Evolution of In-Cylinder Diesel Engine Soot and Emission Characteristics Investigated with Online Aerosol Mass Spectrometry

To design diesel engines with low environmental impact, it is important to link health and climate-relevant soot (black carbon) emission characteristics to specific combustion conditions. The in-cylinder evolution of soot properties over the combustion cycle and as a function of exhaust gas recirculation (EGR) was investigated in a modern heavy-duty diesel engine. A novel combination of a fast gas-sampling valve and a soot particle aerosol mass spectrometer (SP-AMS) enabled online measurements of the in-cylinder soot chemistry. The results show that EGR reduced the soot formation rate. However, the late cycle soot oxidation rate (soot removal) was reduced even more, and the net effect was increased soot emissions. EGR resulted in an accumulation of polycyclic aromatic hydrocarbons (PAHs) during combustion, and led to increased PAH emissions. We show that mass spectral and optical signatures of the in-cylinder soot and associated low volatility organics change dramatically from the soot formation dominated phase to the soot oxidation dominated phase. These signatures include a class of fullerene carbon clusters that we hypothesize represent less graphitized, C5-containing fullerenic (high tortuosity or curved) soot nanostructures arising from decreased combustion temperatures and increased premixing of air and fuel with EGR. Altered soot properties are of key importance when designing emission control strategies such as diesel particulate filters and when introducing novel biofuels

Direct detection of atmospheric particle formation using the Neutral cluster and Air Ion Spectrometer

Aerosol particles play an important role in the Earth s atmosphere and in the climate system: they scatter and absorb solar radiation, facilitate chemical processes, and serve as seeds for cloud formation. Secondary new particle formation (NPF) is a globally important source of these particles. Currently, the mechanisms of particle formation and the vapors participating in this process are, however, not truly understood. In order to fully explain atmospheric NPF and subsequent growth, we need to measure directly the very initial steps of the formation processes. This thesis investigates the possibility to study atmospheric particle formation using a recently developed Neutral cluster and Air Ion Spectrometer (NAIS). First, the NAIS was calibrated and intercompared, and found to be in good agreement with the reference instruments both in the laboratory and in the field. It was concluded that NAIS can be reliably used to measure small atmospheric ions and particles directly at the sizes where NPF begins. Second, several NAIS systems were deployed simultaneously at 12 European measurement sites to quantify the spatial and temporal distribution of particle formation events. The sites represented a variety of geographical and atmospheric conditions. The NPF events were detected using NAIS systems at all of the sites during the year-long measurement period. Various particle formation characteristics, such as formation and growth rates, were used as indicators of the relevant processes and participating compounds in the initial formation. In a case of parallel ion and neutral cluster measurements, we also estimated the relative contribution of ion-induced and neutral nucleation to the total particle formation. At most sites, the particle growth rate increased with the increasing particle size indicating that different condensing vapors are participating in the growth of different-sized particles. The results suggest that, in addition to sulfuric acid, organic vapors contribute to the initial steps of NPF and to the subsequent growth, not just later steps of the particle growth. As a significant new result, we found out that the total particle formation rate varied much more between the different sites than the formation rate of charged particles. The results infer that the ion-induced nucleation has a minor contribution to particle formation in the boundary layer in most of the environments. These results give tools to better quantify the aerosol source provided by secondary NPF in various environments. The particle formation characteristics determined in this thesis can be used in global models to assess NPF s climatic effects.Ilman aerosolihiukkaset ovat jatkuvassa vuorovaikutuksessa toistensa ja ympäröivien kaasujen kanssa. Mikroskooppisesta koostaan huolimatta aerosolihiukkaset vaikuttavat maapallon ilmastoon: hiukkaset sirottavat ja absorboivat auringosta tulevaa säteilyä. Hiukkaset vaikuttavat pilvien muodostumiseen ja sitä kautta pilvien heijastamaan säteilyyn. Ominaisuuksistaan ja sijainnistaan riippuen hiukkaset voivat olla ilmastoa viilentäviä tai lämmittäviä. Merkittävimmän epävarmuustekijän ilmastontutkimuksessa muodostavatkin nimenomaan aerosolien vaikutukset. Aerosolihiukkasten kokonaisvaikutus ilmastoon tunnetaan vielä melko heikosti ilmakehän lukuisten prosessien ja palautemekanismien takia. Nykytiedon mukaan hiukkaset vaikuttavat maapallon ilmastoon pääasiassa viilentävästi. Arviot aerosolien viilentävistä vaikutuksista vaihtelevat paljon muun muassa siksi, ettei aerosolien pitoisuuksia ja ominaisuuksia ilmakehässä kyetä tarkasti mittaamaan. Tässä väitöskirjatyössä on pureuduttu nimenomaan tähän problematiikkaan. Työssä mitattiin ilmakehän hiukkaspitoisuuksia ja -kokojakaumia vastakehitetyllä mittauslaitteistolla useissa eri ympäristössä ympäri Eurooppaa. Kaikissa mittauspaikoissa havaittiin hiukkasmuodosta ilmakehän kaasujen tiivistyessä hiukkasiksi, jolloin hiukkaspitoisuudet nousivat hetkellisesti hyvinkin suuriksi. Lopulta nämä vastamuodostuneet hiukkaset myös kasvoivat kokoihin, joilla on huomattavia ilmastovaikutuksia. Kerättyä ainutlaatuista mittausaineistoa voidaan käyttää hyväksi kehitettäessä maapallon ilmastomalleja, mikä osaltaan pienentää aerosolien aiheuttamaa epävarmuutta ilmastotutkimuksessa. Hiukkasten viipymäaika on kasvihuonekaasuihin verrattuna lyhyt, joten hiukkaspäästöjen muutoksien vaikutukset ilmastoon ovat nopeammin havaittavissa. Tässäkin työssä aloitetut pitkän aikasarjan mittaukset ovat merkittäviä tutkittaessa ilmakehän aerosolihiukkasten vaikutusta ilmastoon sekä erilaisia palautemekanismeja aerosolien, ilmaston, pilvien ja koko ekosysteemin välillä. Työ on tehty Ilmakehän koostumuksen ja ilmastonmuutoksen fysiikan, kemian, biologian ja meteorologian huippuyksikössä Helsingin yliopistossa. Huippuyksikön tavoitteena on a) pitkäaikaiset, jatkuvatoimiset mittaukset ja tietopankit ilmakehän ominaisuuksista ja ekologisista aine- ja energiavirroista ja b) täsmälliset kokeet ja mallit joiden avulla havaittuja ilmiöitä pyritään selvittämään

Sequential Modelling and Inference of High-frequency Limit Order Book with State-space Models and Monte Carlo Algorithms

The high-frequency limit order book (LOB) market has recently attracted increasing research attention from both the industry and the academia as a result of expanding algorithmic trading. However, the massive data throughput and the inherent complexity of high-frequency market dynamics also present challenges to some classic statistical modelling approaches. By adopting powerful state-space models from the field of signal processing as well as a number of Bayesian inference algorithms such as particle filtering, Markov chain Monte Carlo and variational inference algorithms, this thesis presents my extensive research into the high-frequency limit order book covering a wide scope of topics. Chapter 2 presents a novel construction of the non-homogeneous Poisson process to allow online intensity inference of limit order transactions arriving at a central exchange as point data. Chapter 3 extends a baseline jump diffusion model for market fair-price process to include three additional model features taken from real-world market intuitions. In Chapter 4, another price model is developed to account for both long-term and short-term diffusion behaviours of the price process. This is achieved by incorporating multiple jump-diffusion processes each exhibiting a unique characteristic. Chapter 5 observes the multi-regime nature of price diffusion processes as well as the non-Markovian switching behaviour between regimes. As such, a novel model is proposed which combines the continuous-time state-space model, the hidden semi-Markov switching model and the non-parametric Dirichlet process model. Additionally, building upon the general structure of the particle Markov chain Monte Carlo algorithm, I further propose an algorithm which achieves sequential state inference, regime identification and regime parameters learning requiring minimal prior assumptions. Chapter 6 focuses on the development of efficient parameter-learning algorithms for state-space models and presents three algorithms each demonstrating promising results in comparison to some well-established methods. The models and algorithms proposed in this thesis not only are practical tools for analysing high-frequency LOB markets, but can also be applied in various areas and disciplines beyond finance

Chemical assessment of non-thermal plasma for reduction of odour emissions from pig houses

Methanethiol is an important odorant from pig houses, but it can be difficult to measure due to low concentrations, high volatility and becauseit easily reacts to form dimethyl disulphide. A method was developedfor sampling and measuring methanethiol with minimum artefact formation using sorbent materials and thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). As odour from pig production can be a nuisance to neighbours, a non-thermal plasma system for odour removal was tested on emissions from pig houses. The experiments showed good removal for some odorants, especially indole and 3-methyl-1H-indole, and a high degree of particle removal. Gas/particle partitioning of odorants in a pig house was also investigatedand a method for measuring odorants in particles by filters and TDGC-MS was developed and evaluated. Only low concentrations and low fractions of odorants were found in the particle phase, thus the contribution to odour from particles was evaluated to be limited

Highly Oxygenated Organic Molecules (HOM) from Gas-Phase Autoxidation Involving Peroxy Radicals : A Key Contributor to Atmospheric Aerosol

Peer reviewe

Highly Oxygenated Organic Molecules (HOM) from Gas-Phase Autoxidation Involving Peroxy Radicals: A Key Contributor to Atmospheric Aerosol

Highly oxygenated organic molecules (HOM) are formed in the atmosphere via autoxidation involving peroxy radicals arising from volatile organic compounds (VOC). HOM condense on pre-existing particles and can be involved in new particle formation. HOM thus contribute to the formation of secondary organic aerosol (SOA), a significant and ubiquitous component of atmospheric aerosol known to affect the Earth's radiation balance. HOM were discovered only very recently, but the interest in these compounds has grown rapidly. In this Review, we define HOM and describe the currently available techniques for their identification/quantification, followed by a summary of the current knowledge on their formation mechanisms and physicochemical properties. A main aim is to provide a common frame for the currently quite fragmented literature on HOM studies. Finally, we highlight the existing gaps in our understanding and suggest directions for future HOM research. © 2019 American Chemical Society

Organic Constituents of Atmospheric Aerosols in a Hemi-boreal Forest

Atmospheric aerosols have been demonstrated to be a highly dynamic system, playing a significant role in climate change and human health. In nature, ecosystems like boreal forests can modify the atmospheric particles producing a warming or cooling effect on climate. However, the regional and global impact of boreal forest on climate is still difficult to determine, especially due to the heterogeneous chemistry of aerosol samples, the need for multiple instruments for identification, and their limited library of compounds. In this thesis, to overcome these issues, we used a molecular networking technique based on the Global Natural Products Social web platform in combination with Nuclear Magnetic Resonance (NMR) to perform a screening of organic aerosols during the winter spring, and summer seasons from a Hemi-boreal forest. The aerosol samples were recollected in a glass filter weekly from SMEAR Station (Estonia) and analyzed by Gas Chromatography Mass spectrometry and NMR. A variety of chemical functional groups including carboxylic acids, phthalates, and organophosphate among the most abundant were annotated in the studied seasons. Furthermore, it was analyzed the presence of n-alkanol, carboxylic acid, and nalkane to evaluate any hydrocarbon contamination. Phthalates-based compounds like Dibutyl phthalate (~20.59% in winter), and Bis(2-ethylhexyl) phthalate (~3.87% in summer), altogether with organophosphates like Tris(2,4-di-tert-butylphenyl) phosphate (~24.13% in spring) and tris(2,4-di-tertbutylphenyl) phosphite (~5.13% in summer) were annotated as a possible air pollutant. Besides that, conifer burning tracers such as 7-Oxodehydroabietic (~1.18% in spring) and dehydroabietic acid (~0.49% in summer) were annoted. These finding presented in this work gives an insightful impact on the atmospheric aerosol composition presented in a Hemi-boreal forest using a straightforward and versatile technique such as molecular networking