END noise mapping for a sufficiently accurate people exposure estimation in epidemiological studies

The information required to perform an accurate exposure estimation are several, such as: geographical and topographical indications, population distribution, source properties. Years of research have improved and validated different numerical methods, which provide accurate results in controlled conditions, i.e. when all of the above-described information are available. Since the computational speed is increasing by means of parallel systems, it will be possible to develop new more accurate methods. They will be theoretically able to manage more inputs, obtaining more thorough analysis. Actually, it is not unlikely that some of the data required are missing or their accuracy is not suited. This leads to approximations, increasing accordingly the level of uncertainties in the exposure evaluation. Epidemiologists are accustomed to adapt their studies to the amount of available data, nonetheless their results depend onto which extent the exposure evaluation is accurate. In the paper limits and advantages of noise mapping due to END will be discussed in the perspective of the epidemiological studies and their needs and compared also to other approaches used in specific epidemiological studies. It will be also presented the new annex II of END, the work developed in CNOSSOS-EU, as well as some ideas for possible future improvements.