Mixing Layer Height Research Articles

The Analysis of Atmospheric Environment Capacity in the Winter of 2016 in Liaoning

The variations of atmospheric environmental capacity and its relationship to AQI and the height of the atmospheric mixing layer have been studied by using meteorological and environmental monitoring data from Shenyang, Dalian, Dandong and Jinzhou in the winter of 2016. The results show that the atmospheric environmental capacity is obviously different in four cities, but the daily variation trend of atmospheric environmental capacity for PM2.5, PM10, SO2, NO2 and CO is basically the same. The atmospheric environmental capacity and AQI show negative correlation and the correlation coefficients (R2) of the atmospheric environmental capacity to AQI in four cities are respectively 0.1016, 0.1109, 0.3014 and 0.1723. The correlation between the atmospheric environmental capacity of PM10 and the height of the atmospheric mixing layer show positive correlation and the average correlation coefficients(R2) in four cities.

Vertical Characterization of Aerosol Particle Composition in Beijing, China: Insights From 3‐Month Measurements With Two Aerosol Mass Spectrometers

AbstractDespite extensive studies for characterization of aerosol chemistry near ground level, long‐term vertical characterization of aerosol particle composition in Beijing is very limited. In this work, non‐refractory submicron aerosol (NR‐PM1) species were simultaneously measured at ground level and 260 m on a meteorological tower from 14 October 2014 to 18 January 2015 in Beijing using two aerosol mass spectrometers. Our results showed overall lower concentrations of NR‐PM1 at 260 m by 2%–36% than ground level in both heating and non‐heating seasons, and also larger vertical gradients during clean periods than polluted episodes. The vertical ratios and correlations of aerosol species between ground level and 260 m presented higher values in daytime and lower ones at nighttime mainly due to the influences of planetary boundary layer and local source emissions, respectively. Nitrate showed ubiquitously higher ratio of 260 m to ground (ratio260m/ground) than sulfate due to a higher formation potential from gas‐particle partitioning and heterogeneous reactions at higher heights. A detailed analysis of vertical evolution showed relatively stable ratios260m/ground for secondary aerosol species during the early formation stage of haze episodes, which decreased simultaneously along with mixing layer height during the later severely polluted periods with NR‐PM1 concentration above 150 μg/m3. Our results demonstrated that the evolution of vertical differences in megacities is subject to the influences from both physical (e.g., regional transport, mountain‐valley winds, inversions of temperature and relative humidity, and mixing layer height) and chemical processes (e.g., gas‐particle partitioning and aqueous‐phase processing).

Comparison of mixing layer height inversion algorithms using lidar and a pollution case study in Baoding, China

Beijing–Tianjin–Hebei area is suffering from atmospheric pollution from a long time. The understanding of the air pollution mechanism is of great importance for officials to design strategies for the environmental governance. Mixing layer height (MLH) is a key factor influencing the diffusion of air pollutants. It plays an important role on the evolution of heavy pollution events. Light detection and ranging (lidar), is an effective remote-sensing tool, which can retrieve high spatial and temporal evolution process within mixing layer (ML), especially the variation of MLH. There are many methods to retrieve MLH, but each method has its own applicable limitations. The Mie-lidar data in Beijing was firstly used to compare three different algorithms which are widely used under different pollution levels. We find that the multi-layer structure near surface may cause errors in the detection of mixing layer. The MLH retrieved based on image edge detection was better than another two methods especially under heavy polluted episode. Then we applied this method to investigate the evolution of the mixing layer height during a pollution episode in December 2016. MLH at Gucheng county showed the positive correlation with the concentration of particulate matters during the start of this pollution episode. The elevated pollution level in Gucheng was not associated with MLH's decrease, and the significantly increased particulate matters raised the boundary layer, which trapped the pollutants near the surface.

Radon-based estimates of equivalent mixing layer heights: A long-term assessment

Air pollution events at urban locations are driven by both emissions and atmospheric dispersion conditions. Atmospheric dispersion is not routinely assessed at monitoring networks thus preventing the possibility of understanding if high pollution events are due to increasing emissions or to the occurrence of atmospheric stability conditions. In principle, this piece of information would be very useful to implement effective strategies for pollution abatement. In this work, an 18-year long dataset of radon (222Rn) progeny measurements was used to estimate equivalent mixing layer heights (hereafter referred to as MH) with hourly resolution by means of a box model. Mean MH obtained by more conventional modelling approaches based on turbulence variables on a 5-year long dataset agreed very well with results obtained by the box model. It is noteworthy that in the literature there are scarce MH data for such long periods and comparisons between estimates by radioactive tracers and other approaches are often limited to a few days/weeks. Results suggested that relatively simple methods like the one here proposed could be implemented at pollution monitoring stations in order to improve available information and better understand the evolution of pollution events on 1-h timescale. In addition, the long-term assessment here presented provides useful data to pursue MH climatological studies.

Observation and analysis of spatiotemporal characteristics of surface ozone and carbon monoxide at multiple sites in the Kathmandu Valley, Nepal

Abstract. Residents of the Kathmandu Valley experience severe particulate and gaseous air pollution throughout most of the year, even during much of the rainy season. The knowledge base for understanding the air pollution in the Kathmandu Valley was previously very limited but is improving rapidly due to several field measurement studies conducted in the last few years. Thus far, most analyses of observations in the Kathmandu Valley have been limited to short periods of time at single locations. This study extends the past studies by examining the spatial and temporal characteristics of two important gaseous air pollutants (CO and O3) based on simultaneous observations over a longer period at five locations within the valley and on its rim, including a supersite (at Bode in the valley center, 1345 m above sea level) and four satellite sites: Paknajol (1380 m a.s.l.) in the Kathmandu city center; Bhimdhunga (1522 m a.s.l.), a mountain pass on the valley's western rim; Nagarkot (1901 m a.s.l.), another mountain pass on the eastern rim; and Naikhandi (1233 m a.s.l.), near the valley's only river outlet. CO and O3 mixing ratios were monitored from January to July 2013, along with other gases and aerosol particles by instruments deployed at the Bode supersite during the international air pollution measurement campaign SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley – endorsed by the Atmospheric Brown Clouds program of UNEP). The monitoring of O3 at Bode, Paknajol and Nagarkot as well as the CO monitoring at Bode were extended until March 2014 to investigate their variability over a complete annual cycle. Higher CO mixing ratios were found at Bode than at the outskirt sites (Bhimdhunga, Naikhandi and Nagarkot), and all sites except Nagarkot showed distinct diurnal cycles of CO mixing ratio, with morning peaks and daytime lows. Seasonally, CO was higher during premonsoon (March–May) season and winter (December–February) season than during monsoon season (June–September) and postmonsoon (October–November) season. This is primarily due to the emissions from brick industries, which are only operational during this period (January–April), as well as increased domestic heating during winter, and regional forest fires and agro-residue burning during the premonsoon season. It was lower during the monsoon due to rainfall, which reduces open burning activities within the valley and in the surrounding regions and thus reduces sources of CO. The meteorology of the valley also played a key role in determining the CO mixing ratios. The wind is calm and easterly in the shallow mixing layer, with a mixing layer height (MLH) of about 250 m, during the night and early morning. The MLH slowly increases after sunrise and decreases in the afternoon. As a result, the westerly wind becomes active and reduces the mixing ratio during the daytime. Furthermore, there was evidence of an increase in the O3 mixing ratios in the Kathmandu Valley as a result of emissions in the Indo-Gangetic Plain (IGP) region, particularly from biomass burning including agro-residue burning. A top-down estimate of the CO emission flux was made by using the CO mixing ratio and mixing layer height measured at Bode. The estimated annual CO flux at Bode was 4.9 µg m−2 s−1, which is 2–14 times higher than that in widely used emission inventory databases (EDGAR HTAP, REAS and INTEX-B). This difference in CO flux between Bode and other emission databases likely arises from large uncertainties in both the top-down and bottom-up approaches to estimating the emission flux. The O3 mixing ratio was found to be highest during the premonsoon season at all sites, while the timing of the seasonal minimum varied across the sites. The daily maximum 8 h average O3 exceeded the WHO recommended guideline of 50 ppb on more days at the hilltop station of Nagarkot (159 out of 357 days) than at the urban valley bottom sites of Paknajol (132 out of 354 days) and Bode (102 out of 353 days), presumably due to the influence of free-tropospheric air at the high-altitude site (as also indicated by Putero et al., 2015, for the Paknajol site in the Kathmandu Valley) as well as to titration of O3 by fresh NOx emissions near the urban sites. More than 78 % of the exceedance days were during the premonsoon period at all sites. The high O3 mixing ratio observed during the premonsoon period is of a concern for human health and ecosystems, including agroecosystems in the Kathmandu Valley and surrounding regions.

Long-term measurements of volatile organic compounds highlight the importance of sesquiterpenes for the atmospheric chemistry of a boreal forest

Abstract. The concentrations of terpenoids (isoprene; monoterpenes, MTs; and sesquiterpenes, SQTs) and oxygenated volatile organic compounds (OVOCs; i.e. aldehydes, alcohols, acetates and volatile organic acids, VOAs) were investigated during 2 years at a boreal forest site in Hyytiälä, Finland, using in situ gas chromatograph mass spectrometers (GC-MSs). Seasonal and diurnal variations of terpenoid and OVOC concentrations as well as their relationship with meteorological factors were studied. Of the VOCs examined, C2–C7 unbranched VOAs showed the highest concentrations, mainly due to their low reactivity. Of the terpenoids, MTs showed the highest concentrations at the site, but seven different highly reactive SQTs were also detected. The monthly and daily mean concentrations of most terpenoids, aldehydes and VOAs were highly dependent on the temperature. The highest exponential correlation with temperature was found for a SQT (β-caryophyllene) in summer. The diurnal variations in the concentrations could be explained by sources, sinks and vertical mixing. The diurnal variations in MT concentrations were strongly affected by vertical mixing. Based on the temperature correlations and mixing layer height (MLH), simple proxies were developed for estimating the MT and SQT concentrations. To estimate the importance of different compound groups and compounds in local atmospheric chemistry, reactivity with main oxidants (hydroxyl radical, OH; nitrate radical, NO3; and ozone, O3) and production rates of oxidation products (OxPRs) were calculated. The MTs dominated OH and NO3 radical chemistry, but the SQTs greatly impacted O3 chemistry, even though the concentrations of SQT were 30 times lower than the MT concentrations. SQTs were also the most important for the production of oxidation products. Since the SQTs show high secondary organic aerosol (SOA) yields, the results clearly indicate the importance of SQTs for local SOA production.

Year-long variability of the fossil fuel and wood burning black carbon components at a rural site in southern Delhi outskirts

This study examines year-long (April 2015 – March 2016) measurements of black carbon (BC) concentrations acquired with a 7-wavelength Aethalometer (ΑΕ-42) at Panchgaon, in the southern Delhi outskirts. We assess the seasonality of BC concentrations and focus on the quantification of the relative contributions from fossil-fuel combustion (BCff) and wood burning (BCwb) on annual basis. Significant monthly, daily and diurnal variability in both BC components is found due to seasonal changes in the emission sources, dispersion conditions, and boundary-layer dynamics. The annual-mean BC concentration at 880 nm is 7.2 ± 0.3 μg m−3 (range of 0.09–38.6 μg m−3), exhibiting the highest values in winter (9.3 ± 0.7 μg m−3) and the lowest (4.6 ± 0.2 μg m−3) in summer monsoon. BCff (mean of 5.9 ± 0.2 μg m−3) is estimated to account for 81% of the BC mass on annual basis, while the BCwb ranges from 0.55 ± 0.06 μg m−3 in July to 2.7 ± 0.2 μg m−3 in December. The highest BCff/BC fraction is observed in April–June (~86–87% at 880 nm), while the BCwb/BC peaks in October–December (23–29% at 880 nm). The BCff contribution increases in the early-morning hours due to traffic, while the BCwb fraction peaks during the evening and night hours in winter, due to wood and waste material burning for heating. The BC diurnal pattern is highly affected by the mixing-layer height variations, leading to lower concentrations around noon, when the vertical mixing and dilution processes are the strongest. The WRF-Chem model simulations represent rather satisfactorily the BC concentrations and diurnal patterns in summer, but fail to reproduce the BC peaks during late post-monsoon and winter, suggesting the need for refinement of the BC emissions, simulations of local meteorology, and/or boundary-layer dynamics.

Assessment of biomass burning and fossil fuel contribution to black carbon concentrations in Delhi during winter

This study aims to assess the contribution of fossil-fuel combustion (BCff) and biomass (or wood) burning (BCwb) to wintertime black carbon (BC) concentrations in Delhi using the “Aethalometer model” approach. Continuous measurements using 7-wavelength Aethalometer (AE-33) were taken from December 2015 to February 2016 in Delhi downtown, as part of a multi-instrument research campaign, revealing high BC concentrations of 24.4 ± 12.2 μg m−3 (range from 3.2 to 59.9 μg m−3). The BCff contribution dominates with an average fraction of 72% at 880 nm, indicating an important contribution from biomass burning (28%). The daily-averaged Absorption Ångström Exponent (AAE370-880) varies between 1.08 and 1.46 due to changes in the BC emission rates, variations in the relative strength between fossil-fuel and wood-burning sources and mixing processes in the atmosphere. The average BCff/BCwb ratio is estimated as 2.90 ± 1.47 at 880 nm, while the BCwb contribution maximized in the evening hours due to enhanced wood burning for heating. The BC, BCff and BCwb concentrations exhibit remarkable diurnal variations with maximum values in the morning and evening/night hours and lower around noon, primarily driven by changes in the mixing-layer height. The highest BC, BCff and BCwb concentrations are associated with weak winds (<2 ms−1), revealing a dominance of local emission sources within the Delhi metropolitan area. A sensitivity analysis is performed by changing the wavelength pairs and the pre-assumed AAE values in order to evaluate the stability of the “Aethalometer model” in assessment of the BC source apportionment. The results reveal that the “Aethalometer model” is more sensitive in estimating the BCwb, while the changes in the BCff component are rather low.

Influence of Relative Humidity, Mixed-Layer Height, and Mesoscale Vertical-Velocity Variations on Column and Surface Aerosol Characteristics Over an Urban Region

Investigations into the influence of variations in relative humidity, mixed-layer height, and mesoscale vertical velocity on column and surface aerosol characteristics over urban regions are quite rare. Here we report on a comprehensive investigation that was conducted over Ahmedabad, an urban location in western India, during December 2006. In this campaign columnar and surface aerosol characteristics were measured and compared to relative humidity, mixed-layer height, and mesoscale vertical velocity to examine their influence on urban aerosol characteristics. The 500-nm aerosol optical depth was found to be approximately 0.8 between 24 and 26 December while on a cleaner day such as 7 and 18 December the aerosol optical depth was 0.1. Aerosol optical depths based on Moderate Resolution Imaging Spectroradiometer (MODIS) level-2 and level-3 data, and on in situ Sun photometer measurements, show good agreement. The scattering coefficient ( $$\beta _{\mathrm{sca}}$$ ) and absorption coefficient ( $$\beta _{\mathrm{abs}}$$ ) increased by a factor of 5–10 on 26 December compared to 7 December (a normal day). This latter date was characterized by a clear atmosphere, a lower mixed-layer height ( $$\approx $$ 1650 m), positive vertical velocity and higher aerosol scale height (>3 km), while 26 December was marked with hazy and smoky conditions, a larger mixed-layer height ( $$\approx $$ 2500 m), negative vertical velocity and smaller aerosol scale height ( $$\approx $$ 1 km). These atmospheric conditions lead to lower and higher values of surface and columnar aerosol concentrations on 7 and 26 December respectively. A measure of spectral aerosol absorption, $$\alpha '_{\mathrm{abs}}$$ > 2, indicating the dominance of carbonaceous aerosols from biomass/biofuel emissions (open biomass burning), is rather surprising as fossil-fuel emissions that produce strongly light absorbing carbonaceous particles usually dominate urban regions. The single-scattering albedo on both days is 0.56 and 0.67 respectively, while monthly mean hemispheric backscatter fraction b and asymmetry parameter g values are 0.16 and 0.53 respectively. Higher b and lower g values on 7 December, and lower b and higher g values on 26 December, provide the relative scale of variation in the amount of sub-micron aerosols that dominate on a normal/clear day vis-a-vis a smoky/perturbed day. Lower single-scattering albedo indicates the dominance of absorbing aerosols above Ahmedabad, and higher b and lower g values suggest the abundance of fine mode particles in aerosol size distribution. The in-depth results serve as representative inputs to modelling the column and surface characteristics, and the resultant radiative forcing of urban aerosols influenced by variations in relative humidity, mixed-layer height, and mesoscale vertical velocity.

Sensitivity of urban boundary layer simulation to urban canopy models and PBL schemes in Beijing

Mesoscale models with urban canopy models (UCM) have been increasingly used to study urban boundary layer processes. Using the data from a high-resolution Doppler lidar, automatic weather stations (AWS), and a flux tower located in the urban site, we assessed the performance of the urbanized Weather Research and Forecasting (WRF) model through three urban canopy models (the single-layer UCM, and the multi-layer BEP and BEM models) and four planetary boundary layer (PBL) schemes (the non-local first-order YSU, SH and ACM2 schemes, as well as the local TKE-based BouLac scheme) for one cloudy and one clear sky days. Results show that the WRF-Urban generally overestimates the sensible heat flux and underestimates the latent heat flux. The simulated 2-m temperature and 10-m wind speed are more sensitive to UCMs than to PBL schemes. Using the BouLac PBL scheme and the multi-layer BEP generates the best agreement with AWS observations. Simulations with the multi-layer BEM produce the highest mixing-layer heights. The convective boundary layer (CBL) from the single-layer UCM experiment develops at the slowest pace when compared with other two multi-layer UCMs. When the single-layer UCM is used, simulations with the non-local mixing YSU, SH and ACM2 schemes perform better than the TKE-based scheme (BouLac) for representing the CBL structure. Additionally, the scale-aware SH scheme considering the effect of grid resolution on the vertical dimension, simulates the potential temperature profiles that are closest to observations.

Status of atmospheric particulate matter and black carbon concentration at Ashuganj in Brahmanbaria

Atmospheric particulate matter (PM) samples (both PM10 and PM2.5) were collected simultaneously from Midland Power Company Limited at Ashuganj, in Brahmanbaria to monitor the seasonal fluctuations of particulate matter and black carbon (BC) concentrations from air samples. Total eight samples were collected from January 2016 to December 2017 using two Air Metrics MiniVol samplers and the quantity of PM2.5 and PM10 was detected by weighing the filters before and after exposure. The concentration of PM (PM2.5 and PM10) and BC were analyzed at the laboratory of Chemistry Division, Atomic Energy Centre, Dhaka. The black carbon concentration from both PM2.5 and PM10 samples were also determined by reflectance measurement. The concentrations of PM2.5 varied from 12.2–145 μgm−3 where mean value was 67.09 μgm−3. The mean concentration of PM10 was 103.64 μgm−3 whereas the concentration ranged from 20.5–220 μgm−3. The ratios of PM2.5/PM10 fluctuated during different seasons, winter showed higher concentration and summer showed relatively lower concentration for both PM2.5 and PM10. Atmospheric dispersion due to increased wind speeds and wider mixing layer heights are recognized to be responsible for the lower PM concentrations in warmer months. The concentrations of BC in PM2.5 also varied from 2.44–33.4 μgm−3 and BC in PM10 varied from 4.51–57.2 μgm−3, respectively. The concentrations of particulate matter exceeded the Bangladesh National Ambient Air Quality Standard.J. Bangladesh Agril. Univ. 16(2): 232-236, August 2018

Assessment of MODIS, OMI, MISR and CALIOP Aerosol Products for Estimating Surface Visual Range: A Mathematical Model for Hong Kong

Estimation of atmospheric visibility (VR) using ground and satellite sensors is ineffective under Hong Kong’s complex atmosphere and climate. Therefore, the relationship between columnar Aerosol Optical Depth (AOD) from four space-borne sensors (OMI, MODIS, MISR and CALIOP) and Bext from two visibility-recording stations was evaluated, to recommend an effective satellite-based method and spatial resolution, for estimation of VR over Hong Kong. Since most column-integrated aerosol particle extinction occurs within a mixing layer height (MLH) of 1–3 km, column-based AOD from satellites is expected to give a good indication of surface-level conditions, especially when MLH is a known input. The AOD from both MODIS and MISR showed high correlations with Bext; therefore, both were subjected to rigorous statistical analysis along with climatic data to simulate visibility. The best estimate of ground visibility was obtained from MODIS AOD combined with surface-level climatic data, and this explained 84% of the variance in VR, with a low distance error of 0.27 km. Results suggest that the water vapor mixing ratio (Q) alone can explain the combined effect of Atmospheric Pressure (P), Temperature (T) and Relative Humidity (RH) on VR, and that the advection term (VT) alone is sufficient to explain the effects of T, WS and WD on dispersion of aerosols, and hence on VR.

Case study of spring haze in Beijing: Characteristics, formation processes, secondary transition, and regional transportation

Continuous haze monitoring was conducted from 12:00 3 April to 12:00 8 April 2016 in Beijing, China to develop a more detailed understanding of spring haze characteristics. The PM2.5 concentration ranged from 6.30 to 165 μg m−3 with an average of 63.8 μg m−3. Nitrate was the most abundant species, accounting for 36.4% of PM2.5, followed by organic carbon (21.5%), NH4+ (19.3%), SO42− (18.8%), and elemental carbon (4.10%), indicating the key role of nitrate in this haze event. Species contribution varied based on the phase of the haze event. For example, sulfate concentration was high during the haze formation phase, nitrate was high during the haze, and secondary organic carbon (SOC) had the highest contribution during the scavenging phase. The secondary transition of sulfate was influenced by SO2, followed by relative humidity (RH) and Ox (O3+NO2). Nitrate formation occurred in two stages: through NO2 oxidation, which was vulnerable to Ox; and by the partitioning of N (+5) which was susceptible to RH and temperature. SOC tended to form when Ox and RH were balanced. According to hourly species behavior, sulfate and nitrate were enriched during haze formation when the mixed layer height decreased. However, SOC accumulated prior to the haze event and during formation, which demonstrated the strong contribution of secondary inorganic aerosols, and the limiting contribution of SOC to this haze case. Investigating backward trajectories showed that high speed northwestern air masses following a straight path corresponded to the clear periods, while southwesterly air masses which traversed heavily polluted regions brought abundant pollutants to Beijing and stimulated the occurrence of haze pollution. Results indicate that the control of NO2 needs to be addressed to reduce spring haze. Finally, the correlation between air mass trajectories and pollution conditions in Beijing reinforce the necessity of inter-regional cooperation and control.

Atmospheric boundary‐layer characteristics from ceilometer measurements. Part 1: A new method to track mixed layer height and classify clouds

The use of Automatic Lidars and Ceilometers (ALC) is increasingly extended beyond monitoring cloud base height to the study of atmospheric boundary layer (ABL) dynamics. Therefore, long‐term sensor network observations require robust algorithms to automatically detect the mixed layer height (ZML). Here, a novel automatic algorithm CABAM (Characterising the Atmospheric Boundary layer based on ALC Measurements) is presented. CABAM is the first non‐proprietary mixed layer height algorithm specifically designed for the commonly deployed Vaisala CL31 ceilometer. The method tracks ZML, takes into account precipitation, classifies the ABL based on cloud cover and cloud type, and determines the relation between ZML and cloud base height. CABAM relies solely on ALC measurements. Results perform well against independent reference (AMDAR: Aircraft Meteorological Data Relay) measurements and supervised ZML detection. AMDAR‐derived temperature inversion heights allow ZML evaluation throughout the day. Very good agreement is found in the afternoon when the mixed layer height extends over the full ABL. However, during night or the morning transition the temperature inversion is more likely associated with the top of the residual layer. From comparison with SYNOP reports, the ABL classification scheme generally correctly distinguishes between convective and stratiform boundary‐layer clouds, with slightly better performance during daytime. Applied to 6 years of ALC observations in central London, Kotthaus and Grimmond (), a companion paper, demonstrate CABAM results are valuable to characterise the urban boundary layer over London, United Kingdom, where clouds of various types are frequent.

Atmospheric boundary‐layer characteristics from ceilometer measurements. Part 2: Application to London's urban boundary layer

Long‐term measurements of mixed layer height (ZML) are possible with advances in detecting ZML based on Automatic Lidars and Ceilometers (ALC) observations. Six years of ALC measurements in central London are analysed using the CABAM (“Characterising the Atmospheric Boundary layer (ABL) based on ALC Measurements”) algorithm which provides ZML and an ABL classification by cloud cover and type. The boundary‐layer dynamics are shown to respond to day‐length, cloud cover and cloud type. Seasonal median daily maxima range from 707 m (stratiform clouds) to 1704 m (days with convective boundary‐layer clouds following a clear night). A common approach to ABL classification and clear definition of key ZML‐indicators can facilitate inter‐city comparison. A simple parametrisation based on empirical coefficients derived from the London measurements is proposed to generalise the description of diurnal and seasonal variations in ZML, including cloud conditions. This has the potential to aid improved understanding of the complex relations between surface air quality and boundary‐layer dynamics.

Volume for pollution dispersion: London's atmospheric boundary layer during ClearfLo observed with two ground-based lidar types

In urban areas with high air pollution emissions, the boundary layer volume within which gases and particles are diluted is critical to air quality impacts. With advances in ground-based remote sensing technologies and data processing algorithms, observations of layers forming the atmospheric boundary layer (ABL) are becoming increasingly available at high temporal resolution. Here, mixing height (MH) estimates determined from turbulence measurements of Doppler lidars and aerosol-derived mixed layer height (MLH) based on automatic lidar and ceilometer (ALC) observations within the centre of London are assessed. While MH uncertainty increases with shorter duration of vertical stare sampling within the Doppler lidar scan pattern, instrument-related noise of the ALC may result in large MLH errors due to the challenging task of layer attribution. However, when long time series are assessed most of the algorithm- and instrument-related uncertainties average out and therefore become less critical to overall climatological analyses. Systematic differences occur in nocturnal MH from two nearby (3–4 km) sites but MLH estimates at both sites generally agree with MH obtained at the denser urban setting. During daytime, most spatial variations in ABL structure induced by synoptic conditions or land cover heterogeneity at this scale do not exceed measurement uncertainty. Agreement between MH and MLH is clearly affected by ABL aerosol content and cloud conditions. Discrepancies increase with cloud complexity. On average, MH rises ahead of MLH during the morning growth period and peaks earlier in the day. There is a faster afternoon decay of MLH so that MLH and MH converge again around sunset and often have similar nocturnal values. Results demonstrate that turbulence-derived MH and aerosol-derived MLH should not be used inter-changeably for purposes of model evaluation, interpretation of surface air quality observations or initialisation of chemical transport models.

Intra-continental wildfire smoke transport and impact on local air quality observed by ground-based and satellite remote sensing in New York City

The wildfires in Fort McMurray of Alberta, Canada, injected large amounts of smoke aerosols in May 2016 and were identified as being one of Canada's major weather events of the year. This paper presents a synergistic remote sensing and in-situ measurement of the resultant smoke plume transport, optical properties, and its impacts on local air quality in New York City (NYC). Comparisons with the operational air quality model forecast (the NOAA National Air Quality Forecasting Capability, NAQFC) performance are presented. The aloft plume intrusions on May 9–13 and 25–29, 2016, and their mixing down into the planetary-boundary layer (PBL) were observed by a combined lidar, ceilometer and other measurement. A decrease in single-scattering albedo and absorption Angstrom exponent near one indicates that the plumes were absorbing aerosol dominated. Dramatic impacts of smoke transport on the ground air quality are demonstrated with a coincident increase of ground PM2.5 (from 5- to 25–30 μg/m3) in NYC urban and upwind rural area, enhancement of the PM2.5 speciation (organic carbon, elemental carbon, potassium ion (K+)) and the ozone exceedance of NAAQS. Using the satellite and model product, we show regional spatial distribution of smoke, multiple transport paths and wildfire sources. Finally, with the lidar vertical profiling observations, we evaluate the model PBL-height (PBLH) and PM2.5 during May 24th to 30th, 2016. The model PBLH shows consistent diurnal variation with the observed mixing layer height (MLH), but is clearly overestimated during the convective daytime hours. On the other hand, when estimating the MLH directly from the model PM2.5 profile, better agreement with observation was indicated. This helps explain the good agreement between the model PM2.5 and surface measurements except for the model overestimate during the morning of May 25 and 26, 2016.

Assessment of the atmospheric mixing layer height and its effects on pollutant dispersion.

The atmospheric mixing layer height (MLH) is an important parameter of the planetary boundary layer (PBL) because it affects the transportation and dispersion processes of pollutants emitted from different sources. This study investigated the relationship between the surface temperature inversion, elevated temperature inversion, and MLH within the PBL of the Kuwait by collecting and analyzing measurements of the temperature and the air quality of upper air during 2013. The upper air temperature and the MLH were derived using a microwave temperature profiler. Hourly concentrations of SO2, O3, particulate matter (PM10), NO2, CO, NO x , and non-methane hydrocarbons (NMHCs) in ambient air were measured by air quality monitoring stations. The collected data were used to estimate the hourly MLH for the transportation and dispersion of critical pollutants. The results showed that concentrations of SO2 and PM10 have direct correlation with MLH during the day, whereas they have the reverse relationship at night. Conversely, concentrations of CO, NMHCs, and NO x showed negative correlation with MLH during both day and night, whereas concentrations of O3 showed direct correlation with MLH during both day and night. In addition, the relationship between the PBL and concentrations of critical pollutants in residential areas was clarified. These findings indicate the influence of the MLH on SO2 and PM10 is much greater during the day than at night. The findings of the present study could help improve our understanding of the effects of MLH on air quality.

Boundary-layer features and regional transport process of an extreme haze pollution event in Nanjing, China

Extreme haze pollution event is a major environmental concern in East China. In this study, we aim at elucidating the relationships among boundary-layer features, regional transportation and low-visibility event of haze pollution in Nanjing in December 2013. The results showed that this haze event was associated with weak cold front activity under relatively stable weather conditions, including weak surface wind speed. Local pollutant accumulation was the main cause during the whole haze process, the surface wind speed was under 2 m/s , and the irradiance 24-hour change (IR 24 ) had negative values. The higher the pollutants' concentrations, the greater the change of IR 24 . Most of the pollution was circulating and trapped within 130-km range around the observing site. Based on the cluster analysis, the circling trajectory presented the highest PM 2.5 , and the long-distance pollutant transformation from North China also made the pollutants' concentration higher. Multilayer inversions, lower mixed layer height and thick lower wind speed zone promoted extreme haze maintenance. Both inversion and relative humidity (RH) had obvious diurnal variation. During the serious pollution period (visibility <2000 m), the wind speed below 500 m was under 2 m/s all the time. Surface inversion (SI), low-hanging inversion and multi-layer inversion all occurred. The lower the inversion bottom (IB), the lower the visibility. Many multi-layer inversions had intensity greater than 1 °C/100 m , and corresponded to the increase of pollutants concentrations on the ground. Although the low-hanging inversion intensity (LHII) was only 0.32 °C/100 m and the low-hanging inversion bottom (LHIB) rose to 420.0 m, the multi-layer and large thickness (124.9 m) of inversions sustained surface pollutants concentrations at high levels. The downward momentum transport by the weak cold front increased surface wind speeds destroyed the inversions and ended the haze event. • Multilayer inversions corresponded to pollutants' increase. • Most of the pollution was stagnation within 130-km range. • The circling trajectory presents the highest PM 2.5 . • Regional transport from north China brought more pollutants. • The downward momentum transport increased the surface wind speed.

Mixing layer height on the North China Plain and meteorological evidence of serious air pollution in southern Hebei

Abstract. To investigate the spatiotemporal variability of the mixing layer height (MLH) on the North China Plain (NCP), multi-site and long-term observations of the MLH with ceilometers at three inland stations (Beijing, BJ; Shijiazhuang, SJZ; Tianjin, TJ) and one coastal site (Qinhuangdao) were conducted from 16 October 2013 to 15 July 2015. The MLH of the inland stations in the NCP were highest in summer and lowest in winter, while the MLH on the coastal area of Bohai was lowest in summer and highest in spring. As a typical site in southern Hebei, the annual mean of the MLH at SJZ was 464 ± 183 m, which was 15.0 and 21.9 % lower than that at the BJ (594 ± 183 m) and TJ (546 ± 197 m) stations, respectively. Investigation of the shear term and buoyancy term in the NCP revealed that these two parameters in southern Hebei were 2.8 times lower and 1.5 times higher than that in northern NCP within 0–1200 m in winter, respectively, leading to a 1.9-fold higher frequency of the gradient Richardson number &gt; 1 in southern Hebei compared to the northern NCP. Furthermore, combined with aerosol optical depth and PM2.5 observations, we found that the pollutant column concentration contrast (1.2 times) between these two areas was far less than the near-ground PM2.5 concentration contrast (1.5 times). Through analysis of the ventilation coefficient in the NCP, the near-ground heavy pollution in southern Hebei mainly resulted from the lower MLH and wind speed. Therefore, due to the importance of unfavorable weather conditions, heavily polluting enterprises should be relocated and strong emission reduction measures should be introduced to improve the air quality in southern Hebei.