Dominant Aerosol Types Research Articles

Contrasting aerosol optical and radiative properties between dust and urban haze episodes in megacities of Pakistan

Satellite and ground based remote sensors provide vital information about aerosol optical and radiative properties. Analysis of aerosol optical and radiative properties during heavy aerosol loading events in Pakistan are limited and, therefore, require in-depth examination. This work examines aerosol properties and radiative forcing during Dust Episodes (DE) and Haze Episodes (HE) between 2010 and 2014 over mega cities of Pakistan (Karachi and Lahore). Episodes having the daily averaged values of Aerosol Optical Depth (AOD) exceeding 1 were selected. DE were associated with high AOD and low Ångström Exponent (AE) over Karachi and Lahore while high AOD and high AE values were associated with HE over Lahore. Aerosol volume size distributions (AVSD) exhibited a bimodal lognormal distribution with a noticeable coarse mode peak at a radius of 2.24 μm during DE, whereas a fine mode peak was prominent at a radius 0.25 μm during HE. The results reveal distinct differences between HE and DE for spectral profiles of several parameters including Single Scattering Albedo (SSA), ASYmmetry parameter (ASY), and the real and imaginary components of refractive index (RRI and IRI). The AOD-AE correlation revealed that dust was the dominant aerosol type during DE and that biomass burning and urban/industrial aerosol types were pronounced during HE. Aerosol radiative forcing (ARF) was estimated using the Santa Barbra DISORT Atmospheric Radiative Transfer (SBDART) model. Calculations revealed a negative ARF at the Top Of the Atmosphere (ARFTOA) and at the Bottom Of the Atmosphere (ARFBOA), with positive ARF within the Atmosphere (ARFATM) during both DE and HE over Karachi and Lahore. Furthermore, estimations of ARFATM by SBDART were shown to be in good agreement with values derived from AERONET data for DE and HE over Karachi and Lahore.

Classifying aerosol type using in situ surface spectral aerosol optical properties

Abstract. Knowledge of aerosol size and composition is important for determining radiative forcing effects of aerosols, identifying aerosol sources and improving aerosol satellite retrieval algorithms. The ability to extrapolate aerosol size and composition, or type, from intensive aerosol optical properties can help expand the current knowledge of spatiotemporal variability in aerosol type globally, particularly where chemical composition measurements do not exist concurrently with optical property measurements. This study uses medians of the scattering Ångström exponent (SAE), absorption Ångström exponent (AAE) and single scattering albedo (SSA) from 24 stations within the NOAA/ESRL Federated Aerosol Monitoring Network to infer aerosol type using previously published aerosol classification schemes.Three methods are implemented to obtain a best estimate of dominant aerosol type at each station using aerosol optical properties. The first method plots station medians into an AAE vs. SAE plot space, so that a unique combination of intensive properties corresponds with an aerosol type. The second typing method expands on the first by introducing a multivariate cluster analysis, which aims to group stations with similar optical characteristics and thus similar dominant aerosol type. The third and final classification method pairs 3-day backward air mass trajectories with median aerosol optical properties to explore the relationship between trajectory origin (proxy for likely aerosol type) and aerosol intensive parameters, while allowing for multiple dominant aerosol types at each station.The three aerosol classification methods have some common, and thus robust, results. In general, estimating dominant aerosol type using optical properties is best suited for site locations with a stable and homogenous aerosol population, particularly continental polluted (carbonaceous aerosol), marine polluted (carbonaceous aerosol mixed with sea salt) and continental dust/biomass sites (dust and carbonaceous aerosol); however, current classification schemes perform poorly when predicting dominant aerosol type at remote marine and Arctic sites and at stations with more complex locations and topography where variable aerosol populations are not well represented by median optical properties. Although the aerosol classification methods presented here provide new ways to reduce ambiguity in typing schemes, there is more work needed to find aerosol typing methods that are useful for a larger range of geographic locations and aerosol populations.

Characteristics of Aerosol Types in Beijing and the Associations with Air Pollution from 2004 to 2015

With the fast development of the economy and expansion, a large number of people have concentrated in Beijing over the past few decades, leading to the result that Beijing has become home to one of the most complex mixtures of aerosol types in the world. The various aerosol types play different roles in the determination of global climate change, visibility, and human health. However, to the best of our knowledge, research has rarely analyzed the correlation between aerosol types and air quality index (AQI) in Beijing (urban and suburban) over a long-term series of observations. Therefore, in this study, we aim to identify and discuss the different aerosol types and AQI in Beijing from 2004 to 2015. The aerosol types are classified into six categories: dust, mixed, highly-absorbing, moderately-absorbing, slightly-absorbing, and scattering by a multiple clustering method with the fine mode fraction (FMF) and single scattering albedo (SSA) data of retrievals from the global Aerosol Robotic Network (AERONET) sun photometer sites. The AQI levels: are good (0–50); moderate (51–100); unhealthy for sensitive groups (101–150); unhealthy (151–200); very unhealthy (201–300); and hazardous (>300). The results show that a significant FMF variability occurred among different seasons in Beijing, with maximum values present in spring and minimum values in winter. The SSA values exhibit variation, with small fluctuations from season to season. In the case of BJ station, the scattering aerosols are more frequent in summer (39%) and less in winter (1%), while the coarse particles (dust) are more frequent in spring (18%) and less in autumn (6%). In contrast, the absorbing aerosols (especially slightly-absorbing) are more frequent in summer (35%) and winter (15%). However, the mixed aerosol types are more frequent in spring (38%) and less in summer (8%). There is a similar seasonal variation in XH. In the past 12 years, the slightly-absorbing aerosol type in Beijing has increased by approximately 14%, which is believed to be due to the rapid development of industrial cities. In addition, comparing the urban and suburban regions, the slightly-absorbing aerosol type is the dominant aerosol type in both areas. Furthermore, to identify the dominant aerosol types which lead to air pollution, a related analysis was carried out by analyzing different aerosol types and the relationship between aerosol types and AQI. The results indicate that the air pollution was strongly correlated to slightly-absorbing aerosols, in which the percentage of slightly-absorbing aerosols was about 49% during the hazardous days in 2013–2015, and the correlation between AQI and aerosol types is also strong (R2 = 0.76 and 0.97, in Beijing and Xianghe).

Classification of key aerosol types and their frequency distributions based on satellite remote sensing data at an industrially polluted city in the Yangtze River Delta, China

ABSTRACTIn the present study, characterization of columnar aerosol optical properties and classifying the major aerosol types was investigated at an urban–industrial city, Nanjing in the Yangtze River Delta (YRD) region over East China using simultaneous data sets retrieved from the MODerate resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) sensors during 2004–2015. A notable spatiotemporal heterogeneity was observed in the optical properties of aerosols on the seasonal scale over East China. Aerosol optical depth at 550 nm (AOD550) exhibited pronounced seasonal variability over Nanjing in the YRD, with higher values during summer and spring seasons and lower in winter. Ångström exponent (AE470–660) found higher in summer indicating the relative abundance of fine mode aerosols over the coarse mode. We also used the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for presenting cluster trajectory analysis which revealed that the airmasses from different source regions contributed greatly to aerosol loading during the study period. In addition, we followed two techniques for studying classification of major aerosol types based on the predefined thresholds. Using the AOD–AE method (here called as Technique‐I), five major aerosol types were identified via, continental clean (CC), marine (MA), biomass burning/urban–industrial (BU), desert dust (DD), and mixed (MX). In all the seasons, MX is the dominant aerosol type followed by the BU and DD type aerosols during summer and spring seasons, respectively. Further, the sub‐classification of aerosol types was carried out considering into account of the characteristics of absorbing aerosol index (AAI) (here called as Technique‐II). The two clustering techniques showed reasonable consistency in the obtained results. The various aerosol types (absorbing and non‐absorbing) and their change over a region are highly helpful in fine tuning the models to decrease the uncertainty in the radiative and climatic effects of aerosols.

Classifying Aerosols Based on Fuzzy Clustering and Their Optical and Microphysical Properties Study in Beijing, China

Classification of Beijing aerosol is carried out based on clustering optical properties obtained from three Aerosol Robotic Network (AERONET) sites. The fuzzy c-mean (FCM) clustering algorithm is used to classify fourteen-year (2001–2014) observations, totally of 6,732 records, into six aerosol types. They are identified as fine particle nonabsorbing, two kinds of fine particle moderately absorbing (fine-MA1 and fine-MA2), fine particle highly absorbing, polluted dust, and desert dust aerosol. These aerosol types exhibit obvious optical characteristics difference. While five of them show similarities with aerosol types identified elsewhere, the polluted dust aerosol has no comparable prototype. Then the membership degree, a significant parameter provided by fuzzy clustering, is used to analyze internal variation of optical properties of each aerosol type. Finally, temporal variations of aerosol types are investigated. The dominant aerosol types are polluted dust and desert dust in spring, fine particle nonabsorbing aerosol in summer, and fine particle highly absorbing aerosol in winter. The fine particle moderately absorbing aerosol occurs during the whole year. Optical properties of the six types can also be used for radiative forcing estimation and satellite aerosol retrieval. Additionally, methodology of this study can be applied to identify aerosol types on a global scale.

Analysis of aerosol absorption properties and transport over North Africa and the Middle East using AERONET data

Abstract. In this paper particle categorization and absorption properties were discussed to understand transport mechanisms at different geographic locations and possible radiative impacts on climate. The long-term Aerosol Robotic Network (AERONET) data set (1999–2015) is used to estimate aerosol optical depth (AOD), single scattering albedo (SSA), and the absorption Ångström exponent (αabs) at eight locations in North Africa and the Middle East. Average variation in SSA is calculated at four wavelengths (440, 675, 870, and 1020 nm), and the relationship between aerosol absorption and physical properties is used to infer dominant aerosol types at different locations. It was found that seasonality and geographic location play a major role in identifying dominant aerosol types at each location. Analyzing aerosol characteristics among different sites using AERONET Version 2, Level 2.0 data retrievals and the Hybrid Single Particle Lagrangian Integrated Trajectory model (HYSPLIT) backward trajectories shows possible aerosol particle transport among different locations indicating the importance of understanding transport mechanisms in identifying aerosol sources.

In-depth discrimination of aerosol types using multiple clustering techniques over four locations in Indo-Gangetic plains

Discrimination of aerosol types is essential over the Indo-Gangetic plain (IGP) because several aerosol types originate from different sources having different atmospheric impacts. In this paper, we analyzed a seasonal discrimination of aerosol types by multiple clustering techniques using AERosol RObotic NETwork (AERONET) datasets for the period 2007–2013 over Karachi, Lahore, Jaipur and Kanpur. We discriminated the aerosols into three major types; dust, biomass burning and urban/industrial. The discrimination was carried out by analyzing different aerosol optical properties such as Aerosol Optical Depth (AOD), Angstrom Exponent (AE), Extinction Angstrom Exponent (EAE), Abortion Angstrom Exponent (AAE), Single Scattering Albedo (SSA) and Real Refractive Index (RRI) and their interrelationship to investigate the dominant aerosol types and to examine the variation in their seasonal distribution. The results revealed that during summer and pre-monsoon, dust aerosols were dominant while during winter and post-monsoon prevailing aerosols were biomass burning and urban industrial, and the mixed type of aerosols were present in all seasons. These types of aerosol discriminated from AERONET were in good agreement with CALIPSO (the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) measurement.

Column-integrated aerosol optical properties and direct radiative forcing over the urban-industrial megacity Nanjing in the Yangtze River Delta, China.

Aerosol optical properties were measured and analyzed through the ground-based remote sensing Aerosol Robotic Network (AERONET) over an urban-industrial site, Nanjing (32.21° N, 118.72° E, and 62m above sea level), in the Yangtze River Delta, China, during September 2007-August 2008. The annual averaged values of aerosol optical depth (AOD500) and the Ångström exponent (AE440-870) were measured to be 0.94 ± 0.52 and 1.10 ± 0.21, respectively. The seasonal averaged values of AOD500 (AE440-870) were noticed to be high in summer (autumn) and low in autumn (spring). The characterization of aerosol types showed the dominance of mixed type followed by the biomass burning and urban-industrial type of aerosol at Nanjing. Subsequently, the curvature (a 2) obtained from the second-order polynomial fit and the second derivative of AE (α') were also analyzed to understand the dominant aerosol type. The single scattering albedo at 440nm (SSA440) varied from 0.88 to 0.93 with relatively lower (higher) values during the summer (spring), suggesting an increase in black carbon and mineral dust (desert dust) aerosols of absorbing (scattering) nature. The averaged monthly and seasonal evolutions of shortwave (0.3-4.0μm) direct aerosol radiative forcing (DARF) values were computed from the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model both at the top of atmosphere (TOA) and bottom of atmosphere (SUR) during the study period. Further, the aerosol forcing efficiency (AFE) and the corresponding atmospheric heating rates (AHR) were also estimated from the forcing within the atmosphere (ATM). The derived DARF values, therefore, produced a warming effect within the atmosphere due to strong absorption of solar radiation.

Identification of columnar aerosol types under high aerosol optical depth conditions for a single AERONET site in Korea

AbstractDominant aerosol types were classified using level 2 inversion products for the Anmyon Aerosol Robotic Network (AERONET) site in Korea for the period 1999–2007. The aerosol types were mineral dust (MD), MD mixed with carbon, and black carbon mixed coarse particles (BCCP) for coarse mode aerosols, black carbon (BC), organic carbon (OC), and secondary inorganic ions (SII) for fine mode aerosols, and mixed particles between. The classification was carried out using a clustering method based on parameters, including single scattering albedo (SSA), absorption Angstrom exponent (AAE), and fine mode volume fraction (FMVF). Among the seven aerosol types, MD was distinct, with the highest AAE and a very low FMVF and SII with the highest SSA and FMVF. BCCP was introduced to designate coarse particles mixed with BC, of which the AAE was lower than 1, despite a low FMVF. In addition to a large difference in AAE between BC and OC, the SSA of OC was larger than that of BC, indicating the effects of the white smoke produced from the smoldering phase of biomass burning. Monthly variations of the aerosol types were well interpreted by meteorology and emissions and coincided with those in the previous studies. Applying our results to well‐characterized global AERONET sites, we confirmed that the aerosol types at Anmyon were valid at other sites. However, the results also showed that the mean properties for aerosol types were influenced by the specific aerosols prevalent at the study sites.

Satellite and ground-based remote sensing of aerosols during intense haze event of October 2013 over lahore, Pakistan

Due to increase in population and economic development, the mega-cities are facing increased haze events which are causing important effects on the regional environment and climate. In order to understand these effects, we require an in-depth knowledge of optical and physical properties of aerosols in intense haze conditions. In this paper an effort has been made to analyze the microphysical and optical properties of aerosols during intense haze event over mega-city of Lahore by using remote sensing data obtained from satellites (Terra/Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)) and ground based instrument (AErosol RObotic NETwork (AERONET)) during 6-14 October 2013. The instantaneous highest value of Aerosol Optical Depth (AOD) is observed to be 3.70 on 9 October 2013 followed by 3.12 on 8 October 2013. The primary cause of such high values is large scale crop residue burning and urban-industrial emissions in the study region. AERONET observations show daily mean AOD of 2.36 which is eight times higher than the observed values on normal day. The observed fine mode volume concentration is more than 1.5 times greater than the coarse mode volume concentration on the high aerosol burden day. We also find high values (~0.95) of Single Scattering Albedo (SSA) on 9 October 2013. Scatter-plot between AOD (500 nm) and Angstrom exponent (440-870 nm) reveals that biomass burning/urban-industrial aerosols are the dominant aerosol type on the heavy aerosol loading day over Lahore. MODIS fire activity image suggests that the areas in the southeast of Lahore across the border with India are dominated by biomass burning activities. A Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model backward trajectory showed that the winds at 1000 m above the ground are responsible for transport from southeast region of biomass burning to Lahore. CALIPSO derived sub-types of aerosols with vertical profile taken on 10 October 2013 segregates the wide spread aerosol burden as smoke, polluted continental and dust aerosols.

Trend estimates of AERONET-observed and model-simulated AOTs between 1993 and 2013

Abstract Recently, temporal changes in Aerosol Optical Thickness (AOT) have been investigated based on model simulations, satellite and ground-based observations. Most AOT trend studies used monthly or annual arithmetic means that discard details of the generally right-skewed AOT distributions. Potentially, such results can be biased by extreme values (including outliers). This study additionally uses percentiles (i.e., the lowest 5%, 25%, 50%, 75% and 95% of the monthly cumulative distributions fitted to Aerosol Robotic Network (AERONET)-observed and ECHAM/MESSy Atmospheric Chemistry (EMAC)-model simulated AOTs) that are less affected by outliers caused by measurement error, cloud contamination and occasional extreme aerosol events. Since the limited statistical representativeness of monthly percentiles and means can lead to bias, this study adopts the number of observations as a weighting factor, which improves the statistical robustness of trend estimates. By analyzing the aerosol composition of AERONET-observed and EMAC-simulated AOTs in selected regions of interest, we distinguish the dominant aerosol types and investigate the causes of regional AOT trends. The simulated and observed trends are generally consistent with a high correlation coefficient (R = 0.89) and small bias (slope±2σ = 0.75 ± 0.19). A significant decrease in EMAC-decomposed AOTs by water-soluble compounds and black carbon is found over the USA and the EU due to environmental regulation. In particular, a clear reversal in the AERONET AOT trend percentiles is found over the USA, probably related to the AOT diurnal cycle and the frequency of wildfires. In most of the selected regions of interest, EMAC-simulated trends are mainly attributed to the significant changes of the dominant aerosols; e.g., significant decrease in sea salt and water soluble compounds over Central America, increase in dust over Northern Africa and Middle East, and decrease in black carbon and organic carbon over Australia.

Study of aerosol optical properties at Kunming in southwest China and long-range transport of biomass burning aerosols from North Burma

Seasonal variation of aerosol optical properties and dominant aerosol types at Kunming (KM), an urban site in southwest China, is characterized. Substantial influences of the hygroscopic growth and long-range transport of biomass burning (BB) aerosols on aerosol optical properties at KM are revealed. These results are derived from a detailed analysis of (a) aerosol optical properties (e.g. aerosol optical depth (AOD), columnar water vapor (CWV), single scattering albedo (SSA) and size distribution) retrieved from sunphotometer measurements during March 2012–August 2013, (b) satellite AOD and active fire products, (c) the attenuated backscatter profiles from the space-born lidar, and (d) the back-trajectories. The mean AOD440nm and extinction Angstrom exponent (EAE440−870) at KM are 0.42±0.32 and 1.25±0.35, respectively. Seasonally, high AOD440nm (0.51±0.34), low EAE440−870 (1.06±0.34) and high CWV (4.25±0.97cm) during the wet season (May – October) contrast with their counterparts 0.17±0.11, 1.40±0.31 and 1.91±0.37cm during the major dry season (November–February) and 0.53±0.29, 1.39±0.19, and 2.66±0.44cm in the late dry season (March–April). These contrasts between wet and major dry season, together with the finding that the fine mode radius increases significantly with AOD during the wet season, suggest the importance of the aerosol hygroscopic growth in regulating the seasonal variation of aerosol properties. BB and Urban/Industrial (UI) aerosols are two major aerosol types. Back trajectory analysis shows that airflows on clean days during the major dry season are often from west of KM where the AOD is low. In contrast, air masses on polluted days are from west (in late dry season) and east (in wet season) of KM where the AOD is often large. BB air mass is found mostly originated from North Burma where BB aerosols are lifted upward to 5km and then subsequently transported to southwest China via prevailing westerly winds.

A global aerosol classification algorithm incorporating multiple satellite data sets of aerosol and trace gas abundances

Abstract. Detecting the optical properties of aerosols using passive satellite-borne measurements alone is a difficult task due to the broadband effect of aerosols on the measured spectra and the influences of surface and cloud reflection. We present another approach to determine aerosol type, namely by studying the relationship of aerosol optical depth (AOD) with trace gas abundance, aerosol absorption, and mean aerosol size. Our new Global Aerosol Classification Algorithm, GACA, examines relationships between aerosol properties (AOD and extinction Ångström exponent from the Moderate Resolution Imaging Spectroradiometer (MODIS), UV Aerosol Index from the second Global Ozone Monitoring Experiment, GOME-2) and trace gas column densities (NO2, HCHO, SO2 from GOME-2, and CO from MOPITT, the Measurements of Pollution in the Troposphere instrument) on a monthly mean basis. First, aerosol types are separated based on size (Ångström exponent) and absorption (UV Aerosol Index), then the dominating sources are identified based on mean trace gas columns and their correlation with AOD. In this way, global maps of dominant aerosol type and main source type are constructed for each season and compared with maps of aerosol composition from the global MACC (Monitoring Atmospheric Composition and Climate) model. Although GACA cannot correctly characterize transported or mixed aerosols, GACA and MACC show good agreement regarding the global seasonal cycle, particularly for urban/industrial aerosols. The seasonal cycles of both aerosol type and source are also studied in more detail for selected 5° × 5° regions. Again, good agreement between GACA and MACC is found for all regions, but some systematic differences become apparent: the variability of aerosol composition (yearly and/or seasonal) is often not well captured by MACC, the amount of mineral dust outside of the dust belt appears to be overestimated, and the abundance of secondary organic aerosols is underestimated in comparison with GACA. Whereas the presented study is of exploratory nature, we show that the developed algorithm is well suited to evaluate climate and atmospheric composition models by including aerosol type and source obtained from measurements into the comparison, instead of focusing on a single parameter, e.g., AOD. The approach could be adapted to constrain the mix of aerosol types during the process of a combined data assimilation of aerosol and trace gas observations.

AERONET data–based determination of aerosol types

Aerosols are among the most interesting topics investigated by researchers because of their complicated characteristics and poor quantification. Moreover, significant uncertainties are associated with changes in the Earth's radiation budget. Previous studies have shown numerous difficulties and challenges in quantifying aerosol influences. In addition, the heterogeneity from aerosol loading and properties, including spatial, temporal, size, and composition features, presents a challenge. In this study, we investigated aerosol characteristics over two regions with different environmental conditions and aerosol sources. The study sites are Penang and Kuching in Malaysia, where a ground–based AErosol RObotic NETwork (AERONET) sun–photometer was deployed. The types of aerosol, such as biomass burning, urban/industrial, marine, and dust aerosols, for both study sites were identified by analyzing aerosol optical depth and angstrom exponent. Seasonal monsoon variation results in different aerosol optical properties, characteristics, and types of aerosols that are dominant in Penang and Kuching. Seasonal monsoon flow trend patterns from a seven–day back–trajectory frequency plotted by the Hybrid Single–Particle Lagrangian Integrated Trajectory model illustrated the distinct origins of trans–boundary aerosol sources. Finally, we improved our findings in Malaysian sites using the AERONET data from Singapore and Indonesia. Similarities in the optical properties of aerosols and the distribution types (referred to as homogeneous aerosol) were observed in the Penang–Singapore and the Kuching–Pontianak sites. The dominant aerosol distribution types were completely different for locations in the western (Penang–Singapore) and eastern (Kuching–Pontianak) parts of the South China Sea. This is a result of spatial and temporal heterogeneity. The spatial and temporal heterogeneities for the western and eastern portions of South China Sea provide information on the natural or anthropogenic processes that take place.

Aerosol optical properties over a coastal site in Goa, along the west coast of India

Spectral characteristics of the Aerosol optical depths (AODs) measured over a coastal site in Goa (15.46°N and 73.83°E), from a plateau ~50m above mean sea level, for the period 2008–2010, are analyzed to understand the inter-seasonal and intra-seasonal variability and to delineate different aerosol sources. A Microtops-II sunphotometer having five different wavelengths centered at 0.380, 0.440, 0.500, 0.675 and 0.870µm was used to estimate AODs in different seasons classified as: winter monsoon season from December to March (WMS), spring inter-monsoon season from April to May (SIMS), summer monsoon season from June to September (SMS) and fall inter-monsoon season from October to November (FIMS). The number of data (AODs) generated in each season is 569 in WMS, 131 in SIMS, 38 in SMS and 256 in FIMS. The highest AOD at 500nm (AOD500) was recorded in SIMS (0.43±0.18) while the lowest value was observed in SMS (0.32±0.10). The seasonal mean values of Ångström α computed from the least-square method in the wavelength range 0.440–0.870μm showed higher values (1.23±0.20) in FIMS than those in SMS (0.75±0.34). The highest Ångström β values were noticed in SIMS (0.25±0.10) and lowest in FIMS (0.17±0.06). To make a source appropriation and thus to resolve the complexity of aerosols in the study area, α was computed in different wavelength ranges, viz: short wavelengths (0.440–0.500μm) and long wavelengths (0.675–0.870μm), which revealed differing α values for different ranges of wavelengths. To account for the curvature, a second order polynomial fit is introduced. Subsequently, the second-order Ångström exponent (ά) and the coefficient of the second-order polynomial fit are analyzed to understand the dominant aerosol type.

Identification of aerosol types over an urban site based on air-mass trajectory classification

Columnar aerosol properties retrieved from MICROTOPS II Sun Photometer measurements during 2010–2013 over Pune (18°32′N; 73°49′E, 559m amsl), a tropical urban station in India, are analyzed to identify aerosol types in the atmospheric column. Identification/classification is carried out on the basis of dominant airflow patterns, and the method of discrimination of aerosol types on the basis of relation between aerosol optical depth (AOD500nm) and Ångström exponent (AE, α). Five potential advection pathways viz., NW/N, SW/S, N, SE/E and L have been identified over the observing site by employing the NOAA-HYSPLIT air mass back trajectory analysis. Based on AE against AOD500nm scatter plot and advection pathways followed five major aerosol types viz., continental average (CA), marine continental average (MCA), urban/industrial and biomass burning (UB), desert dust (DD) and indeterminate or mixed type (MT) have been identified. In winter, sector SE/E, a representative of air masses traversed over Bay of Bengal and Eastern continental Indian region has relatively small AOD (τpλ=0.43±0.13) and high AE (α=1.19±0.15). These values imply the presence of accumulation/sub-micron size anthropogenic aerosols. During pre-monsoon, aerosols from the NW/N sector have high AOD (τpλ=0.61±0.21), and low AE (α=0.54±0.14) indicating an increase in the loading of coarse-mode particles over Pune. Dominance of UB type in winter season for all the years (i.e. 2010–2013) may be attributed to both local/transported aerosols. During pre-monsoon seasons, MT is the dominant aerosol type followed by UB and DD, while the background aerosols are insignificant.

Identification of aerosol types over Indo-Gangetic Basin: implications to optical properties and associated radiative forcing.

The aerosols in the Indo-Gangetic Basin (IGB) are a mixture of sulfate, dust, black carbon, and other soluble and insoluble components. It is a challenge not only to identify these various aerosol types, but also to assess the optical and radiative implications of these components. In the present study, appropriate thresholds for fine-mode fraction and single-scattering albedo have been used to first identify the aerosol types over IGB. Four major aerosol types may be identified as polluted dust (PD), polluted continental (PC), black carbon-enriched (BCE), and organic carbon-enriched (OCE). Further, the implications of these different types of aerosols on optical properties and radiative forcing have been studied. The aerosol products derived from CIMEL sun/sky radiometer measurements, deployed under Aerosol Robotic Network program of NASA, USA were used from four different sites Karachi, Lahore, Jaipur, and Kanpur, spread over Pakistan and Northern India. PD is the most dominant aerosol type at Karachi and Jaipur, contributing more than 50% of all the aerosol types. OCE, on the other hand, contributes only about 12-15% at all the stations except at Kanpur where its contribution is ∼38%. The spectral dependence of AOD was relatively low for PD aerosol type, with the lowest AE values (<0.5); whereas, large spectral dependence in AOD was observed for the remaining aerosol types, with the highest AE values (>1.0). SSA was found to be the highest for OCE (>0.9) and the lowest for BCE (<0.9) type aerosols, with drastically different spectral variability. The direct aerosol radiative forcing at the surface and in the atmosphere was found to be the maximum at Lahore among all the four stations in the IGB.

Development and basic evaluation of a prognostic aerosol scheme (v1) in the CNRM Climate Model CNRM-CM6

Abstract. We have implemented a prognostic aerosol scheme (v1) in CNRM-CM6, the climate model of CNRM-GAME and CERFACS, based upon the GEMS/MACC aerosol module of the ECMWF operational forecast model. This scheme describes the physical evolution of the five main types of aerosols, namely black carbon, organic matter, sulfate, desert dust and sea salt. In this work, we describe the characteristics of our implementation, for instance, taking into consideration a different dust scheme or boosting biomass burning emissions by a factor of 2, as well as the evaluation performed on simulation output. The simulations consist of time slice simulations for 2004 conditions and transient runs over the 1993–2012 period, and are either free-running or nudged towards the ERA-Interim Reanalysis. Evaluation data sets include several satellite instrument AOD (aerosol optical depth) products (i.e., MODIS Aqua classic and Deep-Blue products, MISR and CALIOP products), as well as ground-based AERONET data and the derived AERONET climatology, MAC-v1. The uncertainty of aerosol-type seasonal AOD due to model internal variability is low over large parts of the globe, and the characteristics of a nudged simulation reflect those of a free-running simulation. In contrast, the impact of the new dust scheme is large, with modelled dust AODs from simulations with the new dust scheme close to observations. Overall patterns and seasonal cycles of the total AOD are well depicted with, however, a systematic low bias over oceans. The comparison to the fractional MAC-v1 AOD climatology shows disagreements mostly over continents, while that to AERONET sites outlines the capability of the model to reproduce monthly climatologies under very diverse dominant aerosol types. Here again, underestimation of the total AOD appears in several cases, sometimes linked to insufficient efficiency of the aerosol transport away from the aerosol sources. Analysis of monthly time series at 166 AERONET sites shows, in general, correlation coefficients higher than 0.5 and lower model variance than observed. A large interannual variability can also be seen in the CALIOP vertical profiles over certain regions of the world. Overall, this prognostic aerosol scheme appears promising for aerosol-climate studies. There is room, however, for implementing more complex parameterisations in relation to aerosols.

Aerosol optical properties under the condition of heavy haze over an urban site of Beijing, China.

In January 2013, several serious haze pollution events happened in North China. Cimel sunphotometer measurements at an urban site of Beijing (Chinese Academy of Meteorological Sciences-CAMS) from 1 to 30 January 2013 were used to investigate the detailed variation of aerosol optical properties. It was found that Angstrom exponents were mostly larger than 0.80 when aerosol optical depth values are higher than 0.60 at the urban region of Beijing during January 2013. The aerosol optical depth (AOD) at the urban region of Beijing can remain steady at approximately 0.40 before haze happening and then increased sharply to more than 1.50 at 500 nm with the onset of haze, which suggests that the fine-mode AOD is a factor of 20 of the coarse-mode AOD during a serious haze pollution event. The single scattering albedo was approximately 0.90 ± 0.03 at 440, 675, 870 and 1,020 nm during the haze pollution period. The single scattering albedo at 440 nm as a function of the fine-mode fraction was relatively consistent, but it was highly variable at 675, 870 and 1,020 nm. Except on January 12 and 18, all the fine-mode particle volumes were larger than those of coarse particles, which suggests that fine particles from anthropogenic activities made up most of the haze. Aerosol type classification analysis showed that the dominant aerosol types can be classified as both "mixed" and "urban/industrial (U/I) and biomass burning (BB)" categories during the heavy haze period of Beijing in January of 2013. The mixed category occurrence was about 31 %, while the U/I and BB was about 69 %.

Radiative signature of absorbing aerosol over the eastern Mediterranean basin

Abstract. The effects of absorbing aerosols on the atmospheric radiation budget and dynamics over the eastern Mediterranean region are studied using satellites and ground-based observations, and radiative transfer model calculations, under summer conditions. Climatology of aerosol optical depth (AOD), single scattering albedo (SSA) and size parameters were analyzed using multi-year (1999–2012) observations from Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging SpectroRadiometer (MISR) and AErosol RObotic NETwork (AERONET). Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)-derived aerosol vertical distributions and their classifications are used to calculate the AOD of four dominant aerosol types: dust, polluted dust, polluted continental, and marine aerosol over the region. The seasonal mean (June–August 2010) AODs are 0.22 ± 0.02, 0.11 ± 0.04, 0.10 ± 0.04 and 0.06 ± 0.01 for polluted dust, polluted continental, dust and marine aerosol, respectively. Changes in the atmospheric temperature profile as a function of absorbing aerosol loading were derived for the same period using observations from the AIRS satellite. We inferred heating rates in the aerosol layer of ~1.7 ± 0.8 K day−1 between 925 and 850 hPa, which is attributed to aerosol absorption of incoming solar radiation. Radiative transfer model (RTM) calculations show significant atmospheric warming for dominant absorbing aerosol over the region. A maximum atmospheric forcing of +16.7 ± 7.9 Wm−2 is calculated in the case of polluted dust, followed by dust (+9.4 ± 4.9 Wm−2) and polluted continental (+6.4 ± 4.5 Wm−2). RTM-derived heating rate profiles for dominant absorbing aerosol show warming of 0.1–0.9 K day−1 in the aerosol layer (&lt; 3.0 km altitudes), which primarily depend on AODs of the different aerosol types. Diabatic heating due to absorbing aerosol stabilizes the lower atmosphere, which could significantly reduce the atmospheric ventilation. These conditions can enhance the "pollution pool" over the eastern Mediterranean.