Helsinki Region Environmental Services Authority

Helsinki, Finland

Helsinki Region Environmental Services Authority

Helsinki, Finland
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Hellen H.,Finnish Meteorological Institute | Kangas L.,Finnish Meteorological Institute | Kousa A.,Helsinki Region Environmental Services Authority | Vestenius M.,Finnish Meteorological Institute | And 5 more authors.
Atmospheric Chemistry and Physics | Year: 2017

Even though emission inventories indicate that wood combustion is a major source of polycyclic aromatic hydrocarbons (PAHs), estimating its impacts on PAH concentration in ambient air remains challenging. In this study the effect of local small-scale wood combustion on the benzo[a]pyrene (BaP) concentrations in ambient air in the Helsinki metropolitan area in Finland is evaluated, using ambient air measurements, emission estimates, and dispersion modeling. The measurements were conducted at 12 different locations during the period from 2007 to 2015. The spatial distributions of annual average BaP concentrations originating from wood combustion were predicted for four of those years: 2008, 2011, 2013, and 2014. According to both the measurements and the dispersion modeling, the European Union target value for the annual average BaP concentrations (1 ng m-3) was clearly exceeded in certain suburban detached-house areas. However, in most of the other urban areas, including the center of Helsinki, the concentrations were below the target value. The measured BaP concentrations highly correlated with the measured levoglucosan concentrations in the suburban detached-house areas. In street canyons, the measured concentrations of BaP were at the same level as those in the urban background, clearly lower than those in suburban detached-house areas. The predicted annual average concentrations matched with the measured concentrations fairly well. Both the measurements and the modeling clearly indicated that wood combustion was the main local source of ambient air BaP in the Helsinki metropolitan area. © Author(s) 2017.


Wanner L.,Catalan Institution for Research and Advanced Studies | Wanner L.,University Pompeu Fabra | Rospocher M.,Fondazione Bruno Kessler | Vrochidis S.,Center for Research and Technology Hellas | And 18 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2015

Citizens are increasingly aware of the influence of environmental and meteorological conditions on the quality of their life. This results in an increasing demand for personalized environmental information, i.e., information that is tailored to citizens’ specific context and background. In this demonstration, we present an environmental information system that addresses this demand in its full complexity in the context of the PESCaDO EU project. Specifically, we will show a system that supports submission of user generated queries related to environmental conditions. From the technical point of view, the system is tuned to discover reliable data in the web and to process these data in order to convert them into knowledge, which is stored in a dedicated repository. At run time, this information is transferred into an ontology-based knowledge base, from which then information relevant to the specific user is deduced and communicated in the language of their preference. © Springer-Verlag Berlin Heidelberg 2015.


Soares J.,Finnish Meteorological Institute | Kousa A.,Helsinki Region Environmental Services Authority | Kukkonen J.,Finnish Meteorological Institute | Matilainen L.,Helsinki Region Environmental Services Authority | And 10 more authors.
Geoscientific Model Development | Year: 2014

A mathematical model is presented for the determination of human exposure to ambient air pollution in an urban area; the model is a refined version of a previously developed mathematical model EXPAND (EXposure model for Particulate matter And Nitrogen oxiDes). The model combines predicted concentrations, information on people's activities and location of the population to evaluate the spatial and temporal variation of average exposure of the urban population to ambient air pollution in different microenvironments. The revisions of the modelling system containing the EXPAND model include improvements of the associated urban emission and dispersion modelling system, an improved treatment of the time use of population, and better treatment for the infiltration coefficients from outdoor to indoor air. The revised model version can also be used for estimating intake fractions for various pollutants, source categories and population subgroups. We present numerical results on annual spatial concentration, time activity and population exposures to PM2.5 in the Helsinki Metropolitan Area and Helsinki for 2008 and 2009, respectively. Approximately 60% of the total exposure occurred at home, 17% at work, 4% in traffic and 19% in other microenvironments in the Helsinki Metropolitan Area. The population exposure originating from the long-range transported background concentrations was responsible for a major fraction, 86 %, of the total exposure in Helsinki. The largest local contributors were vehicular emissions (12 %) and shipping (2 %). © Author(s) 2014. CC Attribution 3.0 License.


Kosonen H.,Aalto University | Heinonen M.,Aalto University | Mikola A.,Aalto University | Haimi H.,Aalto University | And 5 more authors.
Environmental Science and Technology | Year: 2016

The nitrous oxide emissions of the Viikinmäki wastewater treatment plant were measured in a 12 month online monitoring campaign. The measurements, which were conducted with a continuous gas analyzer, covered all of the unit operations of the advanced wastewater-treatment process. The relation between the nitrous oxide emissions and certain process parameters, such as the wastewater temperature, influent biological oxygen demand, and ammonium nitrogen load, was investigated by applying online data obtained from the process-control system at 1 min intervals. Although seasonal variations in the measured nitrous oxide emissions were remarkable, the measurement data indicated no clear relationship between these emissions and seasonal changes in the wastewater temperature. The diurnal variations of the nitrous oxide emissions did, however, strongly correlate with the alternation of the influent biological oxygen demand and ammonium nitrogen load to the aerated zones of the activated sludge process. Overall, the annual nitrous oxide emissions of 168 g/PE/year and the emission factor of 1.9% of the influent nitrogen load are in the high range of values reported in the literature but in very good agreement with the results of other long-term online monitoring campaigns implemented at full-scale wastewater-treatment plants. © 2016 American Chemical Society.


Aurela M.,Finnish Meteorological Institute | Saarikoski S.,Finnish Meteorological Institute | Niemi J.V.,Helsinki Region Environmental Services Authority | Niemi J.V.,University of Helsinki | And 6 more authors.
Aerosol and Air Quality Research | Year: 2015

Chemical characterization of non-refractory submicron particles (NR-PM1) and source apportionment of organic aerosols (OA) were carried out at four different sites in the Helsinki metropolitan area, Finland, using an Aerodyne Aerosol Chemical Speciation Monitor (ACSM). Two of the sites represented suburban residential areas, whereas the other two were traffic sites, one in a curbside in downtown and the other one in a suburban highway edge. The residential and the curbside measurements were conducted during the winter, but the highway campaign was carried out in the autumn. NR-PM1 were composed mainly of organics (40–68% in the different sites), followed by sulphate (11–34%), nitrate (12–16%), ammonium (7.8–8.5%) and chloride (0.24–1.3%). The mean concentrations of NR-PM1 were quite similar during the winter campaigns (10.1–12.5 μg/m3), but NR-PM1 was clearly lower during the autumn campaign at the highway site (6.0 μg/m3) due to the meteorology (favourable mixing conditions), small concentrations of long-range transported particles and non-intensive heating period locally and regionally. Using a multilinear engine algorithm (ME-2) and the custom software tool Source Finder (SoFI), the organic fraction was divided into two or three types of OA representing hydrocarbon-like organic aerosol (HOA), oxygenated organic aerosol (OOA), and in three sites, biomass burning organic aerosol (BBOA). At the downtown traffic site (Curbside), BBOA could not be found, probably because most of the local wood burning occurs in the suburban areas of the Helsinki region. OOA had the largest contribution to OA at all the sites (50–67%). The contribution of HOA was higher at the traffic sites (25–32%) than at the residential sites (15–18%). At the suburban residential and highway sites, the contribution of BBOA was high (25–30%). Especially during cold periods, very high BBOA contributions (~50%) were observed at the residential sites. © Taiwan Association for Aerosol Research.


Mulas M.,Aalto University | Mulas M.,Federal University of Campina Grande | Tronci S.,University of Cagliari | Corona F.,Aalto University | And 6 more authors.
Journal of Process Control | Year: 2015

In this work, we discuss the application of multivariable predictive control for the activated sludge process in a full-scale municipal wastewater treatment plant. Emphasis is given to the selection of a control configuration that contributes to minimising the economic costs while improving the removal efficiency of the nitrogen compounds. For this task, a simple dynamic matrix control algorithm is favoured for controlling the nitrogen concentrations at the end of the biological process. The behaviour of the activated sludge process is reproduced in a commercial simulator that acts as a real-time testing platform and that is also used for identifying the multivariable input-output models for the predictive controller. For demonstrating the effectiveness of the proposed approach, different control configurations are considered and compared against the aeration control strategies currently used at the plant. Based on the simulation results, this work shows the potentiality of the dynamic matrix control which is able to decrease the energy consumption costs and, at the same time, reduce the ammonia peaks and nitrate concentration in the effluent. © 2015 Elsevier Ltd. All rights reserved.


Vaisanen O.,University of Eastern Finland | Ruuskanen A.,Finnish Meteorological Institute | Ylisirnio A.,University of Eastern Finland | Miettinen P.,University of Eastern Finland | And 9 more authors.
Atmospheric Chemistry and Physics | Year: 2016

The relationship between aerosol hygroscopicity and cloud droplet activation was studied at the Puijo measurement station in Kuopio, Finland, during the autumn 2014. The hygroscopic growth of 80, 120 and 150 nm particles was measured at 90% relative humidity with a hygroscopic tandem differential mobility analyzer. Typically, the growth factor (GF) distributions appeared bimodal with clearly distinguishable peaks around 1.0-1.1 and 1.4-1.6. However, the relative contribution of the two modes appeared highly variable reflecting the probable presence of fresh anthropogenic particle emissions. The hygroscopicitydependent activation properties were estimated in a case study comprising four separate cloud events with varying characteristics. At 120 and 150 nm, the activation efficiencies within the low- and high-GF modes varied between 0- 34 and 57-83 %, respectively, indicating that the less hygroscopic particles remained mostly non-activated, whereas the more hygroscopic mode was predominantly scavenged into cloud droplets. By modifying the measured GF distributions, it was estimated how the cloud droplet concentrations would change if all the particles belonged to the more hygroscopic group. According to κ-Köhler simulations, the cloud droplet concentrations increased up to 70% when the possible feedback effects on effective peak supersaturation (between 0.16 and 0.29 %) were assumed negligible. This is an indirect but clear illustration of the sensitivity of cloud formation to aerosol chemical composition. © Author(s) 2016.


Corona F.,Aalto University | Mulas M.,Aalto University | Haimi H.,Aalto University | Sundell L.,Helsinki Region Environmental Services Authority | And 2 more authors.
Journal of Process Control | Year: 2013

Due to stringent environmental regulations, wastewater treatment plants are always challenged to meet new constraints in terms of water pollution prevention. In such an effort, the number of sensors and data available in the plants have increased considerably during the last decades. However, the quality of the collected data and the sensor reliability are often poor mainly due to the hostile environment in which the measurement equipment has to function. In this work, we present the design of an array of soft-sensors to estimate the nitrate concentration in the post-denitrification filter unit of the Viikinmäki wastewater treatment plant in Helsinki (Finland). The developed sensors aim at supporting the existing hardware analyzers by providing a reliable back-up system in case of malfunction. The main stages of the soft-sensors' design are discussed and the development illustrated in detail, starting from the preliminary preprocessing of the available process measurements where sample and variable selection has been performed, toward the calibration of the regression models and discussion on the performance results. The estimation accuracy together with the light computational cost of the developed soft-sensors demonstrate their potential for an on-line implementation in the plant's control system. © 2012 Elsevier Ltd. All rights reserved.


Mulas M.,Aalto University | Tronci S.,University of Cagliari | Corona F.,Aalto University | Haimi H.,Aalto University | And 4 more authors.
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2013

This paper deals with the development of a multivariable predictive control structure for improving the nitrogen removal of a biological wastewater treatment plant while reducing the operational costs. A simple dynamic matrix control algorithm is utilised as predictive controller and applied to a full-scale municipal wastewater treatment plant for controlling nitrogen concentrations at the end of the biological process. The complex calibrated model of the process is implemented in a commercial simulator that acts as a real-time testing platform for the proposed control structure, and allows the identification of the multivariable input-output model for the predictive control. Simulation results show the potentialities of the chosen predictive control, which allows the reduction of ammonia peaks in the effluent and at the same time permits a reduction of the energy consumption costs. © IFAC.


Mulas M.,Aalto University | Corona F.,Aalto University | Haimi H.,Aalto University | Sundell L.,Helsinki Region Environmental Services Authority | And 2 more authors.
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2011

Due to stringent environmental regulations, wastewater treatment plants are always challenged to meet new constraints in terms of water pollution prevention. In such an effort, the number of sensors and data available in the plants have increased considerably during the last decades. However, the quality of the collected data and the sensor reliability are often poor mainly due to the hostile environment in which the measurement equipment has to function. In this work, we present the design of an array of soft-sensors to estimate the nitrate concentration in the post-denitrification filter unit of the Viikinmäki wastewater treatment plant in Helsinki (Finland). The developed sensors aim at supporting the existing hardware analysers by providing a reliable back-up system in case of malfunction. After a careful selection of suitable observations and variables to be used for calibrating the estimation models, the experimental results show the accuracy of the developed soft-sensors and their potential for an on-line implementation in the plant's control system. © 2011 IFAC.

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