Background One of the most air polluted areas in Romania is the Maramures County, in particular the town of Baia Mare, where the presence of two large non-ferrous smelting facilities (Phoenix and Romplumb), are subjecting the local population to toxic substances such as sulphur dioxide and lead powders. The risk of suffering from air quality related diseases is high in this area, which has been listed as one of twenty polluted "hot-spots" in the country by the Romanian authorities. Significantly, the death rate in Baia Mare is 15% higher than the average for Romanian cities. The geography of the Baia Mare area, located in an insulated depression, prevents the dispersion of the air pollutants. The micro-climate increases the risk of the accumulation of pollutants in certain zones, where an even higher concentration of pollutants may occur. Presently, there is no method of predicting when and where high pollution may appear, nor the possibility of warning the population or the polluters. Objectives The aim of the AIRforALL project was to develop and implement a pilot system able to forecast air quality on a 24 to 48 hours basis in an air polluted "hot-spot" and ultimately warn both the local administration and polluters about the forecasted impact. It would untimately discourage polluters to maintain emissions regardless of the atmospheric conditions, and raise public awareness about the polluter impact. Specific objectives included: - To point out potential threats to urban and other air quality sensitive areas 24 to 48 hours in advance; - To develop a GIS-hosted air quality database able to process air quality forecasts on a geographical basis; - To promote co-operation between the atmospheric forecasting authority, the central and local authorities and the polluters in order to avoid dangerous air quality situations; - To monitor ground gas leaks near polluter sites, using a mobile crisis cell auto laboratory. Results The main result of the AIRforALL project is an operational pollution forecast system for remote processing of the local meteorological data and air pollution information. The system is able to make a forecast of the ambient air quality 24 hours in advance. The warning system enables the polluters to take the necessary measures to decrease intensity in certain phases of the technological process, and therefore prevent a higher level of pollution to occur in the next 24 hours. The outputs of the pollution forecast system demonstrated high accuracy at the close of the project. One of the main conditions for the project's success was the good partnership and communication between the partners, that was “tested” in another LIFE project, Assure (LIFE ENV 99/RO/6746). The use of the pollution forecast system has encouraged further cooperation between the institutions in charge of environmental protection and other technical institutions, with a view to providing the polluters with a sound scientific basis for steering their technologies to minimise the risk of pollution. The project has reduced the environmental risks in two ways: by reduction of the emissions during adverse meteo conditions and by alarming the population on the acute pollution episodes. For the first time, ambient air pollution has been predicted in connection with the weather forecast, for such a long period of time (48 hrs). The use of the OpenGIS platform and powerful state-of-the-art models has contributed to this achievement. The proposed system integrates the following components: meteorological high resolution forecast system, local and long distance pollutant dispersion forecast systems, national and local air monitoring systems. The overall forecast results are useful for the development of industry plans, zoning policies, strategic planning in case of accidental pollution. At the European level, the outcomes of the project will be useful for the implementation of the IPPC Directive and for the public participation policies (Aarhus Convention). The project was to be continued after the end of LIFE funding, in that the local Environmental Protection Agency was to continue transmitting the records to the National Administration of Meteorology (beneficiary) to run the forecast models. The outputs of these models were to continue creating a basis for the prevention of pollution dangerous episodes with a high impact on public health at the local (Baia Mare City) and regional level (Maramures County). Long term monitoring indicators of the success of this project would be the number of pollution warnings followed by an actual technology response and the extension of the system to other polluted areas. This project has been selected as one of the 21 "Best" LIFE Environment projects in 2005-2006