Assessment of the Air Pollution Level in the City of Rome (Italy)

Gabriele Battista, Tiziano Pagliaroli, Luca Mauri, Carmine Basilicata, Roberto De Lieto Vollaro
2016 Sustainability  
Exposure to pollutants is usually higher in cities than in the countryside. Generally, in the urban areas pollution sources as traffic, power generator and domestic heating system are more intense and spatially distributed. The pollutants can be classified as a function of long-term toxicological effects due to an exposure and inhalation. In the present work, several kinds of pollutants concentration generated in Rome during 2015 have been analyzed applying different advanced post-processing
more » ... post-processing technique. In particular, statistic and cross-statistic have been computed in time and phase space domain. As main result, it is observed, as expected, that all the pollutant concentrations increase during the winter season into a couple of time ranges despite of [O 3 ] that has high values in summer. It can be clearly concluded that Rome has a strongly unsteady behaviour in terms of a family of pollutant concentration, which fluctuate significantly. It is worth noticing that there is a strong linear dependence between [C 6 H 6 ] and [NO] and a more complex interdependence of [O 3 ] and [C 6 H 6 ]. Qualitatively is provided that, to a reduction of [C 6 H 6 ] under a certain threshold level corresponds an increase of [O 3 ]. 2 of 15 to ambient fine particles (PM 2.5 ) and 22,300 people died because of lung cancer. China and East Asia show the largest number of people who lost their life [5, 6] . With reference to NO 2 , SO 2 and (PMs) there is general agreement in the scientific literature that they are the main agents responsible for the damage encountered on monuments and historical buildings in urban areas [7] . Atmospheric composition is of unquestionable importance in the study of the damage produced on building materials of artistic interest, since it directly influences the species characteristics and entity of the degradation mechanism occurring on the cultural heritage. The urban areas modified the environmental features that contributed to the increase of pollution. As a matter of fact, the large concentration of the built environment, road pavement and the high building materials capacitance changed the local micrometeorological conditions. Air temperature, humidity and wind velocity and direction are altered in the urban environment compared to rural areas. Furthermore, road traffic, domestic heating, industrial activities and lack buildings energy performance involves high discomfort for users [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] . Besides the increase of pollutions, urbanization has led to an increase of the urban heat island intensity (spatially-averaged surface or air-temperature difference between an urban and surrounding rural area(s) [21] ). Several studies are focused to reduce the urban heat island effect with different mitigation techniques [22] [23] [24] [25] [26] [27] [28] . The people exposed to air pollutants are even more evident considering the weak ventilation, because of the presence of high buildings with a consequent reduction of the dispersion of air masses. For this reason, the contaminants formed below the building height remain at the pedestrian level and increase the health damages especially during thermal inversion episodes. Several studies were conducted to analyse the correlation between the street canyon features and the pollution dispersion [29] . If the ratio between the average height of the buildings (H) and the width of the canyon (W) is high enough to establish skimming flow conditions (at least higher than 0.65), the retention of pollutants within the urban canopy layer will be amplified [30] . The major street canyons in the cities have high value of the ratio H/W with a consequent established helical vortex with an axis parallel to the canyon direction. In this case, the pollutants that go out of the canyon are reduced [31] . The identification of analysis tools and methods, pollutant concentrations measurement, comparison with the threshold values prescribed by law, are the activities foreseen by the legislations in order to monitor the air quality and predict rehabilitation through the definition of plans of interventions. As a first step, in order to plain a control strategy of the pollution concentration in medium and high scale cities, proper measurement and data processing are required to highlight the achievement of dangerous concentration levels of pollutants and formulate a prediction model. Actually, the main active control strategy is based on the introduction of some limits of the urban traffic (e.g., number of the vehicles and vehicle categories that are authorized to transit). Other interventions include the increase of efficiency of the heating systems in buildings such as the replacement of traditional boilers with condensation ones integrated with more performing regulation systems based on energy load tracking. In the present work, several kinds of pollutants concentration such as [CO], [SO 2 ], [NOx], [NO], [NO 2 ], [C 6 H 6 ], [PM 10 ], [PM 2.5 ] and [O 3 ] generated in Rome during 2015 have been analysed. These pollutants were taken from the Directive 2008/50/EC, the main legislation about ambient air quality. In these analyses we applied different advanced post-processing techniques. Statistic and cross-statistic have been computed in time and Fourier domain. In particular, probability distribution, Kurtosis, Skewness, Poincaré sections and cross-correlation of the different pollutants were analysed in order to assess the air pollution level in the city of Rome and the correlation of anthropogenic sources with the pollutant emission. The extreme value theory was applied to the experimental data. Especially using the generalized extreme value (GEV) distribution, several fittings of the experiment probability density functions were calculated. GEV distribution introduced by Fisher and Tippett [32] is commonly applied in environmental science to model a wide variety of natural extremes,
doi:10.3390/su8090838 fatcat:p4jncmxrlndxhfh7jtlixirvxa