Neural network forecast of daily pollution concentration using optimal meteorological data at synoptic and local scales

Agirre-Basurko, 2006, Regression and multilayer perceptron-based models to forecast hourly O3 and NO2 levels in the Bilbao area, Environmental Modelling & Software, 21, 430, 10.1016/j.envsoft.2004.07.008 Almeida, 2013, Impact of Maritime Air Mass Trajectories on the Western European Coast Urban Aerosol, Journal of Toxicology and Environmental Health, Part A, 76, 252, 10.1080/15287394.2013.757201 APA (Agencia Portuguesa do Ambiente), 2008. Evolution of the Portuguese Air Quality between the Years 2001 and 2005, 100 pages Arasa, 2010, A performance evaluation of MM5/MNEQA/CMAQ air quality modelling system to forecast ozone concentrations in Catalonia, Tethys, 7, 11 Chaloulakou, 2003, Neural network and multiple regression models for PM10 prediction in Athens: A comparative assessment, Journal of the Air & Waste Management Association, 53, 1183, 10.1080/10473289.2003.10466276 Cobourn, 2000, A comparison of nonlinear regression and neural network models for ground-level ozone forecasting, Journal of the Air & Waste Management Association, 50, 1999, 10.1080/10473289.2000.10464228 Comrie, 1997, Comparing neural networks and regression models for ozone forecasting, Journal of the Air & Waste Management Association, 47, 653, 10.1080/10473289.1997.10463925 Dayan, 2005, The influence of meteorological conditions and atmospheric circulation types on PM10 and visibility in Tel Aviv, Journal of Applied Meteorology, 44, 606, 10.1175/JAM2232.1 Dayan, 2002, Relationship between synoptic-scale atmospheric circulation and ozone concentrations over Israel, Journal of Geophysical Research–Atmospheres, 107, 10.1029/2002JD002147 Dee, 2011, The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Quarterly Journal of the Royal Meteorological Society, 137, 553, 10.1002/qj.828 Demuzere, 2012, The impact of weather and atmospheric circulation on O3 and PM10 levels at a rural mid-latitude site, Atmospheric Chemistry and Physics, 9, 2695, 10.5194/acp-9-2695-2009 Dias, 2012, Particulate matter and health risk under a changing climate: Assessment for Portugal Diaz, 2004, Relationship between environmental factors and infant mortality in Madrid, Journal of Occupational and Environmental Medicine, 6, 768 Du, 2013, Urban boundary layer height characteristics and relationship with particulate matter mass concentrations in Xi’an, Central China, Aerosol and Air Quality Research, 13, 1598, 10.4209/aaqr.2012.10.0274 Dutot, 2007, A 24–h forecast of ozone peaks and exceedance levels using neural classifiers and weather predictions, Environmental Modelling & Software, 22, 1261, 10.1016/j.envsoft.2006.08.002 ECMWF (European Centre for Medium – Range Weather Forecasts), 2013. http://apps.ecmwf.int/datasets/, accessed in 2013. EEA (European Environment Agency), 2013. Every Breath We Take: Improving Air Quality in Europe, EEA Signals 2013 Report, Copenhagen. EEA (European Environment Agency), 2011. Air Quality in Europe — 2011 Report, EEA Technical Report, No 12/2011. Elangasinghe, 2014, Development of an ANN–based air pollution forecasting system with explicit knowledge through sensitivity analysis, Atmospheric Pollution Research, 5, 696, 10.5094/APR.2014.079 Garcia–Herrera, 2007, The outstanding 2004/05 drought in the Iberian Peninsula: Associated atmospheric circulation, Journal of Hydrometeorology, 8, 483, 10.1175/JHM578.1 Gardner, 2000, Meteorologically adjusted trends in UK daily maximum surface ozone concentrations, Atmospheric Environment, 34, 171, 10.1016/S1352-2310(99)00315-5 Gardner, 2000, Statistical surface ozone models: An improved methodology to account for non–linear behaviour, Atmospheric Environment, 34, 21, 10.1016/S1352-2310(99)00359-3 Gardner, 1998, Artificial neural networks (the multilayer perceptron) – A review of applications in the atmospheric sciences, Atmospheric Environment, 32, 2627, 10.1016/S1352-2310(97)00447-0 Haykin, 1999 Hooyberghs, 2005, A neural network forecast for daily average PM10 concentrations in Belgium, Atmospheric Environment, 39, 3279, 10.1016/j.atmosenv.2005.01.050 Jolliffe, 1999 Kolehmainen, 2001, Neural networks and periodic components used in air quality forecasting, Atmospheric Environment, 35, 815, 10.1016/S1352-2310(00)00385-X Kukkonen, 2003, Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki, Atmospheric Environment, 37, 4539, 10.1016/S1352-2310(03)00583-1 Lal, 2012, Prediction of dust concentration in open cast coal mine using artificial neural network, Atmospheric Pollution Research, 3, 211, 10.5094/APR.2012.023 Luecken, 2006, Development and analysis of air quality modeling simulations for hazardous air pollutants, Atmospheric Environment, 40, 5087, 10.1016/j.atmosenv.2005.12.044 Middleton, 1998, A new box model to forecast urban air quality: BOXURB, Environmental Monitoring and Assessment, 52, 315, 10.1023/A:1005817202196 Monteiro, 2005, Long–term simulations of photo oxidant pollution over Portugal using the CHIMERE model, Atmospheric Environment, 39, 3089, 10.1016/j.atmosenv.2005.01.045 Nejadkoorki, 2012, Forecasting extreme PM10 concentrations using artificial neural networks, International Journal of Environmental Research, 6, 277 Papanastasiou, 2007, Development and assessment of neural network and multiple regression models in order to predict PM10 levels in a medium–sized Mediterranean city, Water Air and Soil Pollution, 182, 325, 10.1007/s11270-007-9341-0 Perez, 2006, An integrated neural network model for PM10 forecasting, Atmospheric Environment, 40, 2845, 10.1016/j.atmosenv.2006.01.010 Russo, 2014, NO2, PM10 and O3 urban concentrations and its association with circulation weather types in Portugal, Atmospheric Environment, 89, 768, 10.1016/j.atmosenv.2014.02.010 Russo, 2013, Air quality prediction using optimal neural networks with stochastic variables, Atmospheric Environment, 79, 822, 10.1016/j.atmosenv.2013.07.072 Saavedra, 2012, Synoptic patterns and air mass transport during ozone episodes in Northwestern Iberia, Science of the Total Environment, 441, 97, 10.1016/j.scitotenv.2012.09.014 Shi, 1997, Regression modelling of hourly NOx and NO2 concentrations in urban air in London, Atmospheric Environment, 31, 4081, 10.1016/S1352-2310(97)00282-3 Stedman, 2002 Trigo, 2000, Circulation weather types and their influence on the precipitation regime in Portugal, International Journal of Climatology, 20, 1559, 10.1002/1097-0088(20001115)20:13<1559::AID-JOC555>3.0.CO;2-5 Trigo, 1999, Simulation of daily temperatures for climate change scenarios over Portugal: A neural network model approach, Climate Research, 13, 45, 10.3354/cr013045 Trigo, 2006, Atmospheric conditions associated with the exceptional fire season of 2003 in Portugal, International Journal of Climatology, 26, 1741, 10.1002/joc.1333 Weisberg, 1985 Wilks, 1985 Wong, 2002, A tale of two cities: Effects of air pollution on hospital admissions in Hong Kong and London compared, Environmental Health Perspectives, 110, 67, 10.1289/ehp.0211067 Yi, 1996, A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area, Environmental Pollution, 92, 349, 10.1016/0269-7491(95)00078-X