Surface ozone (SOZ) can be very harmful if it exceeds the threshold limit. It can accumulate over sea and can return back to the land along with the breeze. Rural and vegetation rich areas often record elevated levels of surface ozone because of the variations in Volatile Organic Compound (VOC) levels, wind velocity and direction. Similarly methane is also an important greenhouse gas and plays a vital role in the atmospheric budget. In this work, ozone and methane levels measured during daytime in a mangrove estuary near Manakudy(8.0911 N, 77.477 E),kanyakumari, South India for a period of ten months from March 2014 to December 2014 are analyzed.SOZ showed an imprecise diurnal pattern with an early morning peak whereas methane recorded an apparent diurnality. The maximum value of SOZ was around 50 ppb. Summer months recorded high levels of SOZ followed by Southwest monsoon (SWM) and Northeast monsoon (NEM).High levels of methane were found in SWM followed by NEM and low concentration during summer. The correlation between SOZ and methane was found as r = -0.257, p

Les territoires périurbains, zones de transition entre les zones urbaines et rurales, sont soumis à de nombreuses pollutions à la fois gazeuses et particulaires. Ces pollutions proviennent de sources locales comme les activités résidentielles, le trafic routier et les activités agricoles, mais également de sources régionales issues des activités urbaines et des émissions des zones (pseudo-)naturelles adjacentes. Cet article présente une synthèse des différentes sources de pollution affectant la qualité de l’air en milieu périurbain. Il est évident que les pollutions purement anthropiques ne peuvent être dissociées de celles issues du fonctionnement des écosystèmes (pseudo-)naturels dans ces espaces. Enfin, les enjeux vis-à-vis de l’agriculture périurbaine, fortement présente et en développement du fait d’une volonté de consommer des productions locales, sont discutés. | Periurban areas, zone of transition between urban and rural areas, are submitted to several sources of pollution, both gaseous and particulate. These pollutions originate from local sources such as residential sector, traffic road and agricultural activities, but also from regional ones from adjacent urban and (pseudo-)natural areas. This paper presents a synthesis of the different sources affecting air quality in periurban areas. It is clear that pollutions from anthropogenic activities cannot be fully dissociated to those from (pseudo-)natural ecosystem functioning in these areas. Finally, the atmospheric pollution issues are discussed in emphasis with periurban agriculture, already present and under development in these areas due to the development of short food supply chains and local food consumptions.

The interaction of aerosols and the planetary boundary layer (PBL) plays an important role in deteriorating urban air quality. Aerosols from different sources may have different effects on regulating PBL structures owing to their distinctive dominant compositions and vertical distributions. To characterize the complex feedback of aerosols on PBL over the Beijing megacity, multiple approaches, including in situ observations in the autumn and winter of 2016–2019, backward trajectory clusters, and large-eddy simulations, were adopted. The results revealed notable distinctions in aerosol properties, vertical distributions and thermal stratifications among three types of air masses from the West Siberian Plain (Type-1), Central Siberian Plateau (Type-2) and Mongolian Plateau (Type-3). Low loadings of 0.28 ± 0.26 and 0.15 ± 0.08 of aerosol optical depth (AOD) appeared in the Type-1 and Type-2, accompanied by cool and less stable stratification, with a large part (80%) of aerosols concentrated below 1500 m. For Type-3, the AOD and single scattering albedo (SSA) were as high as 0.75 ± 0.54 and 0.91 ± 0.05, demonstrating severe pollution levels of abundant scattering aerosols. Eighty percent of the aerosols were constrained within a lower height of 1150 m owing to the warmer and more stable environment. Large-eddy simulations revealed that aerosols consistently suppressed the daytime convective boundary layer regardless of their origins, with the PBL height (PBLH) decreasing from 1120 m (Type-1), 1160 m (Type-2) and 820 m (Type-3) in the ideal clean scenarios to 980 m, 1100 m and 600 m, respectively, under polluted conditions. Therefore, the promotion of absorbing aerosols below the residual layer on PBL could be greatly hindered by the suppression effects generated by both absorbing aerosols in the upper temperature inversion layer and scattering aerosols. Moreover, the results indicated the possible complexities of aerosol-PBL interactions under future emission-reduction scenarios and in other urban regions.

Ozone levels have been declining in the Los Angeles, CA, USA area for the last four decades, but there was a recent uptick in the 4th highest daily maximum 8-h (MDA8) ozone concentrations from 2014 to 2018 despite continued reductions in the estimated precursor emissions. In this study, we assess the emissions and meteorological impacts on the 4th highest MDA8 ozone concentrations to better understand the factors affecting the observed MDA8 ozone using a two-step generalized additive model (GAM)/least squares approach applied to the South Coast Air Basin (SoCAB) for the 1990 to 2019 period. The GAM model includes emissions, meteorological factors, large-scale climate variables, date, and the interactions between meteorology and emissions. A least squares method was applied to the GAM output to better capture the 4th highest MDA8 ozone. The resulting two-step model had an R² of 0.98 and a slope of 1 between the observed and predicted 4th highest MDA8 ozone. Emissions and the interactions between the maximum temperature and emissions explain most of the variation in the peak MDA8 ozone concentrations. Declining emissions have lowered the 4th highest MDA8 ozone concentration. Meteorology explains the higher than expected 4th-high, ozone levels observed in 2014–2018, indicating that meteorology was a stronger forcer than the continued reductions in emissions during that time period. The model was applied to estimate future ozone levels. Meteorology developed from climate modeling of the representative concentration pathway (RCP) scenarios, and two sets of emissions were used in the application. The modeling results indicated climate trends will push ozone levels slightly higher if no further emissions reductions are realized and that of two emissions trajectories modeled, the more stringent is required to reliably meet the federal ozone standard given annual meteorological variability.

Air pollution is becoming serious in developing country, and how to quantify the role of local emission and/or meteorological factors is very important for government to implement policy to control pollution. Here, we use a random forest model, a machine learning (ML) approach, combined with a de-weather method to analyze the PM₂.₅ level during the COVID-19 outbreak in Hubei Province. The results show that changes in anthropogenic emissions have reduced PM₂.₅ concentrations in February and March 2020 by about 33.3% compared to the same period in 2019, while changes in meteorological conditions have increased PM₂.₅ concentrations by about 8.8%. Moreover, the impact of meteorological conditions is more significant in the central region, which is likely to be related to regional transport. After excluding the contribution of meteorological conditions, the PM₂.₅ concentration in Hubei Province in February and March 2020 is lower than the secondary standard of China (35 μ g/m³). Our estimates also indicate that under similar meteorological conditions as in February and March 2019, an emission reduction intensity equivalent to about 48% of the emission reduction intensity during the lockdown may bring the annual average PM₂.₅ concentration to the standard (35 μ g/m³). Our study shows that machine learning is a powerful tool to quantify the influencing factors of PM₂.₅, and the results further emphasize the need for scientific emission reduction as well as joint regional control measures in future.

Herein, a two-dimensional (2-D) vertically-averaged hydrodynamic model was applied to study the heavy metal particle footprints pre- and post-Three Gorges Dam (TGD) in Poyang Lake. Two defined indexes-Reserve Impact Index (σRII) and Species Impact Index (ηSII) were applied to assess the potential impact of the copper footprint on nature reserves and sensitive species quantitatively. The results demonstrated that the movement speed, distribution, and trajectory of copper particle footprints differed enormously pre- and post-TGD. By contrast, the post-TGD footprints were more complex because of the dam-induced variations in hydrology and meteorology. TGD had both pros and cons for the copper footprint on the reserves based on the results of σRII. It had changed the way for the transport of heavy metals and altered the patterns of exposure risk in the reserves. Sustainable management of Poyang Lake could be achieved by optimizing daily monitoring works. The ηSII for Finless Porpoises do not differ significantly between scenarios, but the ηSII for Siberian White Cranes increased by 0.92 and 0.83 for the two periods pre- and post-TGD, respectively. Heavy metals in food sources and the excreta of Siberian White Cranes could be of great concern in future studies. This study provides a theoretical basis for the in-depth study of the TGD-induced impact on Poyang Lake and provides a reference for the long-term treatment of Poyang Lake and the protection of key species.

Air pollution and extreme heat have been responsible for more than a million deaths in China every year, especially in densely urbanized regions. While previous studies intensively evaluated air pollution episodes and extreme heat events, a limited number of studies comprehensively assessed atmospheric hot-and-polluted-episodes (HPE) – an episode with simultaneously high levels of air pollution and temperature – which have potential adverse synergic impacts on human health. This study focused on the Pearl River Delta (PRD) region of China due to its high temperature in summer and poor air quality throughout a year. We employed geostatistical downscaling to model meteorology at a spatial resolution of 1 km, and applied a machine learning algorithm (XGBoost) to estimate a high-resolution (1 km) daily concentration of particulate matter with an aerodynamic diameter ≤2.5 μm (PM₂.₅) and ozone (O₃) for June to October over 20 years (2000–2019). Our results indicate an increasing trend (∼50%) in the frequency of HPE occurrence in the first decade (2000–2010). Conversely, the annual frequency of HPE occurrence reduced (16.7%), but its intensity increased during the second decade (2010–2019). The northern cities in the PRD region had higher levels of PM₂.₅ and O₃ than their southern counterparts. During HPEs, regional daily PM₂.₅ exceeded the World Health Organization (WHO) and Chinese guideline levels by 75% and 25%, respectively, while the O₃ exceeded the WHO O₃ standard by up to 69%. Overall, 567,063 (95% confidence interval (CI): 510,357–623,770) and 52,231 (95%CI: 26,116–78,346) excessive deaths were respectively attributable to exposure to PM₂.₅ and O₃ in the PRD region. Our findings imply the necessity and urgency to formulate co-benefit policies to mitigate the region's air pollution and heat problems.

Urban and regional ozone (O₃) pollution is a public health concern and causes damage to ecosystems. Due to the diverse emission sources of O₃ precursors and the complex interactions of air dispersion and chemistry, identifying the contributing sources of O₃ pollution requires integrated analysis to guide emission reduction plans. In this study, the meteorological characteristics leading to O₃ polluted days (in which the maximum daily 8–h average O₃ concentration is higher than the China Class II National O₃ Standard (160 μg/m³)) in Guangzhou (GZ, China) were analyzed based on data from 2019. The O₃ formation regimes and source apportionments under various prevailing wind directions were evaluated using a Response Surface Modeling (RSM) approach. The results showed that O₃ polluted days in 2019 could be classified into four types of synoptic patterns (i.e., cyclone, anticyclone, trough, and high pressure approaching to sea) and were strongly correlated with high ambient temperature, low relative humidity, low wind speed, variable prevailing wind directions. Additionally, the cyclone pattern strongly promoted O₃ formation due to its peripheral subsidence. The O₃ formation was nitrogen oxides (NOₓ)-limited under the northerly wind, while volatile organic compounds (VOC)-limited under other prevailing wind directions. Anthropogenic emissions contributed largely to the O₃ formation (54–78%) under the westerly, southwesterly, easterly, southeasterly, or southerly wind, but only moderately (35–47%) under the northerly or northeasterly wind. Furthermore, as for anthropogenic contributions, local emission contributions were the largest (39–60%) regardless of prevailing wind directions, especially the local NOₓ contributions (19–43%); the dominant upwind regional emissions contributed 12–46% (e.g., contributions from Dongguan were 12–20% under the southeasterly wind). The emission control strategies for O₃ polluted days should focus on local emission sources in conjunction with the emission reduction of upwind regional sources.

Potential health benefits from improved ambient air quality during the COVID-19 shutdown have been recently reported and discussed. Despite the shutdown measures being in place, northern China still suffered severe haze episodes (HE) that are not yet fully understood, particularly how the source emissions changed. Thus, the meteorological conditions and source emissions in processing five HEs occurred in Beijing-Tianjin-Hebei area were investigated by analyzing a comprehensive real-time measurement dataset including air quality data, particle physics, optical properties, chemistry, aerosol lidar remote sensing, and meteorology. Three HEs recorded before the shutdown began were related to accumulated primary pollutants and secondary aerosol formation under unfavorable dispersion conditions. The common “business as usual” emissions from local primary sources in this highly polluted area exceeded the wintertime atmospheric diffusive capacity to disperse them. Thus, an intensive haze formed under these adverse meteorological conditions such as in the first HE, with coal combustion to be the predominant source. Positive responses to the shutdown measures were demonstrated by reduced contributions from traffic and dust during the final two HEs that overlapped the Spring and Lantern Festivals, respectively. Local meteorological dispersion during the Spring Festival was the poorest among the five HEs. Increased residential burning plus fireworks emissions contributed to the elevated PM₂.₅ with the potential of enhancing the HEs. Our results highlight that reductions from shutdown measures alone do not prevent the occurrence of HEs. To further reduce air pollution and thus improve public health, abatement strategies with an emphasis on residential burning are needed.