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Objective: To compare short-term effects of fine particles (PM2.5; aerodynamic diameter <2.5 µm) from different sources on the blood levels of markers of systemic inflammation., Methods: We followed a panel of 52 ischaemic heart disease patients from 15 November 2005 to 21 April 2006 with clinic visits in every second week in the city of Kotka, Finland, and determined nine inflammatory markers from blood samples. In addition, we monitored outdoor air pollution at a fixed site during the study period and conducted a source apportionment of PM2.5 using the Environmental Protection Agency's model EPA PMF 3.0. We then analysed associations between levels of source-specific PM2.5 and markers of systemic inflammation using linear mixed models., Results: We identified five source categories: regional and long-range transport (LRT), traffic, biomass combustion, sea salt, and pulp industry. We found most evidence for the relation of air pollution and inflammation in LRT, traffic and biomass combustion; the most relevant inflammation markers were C-reactive protein, interleukin-12 and myeloperoxidase. Sea salt was not positively associated with any of the inflammatory markers., Conclusions: Results suggest that PM2.5 from several sources, such as biomass combustion and traffic, are promoters of systemic inflammation, a risk factor for cardiovascular diseases., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Short-term exposure to ambient air pollution is associated with increased cardiovascular mortality and morbidity. This adverse health effect is suggested to be mediated by inflammatory processes. The purpose of this study was to determine if low levels of particulate matter, typical for smaller cities, are associated with acute systemic inflammation. Fifty-two elderly individuals with ischemic heart disease were followed for six months with biweekly clinical visits in the city of Kotka, Finland. Blood samples were collected for the determination of inflammatory markers interleukin (IL)-1β, IL-6, IL-8, IL-12, interferon (IFN)γ, C-reactive protein (CRP), fibrinogen, myeloperoxidase and white blood cell count. Particle number concentration and fine particle (particles with aerodynamic diameters <2.5 μm (PM(2.5))) as well as thoracic particle (particles with aerodynamic diameters <10 μm (PM(10))) mass concentration were measured daily at a fixed outdoor measurement site. Light-absorbance of PM(2.5) filter samples, an indicator of combustion derived particles, was measured with a smoke-stain reflectometer. In addition, personal exposure to PM(2.5) was measured with portable photometers. During the study period, wildfires in Eastern Europe led to a 12-day air pollution episode, which was excluded from the main analyses. Average ambient PM(2.5) concentration was 8.7 μg/m(3). Of the studied pollutants, PM(2.5) and absorbance were most strongly associated with increased levels of inflammatory markers; most notably with C-reactive protein and IL-12 within a few days of exposure. There was also some evidence of an effect of particulate air pollution on fibrinogen and myeloperoxidase. The concentration of IL-12 was considerably (227%) higher during than before the forest fire episode. These findings show that even low levels of particulate air pollution from urban sources are associated with acute systemic inflammation. Also particles from wildfires may exhibit pro-inflammatory effects., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Biomass burning has a strong influence on the atmospheric aerosol composition through particulate organic, inorganic, and soot emissions. When biomass burns, cellulose and hemicelluloses degrade, producing monosaccharide anhydrides (MAs) such as levoglucosan, mannosan, and galactosan. Therefore, these compounds have been commonly used as tracers for biomass burning. In this study, a fast water-based method was developed for the routine analysis of MAs, based on high-performance anion-exchange chromatography with electrospray ionization mass spectrometry detection. This method combines simple sample preparation, fast separation, and the advantages of the selective detection with MS. Analysis run was optimized to the maximum separation of levoglucosan, mannosan, and galactosan with 15-min analysis. The validation results indicated that the method showed good applicability for determination of MA isomer concentrations in ambient samples. The limit of detection was 100 pg for levoglucosan and 50 pg for mannosan and galactosan. Wide determination ranges enabled the analysis of samples of different concentration levels. The method showed good precision, both for standard solutions (3.9-5.9% RSD) and for fine particle samples (4.3-8.5% RSD). Co-elution of internal standard (carbon-13-labeled levoglucosan) and sugar alcohols with levoglucosan decreased the sensitivity of levoglucosan determination. The method was used to determine the MA concentrations in ambient fine particle samples from urban background (Helsinki) and rural background (Hyytiälä) in Finland. The average levoglucosan, mannosan, and galactosan concentrations were 77, 8.8, and 4.2 ng m(-3) in Helsinki (winter 2008-2009) and 17, 2.3, and 1.4 ng m(-3) in Hyytiälä (spring 2007), respectively. The interrelation of the three MA isomers was fairly constant in the ambient fine particle samples.

A series of smoke plumes was detected in Helsinki, Finland, during a one-month-lasting period in August 2006. The smoke plumes originated from wildfires close to Finland, and they were short-term and had a high particulate matter (PM) concentration. Physical and chemical properties of fine particles in those smokes were characterised by a wide range of real-time measurements that enabled the examination of individual plume events. Concurrently PM(1) filter samples were collected and analysed off-line. Satellite observations employing MODIS sensor on board of NASA EOS Terra satellite with the dispersion model SILAM and the Fire Assimilation System were used for evaluation of the emission fluxes from wildfires. The model predicted well the timing of the plumes but the predicted PM concentrations differed from the observed. The measurements showed that the major growth in PM concentration was caused by submicrometer particles consisting mainly of particulate organic matter (POM). POM had not totally oxidised during the transport based on the low WSOC-to-OC ratio. The fresh plumes were compared to another major smoke episode that was observed in Helsinki during April-May 2006. The duration and the source areas of the two episode periods differed. The episode in April-May was a period of nearly constantly upraised level of long-range transported PM and it was composed of aged particles when arriving in Helsinki. The two episodes had differences also in the chemical composition of PM. The mass concentrations of biomass burning tracers (levoglucosan, potassium, and oxalate) increased during both the episodes but different concentration levels of elemental carbon and potassium indicated that the episodes differed in the form of burning as well as in the burning material. In spring dry crop residue and hay from the previous season were burnt whereas in August smokes from smouldering and incomplete burning of fresh vegetation were detected., (Copyright 2010 Elsevier B.V. All rights reserved.)

Atmospheric aerosols play an important role in air pollution. Aerosol particle chemical composition is highly variable depending on the season, hour of the day, day of the week, meteorology, and location of the measurement site. Long measurement periods and highly time-resolved data are required in order to achieve a statistically relevant amount of data for assessing those variations and evaluating pollution episodes. In this study, we present continuous atmospheric PM1 (particulate matter < 1 µm) concentration and composition measurements at an urban street canyon site located in Helsinki, Finland. The study was performed for 4.5 years (2015–2019) and involved highly time-resolved measurements by taking advantage of a suite of online state-of-the-art instruments such as an aerosol chemical speciation monitor (ACSM), a multi-angle absorption photometer (MAAP), a differential mobility particle sizer (DMPS), and an Aethalometer (AE). PM1 consisted mostly of organics, with mean mass concentrations of 2.89 µgm-3 (53 % of PM1) followed by inorganic species (1.56 µgm-3 , 29 %) and equivalent black carbon (eBC, 0.97 µgm-3 , 18 %). A trend analysis revealed a decrease in BC from fossil fuel (BCFF), organics, and nitrate over the studied years. Clear seasonal and/or diurnal variations were found for the measured atmospheric PM1 constituents. Particle number and mass size distributions over different seasons revealed the possible influence of secondary organic aerosols (SOAs) during summer and the dominance of ultrafine traffic aerosols during winter. The seasonality of measured constituents also impacted the particle's coating and absorptive properties. The investigation of pollution episodes observed at the site showed that a large fraction of aerosol particle mass was comprised of inorganic species during long-range transport, while during local episodes eBC and organics prevailed together with elevated particle number concentration. Overall, the results increased knowledge of the variability of PM1 concentration and composition in a Nordic traffic site and its implications on urban air quality. Considering the effects of PM mitigation policies in northern Europe in the last decades, the results obtained in this study may be considered illustrative of probable future air quality challenges in countries currently adopting similar environmental regulations. [ABSTRACT FROM AUTHOR]

Low-cost particulate matter (PM) sensors have been under investigation as it has been hypothesized that the use of low-cost and easy-to-use sensors could allow cost-efficient extension of the currently sparse measurement coverage. While the majority of the existing literature highlights that low-cost sensors can indeed be a valuable addition to the list of commonly used measurement tools, it often reiterates that the risk of sensor misuse is still high and that the data obtained from the sensors are only representative of the specific site and its ambient conditions. This implies that there are underlying reasons for inaccuracies in sensor measurements that have yet to be characterized. The objective of this study is to investigate the particle-size selectivity of low-cost sensors. Evaluated sensors were Plantower PMS5003, Nova SDS011, Sensirion SPS30, Sharp GP2Y1010AU0F, Shinyei PPD42NS, and Omron B5W-LD0101. The investigation of size selectivity was carried out in the laboratory using a novel reference aerosol generation system capable of steadily producing monodisperse particles of different sizes (from ∼0.55 to 8.4 µ m) on-line. The results of the study show that none of the low-cost sensors adhered to the detection ranges declared by the manufacturers; moreover, cursory comparison to a mid-cost aerosol size spectrometer (Grimm 1.108, 2020) indicates that the sensors can only achieve independent responses for one or two size bins, whereas the spectrometer can sufficiently characterize particles with 15 different size bins. These observations provide insight into and evidence of the notion that particle-size selectivity has an essential role in the analysis of the sources of errors in sensors. [ABSTRACT FROM AUTHOR]

Lung deposited surface area (LDSA) is a relatively new metric that has been argued to be more accurate at predicting health effects from aerosol exposure. For typical atmospheric aerosol, the LDSA concentration depends mainly on the concentration of ultrafine particles (e.g. vehicular exhaust emissions and residential wood combustion) and therefore optical methods cannot be used to measure and quantify it. The objective of this study was to investigate and describe typical characteristics of LDSA under different urban environments and evaluate how a diffusion charging-based Pegasor AQ Urban sensor (Pegasor Ltd., Finland) can be used as an alternative to optical sensors when assessing local combustion emissions and respective LDSA concentrations. Long-term (12 months) sensor measurements of LDSA were carried out at three distinctly different measurement sites (four sensor nodes) in the Helsinki metropolitan area, Finland. The sites were affected mainly by vehicular exhaust emission (street canyon and urban background stations) and by residential wood combustion (two detached housing area stations). The results showed that the accuracy of the AQ Urban was good (R2 = 0.90) for the measurement of LDSA when compared to differential mobility particle sizer. The mean concentrations of LDSA were more than twice as high at the street canyon (mean 22 µm2 cm−3) site when compared to the urban background site (mean 9.4 µm2 cm−3). In the detached housing area, the mean concentrations were 12 µm2 cm−3, and wood combustion typically caused high LDSA peaks in the evenings. High correlations and similar diurnal cycles were observed for the LDSA and black carbon at street canyon and urban background stations. The utilization of a small-scale sensor network (four nodes) showed that the cross-station variability in hourly LDSA concentrations was significant in every site, even within the same detached housing area (distance between the two sites ∼670 m). [ABSTRACT FROM AUTHOR]

Low-cost particulate matter sensors (PM) have been under investigation due to their prospective nature regarding spatial extension of measurement coverage. While majority of the existing literature highlights that low-cost sensors can be useful in achieving this goal, it is often reminded that the risk of sensor misuse is still high, and that the data obtained from the sensors is only representative of the specific site and its ambient conditions. This implies that there are underlying reasons yet to be characterized which are causing inaccuracies in sensor measurements. The objective of this study was to investigate the particle size-selectivity of low-cost sensors. Evaluated sensors were Plantower PMS5003, Nova SDS011, Sensirion SPS30, Sharp GP2Y1010AU0F, Shinyei PPD42NS, and Omron B5W-ld0101. The investigation of size-selectivity was carried out in laboratory using a novel reference aerosol generation system capable of steadily producing monodisperse particles of different sizes on-line. The results of the study showed that none of the low-cost sensors adhered exactly to the detection ranges declared by the manufacturers, and moreover, cursory comparison to a mid-cost aerosol spectrometer (GRIMM 1.108) indicated that the sensors could only achieve independent responses for 1-2 size bins whereas the spectrometer could sufficiently characterize particles with 15 different size bins. These observations provide insight and evidence to the notion that particle size-selectivity may have an essential role in the error source analysis of sensors. [ABSTRACT FROM AUTHOR]

Particulate matter in the atmosphere is known to affect Earth's climate and to be harmful to human health. Accurately measuring particles from emission sources is important, as the results are used to inform policies and climate models. This study compares the results of two ELPI + devices, two PM10 cascade impactors and an eFilter, in combustion emission measurements. The comparison of the instruments in a realistic setting shows what types of challenges arise from measuring an emission aerosol with unknown particle morphologies and densities, different particle concentrations and high temperature. Our results show that the PM10 cascade impactors have very good intercorrelation when the collected mass is greater than 150 µg, but below that, the uncertainty of the results increases with decreasing mass. The raw signals of two ELPI + devices were nearly identical in most samples, as well as the particle number concentrations and size distributions calculated from raw signals; however, transforming the current distributions into mass distributions showed variation in the mass concentration of particles larger than 1 µm. The real-time time signal measured by eFilter was similar to the total current measured by ELPI+. The eFilter and PM10 cascade impactors showed similar particle mass concentrations, whereas ELPI + showed clearly higher ones in most cases. We concluded that the difference is at least partially due to volatile components being measured by ELPI+, but not by the mass collection measurements. Copyright © 2019 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Measurements of submicron particulate matter (PM) were performed at an urban background station, in Helsinki, Finland during wintertime to investigate the chemical characteristics and sources of PM1. The PM1was dominated by sulfate and organics. The source apportionment indicated that organic aerosol (OA) was a mixture from local sources (biomass burning (BBOA), traffic, coffee roaster (CROA)), secondary compounds formed in local wintertime conditions (nitrogen containing OA (NOA), semivolatile oxygenated OA (SV-OOA), and regional and long-range transported compounds (low volatile oxygenated OA, LV-OOA). BBOA was dominated by the fragments C2H4O2+and C3H4O2+(m/z 60.021 and 73.029) from levoglucosan, or other similar sugar components, comprising on average 32% of the BBOA mass concentration. The ratio between fragments C2H4O2+/C3H4O2+was significantly lower for CROA (=1.1) when compared to BBOA (=2.1), indicating that they consisted of different sugar compounds. In addition, a component containing substantial amount of nitrogen compounds (NOA) was observed in a sub-arctic region for the first time. The NOA contribution to OA ranged from 1% to 29% and elevated concentrations were observed when ambient relative humidity was high and the visibility low. Low solar radiation and temperature in wintertime were observed to influence the oxidation of compounds. A change in aerosol composition, with an increase of LV-OOA and decrease in BBOA, SV-OOA and NOA was noticed during the transition from wintertime to springtime. Size distribution measurements with high-time resolution enabled chemical characterization of externally mixed aerosol from different sources. Aged regional long-range transported aerosols were dominant at around 0.5 μm (vacuum aerodynamic diameter), whereas traffic and CROA emissions dominated at around 120 nm. Copyright 2014 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Abstract: In this study the characteristics, sources and water-solubility of submicron organic aerosol (OA) were investigated in Helsinki, Finland. An Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) was used to determine the submicron non-refractory aerosol components nitrate, sulfate, ammonium, chloride and organics between April 9 and May 8, 2009. The concentrations of the major water-soluble ions and water-soluble organic carbon (WSOC) were measured by a particle-into-liquid sampler (PILS) combined with a total organic carbon (TOC) analyzer and two ion chromatographs (IC) between April 25 and May 28, 2009. Parallel measurements of the submicron particulate matter (PM1), organic carbon (OC), black carbon (BC), meteorological quantities and trace gases were used to complement and validate the AMS and PILS-TOC-IC data. Sources or atmospheric processes affecting the organic aerosol were investigated by applying the Positive Matrix Factorization (PMF) analysis to the high-resolution mass spectra of the HR-ToF-AMS organics. All together seven factors were needed to describe the variation in the obtained dataset. The factors consisted of two different types of low-volatility oxygenated OA (LV-OOA), local and long-range-transported (LRT) biomass burning OA (BBOA), semi-volatile OA (SV-OOA), hydrocarbon-like OA (HOA), and one local source (coffee roastery). These factors were interpretable and could be connected to specific sources or chemical characteristics (biomass burning, traffic, biogenic emissions, oxidized long-range-transported aerosols, marine-processed aerosols and nearby industrial activity) of ambient aerosols. In order to study the organic fraction and PMF factors further, the elemental ratios OM:OC, O:C, H:C and N:C were calculated. The value of the OM:OC ratio varied between 1.4 and 2.1. A high OM:OC ratio (1.5–2.1) was observed for the highly-oxidized and water-soluble fraction, whereas this ratio was clearly lower (1.2–1.4) for local and fresh sources such as traffic. Two different factors representing local and long-range-transported biomass burning were observed. Local biomass burning emissions had a lower OM:OC ratio, indicating that this factor was less aged and had a different source area compared with the LRT BBOA. The water-solubilities of the OA factors were studied by investigating the correlation between these factors and WSOC and by reconstructing the concentration of water-soluble particulate organic matter (WSPOM) from the OA factors. The reconstructed WSPOM had a good correlation with the measured concentration of WSPOM. [Copyright &y& Elsevier]

The frequency, strength and sources of long-range transport (LRT) episodes of fine particles (PM2.5) were studied in southern Finland using air quality monitoring results, backward air mass trajectories, remote sensing of fire hot spots, transport and dispersion modelling of smoke and chemical analysis of particle samples (black carbon, monosaccharide anhydrides, oxalate, succinate, malonate, SO4 2−, NO3 −, K+ and NH4 +). At an urban background site in Helsinki, the daily WHO guideline value (24-h PM2.5 mean 25 μg m−3) was exceeded during 1–7 LRT episodes per year in 1999–2007. The 24-h mean maximum concentrations varied between 25 and 49 μg m−3 during the episodes, which was 3–6 times higher than the local mean concentration (8.7 μg m−3) in 1999–2007. The highest particle concentrations (max. 1-h mean 163 μg m−3) and the longest episodes (max. 9 days) were mainly caused by the emissions from open biomass burning, especially during springs and late-summers in 2002 and 2006. During the period 2001–2007, the satellite remote sensing of active fire hot spots and transport and dispersion modelling of smoke indicated that approximately half of the episodes were caused partly by the emissions from wildfires and/or agricultural waste burning in fields in Eastern Europe, especially in Russia, Belarus and Ukraine. Other episodes were mainly caused by the LRT of ordinary anthropogenic pollutants, e.g. from energy production, traffic, industry and wood combustion. During those ‘other episodes’, air masses also arrived from Eastern Europe, including Poland. The highest concentrations of biomass-burning tracers, such as monosaccharide anhydrides (levoglucosan + mannosan + galactosan) and K+, were observed during open biomass... [Copyright &y& Elsevier]

[Display omitted] • Characteristic LDSAal size distributions depending on urban environment and country. • Ultrafine particles major contributor on LDSAal in Finland and Central Europe. • LDSAal 2.5 per PM 2.5 multiple times higher in areas having low PM 2.5 level. • LDSAal 2.5 per PM 2.5 has similar non-linear behaviour as dose–response curve of PM 2.5. • New LDSAal 2.5 notation indicating deposition region and size range introduced. Recent studies indicate that monitoring only fine particulate matter (PM 2.5) may not be enough to understand and tackle the health risk caused by particulate pollution. Health effects per unit PM 2.5 seem to increase in countries with low PM 2.5 , but also near local pollution sources (e.g., traffic) within cities. The aim of this study is to understand the differences in the characteristics of lung-depositing particles in different geographical regions and urban environments. Particle lung deposited surface area (LDSAal) concentrations and size distributions, along with PM 2.5 , were compared with ambient measurement data from Finland, Germany, Czechia, Chile, and India, covering traffic sites, residential areas, airports, shipping, and industrial sites. In Finland (low PM 2.5), LDSAal size distributions depended significantly on the urban environment and were mainly attributable to ultrafine particles (<100 nm). In Central Europe (moderate PM 2.5), LDSAal was also dependent on the urban environment, but furthermore heavily influenced by the regional aerosol. In Chile and India (high PM 2.5), LDSAal was mostly contributed by the regional aerosol despite that the measurements were done at busy traffic sites. The results indicate that the characteristics of lung-depositing particles vary significantly both within cities and between geographical regions. In addition, ratio between LDSAal and PM 2.5 depended notably on the environment and the country, suggesting that LDSAal exposure per unit PM 2.5 may be multiple times higher in areas having low PM 2.5 compared to areas with continuously high PM 2.5. These findings may partly explain why PM 2.5 seems more toxic near local pollution sources and in areas with low PM 2.5. Furthermore, performance of a typical sensor based LDSAal measurement is discussed and a new LDSAal 2.5 notation indicating deposition region and particle size range is introduced. Overall, the study emphasizes the need for country-specific emission mitigation strategies, and the potential of LDSAal concentration as a health-relevant pollution metric. [ABSTRACT FROM AUTHOR]

Particle size distribution is a major factor in the health and climate effects of ambient aerosols, and it shows a large variation depending on the prevailing atmospheric emission sources. In this work, the particle number size distributions of ambient air were investigated at a suburban detached housing area in northern Helsinki, Finland, during a half-year period from winter to summer of 2020. The measurements were conducted with a scanning mobility particle sizer (SMPS) with a particle size range of 16–698 nm (mobility diameter), and the events with a dominant particle source were identified systematically from the data based on the time of the day and different particle physical and chemical properties. During the measurement period, four different types of events with a dominant contribution from either wood-burning (WB), traffic (TRA), secondary biogenic (BIO), or long-range transported (LRT) aerosol were observed. The particle size was the largest for the LRT events followed by BIO, WB, and TRA events with the geometric mean diameters of 72, 62, 57, and 41 nm, respectively. BIO and LRT produced the largest particle mode sizes followed by WB, and TRA with the modes of 69, 69, 46, and 25 nm, respectively. Each event type had also a noticeably different shape of the average number size distribution (NSD). In addition to the evaluation of NSDs representing different particle sources, also the effects of COVID-19 lockdown on specific aerosol properties were studied as during the measurement period the COVID-19 restrictions took place greatly reducing the traffic volumes in the Helsinki area in the spring of 2020. These restrictions had a significant contribution to reducing the concentrations of NO x and black carbon originating from fossil fuel combustion concentration, but insignificant effects on other studied variables such as number concentration and size distribution or particle mass concentrations (PM 1 , PM 2.5, or PM 10). • Events with a dominant particle source were identified systematically from ambient data. • Particle sources were traffic, biomass combustion, biogenic and long-range transport. • Number size distributions from different sources had different shapes. • Traffic produced significantly smaller particles compared to wood combustion. • Particle number size distribution from wood-burning showed large variability. [ABSTRACT FROM AUTHOR]

The formation of soot, organic, and inorganic aerosols has a profound effect on the environmental and technological feasibility of biomass combustion. In this work, the soot and aerosol processes are examined for a modern pulverized wood-burning 100 MW th district heating plant. Experimental data was collected from two locations inside the furnace (30% and 100% thermal loads), including measurements for fine particle (PM 1) number size distribution, number concentration, and chemical composition. The experiments were complemented with Computational Fluid Dynamics (CFD) simulations and Plug-Flow Reactor (PFR) modeling. The measurements and modeling are combined in a comprehensive analysis, providing fundamental understanding on the aerosol processes inside the furnace. The wood-powder combustion is efficient under both thermal loads, indicated by the low unburned carbon content in fly-ash, and the low CO, NO and soot emissions (<0.3 mg/Nm3). The fine particles consist mainly of K 2 SO 4 , and of lesser amounts of alkali salts (NaCl, KCl), and Ca and Mg compounds (oxides or sulfates). A large concentration of KOH/K 2 CO 3 vapor may exist in the flue gas and play a significant role in the heat exchanger fouling. The applied modeling tools are shown to provide accurate estimations for the composition and formation regions of fine particles inside the industrial biomass furnaces. [ABSTRACT FROM AUTHOR]

[Display omitted] • Freshly emitted PM1 from a natural gas engine originated mostly from unburned and oxygenated lubrication oil. • Three-way catalyst efficiently reduced gaseous and organic PM emissions from a natural gas engine. • PN emissions that include volatile species may highly exceed the regulated non-volatile PN above 23 nm. Since gas engines are considered a future solution to improve air quality and to mitigate climate impacts, there is an urgent need to understand their emissions. The aim for this study was to understand the phenomena affecting the formation of particulate emissions of a non-road natural gas engine. To achieve this, the engine's exhaust emissions were characterized under different operating conditions. The regulated pollutants (gaseous CO, HC, and NO x ; particulate matter (PM) and particle number (PN)) were determined experimentally and a detailed characterization of particulate pollutants over a wide particle size range (particles down to 1.2 nm) was conducted with state-of-the-art instrumentation considering both physical and chemical properties of the exhaust aerosol. The test engine was a prototype non-road spark-ignited natural gas engine, which was studied over the non-road steady test cycle (NRSC). The role of the three-way catalyst (TWC) was studied by sampling and characterizing the exhaust aerosol both with and without the TWC. The TWC was observed to efficiently remove the vast majority of the regulated gaseous (96% CO, 98% HC, 98% NO x) and particulate mass emissions (98%). In general, the measured particle number emission factors were highly dependent on the cut-off sizes of the condensation particle counters. Using CPCs with smaller cut-off sizes resulted in higher particle number emission factors. For black carbon (BC), the intermediate engine speed conditions (modes 5–7) led to lower BC emissions than the high speed conditions (modes 1–3). In contrast, highest BC emissions on a work basis were observed during idling. TWC did not influence BC levels. Without the TWC, PM was comprised mostly of organic compounds (70–100%). Downstream of the TWC, the majority of PM was, depending on the load, composed of organic compounds, sulfate, or black carbon. A statistical source apportionment based on mass spectra revealed that the PM 1 was mostly related to unburned and burned lubricating oil, indicating a minor role of fuel in PM formation. [ABSTRACT FROM AUTHOR]

Residential wood combustion, which is characterized by incomplete combustion, is a common source of particulate matter in suburban areas. This study investigated the usability of three different scattering-based particulate matter (PM) sensors and an absorption-based black carbon (BC) sensor in an environment impacted by wood combustion emissions. The measurement campaign, which lasted approximately 10 weeks, was conducted during wintertime in a suburban detached housing area in Helsinki, Finland. The results indicated that the scattering-based sensors were better suited for the measurement of PM1 (R2: 0.94–0.97) than for the PM2.5 (R2: 0.75–0.87). Analysis of the different proportions of size fractions indicated this was due to the particle size discrimination characteristics of sensors. Furthermore, the sensor responses were affected by the BC to PM1 ratio. This was attributed to the changing optical properties of the measured aerosol; however, the effect was not consistent across all the 3 p.m. sensors. The absorption-based BC sensor exhibited very good performance (R2: 0.97–0.98) at 470 and 880 nm wavelengths, and the source apportionment (BC contributed to wood burning and fossil fuel combustion) results were comparable to that of the reference instrument. When sensor data was applied in practice, a case study demonstrated that a simultaneous use of PM1 and BC sensors enabled more sophisticated data analysis; episodes originating from local wood burning and long-range transported aerosols were distinguishable from each other due to their different BC to PM1 ratios. The evaluated sensors were shown to bring added value to residential area air quality assessments. • Scattering-based sensor are better suited for the measurement of PM1 than PM2.5 • Responses of the scattering-based sensors are affected by eBC to PM1 ratio. • Scattering and absorption-based sensors measure RWC with adequate performance. • Use of different sensor types allows for indicative source apportionment. [ABSTRACT FROM AUTHOR]

Atmospheric trace elements (Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, V, Zn) in particulate matter have been measured since 1996 at Pallas, a subarctic site in Finland. The results indicate a very low level of pollution as the concentrations were among the lowest measured in Europe. The annual average concentration during the whole time series (1996–2018), from the lowest values to the highest, was Co < Cd < Cr < As < V < Ni < Cu < Mn < Pb < Zn < Al < Fe, ranging from 0.02 to 20 ng m−3. For the priority elements As, Cd, Ni and Pb, the annual average concentration was 0.10, 0.02, 0.21 and 0.65 ng m−3, respectively, in 2018. The concentrations were compared with the results from three other sites in Finland, and a clear south-to-north decreasing gradient was found for most elements except for Ni, which was found to be mostly associated with emissions from the Kola Peninsula together with the trace elements of Cu, As and Co, as confirmed by the source apportionment analysis using positive matrix factorization. Cd, Pb, V and Zn were attributed to long-range transported (LRT) pollutants originating from combustion while Al, Fe and Mn were related to the soil origin. Gaseous Hg was included in the source analysis and was found in a separate LRT and marine factors. Considering the full time series, a trend analysis showed statistically significant decreasing trends for As, Cd, Co, Cu, Ni, Pb and V up to 64% in the whole period. Since 2010, six elements (Cd, Co, Ni, Pb, V, Zn) have continued the positive development of declining trends (P < 0.05) with changes between 25% and 53% during the period. No statistically significant increasing trends were observed for the studied elements. Image 1 • Concentrations, trends and sources of heavy metals in particles were determined. • Study included Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn in particulate matter. • Five source factors were identified with positive matrix factorization. • Concentrations of heavy metals decreased up to 64% in 1996–2018. • No increasing temporal trends were observed for the studied heavy metals. [ABSTRACT FROM AUTHOR]