Aerosol Classification Research Articles

Columnar Aerosol Optical Property Characterization and Aerosol Typing Based on Ground-Based Observations in a Rural Site in the Central Yangtze River Delta Region

Accurate and updated aerosol optical properties (AOPs) are of vital importance to climatology and environment-related studies for assessing the radiative impact of natural and anthropogenic aerosols. We comprehensively studied the columnar AOP observations between January 2019 and July 2020 from a ground-based remote sensing instrument located at a rural site operated by Central China Comprehensive Experimental Sites in the center of the Yangtze River Delta (YRD) region. In order to further study the aerosol type, two threshold-based aerosol classification methods were used to investigate the potential categories of aerosol particles under different aerosol loadings. Based on AOP observation and classification results, the potential relationships between the above-mentioned results and meteorological factors (i.e., humidity) and long-range transportation processes were analyzed. According to the results, obvious variation in aerosol optical depth (AOD) during the daytime, as well as throughout the year, was revealed. Investigation into AOD, single-scattering albedo (SSA), and absorption aerosol optical depth (AAOD) revealed the dominance of fine-mode aerosols with low absorptivity. According to the results of the two aerosol classification methods, the dominant aerosol types were continental (accounting for 43.9%, method A) and non-absorbing aerosols (62.5%, method B). Longer term columnar AOP observations using remote sensing alongside other techniques in the rural areas in East China are still needed for accurate parameterization in the future.

Classification and transformation of aerosols over selected Indian cities during reduced emissions under Covid-19 lockdown

Studies in the recent past show improved air quality over India during the Covid-19 lockdown. This research attempts to characterize atmospheric aerosols in terms of α and AOD and their transformation over India during the pandemic lockdown. The type and particle distribution of aerosols, including gaseous species for five Indian regions were considered. Fine to coarse particle shift was observed in most regions. The northern region observed high fire counts, implying crop residue burning season during the stringent lockdown. Thiruvananthapuram, in the south, showed an increase in PM, owing to the resumption of mobility post-lockdown. Hyderabad, however; observed increased PM2.5 (2.79%) and AOD (37.23%) during Phase 1. Maritime (MT) aerosol predominated over Thiruvananthapuram, whereas urban/biomass burning (UBB) type decreased over the eastern region. Contributions from continental average (CA), maritime continental average (MCA), and MT were observed over Hyderabad, post-lockdown. In the central region, MCA was replaced by UBB and mixed type, with isolated episodes of clean continental (CC) and desert dust (DD). During lockdown phases, an increase in O3 over western, northern, and central regions is attributed to increased temperature and decreased NO2. A significant correlation with population density (PD) exists with NO2 (R2 = 0.75; p < 0.05), suggesting human mobility as a major contributor to NO2 in the atmosphere during the lockdown period.Highlights Characterization of atmospheric aerosols during Covid-19 lockdown over India.General shift from fine to coarse particles size in most regions.Crop residue burning increased pollutants in North during lockdown.Forest fire season in central and south-central region increased PM, NO2 concentrations during lockdown.Maritime origin aerosols dominate over Thiruvananthapuram.Decline in pollutants in post-lockdown due to meteorology (early monsoon, cyclone Amphan, and Nisarga). Supplementary InformationThe online version contains supplementary material available at 10.1007/s12040-022-01916-y.

Aerosols over the Foothills of the Eastern Himalayan Region during Post-monsoon and Winter Seasons

In this study a Microtops II sunphotometer is used for the first time over Birtamode, a rapidly growing city located in the eastern Himalayan foothills of Nepal, to measure aerosol optical depth (AOD). The average AOD for the observation period (October 2018–February 2019) was 0.68 ± 0.39 with the post-monsoon season having a higher value (0.74 ± 0.43) compared to the winter season (0.60 ± 0.32). The Angstrom exponent (α) for post-monsoon and winter are found to be 1.08 ± 0.10 and 1.11 ± 0.16 respectively. During the monitoring period, the majority of AOD values (47%) are above 0.60, indicating moderately polluted conditions in the region. Anthropogenic, biomass burning, and mixed aerosols are identified as the prevalent aerosol types in the study region. The observed aerosol classification is also explained in terms of CAMS near-real-time model datasets. The AOD values retrieved by MODIS, VIIRS, Himawari-8, and CAMS show a good correlation with the observed Microtops AOD with R2 values ranging from 0.60 to 0.94. Moreover, different MODIS aerosol products (DB, DT, and combined DB-DT) are evaluated based on a comparison of Collection 6.1 AOD with the ground truth obtained from Microtops. The spatial distribution of AOD as observed by various satellites are compared and the vertical distribution of aerosol is also explained with the extinction coefficient provided by the CALIOP lidar onboard CALIPSO and aerosol types provided by CAMS.

Effect of the Vertical Distribution of Absorbing Aerosols on the Atmospheric Correction for Satellite Ocean Color Remote Sensing

The vertical distribution of absorbing aerosols has nonnegligible impact on the atmospheric correction of satellite ocean color remote sensing, especially for the water-leaving radiance retrieval at blue and ultraviolet bands. In this study, we investigated the impact of the vertical distribution of absorbing aerosols on the satellite-measured radiance at the top of the atmosphere (TOA) and the retrieved water-leaving radiance. First, the global occurrence frequency of absorbing aerosols was mapped, and it was found that the annual averaged occurrence frequencies of absorbing aerosols were >30% over the coasts of the Sahara and Arabian Desert, China, South-Central Africa, and the Indian Peninsula. Second, a new aerosol classification algorithm was developed to establish absorbing aerosol optical models based on AERosol RObotic NETwork (AERONET) site observations. Finally, the effects of the vertical distribution of absorbing aerosols on the upward radiance at the TOA at 412 nm and the retrieved water-leaving radiance were evaluated. The results showed that the influence of the vertical distribution on the TOA radiance could be up to 8% for dust and 10% for fine-dominated absorbing aerosols (FDAs), which was comparable with the influence of aerosol optical depth. Not considering absorbing aerosols during atmospheric correction might produce <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 4$ </tex-math></inline-formula> %–10% errors in the water-leaving radiance retrieval at 412 nm over turbid waters under the assumption of a Gaussian distribution. Simplified exponential and two-layer atmospheric vertical distribution models can lead to errors of water-leaving radiance retrieval up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 12$ </tex-math></inline-formula> %–15% and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 30$ </tex-math></inline-formula> %–40%, respectively. Overall, the imperfect vertical distribution assumption and aerosol model selection might induce uncertainty in water-leaving radiance retrieval from 10% to 80% under absorbing aerosol conditions.

Physical and chemical properties of black carbon and organic matter from different combustion and photochemical sources using aerodynamic aerosol classification

Abstract. The physical and chemical properties of black carbon (BC) and organic aerosols are important for predicting their radiative forcing in the atmosphere. During the Soot Aerodynamic Size Selection for Optical properties (SASSO) project and a EUROCHAMP-2020 transnational access project, different types of light-absorbing carbon were studied, including BC from catalytically stripped diesel exhaust, an inverted flame burner, a colloidal graphite standard (Aquadag) and controlled flaming wood combustion. Brown carbon (BrC) was also investigated in the form of organic aerosol emissions from wood burning (pyrolysis and smouldering) and from the nitration of secondary organic aerosol (SOA) proxies produced in a photochemical reaction chamber. Here we present insights into the physical and chemical properties of the aerosols, with optical properties presented in subsequent publications. The dynamic shape factor (χ) of BC particles and material density (ρm) of organic aerosols was investigated by coupling a charging-free Aerodynamic Aerosol Classifier (AAC) with a Centrifugal Particle Mass Analyzer (CPMA) and a Scanning Mobility Particle Sizer (SMPS). The morphology of BC particles was captured by transmission electron microscopy (TEM). For BC particles from the diesel engine and flame burner emissions, the primary spherule sizes were similar, around 20 nm. With increasing particle size, BC particles adopted more collapsed/compacted morphologies for the former source but tended to show more aggregated morphologies for the latter source. For particles emitted from the combustion of dry wood samples, the χ of BC particles and the ρm of organic aerosols were observed in the ranges 1.8–2.17 and 1.22–1.32 g cm−3, respectively. Similarly, for wet wood samples, the χ and ρm ranges were 1.2–1.85 and 1.44–1.60 g cm−3, respectively. Aerosol mass spectrometry measurements show no clear difference in mass spectra of the organic aerosols in individual burn phases (pyrolysis or smouldering phase) with the moisture content of the wood samples. This suggests that the effect moisture has on the organic chemical profile of wood burning emissions is through changing the durations of the different phases of the burn cycle, not through the chemical modification of the individual phases. In this study, the incandescence signal of a Single Particle Soot Photometer (SP2) was calibrated with three different types of BC particles and compared with that from an Aquadag standard that is commonly used to calibrate SP2 incandescence to a BC mass. A correction factor is defined as the ratio of the incandescence signal from an alternative BC source to that from the Aquadag standard and took values of 0.821 ± 0.002 (or 0.794 ± 0.005), 0.879 ± 0.003 and 0.843 ± 0.028 to 0.913 ± 0.009 for the BC particles emitted from the diesel engine running under hot (or cold idle) conditions, the flame burner and wood combustion, respectively. These correction factors account for differences in instrument response to BC from different sources compared to the standardised Aquadag calibration and are more appropriate than the common value of 0.75 recommended by Laborde et al. (2012b) when deriving the mass concentration of BC emitted from diesel engines. Quantifying the correction factor for many types of BC particles found commonly in the atmosphere may enable better constraints to be placed on this factor depending on the BC source being sampled and thus improve the accuracy of future SP2 measurements of BC mass concentrations.

An mmWave Sensor for Real-Time Monitoring of Gases Based on Real Refractive Index

We propose a millimeter-wave (mmWave) sensor to monitor gases and aerosols based on time-of-flight (ToF), thus, on the real refractive index. It utilizes an ultrawideband frequency-modulated continuous-wave (FMCW) radar operating from 72 to 92 GHz at a sampling rate of 500 Hz. Also, we introduce a model for simulation of the refractive index of arbitrary gases at mmWave frequencies using molecular spectroscopic data. Simulations then allow the identification of the respective gas under test. We characterized the performance of the sensor regarding the refractive index within various experiments. The precision is 0.027 ppm, and the 20-h long-term stability is better than 0.2 ppm. The linearity is at least 1.5 ppm. Due to sophisticated temperature compensation, the temperature drift is less than 10 ppm for 30 K. Since the sensor is accurate, precise, and robust, it is perfect for in-process real-time monitoring and classification of gases or aerosols in the industry.

Development of cutoff size adjustable omnidirectional inlet cyclone separator

The cyclone separator, which is commonly used for size classification and collection of aerosols, have sampling bias that depend on the installation direction of the inlet and significantly limit the change in cutoff size. In this study, these shortcomings were addressed in the developed cutoff size adjustable omnidirectional inlet (CSAOI) cyclone separator, which can suction aerosol from all 360° directions and allows the adjustment of cutoff size without the need to change cyclone geometry or operating flow rate. Although the aerosol was suctioned from the side in a similar way to conventional tangential inlet cyclone separators, an omnidirectional inlet was implemented by installing 16 guide vanes along the circumference of the cyclone separator. As changing the installation angle of the guide vanes also changes the gap between the neighboring guide vanes, the cutoff size can be adjusted because the inlet velocity of the inflow aerosol is changed by the gap under a fixed operating flow rate. A CSAOI cyclone separator was devised, fabricated, and tested for performance evaluation with an operating flow rate of 1,000 L/min. The cutoff size changed from 1.4 to 12.4 μm as the guide vane angle varied between 26° and 46°. For guide vane angles of 29°, 34°, and 42°, the cutoff sizes were 2.8, 5.4, and 10.0 μm, respectively, thereby confirming that the cyclone separator can be used as a PM2.5, PM5, or PM10 sampling inlet, respectively. The developed CSAOI cyclone separator is expected to be applied to various aerosol sampling and collection devices.

Vertical profile of aerosol characteristics including activation over a rain shadow region in India

Unique airborne observations of aerosol size spectral and chemical characteristics over the peninsular Indian region are illustrated in this case study. Multimodal lognormal distributions were required to fit the observed in situ aerosol size distribution. The aerosol composition and mixing state was deduced from the single-particle analyses of aerosols using the transmission electron microscope and soot photometer coupled with satellite retrieved aerosol classification, and back trajectory analyses. Organic carbon was the most prominent aerosol type found at all altitudes. Refractory black carbon aerosols which constituted about 10–12% of the aerosols in the boundary layer were primarily internally mixed with both inorganic and organic coating. Other major aerosol types were dust and sea salt, with the latter primarily found below 2 km. Further, the cloud forming ability of in-situ aerosols is tested through a cloud condensation nuclei closure analysis. The effective hygroscopicity decreased above cloud base due to the absence of sea salt aerosols. The change in large-scale winds with altitude affected the aerosol composition and hygroscopicity. The multimodal aerosol size distribution and hygroscopicity parameter (κ = 0.18) obtained for the cloud base aerosols over the rain shadow region are useful for studying aerosol-cloud interactions using regional cloud-resolving models.

Classification of atmospheric aerosols and clouds by use of dual-polarization lidar measurements.

Accurate identification of aerosols and cloud from remote sensing observations is of importance for quantitatively evaluating their radiative forcing and related impacts. Even though polarization lidar has exhibited a unique advantage of classifying atmospheric aerosols and clouds over the past several decades, polarization measurements are often achieved at one wavelength (UV or VIS) using laser remote sensing. To better identify the types of aerosols and clouds, we developed a ground-based dual-polarization lidar system that can simultaneously detect polarization measurements at wavelengths of 355 nm and 532 nm. Our results show that the volume depolarization ratios (VDRs) at 355 nm and 532 nm markedly differ for typical types of aerosols and clouds in the atmosphere. For non-spherical particles, the ratio of VDRs at 532 nm and 355 nm are 2.87 ± 1.35 for ice cloud and 1.51 ± 0.29 for dust-dominated aerosols, respectively. However, for spherical particles, the ratios are 0.43 ± 0.26 for water cloud and 0.56 ± 0.05 for air pollutants. Consequently, we proposed a simple reliable method for classifying atmospheric aerosols and clouds from polarization measurements observed by the developed lidar system. The proposed method first distinguishes clouds from aerosols using a combination of the color ratio (CR, 532 nm/355 nm) and attenuated backscattering coefficients (ABC) at 532 nm. Then, subtypes of clouds and aerosols are identified based on the ratio of VDRs at 532 nm and 355 nm. The results showed that dual-polarization lidar measurements can remarkably improve the classification of atmospheric aerosols and clouds, compared with results using a traditional method. This study illustrates that more information on atmospheric aerosols and clouds can be obtained from polarization measurements at multiple wavelengths by active remote sensing.

Satellite-Based Aerosol Classification for Capital Cities in Asia Using a Random Forest Model

Aerosol types in Asian capital cities were classified using a random forest (RF) satellite-based aerosol classification model during 2018–2020 in an investigation of the contributions of aerosol types, with or without Aerosol Robotic Network (AERONET) observations. In this study, we used the recently developed RF aerosol classification model to detect and classify aerosols into four types: pure dust, dust-dominated aerosols, strongly absorbing aerosols, and non-absorbing aerosols. Aerosol optical and microphysical properties for each aerosol type detected by the RF model were found to be reasonably consistent with those for typical aerosol types. In Asian capital cities, pollution-sourced aerosols, especially non-absorbing aerosols, were found to predominate, although Asian cities also tend to be seasonally affected by natural dust aerosols, particularly in East Asia (March–May) and South Asia (March–August). No specific seasonal effects on aerosol type were detected in Southeast Asia, where there was a predominance of non-absorbing aerosols. The aerosol types detected by the RF model were compared with those identified by other aerosol classification models. This study indicates that the satellite-based RF model may be used as an alternative in the absence of AERONET sites or observations.

A case study on the vertical distribution and characteristics of aerosols using ground-based raman lidar, satellite and model over Western India

ABSTRACT Ahmedabad is an urban site in western region of India. Dust loading and its variability are very high over this semi-arid location. A state-of-the-art ground-based Raman lidar has been used for the study of day-to-day variability in vertical distribution of aerosol loading over Ahmedabad (23.02° N, 72.57° E) from 8 to 11 May 2018. We have done a comprehensive study about vertical profiles of aerosols across two wavelengths recorded simultaneously, namely, 355 nm and 532 nm, over this location. An interesting hump feature has been noted on 9 May at around 18 h (Local Time), with an additional peak at 19 h on 10 May. The loading over this region has more fine-mode aerosols than coarse-mode particles. Further, findings from ground-based lidar have been compared with MACC-II model simulations and Cloud-Aerosol Lidar with Orthogonal Polarization on-board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observational. Back-trajectory analysis showed majority of the influx came from middle-east, carrying mineral dust and traces of marine aerosols from Arabian Sea, except for 11 May, where low-level dust carrying trajectories and also coarser dust particles were not seen. This type of manifestation has also been observed while classifying aerosols over Ahmedabad using Lidar Depolarization Ratio and Lidar Ratio obtained from Raman Lidar. Fine mode aerosols have been characterized as industrial, vehicular and marine, while coarser as mineral dust and biomass burning. This study focuses on local variation and classification of aerosols based on size and type, which will further help in better estimation of radiative budget and other impacts of aerosols.

Impact of smoke and non-smoke aerosols on radiation and low-level clouds over the southeast Atlantic from co-located satellite observations

Abstract. Data derived from instruments on board the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat satellites as well as meteorological parameters from reanalysis are used to explore situations when moist aerosol layers overlie stratocumulus clouds over the southeast Atlantic during the biomass burning season (June to October). To separate and quantify the impacts of aerosol loading, aerosol type, and humidity on the radiative fluxes (including cloud top cooling), the data are split into different levels of aerosol and moisture loadings. The aerosol classification available from the CALIPSO products is used to compare and contrast situations with pristine air, with smoke, and with other (non-smoke) types of aerosols. A substantial number of cases with non-smoke aerosols above clouds are found to occur under similar meteorological conditions to the smoke cases. In contrast, the meteorology is substantially different for the pristine situations, making a direct comparison with the aerosol cases ambiguous. The moisture content is enhanced within the aerosol layers, but the relative humidity does not always increase monotonously with increasing optical depth. Shortwave (SW) heating rates within the moist aerosol plumes increase with increasing aerosol loading and are higher in the smoke cases compared to the non-smoke cases. However, there is no clear correlation between moisture changes and SW absorption. Cloud top cooling rates do not show a clear correlation with moisture within the overlying aerosol layers due to the strong variability of the cooling rates caused by other meteorological factors (most notably cloud top temperature). No clear influence of aerosol type or loading on cloud top cooling rates is detected. Further, there is no correlation between aerosol loading and the thermodynamic structure of the atmosphere nor the cloud top height.

TAKING INTO ACCOUNT THE PARAMETERS OF AEROSOL EMISSIONS IN THE DEVELOPMENT TECHNOLOGICAL SOLUTIONS TO REDUCE THE IMPACT ON THE ENVIRONMENT

The article discusses the issues of studying the parameters of various origins aerosol emissions in order to make a reasonable choice of appropriate technological solutions to reduce the impact on the environment. Based on the analysis of literary sources, a classical approach to the existing classification of aerosols considered: by the nature of the formation; by dispersion; by the state of aggregation of the dispersed phase; by morphological characteristics of particles; by particle concentration; by the nature of the impact on a person. Refinement of existing classifications was conducted based on the most important physical and chemical characteristics such as cohesiveness of particles, hygroscopicity, and ability to absorb additional substances from the environment which in turn is an important factor in the selection process of environmental solutions. Based on the analysis of aerosols classifications concluded possible solutions of the problem of selection of high-efficiency and reliable equipment capable for trapping fine dust with various physical and physicochemical parameters

Developing automated methods to estimate spectrally resolved direct normal irradiance for solar energy applications

We describe four schemes designed to estimate spectrally resolved direct normal irradiance (DNI) for multi-junction concentrator photovoltaic systems applications. The schemes have increasing levels of complexity in terms of aerosol and circumsolar irradiance (CSI) treatment, ranging from a climatological aerosol classification with no account of CSI, to an approach which includes explicit aerosol typing and type dependent CSI contribution. When tested against ground-based broadband and spectral measurements at five sites spanning a range of aerosol conditions, the most sophisticated scheme yields an average bias of +0.068%, well within photometer calibration uncertainties. The average spread of error is 2.5%. These statistics are markedly better than the climatological approach, which carries an average bias of −1.76% and a spread of 4%. They also improve on an intermediate approach which uses Angström exponents to estimate the spectral variation in aerosol optical depth across the solar energy relevant wavelength domain. This approach results in systematic under and over-estimations of DNI at short and long wavelengths respectively. Incorporating spectral CSI particularly benefits sites which experience a significant amount of coarse aerosol. All approaches we describe use freely available reanalyses and software tools, and can be easily applied to alternative aerosol measurements, including those from satellite.

Improving Spatial Coverage of Satellite Aerosol Classification Using a Random Forest Model

The spatial coverage of satellite aerosol classification was improved using a random forest (RF) model trained with observational data including target (aerosol type) and input (satellite measurement) variables. The AErosol RObotic NETwork (AERONET) aerosol-type dataset was used for the target variables. Satellite input variables with many missing data or low mean-decrease accuracy were excluded from the final input variable set, and good performance in aerosol-type classification was achieved. The performance of the RF-based model was evaluated on the basis of the wavelength dependence of single-scattering albedo (SSA) and fine-mode-fraction values from AERONET. Typical SSA wavelength dependence for individual aerosol types was consistent with that obtained for aerosol types by the RF-based model. The spatial coverage of the RF-based model was also compared with that of previously developed models in a global-scale case study. The study demonstrates that the RF-based model allows satellite aerosol classification with improved spatial coverage, with a performance similar to that of previously developed models.

Improved Algorithms for Remote Sensing-Based Aerosol Retrieval during Extreme Biomass Burning Events

This study proposed an aerosol characterization process using satellites for severe biomass burning events. In general, these severely hazy cases are labeled as “undecided” or “hazy.” Because atmospheric aerosols are significantly affected by factors such as air quality, global climate change, local environmental risk, and human and biological health, efficient and accurate algorithms for aerosol retrieval are required for global satellite data processing. Our previous classification of aerosol types was based primarily on near-ultraviolet (UV) data, which facilitated subsequent aerosol retrieval. In this study, algorithms for aerosol classification were expanded to events with serious biomass burning aerosols (SBBAs). Once a biomass burning event is identified, the appropriate radiation simulation method can be applied to characterize the SBBAs. The second-generation global imager (SGLI) on board the Japanese mission JAXA/Global Change Observation Mission-Climate contains 19 channels, including red (674 nm) and near-infrared (869 nm) polarization channels with a high resolution of 1 km. Using the large-scale wildfires in Kalimantan, Indonesia in 2019 as an example, the complementarity between the polarization information and the nonpolarized radiance measurements from the SGLI was demonstrated to be effective in radiation simulations for biomass burning aerosol retrieval. The retrieved results were verified using NASA/AERONET ground-based measurements, and then compared against JAXA/SGLI/L2-version-1 products, and JMA/Himawari-8/AHI observations.

A First Approach to Aerosol Classification Using Space-Borne Measurement Data: Machine Learning-Based Algorithm and Evaluation

A new method was developed for classifying aerosol types involving a machine-learning approach to the use of satellite data. An Aerosol Robotic NETwork (AERONET)-based aerosol-type dataset was used as a target variable in a random forest (RF) model. The contributions of satellite input variables to the RF-based model were quantified to determine an optimal set of input variables. The new method, based on inputs of satellite variables, allows the classification of seven aerosol types: pure dust, dust-dominant mixed, pollution-dominant mixed aerosols, and pollution aerosols (strongly, moderately, weakly, and non-absorbing). The performance of the model was statistically evaluated using AERONET data excluded from the model training dataset. Model accuracy for classifying the seven aerosol types was 59%, improving to 72% for four types (pure dust, dust-dominant mixed, strongly absorbing, and non-absorbing). The performance of the model was evaluated against an earlier aerosol classification method based on the wavelength dependence of single-scattering albedo (SSA) and fine-mode-fraction values from AERONET. Typical wavelength dependences of SSA for individual aerosol types are consistent with those obtained for aerosol types by the new method. This study demonstrates that an RF-based model is capable of satellite aerosol classification with sensitivity to the contribution of non-spherical particles.

Development of ZJU high-spectral-resolution lidar for aerosol and cloud: Feature detection and classification

A ground-based high-spectral-resolution lidar (HSRL), operated at 532 nm wavelength, has been developed at Zhejiang University (ZJU) for aerosols and clouds studies. This lidar provides vertical profiles of aerosol scattering ratio together with lidar ratio and particle depolarization ratio at 532 nm. These single wavelength HSRL observations can be used to automatically identify the features attributed to dust/polluted dust, urban/smoke, maritime aerosols, as well as ice and liquid water cloud during day and night. Developed algorithm was applied to extended data set obtained during field campaigns performed at coastal city Zhoushan and metropolis Hangzhou over eastern China. To evaluate the practical performance of feature detection, the obtained aerosol optical depth (AOD) from ZJU HSRL has been compared with that from the sun photometers and they agree very well (5.9% in terms of bias error). Also, aerosol classification obtained with presented algorithm agrees well with previous established literatures. Furthermore, based on our method and extensive data sets from ZJU HSRL, measurements performed over eastern China extend the database of aerosols especially with respect to urban and marine and dust near the Yangtze River Delta region.

Identification of key aerosol types and mixing states in the central Indian Himalayas during the GVAX campaign: the role of particle size in aerosol classification

Studies in aerosol properties, types and sources in the Himalayas are important for atmospheric and climatic issues due to high aerosol loading in the neighboring plains. This study uses in situ measurements of aerosol optical and microphysical properties obtained during the Ganges Valley Aerosol eXperiment (GVAX) at Nainital, India over the period June 2011–March 2012, aiming to identify key aerosol types and mixing states for two particle sizes (PM1 and PM10). Using a classification matrix based on SAE vs. AAE thresholds (scattering vs. absorption Ångström exponents, respectively), seven aerosol types are identified, which are highly dependent on particle size. An aerosol type named “large/BC mix” dominates in both PM1 (45.4%) and PM10 (46.9%) mass, characterized by aged BC mixed with other aerosols, indicating a wide range of particle sizes and mixing states. Small particles with low spectral dependence of the absorption (AAE < 1) account for 31.6% and BC-dominated aerosols for 14.8% in PM1, while in PM10, a large fraction (39%) corresponds to “large/low-absorbing” aerosols and only 3.9% is characterized as “BC-dominated”. The remaining types consist of mixtures of dust and local emissions from biofuel burning and display very small fractions. The main optical properties e.g. spectral scattering, absorption, single scattering albedo, activation ratio, as well as seasonality and dependence on wind speed and direction of identified types are examined, revealing a large influence of air masses originating from the Indo-Gangetic Plains. This indicates that aerosols over the central Himalayas are mostly composed by mixtures of processed and transported polluted plumes from the plains. This is the first study that identifies key aerosol populations in the central Indian Himalayas based on in situ measurements and the results are highly important for aerosol-type inventories, chemical transport models and reducing the uncertainty in aerosol radiative forcing over the third pole.

Aerosol optical properties and its type classification based on multiyear joint observation campaign in north China plain megalopolis

Since haze and other air pollution are frequently seen in the North China Plain (NCP), detail information on aerosol optical and radiative properties and its type classification is demanded for the study of regional environmental pollution. Here, a multiyear ground-based synchronous sun photometer observation at seven sites on North China Plain megalopolis from 2013 to 2018 was conducted. First, the annual and seasonal variation of these characteristics as well as the intercomparsion were analyzed. Then the potential relationships between these properties with meteorological factors and the aerosol type classification were discussed. The results show: Particle volume exhibited a decreasing trend from the urban downtown to suburban and the rural region. The annual average aerosol optical depth at 440 nm (AOD440) varied from ∼0.43 to 0.86 over the NCP. Annual average single-scattering albedo at 440 nm (SSA440) varied from ∼0.89 to 0.93, indicating a moderate to slight absorption capacity. Average absorption aerosol optical depth at 440 nm (AAOD440) varied from ∼0.07 to 0.10. The absorption Ångström exponent (AAE) (∼0.89–1.40) indicated the multi-types of absorptive matters originated form nature and anthropogenic emission. The discussion of aerosol composition showed a smaller particle size of aerosol from biomass burning and/or fossil foil consumption with enhanced aerosol scattering and enlarged light extinction. Aerosol classification indicated a large percentage of mixed absorbing aerosol (∼20%–49%), which showed increasing trend between relative humidity (RH) with aerosol scattering and dust was an important environmental pollutant compared to southern China.