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This paper presents the application of TCAM model to assess secondary pollution control policies. The work focuses on two emission scenarios: the current legislation one, related to the emission reduction established by the EU Directives, and the MFR one, referring to the emission reduction caused by the use of the most efficient available reduction technology for each emission sector. The results show that the impact of both scenarios on ozone mean concentration is limited, even as for AOT40, the reduction reaches the 50% with respect to the base case. The impact on PM10 is more significant, also in terms of mean and exceedance days. Therefore, the impact of both emission control strategies does not meet PM10 EU 2010 standards over the whole domain. [ABSTRACT FROM AUTHOR]

Regional authorities need suitable tools to develop air quality plans, in particular when dealing with secondary pollutants, such as ozone, characterized by complex and non-linear dynamics. This work presents a two objective problem considering both effectiveness and costs of alternative environmental policies. To solve the multiobjective problem, an integrated modeling system has been designed and implemented. It includes (1) pollutant-precursor models identified by processing the simulations of the GAMES modeling system, and (2) cost functions computing emission reduction costs. The methodology has been applied to a complex domain in Northern Italy, including Milan metropolitan area, a region characterized by high ozone levels in the summer season. [ABSTRACT FROM AUTHOR]

Road traffic is widely recognised to be a significant and increasing source of photochemical pollution precursors. EU Directives in force up to 2010 require substantial NOx and VOC emission decreases. Such reductions can improve or further deteriorate air quality because of the emission mix and the photochemical regime characterizing the area under study. [ABSTRACT FROM AUTHOR]

In this paper, the problem of forecasting tropospheric ozone concentration is approached by means of nonlinear black-box modeling techniques. In particular Neuro-Fuzzy, Auto Regressive Ciclostationary and Nonlinear Set Membership models are identified and tested in the one day ahead forecast of daily maximum ozone concentration in Brescia, a highly populated and industrialized area in the Po Valley (Northern Italy). The model performances are assessed by means of indexes and statistical indicators suggested by the European Environment Agency. [ABSTRACT FROM AUTHOR]