In recent years, implementation of aggressive and strict clean air policies has resulted in significant decline in observed PM₂.₅ concentration in the Beijing–Tianjin–Hebei (BTH) region and its surrounding areas (i.e., the “2 + 26” region). To eliminate the effects of interannual and seasonal meteorological variation, and to evaluate the effectiveness of emission abatement policies, we applied a boosted regression tree model to remove confounding meteorological factors. Results showed that the annual average PM2.5 concentration normalized by meteorology for the “2 + 26” region declined by 38% during 2014–2019 (i.e., from 96 to 60 μg/m³); however, the BTH region exhibited the most remarkable decrease in PM₂.₅ concentration (i.e., a 60% reduction). Certain seasonal trend in normalized PM₂.₅ level remained for four target subregions owing to the effects of anthropogenic emissions in autumn and winter. Although strong interannual variations of meteorological conditions were unfavorable for pollutant dispersion during the heating seasons of 2016–2018, the aggressive abatement policies were estimated to have contributed to reductions in normalized PM₂.₅ concentration of 19%, 10%, 19%, and 17% in the BTH, Henan, Shandong, and Shanxi subregions, respectively. Our study eliminated the meteorological contribution to concentration variation and confirmed the effectiveness of the implemented clean air policies.

PM₂.₅ pollution is caused by multiple factors and determining how these factors affect PM₂.₅ pollution is important for haze control. In this study, we modified the geographically weighted regression (GWR) model and investigated the relationships between PM₂.₅ and its influencing factors. Experiments covering 368 cities and 9 urban agglomerations were conducted in China in 2015 and more than 20 factors were considered. The modified GWR coefficients (MGCs) were calculated for six variables, including two emission factors (SO₂ and NO₂ concentrations), two meteorological factors (relative humidity and lifted index), and two topographical factors (woodland percentage and elevation). Then the spatial distribution of MGCs was analyzed at city, cluster, and region scales. Results showed that the relationships between PM₂.₅ and the different factors varied with location. SO₂ emission positively affected PM₂.₅, and the impact was the strongest in the Beijing–Tianjin–Hebei (BTH) region. The impact of NO₂ was generally smaller than that of SO₂ and could be important in coastal areas. The impact of meteorological factors on PM₂.₅ was complicated in terms of spatial variations, with relative humidity and lifted index exerting a strong positive impact on PM₂.₅ in Pearl River Delta and Central China, respectively. Woodland percentage mainly influenced PM₂.₅ in regions of or near deserts, and elevation was important in BTH and Sichuan. The findings of this study can improve our understanding of haze formation and provide useful information for policy-making.

Isoprene, formaldehyde and acetaldehyde are important reactive organic compounds which strongly impact atmospheric oxidation processes and formation of tropospheric ozone. Monsoon meteorology and the topography of Himalayan foothills cause surface emissions to get rapidly transported both horizontally and vertically, thereby influencing atmospheric processes in distant regions. Further in monsoon, Indo-Gangetic Plain is a major rice growing region of the world and daytime hourly ozone can frequently exceed phytotoxic dose of 40 ppb O₃. However, the sources and ambient variability of these compounds which are potent ozone precursors are unknown. Here, we investigate the sources and photochemical processes driving their emission/formation during monsoon season from a sub-urban site at the foothills of the Himalayas. The measurements were performed in July, August and September using a high sensitivity mass spectrometer. Average ambient mixing ratios (±1σ variability) of isoprene, formaldehyde, acetaldehyde, and the sum of methyl vinyl ketone and methacrolein (MVK+MACR), were 1.4 ± 0.3 ppb, 5.7 ± 0.9 ppb, 4.5 ± 2.0 ppb, 0.75 ± 0.3 ppb, respectively, and much higher than summertime values in May. For isoprene these values were comparable to mixing ratios observed over tropical forests. Surprisingly, despite occurrence of anthropogenic emissions, biogenic emissions were found to be the major source of isoprene with peak daytime isoprene driven by temperature (r ≥ 0.8) and solar radiation. Photo-oxidation of precursor hydrocarbons were the main sources of acetaldehyde, formaldehyde and MVK+MACR. Ambient mixing ratios of all the compounds correlated poorly with acetonitrile (r ≤ 0.2), a chemical tracer for biomass burning suggesting negligible influence of biomass burning during monsoon season. Our results suggest that during monsoon season when radiation and rain are no longer limiting factors and convective activity causes surface emissions to be transported to upper atmosphere, biogenic emissions can significantly impact the remote upper atmosphere, climate and ozone affecting rice yields.

This paper aims to identify the atmospheric boundary layer turbulence structure and its effect on severe foggy haze events frequently occurring in Northern China. We use data collected from a ground eddy covariance system, meteorology tower, and a PM₂.₅ collector in Baoding, China during December 2016. The data shows that 73.5% of PM₂.₅ concentration is greater than 100 μg m⁻³ with a maximum of 522 μg m⁻³. Analyses on vertical turbulence spectrum also reveal that 1) during the pollution period, lower wind can suppress large-scale turbulence eddies, which are more likely inhomogeneous, breaking into small-scale eddies, and 2) the air pollutant scattering effect for radiation could decrease the air temperature near the ground and generate weak vertical turbulence during the daytime. At night, air pollutants suppress the land surface cooling and decrease the air temperature difference as well as the vertical turbulence intensity difference. The vertical turbulence impact analysis reveals that the percentage of large-scale turbulence eddies can also change the atmospheric vertical mixing capacity. During the daytime, the air pollution evolution is controlled by the wind speed and vertical turbulence intensity. While at night, the vertical turbulence is weak and the atmospheric vertical mixing capacity is mainly controlled by the large-scale eddies’ percentage. The increased number of large-scale turbulence eddies led by low wind at night could increase the vertical mixing of air pollutants and decrease its concentration near the ground.

Eleven years, January 2008 to June 2019, of hourly nitrogen dioxide (NO₂) levels recorded at El Arenosillo observatory (Southwestern Europe) were analyzed. Annual averages ranged between 4 μg m⁻³ and 6 μg m⁻³ with peaks exceeding 40 μg m⁻³. A slight monthly variation was observed with maximum and minimum values in the cold (∼6 μg m⁻³) and warm (∼4 μg m⁻³) seasons respectively. A diurnal pattern was found with a weak amplitude (∼3 μg m⁻³). The monthly trends were investigated using surface observations and OMI (Ozone Monitoring instrument) satellite measurements. An unexpected upward trend was obtained in the last five years. The periods with elevated NO₂ concentrations in the last years were analyzed, showing an increase in its frequency and concentrations, linked with the upward trend observed. The weather conditions in these NO₂ peaks were studied using local surface meteorology, mean sea level pressure and wind fields from the data reanalysis of ERA5. The transport of NO₂ was explored using TROPOMI (Tropospheric Monitoring Instrument) measurements. The events occurred under conditions governed by high-pressure systems, which induced weak synoptic airflows or the development of mesoscale processes. Four scenarios of NO₂ transport were identified, associated with weak synoptic flows from inland or Southern Portugal and with mesoscale processes. The gulf of Cadiz plays an important role as a reservoir where the NO₂ coming from the south of Portugal, the Western Mediterranean Basin and urban-industrial areas can be accumulated and later transported inland. A strong correlation was found between the increase of NO₂ observed in the last years and positive anomalies of the temperature and geopotential height at 850 and 500 hPa levels. These findings could indicate that the causes of the changes in the NO₂ would be attributed to alterations in the weather patterns associated with a warmer climate.

Within the outline of air quality studies at metropolitan city, the mixing ratios of seven selected volatile organic compounds (VOCs) were measured during December 2015 (winter) at an urban site of Pune. The measurement of VOCs was conducted using a proton transfer reaction-quadrupole mass spectrometer (PTR-QMS). The study represents daily variability of ambient VOCs and their various associated emission sources. Diurnal profiles have differed from one VOC to another as the result of their different origins and the influence of different meteorological parameters (i.e. solar radiation, temperature) and planetary boundary layer height (PBL-H). The hourly mixing ratios of Oxygenated-VOCs (OVOCs) and aromatics were in the ranges of 0.6–29 ppbv and 0.13–14 ppbv, respectively with OVOCs accounted for up to 75% of total measured VOCs. The role of long-range transport from the clear Thar Desert and polluted Indo-Gangetic Plain (IGP) was observed during the episodes of 1–15 and 17–31 December 2015, respectively. VOCs showed the strong diurnal variations with peaks during morning and evening hours and lowest in the afternoon. In the evening period, high levels of aromatics coincided with the lowest OVOCs suggests the role of fresh vehicular emissions. Emission ratios of various VOCs as a function of temperature showed the role of different sources including the biogenic and photochemical production as well as the anthropogenic sources, respectively. The higher emission ratio of Δmethanol/Δacetonitrile at the study site suggests the long range transport of biomass burning plumes from the Indo-Gangetic Plain (IGP) during the 17–31, Dec. 2015. In addition to the pattern of emission, the diurnal and day-to-day variations of VOCs were influenced by the local meteorological conditions and depth of planetary boundary layer (PBL-H).

Lockdown measures to contain COVID-19 pandemic has resulted in a considerable change in air pollution worldwide. We estimate the temporal and diurnal changes of the six criteria air pollutants, including particulate matter (PM₂.₅ and PM₁₀) and gaseous pollutants (NO₂, O₃, CO, and SO₂) during lockdown (25ᵗʰ March – 3ʳᵈ May 2020) across regions of India using the observations from 134 real-time monitoring sites of Central Pollution Control Board (CPCB). Significant reduction in PM₂.₅, PM₁₀, NO₂, and CO has been found in all the regions during the lockdown. SO₂ showed mixed behavior, with a slight increase at some sites but a comparatively significant decrease at other locations. O₃ also showed a mixed variation with a mild increase in IGP and a decrease in the South. The absolute decrease in PM₂.₅, PM₁₀, and NO₂ was observed during peak morning traffic hours (08–10 Hrs) and late evening (20–24 Hrs), but the percentage reduction is almost constant throughout the day. A significant decrease in day-time O₃ has been found over Indo Gangetic plain (IGP) and central India, whereas night-time O₃ has increased over IGP due to less O₃ loss. The most significant reduction (∼40–60%) was found in PM₂.₅ and PM₁₀. The highest decrease in PM was found for the north-west and IGP followed by South and central regions. A considerable reduction (∼30–70%) in NO₂ was found except for a few sites in the central region. A similar pattern was observed for CO having a ∼20–40% reduction. The reduction observed for PM₂.₅, PM₁₀, NO₂, and enhancement in O₃ was proportional to the population density. Delhi’s air quality has improved with a significant reduction in primary pollutants, however, an increase in O₃ was observed. The changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations.

This study investigates the influence of meteorology, land use, built environment, and traffic characteristics on near-road ultrafine particle (UFP) concentrations. To achieve this objective, minute-level UFP concentrations were measured at various locations along a major arterial road in the Greater Toronto Area (GTA) between February and May 2019. Each location was visited five times, at least once in the morning, mid-day, and afternoon. Each visit lasted for 30 min, resulting in 2.5 h of minute-level data collected at each location. Local traffic information, including vehicle class and turning movements, were processed using computer vision techniques. The number of fast-food restaurants, cafes, trees, traffic signals, and building footprint, were found to have positive impacts on the mean UFP, while distance to the closest major road was negatively associated with UFP. We employed the Extreme Gradient Boosting (XGBoost) method to develop prediction models for UFP concentrations. The Shapley additive explanation (SHAP) measures were used to capture the influence of each feature on model output. The model results demonstrated that minute-level counts of local traffic from different directions had significant impacts on near-road UFP concentrations, model performance was robust under random cross-validation as coefficients of determination (R²) ranged from 0.63 to 0.69, but it revealed weaknesses when data at specific locations were eliminated from the training dataset. This result indicates that proper cross-validation techniques should be developed to better evaluate machine learning models for air quality predictions.

The hourly concentration of six criteria air pollutants in the Harbin-Changchun region were used to investigate the status and spatiotemporal variation of target air pollutants and their relationships with meteorological factors. The annual concentrations of particulate matters during 2013–2017 were two times higher than the Chinese Ambient Air Quality Standards (CAAQS) Grade Ⅱ. The annual O₃ concentration increased by two times during 2013–2018 in Harbin. The concentration of PM, SO₂, NO₂, and CO depicted a similar seasonal trend with an order of winter > autumn > spring > summer. The consistent interannual variation trends of PM₂.₅/CO, NO₂ and SO₂ indicated that the formation of secondary inorganic aerosols in the annual scale was dominated by the concentrations of NO₂ and SO₂. The interannual variations of the individual meteorological factors causing on PM₂.₅ and O₃ during 2013–2018 varied significantly in seasonal scale. The interannual variations were stable in annual scale indicating that the continuous decline of PM₂.₅ during 2014–2018 can be attributed to the comprehensive and strict prohibition of small coal-fired boilers and straw burning in the study area. Meanwhile, the increase in O₃ during 2013–2018 in the study area were mainly attributed to the rapid growth of the emission of its precursor (VOCs and NOx). The influence of meteorology on PM₂.₅ and ozone were the most stable and strongest in winter than that in the other three seasons.

The outbreak of COVID-19 in Daegu, South Korea, early in 2020 has led this metropolitan city to become one of the major hotspots in the world. This study investigates the association of meteorology and the new daily COVID-19 confirmed cases and the effects of the city lockdown on the variation in criteria air pollutants (CAPs) in Daegu. Ambient temperature and relative humidity were negatively correlated to the new daily cases and played an important role in the spread of COVID-19. Wind speed could enhance the virus transmission through the inhalation of aerosols and/or droplets and contact with fomites. The lockdown has directly decreased the concentrations of CAPs. In particular, reductions of 3.75% (PM₁₀), 30.9% (PM₂.₅), 36.7% (NO₂), 43.7% (CO), and 21.3% (SO₂) between the period before and during the outbreak were observed over the entire city. An increase in O₃ (71.1%) was affected by natural processes and photochemical formation other than the lockdown effects. The three central districts were the areas most affected by the virus and showed the highest reductions in CAPs (except for O₃) during the outbreak. Apart from the influence of the lockdown, the decreasing trend in CAPs may be a result of the actions taken by the government to mitigate air pollutants nationwide since 2019. The results of this study can be useful for government and medical organizations to understand the behavior of the virus in the atmosphere. Further studies are necessary to explore the detailed influences of the lockdown on the environment and public life.