Observational study of aerosol-induced impact on planetary boundary layer based on lidar and sunphotometer in Beijing

Characterization and sources of water-soluble inorganic ions during sulfate-driven and nitrate-driven haze on the largest loess accumulation plateau

With the rapid reduction of anthropogenic SO2 emissions, the critical driver of haze in China has shifted from being dominated by sulfate to alternating sulfate and nitrate. Haze induced by different driver species may differ in the chemical forms of water-soluble inorganic ions (WSIIs). The unique topography and high-emission industrial agglomeration of the Loess Plateau determine its severe local PM2.5 pollution and influence global weather patterns through the outward export of pollutants. PM2.5 samples were conducted in Pingyao, on the eastern Loess Plateau of China, in autumn and winter. The average mass of PM2.5 was 88.82 ± 57.37 μg/m3; sulfate, nitrate, and ammonium were the dominant component. The chemical form of the ion was dominated by (NH4)2SO4, NH4NO3, NaNO3 and KNO3 during the nitrate-driven (ND) haze, while (NH4)2SO4, NH4HSO4, NH4NO3, NaNO3 and KNO3 were predominant species during the sulfate-driven (SD) haze. Heterogeneous oxidation reactions dominated the mechanism of sulfate formation. Primary sulfate emissions or other generation pathways contributed to sulfate formation during the SD haze. The gas-phase homogeneous reaction of NO2 and NH3 dominates the nitrate generation during the ND haze. The heterogeneous reactions also played an essential role during the SD haze. Nitrate aerosol (42.30%) and coal and biomass combustion (23.23%) were the dominant sources of WSIIs during the ND haze. In comparison, nitrate aerosol (31.80%) and sulfate aerosol (25.08%) were considered the primary control direction during the SD haze. The chemical characteristics and sources of aerosols under various types of haze differ significantly, and knowledge gained from this investigation provides insight into the causes of heavy haze.

Spatiotemporal variations and sources of PM2.5 in the Central Plains Urban Agglomeration, China

The Central Plains Urban Agglomeration (CPUA) is the largest region in central China and suffers from serious air pollution. To reveal the spatiotemporal variations and the sources of fine particulate matter (PM_2.5, with an aerodynamic diameter of smaller than 2.5 μm) concentrations of CPUA, multiple and transdisciplinary methods were used to analyse the collected millions of PM_2.5 concentration data. The results showed that during 2017 ~ 2020, the yearly mean concentrations of PM_2.5 for CPUA were 68.3, 61.5, 58.7, and 51.5 μg/m³, respectively. The empirical orthogonal function (EOF) analysis suggested that high PM_2.5 pollution mainly occurred in winter (100.8 μg/m³, 4-year average). The diurnal change in PM_2.5 concentrations varied slightly over the season. The centroid of the PM_2.5 concentration moved towards the west over time. The spatial autocorrelation analysis indicated that PM_2.5 concentrations exhibited a positive spatial autocorrelation in CPUA. The most polluted cities distributed in the northern CPUA (Handan was the centre) formed a high-high agglomeration, and the cities located in the southern CPUA (Xinyang was the centre) formed a low-low agglomeration. The backward trajectory model and potential source contribution function were employed to discuss the regional transportation of PM_2.5. The results demonstrated that internal-region and cross-regional transport of anthropogenic emissions were all important to PM_2.5 pollution of CPUA. Our study suggests that joint efforts across cities and regions are necessary.

Simultaneous Extraction of Planetary Boundary-Layer Height and Aerosol Optical Properties from Coherent Doppler Wind Lidar

Planetary boundary-layer height is an important physical quantity for weather forecasting models and atmosphere environment assessment. A method of simultaneously extracting the surface-layer height (SLH), mixed-layer height (MLH), and aerosol optical properties, which include aerosol extinction coefficient (AEC) and aerosol optical depth (AOD), based on the signal-to-noise ratio (SNR) of the same coherent Doppler wind lidar (CDWL) is proposed. The method employs wavelet covariance transform to locate the SLH and MLH using the local maximum positions and an automatic algorithm of dilation operation. AEC and AOD are determined by the fitting curve using the SNR equation. Furthermore, the method demonstrates the influential mechanism of optical properties on the SLH and MLH. MLH is linearly correlated with AEC and AOD because of solar heating increasing. The results were verified by the data of an ocean island site in China.

Impact of Wildfires on Meteorology and Air Quality (PM2.5 and O3) over Western United States during September 2017

In this study, we investigated the impact of wildfires on meteorology and air quality (PM2.5 and O3) over the western United States during the September 2017 period. This is done by using Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate scenarios with wildfires (base case) and without wildfires (sensitivity case). Our analysis performed during the first half of September 2017 (when wildfire activity was more intense) reveals a reduction in modelled daytime average shortwave surface downward radiation especially in locations close to wildfires by up to 50 W m−2, thus resulting in the reduction of the diurnal average surface temperature by up to 0.5 °C and the planetary boundary layer height by up to 50 m. These changes are mainly attributed to aerosol-meteorology feedbacks that affect radiation and clouds. The model results also show mostly enhancements for diurnally averaged cloud optical depth (COD) by up to 10 units in the northern domain due to the wildfire-related air quality. These changes occur mostly in response to aerosol–cloud interactions. Analysis of the impact of wildfires on chemical species shows large changes in daily mean PM2.5 concentrations (exceeding by 200 μg m−3 in locations close to wildfires). The 24 h average surface ozone mixing ratios also increase in response to wildfires by up to 15 ppbv. The results show that the changes in PM2.5 and ozone occur not just due to wildfire emissions directly but also in response to changes in meteorology, indicating the importance of including aerosol-meteorology feedbacks, especially during poor air quality events.

A full-coverage estimation of PM2.5 concentrations using a hybrid XGBoost-WD model and WRF-simulated meteorological fields in the Yangtze River Delta Urban Agglomeration, China

In spite of the state-of-the-art performances of machine learning in the PM_2.5 estimation, the high-value PM_2.5 underestimation and non-random aerosol optical depth (AOD) missing are still huge obstacles. By incorporating wavelet decomposition (WD) into the extreme gradient boosting (XGBoost), a hybrid XGBoost-WD model was established to obtain the full-coverage PM_2.5 estimation at 3-km spatial resolution in the Yangtze River Delta Urban Agglomeration (YRDUA). In this study, 3-km-resolution meteorological fields simulated by WRF along with AOD derived from Moderate Resolution Imaging Spectroradiometer (MODIS) were served as explanatory variables. Model MW and Model NW were developed using XGBoost-WD for the areas with and without AOD respectively to obtain a full-coverage PM_2.5 mapping in the YRDUA. The XGBoost-WD model showed good performances in estimating PM_2.5 with R² of 0.80 in the Model MW and 0.87 in the Model NW. Moreover, the K-value of Model MW increased from 0.77 to 0.79 and that of Model NM increased from 0.81 to 0.86 compared with the model without the step of WD, indicating an improvement on the problem of PM_2.5 underestimation. Due to a better ability of capturing abrupt changes in the PM_2.5 concentrations, the spatial evolution of PM_2.5 during a typical pollution event could be mapped more accurately. Finally, the analysis of variable importance showed that the three most important variables in the estimation of the low-frequency coefficients of PM_2.5 (PM_2.5_A4) were temperature at 2 m (T2), day of year (DOY) and longitude (LON), while that in the high-frequency coefficients of PM_2.5 (PM_2.5_D) were CO, AOD and NO₂. This study not only provided an effective solution to the PM_2.5 underestimation and AOD missing problems in the PM_2.5 estimation, but also proposed a new method to further refine the sophisticated correlations between PM_2.5 and some spatiotemporal variables.

Variations in Nocturnal Residual Layer Height and Its Effects on Surface PM2.5 over Wuhan, China

Large amounts of aerosols remain in the residual layer (RL) after sunset, which may be the source of the next day’s pollutants. However, the characteristics of the nocturnal residual layer height (RLH) and its effect on urban environment pollution are unknown. In this study, the characteristics of the RLH and its effect on fine particles with diameters <2.5 μm (PM2.5) were investigated using lidar data from January 2017 to December 2019. The results show that the RLH is highest in summer (1.55 ± 0.55 km), followed by spring (1.40 ± 0.58 km) and autumn (1.26 ± 0.47 km), and is lowest in winter (1.11 ± 0.44 km). The effect of surface meteorological factors on the RLH were also studied. The correlation coefficients (R) between the RLH and the temperature, relative humidity, wind speed, and pressure were 0.38, −0.18, 0.15, and −0.36, respectively. The results indicate that the surface meteorological parameters exhibit a slight correlation with the RLH, but the high relative humidity was accompanied by a low RLH and high PM2.5 concentrations. Finally, the influence of the RLH on PM2.5 was discussed under different aerosol-loading periods. The aerosol optical depth (AOD) was employed to represent the total amount of pollutants. The results show that the RLH has an effect on PM2.5 when the AOD is small but has almost no effect on PM2.5 when the AOD is high. In addition, the R between the nighttime mean RLH and the following daytime PM2.5 at low AOD is −0.49, suggesting that the RLH may affect the following daytime surface PM2.5. The results of this study have a guiding significance for understanding the interaction between aerosols and the boundary layer.

Synergistic effect of glutaric acid and ammonia/amine/amide on their hydrates in the clustering: A theoretical study

The formation of molecular clusters makes influence on the atmosphere. The clusters of glutaric acid (GA) and common ammonia (A), amine (methylamine MA, dimethylamine DMA) and representative amide (urea U) along with water molecule were systematically studied theoretically. GA-A-nW (n = 1, 2), GA-MA-nW (n = 1, 2), GA-DMA-1W and GA-U-nW (n = 1-6) are predicted to be feasible thermodynamically with the hydrogen bonds as interaction force. GA and urea promote the clustering synergistically, and ammonia, methylamine, dimethylamine promote the clustering of small GA hydrates (n = 1-2), while inhibit that of large GA hydrates (n = 3-6). The results of humidity show that un-hydrate or mono-hydrate is the main form of GA-mbase-nW (m = 0, 1; n = 1-6) under relative humidity of 20%, 50% and 80%. The global minima remain dominant over the temperature range of 220-320 K. GA contributes more to the Rayleigh scattering properties than sulfuric acid. More importantly, the local minima can undergo isomerization to form the global minima crossing a free energy barrier ranging from 6.66 to 11.78 kcal mol^-1. This study indicates that GA and base molecules play a synergistic role to promote the formation of clusters. We hope it can provide more insights on interesting clustering in theory.

Observations of Atmospheric Aerosol and Cloud Using a Polarized Micropulse Lidar in Xi’an, China

A polarized micropulse lidar (P-MPL) employing a pulsed laser at 532 nm was developed by the Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences). The optomechanical structure, technical parameters, detection principle, overlap factor calculation method, and inversion methods of the atmospheric boundary layer (ABL) depth and depolarization ratio (DR) were introduced. Continuous observations using the P-MPL were carried out at Xi’an Meteorological Bureau, and the observation data were analyzed. In this study, we gleaned much information on aerosols and clouds, including the temporal and spatial variation of aerosols and clouds, aerosol extinction coefficient, DR, and the structure of ABL were obtained by the P-MPL. The variation of aerosols and clouds before and after a short rainfall was analyzed by combining time-height-indication (THI) of range corrected signal (RCS) and DR was obtained by the P-MPL with profiles of potential temperature (PT) and relative humidity (RH) detected by GTS1 Digital Radiosonde. Then, the characteristics of tropopause cirrus cloud were discussed using the data of DR, PT, and RH. Finally, a haze process from January 1st to January 5th was studied by using aerosol extinction coefficients obtained by the P-MPL, PT, and RH profiles measured by GTS1 Digital Radiosonde and the time-varying of PM2.5 and PM10 observed by ambient air quality monitor. The source of the haze was simulated by using the NOAA HYSPLIT Trajectory Model.

Chemical formation and source apportionment of PM2.5 at an urban site at the southern foot of the Taihang mountains

The region along the Taihang Mountains in the North China Plain (NCP) is characterized by serious fine particle pollution. To clarify the formation mechanism and controlling factors, an observational study was conducted to investigate the physical and chemical properties of the fine particulate matter in Jiaozuo city, China. Mass concentrations of the water-soluble ions (WSIs) in PM_2.5 and gaseous pollutant precursors were measured on an hourly basis from December 1, 2017, to February 27, 2018. The positive matrix factorization (PMF) method and the FLEXible PARTicle (FLEXPART) model were employed to identify the sources of PM_2.5. The results showed that the average mass concentration of PM_2.5 was 111 μg/m³ during the observation period. Among the major WSIs, sulfate, nitrate, and ammonium (SNA) constituted 62% of the total PM_2.5 mass, and NO₃^- ranked the highest with an average contribution of 24.6%. NH₄⁺ was abundant in most cases in Jiaozuo. According to chemical balance analysis, SO₄^2-, NO₃^-, and Cl^- might be present in the form of (NH₄)₂SO₄, NH₄NO₃, NH₄Cl, and KCl. The liquid-phase oxidation of SO₂ and NO₂ was severe during the haze period. The relative humidity and pH were the key factors influencing SO₄^2- formation. We found that NO₃^- mainly stemmed from homogeneous gas-phase reactions in the daytime and originated from the hydrolysis of N₂O₅ in the nighttime, which was inconsistent with previous studies. The PMF model identified five sources of PM_2.5: secondary origin (37.8%), vehicular emissions (34.7%), biomass burning (11.5%), coal combustion (9.4%), and crustal dust (6.6%).

Effect of urban underlying surface on PM2.5 vertical distribution based on UAV in Xi'an, China

Fine particulate matter (PM_2.5) has become a significant issue of ecological environment. However, few studies have explored the vertical distribution of PM_2.5 in cities. The objectives of this paper are to reveal the vertical distribution regular pattern of PM_2.5 over urban underlying surfaces near the ground with a hexacopter-type unmanned aerial vehicle (UAV) in winter. Results showed that the maximum vertical gradient of PM_2.5 near the ground was typically the greatest in the morning as the stable atmospheric conditions. Moreover, regression model illustrated that relative humidity had the greatest impact on the vertical profile of PM_2.5 compared to air temperature and altitude as hygroscopic of PM_2.5 aerosols. Curve model shown that vertical profile of PM_2.5 over the surfaces of water and green space first increased slowly and then declined, besides, the highest concentration inflection of PM_2.5 above the water body (23.7 m) is higher than the green space (14.3 m). Thus, suggesting residents living vertical of 10-30 m from the ground around large water bodies and green spaces should not open windows for ventilation in the morning. Therefore, this study provides insights into the vertical distributions of PM_2.5 over different underlying surfaces and should be of reference value to urban planners for designing urban spaces to optimize atmosphere environment to provide a healthy living environment.

Using a coupled LES aerosol-radiation model to investigate the importance of aerosol-boundary layer feedback in a Beijing haze episode

Haze episodes, characterised by extremely high aerosol concentrations and a reduction in visibility to less than 10 km, are a frequent occurrence in wintertime Beijing, despite policy interventions leading to an overall improvement in average annual air quality. The main drivers in the onset of haze episodes in wintertime Beijing are changing synoptic conditions, however, aerosol-radiation interactions and their feedback on boundary layer meteorology are thought to play an essential role in the intensity and longevity of haze episodes. In this study we use a coupled LES aerosol-radiation model (UCLALES-SALSA), which we have recently configured for the urban environment of Beijing. The model's high resolution and control over meteorological and aerosol conditions as well as atmospheric processes means we can directly elucidate and quantify the importance of specific aspects of the aerosol-radiation-meteorology feedback in the cumulative stage of Beijing haze. The main results presented here show (a) synoptic scale meteorology has a larger impact on boundary layer suppression than high aerosol concentrations and (b) unlike previous results obtained using regional models or observationally driven analyses, there is no threshold value at which the aerosol-radiation-meteorology feedback has a significant effect on PBL height. Rather, our work shows that for the aerosol composition in this case study, the role of the feedback effect in reducing PBL height increases under shallow boundary layer conditions and with increasing pollution loading in an almost linear fashion. This lack of a threshold found for our case study has important policy implications since interventions based on such a value will not result in large reductions associated with turning off the feedback process. Furthermore, this work directly shows that although the right synoptic changes are a prerequisite for pollution episodes in Beijing, local and regional emissions drive increases in aerosol load that are sufficient to initiate the aerosol feedback loop. This further drives suppression of the boundary layer top and promotes stagnation of air and increased stability, which can be self-sustaining. This results in higher surface aerosol concentrations for extended periods of time, with severe consequences for human health [Lv et al., Atmos. Environ., 2016, 124, 98-108; Wang et al., Atmos. Chem. Phys., 2019, 19(10), 6949-6967].

Impact of wildfire on particulate matter in the southeastern United States in November 2016

In November 2016, a large area of wildfire occurred in the southeastern United States, concomitant with the occurrence of severe drought during the same period. Whereas the previous studies on biomass burning over this region mainly focused on the prescribed fire, this study investigated the impact of wildfire using the two-way-coupled Weather Research and Forecasting model and Community Multiscale Air Quality model. Two episodic wildfire burning events (November 6 to 9 and November 13 to 16, 2016) were selected, and the mean contribution to fine particulate matter (PM_2.5) in the southeastern United States from wildfires reached 9.6 to 42.5 μg m^-3 and 10.9 to 26.1 μg m^-3, with mean relative contributions of 41% and 49%, respectively, during these two events. The effect of wildfire propagates along the path of the smoke plume, which is determined by the wind speed and direction. For instance, during the first event, the dominant low-altitude wind vector displayed an anticyclonic-type flow with low wind speed, resulting in relatively localized influence and high intensity. In contrast, during the second event, relatively fast eastward wind, particularly over the latter part of the event, strengthened the diffusion and affected larger areas in comparison with the first event. Moreover, differently from the previous studies, this study took a further step to reveal the mechanism of the aerosol direct effect on the deterioration of air quality during wildfire, mainly through the modulation of reduction in surface downward shortwave radiation, planetary boundary layer height and wind speed, subsequently, facilitating pollution accumulation. Quantification analysis showed an average of 10% to 14% extra enhancement of PM_2.5 during the November 6 to 8 episode. Considering that more frequent drought is projected to occur in the southeastern United States, wildfire may play an even more important role in modulating the air quality in this region.