Lower Atmospheric Boundary Layer Research Articles

The global blockage effect of a wind farm cluster - an LES study

The interaction of wind farm clusters with the atmospheric flow is complex. It comes along with phenomena that have still not been fully understood in detail. However, having an understanding of the flow is a prerequisite for the derivation of models that can accurately and with limited computational resources replicate the most prominent features of the flow. This study exploits large-eddy simulations (LES) to create a better understanding of the wind farm cluster blockage under a set of different atmospheric conditions. The specific wind farm cluster consists of three wind farms, with a relatively narrow gap between the two northernmost wind farms. Results reveal that under conventionally neutral boundary layers, the induction zone relatively large is when there is a low atmospheric boundary layer height with a strong temperature inversion. In our LES study, wind speed is reduced between 2% and 4% 2D upstream of the front row of the wind farm, while inside the gap of the wind farm cluster, there is an acceleration of the wind speed. Comparatively, blockage for a solitary row or single wind turbine is similar and smaller than for a whole cluster. On average, turbines in the front row of a cluster produce 5.1% less power than a single turbine.

A model-based study of the dynamics of Arctic low-level jet events for the MOSAiC drift

Low-level jets (LLJs) are studied for the period of the ship-based experiment MOSAiC 2019/2020 using the regional climate model Consortium for Small-scale Model—Climate Limited area Mode (CCLM). The model domain covers the whole Arctic with 14 km resolution. CCLM is run in a forecast mode (nested in ERA5) and with different configurations of sea ice data for the winter. The focus is on the study of LLJs for the MOSAiC site. LLJs are detected using model output every 1 h. We define LLJ events as LLJs that last at least 6 h. Case studies of LLJ events are shown using wind lidar and radiosonde data as well as CCLM simulations. LLJs are not local events but are embedded in large jet structures extending for hundreds of kilometers that are advected toward the MOSAiC site. CCLM simulations are used to study the statistics of LLJs of all profiles and of LLJ events as well as the dynamics. LLJs are found in about 40% of the hourly profiles, but only 26% of the hourly profiles are associated with LLJ events. Strong LLJs (≥15 m/s) are detected in 13% of the hourly profiles, which is about the same fraction as for strong LLJ events. The mean duration of events is about 12 h. The LLJ events are characterized using dynamical criteria for the wind speed profile and the evolution of the jet core. A fraction of 35% of the LLJ events are baroclinic, but more than 40% of the LLJ events show a large contribution of advection to the initial generation as well as for the evolution of the jet core. Only very few events fulfill the criteria of inertial oscillations. LLJ events occur for all months, but strong events have a higher frequency during winter. The turbulent kinetic energy in the lower atmospheric boundary layer (ABL) is twice (4 times) as large for LLJs (strong LLJs) than for situations without LLJs, which underlines the impact of LLJs on turbulent processes in the ABL.

Synergy between Short-Range Lidar and In Situ Instruments for Determining the Atmospheric Boundary Layer Lidar Ratio

Short-range elastic backscatter lidar (SR-EBL) systems are remote sensing instruments for studying low atmospheric boundary layer processes. This work presents a field campaign oriented to filling the gap between the near-surface aerosol processes regarding aerosol radiative properties and connecting them with the atmospheric boundary layer (ABL), centering attention on the residual layer and the ABL transition periods. A Colibri Aerosol Lidar (CAL) instrument, based on the short-range lidar with high spatio-temporal resolution, was used for the first time in the ACTRIS AGORA facility (Andalusian Global Observatory of the Atmosphere) in Granada (Spain). This study showed the possibility of combining lidar and in situ measurements in the lowermost 150 m. The results address, on the one hand, the characterization of the short-range lidar for developing a method to find the calibration constant of the system and to correct the incomplete overlap to further data exploitation. On the other hand, relevant radiative properties such as the temporal series of the aerosol lidar ratio and extinction coefficient were quantified. The campaign was divided in three different periods based on the vehicular emission peak in the early mornings, namely, before, during, and after the emission peak. For before and after the emission peak data classification, aerosol properties presented closer values; however, large variability was obtained after the emission peak reaching the maximum values of extinction and a lidar ratio up to 51.5 ± 11.9 (Mm)−1 and 36.0 ± 10.5 sr, respectively. During the emission peaks, the values reached for extinction and lidar ratio were up to 136.8 ± 26.5 (Mm)−1 and 119.0 ± 22.7 sr, respectively.

Study of spatiotemporal variation and annual emission of CH4 in Shaoxing Yangtze River Delta, China, Using a portable CH4 detector on the UAV

Methane (CH4) is the second greenhouse gas and has a profound impact on global climate change due to its high global warming potential and concentration. By 2022, the CH4 concentration was approximately 1.9 ppm, which was 264% of the pre-industrial level. The spatiotemporal distribution of CH4 was investigated by a portable CH4 detector on an unmanned aerial vehicle and electric bicycles in Shaoxing, a city situated in the Yangtze River Delta, China. The vertical distribution revealed CH4 concentration generally decreased slowly with height. However, the inversion condition and low atmospheric boundary layer height (ABLH) leaded to the enhancement of CH4 with height. The highest CH4 concentration (2.2 ± 0.1 ppm, n = 1428) was observed in winter and the lowest (2.0 ± 0.2 ppm, n = 1530) in spring. Regarding the daily variation, CH4 concentration peaked at 5:00 local time (LT) and reached its lowest level at 14:00 LT, which was attributed to the daily variation of ABLH, lowest in the early morning and highest in the noon. In urban areas, CH4 concentrations showed higher levels near restaurants, natural gas stations and sewerage well, with a maximum value of 13.1 ppm, which was caused by CH4 emission and natural gas leakage from these places. The annual CH4 emission in Shaoxing were estimated to be approximately 69 ton/(km2·year) by the mass balance approach. Compared with other cities in the world, the CH4 emission is in higher level which imply some control measures should be conducted to reduce CH4 emission in Shaoxing.

A Versatile Calibration Method for Rotary-Wing UAS as Wind Measurement Systems

Abstract The use of small uncrewed aircraft systems (UAS) can effectively capture the wind profile in the lower atmospheric boundary layer. This study presents a calibration process to estimate the horizontal wind vector using a rotary-wing UAS in hovering conditions. This procedure does not require wind tunnels or meteorological masts, only the data from the flight control unit and a specific set of calibration flights. A model based on the UAS drag coefficient was proposed and compared to a traditional approach. Validation flights at the German Weather Service MOL-RAO observatory showed that the system can accurately predict wind speed and direction. A modified DJI S900 hexacopter with a Styrofoam sphere casing was used for the study and calibrated for wind speeds between 1 and 14 m s−1. Power spectral density analysis showed the system’s ability to resolve atmospheric eddies up to 0.1 Hz. The overall root-mean-square error was less than 0.7 m s−1 for wind speed and less than 8° for wind direction.

Assessment of aerosol optical and physical properties and implications for radiative effects over the semiarid region of Indo‐Gangetic Basin

This study assesses the physical and optical properties and estimated the radiative forcing of aerosol at Agra over the Indo‐Gangetic Basin (IGB) during July 2016–December 2019 using black carbon (BC) mass concentration (AE‐33 aethalometer), data sets from satellite and model simulations. The optical properties of aerosol and radiative forcing have been measured by the Optical and Physical Properties of Aerosols and Clouds (OPAC) and Santa Barbara Discrete Ordinate Radiative Transfer Atmospheric Radiative Transfer (SBDART) model. The high BC mass concentration has been observed in November and lowest in August. An adverse meteorological condition due to a combination of temperature and low wind speed results in poor dispersion in the wintertime is a common factor for high concentration level pollutants over Agra. The diurnal and temporal cycle of BC mass concentration exhibits a high concentration at nighttime due to the lower atmospheric boundary layer. The seasonal variation of absorption coefficient (βabs) and Absorption Angstrom Exponent (AAE) is found to be higher during post‐monsoon and lowest in monsoon season. This suggests that black carbon concentration over Agra is mainly generated from crop burning, waste burning, automobile exhaust and long‐range transport from Punjab and Haryana as the present site is downwind. OPAC‐derived aerosol optical depth (AOD), single‐scattering albedo (SSA), Angstrom Exponent (AE) and asymmetry parameter (AsyP) were estimated to be 0.57 ± 0.07, 0.78 ± 0.16, 0.99 ± 0.21 and 0.81 ± 0.15, respectively. AOD and AE from the OPAC and the moderate resolution imaging spectroradiometer (MODIS) have shown the consistent relationship. The mean radiative forcing is 18.3 ± 2.1 W m−2 at the top of the atmosphere while, at the surface, net radiative forcing is −42.4 ± 7.2 and 59.1 ± 6.5 W m−2 at the atmosphere during the study period. Vertical profiles were estimated using the observations from Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the change in heating rate from the SBDART model over Agra.

Simulation of Anthropogenic CO2 Emissions in the Yangtze River Delta Based on Different Emission Inventories

Nowadays, great uncertainty still exists on the urban- and regional-scale anthropogenic CO2 emission estimation based on emission inventories. In order to achieve the carbon peaking and neutrality targets for China, it is urgent to accurately estimate anthropogenic CO2 emissions at regional scales, especially in large urban agglomerations. Using two inventories (EDGAR v6.0 inventory and a modified inventory combining EDGAR v6.0 with GCG v1.0) as prior anthropogenic CO2 emission datasets andtaking themas input data respectively, this study utilized the WRF-STILT atmospheric transport model to simulate atmospheric CO2 concentration in the Yangtze River Delta region from December 2017 to February 2018. The simulated atmospheric CO2 concentrations were further improved by referencing atmospheric CO2 concentration observation at a tall tower in Quanjiao County of Anhui Province and using the scaling factors obtained from the Bayesian inversion method. An estimation of anthropogenic CO2 emission flux in the Yangtze River Delta regionwas finally accomplished. The results indicated that:①in winter, in comparison to the atmospheric CO2 concentration simulated based on EDGAR v6.0, the atmospheric CO2 concentration simulated based on the modified inventory was more consistent with observed values. ②The simulated atmospheric CO2 concentration was higher than observation at night and lower than observation during the daytime. The CO2 emission data of emission inventories could not fully reflect the diurnal variation in anthropogenic emissions, andtheoverestimation, caused by the simulated low-atmospheric boundary layer height at night, of the contribution from point sources with higher emission height near the observation station were the main reasons. ③The simulation performance on atmospheric CO2 concentration was greatly affected by the emission bias of the EDGAR grid points that significantly contributed to concentrations of the observation station, and this indicated that the uncertainty in the spatial distribution in EDGAR emission was the main factor influencing the simulation accuracy. ④The posterior anthropogenic CO2 emission flux in the Yangtze River Delta from December 2017 to February 2018 was around (0.184±0.006) mg·(m2·s)-1and (0.183±0.007) mg·(m2·s)-1 based on EDGAR and the modified inventory, respectively. It is suggested that the inventories with higher temporal and spatial resolutions and more accurate spatial emission distribution should be selected as the prior emissions to obtain a more accurate estimation of the regional anthropogenic CO2 emissions.

UAV-based sampling systems to analyse greenhouse gases and volatile organic compounds encompassing compound-specific stable isotope analysis

Abstract. The study herein reports on the development and testing of sampling systems (and subsequent analytical setups) that were deployed on an unmanned aerial vehicle (UAV) for the purpose of analysing greenhouse gases (GHGs) and volatile organic compounds (VOCs) in the lower atmospheric boundary layer. Two sampling devices, both of which can be mounted to an UAV with a payload capability greater than 1 kg, were tested for respective sampling and analysis of specific GHGs (carbon dioxide, CO2, and methane, CH4) and VOCs (chlorinated ethenes, CEs). The gas analyses included measurements of the molar amounts and the respective stable carbon isotope ratios. In addition to compound calibration in the laboratory, the functionality of the samplers and the UAV-based sampling was tested in the field. Atmospheric air was either flushed through sorbent tubes for VOC sampling or collected and sampled in glass vials for GHG analysis. The measurement setup for the sorbent tubes achieved analyte mass recovery rates of 63 %–100 % (more favourable for lower chlorinated ethenes), when prepared from gaseous or liquid calibration standards, and reached a precision (2σ) better than 0.7 ‰ for δ13C values in the range of 0.35–4.45 nmol. The UAV-equipped samplers were tested over two field sampling campaigns designed to (1) compare manual and UAV-collected samples taken up a vertical profile at a forest site and (2) identify potential emissions of CO2, CH4 or VOC from a former domestic waste dump. The precision of CO2 measurements from whole air samples was ≤7.3 µmol mol−1 and ≤0.3 ‰ for δ13C values and ≤0.03 µmol mol−1 and ≤0.2 ‰ for CH4 working gas standards. The results of the whole air sample analyses for CO2 and CH4 were sufficiently accurate to detect and localise potential landfill gas emissions from a secured former domestic waste dump using level flight. Vertical CO2 profiles from a forest location showed a causally comprehensive pattern in the molar ratios and stable carbon isotope ratios but also the potential falsification of the positional accuracy of a UAV-assisted air sample due to the influence of the rotor downwash. The results demonstrate that the UAV sampling systems presented here represent a viable tool for atmospheric background monitoring, as well as for evaluating and identifying emission sources. By expanding the part of the lower atmosphere that can be practicably sampled over horizontal and vertical axes, the presented UAV-capable sampling systems, which also allow for compound-specific stable isotope analysis (CSIA), may facilitate an improved understanding of surface–atmosphere fluxes of trace gas.

A Review on Atmospheric Dispersion System for Air Pollutants Integrated with GIS in Urban Environment

The objective of this article is to present comprehensive findings and analysis of studies performed on air pollutant dispersion in urban environments. It captures India’s rising environmental pollution due to urbanization, industrialization, and population growth. Dispersion of pollutants due to the wind in the lower Atmospheric Boundary Layer (ABL) is a major concern nowadays. The dispersion field around the buildings is a critical parameter to analyze and it primarily depends on the correct simulation of the wind flow structure. Therefore, studies performed on this in past years are being reviewed. Additionally, a brief review of different air dispersion models that are integrated with the Geographic Information System (GIS) has been studied in this article to assess the exposure. The results of these studies provide the urban air dispersion model aligning to three sub-models i.e., Emission, Weather Prediction, and Dispersion models. Various factors like wind speed, wind direction, cloud cover, traffic emission, disposal of waste, transportation, and others are considered. This study also captures the problems and risks being faced while creating a model, and its possible mitigation approaches.

Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime

Abstract. The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models (ESMs). State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land–atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information on the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land–atmosphere interactions. In order to account for the subgrid-scale heterogeneity in land–atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth system model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. The E3SMv1 single-column model (SCM) simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL on non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than the variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path (LWP). These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land–atmosphere coupling in next-generation ESMs.

A Novel Computational Approach for an Improved Expression of the Spectral Content in the Lower Atmospheric Boundary Layer

The paper presents an innovative methodology for the simulation of incoming wind conditions in computational domains that use large eddy simulation (LES) for the evaluation of wind loads on low-rise buildings. Simulating the atmospheric boundary layer has proven to be a challenging process for computational wind engineering, especially to correctly introduce the fluctuations in the high-frequency spectral domain. Experiments in the Concordia University Building Aerodynamics Laboratory were carried out to estimate the evolution of turbulence features in the along-wind direction of a generic profile. Virtual probes were placed inside the computational domain to match the location of those in the wind tunnel and compare mean speed values, turbulence intensity, integral length scales, and spectral content. Synthetic methods were applied for the incoming wind velocity to estimate their capacity to capture the evolution of these turbulence features in the streamwise direction. The inability of these synthetic methods to represent the spectral domain, particularly for heights of interest for low-rise buildings, was examined, and the so-called dynamic terrain method in which velocity time histories are extracted from wind tunnel measurements and reconstructed to fit certain statistical parameters was implemented. The proposed method represents the frequency domain’s spectral content with good agreement with the theoretical von Karman spectrum and the experimental results. Advantages of the method include time efficiency and relative simplicity, which makes it attractive to the practitioners for the design of a neutral atmospheric boundary layer respecting the turbulent wind characteristics.

Field Study of Turbulence Intensity measurement by Nacelle Mounted Lidar (NML)

In this paper, Nacelle Mounted LiDAR (NML) was used to study Turbulence Intensity (TI) by dataset from three measurement campaigns, using two approaches: the white box test and the black box test. The white box test was to compare TI LOS using each Line Of Sight, while the black box test was to compare TI Hub using all LOS by relative reconstruction algorithm at wind turbine hub height. The result of white box test showed that the correlation coefficient of TI LOS varied from 0.923 to 0.955 and the slope varied from 0.978 to 1.030. The result of black box test showed that the correlation coefficient of TI Hub is 0.8337∼0.8924 and the slope is 0.904∼0.935. This study provided some promising results to wind energy community, which could be the evidence base for the further investigation for the temporal-spatial turbulence structure in low Atmospheric Boundary Layer.

Two Typical Patterns of Regional PM2.5 Transport for Heavy Air Pollution Over Central China: Rapid Transit Transport and Stationary Accumulation Transport

The regional transport of air pollutants has been identified as a critical factor that affects air quality over downwind receptor areas; however, the regional transport patterns for air pollution episodes remain poorly understood. In this study, we identified two distinct patterns of regional transport: rapid transit transport (RTT) and stationary accumulation transport (SAT), both of which induced severe PM2.5 pollution episodes in central China during 2015–2020. The differences and similarities between the two regional transport patterns of air pollution were characterized by their influencing meteorological factors. Similar meteorological conditions trigger the RTT and SAT, with a high-PM2.5 concentration air mass from the upstream regions transported to the Twain-Hu Basin (THB) by the strong northerly winds with a southward advance of cold air mass. The average rate of increase in the PM2.5 concentration of the RTT (12.5 μg/m3/h) is more than that of the SAT (5.7 μg/m3/h). However, meteorological conditions evolved differently in RTT and SAT. For RTT with the fast passage of cold air, the THB is located behind the strong cold front during the later stage, and these events rapidly ended owing to the northerly winds and wet scavenging of precipitation. For SAT with the slow cold air accumulation, the THB is mainly occupied by a weak high-pressure system with low wind speeds, strong descending airflow, and a low atmospheric boundary layer height, trapping the air pollutants accumulated in the THB and resulting in persistent heavy pollution incidents. This study provides new insights into the meteorological mechanism underlying the formation of severe air pollution episodes over a receptor region owing to the regional transport patterns of air pollutants.

Development and Calibration of Pressure-Temperature-Humidity (PTH) Probes for Distributed Atmospheric Monitoring Using Unmanned Aircraft Systems.

Small unmanned aircraft systems (UAS) are increasingly being used for meteorology and atmospheric monitoring. The ease of deployment makes distributed sensing of parameters such as barometric pressure, temperature, and relative humidity in the lower atmospheric boundary layer feasible. However, constraints on payload size and weight, and to a lesser extent power, limit the types of sensors that can be deployed. The objective of this work was to develop a miniature pressure-temperature-humidity (PTH) probe for UAS integration. A set of eight PTH probes were fabricated and calibrated/validated using an environmental chamber. An automated routine was developed to facilitate calibration and validation from a large set of temperature and relative humidity setpoints. Linear regression was used to apply temperature and relative humidity calibrations. Barometric pressure was calibrated using a 1-point method consisting of an offset. The resulting PTH probes were less than 4 g in mass and consumed less than 1 mA when operated from a 5 VDC source. Measurements were transmitted as a formatted string in ASCII format at 1 Hz over a 3.3 V TTL UART. Prior to calibration, measurements between individual PTH probes were significantly different. After calibration, no significant differences in temperature measurements across all PTH probes were observed, and the level of significance between PTH probes was reduced. Actual differences between calibrated PTH probes were likely to be negligible for most UAS-based applications, regardless of significance. RMSE across all calibrated PTH probes for the pressure, temperature, and relative humidity was less than 31 Pa, 0.13 °C, and 0.8% RH, respectively. The resulting calibrated PTH probes will improve the ability to quantify small variations in ambient conditions during coordinated multi-UAS flights.

Turbulence of Landward and Seaward Wind during Sea-Breeze Days within the Lower Atmospheric Boundary Layer

Reynolds stress anisotropy is estimated from the stress spheroids, based on 20 Hz ultrasonic anemometer measurements, performed in the coastal area of northern France, over a 1.5-year long period. Size and shape variation (i.e., prolate, oblate, disk, rod, etc.) of stress spheroids are used for the characterization of energy redistribution by turbulent eddies. The sea-breeze (SB) events were identified using a change in wind direction from seaward (SWD) to landward (LWD) during the day time. We found that the LWD wind creates more turbulent anisotropic states than SWD wind. The prolate-shaped stress spheroids correspond to small-scale turbulence observed during LWD wind, while oblate spheroids are found during SWD winds. Moreover, it was found that during LWD winds, large turbulence kinetic energy (TKE) in the flow field produces large stress spheroids. On the contrary, during SWD winds, a smaller level of TKE is responsible for small-size stress spheroid formation. The average volume of the corresponding Reynolds stress spheroids during the LWD is 13% larger than that of during SWD wind.

Analysis of Atmospheric Stability for the Prevention of Coastal Disasters and the Development of Efficient Coastal Renewable Energy

Kim, H.; Moon, C.-J.; Kim, Y.-G.; Chon, K.-H.; Joo, J.Y., and Ryu, G.H., 2021. Analysis of atmospheric stability for the prevention of coastal disasters and the development of efficient coastal renewable energy. In: Lee, J.L.; Suh, K.S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 241–245. Coconut Creek (Florida), ISSN 0749–0208. The ground friction force is lower in coastal and marine areas than it is on land, and there is a relatively high frequency of strong winds in such areas, which substantially affects the life and stability of wind turbines. In particular, the strong wind at the bottom of the atmospheric boundary layer is generated by a combination of thermal and mechanical factors, so there is always a risk due to vertical wind shear and strong turbulent gusts. Therefore, to prevent physical loss of wind turbines located in the atmospheric boundary layer, it is necessary to analyze the wind condition through a more accurate atmospheric stability analysis. In this study, observation data from the Boseong Standard Meteorological Tower are examined to select strong wind cases in the lower atmospheric boundary layer, and the vertical distribution characteristics of the wind resources are analyzed according to the Monin-Obukhov length (MOL). The results confirmed that the vertical wind velocity gradient caused by atmospheric stability mainly changes when the atmosphere is in the near-neutral state at night during the winter.

Impact of the Nocturnal Low-Level Jet and Orographic Waves on Turbulent Motions and Energy Fluxes in the Lower Atmospheric Boundary Layer

The nocturnal low-level jet (LLJ) and orographic (gravity) waves play an important role in the generation of turbulence and pollutant dispersion and can affect the energy production by wind turbines. Additionally, gravity waves have an influence on the local mixing and turbulence within the surface layer and the vertical flux of mass into the lower atmosphere. On 25 September 2017, during a field campaign, a persistent easterly LLJ and gravity waves were observed simultaneously in a coastal area in the north of France. We explore the variability of the wind speed, turbulent eddies, and turbulence kinetic energy in the time–frequency and space domain using an ultrasonic anemometer and a scanning wind lidar. The results reveal a significant enhancement of the turbulence-kinetic-energy dissipation (by 50%) due to gravity waves in the LLJ shear layer (below the jet core) during the period of wave propagation. Large magnitudes of zonal and vertical components of the shear stress (approximately 0.4 and 1.5 m2 s−2, respectively) are found during that period. Large eddies (scales of 110 to 280 m) matching the high-wind-speed regime are found to propagate the momentum downwards, which enhances the mass transport from the LLJ shear layer to the roughness layer. Furthermore, these large-scale eddies are associated with the crests while comparatively small-scale eddies are associated with the troughs of the gravity wave.

Observations of Sweep–Ejection Dynamics for Heat and Momentum Fluxes during Wildland Fires in Forested and Grassland Environments

AbstractThe vertical turbulent transfer of heat and momentum in the lower atmospheric boundary layer is accomplished through intermittent sweep, ejection, outward interaction, and inward interaction events associated with turbulent updrafts and downdrafts. These events, collectively referred to as sweep–ejection dynamics, have been studied extensively in forested and nonforested environments and reported in the literature. However, little is known about the sweep–ejection dynamics that occur in response to turbulence regimes induced by wildland fires in forested and nonforested environments. This study attempts to fill some of that knowledge gap through analyses of turbulence data previously collected during three wildland (prescribed) fires that occurred in grassland and forested environments in Texas and New Jersey. Tower-based high-frequency (10 or 20 Hz) three-dimensional wind-velocity and temperature measurements are used to examine frequencies of occurrence of sweep, ejection, outward interaction, and inward interaction events and their actual contributions to the mean vertical turbulent fluxes of heat and momentum before, during, and after the passage of fire fronts. The observational results suggest that wildland fires in these environments can substantially change the sweep–ejection dynamics for turbulent heat and momentum fluxes that typically occur when no fires are present, especially the relative contributions of sweeps versus ejections in determining overall heat and momentum fluxes.

Formation mechanism of a severe air pollution event: A case study in the Sichuan Basin, Southwest China

The formation mechanism of air pollution events in the Sichuan Basin (SB), which is the fourth most heavily polluted area in China, has not been fully revealed. This study investigated the formation mechanism of a severe air pollution event over the SB using synoptic approaches and model simulations. The results can be summarized as follows: (1) Heavy air pollution in the SB was characterized by low visibility, low atmospheric boundary layer (ABL) height, high temperature, high relative humidity, strong temperature inversion layer, subsidence in the troposphere, high water vapor content between 500 and 900 hPa, southerly winds in the low troposphere, and surface winds with low speed and irregular direction. (2) Air quality in the SB was closely related to the weather system at 700 hPa over the basin. When the 700 hPa weather system affecting the SB was a high-pressure system, the subsidence and stable atmospheric stratification increased the air pollutant concentrations near the ground. When the 700 hPa weather system affecting the SB was a low-pressure system and the basin was in front of this low-pressure system, southwesterly warm and moist airflow and adiabatic subsidence warming formed the thick temperature inversion layer over the basin. As a result, the temperature inversion layer trapped air pollutants in the basin and induced the heavy air pollution event. When the 700 hPa weather system over the SB was a low-pressure system and the basin was behind the low-pressure system, the dry and cold airflow from the north invaded southward to the basin and broke the temperature inversion layer. Consequently, air pollutants dispersed vertically, resulting in decreased concentrations near the ground. (3) Air pollutants from December 17, 2017 to January 4, 2018 were mainly from local emissions. (4) The WRF-Chem model not only reproduced the variations in PM2.5 concentrations, the ABL height, and the height-time cross-sections of temperature, water vapor content, and wind over Chengdu during the air pollution event, but also revealed the formation mechanism of this heavy air pollution event. The results of this study reveal the formation mechanism of winter heavy air pollution events over the SB and help develop effective regional air quality management strategies to reduce the likelihood of local air pollution events and minimize the adverse impacts of air pollution.

A comparison of PM<sub>2.5</sub>-bound polycyclic aromatic hydrocarbons in summer Beijing (China) and Delhi (India)

Abstract. Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants in air, soil, and water and are known to have harmful effects on human health and the environment. The diurnal and nocturnal variations of 17 PAHs in ambient particle-bound PAHs were measured in urban Beijing (China) and Delhi (India) during the summer season using gas-chromatography–quadrupole time-of-flight mass spectrometry (GC-Q-TOF-MS). The mean concentration of particles less than 2.5 µm (PM2.5) observed in Delhi was 3.6 times higher than in Beijing during the measurement period in both the daytime and night-time. In Beijing, the mean concentration of the sum of the 17 PAHs (∑17 PAHs) was 8.2 ± 5.1 ng m−3 in daytime, with the highest contribution from indeno[1,2,3-cd]pyrene (12 %), while at night-time the total PAHs was 7.2 ± 2.0 ng m−3, with the largest contribution from benzo[b]fluoranthene (14 %). In Delhi, the mean ∑17 PAHs was 13.6 ± 5.9 ng m−3 in daytime and 22.7 ± 9.4 ng m−3 at night-time, with the largest contribution from indeno[1,2,3-cd]pyrene in both the day (17 %) and night (20 %). Elevated mean concentrations of total PAHs in Delhi observed at night were attributed to emissions from vehicles and biomass burning and to meteorological conditions leading to their accumulation from a stable and low atmospheric boundary layer. Local emission sources were typically identified as the major contributors to total measured PAHs in both cities. Major emission sources were characterized based on the contribution from each class of PAHs, with the four-, five- and six-ring PAHs accounting ∼ 95 % of the total PM2.5-bound PAHs mass in both locations. The high contribution of five-ring PAHs to total PAH concentration in summer Beijing and Delhi suggests a high contribution from petroleum combustion. In Delhi, a high contribution from six-ring PAHs was observed at night, suggesting a potential emission source from the combustion of fuel and oil in power generators, widely used in Delhi. The lifetime excess lung cancer risk (LECR) was calculated for Beijing and Delhi, with the highest estimated risk attributed to Delhi (LECR = 155 per million people), which is 2.2 times higher than the Beijing risk assessment value (LECR = 70 per million people). Finally, we have assessed the emission control policies in each city and identified those major sectors that could be subject to mitigation measures.