GNGTS 2023 - Atti del 41° Convegno Nazionale

Session 2.2 GNGTS 2023 Town Compartments (TCs), characterised by the homogeneity of the building stock in terms of construction age and construction techniques and/or structural types. Although the TCs identified by CARTIS for Portici are not entirely consistent with the OMI zones, CARTIS information can be first associated with census tracts (e.g., based on the geographic identification of the TC) and then, in turn, with OMI zones. We adopt the consequence model proposed by Dolce et al. (2021) to estimate economic losses; this model associates a loss ratio (i.e., repair to replacement costs) based on the damage grade attained by buildings, regardless of the construction material or the building class. A probabilistic seismic risk assessment is performed as in Dolce et al. (2021), and the expected annual economic losses (EAL) are calculated per square meter. The latter result is quite high for all OMI areas, with a value greater than 0.20 EAL/ m 2 everywhere. The area with the highest value is B5 (0.73 EAL/ m 2 ), followed by the C4 zone (0.40 EAL/ m 2 ) and the C6 zone (0.40 EAL/ m 2 ); for all these areas, the SoVI is very high as well (Figure 2). We repeat our assessment twice with some modelling modifications to evaluate the effectiveness of reducing EAL/m 2 through some disaster risk reduction strategies and related policies, i.e., building retrofit (a hard policy) and post-disaster assistance through insurance coverage (a soft policy). In the first re-assessment (herein denoted as “hard policy”), we consider that the most vulnerable masonry buildings are retrofitted through the insertion of tie rods or the stiffening of slabs. Similarly, we assume that the most vulnerable RC structures are strengthened using fibre-reinforced polymers or steel/RC jacketing of columns to increase the structural capacities and ductilities. To reflect this policy in the calculations, masonry buildings classified in the most vulnerable class are re-assigned to the next most vulnerable class. For RC buildings, the medians of the corresponding fragility curves adopted are increased between 15% and 50%, depending on the damage grade, to reflect improved seismic performance (e.g., Aljawhari et al., 2022). In the second re-assessment (herein denoted as “soft policy”), we assume that insurance coverage will cover all minor damages to buildings, such that the corresponding EAL is calculated without considering these losses. Figure 3 compares the EAL/m 2 values obtained for all scenarios considered (i.e., original - no policies, hard policy and soft policy) across three defined income groups. The proportion of people in different income levels is obtained from OMI zone market values. High-income zones are designated as those where the minimum market value is greater than 1,900 euro per square meter (euro/ m 2 ), middle-income zones are designated as those where the market value lies between 1,650 euro/m 2 and 1,900 euro/ m 2 , and low-income zones are those where the market value is lower than 1,650 euro/ m 2 . EAL/m 2 is consistently highest for the most vulnerable population class (i.e., low-income). The reduction in EAL/m 2 from adopting the hard policy is highest for all three income classes (approximately 70% on average) and is particularly notable for those of the lowest income. The different income classes benefit to a lesser extent from adopting the proposed soft policy, which again leads to the largest reduction in EAL/ m 2 for the low-income class (of 35%). The difference in the effectiveness of the policies is because hard policies directly affect buildings’ physical vulnerability and all resulting losses. In contrast, the considered soft policy only covers losses associated with minor damage.