International Journal of Environmental Research and Public Health
Spatio-temporal Bayesian disease mapping is the branch of spatial epidemiology interested in prov... more Spatio-temporal Bayesian disease mapping is the branch of spatial epidemiology interested in providing valuable risk estimates in certain geographical regions using administrative areas as statistical units. The aim of the present paper is to describe spatio-temporal distribution of cardiovascular mortality in the Province of Pavia in 2010 through 2015 and assess its association with environmental pollution exposure. To produce reliable risk estimates, eight different models (hierarchical log-linear model) have been assessed: temporal parametric trend components were included together with some random effects that allowed the accounting of spatial structure of the region. The Bayesian approach allowed the borrowing information effect, including simpler model results in the more complex setting. To compare these models, Watanabe–Akaike Information Criteria (WAIC) and Leave One Out Information Criteria (LOOIC) were applied. In the modelling phase, the relationship between the disease ...
When adopting regional plans aimed at improving air quality, environmental authorities are often ... more When adopting regional plans aimed at improving air quality, environmental authorities are often confronted with the relevant costs that the adoption of abatement measures implies. On the other hand, scientific literature has well documented damages due to air pollution impact on human and ecosystem health. The paper proposes a tool that allows balancing these two viewpoints and thus allows defining the efficient set of measures in a multi-objective perspective. Despite both external and internal costs/damages can be measured in the same unit, namely money, it appears unacceptable to add them together as in a classical cost-benefit analysis, since they pertain to quite different social groups. The tool can thus be seen as a support to actual decision makers and allows them to compare in a ponderable way the pros and cons of any abatement policy. This contrasts what normally happens when air quality health impacts are simply defined as the satisfaction of a constraint at few specific...
ABSTRACT Air quality models which are nowadays used for a wide range of scopes (i.e. assessment, ... more ABSTRACT Air quality models which are nowadays used for a wide range of scopes (i.e. assessment, forecast, planning) see their intrinsic complexity progressively increasing as better knowledge of the atmospheric chemistry processes is gained. As a result of this increased complexity potential non-linearities are implicitly and/or explicitly incorporated in the system. These non-linearities represent a key and challenging aspect of air quality modeling, especially to assess the robustness of the model responses. In this work the importance of non-linear effects in air quality modeling is quantified, especially as a function of time averaging. A methodology is proposed to decompose the concentration change resulting from an emission reduction over a given domain into its linear and non-linear contributions for each precursor as well as in the contribution resulting from the interactions among precursors. Simulations with the LOTOS-EUROS model have been performed by TNO over three regional geographical areas in Europe for this analysis. In all three regions the non-linear effects for PM10 and PM2.5 are shown to be relatively minor for yearly and monthly averages whereas they become significant for daily average values. For Ozone non-linearities become important already for monthly averages in some regions. An approach which explicitly deals with monthly variations seems therefore more appropriate for O3. In general non-linearities are more important at locations where concentrations are the lowest, i.e. at urban locations for O3 and at rural locations for PM10 and PM2.5. Finally the impact of spatial resolution (tested by comparing coarse and fine resolution simulations) on the degree of non-linearity has been shown to be minor as well. The conclusions developed here are model dependent and runs should be repeated with the particular model of interest but the proposed methodology allows with a limited number of runs to identify where efforts should be focused in order to include the relevant terms into a simplified surrogate model for integrated assessment purposes.
In this paper we present a Sysquake interactive software tool for the loopshaping design of fract... more In this paper we present a Sysquake interactive software tool for the loopshaping design of fractional-order PID controllers. In particular, the tool allows to determine automatically the controller parameters by mapping a point of the process Nyquist plot to a point of the loop transfer function Nyquist plot. In this context, constraints on the gain or phase margin or on the maximum sensitivity can be effectively considered. Then, the effects of changing user-chosen parameters can be interactively verified both in the time and frequency domain. It is believed that this kind of Computer Aided Control System Design tools are very useful from an educational viewpoint and in allowing a widespread use of fractional PID controllers in industry.
Proceedings of the 17th IFAC World Congress, 2008, 2008
Atmospheric Particulate Matter (PM10) control is at the moment a great challenge for air quality ... more Atmospheric Particulate Matter (PM10) control is at the moment a great challenge for air quality management, due to the strong non linearities that affect formation and accumulation of this pollutant. This work presents the formalization and application of a twoobjective methodology to select effective particulate matter control strategies on a mesoscale domain. The two considered objectives are emission reduction costs and the PM10 exposure index. The decision variables are the precursor emission reductions due to ablation technologies. The nonlinear relationships linking air quality objective and precursor emissions are described by neuro-fuzzy models, identified through the processing of simulations of the TCAM deterministic multiphase modeling system, performed in the framework of the CityDelta-CAFE Project (EU 6th Framework Program). The two-objective problem has been applied to a complex domain in Northern Italy, including the Milan metropolitan area, a region characterized by high emissions and frequent and persistent secondary pollution episodes.
International Journal of Environmental Research and Public Health
Spatio-temporal Bayesian disease mapping is the branch of spatial epidemiology interested in prov... more Spatio-temporal Bayesian disease mapping is the branch of spatial epidemiology interested in providing valuable risk estimates in certain geographical regions using administrative areas as statistical units. The aim of the present paper is to describe spatio-temporal distribution of cardiovascular mortality in the Province of Pavia in 2010 through 2015 and assess its association with environmental pollution exposure. To produce reliable risk estimates, eight different models (hierarchical log-linear model) have been assessed: temporal parametric trend components were included together with some random effects that allowed the accounting of spatial structure of the region. The Bayesian approach allowed the borrowing information effect, including simpler model results in the more complex setting. To compare these models, Watanabe–Akaike Information Criteria (WAIC) and Leave One Out Information Criteria (LOOIC) were applied. In the modelling phase, the relationship between the disease ...
When adopting regional plans aimed at improving air quality, environmental authorities are often ... more When adopting regional plans aimed at improving air quality, environmental authorities are often confronted with the relevant costs that the adoption of abatement measures implies. On the other hand, scientific literature has well documented damages due to air pollution impact on human and ecosystem health. The paper proposes a tool that allows balancing these two viewpoints and thus allows defining the efficient set of measures in a multi-objective perspective. Despite both external and internal costs/damages can be measured in the same unit, namely money, it appears unacceptable to add them together as in a classical cost-benefit analysis, since they pertain to quite different social groups. The tool can thus be seen as a support to actual decision makers and allows them to compare in a ponderable way the pros and cons of any abatement policy. This contrasts what normally happens when air quality health impacts are simply defined as the satisfaction of a constraint at few specific...
ABSTRACT Air quality models which are nowadays used for a wide range of scopes (i.e. assessment, ... more ABSTRACT Air quality models which are nowadays used for a wide range of scopes (i.e. assessment, forecast, planning) see their intrinsic complexity progressively increasing as better knowledge of the atmospheric chemistry processes is gained. As a result of this increased complexity potential non-linearities are implicitly and/or explicitly incorporated in the system. These non-linearities represent a key and challenging aspect of air quality modeling, especially to assess the robustness of the model responses. In this work the importance of non-linear effects in air quality modeling is quantified, especially as a function of time averaging. A methodology is proposed to decompose the concentration change resulting from an emission reduction over a given domain into its linear and non-linear contributions for each precursor as well as in the contribution resulting from the interactions among precursors. Simulations with the LOTOS-EUROS model have been performed by TNO over three regional geographical areas in Europe for this analysis. In all three regions the non-linear effects for PM10 and PM2.5 are shown to be relatively minor for yearly and monthly averages whereas they become significant for daily average values. For Ozone non-linearities become important already for monthly averages in some regions. An approach which explicitly deals with monthly variations seems therefore more appropriate for O3. In general non-linearities are more important at locations where concentrations are the lowest, i.e. at urban locations for O3 and at rural locations for PM10 and PM2.5. Finally the impact of spatial resolution (tested by comparing coarse and fine resolution simulations) on the degree of non-linearity has been shown to be minor as well. The conclusions developed here are model dependent and runs should be repeated with the particular model of interest but the proposed methodology allows with a limited number of runs to identify where efforts should be focused in order to include the relevant terms into a simplified surrogate model for integrated assessment purposes.
In this paper we present a Sysquake interactive software tool for the loopshaping design of fract... more In this paper we present a Sysquake interactive software tool for the loopshaping design of fractional-order PID controllers. In particular, the tool allows to determine automatically the controller parameters by mapping a point of the process Nyquist plot to a point of the loop transfer function Nyquist plot. In this context, constraints on the gain or phase margin or on the maximum sensitivity can be effectively considered. Then, the effects of changing user-chosen parameters can be interactively verified both in the time and frequency domain. It is believed that this kind of Computer Aided Control System Design tools are very useful from an educational viewpoint and in allowing a widespread use of fractional PID controllers in industry.
Proceedings of the 17th IFAC World Congress, 2008, 2008
Atmospheric Particulate Matter (PM10) control is at the moment a great challenge for air quality ... more Atmospheric Particulate Matter (PM10) control is at the moment a great challenge for air quality management, due to the strong non linearities that affect formation and accumulation of this pollutant. This work presents the formalization and application of a twoobjective methodology to select effective particulate matter control strategies on a mesoscale domain. The two considered objectives are emission reduction costs and the PM10 exposure index. The decision variables are the precursor emission reductions due to ablation technologies. The nonlinear relationships linking air quality objective and precursor emissions are described by neuro-fuzzy models, identified through the processing of simulations of the TCAM deterministic multiphase modeling system, performed in the framework of the CityDelta-CAFE Project (EU 6th Framework Program). The two-objective problem has been applied to a complex domain in Northern Italy, including the Milan metropolitan area, a region characterized by high emissions and frequent and persistent secondary pollution episodes.
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Papers by enrico pisoni