Poor air quality influences the quality of life in the urban environment. The regulatory observation stations provide the backbone for the city administration to monitor urban air quality. Recently a suite of cost-effective air quality sensors has emerged to provide novel insights into the spatio-temporal variability of aerosol particles and trace gases. Particularly in low concentrations these sensors might suffer from issues related e.g., to high detection limits, concentration drifts and interdependency between the observed trace gases and environmental parameters. In this study we characterize the optical particle detector used in AQT530 (Vaisala Ltd.) air quality sensor in the laboratory. We perform a measurement campaign with a network of AQT530 sensors in Helsinki, Finland in 2020-2021 and present a long-term performance evaluation of five sensors for particulate (PM10, PM2.5) and gaseous (NO2, NO, CO, O-3) components during a half-year co-location study with reference instruments at an urban traffic site. Furthermore, short-term (3-5 weeks) co-location tests were performed for 25 sensors to provide sensor-specific correction equations for the fine-tuning of selected pollutants in the sensor network. We showcase the added value of the verified network of 25 sensor units to address the spatial variability of trace gases and aerosol mass concentrations in an urban environment. The analysis assesses road and harbor traffic monitoring, local construction dust monitoring, aerosol concentrations from fireworks, impact of sub-urban small scale wood combustion and detection of long-range transport episodes on a city scale. Our analysis illustrates that the calibrated network of Vaisala AQT530 air quality sensors provide new insights into the spatio-temporal variability of air pollution within the city. This information is beneficial to, for example, optimization of road dust and construction dust emission control as well as provides data to tackle air quality problems arising from traffic exhaust and localized wood combustion emissions in the residential areas.

Interest towards indoor air quality has increased for several decades from human health perspective. In order to evaluate the quality of indoor air in terms of volatile organic compound (VOC) levels, robust analytical procedures and techniques must be used for indoor air VOC measurements. Since indoor building materials are the greatest source of indoor VOC emissions, same kind of procedures must be used for analysis of emission rates from building materials and their surfaces. Theory part of this thesis reviews background of VOCs and human health, legislation and guideline values, common building materials with emissions and used sampling techniques/approaches for indoor air sampling and surface material emission rate sampling & analysis. Discussed sampling techniques include, for example, material emission test chambers, field and laboratory test emission cells, solid phase microextraction (SPME) fibre applications and Radiello passive samplers. Also new innovative approaches are discussed. Used common analysis instruments are Gas Chromatography (GC) with Mass Spectrometer (MS) or Flame Ionization Detector (FID) for VOCs and High-Performance Liquid Chromatography-Ultraviolet/Visible light detector (HPLC-UV/VIS) for carbonyl VOCs (e.g. formaldehyde) after suitable derivatization. Analytical procedures remain highly ISO 16000 standard series orientated even in recent studies. In addition, potential usage of new modern miniaturized sample collection devices SPME Arrow and In-tube extraction (ITEX) used in experimental part of this thesis are discussed as an addition to indoor air and VOC emission studies. The aim of the experimental part of this thesis was to develop calibrations for selected organic nitrogen compounds with SPME Arrow and ITEX sampling techniques and test the calibration with indoor and outdoor samples. A calibration was successfully carried out with SPME Arrow (MCM-41 sorbent), ITEX (MCM-TP sorbent) and ITEX (Polyacrylonitrile (PAN) 10 % sorbent) with permeation system combined with GC-MS for the following selected organic nitrogen compounds: triethylamine, pyridine, isobutyl amine, allylamine, trimethylamine, ethylenediamine, dipropyl amine, hexylamine, 1,3-diaminopropane, 1-methyl-imidazole, N, N-dimethylformamide, 1,2-diaminocyclohexane, 1-nitropropane and formamide. The overall quality of the calibration curves was evaluated, and the calibrations were compared in terms of linear range, relative standard deviation (RSD) % for accepted calibration levels and obtained Limits of Detection (LOD) values. Also, ways to improve the calibrations were discussed. The calibration curves were tested with real indoor and outdoor samples and quantitative, as well as semi-quantitative, results were obtained.

COVID-19 has highlighted the need for indoor risk-reduction strategies. Our aim is to provide information about the virus dispersion and attempts to reduce the infection risk. Indoor transmission was studied simulating a dining situation in a restaurant. Aerosolized Phi6 viruses were detected with several methods. The aerosol dispersion was modeled by using the Large-Eddy Simulation (LES) technique. Three risk-reduction strategies were studied: (1) augmenting ventilation with air purifiers, (2) spatial partitioning with dividers, and (3) combination of 1 and 2. In all simulations infectious viruses were detected throughout the space proving the existence long-distance aerosol transmission indoors. Experimental cumulative virus numbers and LES dispersion results were qualitatively similar. The LES results were further utilized to derive the evolution of infection probability. Air purifiers augmenting the effective ventilation rate by 65% reduced the spatially averaged infection probability by 30%–32%. This relative reduction manifests with approximately 15 min lag as aerosol dispersion only gradually reaches the purifier units. Both viral findings and LES results confirm that spatial partitioning has a negligible effect on the mean infection-probability indoors, but may affect the local levels adversely. Exploitation of high-resolution LES jointly with microbiological measurements enables an informative interpretation of the experimental results and facilitates a more complete risk assessment.

Numerical models are needed for evaluating aerosol processes in the atmosphere in state-of-the-art chemical transport models, urban-scale dispersion models, and climatic models. This article describes a publicly available aerosol dynamics model, MAFOR (Multicomponent Aerosol FORmation model; version 2.0); we address the main structure of the model, including the types of operation and the treatments of the aerosol processes. The model simultaneously solves the time evolution of both the particle number and the mass concentrations of aerosol components in each size section. In this way, the model can also allow for changes in the average density of particles. An evaluation of the model is also presented against a high-resolution observational dataset in a street canyon located in the centre of Helsinki (Finland) during afternoon traffic rush hour on 13 December 2010. The experimental data included measurements at different locations in the street canyon of ultrafine particles, black carbon, and fine particulate mass PM1. This evaluation has also included an intercomparison with the corresponding predictions of two other prominent aerosol dynamics models, AEROFOR and SALSA. All three models simulated the decrease in the measured total particle number concentrations fairly well with increasing distance from the vehicular emission source. The MAFOR model reproduced the evolution of the observed particle number size distributions more accurately than the other two models. The MAFOR model also predicted the variation of the concentration of PM1 better than the SALSA model. We also analysed the relative importance of various aerosol processes based on the predictions of the three models. As expected, atmospheric dilution dominated over other processes; dry deposition was the second most significant process. Numerical sensitivity tests with the MAFOR model revealed that the uncertainties associated with the properties of the condensing organic vapours affected only the size range of particles smaller than 10 nm in diameter. These uncertainties therefore do not significantly affect the predictions of the whole of the number size distribution and the total number concentration. The MAFOR model version 2 is well documented and versatile to use, providing a range of alternative parameterizations for various aerosol processes. The model includes an efficient numerical integration of particle number and mass concentrations, an operator splitting of processes, and the use of a fixed sectional method. The model could be used as a module in various atmospheric and climatic models.

Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013–2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30–240 min) and long-term data coverage (9–36 months), providing essential information to improve/validate air quality, health impact, and climate models.

Atmospheric composition has strong influence on human health, ecosystems and also Earth's climate. Among the atmospheric constituents, particulate matter has been recognized as both a strong climate forcer and a significant risk factor for human health, although the health relevance of the specific aerosol characteristics, such as its chemical composition, is still debated. Clouds and aerosols also contribute the largest uncertainty to the radiative budget estimates for climate projections. Thus, reliable estimates of emissions and distributions of pollutants are necessary for assessing the future climate and air-quality related health effects. Chemistry-transport models (CTMs) are valuable tools for understanding the processes influencing the atmospheric composition. This thesis consists of a collection of developments and applications of the chemistry-transport model SILAM. SILAM's ability to reproduce the observed aerosol composition was evaluated and compared with three other commonly used CTM-s in Europe. Compared to the measurements, all models systematically underestimated dry PM10 and PM2.5 by 10-60%, depending on the model and the season of the year. For majority of the PM chemical components the relative underestimation was smaller than that, exceptions being the carbonaceous particles and mineral dust - species that suffer from relatively small amount of available oservational data. The study stressed the necessity for high-quality emissions from wild-land fires and wind-suspended dust, as well as the need for an explicit consideration of aerosol water content in model-measurement comparison. The average water content at laboratory conditions was estimated between 5 and 20% for PM2.5 and between 10 and 25% for PM10. SILAM predictions were used to assess the annual mortality attributable to short-term exposures to vegetation-fire originated PM2.5 in different regions in Europe. PM2.5 emitted from vegetation fires was found to be a relevant risk factor for public health in Europe, more than 1000 premature deaths per year were attributed to vegetation-fire released PM2.5. CTM predictions critically depend on emission data quality. An error was found in the EMEP anthropogenic emission inventory regarding the SOx and PM missions of metallurgy plants on the Kola Peninsula and SILAM was applied to estimate the accuracy of the proposed correction. Allergenic pollen is arguably the type of aerosol with most widely recognised effect to health. SILAM's ability to predict allergenic pollen was extended to include Ambrosia Artemisiifolia - an invasive weed spreading in Southern Europe, with extremely allergenic pollen capable of inducing rhinoconjuctivitis and asthma in the sensitive individuals even in very low concentrations. The model compares well with the pollen observations and predicts occasional exceedances of allergy relevant thresholds even in areas far from the plants' habitat. The variations of allergenicity in grass pollen were studied and mapped to the source areas by adjoint computations with SILAM. Due to the high year-to-year variability of the observed pollen potency between the studied years and the sparse observational network, no clear geographic pattern of pollen allergenicity was detected.

Long-term trends of ambient gaseous pollutants and particulate matter in Helsinki metropolitan area were analyzed from 1994 to 2019. Measurement data from ten monitoring stations located in different types of urban environments including traffic, urban background, rural background, and suburban area were included in this study. We analyzed gas-phase air pollutants, such as NO, NO2, NOx, O3, SO2 and CO; and for aerosol pollutants, we explored mass concentrations for particles smaller than 10 µm and 2.5 µm in diameter (PM10 and PM2.5, respectively ). In order to quantify trends in the data, we deployed a non-parametric Mann-Kendall test and Theil-Sen method. The results were compared with the regional emissions trends and changes in meteorological conditions. Our analysis indicates that SO2 and CO in all stations have decreased to values corresponding to their regional background concentration levels and their role as urban air pollutants have diminished. Our results from the Helsinki Metropolitan area during the last 25 years show that the air quality improved and all the air pollutant concentrations show a decreasing trend, except ozone. Based on our analysis of the Air Quality Index (AQI) at traffic and urban background environments, NO2 concentration, which have typically represented the health effects resulting from vehicular traffic, is rapidly decreasing also in traffic environments. The current AQI standard therefore lacks clarity on the potential health risks from other air pollutants emitted from traffic exhaust. In addition, the air quality indicators currently considered in the AQI do not represent well enough residential wood burning and the possible health outcomes from its exposure. We suggest that the current AQI should be revised in a way that new air quality parameters would be considered, which would better represent the health effects resulting from these local combustion sources.

Marine traffic in harbors can be responsible for significant atmospheric concentrations of ultrafine particles (UFPs), which have widely recognized negative effects on human health. It is therefore essential to model and measure the time evolution of the number size distributions and chemical composition of UFPs in ship exhaust to assess the resulting exposure in the vicinity of shipping routes. In this study, a sequential modelling chain was developed and applied, in combination with the data measured and collected in major harbor areas in the cities of Helsinki and Turku in Finland, during winter and summer in 2010-2011. The models described ship emissions, atmospheric dispersion, and aerosol dynamics, complemented with a time-microenvironment-activity model to estimate the short-term UFP exposure. We estimated the dilution ratio during the initial fast expansion of the exhaust plume to be approximately equal to eight. This dispersion regime resulted in a fully formed nucleation mode (denoted as Nuc(2)). Different selected modelling assumptions about the chemical composition of Nuc(2) did not have an effect on the formation of nucleation mode particles. Aerosol model simulations of the dispersing ship plume also revealed a partially formed nucleation mode (Nuc(1); peaking at 1.5 nm), consisting of freshly nucleated sulfate particles and condensed organics that were produced within the first few seconds. However, subsequent growth of the new particles was limited, due to efficient scavenging by the larger particles originating from the ship exhaust. The transport of UFPs downwind of the ship track increased the hourly mean UFP concentrations in the neighboring residential areas by a factor of two or more up to a distance of 3600 m, compared with the corresponding UFP concentrations in the urban background. The substantially increased UFP concentrations due to ship traffic significantly affected the daily mean exposures in residential areas located in the vicinity of the harbors.

Atmospheric particles are one of the leading mortality risk factors in the Global Burden of Disease study (GBD). The association between particulate mass of particles smaller than 2.5 μm in diameter (PM2.5) and cardiovascular and pulmonary diseases has been characterized by multiple epidemiological studies, and varying estimates suggest that several million premature death occur globally each year due to PM2.5 exposure. Mitigation of the adverse health effects of particulate matter requires comprehensive understanding of their sources and dynamic processes, such as spatial dispersion. Recent emergence and development of aerosol sensors, which are typically characterized as small, relatively low cost and easy to use, have enabled new opportunities in air quality monitoring. As a result of their practical convenience, sensors can be deployed to the field in high quantities which, consequently, enables network-type, spatially comprehensive measurements. However, with more simplified and less expensive measurement approach, less accurate and reliable results may be expected. This study aimed to evaluate and characterize the accuracy and usability of aerosol sensor to urban air quality measurements. The investigation focused on two of the most prominent measurement techniques applicable to sensor type monitoring; optical and diffusion chargingbased techniques. Sensors utilizing optical technique were evaluated in laboratory and field studies for their error sources and particle size-selectivity, specifically. Diffusion charging-based sensors, which measure lung deposited surface area of particles, were evaluated in the field for their suitability to measure combustion emitted particles, such as vehicular exhaust and residential wood combustion emissions. Results of the study indicated that optical aerosol sensors are unlikely to be fit for long-term regulatory monitoring. The main issues preventing this arise from their improper calibration which poses a significant risk of data misinterpretation; none of the laboratory evaluated sensors measured particle sizes which their technical specifications implied. On the other hand, field tests showed that when the measured size fraction was targeted to match the true detection range of the sensor, highly accurate and repeatable results were obtained. This implies that, while the usability of optical sensors is limited in their current form, the concept and vision of a sensor driven air quality monitoring network remains valid and achievable. In comparison to optical sensors, diffusion charging-based sensors were found to be more mature in terms of their technological development. The evaluated sensors exhibited accurate and stable performance throughout the test campaigns and were shown to be particularly well-suited the measurement of combustion emitted particles. Hence, diffusion charger sensors would be a valuable addition to be used alongside other measurement techniques as urban air quality is heavily affected by nanoparticles. *** Ilmakehän pienhiukkaset ovat yksi keskeisimmistä kuolleisuuden riskitekijöistä kansainvälisessä taudin rasittavuuden analyysissä. Useat epidemiologiset tutkimukset ovat osoittaneet pienhiukkasten ja sydän- ja verisuoni- sekä hengitystiesairauksien yhteyden, ja eri arvioiden mukaan useita miljoonia ennenaikaisia kuolemia tapahtuu joka vuosi pienhiukkasaltistumisen seurauksena. Jotta pienhiukkasten negatiivisiin terveysvaikutuksiin voitaisiin vaikuttaa, tulee niiden lähteet ja dynaamiset prosessit, kuten alueellinen leviäminen, tuntea hyvin. Viimeaikainen aerosolisensoreiden esilletulo ja kehittyminen ovat avanneet uusia mahdollisuuksia ilmanlaadun seurantaan. Sensorit, jotka ovat tyypillisesti pienikokoisia, suhteellisen edullisia ja helppokäyttöisiä, mahdollistavat alueellisesti kattavien sensoriverkkomittausten toteuttamisen ja siten pienhiukkasten tarkemman tutkimisen. Sensoreiden edullisempi ja siten yksinkertaisempi mittaustekniikka saattaa toisaalta johtaa suurempaan mittausepätarkkuuteen ja huonompaan laatuun. Tämän työn tavoitteena oli arvioida ja luonnehtia aerosolisensoreiden tarkkuutta ja soveltuvuutta kaupunkialueiden ilmanlaadun seurantaan. Tutkimus keskittyi kahteen mittaustekniikkaan, jotka ovat parhaiten sovellettavissa sensorityyppisiin mittauksiin; optiseen ja diffuusiovarautumiseen perustuvaan tekniikkaan. Optisia sensoreita testattiin sekä ulkoilmassa että laboratoriossa, missä niiden hiukkaskokovalikoivuutta arvioitiin tutkimalla sensorin vastetta keinotekoisesti tuotetuilla erikokoisilla referenssihiukkasilla. Diffuusiovarautumiseen perustuvia sensoreita, jotka mittaavat niin kutsuttua keuhkodeposoituvaa pinta-ala, testattiin ulkoilmassa, missä niiden suorituskykyä arvioitiin erityisesti erittäin pienten nanohiukkasten, kuten liikenteen pakokaasun sekä puunpolton päästöjen, näkökulmasta. Tutkimustulosten perusteella optiset aerosolisensorit eivät toistaiseksi ole soveltuvia pitkäaikaiseen viranomaisvalvonnassa tehtävään ilmanlaadun seurantaan. Tämä johtuu niiden virheellisestä kalibroinnista, jonka seurauksena sensorit eivät mittaa hiukkaskokoluokkia, joita niiden tekniset tuoteselosteet antavat olettaa. Riski mittausdatan väärin tulkinnalle on täten ilmeinen. Toisaalta, kun mitattu hiukkasten kokojakauma rajattiin vastaamaan sensorin ominaista vastealuetta, sensorin mittaustarkkuus oli hyvä ja toistettava. Tämän perusteella, vaikkakin virheellinen kalibrointi rajoittaa optisten sensoreiden käytettävyyttä, konsepti ja visio sensoripohjaisesta mittausverkosta on mahdollinen ja saavutettavissa. Diffuusiovarautumiseen perustuvat sensorit osoittivat olevan teknisesti kehittyneempiä kuin optiset sensorit. Testatut sensorit olivat tarkkoja ja stabiileja kaikissa kenttämittauskampanjoissa, ja ne olivat erityisen hyvin soveltuvia liikenteen pakokaasujen sekä puunpolton päästöjen mittaamiseen. Tämän vuoksi diffuusiovaraukseen perustuvat sensorit olisivat arvokas lisä muiden mittaustekniikoiden rinnalle, varsinkin kun nanohiukkasten osuus kaupunki-ilmassa on merkittävä.