Novel Electrical Aerosol Instrumentation for Calibration and Charge Measurement Applications

Aerosol measurements are conducted in several applications, such as in air quality and emission analysis. This thesis focuses on electrical aerosol instrumentation, in which the aerosol detection is achieved by measuring electric current from charged particles. If particle charge is known accurately, the current produced by particles can be used as an accurate and traceable concentration reference in calibration of various aerosol instruments. Additionally, same methods can be applied with small modifications in the measurement of particle charge. These form the main objectives of this thesis, which are to develop particle charge measurement and aerosol instrument calibration methods in a size range from nanometers to micrometers.In this thesis, the operation of the Electrical Low Pressure Impactor (ELPI+) is introduced. The instrument contains two main components, charger and impactor, which were characterized in calibration measurements. The ELPI+ and the Differential Mobility Analyzer (DMA) were used as a basis of the developed DMA-ELPI particle charge measurement method, in which particles are classified according to their electrical mobility, which is a function of particle size and charge. This is followed by aerodynamic size classification and detection with an ELPI+. The main advantage of the developed method is the wide particle size range compared to other available techniques. The charge measurement was successfully tested using particles with well-defined size distributions and charging states. Additionally, an instrument called BOLAR was developed for studying charge from inhaler-generated particles. The BOLAR is capable of measuring the size fractioned bipolar charging state of aerosol particles. The operation of the instrument was verified with calibration measurements, and the instrument was applied in studying charge of inhaler-generated particles. As a final application of electrical aerosol instrumentation, a new wide size range instrument calibration setup was developed. This included designing and constructing a particle growth unit, an electrical mobility classifier for μm-sized particles and a flow mixing and splitting assembly. All these components were characterized, and the setup was used to calibrate a particle counter traceably in the size range from 3.6 nm to 5.3 μm, which has not previously been possible with any single setup. The introduced high accuracy calibration method can be used as a traceable primary standard for particle number concentration

Reducing particle emissions from marine engines – fuel choices and technology pathways

Particle emissions from marine applications have been receiving increasing attention in recent years, whether as black carbon for their impact in artic ice melting and global warming, as nanoparticles for their health impact or due to the general classification of soot as a carcinogenic substance by the World Health Organization. Fulfiling the global requirements of marine propulsion and power generation applications only a few technology paths are commercially available which have the potential to reduce particle emissions significantly. SOX scrubber in combination with traditional HFO operated diesel engines represent one route trying to achieve this objective. Alternatively, the engines can be converted to dual fuel operation, including liquified natural gas (LNG) operation or the fuel can be changed to a distillate liquid fuel which can be combined with a diesel particulate filter (DPF). In detail, these different approaches vary not only in terms of technical challenges, required onboard modifications and costs, but also with regards to their actual performance in reducing black carbon (BC), particle mass (PM) and nanoparticle-related particle number (PN) emissions. In the European Union the PN abatement performance will gain additional attention as in upcoming regulations a cutoff level for ultra-fine nanoparticle emissions of 10 nm will likely be introduced. In this contribution we present a comparison of the different technological options for low BC, PM &amp; PN with their respective challenges and performance characteristics. Measurements have been conducted on marine medium-speed and high-speed engines on both engine test beds and on board. The setups were chosen in a way to cover the range of commercially available paths to reduce particulate emissions. For the measurements a range of analytical devices for assessing particlerelated emissions (together with gaseous emissions measurements) were employed. Results are set in context of current and upcoming emission regulation for international, near-coast and inland water marine applications.<br/

Reducing particle emissions from marine engines – fuel choices and technology pathways

Particle emissions from marine applications have been receiving increasing attention in recent years, whether as black carbon for their impact in artic ice melting and global warming, as nanoparticles for their health impact or due to the general classification of soot as a carcinogenic substance by the World Health Organization. Fulfiling the global requirements of marine propulsion and power generation applications only a few technology paths are commercially available which have the potential to reduce particle emissions significantly. SOX scrubber in combination with traditional HFO operated diesel engines represent one route trying to achieve this objective. Alternatively, the engines can be converted to dual fuel operation, including liquified natural gas (LNG) operation or the fuel can be changed to a distillate liquid fuel which can be combined with a diesel particulate filter (DPF). In detail, these different approaches vary not only in terms of technical challenges, required onboard modifications and costs, but also with regards to their actual performance in reducing black carbon (BC), particle mass (PM) and nanoparticle-related particle number (PN) emissions. In the European Union the PN abatement performance will gain additional attention as in upcoming regulations a cutoff level for ultra-fine nanoparticle emissions of 10 nm will likely be introduced. In this contribution we present a comparison of the different technological options for low BC, PM &amp; PN with their respective challenges and performance characteristics. Measurements have been conducted on marine medium-speed and high-speed engines on both engine test beds and on board. The setups were chosen in a way to cover the range of commercially available paths to reduce particulate emissions. For the measurements a range of analytical devices for assessing particlerelated emissions (together with gaseous emissions measurements) were employed. Results are set in context of current and upcoming emission regulation for international, near-coast and inland water marine applications.<br/

Prostate MRI added to CAPRA, MSKCC and Partin cancer nomograms significantly enhances the prediction of adverse findings and biochemical recurrence after radical prostatectomy

Background To determine the added value of preoperative prostate multiparametric MRI (mpMRI) supplementary to clinical variables and their role in predicting post prostatectomy adverse findings and biochemically recurrent cancer (BCR). Methods All consecutive patients treated at HUS Helsinki University Hospital with robot assisted radical prostatectomy (RALP) between 2014 and 2015 were included in the analysis. The mpMRI data, clinical variables, histopathological characteristics, and follow-up information were collected. Study end-points were adverse RALP findings: extraprostatic extension, seminal vesicle invasion, lymph node involvement, and BCR. The Memorial Sloan Kettering Cancer Center (MSKCC) nomogram, Cancer of the Prostate Risk Assessment (CAPRA) score and the Partin score were combined with any adverse findings at mpMRI. Predictive accuracy for adverse RALP findings by the regression models was estimated before and after the addition of MRI results. Logistic regression, area under curve (AUC), decision curve analyses, Kaplan-Meier survival curves and Cox proportional hazard models were used. Results Preoperative mpMRI data from 387 patients were available for analysis. Clinical variables alone, MSKCC nomogram or Partin tables were outperformed by models with mpMRI for the prediction of any adverse finding at RP. AUC for clinical parameters versus clinical parameters and mpMRI variables were 0.77 versus 0.82 for any adverse finding. For MSKCC nomogram versus MSKCC nomogram and mpMRI variables the AUCs were 0.71 and 0.78 for any adverse finding. For Partin tables versus Partin tables and mpMRI variables the AUCs were 0.62 and 0.73 for any adverse finding. In survival analysis, mpMRI-projected adverse RP findings stratify CAPRA and MSKCC high-risk patients into groups with distinct probability for BCR. Conclusions Preoperative mpMRI improves the predictive value of commonly used clinical variables for pathological stage at RP and time to BCR. mpMRI is available for risk stratification prebiopsy, and should be considered as additional source of information to the standard predictive nomograms.Peer reviewe

A practical approach to improve the statistical performance of surface water monitoring networks

The representativeness of aquatic ecosystem monitoring and the precision of the assessment results are of high importance when implementing the EU’s Water Framework Directive that aims to secure a good status of waterbodies in Europe. However, adapting monitoring designs to answer the objectives and allocating the sampling resources effectively are seldom practiced. Here, we present a practical solution how the sampling effort could be re-allocated without decreasing the precision and confidence of status class assignment. For demonstrating this, we used a large data set of 272 intensively monitored Finnish lake, coastal, and river waterbodies utilizing an existing framework for quantifying the uncertainties in the status class estimation. We estimated the temporal and spatial variance components, as well as the effect of sampling allocation to the precision and confidence of chlorophyll-a and total phosphorus. Our results suggest that almost 70% of the lake and coastal waterbodies, and 27% of the river waterbodies, were classified without sufficient confidence in these variables. On the other hand, many of the waterbodies produced unnecessary precise metric means. Thus, reallocation of sampling effort is needed. Our results show that, even though the studied variables are among the most monitored status metrics, the unexplained variation is still high. Combining multiple data sets and using fixed covariates would improve the modeling performance. Our study highlights that ongoing monitoring programs should be evaluated more systematically, and the information from the statistical uncertainty analysis should be brought concretely to the decision-making process

Associations of PTEN and ERG with Magnetic Resonance Imaging Visibility and Assessment of Non–organ-confined Pathology and Biochemical Recurrence After Radical Prostatectomy

Background: Diagnosing clinically significant prostate cancer (PCa) is challenging, but may be facilitated by biomarkers and multiparametric magnetic resonance imaging (MRI). Objective: To determine the association between biomarkers phosphatase and tensin homolog (PTEN) and ETS-related gene (ERG) with visible and invisible PCa lesions in MRI, and to predict biochemical recurrence (BCR) and non-organ-confined (non-OC) PCa by integrating clinical, MRI, and biomarker-related data. Design, setting, and participants: A retrospective analysis of a population-based cohort of men with PCa, who underwent preoperative MRI followed by radical prostatectomy (RP) during 2014-2015 in Helsinki University Hospital (n = 346), was conducted. A tissue microarray corresponding to the MRI-visible and MRI-invisible lesions in RP specimens was constructed and stained for PTEN and ERG. Outcome measurements and statistical analysis: Associations of PTEN and ERG with MRI-visible and MRI-invisible lesions were examined (Pearson's chi 2 test), and predictions of non-OC disease together with clinical and MRI parameters were determined (area under the receiver operating characteristic curve and logistic regression analyses). BCR prediction was analyzed by Kaplan-Meier and Cox proportional hazard analyses. Results and limitations: Patients with MRI-invisible lesions (n = 35) had less PTEN loss and ERG-positive expression compared with patients (n = 90) with MRI-visible lesions (17.2% vs 43.3% [p = 0.006]; 8.6% vs 20.0% [p = 0.125]). Patients with invisible lesions had better, but not statistically significantly improved, BCR-free survival probability in Kaplan-Meier analyses (p = 0.055). Rates of BCR (5.7% vs 21.1%; p = 0.039), extraprostatic extension (11.4% vs 44.6%; p < 0.001), seminal vesicle invasion (0% vs 21.1%; p = 0.003), and lymph node metastasis (0% vs 12.2%; p = 0.033) differed between the groups in favor of patients with MRI-invisible lesions. Biomarkers had no independent role in predicting non-OC disease or BCR. The short follow-up period was a limitation. Conclusions: PTEN loss, BCR, and non-OC RP findings were more often encountered with MRI-visible lesions. Patient summary: Magnetic resonance imaging (MRI) of the prostate misses some cancer lesions. MRI-invisible lesions seem to be less aggressive than MRI-visible lesions. (C) 2020 European Association of Urology. Published by Elsevier B.V. All rights reserved.Peer reviewe

Added Value of Vaisala AQT530 Sensors as a Part of a Sensor Network for Comprehensive Air Quality Monitoring

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.Peer reviewe

Towards zero pollution vehicles by advanced fuels and exhaust aftertreatment technologies

Vehicular emissions deteriorate air quality in urban areas notably. The aim of this study was to conduct an in-depth characterization of gaseous and particle emissions, and their potential to form secondary aerosol emissions, of the cars meeting the most recent emission Euro 6d standards, and to investigate the impact of fuel as well as engine and aftertreatment technologies on pollutants at warm and cold ambient temperatures. Studied vehicles were a diesel car with a diesel particulate filter (DPF), two gasoline cars (with and without a gasoline particulate filter (GPF)), and a car using compressed natural gas (CNG). The impact of fuel aromatic content was examined for the diesel car and the gasoline car without the GPF. The results showed that the utilization of exhaust particulate filter was important both in diesel and gasoline cars. The gasoline car without the GPF emitted relatively high concentrations of particles compared to the other technologies but the implementation of the GPF decreased particle emissions, and the potential to form secondary aerosols in atmospheric processes. The diesel car equipped with the DPF emitted low particle number concentrations except during the DPF regeneration events. Aromatic-free gasoline and diesel fuel efficiently reduced exhaust particles. Since the renewal of vehicle fleet is a relatively slow process, changing the fuel composition can be seen as a faster way to affect traffic emissions.Peer reviewe

Performance of a Wet Electrostatic Precipitator in Marine Applications

Emissions of marine traffic can be lowered by switching to less polluting fuels or by investing in exhaust aftertreatment. Electrostatic precipitation is a widely used method for particle removal but it is not currently used in combination with marine engines. This study presents the particle filtration characteristics of an emission reduction system designed for marine applications and consisting of a scrubber and a Wet Electrostatic Precipitator (WESP) in series. Partial flow of exhaust from a 1.6 MW marine engine, operated with light and heavy fuel oil, was led to the system. Particle concentrations were measured before the system, after the scrubber and after the WESP. Particle removal characteristics were determined for different engine loads. The scrubber alone removed 15–55% of non-volatile particle number, 30–40% of particle mass and 30–40% of black carbon mass depending on engine load, when HFO fuel was used. By studying particle size distributions, scrubber was found also to generate particles seen as an additional mode in 20–40 nm size range. The system combining the scrubber and WESP removed over 98.5% of particles in number, mass and black carbon metrics when HFO fuel was used. With MDO fuel, 96.5% of PN and 99% of black carbon were removed.publishedVersionPeer reviewe

InDEx – Industrial Data Excellence

InDEx, the Industrial Data Excellence program, was created to investigate what industrial data can be collected, shared, and utilized for new intelligent services in high-performing, reliable and secure ways, and how to accomplish that in practice in the Finnish manufacturing industry.InDEx produced several insights into data in an industrial environment, collecting data, sharing data in the value chain and in the factory environment, and utilizing and manipulating data with artificial intelligence. Data has an important role in the future in an industrial context, but data sources and utilization mechanisms are more diverse than in cases related to consumer data. Experiences in the InDEx cases showed that there is great potential in data utili zation.Currently, successful business cases built on data sharing are either company-internal or utilize an existing value chain. The data market has not yet matured, and third-party offerings based on public and private data sources are rare. In this program, we tried out a framework that aimed to securely and in a controlled manner share data between organizations. We also worked to improve the contractual framework needed to support new business based on shared data, and we conducted a study of applicable business models. Based on this, we searched for new data-based opportunities within the project consortium. The vision of data as a tradeable good or of sharing with external partners is still to come true, but we believe that we have taken steps in the right direction.The program started in fall 2019 and ended in April 2022. The program faced restrictions caused by COVID-19, which had an effect on the intensity of the work during 2020 and 2021, and the program was extended by one year. Because of meeting restrictions, InDEx collaboration was realized through online meetings. We learned to work and collaborate using digital tools and environments. Despite the mentioned hindrances, and thanks to Business Finland’s flexibility, the extension time made it possible for most of the planned goals to be achieved.This report gives insights in the outcomes of the companies’ work within the InDEx program. DIMECC InDEx is the first finalized program by the members of the Finnish Advanced Manufacturing Network (FAMN, www.famn.fi).</p