Characterization Of Atmospheric Aerosols Research Articles

Approximated expression of the hygroscopic growth factor for polydispersed aerosols

Hygroscopic growth of aerosols plays an important role in the characterization of atmospheric aerosols. Physico-chemical and optical properties of aerosols are dependent on relative humidity (RH) as well as on their size and composition. In this study, scattering enhancement factors, f(RH), for polydispersed aerosols were approximated. f(RH) of ammonium sulfate and ammonium nitrate (AS) and NaCl aerosols (ss) were considered under the assumption of externally mixed aerosols. f(RH) was calculated using the Mie theory for polydispersed aerosols at a given RH and corresponding water uptake (denoted as fMie(RH)). f(RH) was approximated as a quadratic function of RH (denoted as fapp(RH)). The obtained approximated f(RH) or fapp(RH)) values were compared with the values based on the Mie theory and showed a reasonable agreement between them. To the best of our knowledge, this is the first study that parametrizes the size dependency of f(RH) for log normally distributed aerosols.

Investigation and characterization of atmospheric aerosols over the Urmia Lake using the satellite data and synoptic recordings

The Urmia Lake, a hypersaline lake in Northwest Iran is facing a severe drying scenario. The dried part of the lake can act as a source of salt particles that may contaminate the atmosphere of the lake and its surrounding regions. We used the CALIPSO satellite recordings on particulate depolarization ratio (PDR) and aerosol optical depth (AOD) at 532 nm as well as MODIS AOD at 550 nm during June 2006 to December 2017, to characterize the atmospheric aerosols over the Urmia Lake water catchment region. By monitoring the aerosol layer height that is retrieved from the CALIPSO recordings, we found that most of the dust layers over the Urmia Lake, are transported from the neighboring sources. The mean PDR value for the aerosol layers that are in contact with the lake surface during dry months is ~0.16 ± 0.03 but for dense dust layers, high above the mountain ranges, this is ~0.19 ± 0.04. This study shows that the Urmia Lake is a minor source of atmospheric mineral particles and is very much under the influence of other major neighboring dust sources. Even though it is not easy to distinguish between transported dust layers and particles that may originate from the lake, our investigations show that the lake is mostly active during the driest times of the year, i.e., June to September. During these times, the PDR for the aerosols that are appearing in the vicinity of the dried lake bed is very close to that of dry salt particles.

Physico-chemical characterization and sink mechanism of atmospheric aerosols over South-west India

The properties of the atmospheric aerosols depend on the source region and on the modifications that occur during their transport in the air. We have studied physical and chemical properties of aerosols along with their sink mechanism over two locations in southwest India, an urban site (Pune) and well-established climate observatory at Sinhagad (SINH), which represents rural and high altitude site. The ground-based measurements of aerosols, together with their radiative properties in this study have provided means to understand the observed variability and the impact on the aerosol radiative properties effectively over this region. The annual mean elemental carbon concentration (3.4 µg m− 3) at Pune was observed about three times higher compared to SINH (1.3 µg m− 3), indicating strong emissions of carbon-rich aerosols at the urban location. Aerosol optical properties were derived using the OPAC model which were used to compute the Aerosol radiative forcing (ARF) over both stations calculated using SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer) model shows pronounced seasonal variations due to changes in aerosol optical depth and single scattering albedo at both locations. The year-round ARF was 4–5 times higher over Pune (31.4 ± 3.5 Wm− 2) compared to SINH (7.2 ± 1.1 Wm− 2). The atmospheric heating rate due to aerosols shows a similar pattern as ARF for these locations. The heating was higher in the wintertime, ~ 0.9–1.6 K day− 1 at Pune, and ~ 0.3–0.6 K day− 1 at SINH. The estimated scavenging ratio was found high for NO3− and Ca.2+. The wet deposition fluxes of Cl−, SO42−, Na+, Mg2+ were observed higher for SINH as compared to Pune, due to the high amount of rain received at SINH.

Quantifying and improving the optical performance of the laser ablation aerosol particle time of flight mass spectrometer (LAAPToF) instrument

Single particle mass spectrometer (SPMS) instruments have been used for in-situ chemical characterization of atmospheric aerosols, both in the field and laboratory, for over two decades. SPMSs typi...

Coarse, fine and ultrafine particles of sub-urban continental aerosols measured using an 11-stage Berner cascade impactor

The main aim of this work is characterization of atmospheric aerosol using 11 stage cascade impactor. The first investigation of size-segregated sub-urban aerosols from the continental part of the Balkan peninsula in 11 fractions in the range of 0.0085 < Dp < 16 μm was performed from March 2012 to December 2013. Aerosols were measured at the Zeleno Brdo observatory (ϕ = 44°48’; λ = 20°28′–243 m above sea level), the highest landmark on the eastern side of Belgrade. Zeleno Brdo is surrounded by wooded vegetation and comprises of both southern facing rural and north-west orientated urban areas. About 70% of total aerosols are fine particles, belonging especially to the PM0.53–1.06 fraction which is found to be more pronounced in winter period. In this work, we applied tests of probability function models for three distributions: normal, log-normal and three-parameter Weibull, by comparing expected and observed values. We found that these models offer the possibility to determine whether the dominant emission source was the vicinity or distance of the measuring point. Results of this test could be a significant supplement to existing multivariate mathematical models for source apportionment, providing accurate estimation of the origin of emission sources and offering information on their position relative to the investigated area (local, regional or remote). In addition, the dependence of particle concentrations for each fraction investigated versus meteorological parameters was determined.

Continental outflow of anthropogenic aerosols over Arabian Sea and Indian Ocean during wintertime: ICARB-2018 campaign

Chemical characterisation of atmospheric aerosols over Arabian Sea (AS) and Indian Ocean (IO) have been carried out during the winter period (January to February 2018) as part of the Integrated Campaign for Aerosols, gases and Radiation Budget (ICARB-2018). Mass concentrations of organic carbon (OC), elemental carbon (EC), water soluble and insoluble OC (WSOC, WIOC), primary and secondary OC (POC, SOC), water-soluble inorganic ions and trace metals have been estimated with a view to identify and quantify the major anthropogenic pollutants affecting the oceanic environments. Aerosol mass loading was found to exhibit strong spatial heterogeneity (varying from 13 to 84 μg m−3), significantly modulated by the origin of air-mass trajectories. Chemical analysis of aerosols revealed the presence of an intense pollution plume over south-eastern coastal Arabian Sea, near to south-west Indian peninsula (extending from ~ 12°N to 0° at 75°E) with a strong latitudinal gradient (~3 μg m−3/deg. from north to south) dominated by anthropogenic species contributing as high as 73% (38% nss-SO42−, 24.2% carbonaceous aerosols (21% Organic Matter, 3.2% EC) and 10% NH4+). Anthropogenic signature over oceanic environment was also evident from the dominance and high enrichment of elements like Zn, Cu, Mn and Pb in trace metals. Long-range transport of air-masses originating from Indo Gangetic Plains and its outflow regions in Bay of Bengal, has been seen over Arabian Sea during winter, that imparted such strong anthropogenic signatures over this oceanic environment. Comparison with previous cruise studies conducted nearly two decades ago shows a more than two-fold increase in the concentration of nss-SO42−, over the continental outflow region in Arabian Sea.

Characterization of atmospheric aerosols and source apportionment analyses in urban Harbin, northeast China

Detailed knowledge of aerosol chemical characteristics and emission sources play a key role in climate and human health. In this study, we collected the atmospheric aerosol particles in urban Harbin, the northernmost provincial capital in northeast China, using an ambient sampler during the period from April to June 2017. Morphological and chemical composition analyses of collected particles were performed using a Fourier transform infrared spectrometer (FTIR), an X-ray fluorescence spectrometer (XRF), and a scanning electron microscope equipped with an energy dispersion spectrum (SEM-EDS). Emission sources of these aerosol particles were determined via an enrichment factor analysis and then their variation were further discussed. During the studying period, the atmospheric particles were mainly composed of organics, inorganic ions and oxides with 20 elements (i.e., C, O, Na, Mg, Al, Si, P, and S) observed. Among the detected elements, Cr, Ni, Cu, Br, and Zn were found to be enriched, indicating considerable anthropogenic influence during high pollution days. In early April, most of the aerosol particles were emitted from coal-fired boilers and coal-fired power plants; in early May, they mainly originated from soil dust and dust, traffic, and industry emissions; and in late May and June, traffic and industry became the major aerosol sources over Harbin.

Characterization of atmospheric aerosol (PM10 and PM2.5) from a medium sized city in São Paulo state, Brazil

Air pollution causes deleterious effects on human health with aerosols being among the most polluting agents. The objective of this work is the characterization of the PM2.5 and PM10 aerosol mass in the atmosphere. The methods of analysis include WD-XRF and EDS. Data were correlated with meteorological information and air mass trajectories (model HYSPLIT) by multivariate analysis. A morphological structural analysis was also carried out to identify the probable sources of atmospheric aerosols in the city of São José do Rio Preto, Brazil. The mean mass concentration values obtained were 24.54 μg/m3 for PM10, above the WHO annual standard value of 20 μg/m3 and 10.88 μg/m3 for PM2.5 whose WHO recommended limit is 10 μg/m3. WD-XRF analysis of the samples revealed Si and Al as major components of the coarse fraction. In the fine fraction, the major elements were Al and S. The SEM-FEG characterization allowed identifying the morphology of the particles in agglomerates, ellipsoids and filaments in the PM10, besides spherical in the PM2.5. The analysis by EDS corroborated WD-XRF results, identifying the crustal elements, aluminosilicates and elements of anthropogenic origin in the coarse fraction. For the fine fraction crustal elements were also identified; aluminosilicates, black carbon and spherical particles (C and O) originating from combustion processes were predominant. The use of multivariate analysis to correlate air mass trajectories with the results of the morpho-structural characterization of the particulate matter allowed confirmation of the complex composition of the particles resulting from the combination of both local and long-distance sources.

Molecular Characterization of Atmospheric Organic Aerosol by Mass Spectrometry.

Atmospheric aerosol, particulate matter suspended in the air we breathe, exerts a strong impact on our health and the environment. Controlling the amount of particulate matter in air is difficult, as there are many ways particles can form by both natural and anthropogenic processes. We gain insight into the sources of particulate matter through chemical composition measurements. A substantial portion of atmospheric aerosol is organic, and this organic matter is exceedingly complex on a molecular scale, encompassing hundreds to thousands of individual compounds that distribute between the gas and particle phases. Because of this complexity, no single analytical technique is sufficient. However, mass spectrometry plays a crucial role owing to its combination of high sensitivity and molecular specificity. This review surveys the various ways mass spectrometry is used to characterize atmospheric organic aerosol at a molecular level, tracing these methods from inception to current practice, with emphasis on current and emerging areas of research. Both offline and online approaches are covered, and molecular measurements with them are discussed in the context of identifying sources and elucidating the underlying chemical mechanisms of particle formation. There is an ongoing need to improve existing techniques and develop new ones if we are to further advance our knowledge of how to mitigate the unwanted health and environmental impacts of particles.

Identification of absorbing aerosol types at a site in the northern edge of Indo-Gangetic Plain and a polluted valley in the foothills of the central Himalayas

Identification of atmospheric aerosol types and characterization of absorbing aerosols, based on AErosol RObotic NETwork (AERONET) data collected during 2013–2014 over two sites in Nepal: Lumbini in the northernmost part of central Indo-Gangetic Plain (IGP) and Kathmandu Valley in foothills of the central Himalayas, have been conducted in the present study. The relationship between four aerosol parameters; Extinction Angstrom Exponent (EAE), Absorption Angstrom Exponent (AAE), Single Scattering Albedo (SSA) and Real Refractive Index (RRI) was analyzed to study the aerosol types. This resulted in the identification of two types of aerosols concerning their origin: biomass burning and urban/industrial mix. Furthermore, to understand the absorbing aerosol types, the relationship between aerosol size parameters; Fine Mode Fraction (FMF) and Angstrom Exponent (AE), and aerosol absorption characteristics; SSA and AAE were investigated. In regards to the absorbing aerosol types, ‘Mostly BC’ was the dominant absorbing aerosol, over both sites, with comparatively negligible contribution from other absorbing aerosol types such as dust. The aerosol subtypes obtained from satellite-borne CALIPSO instrument supported the results derived from the AERONET data. The CALIPSO images also indicated that the aerosols over the foothills of the Himalayas could extend to the height of >5 km above the ground, which could be transported towards the Himalayan and Tibetan Plateau (HTP) region with sensitive ecosystems. The multi-sites based study of long-term records is required to elucidate the nature and trends of aerosols in the HTP region and any perturbation to the atmospheric environment and other environments in this region.

A 13-year climatological study on the variations of aerosol and cloud properties over Kazakhstan from remotely sensed satellite observations

The Republic of Kazakhstan, by geographical and climatological conditions, is a key location for the characterization of atmospheric aerosols due to an unprecedented increase of aerosol's concentrations in the recent years. This study presents a 13-year (2003-2015) analysis of the spatiotemporal distributions and trends of aerosol and cloud properties derived from the Moderate Resolution Imaging Spectroradiometer (MODIS)–Aqua (Dark Target–DT) and Ozone Monitoring Instrument (OMI) over Kazakhstan. The spatial patterns of annual mean AOD were generally characterized with low (<0.1), moderate (0.1–0.5) and high (>035) AOD centers over Kazakhstan. The respective maximum and minimum values of AOD550 were observed in July (0.22 ± 0.07) and November (0.12 ± 0.03), with an annual mean of 0.18 ± 0.03. The seasonal mean values of AOD was noticed to be maximum (0.21 ± 0.02) during summer and minimum (0.14 ± 0.01) during autumn seasons. The inter-annual variations in AOD showed enhanced AOD values during 2012 (0.23) followed by 2014 (0.21) and low during 2003 (0.15) and 2004 (0.14). The spatial trend analysis revealed an increase in AOD over most parts of the study domain. Also, the most important cloud parameters such as cloud fraction (CF) and cloud effective radius (CER) were investigated to assess their relationship with the AOD over Kazakhstan. It was found that the CF and CER were negatively and positively correlated with AOD over most parts of the study domain attributed to the strong influence of dust and continental background aerosols, respectively. The backward trajectories obtained from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model showed air parcels originating from the Barents Sea, Russia, Europe, China, and the mainland of Kazakhstan. The results derived from the present study gives a sense of aerosol and cloud properties, and form a basis for further research over this unique and unexplored landmass of the Asian Continent.

Calibration and validation of Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) polarization measurements.

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), a precursor to the future Multi-Angle Imager for Aerosols satellite instrument, is a remote-sensing instrument for the characterization of atmospheric aerosols and clouds. To help discriminate between different aerosol particle types, which is crucial to improve our understanding of their impact on climate and air quality, AirMSPI acquires imagery over multiple view angles in the ultraviolet, visible, and near-infrared, and it employs dual photoelastic modulators (PEMs) to target an uncertainty requirement of ±0.005 in the degree of linear polarization (DoLP) at selected wavelengths. Laboratory polarimetric calibrations using a second-generation Polarization State Generator-2 (PSG-2) and validation measurements at 0<DoLP<1 demonstrate a systematic uncertainty of <0.002. In-flight calibrations of the temperature sensitivity of the PEMs, which could otherwise introduce DoLP errors up to 0.02, are extracted from onboard "validator" measurements as well as from the AirMSPI imagery of the Earth. After this in-flight calibration, the stability of measurements of the validator's DoLP throughout the POlarimeter Definition EXperiment and Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys field campaigns is ±0.001. Comparisons of DoLP data from these campaigns with the Research Scanning Polarimeter show root-mean-square differences ranging between 0.003 and 0.006, while the regression slopes deviate from unity by currently unexplained values up to 0.024. The observed differences are the result of measurement errors in both instruments, as well as imperfections in the intercomparison. A complete polarimetric uncertainty model for AirMSPI is presented, including the effects of absolute calibration uncertainty, in-flight modulation uncertainty, and random noise.

Chemical characterisation and source identification of atmospheric aerosols in the Snowy Mountains, south-eastern Australia

Characterisation of atmospheric aerosols is of major importance for: climate, the hydrological cycle, human health and policymaking, biogeochemical and palaeo-climatological studies. In this study, the chemical composition and source apportionment of PM2.5 (particulate matter with aerodynamic diameters less than 2.5μm) at Yarrangobilly, in the Snowy Mountains, SE Australia are examined and quantified. A new aerosol monitoring network was deployed in June 2013 and aerosol samples collected during the period July 2013 to July 2017 were analysed for 22 trace elements and black carbon by ion beam analysis techniques. Positive matrix factorisation and back trajectory analysis and trajectory clustering methods were employed for source apportionment and to isolate source areas and air mass travel pathways, respectively. This study identified the mean atmospheric PM2.5 mass concentration for the study period was (3.3±2.5)μgm−3. It is shown that automobile (44.9±0.8)%, secondary sulfate (21.4±0.9)%, smoke (12.3±0.6)%, soil (11.3±0.5)% and aged sea salt (10.1±0.4)% were the five PM2.5 source types, each with its own distinctive trends. The automobile and smoke sources were ascribed to a significant local influence from the road network and bushfire and hazard reduction burns, respectively. Long-range transport are the dominant sources for secondary sulfate from coal-fired power stations, windblown soil from the inland saline regions of the Lake Eyre and Murray-Darling Basins, and aged sea salt from the Southern Ocean to the remote alpine study site. The impact of recent climate change was recognised, as elevated smoke and windblown soil events correlated with drought and El Niño periods. Finally, the overall implications including potential aerosol derived proxies for interpreting palaeo-archives are discussed. To our knowledge, this is the first long-term detailed temporal and spatial characterisation of PM2.5 aerosols for the region and provides a crucial dataset for a range of multidisciplinary research.

Earlinet single calculus chain: new products overview

The Single Calculus Chain (SCC) is an automatic and flexible tool to analyze raw lidar data using EARLINET quality assured retrieval algorithms. It has been already demonstrated the SCC can retrieve reliable aerosol backscatter and extinction coefficient profiles for different lidar systems. In this paper we provide an overview of new SCC products like particle linear depolarization ratio, cloud masking, aerosol layering allowing relevant improvements in the atmospheric aerosol characterization.

Spatial-Temporal Characterization of Atmospheric Aerosols via Airborne Spectral Imaging and Growing Hierarchical Self-Organizing Maps

Neural network analysis based on Growing Hierarchical Self-Organizing Map (GHSOM) is used to examine Spatial-Temporal characteristics in Aerosol Optical Depth (AOD), Ångström Exponent (ÅE) and Precipitation Rate (PR) over selected East African sites from 2000 to 2014. The selected sites of study are Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0° - 0.6°S; 35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). GHSOM analysis reveals a marked spatial variability in AOD and ÅE that is associated to changing PR, urban heat islands, diffusion, direct emission, hygroscopic growth and their scavenging from the atmosphere specific to each site. Furthermore, spatial variability in AOD, ÅE and PR is distinct since each variable corresponds to a unique level of classification. On the other hand, GHSOM algorithm efficiently discriminated by means of clustering between AOD, ÅE and PR during Long and Short rain spells and dry spell over each variable emphasizing their temporal evolution. The utilization of GHSOM therefore confirms the fact that regional aerosol characteristics are highly variable be it spatially or temporally and as well modulated by PR received over each variable.

Optical Characterization of Atmospheric Aerosols via Airborne Spectral Imaging and Self-Organizing Map for Climate Change Diagnostics

Self-Organizing Map (SOM) analysis is used to perform optical characteri- zation of both Aerosol Optical Depth (AOD) and Angstrom Exponent (AE) retrieved from Moderate-resolution Imaging Spectroradiometer (MODIS) in relation to Precipitation Rate (PR) from Tropical Rainfall Measurement Mission (TRMM) over selected East African sites from 2000 to 2014 and further diagnose climate change over the region if any. SOM reveals a marked spatial variability in AOD and AE that is associated to changing aerosol transport, urban heat islands, diffusion, direct emission, hygroscopic growth and their scavenging from the atmosphere specific to each site. Temporally, all sites except Mbita and Kampala indicate two clusters in AOD that are associated to prevailing dry and wet seasons over East Africa. Moreover, all sites except Mbita and Mount Kilimanjaro show two clusters in AE that are related to aerosol mode of generation and composition over the region. The single cluster in AOD and ？E over Mbita indicate that aerosol characteristics over the site are influenced by biomass burning and local air circulation rather than the monsoon precipitation throughout the study period.

Bayesian Merging of MISR and MODIS Aerosol Optical Depth Products Using Error Distributions From AERONET

Aerosol Optical depth (AOD) routinely retrieved by spaceborne sensors (e.g., MODIS and MISR) is widely used in studies focused on atmospheric aerosol characterization, their variability/trends, and environmental/climate impacts. Despite significant advancement in the understanding of aerosol loading patterns, there exist global/regional differences among AOD products from various satellite sensors; owing to differences in retrieval algorithms, spatial/temporal resolution and sampling, and cloud-screening schemes. A merged AOD dataset combining multiple satellite retrievals is therefore desirable, which utilizes the strengths of individual products, and at the same time reduces biases relative to ground-based measurements (e.g., from aerosol robotic network (AERONET)). In view of this, a Level-2 ‘‘merged’’ AOD dataset based on MODIS and MISR retrievals is developed in this study using Bayesian principles, which takes into account the error distribution of AOD from AERONET data. The merged AOD dataset is demonstrated over the Indo-Gangetic Plains, in southern Asia, and is intercompared with existing satellite and AERONET data. The RMSE of the merged AOD data (0.08–0.13) is lower than the MISR and MODIS retrievals. Additionally, the merged AOD data have higher correlation with AERONET data ( r within 0.89–0.93), compared to MISR (0.82–0.89) and MODIS (0.76–0.77) data. In terms of the expected error (EE), the accuracy of merged data is found to be higher, with larger percent of merged AOD within the EE envelope (74.7%–88.7%) compared to MISR (62.7%–84.9%) and MODIS (67.9%–69.8%) data. The merging methodology and resulting dataset are especially relevant in the scenario of fusing multisensor retrievals for producing long-term satellite-based climate data records.

Traffic is a major source of atmospheric nanocluster aerosol

In densely populated areas, traffic is a significant source of atmospheric aerosol particles. Owing to their small size and complicated chemical and physical characteristics, atmospheric particles resulting from traffic emissions pose a significant risk to human health and also contribute to anthropogenic forcing of climate. Previous research has established that vehicles directly emit primary aerosol particles and also contribute to secondary aerosol particle formation by emitting aerosol precursors. Here, we extend the urban atmospheric aerosol characterization to cover nanocluster aerosol (NCA) particles and show that a major fraction of particles emitted by road transportation are in a previously unmeasured size range of 1.3-3.0 nm. For instance, in a semiurban roadside environment, the NCA represented 20-54% of the total particle concentration in ambient air. The observed NCA concentrations varied significantly depending on the traffic rate and wind direction. The emission factors of NCA for traffic were 2.4·1015 (kgfuel)-1 in a roadside environment, 2.6·1015 (kgfuel)-1 in a street canyon, and 2.9·1015 (kgfuel)-1 in an on-road study throughout Europe. Interestingly, these emissions were not associated with all vehicles. In engine laboratory experiments, the emission factor of exhaust NCA varied from a relatively low value of 1.6·1012 (kgfuel)-1 to a high value of 4.3·1015 (kgfuel)-1 These NCA emissions directly affect particle concentrations and human exposure to nanosized aerosol in urban areas, and potentially may act as nanosized condensation nuclei for the condensation of atmospheric low-volatile organic compounds.

Undergraduate Research and Training in Ion-Beam Analysis of Environmental Materials

We have an active undergraduate research program at the Union College Ion-Beam Analysis Laboratory (UCIBAL) focused on the study of environmental materials. Accelerator-based ion-beam analysis (IBA) is a powerful tool for the study of environmental pollution because it can provide information on a broad range of elements with high sensitivity and low detection limits, is non-destructive, and requires little or no sample preparation. It also provides excellent training for the next generation of environmental scientists. Beams of protons and alpha particles with energies of a few MeV from the 1.1-MV tandem Pelletron accelerator (NEC Model 3SDH) in the UCIBAL are used to characterize environmental samples using IBA techniques such as proton-induced X-ray emission, Rutherford back-scattering, and proton-induced gamma-ray emission. Recent projects include the characterization of atmospheric aerosols in the Adirondack Mountains of upstate New York, the study of heavy metal pollutants in river sediment, measurements of Pb diffusion in sulfide minerals to help constrain the determination of the age of iron meteorites, and the search for heavy metals and toxins in artificial turf.

Size-segregated aerosol chemical composition from an agro-industrial region of São Paulo state, Brazil

The main objective of this research included a detailed inorganic and organic characterisation of atmospheric aerosols, to understand the changes in their composition as a result of the implementation of the Sugar and Ethanol Industry Green Protocol, in the southeastern region of Brazil. A set of 10 samples segregated into PM2.5, PM2.5–10 and PM>10 fractions were collected in May and July of 2014, covering the beginning of the sugarcane harvest period. The analytical methods included gravimetric determination, water-soluble ions by ion chromatography, major elements by inductively coupled plasma mass spectrometry, carbonaceous content by a thermal-optical system and organic speciation by gas chromatography–mass spectrometry. A substantially higher mean concentration (57 ± 36 μg m−3) was obtained for PM2.5 in comparison with PM2.5–10 (15 ± 6.2 μg m−3) and PM>10 (8.5 ± 13 μg m−3). The carbonaceous content represented, on average, approximately 18 and 21 % of the particulate matter of the PM2.5 and PM2.5–10 fractions, respectively. On average, water-soluble ions accounted for 12 and 7.7 % of the PM2.5 and PM2.5–10 mass, respectively. With the implementation of the Green Protocol, a decrease of biomass burning ion tracers would be expected, however, this trend was not observed. With regard to major elements, aerosols from both fractions were dominated by K, Ca, Na and Al. Concentrations of the major elements were lower than those observed in earlier studies. Organic compounds were present at higher levels in the fine than in the coarse fraction. n-Alkanes, n-alkanoic acids and polycyclic aromatic hydrocarbons related to biomass combustion showed lower concentrations than previously reported.