Aerosol Optical Properties Based on Ground and Satellite Retrievals during a Serious Haze Episode in December 2015 over Beijing

Atmospheric microplastic deposition in a coastal city of India: The influence of a landfill source on monsoon winds

Coastal zones experience various wind events that may influence the characteristics, distribution, and dynamics of atmospheric microplastic pollutants. In the present study, we investigated the characteristics of the bulk atmospheric microplastic deposition in Kochi, Kerala, India, during three distinct seasons: Northeast Monsoon (NEM), Summer (SMR), and Southwest monsoon (SWM). Seasonally, the highest microplastic fallout rate was recorded for the NEM (37.29 particles m-2d-1), followed by SMR (15.17 particles m-2 d-1) and the SWM (11.57 particles m-2d-1). The microplastic abundance was not correlated to the amount of rainfall. Further, the wind rose and HYSPLIT trajectory analysis illustrated the arrival of northeast monsoon winds to the city via the region in and around the municipal landfill, which could be a major source of airborne microplastic to the sampling stations, and the forward trajectories from the landfill site extended into the Arabia Sea, providing evidence on the potential atmospheric transport and subsequent deposition of microplastics into the ocean. With respect to the qualitative characteristics, blue-coloured and fibrous microplastics dominated the samples with a considerable number of particles belonging to the size range of 200-500 μm. The practice of drying synthetic clothes under natural sunlight may have substantially contributed to the increased prevalence of airborne microfibers. The higher numbers of polyethylene (PE) and polypropylene (PP) in the bulk microplastic deposition reinforce the concept of low-density polymers being more susceptible to deflation by the wind. Overall, the work signifies the role of monsoon winds in transporting microplastics from an unscientifically managed municipal landfill site and also highlights the importance of reducing the quantity of plastic waste ending up at the landfill to reduce the emission of microplastics proportionately.

Construction of a virtual PM2.5 observation network in China based on high-density surface meteorological observations using the Extreme Gradient Boosting model

With increasing public concerns on air pollution in China, there is a demand for long-term continuous PM_2.5 datasets. However, it was not until the end of 2012 that China established a national PM_2.5 observation network. Before that, satellite-retrieved aerosol optical depth (AOD) was frequently used as a primary predictor to estimate surface PM_2.5. Nevertheless, satellite-retrieved AOD often encounter incomplete daily coverage due to its sampling frequency and interferences from cloud, which greatly affect the representation of these AOD-based PM_2.5. Here, we constructed a virtual ground-based PM_2.5 observation network at 1180 meteorological sites across China using the Extreme Gradient Boosting (XGBoost) model with high-density meteorological observations as major predictors. Cross-validation of the XGBoost model showed strong robustness and high accuracy in its estimation of the daily (monthly) PM_2.5 across China in 2018, with R², root-mean-square error (RMSE) and mean absolute error values of 0.79 (0.92), 15.75 μg/m³ (6.75 μg/m³) and 9.89 μg/m³ (4.53 μg/m³), respectively. Meanwhile, we find that surface visibility plays the dominant role in terms of the relative importance of variables in the XGBoost model, accounting for 39.3% of the overall importance. We then use meteorological and PM_2.5 data in the year 2017 to assess the predictive capability of the model. Results showed that the XGBoost model is capable to accurately hindcast historical PM_2.5 at monthly (R² = 0.80, RMSE = 14.75 μg/m³), seasonal (R² = 0.86, RMSE = 12.28 μg/m³), and annual (R² = 0.81, RMSE = 10.10 μg/m³) mean levels. In general, the newly constructed virtual PM_2.5 observation network based on high-density surface meteorological observations using the Extreme Gradient Boosting model shows great potential in reconstructing historical PM_2.5 at ~1000 meteorological sites across China. It will be of benefit to filling gaps in AOD-based PM_2.5 data, as well as to other environmental studies including epidemiology.

Study of Persistent Foggy-Hazy Composite Pollution in Winter over Huainan Through Ground-Based and Satellite Measurements

Through the observation of ground-based LIDAR and satellite sensors, the weather conditions of continuous foggy-hazy alternations in the Huainan region from 26 December 2016 to 5 January 2017 were analyzed and observed. In this study, the formation and influence of this event were discussed by analyzing pollutant concentrations, meteorological factors and aerosol optical characteristics. The concentrations of PM10 and PM2.5 increased significantly. The maximum value of PM10 was 412 μg/m3, and the maximum value of PM2.5 was 258 μg/m3. The transportation of pollutants and the production of man-made pollutants promote the accumulation of pollutants. In this weather process, meteorological factors such as the surface wind speed, humidity, surface temperature, and inversion also promote the accumulation of pollutants, which is the main reason for the formation of this weather process. Furthermore, the near surface air mass mainly came from the cities near the Huainan region and the heavily polluted areas in the north, while the upper air mass came from Inner Mongolia. In this paper, piecewise inversion was adopted to achieve accurate all-weather extinction coefficient profile inversion by reasonably selecting a cloud LIDAR ratio through a backscatter ratio, and the LIDAR ratio of cloud in this period was 22.57–34.14 Sr. By means of extinction coefficient inversion and correlation analysis, the correlation index of PM2.5 and the aerosol optical depth (AOD) was 0.7368, indicating that there was a positive correlation between PM2.5 and AOD, and AOD can also reflect the pollution condition of this region. The formation process of foggy-hazy weather in the Huainan region studied in this paper can provide a research basis for foggy-hazy pollution in this region.

Contribution of Meteorological Conditions to the Variation in Winter PM2.5 Concentrations from 2013 to 2019 in Middle-Eastern China

Severe air pollution events accompanied by high PM2.5 concentrations have been repeatedly observed in Middle-Eastern China since 2013 and decreased in recent years. The reason for this caused widespread attention. The month of January was selected to represent the winter season annual changes in the winter PM2.5 and meteorological conditions—including the upper-air meridional circulation index (MCI), winds at 700 and 850 hPa levels and surface meteorology—from 2013 to 2019. These conditions were analyzed to study the contribution of meteorology changing to the annual PM2.5 changing on the regional scale. Results show that, based on values of upper-level MCI, the years 2014, 2015, 2017, and 2019 were defined as meteorology-haze years and the years 2016 and 2018 were defined as meteorology-clean years. A change in meteorological conditions may lead to a 26% change in PM2.5 concentration between 2014 and 2013 (two meteorology-haze years) and 16–20% changes in PM2.5 concentration between meteorology-haze years and meteorology-clean years. Changes in pollutant emissions may cause 21–47% changes in PM2.5 concentration between each two meteorology-haze years. A comparison of two meteorology-clean years and pollutant emissions in 2018 may be reduced by 40% compared with 2016. Overall, changes in emissions had a greater influence on changes in PM2.5 compared with meteorological conditions.

Five-year observation of aerosol optical properties and its radiative effects to planetary boundary layer during air pollution episodes in North China: Intercomparison of a plain site and a mountainous site in Beijing

The aerosol microphysical, optical and radiative properties of the whole column and upper planetary boundary layer (PBL) were investigated during 2013 to 2018 based on long-term sun-photometer observations at a surface site (~106 m a.s.l.) and a mountainous site (~1225 m a.s.l.) in Beijing. Raman-Mie lidar data combined with radiosonde data were used to explore the aerosol radiative effects to PBL during dust and haze episodes. The results showed size distribution exhibited mostly bimodal pattern for the whole column and the upper PBL throughout the year, except in July for the upper PBL, when a trimodal distribution occurred due to the coagulation and hygroscopic growth of fine particles. The seasonal mean values of aerosol optical depth at 440 nm for the upper PBL were 0.31 ± 0.34, 0.30 ± 0.37, 0.17 ± 0.30 and 0.14 ± 0.09 in spring, summer, autumn and winter, respectively. The single-scattering albedo at 440 nm of the upper PBL varied oppositely to that of the whole column, with the monthly mean value between 0.91 and 0.96, indicating weakly to slightly strong absorptive ability at visible spectrum. The monthly mean direct aerosol radiative forcing at the Earth's surface and the top of the atmosphere varied from -40 ± 7 to -105 ± 25 and from -18 ± 4 to -49 ± 17 W m^-2, respectively, and the maximum atmospheric heating was found in summer (~66 ± 12 W m^-2). From a radiative point of view, during dust episode, the presence of mineral dust heated the lower atmosphere, thus promoting vertical turbulence, causing more air pollutants being transported to the upper air by the increasing PBLH. In contrast, during haze episode, a large quantity of absorbing aerosols (such as black carbon) had a cooling effect on the surface and a heating effect on the upper atmosphere, which favored the stabilization of PBL and occurrence of inversion layer, contributing to the depression of the PBLH.

Air stagnation and its impact on air quality during winter in Sichuan and Chongqing, southwestern China

The Sichuan and Chongqing regions suffer from severe haze weather in winter due to the unfavourable atmospheric diffusion conditions. Reanalysis and precipitation datasets were applied in this study to calculate and distinguish air stagnation events using a developed criterion, and the impacts of the occurrence of air stagnation events on air quality were analysed in combination with the PM_2.5 concentration data for the winters of 2013-2016. The highest occurrence frequency of air stagnation events was observed in 2013, and the lowest, 2015. The meteorological conditions during winter in the Sichuan Basin were inclined to form unfavourable atmospheric diffusion conditions, and the occurrence frequency of air stagnation days was up to 76.6% on average during the four winters. The effects of air stagnation events on air quality were most obvious in the western and southern Sichuan Basin. The mean concentrations of PM_2.5 during air stagnation days were higher by 41.9% than those during non-air stagnation days. The PM_2.5 concentrations were adjusted using the favourable atmospheric diffusion conditions in 2015 as a baseline to quantify the PM_2.5 contribution to the improvement of air quality in the other years, which revealed that the level of PM_2.5 in the Sichuan and Chongqing regions was declining at a rate of approximately 10.7% overall during the winters of 2013-2016, implying that the air pollutant reduction measures have been highly effective. Furthermore, the occurrence frequency of air stagnation days and events were increased in recent ten years of 2007-2016, with linear slopes of 0.61yr^-1 and 0.26yr^-1, respectively. The study revealed that the government might face a greater challenge in improving the air quality over winter and should pay more attention to reduction of pollutant emission in areas of Chengdu, Chongqing and cities in the south of the Sichuan Basin.

Changes in Haze Trends in the Sichuan-Chongqing Region, China, 1980 to 2016

This study analyzed the long-term variations and trends of haze pollution and its relationships with emission and meteorological factors using the haze days (HDs) data derived from surface observation stations in Sichuan-Chongqing (SCC) region during 1980–2016. The results showed that the multi-year mean number of HDs were 68.7 and 4.9 days for the Sichuan-Basin (SCB) and the rest of SCC region, respectively. The seasonally averaged HDs over SCB reached its maximum in winter (34.7 days), followed by autumn (17.0 days) and spring (11.6 days), and with the minimum observed in summer (5.5 days). The inter-annual variations of HDs in 18 main cities revealed that Zigong, Neijiang, and Yibin, which are located in the southern of SCB, have been the most polluted areas over the SCC region in the past decades. A notable increasing trend in annual HDs over the majority of SCC region was found during 1980–1995, then the trend sharply reversed during 1996–2005, while it increased, fluctuating at some cities after 2006. Seasonally, the increased trend in spring and autumn seems to be the strongest during 1980–1995, whereas the decreased trend in spring and winter was stronger than other seasons during 1996–2005. In addition, a remarkable increasing trend was found in winter since 2006. Using correlation analysis between HDs and emission and meteorological factors during different periods, we found that the variability of local precipitation days (PDs), planetary boundary layer height (PBLH), near-surface wind speed (WS), and relatively humidity (RH) play different roles in influencing the haze pollution change during different historical periods. The joint effect of sharp increase of anthropogenic emissions, reduced PDs and WS intensified the haze pollution in SCB during 1980–1995. In contrast, decreased HDs during 1996–2005 are mainly attributable to the reduction of PM2.5 emission and the increase of PDs (especially in winter). In addition, the decrease of PDs is likely to be responsible for the unexpected increase in winter HDs over SCB in the last decade.