Found 9759 publications. Showing page 193 of 391:
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This report presents the database for the second phase of the ECE ICP material programme. Besides presenting the available data for the three exposure years 1995/96, 1996/97 and 1997/98, the report presents the spread in the yearly mean values for the exposure sites. To show the reductions in the air pollutions observed during the ruling time of the project, scatterplots for SO2, NO2 and O3 for the two years 1987/88 and 1997/98 are presented. They show that the reduction for SO2 at the sites during the ten years period has been 75% in average, NO2 the reduction has been 25% and for O3 no detectable change has been observed.
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This report presents the ICP Materials database for the period October 2008-December 2009. It includes environmental data from the ICP Materials trend exposure programme for 2008 - 2009. The database consists of meteorological data, and pollution data as gasses and in precipitation. Also reported are HNO3 and amount and composition in particle deposition in soiling.
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Interpolation and assimilation methods for European scale air quality assessment and mapping. Part 1: Review and recommendations. Final draft. ETC/ACC Technical Paper, 2005/7
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Interpolation and assimilation methods for European scale air quality assessment and mapping. Part II: Development and testing new methodologies. Final draft. ETC/ACC Technical Paper, 2005/8
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Fine-resolution spatio-temporal maps of near-surface urban air temperature (Ta) provide crucial data inputs for sustainable urban decision-making, personal heat exposure, and climate-relevant epidemiological studies. The recent availability of IoT weather station data allows for high-resolution urban Ta mapping using approaches such as interpolation techniques or machine learning (ML). This study is aimed at executing these approaches and traditional numerical modeling within a practical and operational framework and evaluate their practicality and efficiency in cases where data availability, computational constraints, or specialized expertise pose challenges. We employ Netatmo crowd-sourced weather station data and three geospatial mapping approaches: (1) Ordinary Kriging, (2) statistical ML model (using predictors primarily derived from Earth Observation Data), and (3) weather research and forecasting model (WRF) to predict/map daily Ta at nearly 1-km spatial resolution in Warsaw (Poland) for June–September and compare the predictions against observations from 5 meteorological reference stations. The results reveal that ML can serve as a viable alternative approach to traditional kriging and numerical simulation, characterized by reduced complexity and higher computational speeds within the domain of urban meteorological studies (overall RMSE = 1.06 °C and R2 = 0.94, compared to ground-based meteorological stations). The results have implications for identifying the urban regions vulnerable to overheating and evidence-based urban management in response to climate change. Due to the open-sourced nature of the applied predictors and input parsimony, the ML method can be easily replicated for other EU cities.
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