Minimizing external indirect health costs due to aerosol population exposure: a case study from Northern Italy

Environmental Agencies require Decision Support Systems, in order to plan Air Quality Policies considering the cost of emission reduction measures and the human health effects (with related social costs). The use of Decision Support Systems is also useful to spread information to general public, explaining the effectiveness of proposed air quality plans. In this paper, a multi-objective approach to control PM10 concentration at a regional level is presented. The problem considers both the internal costs (due to the implementation of emission reduction measures) and the external costs (due to population exposure to high PM10 concentrations). To model PM10 concentrations, a single surrogate model is used for the entire domain, allowing the implementation of a very efficient optimization procedure. The surrogate model is derived through a set of 10 simulations, performed using a Chemistry Transport Model fed with different emission reduction scenarios. The methodology is applied to Northern Italy, a region affected by very high PM10 concentrations that exceed the limit values specified by the EU legislation.     

Modelling assessment of PM10 exposure control policies in Northern Italy

To assess the impact of three different emission reduction scenarios on PM10 concentrations in Northern Italy, the TCAM multiphase model has been applied in the framework of the CityDelta III-CAFE EU project. The considered domain, that is characterized by high urban and industrial emissions and a dense road traffic, due to frequently stagnating meteorological conditions is often affected by severe PM10 levels, far from the European standard regulations. The impact evaluation has been performed in terms of both yearly mean values and 50 g/m³ exceedance days for the 2004 Base Case simulation. The results show that the three selected emission reduction scenarios up to 2020 improve air quality all over the domain, in particular, in the area with higher emission density.     

A decision support system for air quality network design

In the last few years, due to the implementation of European and Italian laws, public agencies are in urgent need of objective criteria and methodologies for the correct location of air quality monitoring networks. This paper describes MoNet, a decision support system oriented to network designers, to help them in the choice of the number and the location of instruments in an assigned area. The package includes a model base consisting of a set of pollution diffusion simulation models and two optimization algorithms for network location and allows the user to integrate his or her own subjective knowledge of the problem with the results of the simulations performed by means of objective techniques. The package has been applied to revise the air quality network located in an industrial and urban area of Northern Italy. The results of the simulations performed by using different diffusion models, location algorithms and problem constraints are shown and discussed in the concluding section.     

Atmospheric deposition may affect northern hardwood forest composition by altering soil nutrient supply.

In the northeastern United States, the input of reactive nitrogen (N) via atmospheric deposition has increased rapidly since the onset of the industrial revolution. During the same period of time, acid precipitation and forest harvest have removed substantial quantities of base cations from soil. Because of the dominance of base-poor soils and the low rates of atmospheric base cation deposition, soils throughout the northeastern United States may be increasingly rich in N but poor in calcium (Ca). We studied the consequences of a change in soil N and Ca availability on forest composition by transplanting seedlings of four tree species into replicate plots in the understory and in canopy gaps amended with N and Ca in factorial combination. In this paper, we report on the growth and survivorship of seedlings over a four-year period. Relative to control plots, fertilization with N increased red maple growth by an average of 39% whereas fertilization with Ca decreased survivorship in the understory by 41%. In sugar maple, fertilization with Ca increased growth by 232% and 46% in the forest understory and in canopy gaps, respectively, and significantly increased high light survivorship. Fertilization with N decreased white pine survivorship by 69% in the understory whereas high Ca availability significantly increased survivorship. Fertilization with N or Ca alone reduced red oak growth but had no effect on survivorship. The results of this study suggest that historical losses of soil Ca and the continuing effects of atmospheric-N deposition on N availability are likely to alter the composition of northeastern North American forests because of the positive effects of N enrichment on the growth of red maple and the negative effects of Ca loss on the growth and survivorship of sugar maple and white pine.     

PM10 Chemical Model Simulations Over Northern Italy in the Framework of the CityDelta Exercise

Within the framework of CityDelta open model inter-comparison exercise, two different atmospheric chemical transport models, comprehensive air quality model with extension and transport chemical aerosol model, have been applied over a domain centred on Milan (North of Italy) as a result of a cooperation of five Italian groups. The two models have shared the same input fields for yearly PM10 simulations. The paper illustrates the analysis of the particulate matter-simulated concentrations and the comparison with the available experimental data.     

Evaluation by TCAM Model of Physical–Chemical Properties of Aerosol in Northern Italy

The chemical and size characterisation of aerosol in northern Italy was investigated by means of transport chemical aerosol model (TCAM) multiphase model long-term simulations performed within the frame of the CityDelta-CAFE exercise. The results show a high contribution of secondary inorganic compounds, in particular far from the Milan metropolitan area and in the large rural area of the Po valley where the major chemical fractions are ammonium and nitrates. The sulphate contribution is quite similar throughout this region, with the exception of areas close to SOx point emissions. Primary PM and organic compounds fractions, on the other hand, are greater close to major urban areas, in particular the Milan metropolitan zone. This work also presents a seasonal characterisation analysis of physical and chemical aerosol features. The results show that in winter, due to domestic heating emission of NOx and low temperatures, which favour the formation of secondary nitrate and organic aerosol, the PM10 and PM2.5 concentrations are higher than those in summer, in agreement with experimental data presented in several studies focussing on the same region.     

Increasing plant use of organic nitrogen with elevation is reflected in nitrogen uptake rates and ecosystem delta15N

It is hypothesized that decreasing mean annual temperature and rates of nitrogen (N) cycling causes plants to switch from inorganic to organic forms of N as the primary mode of N nutrition. To test this hypothesis, we conducted field experiments and collected natural-abundance delta15N signatures of foliage, soils, and ectomycorrhizal sporocarps along a steep elevation-climate gradient in the White Mountains, New Hampshire, USA. Here we show that with increasing elevation organic forms of N became the dominant source of N taken up by hardwood and coniferous tree species based on dual-labeled glycine uptake analysis, an important confirmation of an emerging theory for the biogeochemistry of the N cycle. Variation in natural abundance foliar delta15N with elevation was also consistent with increasing organic N uptake, though a simple, mass balance model demonstrated that the uptake of delta15N depleted inorganic N, rather than fractionation upon transfer of N from mycorrhizal fungi, best explains variations in foliar delta15N with elevation.     

An integrated air quality forecast system for a metropolitan area

Air quality forecasting is an important issue in environmental research, due to the effects that air pollutants have on population health. To deal with this topic, in this work an integrated modelling system has been developed to forecast daily maximum eight hours ozone concentrations and daily mean PM10 concentrations, up to two days in advance, over an urban area. The presented approach involves two steps. In the first step, artificial neural networks are identified and applied to get point-wise forecasting. In the second step, the forecasts obtained at the monitoring station locations are spatially interpolated all over the domain using the cokriging technique, which allows to improve the spatial interpolation in the absence of densely sampled data. The integrated modelling system has been then applied to a case study over Northern Italy, performing a validation over space and time for the year 2004 and analyzing if the limit values for the protection of human health set by the European Commission are respected. The presented approach represents a fast and reliable way to provide decision makers and the general public with air quality forecasting, and to support prevention and precautionary measures.     

Substrate supply, fine roots, and temperature control proteolytic enzyme activity in temperate forest soils

Temperature and substrate availability constrain the activity of the extracellular enzymes that decompose and release nutrients from soil organic matter (SOM). Proteolytic enzymes are the primary class of enzymes involved in the depolymerization of nitrogen (N) from proteinaceous components of SOM, and their activity affects the rate of N cycling in forest soils. The objectives of this study were to determine whether and how temperature and substrate availability affect the activity of proteolytic enzymes in temperate forest soils, and whether the activity of proteolytic enzymes and other enzymes involved in the acquisition of N (i.e., chitinolytic and ligninolytic enzymes) differs between trees species that form associations with either ectomycorrhizal or arbuscular mycorrhizal fungi. Temperature limitation of proteolytic enzyme activity was observed only early in the growing season when soil temperatures in the field were near 4 degrees C. Substrate limitation to proteolytic activity persisted well into the growing season. Ligninolytic enzyme activity was higher in soils dominated by ectomycorrhizal associated tree species. In contrast, the activity of proteolytic and chitinolytic enzymes did not differ, but there were differences between mycorrhizal association in the control of roots on enzyme activity. Roots of ectomycorrhizal species but not those of arbuscular mycorrhizal species exerted significant control over proteolytic, chitinolytic, and ligninolytic enzyme activity; the absence of ectomycorrhizal fine roots reduced the activity of all three enzymes. These results suggest that climate warming in the absence of increases in substrate availability may have a modest effect on soil-N cycling, and that global changes that alter belowground carbon allocation by trees are likely to have a larger effect on nitrogen cycling in stands dominated by ectomycorrhizal fungi.