br A further limitation is the lung
A further limitation is the lung cancer risk model itself. The model pro-posed by Sze-To et al. (2012) represents a first simple attempt to include the sub-micron particle range in the risk evaluation; its application is use-ful to evaluate the order of magnitude of the lung cancer risk as shown in our previous studies (Buonanno et al., 2015; Buonanno et al., 2017; Pacitto et al., 2018; Scungio et al., 2018a; Stabile et al., 2018; Stabile et al., 2017), nonetheless significant simplifying hypotheses are adopted in its application. In particular, the main simplification is due to the chem-ical composition of the aerosol which is considered uniform within the entire particle size range; this is usually not true since ultrafine and coarse particles present different formation processes (Sophonsiri and Morgenroth, 2004). Including the size-dependent particle chemistry in the model would require chemical composition data characteristics of each size range for all the sources investigated: to the authors' knowledge the scientific and technical literature is not able to provide such detailed data so far. A further aspect to be considered in the risk model uncertainty is the conversion coefficient cf: it represents the equivalent toxicity of the particle surface area metric expressed as particle mass and, at first, was considered not depending on aerosol typology and size by Sze-To et al. (2012). Therefore, this Midostaurin (PKC412) merits an in-depth analysis, involving both aerosol experts and toxicologists, aiming to assess the toxicity of the two particle metrics for different aerosols.
In the present paper an emission inventory of the particle-related lung cancer risk emitted by sources placed in a city is reported. Such an emis-sion inventory represents a novel approach able to summarize both the particle emission and the particle carcinogenetic potential in a single pa-rameter, which is the lung cancer risk emission. The approach here pro-posed was applied to an Italian municipal area as a pilot case-study.
The main findings of the paper are the determination of parameters able to measure the overall lung cancer potential of the city: a) the weighted average slope factor of the city (5.27 × 10−4 kg day mg−1 in the present case) and b) the lung can risk globally emitted by the city, expressed as the number of new cases of lung cancer of the city as the people breathe directly at the emission of the different sources. These
two parameters could be used to compare the emissions of different cit-ies as currently done in terms of CO2.
The results of the emission inventory shown that PM10, Cd, B(a)P, Di-oxins, CO and SO2 are mostly emitted by residential combustions for heating purposes, whereas As, Ni, NOx and UFPs are mainly related to the traffic sector. Thus, the data revealed the completely different con-tributions of the two aerosol metrics (PM10 and ultrafine particles).
Concerning the lung cancer risk emitted by the different sources, the main contribution is due to the particle surface area metric (i.e. sub-micron particles) whereas a negligible effect was related to the PM10. As regard the source apportionment of the emitted risk, the higher risk is due to the extra-urban area (89%) with respect to the urban area; in particular, the main source contributing to the overall emitted risk is the traffic sector (92%) whereas minor contributions are due to the residential and industrial sectors.
The authors point out that such “bottom-up” emission inventory model here proposed is able to localize the risk sources then allowing further risk dispersion modeling at different scales: blastocyst will support the evaluation of map risk of the entire city and the simulation of sce-narios involving different policies of emissions.