Comparison of five methodologies to apportion organic aerosol sources during a PM pollution event

This study presents a comparison of five methodologies to apportion primary (POA) and secondary organic aerosol (SOA) sources from measurements performed in the Paris region (France) during a highly processed PM pollution event. POA fractions, estimated from EC-tracer method and positive matrix factorization (PMF) analyses, conducted on measurements from PM₁₀ filters, aerosol chemical speciation monitor (ACSM) and offline aerosol mass spectrometry (AMS), were all comparable (2.2-3.7 μg m^-3 as primary organic carbon (POC)). Associated relative uncertainties (measurement + model) on POC estimations ranged from 8 to 50%. The best apportionment of primary traffic OA was achieved using key markers (EC and 1-nitropyrene) in the chemical speciation-based PMF showing more pronounced rush-hour peaks and greater correlation with NO_x than other traffic related POC factors. All biomass burning-related factors were in good agreement, with a typical diel profile and a night-time increase linked to residential heating. If PMF applied to ACSM data showed good agreement with other PMF outputs corrected from dust-related factors (coarse PM), discrepancies were observed between individual POA factors (traffic, biomass burning) and directly comparable SOA factors and highly oxidized OA. Similar secondary organic carbon (SOC) concentrations (3.3 ± 0.1 μg m^-3) were obtained from all approaches, except the SOA-tracer method (1.8 μg m^-3). Associated uncertainties ranged from 14 to 52% with larger uncertainties obtained for PMF-chemical data, EC- and SOA-tracer methods. This latter significantly underestimated total SOA loadings, even including biomass burning SOA, due to missing SOA classes and precursors. None of the approaches was able to identify the formation mechanisms and/or precursors responsible for the highly oxidized SOA fraction associated with nitrate- and/or sulfate-rich aerosols (35% of OA). We recommend the use of a combination of different methodologies to apportion the POC/SOC concentrations/contributions to get the highest level of confidence in the estimates obtained.

Groundwater and surface water quality characterization through positive matrix factorization combined with GIS approach

This study aims at testing the effectiveness of Positive Matrix Factorization in characterizing groundwater and surface water quality, in terms of identifying main hydrochemical features and processes (natural and anthropogenic) that govern them. This method is applied in a hydro-system featured by a strong interrelation between groundwater and surface water and highly impacted by agricultural activities. Therefore, a holistic approach considering groundwater together with the surface water bodies, consisting in lake, several rivers and springs, was used. Multivariate statistical analysis, in particular Factor Analysis, has been proved to be effective in elaborating and interpreting water quality data highlighting the information carried within them, but it presents some limitations: it does not consider data uncertainty and it groups variables which are correlated positively and negatively. Moreover, in some cases the resulting factors are not clearly interpretable, describing each one various overlapping features/processes. Here, Positive Matrix Factorization is applied to groundwater and surface water quality data, and the results are compared to those obtained through a Factor Analysis in terms of both factor profiles and their spatial distribution through a GIS approach. Results of isotopes analysis are used to validate PMF output and support interpretation. Positive Matrix Factorization allows to consider data uncertainty and the solution respects two positivity constraints, based on the concept of chemical mass balance, which leads to a more environmentally interpretable solution. Results show that Positive Matrix Factorization identifies five different factors reflecting main features and natural and anthropogenic processes affecting the study area: 1) surface water used for irrigation, 2) groundwater subjected to reducing processes at advanced stages, 3) groundwater subjected to reducing processes at early stages, 4) groundwater residence time and 5) the effects of the agricultural land use on both groundwater and surface water. Positive Matrix Factorization leads to a more detailed understanding of the studied system as compared to Factor Analysis which identifies only three factors with overlapping information. Based on the results of this study, Positive Matrix Factorization could be a useful technique to perform groundwater and surface water quality characterization and to reach a deeper understanding of the phenomena that govern water chemistry.

Quantification of source specific black carbon scavenging using an aethalometer and a disdrometer

Aerosol black carbon (BC) is the second strongest contributor to global warming, after CO₂, and it is linked to many adverse health effects. A sampling campaign of 15 months was carried out in León (Spain) in order to evaluate the scavenging of BC with an ensemble aethalometer-disdrometer. The aethalometer provides the concentration of equivalent black carbon (eBC), and the disdrometer, the raindrop size distribution. A total of seventy-five rain events were studied and in 73% of them there was an effective (eBC_initial > eBC_final) scavenging, with a mean decrease of 48 ± 37% in long rain events (>8 h) and 39 ± 38% in short rain events. The scavenging of BC is strongly related to its source. Thus, the scavenging coefficient (SC) mean value of the BC from fossil fuel (eBC_ff) for short and long rain events was 5.1 10^-5 and 1.3 10^-5 s^-1, respectively. For the BC from biomass burning (eBC_bb), the SC values were 1.6 10^-4 and 2.8 10^-5 s^-1 in short and long events, respectively. There was a significant positive correlation between the SC and the number of drops with diameters between 0.375 and 2.5 mm. Rain scavenging of eBC was analyzed depending on the air mass origin obtaining an effective scavenging for air masses from Atlantic, Arctic and Africa. A linear model (R² = 0.72) was built to estimate the ΔeBC values with variables from an aethalometer, a disdrometer and a weather station: eBC concentration before rain, swept volume and precipitation accumulated. A Kolmogorov-Smirnov statistical test confirmed the goodness of fit of the model to the measured data.

Trace Metals in Soot and PM2.5 from Heavy-Fuel-Oil Combustion in a Marine Engine

Heavy fuel oil (HFO) particulate matter (PM) emitted by marine engines is known to contain toxic heavy metals, including vanadium (V) and nickel (Ni). The toxicity of such metals will depend on the their chemical state, size distribution, and mixing state. Using online soot-particle aerosol mass spectrometry (SP-AMS), we quantified the mass of five metals (V, Ni, Fe, Na, and Ba) in HFO-PM soot particles produced by a marine diesel research engine. The in-soot metal concentrations were compared to in-PM2.5 measurements by inductively coupled plasma-optical emission spectroscopy (ICP-OES). We found that <3% of total PM2.5 metals was associated with soot particles, which may still be sufficient to influence in-cylinder soot burnout rates. Since these metals were most likely present as oxides, whereas studies on lower-temperature boilers report a predominance of sulfates, this result implies that the toxicity of HFO PM depends on its combustion conditions. Finally, we observed a 4-to-25-fold enhancement in the ratio V:Ni in soot particles versus PM2.5, indicating an enrichment of V in soot due to its lower nucleation/condensation temperature. As this enrichment mechanism is not dependent on soot formation, V is expected to be generally enriched within smaller HFO-PM particles from marine engines, enhancing its toxicity.

Gasoline cars produce more carbonaceous particulate matter than modern filter-equipped diesel cars

Carbonaceous particulate matter (PM), comprising black carbon (BC), primary organic aerosol (POA) and secondary organic aerosol (SOA, from atmospheric aging of precursors), is a highly toxic vehicle exhaust component. Therefore, understanding vehicle pollution requires knowledge of both primary emissions, and how these emissions age in the atmosphere. We provide a systematic examination of carbonaceous PM emissions and parameterisation of SOA formation from modern diesel and gasoline cars at different temperatures (22, -7 °C) during controlled laboratory experiments. Carbonaceous PM emission and SOA formation is markedly higher from gasoline than diesel particle filter (DPF) and catalyst-equipped diesel cars, more so at -7 °C, contrasting with nitrogen oxides (NOX). Higher SOA formation from gasoline cars and primary emission reductions for diesels implies gasoline cars will increasingly dominate vehicular total carbonaceous PM, though older non-DPF-equipped diesels will continue to dominate the primary fraction for some time. Supported by state-of-the-art source apportionment of ambient fossil fuel derived PM, our results show that whether gasoline or diesel cars are more polluting depends on the pollutant in question, i.e. that diesel cars are not necessarily worse polluters than gasoline cars.

Ambient and laboratory observations of organic ammonium salts in PM1

Ambient measurements of PM₁aerosol chemical composition at Cabauw, the Netherlands, implicate higher ammonium concentrations than explained by the formation of inorganic ammonium salts. This additional particulate ammonium is called excess ammonium (e_NH4). Height profiles over the Cabauw Experimental Site for Atmospheric Research (CESAR) tower, of combined ground based and airborne aerosol mass spectrometric (AMS) measurements on a Zeppelin airship show higher concentrations ofe_NH4at higher altitudes compared to the ground. Through flights across the Netherlands, the Zeppelin based measurements furthermore substantiatee_NH4as a regional phenomenon in the planetary boundary layer. The excess ammonium correlates with mass spectral signatures of (di-)carboxylic acids, making a heterogeneous acid–base reaction the likely process of NH₃uptake. We show that this excess ammonium was neutralized by the organic fraction forming particulate organic ammonium salts. We discuss the significance of such organic ammonium salts for atmospheric aerosols and suggest that NH₃emission control will have benefits for particulate matter control beyond the reduction of inorganic ammonium salts.

Characterization of ice-nucleating bacteria using on-line electron impact ionization aerosol mass spectrometry

The mass spectral signatures of airborne bacteria were measured and analyzed in cloud simulation experiments at the AIDA (Aerosol Interaction and Dynamics in the Atmosphere) facility. Suspensions of cultured cells in pure water were sprayed into the aerosol and cloud chambers forming an aerosol which consisted of intact cells, cell fragments and residual particles from the agar medium in which the bacteria were cultured. The aerosol particles were analyzed with a high-resolution time-of-flight aerosol mass spectrometer equipped with a newly developed PM2.5 aerodynamic lens. Positive matrix factorization (PMF) using the multilinear engine (ME-2) source apportionment was applied to deconvolve the bacteria and agar mass spectral signatures. The bacteria mass fraction contributed between 75 and 95% depending on the aerosol generation, with the remaining mass attributed to agar. We present mass spectra of Pseudomonas syringae and Pseudomonas fluorescens bacteria typical for ice-nucleation active bacteria in the atmosphere to facilitate the distinction of airborne bacteria from other constituents in ambient aerosol, e.g. by PMF/ME-2 source apportionment analyses. Nitrogen-containing ions were the most salient feature of the bacteria mass spectra, and a combination of C4 H8 N(+) (m/z 70) and C5 H12 N(+) (m/z 86) may be used as marker ions.

Biomass burning contributions to urban aerosols in a coastal Mediterranean city

Mean annual biomass burning contributions to the bulk particulate matter (PM(X)) load were quantified in a southern-European urban environment (Barcelona, Spain) with special attention to typical Mediterranean winter and summer conditions. In spite of the complexity of the local air pollution cocktail and the expected low contribution of biomass burning emissions to PM levels in Southern Europe, the impact of these emissions was detected at an urban background site by means of tracers such as levoglucosan, K(+) and organic carbon (OC). The significant correlation between levoglucosan and OC (r(2)=0.77) and K(+) (r(2)=0.65), as well as a marked day/night variability of the levoglucosan levels and levoglucosan/OC ratios was indicative of the contribution from regional scale biomass burning emissions during night-time transported by land breezes. In addition, on specific days (21-22 March), the contribution from long-range transported biomass burning aerosols was detected. Quantification of the contribution of biomass burning aerosols to PM levels on an annual basis was possible by means of the Multilinear Engine (ME). Biomass burning emissions accounted for 3% of PM(10) and PM(2.5) (annual mean), while this percentage increased up to 5% of PM(1). During the winter period, regional-scale biomass burning emissions (agricultural waste burning) were estimated to contribute with 7±4% of PM(2.5) aerosols during night-time (period when emissions were clearly detected). Long-range transported biomass burning aerosols (possibly from forest fires and/or agricultural waste burning) accounted for 5±2% of PM(2.5) during specific episodes. Annually, biomass burning emissions accounted for 19%-21% of OC levels in PM(10), PM(2.5) and PM(1). The contribution of this source to K(+) ranged between 48% for PM(10) and 97% for PM(1) (annual mean). Results for K(+) from biomass burning evidenced that this tracer is mostly emitted in the fine fraction, and thus coarse K(+) could not be taken as an appropriate tracer of biomass burning.

Fine and coarse PM composition and sources in rural and urban sites in Switzerland: local or regional pollution?

The chemical composition and sources of ambient particulate matter (PM) in Switzerland were studied. PM(1) and PM(10) samples were collected in winter and summer at an urban background site in Zurich and a rural background site in Payerne. Concentrations of major and trace elements, NO(3)(-), SO(4)(2-), NH(4)(+), organic and elemental carbon were determined. A subsequent Positive Matrix Factorization (PMF) analysis was performed. PM(10) and PM(1) concentrations varied similarly at both sites, with average PM(10) concentrations 24-25 μg/m(3) and 13-14 μg/m(3) in winter and summer, respectively, and average PM(1) concentrations 12-17 μg/m(3) and 6-7 μg/m(3). The influence of local sources was found to be higher in winter. PM was dominated by nitrate and organic matter in winter, and by mineral matter and organic matter in summer. Trace element concentrations related to road traffic (Zn, Cu, Sb, Sn) were higher at Zurich. Concentrations of Tl and Cs, attributed to the influence of a glass industry, were higher at Payerne. The elements mainly present in the coarse fraction were those related to mineral matter and brake and tyre abrasion (Cu, Mn, Ti, Sb, Sr, Bi, Li, La, Nd), and those in the fine fraction were related to high temperature anthropogenic processes (Pb, As, Cd, Tl, Cs). Common PM(1) and PM(1-10) sources identified by PMF were: ammonium nitrate, present in winter, negligible in summer; ammonium sulfate+K(biomass burning)+road traffic; and road traffic itself, related to exhaust emissions in PM(1) and to road dust resuspension in PM(1-10). Size-fraction specific sources were: a PM(1) glass industry source characterized by Cs, Tl, Rb, Li and Na, only present in Payerne; a PM(1) background source characterized by V, Ni, sulfate and Fe; two PM(1-10) mineral-related sources, with higher contribution in summer; a PM(1-10) salt source; and a PM(1-10) organic source, with higher contribution in summer, attributed to bioaerosols.