V. Tarvainen

Atmospheric Nutrient Input to the Baltic Sea from 1850 to 2006: A Reconstruction from Modeling Results and Historical Data

In this study, a consistent basin-wise monthly time series of the atmospheric nutrient load to the Baltic Sea during 1850–2006 was compiled. Due to the lack of a long time series (1850–1960) of nutrient deposition to the Baltic Sea, the data set was compiled by combining a time series of deposition data at the Baltic Nest Institute from 1970 to 2006, published historical monitoring data and deposition estimates, as well as recent modeled Representative Concentration Pathways (RCP) emission estimates. The procedure for nitrogen compounds included estimation of the deposition in a few intermediate reference years, linear interpolation between them, and the decomposition of annual deposition into a seasonal deposition pattern. As no reliable monitoring results were found for the atmospheric deposition of phosphorus during the early period of our study, we used published estimates for the temporal and spatial pattern of the phosphorus load.

Building an Environmental Information System for Personalized Content Delivery

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 work we describe the development of an environmental information system that addresses this demand in its full complexity. Specifically, we aim at developing 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-structured knowledge base, from which then information relevant to the specific user is deduced and communicated in the language of their preference.

Personalized Environmental Service Orchestration for Quality of Life Improvement

Environmental and meteorological conditions are of utmost importance for the population, as they are strongly related to the quality of life. Citizens are increasingly aware of this importance. This awareness results in an increasing demand for environmental information tailored to their specific needs and background. We present an environmental information platform that supports submission of user queries related to environmental conditions and orchestrates results from complementary services to generate personalized suggestions. From the technical viewpoint, the system discovers and processes reliable data in the web in order to convert them into knowledge. At run time, this information is transferred into an ontology-structured knowledge base, from which then information relevant to the specific user is deduced and communicated in the language of their preference. The platform is demonstrated with real world use cases in the south area of Finland showing the impact it can have on the quality of everyday life.

Personalized Environmental Service Configuration and Delivery Orchestration: The PESCaDO Demonstrator

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.

Operational Chemical Weather Forecasting Models on a Regional Scale in Europe

Methods that include a combination of weather forecasting and atmospheric chemistry simulations are here referred to as chemical weather forecasting (CWF). We have selected 18 operational CWF models on regional and continental scales in Europe for a more detailed analysis. We have collected the information in a structured form, and inter-compared and evaluated the mathematical structure of these models. This information makes it possible to evaluate the relative advantages and limitations of the various modeling systems, modeling approaches and sub-models. We have also surveyed the most prominent gaps of knowledge in this field, and suggested potential priorities for future research directions. There are substantial gaps of knowledge, especially in the following fields: emission inventories, the availability and exchange of observations, the evaluation of the boundary conditions for the CWF models, the integration of numerical weather prediction and atmospheric chemical transport models, the data assimilation of the various chemical species, the understanding of several chemical and physical processes, the construction of model ensembles, and the scientific evaluation of the CWF models, including their evaluation against data.