Aerosol Extinction Coefficient Profiles Research Articles

Multi-wavelength dataset of aerosol extinction profiles retrieved from GOMOS stellar occultation measurements

Abstract. In this paper, we present the new multi-wavelength dataset of aerosol extinction profiles, which are retrieved from the averaged transmittance spectra by the Global Ozone Monitoring by Occultation of Stars instrument aboard the Envisat satellite. Using monthly and zonally averaged transmittances as a starting point for the retrievals enables us to improve the signal-to-noise ratio and eliminate possible modulation of transmittance spectra by uncorrected scintillations. The two-step retrieval method is used: the spectral inversion is followed by the vertical inversion. The spectral inversion relies on the removal of contributions from ozone, NO2, NO3 and Rayleigh scattering from the optical depth spectra for each ray perigee altitude. In the vertical inversion, the profiles of aerosol extinction coefficients at several wavelengths are retrieved from the collection of slant aerosol optical depth profiles. The retrieved aerosol extinction profiles (FMI-GOMOSaero dataset v1) are provided in the altitude range 10–40 km at wavelengths of 400, 440, 452, 470, 500, 525, 550, 672 and 750 nm for the whole GOMOS operating period from August 2002 to March 2012. Extensive intercomparisons of the retrieved FMI-GOMOSaero aerosol profiles with aerosol profile data from other satellite instruments at several wavelengths have been performed. It is found that the average difference between FMI-GOMOSaero and other datasets is within 20 %–40 % in the lower and middle stratosphere, the standard deviation is ∼ 20 %–50 %, and the correlation coefficient of the time series is 0.65–0.85. The created FMI-GOMOSaero dataset can be used in merged datasets of stratospheric aerosols. It might be also used as a priori information for satellite retrievals during 2002–2012.

Assessment of smoke plume height products derived from multisource satellite observations using lidar-derived height metrics for wildfires in the western US

Abstract. As wildfires intensify and fire seasons lengthen across the western US, the development of models that can predict smoke plume concentrations and track wildfire-induced air pollution exposures has become critical. Wildfire smoke plume height is a key indicator of the vertical placement of plume mass emitted from wildfire-related aerosol sources in climate and air quality models. With advancements in Earth observation (EO) satellites, spaceborne products for aerosol layer height or plume injection height have recently emerged with increased global-scale spatiotemporal resolution. However, to evaluate column radiative effects and refine satellite algorithms, vertical profiles of regionally representative aerosol properties from wildfires need to be measured directly. In this study, we conducted the first comprehensive evaluation of four passive satellite remote-sensing techniques specifically designed for retrieving plume height. We compared these satellite products with the airborne Wyoming Cloud Lidar (WCL) measurements during the 2018 Biomass Burning Flux Measurements of Trace Gases and Aerosols (BB-FLUX) field campaign in the western US. Two definitions, namely, “plume top” and “extinction-weighted mean plume height”, were used to derive the representative heights of wildfire smoke plumes, based on the WCL-derived vertical aerosol extinction coefficient profiles. Using these two definitions, we performed a comparative analysis of multisource satellite-derived plume height products for wildfire smoke. We provide a discussion related to which satellite product is most appropriate for determining plume height characteristics near a fire event or estimating downwind plume rise equivalent height, under multiple aerosol loadings. Our findings highlight the importance of understanding the sensitivity of different passive remote-sensing techniques on space-based wildfire smoke plume height observations, in order to resolve ambiguity surrounding the concept of “effective smoke plume height”. As additional aerosol-observing satellites are planned in the coming years, our results will inform future remote-sensing missions and EO satellite algorithm development. This bridges the gap between satellite observations and plume rise modeling to further investigate the vertical distribution of wildfire smoke aerosols.

Aerosol Vertical Structure and Optical Properties during Two Dust and Haze Episodes in a Typical Valley Basin City, Lanzhou of Northwest China

The vertical profiles of aerosol optical properties are vital to clarify their transboundary transport, climate forcing and environmental health influences. Based on synergistic measurements of multiple advanced detection techniques, this study investigated aerosol vertical structure and optical characteristics during two dust and haze events in Lanzhou of northwest China. Dust particles originated from remote deserts traveled eastward at different altitudes and reached Lanzhou on 10 April 2020. The trans-regional aloft (~4.0 km) dust particles were entrained into the ground, and significantly modified aerosol optical properties over Lanzhou. The maximum aerosol extinction coefficient (σ), volumetric depolarization ratio (VDR), optical depth at 500 nm (AOD500), and surface PM10 and PM2.5 concentrations were 0.4~1.5 km−1, 0.15~0.30, 0.5~3.0, 200~590 μg/m3 and 134 μg/m3, respectively, under the heavy dust event, which were 3 to 11 times greater than those at the background level. The corresponding Ångström exponent (AE440–870), fine-mode fraction (FMF) and PM2.5/PM10 values consistently persisted within the ranges of 0.10 to 0.50, 0.20 to 0.50, and 0.20 to 0.50, respectively. These findings implied a prevailing dominance of coarse-mode and irregular non-spherical particles. A severe haze episode stemming from local emissions appeared at Lanzhou from 30 December 2020 to 2 January 2021. The low-altitude transboundary transport aerosols seriously deteriorated the air quality level in Lanzhou, and aerosol loading, surface air pollutants and fine-mode particles strikingly increased during the gradual strengthening of haze process. The maximum AOD500, AE440–870nm, FMF, PM2.5 and PM10 concentrations, and PM2.5/PM10 were 0.65, 1.50, 0.85, 110 μg/m3, 180 μg/m3 and 0.68 on 2 January 2021, respectively, while the corresponding σ and VDR at 0.20–0.80 km height were maintained at 0.68 km−1 and 0.03~0.12, implying that fine-mode and spherical small particles were predominant. The profile of ozone concentration exhibited a prominent two-layer structure (0.60–1.40 km and 0.10–0.30 km), and both concentrations at two heights always remained at high levels (60~72 μg/m3) during the entire haze event. Conversely, surface ozone concentration showed a significant decrease during severe haze period, with the peak value of 20~30 μg/m3, which was much smaller than that before haze pollution (~80 μg/m3 on 30 December). Our results also highlighted that the vertical profile of aerosol extinction coefficient was a good proxy for evaluating mass concentrations of surface particulate matters under uniform mixing layers, which was of great scientific significance for retrieving surface air pollutants in remote desert or ocean regions. These statistics of the aerosol vertical profiles and optical properties under heavy dust and haze events in Lanzhou would contribute to investigate and validate the transboundary transport and radiative forcing of aloft aerosols in the application of climate models or satellite remote sensing.

Comparative Analysis of Aerosol Vertical Characteristics over the North China Plain Based on Multi-Source Observation Data

In this paper, multi-source observation, such as aircraft, ground-based remote sensing, and satellite-retrieved data, has been utilized to compare and analyze the vertical characteristics of aerosol optical properties and the planetary boundary layer height (HPBL) over the North China Plain (NCP) region during May–June 2016. Aircraft observations show the vertical profiles of aerosol absorption coefficients (σabs), scattering coefficients (σsca), and extinction coefficients (σext) gradually decrease with altitude, with their maximum values near HPBL. The vertical profiles of σext depended most on the vertical distribution of measured σsca, indicating a significant contribution of scattering aerosols. In addition, the prominent characteristic of the inverse relationship between σext and moisture profile could serve as a reference for predicting air quality in the NCP region. The lower layer pollution during the field experiment was likely caused by the accumulation of fine-mode aerosols, characterized by the vertical distribution of the Ångström exponent and the Aerosol Robotic Network (AERONET) products. Typically, HPBL derived from aircraft and surface Micro Pulse Lidar (MPL) was approximate, while the predicted HPBL by meteorological data indicates an underestimation of ~192 m. Aerosol optical depth (AOD) calculated from aircraft and ground-based remote sensing (such as MPL and AERONET) experienced a strong correlation, and both of them exhibited a similar tendency. However, the AOD retrieved from satellites was significantly larger than that from aircraft and ground-based remote sensing. Overall, the inversion algorithm, cloud identification algorithm, representativeness of the space, and time of the observation may lead to an overestimation or underestimation of AOD under certain circumstances. This study may serve as a re-evaluation of AOD retrieved from multi-source observations and provide a reference to uncover the actual atmospheric environment in the NCP regions.

Assessment of vertical characterization and potential sources of aerosols in different altitude layers: Combined application of MAX-DOAS observation and the 3D-CWT model

Vertical distribution is essential for understanding the regional transport sources of pollutants accumulated at different altitudes. We investigate aerosol extinction coefficient (AEC) profiles based on ground-based multi-Axis differential optical absorption spectroscopy measurements from August 2020 to June 2021 in Ningbo, East China. AEC vertical structures can be classified into three groups: decreasing with height (51.2%), well-mixed (2.4%), and inverse structures (46.4%), which can be explained by long-range transport, the planetary boundary layer heigh, and temperature inversion. Except in the winter, the vertical profile of the AEC typically extends to higher altitudes, which suggests the accumulation, secondary formation, or long-range transport of aerosols at higher altitudes. The three-dimensional concentration weighted trajectory (3D-CWT) model is utilized to elucidate not only altitudinal atmospheric layers in which aerosol transport occurs, but also the potential source areas of aerosols at multiple air mass arrival altitudes. The 3D-CWT model results indicate the long-range transport of aerosols, mainly through backward air mass trajectories within layers 1 (0–500 m) and 2 (500–1000 m). The potential source areas of aerosols at lower altitudes are mainly distributed in the North China Plain. At air mass arrival altitudes exceeding 600 m, the sources likely to affect aerosols in Ningbo are both land-sourced and marine-sourced (including the East China Sea, Yellow Sea, and the marginal sea between Korea and Japan) air flows. At different air mass arrival altitudes, the estimated contributions of long-range transport to aerosols are approximately 6% (200 m), 11% (600 m), and 18% (1000 m). Our findings provide a scientific basis for revealing different aerosol vertical structures and assessing long-range transport contributions in coastal urban areas.

Retrieval of the aerosol extinction coefficient from scanning Scheimpflug lidar measurements for atmospheric pollution monitoring

In this work, an 808-nm Scheimpflug lidar (SLidar) system, employing a laser diode as the light source and an image sensor as the detector, has been utilized for practical applications of air pollution monitoring in urban area. A comprehensive retrieval method has been proposed and developed for reliable and automatic retrieval of the aerosol extinction coefficient (AEC) from near-horizontal scanning SLidar measurements. The characteristics of the pixel-intensity curves measured by the SLidar system have been statistically examined, and a quality control process is developed to eliminate abnormal lidar profiles. An improved Douglas-Pucker algorithm has been utilized for the determination of the boundary value of the AEC. The AEC profile is thus obtained according to the Klett method with the boundary value as the input. Meanwhile, an angular iterative retrieval (AIR) algorithm has been developed with the AECs at neighboring scanning angles as references, which is able to significantly improve the retrieval reliability of the AEC for each scanning angle. Comparison studies with a local pollution monitoring station have also been carried out to verify the present retrieval method. Besides, the Scheimpflug lidar technique in combination with the retrieval method has shown promising performance in tracking pollution sources in urban area.

Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic

Abstract. Accurately capturing cloud condensation nuclei (CCN) concentrations is key to understanding the aerosol–cloud interactions that continue to feature the highest uncertainty amongst numerous climate forcings. In situ CCN observations are sparse, and most non-polarimetric passive remote sensing techniques are limited to providing column-effective CCN proxies such as total aerosol optical depth (AOD). Lidar measurements, on the other hand, resolve profiles of aerosol extinction and/or backscatter coefficients that are better suited for constraining vertically resolved aerosol optical and microphysical properties. Here we present relationships between aerosol backscatter and extinction coefficients measured by the airborne High Spectral Resolution Lidar 2 (HSRL-2) and in situ measurements of CCN concentrations. The data were obtained during three deployments in the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project, which took place over the southeast Atlantic (SEA) during September 2016, August 2017, and September–October 2018. Our analysis of spatiotemporally collocated in situ CCN concentrations and HSRL-2 measurements indicates strong linear relationships between both data sets. The correlation is strongest for supersaturations (S) greater than 0.25 % and dry ambient conditions above the stratocumulus deck, where relative humidity (RH) is less than 50 %. We find CCN–HSRL-2 Pearson correlation coefficients between 0.95–0.97 for different parts of the seasonal burning cycle that suggest fundamental similarities in biomass burning aerosol (BBA) microphysical properties. We find that ORACLES campaign-average values of in situ CCN and in situ extinction coefficients are qualitatively similar to those from other regions and aerosol types, demonstrating overall representativeness of our data set. We compute CCN–backscatter and CCN–extinction regressions that can be used to resolve vertical CCN concentrations across entire above-cloud lidar curtains. These lidar-derived CCN concentrations can be used to evaluate model performance, which we illustrate using an example CCN concentration curtain from the Weather Research and Forecasting Model coupled with physics packages from the Community Atmosphere Model version 5 (WRF-CAM5). These results demonstrate the utility of deriving vertically resolved CCN concentrations from lidar observations to expand the spatiotemporal coverage of limited or unavailable in situ observations.

Vertical distribution of aerosol extinction coefficients at night derived from radiometry of scattered laser light

Determining the nighttime aerosol extinction coefficient profile in the lower atmosphere through optical measurements is a necessary but challenging task in environmental science due, among other factors, to the lack of a suitable extra-atmospheric night light source. In this work we present a method for retrieving the vertical distribution of the aerosol extinction coefficient via light scattered from a low-divergence light beam. We demonstrate its practical implementation using a low-power, portable green laser light source to sample the air column and an off-the-shelf, wide-angle digital camera located a few hundred meters away as detector. The light scattered off the laser beam in the direction toward the camera contains enough information to retrieve the aerosol extinction profile by inverting the integral equation relating the radiance of the recorded beam image to the aerosol distribution. An efficient and robust numerical inversion procedure is developed and demonstrated here. This approach can be used both in permanent measurement facilities or in mobile stations, and it facilitates the task of characterizing nighttime aerosols both on-demand or in the framework of routine environmental monitoring protocols.

Improved Aerosol Lidar Ratio Profile by Introducing Pseudo-Constant

Aerosol lidar ratio (LR) is important for inversion of aerosol optical characteristics. Single aerosol LR value adopted in the inversion not only causes difficulties in improving aerosol inversion accuracy but also hinders the analysis of aerosol types. In this paper, a pseudo-constant method with certain universality is proposed for inverting aerosol LR profiles. Simulation results show a decrease in the mean absolute error (MAE) of the aerosol LR from 3.57% (iteration method) and 9.96% (Fernald method) to 1.82% (pseudo-constant method). In the near-surface region (<1.5 km), the MAE of aerosol LR decreases from 4.97% (iteration) and 21.66% (Fernald) to 1.54% (pseudo-constant). Moreover, the inversion accuracy of aerosol LR obtained from pseudo-constant method is less influenced by the precision of the pre-estimated aerosol LR value than that from iteration method. Experimentally, the aerosol LR and aerosol extinction coefficient profiles obtained from the pseudo-constant method are more accurate than those from the iteration and Fernald methods. In addition, both the simulations and experiments indicate that the pseudo-constant method has higher efficiency; the processing time is shortened from approximately 5 s per signal (iteration) to approximately 0.1 s per signal. Finally, aerosol types can be distinguished to a certain degree by combining the improved aerosol LR profile.

Stratospheric Aerosol Characteristics from the 2017–2019 Volcanic Eruptions Using the SAGE III/ISS Observations

In recent years (2017–2019), several moderate volcanic eruptions and wildfires have perturbed the stratospheric composition and concentration with distinct implications on radiative forcing and climate. The Stratospheric Aerosol and Gas Experiment III instruments onboard the International Space Station (SAGE III/ISS) have been providing aerosol extinction coefficient (EC) profiles at multiple wavelengths since June 2017. In this study, a method to invert the spectral stratospheric aerosol optical depth (sAOD) or EC values from SAGE III/ISS (to retrieve the number/volume size distributions and other microphysical properties) is presented, and the sensitivity of these retrievals is evaluated. It was found that the retrievals are strongly dependent on the choices of wavelengths, which in turn determine the shapes of the calculated curves. Further, we examine the changes in stratospheric aerosol spectral behavior, size distribution properties, time evolution (growth/decay) characteristics associated with subsequent moderate volcanic eruptions, namely, Ambae (15∘S, 167∘E; April and July 2018), Raikoke (48∘N, 153∘E; June 2019), and Ulawun (5∘S, 151∘E; June and August 2019), in different spatial regions. The observational period was classified with reference to Ambae eruptions into four phases (pre-Ambae, Ambae1, Ambae2, and post-Ambae). The pre-Ambae and post-Ambe periods comprise the 2017 Canadian fires and 2019 Raikoke/Ulawun eruptions, respectively. The spectral dependence of sAOD was comparable and lowest during the pre-Ambae and Ambae1 periods in all regions. The number concentration at the principal mode radius (between 0.07 and 0.2 μm) was observed to be higher during the Ambae2 period over the Northern Hemisphere (NH). The rate of change (growth/decay) in the sAOD on a global scale resembled the changes in the Southern Hemisphere (SH), unlike the time-lag-associated changes in the NH. These differences could be attributed to the prevailing horizontal and vertical dispersion mechanisms in the respective regions. Lastly, the radiative forcing estimates of Ambae and Raikoke/Ulawun eruptions, as reported in recent studies, was discussed by taking clues from other major and moderate eruptions to gain insight on their role in climate change.

3DVAR Aerosol Data Assimilation and Evaluation Using Surface PM2.5, Himawari-8 AOD and CALIPSO Profile Observations in the North China

Based on the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol scheme of the Weather Research and Forecasting model coupled with online Chemistry (WRF-Chem) and the three-dimensional variational (3DVAR) assimilation method, a 3DVAR data assimilation (DA) system for aerosol optical depth (AOD) and aerosol concentration observations was developed. A case study on assimilating the Himawari-8 satellite AOD and/or fine particulate matter (PM2.5) was conducted to investigate the improvement of DA on the analysis accuracy and forecast skills of the spatial distribution characteristics of aerosols, especially in the vertical dimension. The aerosol extinction coefficient (AEC) profile data from The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), surface PM2.5 and Himawari-8 AOD measurements were used for verification. One control experiment (without DA) and two DA experiments including a PM2.5 DA experiment denoted by Da_PM and a combined PM2.5 and AOD DA experiment denoted by Da_AOD_PM were conducted. Both DA experiments had positive effects on the surface PM2.5 mass concentration forecast skills for more than 60 h. However, the Da_PM showed a slight improvement in the analysis accuracy of the AOD distribution compared with the control experiment, while the Da_AOD_PM showed a considerable improvement. The Da_AOD_PM had the best positive effect on the AOD forecast skills. The correlation coefficient (CORR), root mean square error (RMSE), and mean fraction error (MFE) of the 24 h AOD forecasts for the Da_AOD_PM were 0.73, 0.38, and 0.54, which are 0.09 (14.06%), 0.08 (17.39%), and 0.22 (28.95%) better than that of the control experiment, and 0.05 (7.35%), 0.06 (13.64%), and 0.19 (26.03%) better than that of the Da_PM, respectively. Moreover, improved performance for the Da_AOD_PM occurred when the AEC profile was used for verification, as when the AOD was used for verification. The Da_AOD_PM successfully simulated the first increasing and then decreasing trend of the aerosol extinction coefficients below 1 km, while neither the control nor the Da_PM did. This indicates that assimilating AOD can effectively improve the analyses and forecast accuracy of the aerosol structure in both the horizontal and vertical dimensions, thereby compensating for the limitations associated with assimilating traditional surface aerosol observations alone.

Long-Term Investigation of Aerosols in the Urmia Lake Region in the Middle East by Ground-Based and Satellite Data in 2000–2021

Dried lake beds are some of the largest sources of dust in the world and have caused environmental problems in the surrounding areas in recent decades. In the present work, we studied the monthly and annual occurrence of dust storms at selected weather stations around Urmia Lake in northwestern (NW) Iran. Furthermore, we investigated the variations in the daily aerosol optical depth (AOD at 550 nm) and the Ångström exponent (at 412/470 nm), as well as the vertical profile of the total aerosol extinction coefficient and AOD at 532 nm, using space-borne MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and CALIPSO Satellite LiDAR data over the Urmia Lake region (36–39°N, 44–47°E). The monthly variations of AOD550 and AOD532 for the regions 37–39°N and 46–59°E were compared, and it was found that the CALIPSO AOD532 and MODIS AOD532 (reconstructed using the Ångström exponent) were in good agreement. In general, the dust storms during 2000–2021 increased the AOD550 above average around the Urmia Lake. The vertical profile of aerosols showed that the largest contribution to total aerosol loading over the Urmia Lake was from 1.5–3 km, 1.5–4 km, 1.5–5 km, and 1.5–3 km during winter, spring, summer, and autumn seasons, respectively.

Calibration Methods of Atmospheric Aerosol Lidar and a Case Study of Haze Process

Lidar is a reliable tool for active remote sensing detection of atmospheric aerosols. A multi-wavelength aerosol lidar (MWAL) with 355 nm, 532 and 1064 nm as detection light sources has been developed and deployed for operational observations at Haidian District Meteorological Service of Beijing. The structure design, specifications, observation campaign, and detection principle of the MWAL are introduced. To ensure the accuracy and reliability of the lidar observation data, the calibration contents, and methods of lidar are proposed, including the correction, and gluing of the original data, the collimation of the transmitting and receiving optical axes, the testing of signal saturation, the correction of molecular Rayleigh fitting and the determination of the depolarization ratio correction factor. Finally, a haze process from 29 September to 2 October 2019 was observed and analyzed using the data of lidar, digital radiosonde, air quality and relative humidity observed by the Haidian District Meteorological Service. The detection results show the reliability of lidar which can effectively obtain the temporal and spatial variation characteristics of the haze. The profiles of aerosol extinction coefficient, potential temperature and relative humidity can be effectively used to analyze the haze thickness and the influence of relative humidity on aerosol particles. The data of air quality monitor shows that PM10 is the main pollutant and the ratio of PM2.5/PM10 is negatively correlated with relative humidity. Finally, the HYSPLIT trajectory tracking model of the National Oceanic and Atmospheric Administration (NOAA) is used to further study the source of pollutants in this haze process.

Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook

Observations and numerical models are mainly used to investigate the spatiotemporal distribution and vertical structure characteristics of aerosols to understand aerosol pollution and its effects. However, the limitations of observations and the uncertainties of numerical models bias aerosol calculations and predictions. Data assimilation combines observations and numerical models to improve the accuracy of the initial, analytical fields of models and promote the development of atmospheric aerosol pollution research. Numerous studies have been conducted to integrate multi-source data, such as aerosol optical depth and aerosol extinction coefficient profile, into various chemical transport models using various data assimilation algorithms and have achieved good assimilation results. The definition of data assimilation and the main algorithms will be briefly presented, and the progress of aerosol assimilation according to two types of aerosol data, namely, aerosol optical depth and extinction coefficient, will be presented. The application of vertical aerosol data assimilation, as well as the future trends and challenges of aerosol data assimilation, will be further analysed.

Variations and drivers of aerosol vertical characterization after clean air policy in China based on 7-years consecutive observations

Understanding the aerosol vertical characterization is of great importance to both climate and atmospheric environment. This study investigated the variations of aerosol profiles over eight regions of interest in China after clean air policy (2013-2019) and discussed the drivers of the vertical aerosol structure, using observations from active satellite measurements (CALIPSO). From the annual variation, the amplitude of extinction coefficient profiles showed a decreasing trend with fluctuations, and the maximum was 0.21 km−1 in Beijing-Tianjin-Hebei (JJJ). For regions suffered from air pollution, the variation was greatest below 0.45 km, while it was between 1-1.5 km for Sichuan Basin. The correlation coefficient between the relative humidity (RH) and the extinction coefficient indicated that the increase of RH inhibited the decrease of the extinction coefficient in the Yangtze River Delta. In most regions, the main aerosol subtypes were polluted dust and polluted continental, but they were coarser in JJJ and North West. The frequency of concurrency of dust and polluted dust aerosols decreased in JJJ, but polluted continental aerosols occurred more frequently. Further, the aerosol extinction coefficient profiles under different pollution conditions showed that it changed most during heavy pollution periods in JJJ, especially in 2017, with a significant aerosol loading between ∼700 and 1200 m. The atmospheric reanalysis data revealed that the weak convergence at low level and the divergence at high level supported the upward transport of aerosols in 2017. Overall, the differences in divergence allocation, RH, and wind filed were the main meteorological drivers.

Analysis of Wildfires in the Mid and High Latitudes Using a Multi-Dataset Approach: A Case Study in California and Krasnoyarsk Krai

In this study, we investigate the emissions from wildfires in the mid latitude (California) and high latitude (Krasnoyarsk Krai) during the periods of 16–17 August 2020 and 28 July 2019, respectively. Wildfires are unique in themselves as they are driven by various factors such as fuel type, topology, and meteorology. In this study, we analyze whether there are any major variations in the emissions and transport of pollutants between two large wildfire cases in the mid latitude of California and high latitude of Krasnoyarsk Krai. The study is important to understand and characterize the emission regime from biomass burning of different land covers using a mutli-dataset approach. We analyze whether there are any major variations in the emissions and transport of pollutants from these wildfires. For example, the aerosol extinction coefficient profile showed smoke detected at the highest altitude of 9 km in Krasnoyarsk Krai, whereas in California the highest altitude was observed at approximately 6 km. Moreover, large values of black carbon (BC) concentration were observed in Krasnoyarsk Krai approximately 7 µg/m3 compared to the 0.44 µg/m3 observed in California. Areas with an immense dense vegetation are prone to large emissions. The results from this case study suggest that high latitude wildfires emit more pollutants than mid latitude wildfires. However, more studies in the future will be conducted to conclude this observation and finding with certainty.

Effect of Aerosol Vertical Distribution on the Modeling of Solar Radiation

Default aerosol extinction coefficient profiles are commonly used instead of measured profiles in radiative transfer modeling, increasing the uncertainties in the simulations. The present study aimed to determine the magnitude of these uncertainties and contribute towards the understanding of the complex interactions between aerosols and solar radiation. Default, artificial and measured profiles of the aerosol extinction coefficient were used to simulate the profiles of different radiometric quantities in the atmosphere for different surface, atmospheric, and aerosol properties and for four spectral bands: ultraviolet-B, ultraviolet-A, visible, and near-infrared. Case studies were performed over different areas in Europe and North Africa. Analysis of the results showed that under cloudless skies, changing the altitude of an artificial aerosol layer has minor impact on the levels of shortwave radiation at the top and bottom of the atmosphere, even for high aerosol loads. Differences of up to 30% were, however, detected for individual spectral bands. Using measured instead of default profiles for the simulations led to more significant differences in the atmosphere, which became very large during dust episodes (10–60% for actinic flux at altitudes between 1 and 2 km, and up to 15 K/day for heating rates depending on the site and solar elevation).

Impact of CALIPSO profile data assimilation on 3-D aerosol improvement in a size-resolved aerosol model

Based on the three-dimensional variational assimilation (3DVAR) algorithm, the extinction coefficient profiles of the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite were assimilated for the first time on the basis of the aerosol variables from the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) mechanism of the Weather Research and Forecasting-Chemistry (WRF-Chem) model. A light aerosol pollution episode (case1) and a heavy pollution event (case2) were selected to simulate and predict using the WRF-Chem model. Two sets of data were assimilated: CALIPSO derived aerosol extinction coefficient profiles and surface PM mass concentration data obtained from ground monitoring stations across China. Then, various aerosol data sources including ground-based lidar in Beijing area, Himawari-8 (H-8) satellite aerosol optical depth (AOD) and surface PM monitors were used for comprehensive evaluate the impact of CALIPSO data assimilation on the model performance. The results showed that simultaneous assimilation of the CALIPSO extinction coefficient profiles and surface PM mass concentration data can effectively improve the model aerosol initial conditions and forecasting accuracy of PM2.5, PM10 and AOD. The positive impact on PM2.5 and PM10 forecasting by the assimilation can be maintained for more than 14 h for the case1 and 24 h for the case2, and the initial field of AOD in assimilation experiment has been greatly improved comparing the model control run (cn, without data assimilation). For the simulation of the case2, the assimilation of CALIPSO extinction coefficient profiles reduced the root mean square error (RMSE), mean fraction (MFE) and bias (BIAS) of the AOD in the initial field of the model by 0.08 (19.5%), 0.34 (55.7%) and 0.16 (48.5%) compared to the cn experiment, respectively. When the CALIPSO extinction coefficient profiles and surface PM mass concentration data were assimilated simultaneously, the reduction of the RMSE, MFE and BIAS of the AOD was 0.6 (14.6%), 0.32 (52.5%) and 0.12 (36.4%), respectively. Additionally, aerosol extinction coefficient are remarkably underestimated in the cn experiment, particularly during heavy aerosol pollution case. Assimilating surface PM data can improve the extinction coefficient distribution below 500 m. The simulated aerosol extinction coefficient distribution at 1 km to 2 km can be significantly improved in both cases by assimilating the CALIPSO extinction coefficient profiles, and the value of model simulated extinction coefficient is nearly doubled compared to the cn experiment. Finally, the evaluation with independent ground-based lidar measurements indicates that combined assimilation of surface PM mass concentration and CALIPSO extinction coefficient profile can effectively improve the aerosol distribution near the ground and in the upper layer, and thus generate a more accurate 3D aerosol analysis and forecast field.

Comparative observation of aerosol vertical profiles in urban and suburban areas: Impacts of local and regional transport

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments were used to carry out observation of aerosol in the urban and suburban areas of Shanghai from October 17 to November 21, 2019. Fudan University (FDU) site is a typical urban environment, surrounded by residential areas, commercial areas and arterial roads, while Dianshan Lake (DSL) site is a suburban environment with high vegetation coverage and no pollutant emission sources. The aerosol retrieved by MAX-DOAS was in good correlation with the observation of sun photometer and the PM2.5 concentration of the corresponding site, which demonstrates that the aerosol retrieved by MAX-DOAS is reliable and feasible. Comparing the mean aerosol extinction coefficient (AEC) profiles during the observation period between urban and suburban areas, it was found that the occurrence of high aerosol concentration at FDU was nearly 3 h later than that of DSL at suburban site. And the aerosol at DSL was concentrated at an altitude of 0.3– 0.5 km, with a mean peak value of 0.486 km−1, which was slightly higher than the peak AEC of 0.453 km−1 at FDU of 0.2– 0.4 km. The difference in aerosol characteristics between the two sites may be due to the fact that the influences of aerosol transport and boundary layer dynamics are different between the two sites. The backward trajectories analysis also presents that there were mutual transports of aerosol between urban and suburban areas, which affect the optical properties of the aerosol in these two sites. In a case of aerosol pollution, we visualized the transport pathway of aerosol from the western part of the North China Plain to Shanghai using AEC profiles and backward trajectories, providing the evidence that the local aerosol pollution in Shanghai was affected by long-distance transport.

Capabilities of an Automatic Lidar Ceilometer to Retrieve Aerosol Characteristics within the Planetary Boundary Layer

Continuous observation and quantitative retrieval of aerosol backscatter coefficients are important in the study of air quality and climate in metropolitan areas such as New York City. Ceilometers are ideal for this application, but aerosol backscatter coefficient retrievals from ceilometers are challenging and require proper calibration. In this study, we calibrate the ceilometer (Lufft CHM15k, 1064 nm) system constant with the molecular backscatter coefficient and evaluate the calibrated profiles with other independent methods, including the water-phase cloud method and comparison with the NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) attenuated backscatter coefficient profile. Multiple-day calibration results show a stable system constant with a relative uncertainty of about 7%. We also evaluate the overlap correction for the CHM15k ceilometer (provided by Lufft) with a Vaisala CL-31 ceilometer, and the results show good consistency between two ceilometers’ range-corrected signal (RCS) profiles above 200 m. Next, we implement a forward iterative method to retrieve aerosol backscatter coefficients from continuous ceilometer measurements. In the retrieval, the lidar ratio is constrained by the co-located NASA AERONET radiometer aerosol optical depth (AOD) retrieval and agrees with the AERONET lidar-ratio products, derived from aerosol microphysical parameters. The aerosol backscatter coefficient retrievals are validated with co-located elastic-Raman lidar retrievals and indicate a good correlation (R2≥0.95) in the planetary boundary layer (PBL). Furthermore, a case study shows that the ceilometer retrieved aerosol extinction coefficient profiles can be used to estimate the AOD of the PBL and the aloft plumes. Finally, simulations of the uncertainty of aerosol backscatter coefficient retrieval show that a calibration error of 10% results in 10–20% of relative error in the aerosol backscatter coefficient retrievals, while relative error caused by a lidar-ratio error of 10% is less than 4% in the PBL.