Source apportionment of PM_2.5 in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed for the measurement of the size resolved chemical composition of single particles at a site in Cork Harbour, Ireland for three weeks in August 2008. The ATOFMS was co-located with a suite of semi-continuous instrumentation for the measurement of particle number, elemental carbon (EC), organic carbon (OC), sulfate and particulate matter smaller than 2.5 μm in diameter (PM_2.5). The temporality of the ambient ATOFMS particle classes was subsequently used in conjunction with the semi-continuous measurements to apportion PM_2.5 mass using positive matrix factorisation. The synergy of the single particle classification procedure and positive matrix factorisation allowed for the identification of six factors, corresponding to vehicular traffic, marine, long-range transport, various combustion, domestic solid fuel combustion and shipping traffic with estimated contributions to the measured PM_2.5 mass of 23%, 14%, 13%, 11%, 5% and 1.5% respectively. Shipping traffic was found to contribute 18% of the measured particle number (20–600 nm mobility diameter), and thus may have important implications for human health considering the size and composition of ship exhaust particles. The positive matrix factorisation procedure enabled a more refined interpretation of the single particle results by providing source contributions to PM_2.5 mass, while the single particle data enabled the identification of additional factors not possible with typical semi-continuous measurements, including local shipping traffic

Investigation of coastal sea-fog formation using the WIBS (wideband integrated bioaerosol sensor) technique

A wideband integrated bioaerosol sensor (WIBS-4) was deployed in Haulbowline Island, Cork Harbour, to detect fluorescence particles in real time during July and September 2011. A scanning mobility particle sizer (SMPS) was also installed providing sizing analysis of the particles over the 10–450&thinsp;nm range. During the campaign, multiple fog formation events occurred; they coincided with dramatic increases in the recorded fluorescent particle counts. The WIBS sizing and fluorescence intensity profiles indicated that the origin of the signals was potentially non-biological in nature (i.e. PBAPs, primary biological aerosol particles). Furthermore, the data did not support the presence of known fluorescing chemical particles like SOA (secondary organic aerosol). Complementary laboratory studies showed that the field results could potentially be explained by the adsorption of molecular iodine onto water droplets to form I2&thinsp;⋅&thinsp;(H2O)x complexes. The release of iodine into the coastal atmosphere from exposed kelp at low tides has been known for many years. This process leads to the production of small IxOy particles, which can act as cloud condensation nuclei (CCN). While the process of molecular iodine release from coastal kelp sources, subsequent particle formation, and the observations of sea mists and fogs have been studied in detail, this study provides a potential link between the three phenomena. Of mechanistic interest is the fact that molecular iodine included into (rather than on) water droplets does not appear to fluoresce as measured using WIBS instrumentation. The study indicates a previously unsuspected stabilizing transport mechanism for iodine in the marine environment. Hence the stabilization of the molecular form would allow its more extensive distribution throughout the troposphere before eventual photolysis.</p

Precision of the current methods to measure the alkenone proxy UK'37 and absolute alkenone abundance in sediments : results of an interlaboratory comparison study

Measurements of the UK'37 index and the absolute abundance of alkenones in marine sediments are increasingly used in paleoceanographic research as proxies of past sea surface temperature and haptophyte (mainly coccolith-bearing species) primary productivity, respectively. An important aspect of these studies is to be able to compare reliably data obtained by different laboratories from a wide variety of locations. Hence the intercomparability of data produced by the research community is essential. Here we report results from an anonymous interlaboratory comparison study involving 24 of the leading laboratories that carry out alkenone measurements worldwide. The majority of laboratories produce data that are intercomparable within the considered confidence limits. For the measurement of alkenone concentrations, however, there are systematic biases between laboratories, which might be related to the techniques employed to quantify the components. The maximum difference between any two laboratories for any two single measurements of UK'37 in sediments is estimated, with a probability of 95%, to be <2.18C. In addition, the overall within-laboratory precision for the UK'37 temperature estimates is estimated to be <1.68C (95% probability). Similarly, from the analyses of alkenone concentrations the interlaboratory reproducibility is estimated at 32%, and the repeatability is estimated at 24%. The former is compared to a theoretical estimate of reproducibility and found to be excessively high. Hence there is certainly scope and a demonstrable need to improve reproducibility and repeatability of UK'37 and especially alkenone quantification data across the community of scientists involved in alkenone research

A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises

The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management

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

Results of the first European Source Apportionment intercomparison for Receptor and Chemical Transport Models

In this study, the performance of the source apportionment model applications were evaluated by comparing the model results provided by 44 participants adopting a methodology based on performance indicators: z-scores and RMSEu, with pre-established acceptability criteria. Involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), provided a unique opportunity to cross-validate them. In addition, comparing the modelled source chemical profiles, with those measured directly at the source contributed to corroborate the chemical profile of the tested model results. The most used RM was EPA- PMF5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) and more difficulties are observed with SCE time series (72% of RMSEu accepted). Industry resulted the most problematic source for RMs due to the high variability among participants. Also the results obtained with CTMs were quite comparable to their ensemble reference using all models for the overall average (>92% of successful z-scores) while the comparability of the time series is more problematic (between 58% and 77% of the candidates’ RMSEu are accepted). In the CTM models a gap was observed between the sum of source contributions and the gravimetric PM10 mass likely due to PM underestimation in the base case. Interestingly, when only the tagged species CTM results were used in the reference, the differences between the two CTM approaches (brute force and tagged species) were evident. In this case the percentage of candidates passing the z-score and RMSEu tests were only 50% and 86%, respectively. CTMs showed good comparability with RMs for the overall dataset (83% of the z-scores accepted), more differences were observed when dealing with the time series of the single source categories. In this case the share of successful RMSEu was in the range 25% - 34%.JRC.C.5-Air and Climat

Precision of the current methods to measure the alkenone proxy U₃₇ K’ and absolute alkenone abundance in sediments: results of an interlaboratory comparison study

Measurements of the U₃₇ K’ index and the absolute abundance of alkenones in marine sediments are increasingly used in paleoceanographic research as proxies of past sea surface temperature and haptophyte (mainly coccolith-bearing species) primary productivity, respectively. An important aspect of these studies is to be able to compare reliably data obtained by different laboratories from a wide variety of locations. Hence the intercomparability of data produced by the research community is essential. Here we report results from an anonymous interlaboratory comparison study involving 24 of the leading laboratories that carry out alkenone measurements worldwide. The majority of laboratories produce data that are intercomparable within the considered confidence limits. For the measurement of alkenone concentrations, however, there are systematic biases between laboratories, which might be related to the techniques employed to quantify the components. The maximum difference between any two laboratories for any two single measurements of U₃₇ K’ in sediments is estimated, with a probability of 95%, to be <2.1°C. In addition, the overall within-laboratory precision for the U₃₇ K’ temperature estimates is estimated to be <1.6°C (95% probability). Similarly, from the analyses of alkenone concentrations the interlaboratory reproducibility is estimated at 32%, and the repeatability is estimated at 24%. The former is compared to a theoretical estimate of reproducibility and found to be excessively high. Hence there is certainly scope and a demonstrable need to improve reproducibility and repeatability of U₃₇ K’ and especially alkenone quantification data across the community of scientists involved in alkenone research