A new method to retrieve the real part of the equivalent refractive index of atmospheric aerosols

This document is the Accepted Manuscript version of the following article: S. Vratolis, et al, ‘A new method to retrieve the real part of the equivalent refractive index of atmospheric aerosols’, Journal of Aerosol Science, Vol. 117: 54-62, March 2018. Under embargo until 29 December 2019. The final, published version is available online at DOI: https://doi.org/10.1016/j.jaerosci.2017.12.013.In the context of the international experimental campaign Hygroscopic Aerosols to Cloud Droplets (HygrA-CD, 15 May to 22 June 2014), dry aerosol size distributions were measured at Demokritos station (DEM) using a Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 550 nm (electrical mobility diameter), and an Optical Particle Counter (OPC model Grimm 107 operating at the laser wavelength of 660 nm) to acquire the particle size distribution in the size range of 250 nm to 2.5 μm optical diameter. This work describes a method that was developed to align size distributions in the overlapping range of the SMPS and the OPC, thus allowing us to retrieve the real part of the aerosol equivalent refractive index (ERI). The objective is to show that size distribution data acquired at in situ measurement stations can provide an insight to the physical and chemical properties of aerosol particles, leading to better understanding of aerosol impact on human health and earth radiative balance. The resulting ERI could be used in radiative transfer models to assess aerosol forcing direct effect, as well as an index of aerosol chemical composition. To validate the method, a series of calibration experiments were performed using compounds with known refractive index (RI). This led to a corrected version of the ERI values, (ERICOR). The ERICOR values were subsequently compared to model estimates of RI values, based on measured PM2.5 chemical composition, and to aerosol RI retrieved values by inverted lidar measurements on selected days.Peer reviewe

A new method for the quantification of ambient particulate-matter emission fluxes

An inversion method has been developed in order to quantify the emission fluxes of certain aerosol pollution sources across a wide region in the Northern Hemisphere, mainly in Europe and western Asia. The data employed are the aerosol contribution factors deducted by positive matrix factorization (PMF) on a PM2.5 chemical composition dataset from 16 European and Asian cities for the period 2014 to 2016. The spatial resolution of the method corresponds to the geographic grid cell size of the Lagrangian particle dispersion model (Flexible Particle Dispersion Model, FLEXPART, 1∘ × 1∘) which was utilized for the air mass backward simulations. The area covered is also related to the location of the 16 cities under study. Species with an aerodynamic geometric mean diameter of 400 nm and 3.1 µm and a geometric standard deviation of 1.6 and 2.25, respectively, were used to model the secondary sulfate and dust aerosol transport. Potential source contribution function (PSCF) analysis and generalized Tikhonov regularization were applied so as to acquire potential source areas and quantify their emission fluxes. A significant source area for secondary sulfate on the east of the Caspian Sea is indicated, when data from all stations are used. The maximum emission flux in that area is as high as 10 × 10−12 kg m−2 s−1. When Vilnius, Dushanbe, and Kurchatov data were excluded, the areas with the highest emission fluxes were the western and central Balkans and southern Poland. The results display many similarities to the SO2 emission maps provided by the OMI-HTAP (Ozone Monitoring Instrument-Hemispheric Transport Air Pollution) and ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) databases. For dust aerosol, measurements from Athens, Belgrade, Debrecen, Lisbon, Tirana, and Zagreb are utilized. The west Sahara region is indicated as the most important source area, and its contribution is quantified, with a maximum of 17.6 × 10−12 kg m−2 s−1. When we apply the emission fluxes from every geographic grid cell (1∘ × 1∘) for secondary sulfate aerosol deducted with the new method to air masses originating from Vilnius, a useful approximation to the measured values is achieved.</p

Comparison and complementary use of in situ and remote sensing aerosol measurements in the Athens Metropolitan Area

© 2020 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/.In the summer of 2014 in situ and remote sensing instruments were deployed in Athens, in order to study the concentration, physical properties, and chemical composition of aerosols. In this manuscript we aim to combine the measurements of collocated in situ and remote sensing instruments by comparison and complementary use, in order to increase the accuracy of predictions concerning climate change and human health. We also develop a new method in order to select days when a direct comparison on in situ and remote sensing instruments is possible. On selected days that displayed significant turbulence up to approximately 1000 m above ground level (agl), we acquired the aerosol extinction or scattering coefficient by in situ instruments using three approaches. In the first approach the aerosol extinction coefficient was acquired by adding a Nephelometer scattering coefficient in ambient conditions and an Aethalometer absorption coefficient. The correlation between the in situ and remote sensing instruments was good (coefficient of determination R2 equal to 0.69). In the second approach we acquired the aerosol refractive index by fitting dry Nephelometer and Aethalometer measurements with Mie algorithm calculations of the scattering and absorption coefficients for the size distribution up to a maximum diameter of 1000 nm obtained by in situ instruments. The correlation in this case was relatively good (R2 equal to 0.56). Our next step was to compare the extinction coefficient acquired by remote sensing instruments to the scattering coefficient calculated by Mie algorithm using the size distribution up to a maximum diameter of 1000 nm and the equivalent refractive index (ERICOR), which is acquired by the comparison of the size distributions obtained by a Scanning Mobility Particle Sizer (SMPS) and an Optical Particle Counter (OPC). The agreement between the in situ and remote sensing instruments in this case was not satisfactory (R2 equal to 0.35). The last comparison for the selected days was between the aerosol extinction Ångström exponent acquired by in situ and remote sensing instruments. The correlation was not satisfactory (R2 equal to 0.4), probably due to differences in the number size distributions present in the air volumes measured by in situ and remote sensing instruments. We also present a day that a Saharan dust event occurred in Athens in order to demonstrate the information we obtain through the synergy of in situ and remote sensing instruments on how regional aerosol is added to local aerosol, especially during pollution events due to long range transport.Peer reviewe

AIRUSE-LIFE+:A harmonized PM speciation and source apportionment in five southern European cities

The AIRUSE-LIFE+ project aims at characterizing similarities and heterogeneities in particulate matter (PM) sources and contributions in urban areas from southern Europe. Once the main PMx sources are identified, AIRUSE aims at developing and testing the efficiency of specific and non-specific measures to improve urban air quality. This article reports the results of the source apportionment of PM₁₀ and PM_2.5 conducted at three urban background sites (Barcelona, Florence and Milan, BCN-UB, FI-UB and MLN-UB), one suburban background site (Athens, ATH-SUB) and one traffic site (Porto, POR-TR). After collecting 1047 PM₁₀ and 1116 PM_2.5 24 h samples during 12 months (from January 2013 on) simultaneously at the five cities, these were analysed for the contents of OC, EC, anions, cations, major and trace elements and levoglucosan. The USEPA PMF5 receptor model was applied to these data sets in a harmonized way for each city. <br><br> The sum of vehicle exhaust (VEX) and non-exhaust (NEX) contributes between 3.9 and 10.8 µg m⁻³ (16–32 %) to PM₁₀ and 2.3 and 9.4 µg m⁻³ (15–36 %) to PM_2.5, although a fraction of secondary nitrate is also traffic-related but could not be estimated. Important contributions arise from secondary particles (nitrate, sulfate and organics) in PM_2.5 (37–82 %) but also in PM₁₀ (40–71 %), mostly at background sites, revealing the importance of abating gaseous precursors in designing air quality plans. <br><br> Biomass burning (BB) contributions vary widely, from 14–24 % of PM₁₀ in POR-TR, MLN-UB and FI-UB, 7 % in ATH-SUB, to  &lt;  2 % in BCN-UB. In PM_2.5, BB is the second most important source in MLN-UB (21 %) and in POR-TR (18 %), the third one in FI-UB (21 %) and ATH-SUB (11 %), but is again negligible (&lt; 2 %) in BCN-UB. This large variability among cities is mostly due to the degree of penetration of biomass for residential heating. In Barcelona natural gas is very well supplied across the city and is used as fuel in 96 % of homes, while in other cities, PM levels increase on an annual basis by 1–9 µg m⁻³ due to biomass burning influence. Other significant sources are the following. <br><br> &ndash; Local dust, 7–12 % of PM₁₀ at SUB and UB sites and 19 % at the TR site, revealing a contribution from road dust resuspension. In PM_2.5 percentages decrease to 2–7 % at SUB-UB sites and 15 % at the TR site. <br><br> &ndash; Industry, mainly metallurgy, contributing 4–11 % of PM₁₀ (5–12 % in PM_2.5), but only at BCN-UB, POR-TR and MLN-UB. No clear impact of industrial emissions was found in FI-UB and ATH-SUB. <br><br> &ndash; Natural contributions from sea salt (13 % of PM₁₀ in POR-TR, but only 2–7 % in the other cities) and Saharan dust (14 % in ATH-SUB, but less than 4 % in the other cities). <br><br> During high pollution days, the largest sources (i.e. excluding secondary aerosol factors) of PM₁₀ and PM_2.5 are VEX + NEX in BCN-UB (27–22 %) and POR-TR (31–33 %), BB in FI-UB (30–33 %) and MLN-UB (35–26 %) and Saharan dust in ATH-SUB (52–45 %). During those days, there are also quite important industrial contributions in BCN-UB (17–18 %) and local dust in POR-TR (28–20 %)

Evaluation of receptor and chemical transport models for PM10 source apportionment

In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs varied depending on the source: traffic/exhaust and industry were the source categories with the best results in the RMSEu tests while the most critical ones were soil dust and road dust. The differences between RMs and CTMs source reconstructions confirmed the importance of cross validating the results of these two families of models

Source apportionment by PMF on elemental concentrations obtained by PIXE analysis of PM10 samples collected at the vicinity of lignite power plants and mines in Megalopolis, Greece

Particulate matter (PM) is an important constituent of atmospheric pollution especially in areas under the influence of industrial emissions. Megalopolis is a small city of 10,000 inhabitants located in central Peloponnese in close proximity to three coal opencast mines and two lignite fired power plants. 50 PM10 samples were collected in Megalopolis during the years 2009–11 for elemental and multivariate analysis. For the elemental analysis PIXE was used as one of the most effective techniques in APM analytical characterization. Altogether, the concentrations of 22 elements (Z = 11–33), whereas Black Carbon was also determined for each sample using a reflectometer. Factorization software was used (EPA PMF 3.0) for source apportionment analysis. The analysis revealed that major emission sources were soil dust 33% (7.94 ± 0.27 μg/m3), biomass burning 19% (4.43 ± 0.27 μg/m3), road dust 15% (3.63 ± 0.37 μg/m3), power plant emissions 13% (3.01 ± 0.44 μg/m3), traffic 12% (2.82 ± 0.37 μg/m3), and sea spray 8% (1.99 ± 0.41 μg/m3). Wind trajectories have suggested that metals associated with emission from the power plants came mainly from west and were connected with the locations of the lignite mines located in this area. Soil resuspension, road dust and power plant emissions increased during the warm season of the year, while traffic/secondary, sea spray and biomass burning become dominant during the cold season

A novel probabilistic source apportionment approach: Bayesian auto-correlated matrix factorization

The concentrations of atmospheric particulate matter and many of its constituents are temporally auto-correlated. However, this information has not been utilized in source apportionment methods. Here, we present a Bayesian matrix factorization model (BAMF) that considers the temporal auto-correlation of the components (sources) and provides a direct error estimation. The performance of BAMF is compared with positive matrix factorization (PMF) using synthetic Time-of-Flight Aerosol Chemical Speciation Monitor data, representing different urban environments from typical European towns to megacities. We find that BAMF resolves sources with overall higher factorization performance (temporal behavior and bias) than PMF on all datasets with temporally auto-correlated components. Highly correlated components continue to be challenging and ancillary information is still required to reach good factorizations. However, we demonstrate that adding even partial prior information about the chemical composition of the components to BAMF improves the factorization. Overall, BAMF-type models are promising tools for source apportionment and merit further research.</p

Source identification of the elemental fraction of particulate matter using size segregated, highly time-resolved data and an optimized source apportionment approach

Source emissions with high covariance degrade the performance of multivariate models, and often highly-time resolved data is needed to accurately extract the contribution of different emissions. Here, we use highly time-resolved size segregated elemental composition data to apportion the sources of the elemental fraction of PM in Zürich (May 2019–May 2020). For data collection, we have used an ambient metals monitor, Xact 625i, equipped with a sampling inlet alternating between PM2.5 and PM10. By implementing interpolation and a newly proposed uncertainty estimation methodology, it was possible to obtain and use in PMF a combined dataset of PM2.5 and PMcoarse (PM10-2.5) having data from only one instrument. The combination of the inlet switching system, the instrument's high time resolution, and the use of advanced source apportionment approaches yielded improved source apportionment results in terms of the number of identified sources, as the model, additionally to the diurnal and seasonal variation of the dataset, also utilizes the variation from the size segregated data. Thirteen sources of elements were identified, i.e., sea salt (5.4%), biomass burning (7.2%), construction (4.3%), industrial (3.3%), light-duty vehicles (5.4%), Pb (0.7%), Zn (0.7%), dust (22.1%), transported dust (9.5%), sulfates (15.4%), heavy-duty vehicles (17%), railway (6.6%) and fireworks (2.4%). The Covid-19 lockdown effect in PM sources in the area was also quantified. High-intensity events disproportionally affect the PMF solution, and in many cases, they are getting discarded before analysis, removing thus valuable information from the dataset. In this study, a three-step source apportionment approach was used to get a well-resolved unmixed solution when firework data points were included in the analysis. This approach can also be used for other sources and/or events with very high contributions that distort source apportionment analysis. Optimized source apportionment techniques are necessary for effective air pollution monitoring

Comparison and complementary use of in situ and remote sensing aerosol measurements in the Athens Metropolitan Area

In the summer of 2014 in situ and remote sensing instruments were deployed in Athens, in order to study the concentration, physical properties, and chemical composition of aerosols. In this manuscript we aim to combine the measurements of collocated in situ and remote sensing instruments by comparison and complementary use, in order to increase the accuracy of predictions concerning climate change and human health. We also develop a new method in order to select days when a direct comparison on in situ and remote sensing instruments is possible. On selected days that displayed significant turbulence up to approximately 1000 m above ground level (agl), we acquired the aerosol extinction or scattering coefficient by in situ instruments using three approaches. In the first approach the aerosol extinction coefficient was acquired by adding a Nephelometer scattering coefficient in ambient conditions and an Aethalometer absorption coefficient. The correlation between the in situ and remote sensing instruments was good (coefficient of determination R2 equal to 0.69). In the second approach we acquired the aerosol refractive index by fitting dry Nephelometer and Aethalometer measurements with Mie algorithm calculations of the scattering and absorption coefficients for the size distribution up to a maximum diameter of 1000 nm obtained by in situ instruments. The correlation in this case was relatively good (R2 equal to 0.56). Our next step was to compare the extinction coefficient acquired by remote sensing instruments to the scattering coefficient calculated by Mie algorithm using the size distribution up to a maximum diameter of 1000 nm and the equivalent refractive index (ERICOR), which is acquired by the comparison of the size distributions obtained by a Scanning Mobility Particle Sizer (SMPS) and an Optical Particle Counter (OPC). The agreement between the in situ and remote sensing instruments in this case was not satisfactory (R2 equal to 0.35). The last comparison for the selected days was between the aerosol extinction Ångström exponent acquired by in situ and remote sensing instruments. The correlation was not satisfactory (R2 equal to 0.4), probably due to differences in the number size distributions present in the air volumes measured by in situ and remote sensing instruments. We also present a day that a Saharan dust event occurred in Athens in order to demonstrate the information we obtain through the synergy of in situ and remote sensing instruments on how regional aerosol is added to local aerosol, especially during pollution events due to long range transport. © 2020 Elsevier Lt