Lower Planetary Boundary Layer Research Articles

Investigation of NOx and related secondary pollutants at Anand Vihar, one of the most polluted area of Delhi

This research investigates the influence of meteorological parameters on NOx concentrations, particularly NO2, and related secondary & primary pollutants at the Anand Vihar interstate bus terminal in Delhi. Statistical analysis of long-term data (2016–2021) examines seasonal, weekly, and daily variations in NOx and other pollutants. Temperature and relative humidity show a significant impact on NO2 levels. Seasonal patterns reveal lower concentrations during the monsoon season and higher concentrations in winter and post-monsoon periods, except for ozone. The year 2018 stands out as the most polluted for NO2. Vehicular activities directly influence pollution, evident through reduced NO2 and benzene levels during the COVID-19 lockdown. The Planetary Boundary Layer (PBL) height plays a critical role, with lower PBL heights associated with increased NO2 concentrations. Electric Vehicles (EVs) have a positive effect on reducing NO2 pollution. Comparison with a less transportation-impacted site highlights higher NO2 concentrations in areas with heavy vehicular traffic, emphasizing the need for pollution control measures and sustainable transportation. Correlation and regression analyses confirm the interdependence between PM and NO emissions, underscoring the significance of addressing vehicular emissions for effective pollution mitigation. This study provides valuable insights into the intricate relationship between meteorological parameters, vehicular emissions, and NOx concentrations.

Response of organic aerosol to Delhi's pollution control measures over the period 2011–2018

Some of the world's highest air pollution episodes occur in Delhi, India and studies have shown particulate matter (PM) is the leading air pollutant to cause adverse health effects on Delhi's population. It is therefore vital to chart sources of PM over long time periods to effectively identify trends, particularly as multiple air quality mitigation measures have been implemented in Delhi over the past 10 years but remain unevaluated. An automated offline aerosol mass spectrometry (AMS) method has been developed which has enabled high-throughput analysis of PM filters. This novel offline-AMS method uses an organic solvent mix of acetone and water to deliver high extraction recoveries of organic aerosol (OA) (95.4 ± 8.3%). Positive matrix factorisation (PMF) source apportionment was performed on the OA fraction extracted from PM10 filter samples collected in Delhi in 2011, 2015 and 2018 to provide snapshots of the responses of OA to changes in sources in Delhi. The nine factors of OA resolved by PMF group into four primary source categories: traffic, cooking, coal-combustion and burning-related (solid fuel or open burning). Burning-related OA made the largest contribution during the winter and post-monsoon, when total OA concentrations were at their highest. Annual mean burning-related OA concentrations declined by 47% between 2015 and 2018, likely associated with the 2015 ban on open waste burning and controls and incentives to reduce crop-residue burning. Compositional analysis of OA factors shows municipal waste burning tracers still present in 2018, indicating further scope to reduce burning-related OA. The closure of the two coal power stations, along with initiatives to decrease coal use in industry, businesses, and residential homes, resulted in a significant decrease (87%) in coal-combustion OA. This corresponds to a 17% reduction in total OA, which shows the effectiveness of these measures in reducing PM10. Increases in traffic OA appear to have been offset by the introduction of the Bharat stage emissions standards for vehicles as the increases do not reflect the rapid increase in registered vehicles. However, daytime restrictions on heavy goods vehicles (HGVs) entering the city is linked to large increases in PM10 during the winter and post-monsoon, likely because the large influx of diesel-engine HGVs during the early mornings and evenings is timed with a particularly low planetary boundary layer height that enhances surface concentrations.

The Effects of Planetary Boundary Layer Features on Air Pollution Based on ERA5 Data in East China

The planetary boundary layer (PBL) structure and its evolution can significantly affect air pollution. Here, the PBL’s characteristics and their association with air pollution were analyzed in Hefei, east China, using ERA5 reanalysis data, weather observations and air pollutant measurements from 2016 to 2021. In the near-surface level, air pollution was directly influenced by ground meteorological conditions, and high PM2.5 was normally related to weak wind speed, northwest wind anomalies, low temperature and high relative humidity. Moreover, in the trajectory analysis, air masses from the north and the northwest with short length played an important role in the high PM2.5 with pollutant transport within the PBL. Furthermore, high PM2.5 showed a tight dependence on PBL stratification. There was high temperature and relative humidity and low wind speed and PBL height within all PBL altitudes in the polluted condition. Notably, vertical wind shear (VWS) and temperature gradient tended to be much weaker below 900 hPa, which created a deeply stable stratification that acted as a cap to upward-moving air. Such a PBL structure facilitated more stable stratification and enhanced the generation of air pollution. Finally, the stable stratification in the PBL was related to the special synoptic configuration for the high PM2.5 conditions, which included the block situation at the high level, the southerly wind anomalies at the middle level and the wild range of the uniform pressure field at the near-ground level. Therefore, air pollutant concentrations were regulated by ground factors, PBL structure and the synoptic situation. Our results provide a precise understanding of the role of PBL features in air pollution, which contributes to improving the assimilation method of the atmospheric chemistry model in east China.

An urban air quality assessment based on a meteorological perspective.

An integrated approach to understanding all measured pollutants with multi-discipline in different time scales and understanding the mechanisms hidden under low air quality (AQ) conditions is essential for tackling potential air pollution issues. In this study, the air pollution of Sivas province was analyzed with meteorological and PM2.5 data over six years to assess the city's AQ in terms of PM2.5 pollution and analyze the effect of meteorological factors on it. It was found that the winter period (January-February-November-December) of every year except 2019-which has missing data-is the period with the highest air pollution in the province. In addition, the days exceeding the daily PM2.5 limit values in 2016, 2017, 2020, and 2021 were also seen in the spring and summer months, which inclined the study to focus on additional pollutant sources such as long-range dust transport and road vehicles. The year 2017 has the highest values and was analyzed in detail. Pollution periods with the most increased episodes in 2018 were analyzed with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Dust Regional Atmospheric Model (DREAM) models. As a result of the study, the average PM2.5 values in 2017 were 31.66 ± 19.2µg/m3 and a correlation of -0.49 between temperature and PM2.5. As a result of model outputs, it was found that the inversion is intensely observed in the province, which is associated with an increase of PM2.5 during the episodes. Dust transport from northwestern Iraq and northeastern Syria is observed, especially on days with daily average PM2.5 values above 100µg/m3. Additionally, planetary boundary layer (PBL) data analysis with PM pollution revealed a significant negative correlation (r = -0.61). Air pollutants, particularly PM2.5, were found to be higher during lower PBL levels.

Using the COVID-19 lockdown to identify atmospheric processes and meteorology influences on regional PM2.5 pollution episodes in the Beijing-Tianjin-Hebei, China

A major tool for curtailing the spread of COVID-19 pandemic in China was a nationwide lockdown implemented by the Chinese authorities, which also led to significant reductions in anthropogenic emissions and fine particulate matter (PM2.5) concentrations. However, the lockdown measures did not prevent high PM2.5 pollution episodes (EPs). Three severe EPs were identified in the Beijing-Tianjin-Hebei (BTH) region during the lockdown. The integrated process rate (IPR) analysis tool in the Community Multiscale Air Quality (CMAQ) model was employed to identify and quantify the contributions of individual atmospheric processes to PM2.5 formation during the EPs in four representative cities (Beijing, Tianjin, Shijiazhuang, and Baoding) of the BTH. The influence of meteorological conditions on the accumulation and dispersion of PM2.5 during the EPs was also elucidated. The results of the IPR showed that emissions and aerosol processes were the dominant sources of net surface PM2.5 in Beijing and Tianjin, constituting a total of 86.2% and 92.9%, respectively, while emissions, horizontal transport, and aerosol processes dominated the net surface PM2.5 formation in Shijiazhuang and Baoding. In addition, the three pollution episodes in Beijing and Tianjin were primarily driven by local emissions, while the pollution events in Shijiazhuang and Baoding were attributed to the combined local emissions and regional transport. Also, the EPs were driven by low planetary boundary layer heights, low vertical export of PM2.5 from the boundary layer to the free troposphere, and substantial horizontal import, especially in Shijiazhuang and Baoding. Furthermore, the elevated PM2.5 concentrations during the EPs were greatly enhanced by unfavorable meteorological conditions, with the first two EPs being characterized with low ventilation coefficient (VC) values in the four representative cities. This study improves the understanding of buildup of PM2.5 during the pollution episodes, and the results provide insights for designing more effective emissions control strategies to mitigate future PM2.5 pollution episodes.

Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework

Abstract. The transport of water, heat, and momentum from the surface to the atmosphere is dependent, in part, on the characteristics of the land surface. Along with the model physics, parameterization schemes, and parameters employed, land datasets determine the spatial variability in land surface states (i.e., soil moisture and temperature) and fluxes. Despite the importance of these datasets, they are often chosen out of convenience or owing to regional limitations, without due assessment of their impacts on model results. Irrigation is an anthropogenic form of land heterogeneity that has been shown to alter the land surface energy balance, ambient weather, and local circulations. As such, irrigation schemes are becoming more prevalent in weather and climate models, with rapid developments in dataset availability and parameterization scheme complexity. Thus, to address pragmatic issues related to modeling irrigation, this study uses a high-resolution, regional coupled modeling system to investigate the impacts of irrigation dataset selection on land–atmosphere (L–A) coupling using a case study from the Great Plains Irrigation Experiment (GRAINEX) field campaign. The simulations are assessed in the context of irrigated vs. nonirrigated regions, subregions across the irrigation gradient, and sub-grid-scale process representation in coarser-scale models. The results show that L–A coupling is sensitive to the choice of irrigation dataset and resolution and that the irrigation impact on surface fluxes and near-surface meteorology can be dominant, conditioned on the details of the irrigation map (e.g., boundaries and heterogeneity), or minimal. A consistent finding across several analyses was that even a low percentage of irrigation fraction (i.e., 4 %–16 %) can have significant local and downstream atmospheric impacts (e.g., lower planetary boundary layer, PBL, height), suggesting that the representation of boundaries and heterogeneous areas within irrigated regions is particularly important for the modeling of irrigation impacts on the atmosphere in this model. When viewing the simulations presented here as a proxy for “ideal” tiling in an Earth-system-model-scale grid box, the results show that some “tiles” will reach critical nonlinear moisture and PBL thresholds that could be important for clouds and convection, implying that heterogeneity resulting from irrigation should be taken into consideration in new sub-grid L–A exchange parameterizations.

Significantly mitigating PM2.5 pollution level via reduction of NOx emission during wintertime

Despite considerable decreases in fine particulate matter (PM2.5) in Chinese megacities over the past decade, many second- and third-tier cities that distribute abundant industrial enterprises are still facing great challenges for PM2.5 further reduction under the recent policy background of eliminating heavily-polluted weather. In view of core effects of NOx on PM2.5, the deeper reductions of NOx in these cities are expected to break the plateau of PM2.5 decline, however, the link between NOx emission and PM2.5 mass loading is currently lacking. Herein, we progressively construct an evaluation system for PM2.5 productions based on daily NOx emissions in a typical industrial city (Jiyuan), considering a sequence of nested parameters involving evolutions of NO2 into nitric acid and then nitrate, and contributions of nitrate to PM2.5. The evaluation system was subsequently validated to better reproduce real increasing processes for PM2.5 pollution based on 19 pollution cases, with root mean square errors of 19.2 ± 16.4 %, suggesting the feasibility of developing NOx emission indicators linked to goals of mitigating atmospheric PM2.5. Additionally, further comparative results reveal that currently high NOx emissions in this industrial city severely hinder the achievement of atmospheric PM2.5 environmental capacity targets, especially in the scenarios of high initial PM2.5 level, low planetary boundary layer height and long pollution duration. It is anticipated that these methodologies and findings would supply guidelines for further regional PM2.5 mitigation, in which source-oriented NOx indicators could also provide some orientations for industrial cleaner production such as denitrification and low nitrogen combustion.

The influence of different parameterizations on diurnal cycle of land precipitation in CAS-ESM

The impacts of physical parameterizations on the diurnal cycle of precipitation (DCP) over land are investigated by comparing long-term simulations of the Chinese Academy of Sciences Earth System Model (CAS-ESM). Significant improvements in the DCP occur when the model replaces the Community Atmosphere Model version 4 (CAM4) physics package with the CAM5 package at both global and regional scales. Globally, the reduced amplitudes and delayed phases of DCP with the CAM5 package can be explained by the diurnal variations in convective available potential energy (CAPE). Regionally, the improvements in the DCP are caused by the decreased daytime convergence at 850 hPa, smaller vertically integrated water vapor transport, weakened vertical velocity, and smaller stratus cloud liquid water amount simulated by the CAM5 package. Besides, CAS-ESM with the CAM5 package produces the decreased amplitudes and delayed phases of the diurnal variation of the convective cloud, which is closely related to the planetary boundary layer (PBL) processes. CAS-ESM with the CAM5 package exhibits a significantly lower PBL height than with the CAM4 package for both direct model outputs and estimates with the bulk Richardson number method. The peaks of lifting condensation level (LCL) deficit (difference between PBL height and LCL height) occur later (∼1–3 h) and are lower with the CAM5 package than with the CAM4 package. Consequently, CAS-ESM with the CAM5 package decreases the probability of cloud formation and produces more realistic DCP. This study underscores the importance of PBL schemes to the simulated convective clouds and DCP.

Dust-planetary boundary layer interactions amplified by entrainment and advections

Mineral dust contributes to more than half of the global aerosol loading. However, the radiative impacts of dust aerosols on planetary boundary layer (PBL) structure have not been explored sufficiently. During a typical dust storm event over Tarim Basin, dust aerosols exhibit a well-mixed distribution during the daytime in spite of a shallow layer of dust particles accumulated at higher altitudes. By contrast, nocturnal dust plumes are located near the surface due to stable stratification. We demonstrate that these differentiated vertical distributions determine the spatial heterogeneity of dust loading, radiative fluxes and PBL height variations. Dust aerosols cause daytime PBL suppression and nighttime PBL promotion through modulating surface and atmospheric radiative budgets. Specifically, dust-induced cooling effect within PBL directly inhibits the daytime PBL development. PBL suppression effect is then amplified by entrainment processes resulting in excessively low PBL height, especially for dust particles below but near the PBL top. Dust plumes weaken updrafts from PBL and downdrafts of the free atmosphere, which further reduce the entrainment mixing through attenuating horizontal and vertical advection, and eventually amplify PBL suppression. At night, near-surface dust aerosols stimulate a warm and unstable lower atmosphere, generate warm advection heating and promote the PBL development. Our study highlights the importance of specifying entrainment parameters and nighttime advection activities in quantifying the dust-PBL interactions.

Modulation of Wintertime Canopy Urban Heat Island (CUHI) Intensity in Beijing by Synoptic Weather Pattern in Planetary Boundary Layer

AbstractStudying the spatiotemporal variations of the urban heat island (UHI) effect and its cause is important towards understanding urban climate change, planning and green development, and disaster mitigation. In this paper, by using surface observations and reanalysis data with objective classification of synoptic weather patterns (SWPs), we analyze the associations between canopy UHI intensity (CUHI) and SWPs in the planetary boundary layer (PBL) and their potential drivers during wintertime of the period 2012–2017. Six dominant types of SWP are identified as follows: In the case of Types 3, 4, and 6, weak high‐pressure systems exist to the south of Beijing, resulting in weak southerly winds with low PBL height, large cloud coverage and high relative humidity (RH). These conditions are generally conducive to a strengthening of the CUHII. In contrast, under Types 1, 2, and 5, high‐pressure systems are located to the northwest of Beijing, and the associated strong northwesterly flows of dry and cold air strengthen the boundary layer mixing process, resulting in large wind speed and low RH. This is conducive to a weakening of the CUHII. In general, our work reveals the impacts of SWPs on the strength of CUHII mainly via the modulation of local weather conditions at diurnal and interannual scales, while spatial pattern of CUHII is largely dominated by local climate zones. Our findings have implications for CUHII forecasts, as well as impact assessments and policymaking in the context of UHI‐related energy conservation in winter over high‐density urban areas on the synoptic scale.

Surface and aloft NO2 pollution over the greater Tokyo area observed by ground-based and MAX-DOAS measurements bridged by kilometer-scale regional air quality modeling

To advance our understanding of surface and aloft nitrogen dioxide (NO2) pollution, this study extensively evaluated NO2 concentrations simulated by the regional air quality modeling system with a 1.3 km horizontal grid resolution using the Atmospheric Environmental Regional Observation System ground-based observation network and aloft measurements by multi-axis differential optical absorption spectroscopy (MAX-DOAS) over the greater Tokyo area. Observations are usually limited to the surface level, and gaps remain in our understanding of the behavior of air pollutants above the near-surface layer, particularly within the planetary boundary layer (PBL). Therefore, MAX-DOAS measurement was used, which observes scattered sunlight in the ultraviolet/visible range at several elevation angles between the horizon and zenith to determine the aloft NO2 pollution averaged over 0–1 km. In total, four MAX-DOAS measurement systems at Chiba University (35.63°N, 140.10°E) systematically covered the north, east, west, and south directions to capture the aloft NO2 pollution over the greater Tokyo area. The target period was Chiba-Campaign 2015 conducted during 9–23 November 2015. The evaluations showed that the air quality modeling system can generally capture the observed behavior of both surface and aloft NO2 pollution in terms of spatial and temporal coverage. The diurnal variation, which typically showed an increase from evening to early morning without daylight and a decrease during the daytime, was also captured by the model. During Chiba-Campaign 2015, two cases of episodic higher NO2 concentration were identified: one during the nighttime and another during the daytime as different diurnal patterns. These were related to a stagnant wind field, with the latter also connected to a lower PBL height in cloudy conditions. Comparison of the modeled daily-averaged surface and aloft NO2 concentrations showed that aloft NO2 concentration exhibited a strong linear correlation with surface NO2 concentration, with the aloft (0–1 km) value scaled to 0.4–0.5-fold the surface value, irrespective of whether the day was clean or polluted. This scaling value was lower during the nighttime and higher during the daytime. Based on this synergetic analysis of surface and aloft observation bridged by a kilometer-scale fine-resolution modeling simulation, this study contributes to fostering understanding of aloft NO2 pollution.

Planetary Boundary Layer Height Modulates Aerosol—Water Vapor Interactions During Winter in the Megacity of Delhi

AbstractThe Indo‐Gangetic Plain (IGP) is one of the dominant sources of air pollution worldwide. During winter, the variations in planetary boundary layer (PBL) height, driven by a strong radiative thermal inversion, affect the regional air pollution dispersion. To date, measurements of aerosol‐water vapor interactions, especially cloud condensation nuclei (CCN) activity, are limited in the Indian subcontinent, causing large uncertainties in radiative forcing estimates of aerosol‐cloud interactions. We present the results of a one‐month field campaign (February‐March 2018) in the megacity, Delhi, a significant polluter in the IGP. We measured the composition of fine particulate matter (PM1) and size‐resolved CCN properties over a wide range of water vapor supersaturations. The analysis includes PBL modeling, backward trajectories, receptor models and fire spots to elucidate the influence of PBL and air mass origins on aerosols. The aerosol properties depended strongly on PBL height and a simple power‐law fit could parameterize the observed correlations of PM1 mass, aerosol particle number and CCN number with PBL height, indicating PBL induced changes in aerosol accumulation. The low inorganic mass fractions, low aerosol hygroscopicity and high externally mixed weakly CCN‐active particles under low PBL height (100 m) indicated the influence of PBL on aerosol aging processes. In contrast, aerosol properties did not depend strongly on air mass origins or wind direction, implying that the observed aerosol and CCN are from local emissions. An error function could parameterize the relationship between CCN number and supersaturation throughout the campaign.

Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM<sub>2.5</sub>): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations

Abstract. Geostationary satellite measurements of aerosol optical depth (AOD) over East Asia from the Geostationary Ocean Color Imager (GOCI) and Advanced Himawari Imager (AHI) instruments can augment surface monitoring of fine particulate matter (PM2.5) air quality, but this requires better understanding of the AOD–PM2.5 relationship. Here we use the GEOS-Chem chemical transport model to analyze the critical variables determining the AOD–PM2.5 relationship over East Asia by simulation of observations from satellite, aircraft, and ground-based datasets. This includes the detailed vertical aerosol profiling over South Korea from the KORUS-AQ aircraft campaign (May–June 2016) with concurrent ground-based PM2.5 composition, PM10, and AERONET AOD measurements. The KORUS-AQ data show that 550 nm AOD is mainly contributed by sulfate–nitrate–ammonium (SNA) and organic aerosols in the planetary boundary layer (PBL), despite large dust concentrations in the free troposphere, reflecting the optically effective size and high hygroscopicity of the PBL aerosols. We updated SNA and organic aerosol size distributions in GEOS-Chem to represent aerosol optical properties over East Asia by using in situ measurements of particle size distributions from KORUS-AQ. We find that SNA and organic aerosols over East Asia have larger size (number median radius of 0.11 µm with geometric standard deviation of 1.4) and 20 % larger mass extinction efficiency as compared to aerosols over North America (default setting in GEOS-Chem). Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM2.5 nitrate. The GOCI–AHI AOD data over East Asia in different seasons show agreement with AERONET AODs and a spatial distribution consistent with surface PM2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM2.5. This is due to low PBL depths compounded by high residential coal emissions in winter and high relative humidity (RH) in summer. Seasonality of AOD and PM2.5 over South Korea is much weaker, reflecting weaker variation in PBL depth and lack of residential coal emissions.

Characterizing vertical distribution patterns of PM2.5 in low troposphere of Shanghai city, China: Implications from the perspective of unmanned aerial vehicle observations

The vertical distribution patterns of PM2.5 (particulate matters with diameters ≤2.5 μm) are crucial for understanding the aggregation, dispersion, and regional transport of PM2.5. However, due to the measurement limitation, the vertical observational data o is difficult to be obtained and is relatively insufficient at present stage. With this consideration, two electric-fueled rotary-wing unmanned aerial vehicles (UAVs) are used in this study to reveal the vertical distribution of PM2.5 in Shanghai of China. Totally 53 vertical profiles of PM2.5 concentration and meteorological factors are collected to reveal the vertical distribution pattern of PM2.5. The results indicate that PM2.5 vertical concentration, especially the maximum of the PM2.5 vertical concentration, shows a good correlation with surface PM2.5 concentration, which means it is possible to use surface PM2.5 concentration to extrapolate PM2.5 vertical concentration. In terms of meteorological factors, low wind speed and northerly (or northwesterly) wind direction significantly contribute to the accumulation of high concentration PM2.5 in Shanghai during the winter. Furthermore, the low height of the planetary boundary layer (PBL) facilitates the accumulation of pollutants near the ground, but it is not imperative for the vertically high concentration of PM2.5, since vertically high PM2.5 concentration exists within high PBL as well. It has been concluded that low PBL height is not mandatory for well vertical mixing within it, for the vertically even distribution of PM2.5 occurred under both low and high PBL. In terms of the effect the temperature, although temperature makes a significant contribution to the inverse distribution of PM2.5, no significant linear correlation was found between temperature and PM2.5 vertical distribution. The findings in this study could help to understand the vertical distribution patterns of PM2.5 during the winter, and provide more evidence of how other factors impact these patterns.

Can we constrain the origin of Mars' recurring slope lineae using atmospheric observations?

Flowing water and brine have been proposed to cause seasonally reappearing dark streaks called recurring slope lineae (RSL) on steep warm slopes on Mars, along with other formation mechanisms that do not involve water. This study aims to examine whether the evaporation of water vapor from the RSL, whether from fresh water or brine, is detectable by observing water vapor and/or clouds. In this study, we summarize the possible rate and duration of water-vapor emission from RSL in different scenarios, simulate how the emitted water vapor behaves in a global climate model, and discuss the detectability of water vapor in nadir observations during existing and future explorations. We found that, in typical cases, rapid horizontal dissipation within the planetary boundary layer (PBL) following the release of water vapor prohibits cloud formation and the excess water vapor from being distinguished from the background with existing observations. Thus, we conclude that the lack of correlation between the RSL activities and the overlying water-vapor column density does not necessarily rule out the wet origin of RSL. Nevertheless, we also found that water vapor tends to accumulate in basins and valleys in some cases due to the combined effects of topography and low PBL; we suggest the locations of such configuration as targets for future atmospheric studies of Mars dedicated to quantifying water-vapor release (associated with RSL) to elucidate the formation mechanism(s) of the RSL on the planet.

Particulate pollution over an urban Himalayan site: Temporal variability, impact of meteorology and potential source regions

Five-year (2013–2017) particulate matter (PM) data observed at an urban site, Srinagar, Kashmir Himalaya, India was used to examine the temporal variability, meteorological impacts and potential source regions of PM. The daily mean PM10 and PM2.5 concentration was 135 ± 112 μg/m3 and 87 ± 93 μg/m3 respectively with significant intra- and inter-daily variation. The annual PM10 and PM2.5 concentration was 2.0–3.2 and 1.7–2.8 times higher than the annual Indian National Ambient Air Quality Standards (PM10 = 60 μg/m3 and PM2.5 = 40 μg/m3). PM concentration shows a bimodal diurnal pattern with morning and evening peaks, which coincide with the increased anthropogenic activity and shallow planetary boundary layer (PBL). The combined effect of the low temperature, low wind speed, shallow and stable PBL and geomorphic setup of Kashmir valley leads to the accumulation of particulate pollution during autumn and winter and the converse meteorological conditions leads to dispersion, dilution and deposition during spring and summer. High precipitation rate (>15 mm/day) removes the coarse particles (PM10) more efficiently than fine particles (PM2.5), while as the moderate to high humid conditions (55–95%) leads to the accumulation and growth of more PM. It was observed that ~80% of the air masses arriving at the site during spring, autumn and winter are westerlies. Source contribution analysis revealed that highly potential source regions of PM at the site are neighboring Pakistan, Afghanistan, parts of Iran and Trans-Gangetic Plains, which could contribute high concentration of the PM10 (>250 μg/m3) and PM2.5 (>150 μg/m3) during autumn and winter. The high PM load observed at the site during autumn and winter, with major contribution from the anthropogenic source emissions like biomass and coal burning, fossil fuel combustion and suspension of road dust, is aggravated by the geomorphic and meteorological setup of the Kashmir valley.

Meteorological Impact on Winter PM2.5 Pollution in Delhi: Present and Future Projection Under a Warming Climate

AbstractThis study employs the self‐organizing map classification to track wintertime PM2.5 pollutions in Delhi under four atmospheric circulation patterns during 2013–2020. We found that the most polluted circulation pattern was characterized by a northward shift in the subtropical jet stream and a northward intrusion of the subtropical high, leading to descending anomalies from the upper troposphere to the near surface. Together, the resultant reduced passage of cyclones, lower planetary boundary layer, weakened near‐surface winds and less precipitation contributed to wintertime PM2.5 pollution in Delhi. Compared with the 1981–2010 mean levels, Coupled Model Intercomparison Project 6 models project Delhi would experience two fewer days of severe pollution‐favorable circulation pattern and seven more days of clean‐favorable circulation pattern in 2070–2099 under the shared socioeconomic pathway 5–8.5. Future decrease in the severe pollution‐favorable circulation pattern may be attributed to the warming trends in sea surface temperature over the central Pacific and North Atlantic Ocean.

Detection of Upper and Lower Planetary-Boundary Layer Curves and Estimation of Their Heights from Ceilometer Observations under All-Weather Conditions: Case of Athens, Greece

The planetary-boundary layer (PBL) plays an important role in air-pollution studies over urban/industrial areas. Therefore, numerous experimental/modelling efforts have been conducted to determine the PBL height and provide statistics. Nowadays, remote-sensing techniques such as ceilometers are valuable tools in PBL-height estimation. The National Observatory of Athens operates a Vaisala CL31 ceilometer. This study analyses its records over a 2-year period and provides statistics about the PBL height over Athens. A specifically developed algorithm reads the CL31 records and estimates the PBL height. The algorithm detects an upper and a lower PBL curve. The results show maximum values of about 2500 m above sea level (asl)/3000 m asl in early afternoon hours in all months for upper PBL, and particularly the summer ones, under all-/clear-sky conditions, respectively. On the contrary, the lower PBL does not possess a clear daily pattern. Nevertheless, one morning and another afternoon peak can be identified. The intra-annual variation of the upper PBL height shows a peak in August in all-weather conditions and in September under clear-sky ones. Season-wise, the upper PBL height varies showing an autumn peak for all-weather cases, while the lower PBL height shows a winter maximum due to persistent surface-temperature inversions in this season.

Measurement report: Fourteen months of real-time characterisation of the submicronic aerosol and its atmospheric dynamics at the Marseille–Longchamp supersite

Abstract. This study reports results of PM1 chemical composition determined using a Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM) over a 14-month period (1 February 2017–13 April 2018) at the Marseille–Longchamp supersite (MRS-LCP) in France. Parallel measurements were performed with an aethalometer, an ultrafine particle monitor and a suite of instruments to monitor regulated pollutants (PM2.5, PM10, NOx, O3 and SO2). The average PM1 chemical composition over the period was dominated by organic aerosol (OA; 49.7 %) and black carbon (BC; 17.1 %), while sulfate accounted for 14.6 %, nitrate for 10.2 %, ammonium for 7.9 % and chloride for 0.5 % only. Wintertime was found to be the season contributing the most to the annual PM1 mass concentration (30 %), followed by autumn (26 %), summer (24 %) and spring (20 %). During this season, OA and BC concentrations were found to contribute 32 % and 31 % of their annual concentrations, respectively, as a combined result of heavy urban traffic, high emissions from residential heating and low planetary boundary layer (PBL) height. Most (75 %) of the 15 days exceeding the target daily PM2.5 concentration value recommended by the World Health Organization (WHO) occurred during this season. Local and long-range pollution episodes with contrasting chemical composition could be distinguished, accounting for 40 % and 60 % of the exceedance days, respectively. Enhanced OA and BC concentrations, mostly originating from domestic wood burning under nocturnal land breeze conditions, were observed during local pollution episodes, while high levels of oxygenated OA and inorganic nitrate were associated with medium-/long-range transported particles. In summertime, substantially higher concentrations of sulfate were found, with an average and a maximum contribution to the PM1 mass of 24 % and 66 %, respectively. Results from k-means clustering analysis of daily profiles of sulfate concentrations clearly reveal the significant influence of local harbour/industrial activities on air quality in addition to the more regional contribution of shipping traffic that originates from the Mediterranean basin.

Cross-boundary transport and source apportionment for PM2.5 in a typical industrial city in the Hebei Province, China: A modeling study

Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain. In this study, an industrial district (Shahe City) with a large glass manufacturing sector was investigated to clarify the relative contribution of fine particulate matter (PM2.5) to the city's high levels of pollution. The Nest Air Quality Prediction Model System (NAQPMS), paired with Weather Research and Forecasting (WRF), was adopted and applied with a spatial resolution of 5 km. During the study period, the mean mass concentrations of PM2.5, SO2, and NO2 were observed to be 132.0, 76.1, and 55.5 μg/m3, respectively. The model reproduced the variations in pollutant concentrations in Shahe at an acceptable level. The simulation of online source-tagging revealed that pollutants emitted within a 50-km radius of downtown Shahe contributed 63.4% of the city's total PM2.5 concentration. This contribution increased to 73.9±21.2% when unfavorable meteorological conditions (high relative humidity, weak wind, and low planetary boundary layer height) were present; such conditions are more frequently associated with severe pollution (PM2.5 ≥ 250 μg/m3). The contribution from Shahe was 52.3±21.6%. The source apportionment results showed that industry (47%), transportation (10%), power (17%), and residential (26%) sectors were the most important sources of PM2.5 in Shahe. The glass factories (where chimney stack heights were normally < 70 m) in Shahe contributed 32.1% of the total PM2.5 concentration in Shahe. With an increase in PM2.5 concentration, the emissions from glass factories accumulated vertically and narrowed horizontally. At times when pollution levels were severe, the horizontally influenced area mainly covered Shahe. Furthermore, sensitivity tests indicated that reducing emissions by 20%, 40%, and 60% could lead to a decrease in the mass concentration of PM2.5 of of 12.0%, 23.8%, and 35.5%, respectively.