Long-term variation in exposure to NO2 concentrations in the city of Naples, Italy: Results of a citizen science project.

The objective of this study is to evaluate long-term changes in the level of exposure to NO2 among the population living in the urban area of Naples (south Italy). This has been achieved by integrating data from the regional reference monitoring network with information collected during the citizen science initiative called 'NO2, NO grazie!' conducted in February 2020 and coordinated by the Non-Governmental Organisation 'Cittadini per l'aria'. This citizen science campaign was based on low-cost passive samplers (Palmes tubes), providing the ability to obtain unprecedented high-resolution NO2 levels. Using a Land Use Random Forest (LURF), we extrapolated the experimental data obtained from the citizen science campaign and evaluated the changes in population exposure from 2013 to 2022 and the uncertainty associated with this assessment was quantified. The results indicate that a large proportion of the inhabitants of Naples are still exposed to high NO2 concentrations, even if strict emission containment measures are enforced. The average levels remain higher than the new interim and air quality targets suggested by the World Health Organisation. The implementation of co-created citizen science projects, where NGO and citizens actively participate alongside scientists, can significantly improve the estimation and the interpretation of official reference data.

A large contribution of methylsiloxanes to particulate matter from ship emissions.

The chemical and stable carbon isotopic composition of the organic aerosol particles (OA) emitted by a shuttle passenger ship between mainland Naples and island Capri in Italy were investigated. Various methylsiloxanes and derivatives were found in particulate ship emissions for the first time, as identified in the mass spectra of a thermal desorption - proton transfer reaction - mass spectrometer (TD-PTR-MS) based on the natural abundance of silicon isotopes. Large contributions of methylsiloxanes to OA (up to 59.3%) were found under inefficient combustion conditions, and considerably lower methylsiloxane emissions were observed under cruise conditions (1.2% of OA). Furthermore, the stable carbon isotopic composition can provide a fingerprint for methylsiloxanes, as they have low δ13C values in the range of -44.91‰ ± 4.29‰. The occurrence of methylsiloxanes was therefore further supported by low δ13C values of particulate organic carbon (OC), ranging from -34.7‰ to -39.4‰, when carbon fractions of methylsiloxanes in OC were high. The δ13C values of OC increased up to around -26.7‰ under cruise conditions, when carbon fractions of methylsiloxanes in OC were low. Overall, the δ13C value of OC decreased linearly with increasing carbon fraction of methylsiloxanes in OC, and the slope is consistent with a mixture of methylsiloxanes and fuel combustion products. The methylsiloxanes in ship emissions may come from engine lubricants.

Chemical characterisation of PM10 from ship emissions: a study on samples from hydrofoil exhaust stacks.

A chemical characterization of PM10 collected at hydrofoil exhaust stacks was performed conducting two on-board measuring campaigns, with the aim of assessing the ship emission impact on PM10 collected in the coastal area of Naples (Southern Italy) and providing information about the characteristics of this important PM emission source.Samples were analysed determining the contribution of different chemical parameters to PM10's mass, which consisted of polycyclic aromatic hydrocarbons (PAHs) (0.10 ± 0.12%), total carbon (61.9% ± 20.0%, with 40.4% of organic carbon, OC, and 21.5% of elemental carbon, EC) and elemental fraction (0.44% ± 1.00%). Differences in terms of composition and chemical parameter profiles were observed between samples collected during offshore navigation (Off) and samples collected during shunting operations (SO), the latter of higher concern on a local scale. For SO samples, lower contributions of OC and EC were observed (39.7% and 19.6% respectively) compared to Off samples (41.5% and 24.2%), and an increase in terms of elements (from 0.32 to 0.51%) and PAHs (from 0.06 to 0.12%) concentrations was observed. In addition, enrichment factors (EFs) for some elements such as V, Zn, Cd, Cu, Ag and Hg as well as PAHs profile varied significantly between SO and Off. Data presented here were compared with data on chemical composition of PM10 sampled in a tunnel, in a background site and in an urban site in the city of Naples. Results indicated that shipping activities contributed significantly to the emission of V and, in some extent, Zn and Cd; in addition, PAH profiles indicated a greater contribution to urban PM10 from vehicular traffic than shipping emissions. These results can significantly contribute to the correct evaluation of the influence of shipping emission on PM10 generation in urban coastal areas and can be a useful reference for similar studies. The coastal area of Naples is an important example of the coexistence of residential, touristic and natural areas with pollutants emission sources including, among the others, shipping emissions. In this and similar contexts, it is important to distinguish the contribution of each emission source to clearly define environmental control policies.

Evaluation and uncertainty estimation of the impact of air quality modelling on crop yields and premature deaths using a multi-model ensemble.

This study promotes the critical use of air pollution modelling results for health and agriculture impacts, with the primary goal of providing more reliable estimates to decision makers. To date, the accuracy of air quality (AQ) models and the effects of model-to-model result variability (which we will refer to as model uncertainty) on impact assessment studies have been often ignored, thus undermining the robustness of the information used in the decision making process and the confidence in the results obtained. A suite of twelve PM2.5 and ozone concentration fields produced by regional-scale chemistry transport Air Quality (AQ) models during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) has been used to calculate the impact of air pollution on premature deaths and crop yields. An innovative technique is applied to bias-adjust the models to available observations. The model results for ozone and PM2.5 are combined in a multi-model (MM) ensemble, which is used to estimate the damage and economic cost to human health and crop yields, as well as the associated uncertainties. The MM ensemble quantifies directly the uncertainty introduced by AQ models into the air pollution impact assessment chain, while the indirect use of experimental information through a bias adjustment, reduces the uncertainty in the ozone and PM2.5 fields and subsequently the uncertainty of the final impact assessment and cost valuation. The analysis over the European countries analysed in this study shows a mean number of premature deaths due to exposure to PM2.5 and ozone of approximately 370,000 (inter-quantile range between 260,000 and 415,000) and a relative yield loss of approximately 7% to 9% (depending on the exposure metrics used, for wheat and maize together). Furthermore, the results indicate that a reduction in the uncertainty of the modelled ozone by 61% and by 80% (depending on the aggregation metric used) and by 46% for PM2.5, produces a reduction in the uncertainty in premature mortality and crop loss of >60%, and of an equivalent percentage in the final uncertainty of cost valuation, providing decision makers with more accurate estimations for more targeted interventions.

Industrial point source CO2 emission strength estimation with aircraft measurements and dispersion modelling.

CO2 remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO2 emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO2 industrial point source, located in Biganos, France. CO2 density measurements were obtained by applying the mass balance method, while CO2 emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments.

Cold unfolding of ß-hairpins: a molecular-level rationalization.

Isolated ß-hairpins in water have a temperature dependence of their conformational stability qualitatively resembling that of globular proteins, showing both cold and hot unfolding transitions. It is shown that a molecular-level rationalization of this cold unfolding can be provided extending the approach devised for globular proteins (Graziano G. Phys Chem Chem Phys 2010; 12:14245-14252). The decrease in the solvent-excluded volume upon folding, measured by the decrease in the solvent accessible surface area, produces a gain in configurational/translational entropy of water molecules that is the main stabilizing contribution of the folded conformation. This always stabilizing Gibbs energy contribution has a parabolic-like temperature dependence in water and is exactly counterbalanced at two temperatures (i.e., the cold and hot unfolding temperatures) by the always destabilizing Gibbs energy contribution due to the loss in conformational degrees of freedom of the peptide chain.