On 4 September 2002, the Sicily Region issued a regional decree that established a high-risk area in the Milazzo–Valle del Mela district, which included the municipalities of Condrò, Gualtieri Sicaminò, Milaz-zo, Pace del Mela, San Filippo del Mela (Province of Messina), Santa Lucia del Mela and San Pier Niceto (Sicilian Region Department of Land and Environment, 2002).
Awaiting the start of the remediation plan, the Regional Special Office issued an important decree on September 2006 – “Remediation plan for air quality within the framework of the remediation plan of the high-risk area of the Mela District” – that lists the first set of actions to be taken (Sicilian Region Department of Land and Environment, 2006). The Regional Special Office also reported that the effectiveness of the intervention provided by the present measure will be verified a year after the start of operation of the inter-connected monitoring system and that the intervention will be revised based on the experience acquired.
Further administrative actions established by the Region followed. These actions aimed at introducing inter-ventions that prevent and self-regulate emissions. Also, these actions were to be taken by the Edipower plant and Milazzo refinery as soon as pre-alarm, alarm and emergency threshold limits were exceeded.
The high-risk Milazzo–Valle del Mela area is controlled by four monitoring systems that belong to four different bodies (see Table 46):
1. Messina Province: six stations for chemical parameters: San Filippo del Mela (Archi), Condrò, Santa Lucia del Mela, Port of Milazzo, Pace del Mela Mandravecchia and Pace del Mela Giammoro;
2. ARPA Sicily: three stations for meteorological parameters, including two stations for chemical param-eters: San Pietro di Milazzo Contrada Carrubbo and Zona Industriale Giammoro Contrada Gabbia;
3. Edipower: five stations for chemical parameters: Valdina Via Perre, San Pier Niceto, San Filippo del Mela, Pace del Mela and Milazzo Via Croce a Mare; and
4. Milazzo Mediterranea Refinery: two stations for chemical parameters.
Even if some data are missing, as is the case in the Gela area, the monitoring network allows an initial over-view of the environmental situation, indicating the main problems with which authorities should deal. So far, it is still difficult to understand if the air quality monitoring systems active in the area are interconnected.
Table 46. Monitoring system of air quality in the industrial area of Milazzo–Valle del Mela
Monitoring station Typea Measurement
CO C6H6 CH4 PM10/PM2.5 Pb SO2 O3 H2S Non-CH4 HCs NO NOx NO2 Meteorological
San Filippo del Mela (Archi) IU — X — — — X — X — X X X X
Condrò IR — — — — — X — — — — — — X
San Filippo del Mela IR X — — X — X X — — X X X X
Santa Lucia del Mela IR — — — — — X — — — X X X —
Port of Milazzo IU X — — X — X X — X X X X X
Milazzo via Croce a Mare IU X — — X — X X — — X X X —
Valdina Via Perre IU X — — X — X X — — X X X X
Pace del Mela
Giammoro IU — X — — — X — — — — — — —
Pace del Mela
Mandravecchia IR — — — — — X — — — X X X X
San Pietro di Milazzo
Contrada Carrubbo BS X X X X — — X — X X X X X
San Pier Niceto IU X — — X — X X — — X X X X
Zona Industriale Giammoro
Contrada Gabbia BS X X — X — X X — — X X X X
Mediterranea Refinery 1
and 2 IU — — — — — — — — X — — — —
Abbreviations: CO: carbon monoxide; C6H6: benzene; CH4: methane; PM10: particulate matter with an aerodynamic diameter smaller than 10 µm; Pb: lead; SO2: sulfur dioxide; O3: ozone; HS: hydrogen sulfide; Non-CH4 HCs: non-methane hydrocarbons; NO: nitrogen monoxide; NOx: nitrogen oxides; NO2: nitrogen dioxide; NA: not applicable�
a Type of monitoring station: IU: Industrial Urban, IR: Industrial Rural, IS: Industrial Suburban, SB: Background Suburban�
Note. X indicates the presence of a monitoring station and the long dash indicates its absence�
Source: Adapted from Sicilian Region Department of Land and Environment (2006)�
The Sicily Region Special Office reported that the available monitoring data do not allow a full descrip-tion of the contaminadescrip-tion levels for each pollutant in the high-risk Milazzo–Valle del Mela area. The data available do not allow either air quality characterization or exposure risk categorization for residents and ecosystems. Moreover, average concentrations of sulfur dioxide that exceeded acceptable limits coincided with high sulfur dioxide maximum hourly values – mostly in summer and when particular meteorologi-cal conditions caused air stagnation. Additional attention is needed to continuously survey other param-eters, such as ozone, nitrogen oxides, PM10, PM2.5, polycyclic aromatic hydrocarbons, benzene, volatile organic compounds and toxic metals (Triolo et al., 2008). From 2002, the total mass flows of pollutants show a general decline, but these pollutants still alter the normal environmental conditions and healthi-ness of the air in the high-risk area. The health risk to the population due to these pollutants and the risk to the ecosystems involved still remain.
In 2005, ARPA Sicily reported that the available air quality monitoring data do not allow a full description of the contamination levels for each pollutant (ARPA Sicily, 2005). The analysis of available information shows a relevant lack of measuring equipment, which makes the available data statistically irrelevant. In the last few years, air pollution monitoring has further deteriorated, because of equipment obsolescence and because the subsequent ordinances for further pollutants to be monitored was followed by no system adjustment.
In summary, some historical series are available for the high-risk Milazzo–Valle del Mela area, but they are useful only for two parameters: sulfur dioxide and particulate matter. Little is known, however, about the other pollutants included in the law in force.
In the closing remarks of the document entitled Air pollution campaign through mobile laboratory meas-urement in Milazzo Municipality, Acque Viole, 08/03/2009–03/07/2009, ARPA Sicily mentioned frequent hourly average concentration values for non-methane hydrocarbons, a consequence of the high values of the volatile organic compounds (ARPA Sicily, 2009a). Since these hourly average concentration values are highly abnormal and can be attributed to the activity of the Mediterranea Refinery, they represent a pollution sign that should be monitored, both for the olfactory nuisance that some of these non-methane hydrocarbons present and, most of all, for their adverse effects on health.
In the high-risk Milazzo–Valle del Mela area, collecting information and air quality data is difficult.
Therefore, it is not possible to make any recommendation.
Conclusions
Well-known oil and energy multinationals and their associated companies, plus a few large national industrial operators are the main industrial actors in the three Sicilian high-risk areas of Augusta–Priolo, Gela and Milazzo–Valle del Mela. Data collected for these areas suggest that type, number of plants and potential production taking place are likely to have a significant adverse effect on the surrounding en-vironment. Measurements performed by the air quality monitoring systems available have shown both critical aspects and exceeded national legislated limits for some of the pollutants (sulfur dioxide, PM10, nitrogen dioxide and ozone) (Parliament, 2002).
Although the legislation for air pollution caused by many substances has been in force since the 1980s, a great deal of data on these substances has never been collected. Still, in 2009, ARPA Sicily reported that the fragmentation of the jurisdiction over the monitoring system causes lack of homogeneity of data man-agement and transmission, making data unreadable and unusable (ARPA Sicily, 2009b). Also, although the law in force requests it (Parliament, 2010), further studies on air pollution are needed, particularly for the most critical pollutants or the ones that are not systematically monitored, such as PM2.5, polycyclic aromatic hydrocarbons, heavy metals and ozone precursors.
Moreover, it appears that the sampling and analysis of lead and other metals have never been systematically performed, and such data gaps do not allow comparisons with the national law in force (Parliament, 2002).
It is desirable that, in pursuance of recent Legislative Decree 155/10 (Parliament, 2010), the monitoring and analysis of such metals be assured. Monitoring the organic micropollutants polychlorinated dibenzo-p-di-oxins and dibenzofurans, dioxin-like polychlorinated biphenyls, and polycyclic aromatic hydrocarbons was already planned in the old land remediation plan for the Gela and Augusta–Priolo areas, but the data from monitoring campaigns are not available. Considering the critical aspects of the three areas, it is of primary importance to better monitor the environment by optimizing the existing monitoring system (ARPA, prov-inces, municipalities, regions) and by installing PM2.5 deposimeters and also monitors for heavy metals, polychlorinated dibenzo-p-dioxins and dibenzofurans, dioxin-like polychlorinated biphenyls, and poly-cyclic aromatic hydrocarbons. Particularly strong attention should be given to micropollutants, because organic and inorganic micropollutants accumulate in the environment, and this can adversely affect the population exposed, in terms of inhalation and ingestion (see Chapters 10 and 11).
8. socioEconoMic EnvironMEnT: THE indusTriAlizATion ModEl oF siciliAn HigH-risk PETrocHEMicAl ArEAs
Guido Signorino, Marina La Rocca and Elisa Gatto
Introduction
The aim of this chapter is to use the industrialization model to frame public health investigations of the three high-risk petrochemical areas of Sicily. The analysis proposed supports an evaluation of the socio-economic sustainability of the industrialization model.
The relationship between economic factors and health has been considered from a number of perspec-tives. Several epidemiological studies have analysed in depth the theoretical and empirical aspects of deprivation, particularly in relation to small areas (Jarman, 1983; Bithell et al., 1995; Costa, Spadea &
Cardano, 2004; Grisotto et al., 2007; Biggeri & Grisotto, 2009). In general, evidence shows that greater socioeconomic deprivation leads to worse health (Eibner & Evans, 2005; Subramanian & Kawachi, 2006).
Similarly, low levels of economic development (in terms of gross domestic product per person) and of public intervention, as well as a less equitable income distribution, all produce less favourable outcomes for poorer communities (Xu, 2006). Also, beyond (and independent of) the effects of individual charac-teristics, the socioeconomic features of an area affect personal health (Wen, Browning & Cagney, 2003).
On the other hand, in as much as health conditions affect people’s productivity and their ability to adapt technology (Ersado, Amacher & Alwang, 2004 – as far as agriculture is concerned), the health of local populations should be carefully considered when assessing development projects.
Relatively little attention has been given to analysing macroeconomic conditions that can affect human health through their joint effect on the environment and society. Only recently have attempts been made to view the importance of local economic development patterns and structural changes to the evolution of population health (La Rocca, 2010). Assuming this orientation, the present chapter argues that actual development paths for territorial units are often the result of policy options that determine the socioeco-nomic milieu of a territorial unit and its productive organization; the choice of such options also affects the environment and public health.
Framing a territory’s economic dynamics and assessing its development model help to deepen the analysis of the relationship between socioeconomic conditions and health. In this light, referring to the three high-risk petrochemical areas of Sicily, we propose:
• a dynamic analysis of the local productive organization that investigates, in particular, the evolution of the labour market (employment and migration) and that assesses the long-term socioeconomic sustainability of the petrochemical industrialization model; and
• a brief description of sustainability and of the data and methods used to conduct socioeconomic sustainability analysis.