Effect of industrialization on the differences in sources and composition of ambient PM2.5 in two Southern Ontario locations.

PM2.5 was sampled over a seven-year period (2013-2019) at two locations ∼50 km apart in Southern Ontario (concurrently for five years: 2015-2019). One is a heavily industrialized site (Hamilton), while the other was a rural site (Simcoe). To assess the impact of industrialization on the composition and sources of PM affecting air quality in these two locations, positive matrix factorization coupled with dispersion normalization (DN-PMF) was used to identify six and eight factors at Simcoe and Hamilton, respectively. The Simcoe factors in order of diminishing PM mass contribution were: particulate sulphate (pSO4), secondary organic aerosol (SOA), crustal matter, particulate nitrate (pNO3), biomass burning, and vehicular emissions. At Hamilton, the effects of industrialization were observed by the ∼36% higher average ambient PM2.5 concentration for the study period as well as the presence of factors unique to metallurgy, i.e., coking and steelmaking, compared to Simcoe. The coking and steelmaking factors contributed ∼15% to the PM mass at Hamilton. Seasonal variants of appropriate nonparametric trend tests with the associated slopes (Sen's) were used to assess statistically significant changes in the factor contributions to PM2.5 over time. Specifically at Hamilton, a significant decline in PM contributions was noted for coking (-0.03 µg/m³/yr or -4.1%/yr) while steelmaking showed no statistically significant decline over the study period. Other factors at Hamilton that showed statistically significant declines over the study period were: pSO4 (-0.27 µg/m³/yr or -12.6%/yr), biomass burning (-0.05 µg/m³/yr or -9.02%/yr), crustal matter (-0.03 µg/m³/yr or -5.28%/yr). These factors mainly accounted for the significant decline in PM2.5 over the study period (-0.35 µg/m³/yr or -4.24%/yr). This work shows the importance of long-term monitoring in assessing the unique contributions and temporal changes of industrialization on air quality in Ontario and similarly affected locations.

Evaluating the effectiveness of low-sulphur marine fuel regulations at improving urban ambient PM2.5 air quality: Source apportionment of PM2.5 at Canadian Atlantic and Pacific coast cities with implementation of the North American Emissions Control Area.

Ambient fine size fraction particulate matter (PM2.5) sources were resolved by positive matrix factorization at two Canadian cities on the Atlantic and Pacific coast over the 2010-2016 period, corresponding to implementation of the North American Emissions Control Area (NA ECA) low-sulphur marine fuel regulations. Source types contributing to local PM2.5 concentrations were: ECA regulation-related (residual oil, anthropogenic sulphate), urban transportation and residential (gasoline, diesel, secondary nitrate, biomass burning, road dust/soil), industry (refinery, Pb-enriched), and largely natural (biogenic sulphate, sea salt). Anthropogenic sources accounted for approximately 80 % of PM2.5 mass over 2010-2016. Anthropogenic and biogenic sources of PM2.5-sulphate were separated and apportioned. Anthropogenic PM2.5-sulphate was approximately 2-3 times higher than biogenic PM2.5-sulphate prior to implementation of the NA ECA low-S marine fuel regulations, decreasing to 1-2 times higher after regulation implementation. Non-marine anthropogenic sources (gasoline, road dust, local industry factors) were shown to together contribute 38 % - 45 % of urban PM2.5. At both coastal cities, the residual oil and anthropogenic sulphate factors clearly reflected the effects of the low-S fuel regulations at reducing primary and secondary sulphur-related PM2.5 emissions. Comparing a pre-regulation and post-regulation period, residual oil combustion PM2.5 decreased by 0.24-0.25 µg/m3 (94%-95 % decrease) in both cities and anthropogenic sulphate PM2.5 decreased by 0.78 µg/m3 in Halifax (47 % decrease) and 0.71 µg/m3 in Burnaby (58 % decrease). Regulation-related PM2.5 across these factors decreased by approximately 1 µg/m3 after regulation implementation, providing a quantified lower estimate of the beneficial influence of the regulations on urban ambient PM2.5 concentrations. Further reductions in coastal city ambient PM2.5 may best consider air quality strategies that include multiple sources, including marine shipping and non-marine anthropogenic source types given this analysis found that marine vessel emissions remain an important source of urban ambient PM2.5.

The variability of mass concentrations and source apportionment analysis of equivalent black carbon across urban Europe.

This study analyzed the variability of equivalent black carbon (eBC) mass concentrations and their sources in urban Europe to provide insights into the use of eBC as an advanced air quality (AQ) parameter for AQ standards. This study compiled eBC mass concentration datasets covering the period between 2006 and 2022 from 50 measurement stations, including 23 urban background (UB), 18 traffic (TR), 7 suburban (SUB), and 2 regional background (RB) sites. The results highlighted the need for the harmonization of eBC measurements to allow for direct comparisons between eBC mass concentrations measured across urban Europe. The eBC mass concentrations exhibited a decreasing trend as follows: TR > UB > SUB > RB. Furthermore, a clear decreasing trend in eBC concentrations was observed in the UB sites moving from Southern to Northern Europe. The eBC mass concentrations exhibited significant spatiotemporal heterogeneity, including marked differences in eBC mass concentration and variable contributions of pollution sources to bulk eBC between different cities. Seasonal patterns in eBC concentrations were also evident, with higher winter concentrations observed in a large proportion of cities, especially at UB and SUB sites. The contribution of eBC from fossil fuel combustion, mostly traffic (eBCT) was higher than that of residential and commercial sources (eBCRC) in all European sites studied. Nevertheless, eBCRC still had a substantial contribution to total eBC mass concentrations at a majority of the sites. eBC trend analysis revealed decreasing trends for eBCT over the last decade, while eBCRC remained relatively constant or even increased slightly in some cities.

Source apportionment of ambient PM2.5 in an industrialized city using dispersion-normalized, multi-time resolution factor analyses.

Ambient fine particulate matter (PM2.5) data were collected in the lower City of Hamilton, Ontario to apportion the sources of this pollutant over an 18-month period. Hamilton has complex topographical features that may result in worsened air pollution within the lower city, thus, dispersion-normalized, multi-time resolution factor analysis (DN-MT-FA) was used to identify and quantify contributions of factors in a manner that reduced the influence of local meteorology. These factors were secondary organic aerosols type 1 (SOA_1), particulate nitrate (pNO3), particulate sulphate (pSO4), primary traffic organic matter (PTOM), Steel/metal processing and vehicular road dust emissions (Steel & Mobile) and, secondary organic aerosols type 2 (SOA_2) with origins ranging from mainly regional to mainly local. Factors that were mainly local (PTOM, Steel & Mobile, SOA_2) contributed up to 17% of the average PM2.5 mass while mixed local/regional factors (pNO3, pSO4) made up 43% on average, indicating the potential for further reduction of harmful PM concentrations locally. Of particular interest from a health protection perspective, was the composition of PM2.5 on days when an exceedance of the 24-hr WHO air quality guideline for this pollutant was observed. In general, SOA_1 was found to drive summer exceedances while pNO3 dominated in the winter. During the summer period, SOA_1 was attributable to wildfires in the northern parts of Canada while local traffic sources in winter contributed to the high levels of pNO3. While local, industrial factors only had minor relative mass contributions during exceedances, they are high in highly oxidized organic species (SOA_2) and toxic metals (Steel & Mobile). Thus, they are likely to have more impacts on human health. The methods and results described in this work will be useful in understanding prevalent sources of particulate matter pollution in the ambient air in the presence of complex topography and meteorological effects.

Source apportionment of ambient PM10 collected at three sites in an urban-industrial area with multi-time resolution factor analyses.

Chemical speciation data for PM10, collected for annual trend analyses of health-relevant species, at three receptor sites in a highly industrialized area (IJmond) in the Netherlands were used in a multi-time resolution receptor model (ME-2) to identify the PM10 sources in this area. Despite the available data not being optimized for receptor modelling, five-factor solutions were obtained for all sites based on independent PMF analysis on PM10 data from the three sites (IJM, WAZ and BEV). Four factors were common to all three sites: nitrate-sulphate (average percentage contributions to PM10: IJM: 35.3 %, WAZ: 37.7 %, and BEV: 36.3 %); sea salt (20.2 %, 23.7 %, 15.2 %); industrial (8.1 %, 11.0 %, 18.1 %) and brake wear/traffic (31.4 %, 21.2 %, 20.6 %). At WAZ, a local/site-specific factor containing most of the PAH measurements was found (6.4 %) while a crustal matter factor was resolved at IJM (7.6 %) and BEV (9.8 %). Additionally, sludge-drying was a potential source of the marker species in the industrial factor at WAZ. Bootstrapping (BS) and factor displacement (DISP) were applied to the factor profiles in this work for error estimation. In general, the factor profiles at all three sites had very small intervals from both BS and DISP methods. To our knowledge, this is the first time DISP was applied in a complex model such as the multi-time resolution model. Most of the measured metal and PAH concentrations found in the IJmond area during the 2017-2019 period had local sources, with significant contributions from several processes related to the steel industry. This study shows that available detailed PM10 chemical speciation data, although primarily collected for annual trend analyses of health-relevant species, could also be used in receptor modelling by applying a multi-time framework. We propose general recommendations for the optimization of the measurement strategy for source apportionment of PM in areas with similar urban-industrial land use.

Improvements in air quality in the Netherlands during the corona lockdown based on observations and model simulations.

The lockdown measures in response to the SARS-CoV-2 virus outbreak in 2020 have resulted in reductions in emissions of air pollutants and corresponding ambient concentrations. In the Netherlands, the most stringent lockdown measures were in effect from March to May 2020. These measures coincided with a period of unusual meteorological conditions with wind from the north-east and clear-sky conditions, which complicates the quantification of the effect of the lockdown measures on the air quality. Here we quantify the lockdown effects on the concentrations of nitrogen oxides (NOx and NO2), particulate matter (PM10 and PM2.5) and ozone (O3) in the Netherlands, by analyzing observations and simulations with the atmospheric chemistry-transport model EMEP/MSC-W in its EMEP4NL configuration, after eliminating the effects of meteorological conditions during the lockdown. Based on statistical analyses with a Random Forest method, we estimate that the lockdown reduced observed NO2 concentrations by 30% (95% confidence interval 25-35%), 26% (21-32%), and 18% (10-25%) for traffic, urban, and rural background locations, respectively. Slightly smaller reductions of 8-28% are found with the EMEP4NL simulations for urban and regional background locations based on estimates in reductions in economic activity and emissions of traffic and industry in the Netherlands and other European countries. Reductions in observed PM2.5 concentrations of about 20% (10-25%) are found for all locations, which is somewhat larger than the estimates of 5-16% based on the model simulations. A comparison of the calculated NO2 traffic contributions with observations shows a substantial drop of about 35% in traffic contributions during the lockdown period, which is similar to the estimated reductions in mobility data as reported by Apple and Google. Since the largest health effects related to air pollution in the Netherlands are associated with exposure to PM10 and PM2.5, the lockdown measures in spring of 2020 have temporarily improved the air quality in the Netherlands. The concentrations of the most health relevant compounds have only been reduced by about 10-25%.

Stable isotope tagging of epitopes: a highly selective strategy for the identification of major histocompatibility complex class I-associated peptides induced upon viral infection.

Identification of peptides presented in major histocompatibility complex (MHC) class I molecules after viral infection is of strategic importance for vaccine development. Until recently, mass spectrometric identification of virus-induced peptides was based on comparative analysis of peptide pools isolated from uninfected and virus-infected cells. Here we report on a powerful strategy aiming at the rapid, unambiguous identification of naturally processed MHC class I-associated peptides, which are induced by viral infection. The methodology, stable isotope tagging of epitopes (SITE), is based on metabolic labeling of endogenously synthesized proteins during infection. This is accomplished by culturing virus-infected cells with stable isotope-labeled amino acids that are expected to be anchor residues (i.e. residues of the peptide that have amino acid side chains that bind into pockets lining the peptide-binding groove of the MHC class I molecule) for the human leukocyte antigen allele of interest. Subsequently these cells are mixed with an equal number of non-infected cells, which are cultured in normal medium. Finally peptides are acid-eluted from immunoprecipitated MHC molecules and subjected to two-dimensional nanoscale LC-MS analysis. Virus-induced peptides are identified through computer-assisted detection of characteristic, binomially distributed ratios of labeled and unlabeled molecules. Using this approach we identified novel measles virus and respiratory syncytial virus epitopes as well as infection-induced self-peptides in several cell types, showing that SITE is a unique and versatile method for unequivocal identification of disease-related MHC class I epitopes.

Survey of the occurrence of residues of methyl tertiary butyl ether (MTBE) in Dutch drinking water sources and drinking water.

An indicative survey has been carried out in The Netherlands investigating the presence of methyl tertiary butyl ether (MTBE) in drinking water and the corresponding sources. In total, 71 different sites used for the preparation of drinking water in The Netherlands were sampled in two successive seasons in 2001 involving the analysis of 156 samples. (ground water (n = 88), surface water (n = 17), bank filtrate water (n = 6) and drinking water (n = 45)). To combine high sample throughput with high selectivity and sensitivity, off-line purge and trap for sampling and gas chromatography mass spectrometry equipped with an automated thermal desorption sampler (TDS-GC-MS) was selected as the preferred analytical methodology. The developed procedure enabled the analysis of at least 40 samples per day and provided a limit of quantification of 2 ng l(-1). In the first period 63 samples of raw water were analyzed. Concentrations ranged between < 10 ng l(-1) and 420 ng l(-1) with a median concentration below 10 ng l(-1). The second period was focused at the re-sampling of positive locations (MTBE > 10 ng l(-1)) and a few additional drinking water utilities of which both the raw and drinking water of the utilities were analyzed. The median concentration of MTBE in the selected set of drinking water samples was 20 ng l(-1) (n = 45). At one location MTBE was found at a level of 2900 ng l(-1) caused by point source contamination of the ground water (11 900 ng l(-1)). Special attention has been paid to the quality of the results by analyzing all samples in duplicate and the analysis of control samples during each series of analyses.