Various receptor methodologies have been developed in the last decades to investigate the geographical origins of atmospheric pollution, based either on wind data or on backtrajectory analyses. To ...date, only few software packages exist to make use of one or the other approach. We present here ZeFir, an Igor-based package specifically designed to achieve a comprehensive geographical origin analysis using a single statistical tool. ZeFir puts the emphasis on a user-friendly experience in order to facilitate and speed up working time. Key parameters can be easily controlled, and unique innovative features bring geographical origins work to another level.
Source apportionment using the bilinear model through a multilinear engine (ME-2) was successfully applied to non-refractory organic aerosol (OA) mass spectra collected during the winter of 2011 and ...2012 in Zurich, Switzerland using the aerosol chemical speciation monitor (ACSM). Five factors were identified: low-volatility oxygenated OA (LV-OOA), semivolatile oxygenated OA (SV-OOA), hydrocarbon-like OA (HOA), cooking OA (COA) and biomass burning OA (BBOA). A graphical user interface SoFi (Source Finder) was developed at PSI in order to facilitate the testing of different rotational techniques available within the ME-2 engine by providing a priori factor profiles for some or all of the expected factors. ME-2 was used to test the positive matrix factorization (PMF) model, the fully constrained chemical mass balance (CMB) model, and partially constrained models utilizing a values and pulling equations. Within the set of model solutions determined to be environmentally reasonable, BBOA and SV-OOA factor mass spectra and time series showed the greatest variability. This variability represents the uncertainty in the model solution and indicates that analysis of model rotations provides a useful approach for assessing the uncertainty of bilinear source apportionment models.
During winter 2013, extremely high concentrations (i.e., 4–20 times higher than the World Health Organization guideline) of PM2.5 (particulate matter with an aerodynamic diameter < 2.5 μm) mass ...concentrations (24 h samples) were found in four major cities in China including Xi'an, Beijing, Shanghai and Guangzhou. Statistical analysis of a combined data set from elemental carbon (EC), organic carbon (OC), 14C and biomass-burning marker measurements using Latin hypercube sampling allowed a quantitative source apportionment of carbonaceous aerosols. Based on 14C measurements of EC fractions (six samples each city), we found that fossil emissions from coal combustion and vehicle exhaust dominated EC with a mean contribution of 75 ± 8% across all sites. The remaining 25 ± 8% was exclusively attributed to biomass combustion, consistent with the measurements of biomass-burning markers such as anhydrosugars (levoglucosan and mannosan) and water-soluble potassium (K+). With a combination of the levoglucosan-to-mannosan and levoglucosan-to-K+ ratios, the major source of biomass burning in winter in China is suggested to be combustion of crop residues. The contribution of fossil sources to OC was highest in Beijing (58 ± 5%) and decreased from Shanghai (49 ± 2%) to Xi'an (38 ± 3%) and Guangzhou (35 ± 7%). Generally, a larger fraction of fossil OC was from secondary origins than primary sources for all sites. Non-fossil sources accounted on average for 55 ± 10 and 48 ± 9% of OC and total carbon (TC), respectively, which suggests that non-fossil emissions were very important contributors of urban carbonaceous aerosols in China. The primary biomass-burning emissions accounted for 40 ± 8, 48 ± 18, 53 ± 4 and 65 ± 26% of non-fossil OC for Xi'an, Beijing, Shanghai and Guangzhou, respectively. Other non-fossil sources excluding primary biomass burning were mainly attributed to formation of secondary organic carbon (SOC) from non-fossil precursors such as biomass-burning emissions. For each site, we also compared samples from moderately to heavily polluted days according to particulate matter mass. Despite a significant increase of the absolute mass concentrations of primary emissions from both fossil and non-fossil sources during the heavily polluted events, their relative contribution to TC was even decreased, whereas the portion of SOC was consistently increased at all sites. This observation indicates that SOC was an important fraction in the increment of carbonaceous aerosols during the haze episode in China.
Aerosol chemical speciation monitor (ACSM) measurements were performed in Zurich, Switzerland, for 13 months (February 2011 through February 2012). Many previous studies using this or related ...instruments have utilized the fraction of organic mass measured at m/z 44 (f44), which is typically dominated by the CO2+ ion and related to oxygenation, as an indicator of atmospheric aging. The current study demonstrates that during summer afternoons, when photochemical processes are most vigorous as indicated by high oxidant - OX (O3 + NO2), f44 for ambient secondary organic aerosol (SOA) is not higher but is rather similar or lower than on days with low OX. On the other hand, f43 (less oxidized fragment) tends to increase. These changes are discussed in the f44 / f43 space frequently used to interpret ACSM and aerosol mass spectrometer (AMS) data. This is likely due to the formation of semi-volatile oxygenated aerosol produced from biogenic precursor gases, whose emissions increase with ambient temperature. In addition, source apportionment analyses conducted on winter and summer data using positive matrix factorization (PMF) yield semi-volatile oxygenated organic aerosol (SV-OOA) factors that retain source-related chemical information. Winter SV-OOA is highly influenced by biomass burning, whereas summer SV-OOA is to a high degree produced from biogenic precursor gases. These sources contribute to substantial differences between the winter and summer f44 / f43 data, suggesting that PMF analysis of multi-season data employing only two OOA factors cannot capture the seasonal variability of OOA.
The aerosol chemical composition in air masses affected by wildfires from the Greek islands of Chios, Euboea and Andros, the Dalmatian Coast and Sicily, during late summer of 2012 was characterized ...at the remote background site of Finokalia, Crete. Air masses were transported several hundreds of kilometers, arriving at the measurement station after approximately half a day of transport, mostly during nighttime. The chemical composition of the particulate matter was studied by different high-temporal-resolution instruments, including an aerosol chemical speciation monitor (ACSM) and a seven-wavelength aethalometer. Despite the large distance from emission and long atmospheric processing, a clear biomass-burning organic aerosol (BBOA) profile containing characteristic markers is derived from BC (black carbon) measurements and positive matrix factorization (PMF) analysis of the ACSM organic mass spectra. The ratio of fresh to aged BBOA decreases with increasing atmospheric processing time and BBOA components appear to be converted to oxygenated organic aerosol (OOA). Given that the smoke was mainly transported overnight, it appears that the processing can take place in the dark. These results show that a significant fraction of the BBOA loses its characteristic AMS (aerosol mass spectrometry) signature and is transformed to OOA in less than a day. This implies that biomass burning can contribute almost half of the organic aerosol mass in the area during periods with significant fire influence.
Atmospheric submicron particulate matter (PM1) is one of the most significant pollution components in China. Despite its current popularity in the studies of aerosol chemistry, the characteristics, ...sources and evolution of atmospheric PM1 species are still poorly understood in China, particularly for the two harvest seasons, namely, the summer wheat harvest and autumn rice harvest. An Aerodyne Aerosol Chemical Speciation Monitor (ACSM) was deployed for online monitoring of PM1 components during summer and autumn harvest seasons in urban Nanjing, in the Yangtze River delta (YRD) region of China. PM1 components were shown to be dominated by organic aerosol (OA, 39 and 41%) and nitrate (23 and 20%) during the harvest seasons (the summer and autumn harvest). Positive matrix factorization (PMF) analysis of the ACSM OA mass spectra resolved four OA factors: hydrocarbon-like mixed with cooking-related OA (HOA + COA), fresh biomass-burning OA (BBOA), oxidized biomass-burning-influenced OA (OOA-BB), and highly oxidized OA (OOA); in particular the oxidized BBOA contributes ~80% of the total BBOA loadings. Both fresh and oxidized BBOA exhibited apparent diurnal cycles with peak concentration at night, when the high ambient relative humidity and low temperature facilitated the partitioning of semi-volatile organic species into the particle phase. The fresh BBOA concentrations for the harvests are estimated as BBOA = 15.1 × (m/z 60–0.26% × OA), where m/z (mass-to-charge ratio) 60 is a marker for levoglucosan-like species. The (BBOA + OOA-BB)/ΔCO, (ΔCO is the CO minus background CO), decreases as a function of f44 (fraction of m/z 44 in OA signal), which might indicate that BBOA was oxidized to less volatile OOA, e.g., more aged and low volatility OOA (LV-OOA) during the aging process. Analysis of air mass back trajectories indicates that the high BB pollutant concentrations are linked to the air masses from the western (summer harvest) and southern (autumn harvest) areas.
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.
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•Positive Matrix Factorization for groundwater and surface water characterization.•Positive Matrix Factorization is coupled with GIS approach.•Positive Matrix Factorization is validated through a comparison with isotopic data.•This leads to a detailed understanding of main chemical features and processes.
An Aerosol Chemical Speciation Monitor (ACSM, Aerodyne Research Inc.) was deployed at the Montseny (MSY; 41 degree 46'46" N, 02 degree 21'29" E, 720 m a.s.l.) regional background site in the western ...Mediterranean, Spain, from June 2012 to July 2013 to measure real-time inorganic (nitrate, sulfate, ammonium and chloride) and organic submicron aerosol concentrations. Co-located measurements, including real-time submicron particulate matter (PM1) and black carbon (BC) concentrations, and off-line PM1 chemical analysis were also carried out. This is one of the few studies that compare ACSM data with off-line PM1 measurements, avoiding the tail of the coarse mode included in the PM2.5 fraction. The ACSM + BC concentrations agreed with the PM1 measurements, and a strong correlation was found between the concentrations of ACSM species and the off-line measurements, although some discrepancies remain unexplained. Results point to a current underestimation of the relative ionization efficiency (RIE) established for organic aerosol (OA), which should be revised in the future. The OA was the major component of submicron aerosol (53% of PM1), with a higher contribution in summer (58% of PM1) than in winter (45% of PM1). Source apportionment of OA was carried out by applying positive matrix factorization (PMF), using the multilinear engine (ME-2) to the organic mass spectral data matrix. Three sources were identified in summer: hydrocarbon-like OA (HOA), low-volatile oxygenated OA (LV-OOA), and semi-volatile oxygenated OA (SV-OOA). The secondary OA (SOA; 4.8 mu g m-3, sum of LV-OOA and SV-OOA) accounted for 85% of the total OA, and its formation during daytime (mainly SV-OOA) was estimated to be 1.1 mu g m-3. In winter, HOA was also identified (12% of OA), a contribution from biomass burning OA (BBOA) was included and it was not possible to differentiate between two different SOA factors, but a single oxygenated OA (OOA) factor was resolved. The OOA contribution represented 60% of the total OA, with a degree of oxidation higher than both OOA summer factors. An intense wildfire episode was studied, obtaining a region-specific BBOA profile.
In the atmosphere nighttime removal of volatile organic compounds is initiated to a large extent by reaction with the nitrate radical (NO3) forming organic nitrates which partition between gas and ...particulate phase. Here we show based on particle phase measurements performed at a suburban site in the Netherlands that organic nitrates contribute substantially to particulate nitrate and organic mass. Comparisons with a chemistry transport model indicate that most of the measured particulate organic nitrates are formed by NO3 oxidation. Using aerosol composition data from three intensive observation periods at numerous measurement sites across Europe, we conclude that organic nitrates are a considerable fraction of fine particulate matter (PM1) at the continental scale. Organic nitrates represent 34% to 44% of measured submicron aerosol nitrate and are found at all urban and rural sites, implying a substantial potential of PM reduction by NOx emission control.
Key Points
Particulate organic nitrate is ubiquitous in Europe
The 34 to 44 percent of fine particulate nitrate is organic
Nighttime chemistry is a dominant source of particulate organic nitrates
Trace element measurements in PM10-2.5, PM2.5-1.0 and PM1.0-0.3 aerosol were performed with 2 h time resolution at kerbside, urban background and rural sites during the ClearfLo winter 2012 campaign ...in London. The environment-dependent variability of emissions was characterized using the Multilinear Engine implementation of the positive matrix factorization model, conducted on data sets comprising all three sites but segregated by size. Combining the sites enabled separation of sources with high temporal covariance but significant spatial variability. Separation of sizes improved source resolution by preventing sources occurring in only a single size fraction from having too small a contribution for the model to resolve. Anchor profiles were retrieved internally by analysing data subsets, and these profiles were used in the analyses of the complete data sets of all sites for enhanced source apportionment. A total of nine different factors were resolved (notable elements in brackets): in PM10-2.5, brake wear (Cu, Zr, Sb, Ba), other traffic-related (Fe), resuspended dust (Si, Ca), sea/road salt (Cl), aged sea salt (Na, Mg) and industrial (Cr, Ni); in PM2.5-1.0, brake wear, other traffic-related, resuspended dust, sea/road salt, aged sea salt and S-rich (S); and in PM1.0-0.3, traffic-related (Fe, Cu, Zr, Sb, Ba), resuspended dust, sea/road salt, aged sea salt, reacted Cl (Cl), S-rich and solid fuel (K, Pb). Human activities enhance the kerb-to-rural concentration gradients of coarse aged sea salt, typically considered to have a natural source, by 1.7-2.2. These site-dependent concentration differences reflect the effect of local resuspension processes in London. The anthropogenically influenced factors traffic (brake wear and other traffic-related processes), dust and sea/road salt provide further kerb-to-rural concentration enhancements by direct source emissions by a factor of 3.5-12.7. The traffic and dust factors are mainly emitted in PM10-2.5 and show strong diurnal variations with concentrations up to 4 times higher during rush hour than during night-time. Regionally influenced S-rich and solid fuel factors, occurring primarily in PM1.0-0.3, have negligible resuspension influences, and concentrations are similar throughout the day and across the regions.
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