparative analysis of the microphysical and optical properties, and radiative forcing of aerosols was conducted between three stations in different developed environments during a severe air pollution episode during the Spring Festival over Beijing. During the most polluted period, the daily peak values of the aerosol optical depth were ~1.62, ~1.73, and ~0.74, which were about 2.6, 2.9, and 2.1 times higher than the background levels at the CAMS, Xianghe, and Shangdianzi sites, respectively. The daily peak values of the single scattering albedo were ~0.95, ~0.96, and ~0.87. The volume of fine-mode particles varied from 0.04 to 0.21 µm3 µm–2, 0.06 to 0.17 µm3 µm–2, and 0.01 to 0.10 µm3 µm–2, which were about 0.3 to 5.8, 1.1 to 4.7, and 1.2 to 8.9 times greater than the background values, respectively. The daily absorption aerosol optical depth was ~0.01 to ~0.13 at CAMS, ~0.03 to ~0.14 at Xianghe, and ~0.01 to ~0.09 at Shangdianzi, and the absorption Angstrom exponents reflected a significant increase in organic aerosols over CAMS and Xianghe and in black carbon over Shangdianzi. Aerosol radiative forcing at the bottom of the atmosphere varied from –20 to –130, –40 to –150, and –10 to –110 W m–2 for the whole holiday period, indicating the cooling effect. The potential source contribution function and concentration-weighted trajectory analysis showed that Beijing, the southern parts of Hebei and Shanxi, and the central northern part of Shandong contributed greatly to the pollution.

Predicting air pollution events in the low atmosphere over megacities requires a thorough understanding of the tropospheric dynamics and chemical processes, involving, notably, continuous and accurate determination of the boundary layer height (BLH). Through intensive observations experimented over Beijing (China) and an exhaustive evaluation of existing algorithms applied to the BLH determination, persistent critical limitations are noticed, in particular during polluted episodes. Basically, under weak thermal convection with high aerosol loading, none of the retrieval algorithms is able to fully capture the diurnal cycle of the BLH due to insufficient vertical mixing of pollutants in the boundary layer associated with the impact of gravity waves on the tropospheric structure. Consequently, a new approach based on gravity wave theory (the cubic root gradient method: CRGM) is developed to overcome such weakness and accurately reproduce the fluctuations of the BLH under various atmospheric pollution conditions. Comprehensive evaluation of CRGM highlights its high performance in determining BLH from lidar. In comparison with the existing retrieval algorithms, CRGM potentially reduces related computational uncertainties and errors from BLH determination (strong increase of correlation coefficient from 0.44 to 0.91 and significant decreases of the root mean square error from 643 to 142 m). Such a newly developed technique is undoubtedly expected to contribute to improving the accuracy of air quality modeling and forecasting systems.

Hong Kong is one of the most high-rise and highly compact cities in the world. The urban land surface is highly heterogeneous, which creates low-level convergence zones in urban areas, particularly the Kowloon Peninsula. The low-level convergence zone is due to the combined effect of urban heat island circulation (UHIC) and sea-land breeze circulation (SLBC) under weak northeasterly synoptic flow. To study the impacts of anthropogenic fluxes and built-up areas on the local circulation, the Weather Research and Forecasting (WRF) mesoscale model is combined with the multilayer urban canopy building effect parameterization/building energy model (BEP/BEM) parameterization to produce a 3 day simulation of an air pollution episode in Hong Kong in September 2012. To better represent the city land surface features, building information is assimilated in the central part of the Kowloon Peninsula. The WRF-BEP-BEM model captures the 2 m temperature distribution and local wind rotation reasonably well but overestimates the 10 m wind speed with a mean bias error of 0.70 m/s. A dome-shaped feature with a high level of moisture is captured in the convergence zones due to intensified UHIC and inflowing SLBC. The anthropogenic heat increases the air temperature by around 0.3°C up to 250 m, which in turn modifies the SLBC. A new drag coefficient based on λP, plan area per unit ground area, is tested. Besides the basic physical characteristics captured by the WRF-BEP-BEM model, the stagnation of wind in the lower level convergence zone is better captured by this approach than by the traditional constant value coefficient.

In the present study, the WRF-CHEM model is used to evaluate the contributions of trans-boundary transport to the air quality in Beijing during a persistent air pollution episode from 5 to 14 July 2015 in Beijing–Tianjin–Hebei (BTH), China. Generally, the predicted temporal variations and spatial distributions of PM2.5 (fine particulate matter), O3 (ozone), and NO2 are in good agreement with observations in BTH. The WRF-CHEM model also reproduces reasonably well the temporal variations of aerosol species compared to measurements in Beijing. The factor separation approach is employed to evaluate the contributions of trans-boundary transport of non-Beijing emissions to the PM2.5 and O3 levels in Beijing. On average, in the afternoon during the simulation episode, the local emissions contribute 22.4 % to the O3 level in Beijing, less than 36.6 % from non-Beijing emissions. The O3 concentrations in Beijing are decreased by 5.1 % in the afternoon due to interactions between local and non-Beijing emissions. The non-Beijing emissions play a dominant role in the PM2.5 level in Beijing, with a contribution of 61.5 %, much higher than 13.7 %, from Beijing local emissions. The emission interactions between local and non-Beijing emissions enhance the PM2.5 concentrations in Beijing, with a contribution of 5.9 %. Therefore, the air quality in Beijing is generally determined by the trans-boundary transport of non-Beijing emissions during summertime, showing that the cooperation with neighboring provinces to mitigate pollutant emissions is key for Beijing to improve air quality.

Air pollution episode, which are periods with excessive air pollutants, can cause a sharp increase in mortality and morbidity. Nitrogen oxides have an adverse impact on human health and the environment. Previous studies mainly focus on the time period, the frequency, and the duration of heavy NO2 pollution, while ignored its spatial extent which is pivotal in providing early warning and prediction. In this study, we investigated the spatiotemporal variation of the heavy NO2 pollution extent (i.e., heavy pollution center), analyzed its association with meteorological condition and further predicted its distribution in the future. A case study in Jing-Jin-Ji (JJJ), Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations showed that the HPC exhibited evident seasonal (winter > summer) and inter-city (mega and medium cities > small cities) differences. In concretion analysis, the HPC areas were negatively correlated with temperature and precipitation, suggesting that dry and cold meteorological conditions were responsible for the severe NO2 pollution events. Trend analysis showed that the small and medium cities may serve as the HPC in the future. During the 2005–2016, the medium and small cities in JJJ experience a more rapid increase in NO2 concentration in comparison to mega cities. Meanwhile, in YRD and PRD, a more rapid decrease was witnessed in the mega cities. The results of this study would provide support for early warning and prediction of heavy air pollutants and offer scientific insights for air pollution episode management.

The quasi-stationary front is a significant weather system which influences East Asia in spring. The air quality deteriorated along with the moist circumstance when the quasi stationary front dominated the area. Surface meteorological parameters, air pollutants and PM2.5 chemical species were observed during the air pollution episode. Liquid water content and aerosol acidity were calculated by thermodynamic model in order to investigate heterogeneous/aqueous reactions for secondary aerosol formation. The episode was divided into four stages based on quasi-stationary front influences. Hourly PM2.5 concentrations were up to 150.2 μg·m−3 while O3 concentrations reached the minimum value of 1.27 μg·m−3, indicating that the precursor gas NOx participated in the different reactions during the episode. Nitrate proportion of water-soluble inorganic ions was 42.2%. High concentrations of secondary inorganic aerosol ions and the high sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) indicated the increasing conversions from SO2 and NOx to their corresponding particulate phases. Ratios of [NO3−]/[SO42−] and [NH4+]/[SO42−] in the four stages declared that nitrate formation preferred heterogeneous conversions. A series of liquid water content (LWC) fitting equations between relative humidity and inorganic ions were conducted to verify heterogeneous aqueous reactions of NO2 and secondary nitrate formation. The results of this study highlighted the significance of LWC and chemical reactions associated with acidity during the specific synoptic situation in South China.

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.

Sulfate aerosols exert profound impacts on climate, ecosystem, visibility, and public health, but the sulfate formation pathway remains elusive. In the present study, a source-oriented WRF-Chem model is applied to simulate a persistent air pollution episode from 04 to 15 July 2015 in Beijing-Tianjin-Hebei (BTH), China to study contributions of four pathways to the sulfate formation. When comparing simulations to measurements in BTH, the index of agreement (IOA) of meteorological parameters, air pollutants and aerosol species generally exceeds 0.6. On average in BTH, the heterogeneous reaction of SO2 involving aerosol water and the SO2 oxidation by OH constitutes the two most important sulfate sources, with a contribution of about 35 %–38 % and 33 %–36 % respectively. The primary emission accounts for around 22 %–24 % of sulfate concentrations due to high SO2 emissions. The SO2 oxidation by stabilized Criegee Intermediates (sCI) also plays an appreciable role in the sulfate formation, with a contribution of around 9 % when an upper limit of the reaction rate constant of sCI with SO2 (κsCI + SO2 = 3.9 × 10−11 cm3 s−1) and a lower limit of the reaction rate constant of sCI with H2O (κsCI + H2O = 1.97 × 10−18 cm3 s−1) are used. Sensitivity studies reveal that there still exist large uncertainties in the sulfate contribution of the SO2 oxidation by sCI. The sulfate contribution of the reaction is decreased to less than 3 % when κsCI + SO2 is decreased to 6.0 × 10−13 cm3 s−1. Furthermore, when κsCI + H2O is increased to 2.38 × 10−15 cm3 s−1 based on the reported ratio of κsCI + SO2 to κsCI + H2O (6.1 × 10−5), the sulfate contribution becomes insignificant, less than 2%. Further studies need to be conducted to better determine κsCI + SO2 and κsCI + H2O to evaluate effects of the sCI chemistry on the sulfate formation.

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.

One vertical observation field campaign based on a tethered mega-balloon (with onboard instruments over 200 kg) was conducted at a campus site in rural Shanghai in order to investigate the vertical distributions of key air pollutants (PM2.5, SO2, black carbon (BC) and O3) and regional transport characteristics during a severe air pollution episode in mid-December 2015. Vertical patterns of measured air pollutants show relatively even profiles within the planetary boundary layer (PBL) while declined sharply above PBL during the daytime. Specifically, high concentrations of SO2 were observed near the top of the boundary layer. Lagrangian particle dispersion modeling showed air pollutants within the boundary layer mainly derived from local sources (i.e. Shanghai) and regional transport within the Yangtze River Delta (YRD) region in the morning before the development of boundary layer. Aerosol chemical components measured at a ground site (about 60 km northwest of the balloon site) showed that regional transport brought a large amount of aged sulfate and nitrate. This study provides new insights in the vertical distribution and transport of haze associated with the PBL development and long-range transport.

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.