Odors are typically released into the atmosphere as diffuse emissions from area and volume sources, whose detailed quantification in terms of odor emission rate is often hardly achievable by direct ...source sampling. Indirect methods, involving the use of micrometeorological methods in order to correlate downwind concentrations to the emission rates, are already mentioned in literature, but rarely found in real applications for the quantification of odor emissions. The instrumentation needed for the development of micrometeorological methods has nowadays become accessible in terms of prices and reliability, thus making the implementation of such methods to industrial applications more and more interesting. For this reason, this work aims to provide an overview of micrometeorological methods and investigate their effective applicability to odors, thereby providing a short description of the physics related to such methods and analyzing the relevant scientific literature. The theoretical basis of these methods is presented, and their advantages and disadvantages are discussed. Moreover, their applicability to the estimation of odor emissions is discussed by providing some suggestions about the suitable ways to evaluate the most critical parameters needed for the calculation of the odor emission rate.
The evidence on the health effects related to residing close to landfills is controversial. Nine landfills for municipal waste have been operating in the Lazio region (Central Italy) for several ...decades. We evaluated the potential health effects associated with contamination from landfills using the estimated concentration of hydrogen sulphide (H2S) as exposure.
A cohort of residents within 5 km of landfills was enrolled (subjects resident on 1 January 1996 and those who subsequently moved into the areas until 2008) and followed for mortality and hospitalizations until 31 December 2012. Assessment of exposure to the landfill (H2S as a tracer) was performed for each subject at enrolment, using a Lagrangian dispersion model. Information on several confounders was available (gender, age, socioeconomic position, outdoor PM10 concentration, and distance from busy roads and industries). Cox regression analysis was performed Hazard Ratios (HRs), 95% confidence intervals (CIs).
The cohort included 242 409 individuals. H2S exposure was associated with mortality from lung cancer and respiratory diseases (e.g. HR for increment of 1 ng/m(3) H2S: 1.10, 95% CI 1.02-1.19; HR 1.09, 95% CI 1.00-1.19, respectively). There were also associations between H2S and hospitalization for respiratory diseases (HR = 1.02, 95% CI 1.00-1.03), especially acute respiratory infections among children (0-14 years) (HR = 1.06, 95% CI 1.02-1.11).
Exposure to H2S, a tracer of airborne contamination from landfills, was associated with lung cancer mortality as well as with mortality and morbidity for respiratory diseases. The link with respiratory disease is plausible and coherent with previous studies, whereas the association with lung cancer deserves confirmation.
Turbulence closure schemes, besides their intrinsic theoretical importance, represent a fundamental component in the atmospheric numerical models. Among his numerous and diverse scientific ...contributions, Prof. Sergej S. Zilitinkevich, with his coauthors, elaborated a turbulence closure model for stably-stratified geophysical flows, the Energy and Flux Budget (EFB) model. This closure has been verified and applied on many different experimental datasets and case studies, for steady state and homogeneous conditions. Having available observational datasets for urban and suburban sites in different cities in Italy, we investigate the deviation of the observations of turbulent kinetic energy and momentum flux from the EFB turbulence closure model in heterogeneous conditions. This allows addressing and interpreting the features that induce such deviation between the model and the observations. The EFB model is then revisited including residual terms that can account for the non-stationarity and heterogeneity of the considered cases. The correction with the residual terms leads to improve the agreement between the theoretical formulations and the observed behaviour for the turbulent kinetic energy shares and for the vertical momentum flux.
Cities are severely affected by air pollution. Local emissions and urban structures can produce large spatial heterogeneities. We aim to improve the estimation of NO2, O3, PM2.5 and PM10 ...concentrations in 6 Italian metropolitan areas, using chemical-transport and machine learning models, and to assess the effect on population exposure by using information on urban population mobility. Three years (2013–2015) of simulations were performed by the Chemical-Transport Model (CTM) FARM, at 1 km resolution, fed by boundary conditions provided by national-scale simulations, local emission inventories and meteorological fields. A downscaling of daily air pollutants at higher resolution (200 m) was then carried out by means of a machine learning Random-Forest (RF) model, considering CTM and spatial-temporal predictors, such as population, land-use, surface greenness and vehicular traffic, as input. RF achieved mean cross-validation (CV) R2 of 0.59, 0.72, 0.76 and 0.75 for NO2, PM10, PM2.5 and O3, respectively, improving results from CTM alone. Mean concentration fields exhibited clear geographical gradients caused by climate conditions, local emission sources and photochemical processes. Time series of population weighted exposure (PWE) were estimated for two months of the year 2015 and for five cities, by combining population mobility data (derived from mobile phone traffic volumes data), and concentration levels from the RF model. PWE_RF metric better approximated the observed concentrations compared with the predictions from either CTM alone or CTM and RF combined, especially for pollutants exhibiting strong spatial gradients, such as NO2. 50% of the population was estimated to be exposed to NO2 concentrations between 12 and 38 μg/m3 and PM10 between 20 and 35 μg/m3. This work supports the potential of machine learning methods in predicting air pollutant levels in urban areas at high spatial and temporal resolutions.
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•Machine learning methods were applied to obtain pollutant concentration in urban areas.•Population weighted exposure was estimated using dynamic mobile phone location data.•Long term NO2, PM, and O3 daily concentrations were provided for 6 urban areas.•Differences among cities were found with spatial/geographical concentration gradients.
The relationship between air pollution and respiratory morbidity has been widely addressed in urban and metropolitan areas but little is known about the effects in non-urban settings. Our aim was to ...assess the short-term effects of PM10 and PM2.5 on respiratory admissions in the whole country of Italy during 2006–2015.
We estimated daily PM concentrations at the municipality level using satellite data and spatiotemporal predictors. We collected daily counts of respiratory hospital admissions for each Italian municipality. We considered five different outcomes: all respiratory diseases, asthma, chronic obstructive pulmonary disease (COPD), lower and upper respiratory tract infections (LRTI and URTI). Meta-analysis of province-specific estimates obtained by time-series models, adjusting for temperature, humidity and other confounders, was applied to extrapolate national estimates for each outcome. At last, we tested for effect modification by sex, age, period, and urbanization score. Analyses for PM2.5 were restricted to 2013–2015 cause the goodness of fit of exposure estimation.
A total of 4,154,887 respiratory admission were registered during 2006–2015, of which 29% for LRTI, 12% for COPD, 6% for URTI, and 3% for asthma. Daily mean PM10 and PM2.5 concentrations over the study period were 23.3 and 17 μg/m3, respectively. For each 10 μg/m3 increases in PM10 and PM2.5 at lag 0–5 days, we found excess risks of total respiratory diseases equal to 1.20% (95% confidence intervals, 0.92, 1.49) and 1.22% (0.76, 1.68), respectively. The effects for the specific diseases were similar, with the strongest ones for asthma and COPD. Higher effects were found in the elderly and in less urbanized areas.
Short-term exposure to PM is harmful for the respiratory system throughout an entire country, especially in elderly patients. Strong effects can be found also in less urbanized areas.
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•PM increases cause excess in risk of hospitalization for respiratory outcomes.•Rural areas display similar risks than urban areas.•Higher risks are found in elderly.•Almost 5000 hospitalizations could be prevented each year.
The health effects of long-term exposure to ultrafine particles (UFPs) are poorly understood. Data on spatial contrasts in ambient ultrafine particles (UFPs) concentrations are needed with fine ...resolution. This study aimed to assess the spatial variability of total particle number concentrations (PNC, a proxy for UFPs) in the city of Rome, Italy, using land use regression (LUR) models, and the correspondent exposure of population here living. PNC were measured using condensation particle counters at the building facade of 28 homes throughout the city. Three 7-day monitoring periods were carried out during cold, warm and intermediate seasons. Geographic Information System predictor variables, with buffers of varying size, were evaluated to model spatial variations of PNC. A stepwise forward selection procedure was used to develop a “base” linear regression model according to the European Study of Cohorts for Air Pollution Effects project methodology. Other variables were then included in more enhanced models and their capability of improving model performance was evaluated. Four LUR models were developed. Local variation in UFPs in the study area can be largely explained by the ratio of traffic intensity and distance to the nearest major road. The best model (adjusted R2 = 0.71; root mean square error = ±1,572 particles/cm³, leave one out cross validated R2 = 0.68) was achieved by regressing building and street configuration variables against residual from the “base” model, which added 3% more to the total variance explained. Urban green and population density in a 5,000 m buffer around each home were also relevant predictors. The spatial contrast in ambient PNC across the large conurbation of Rome, was successfully assessed. The average exposure of subjects living in the study area was 16,006 particles/cm³ (SD 2165 particles/cm³, range: 11,075–28,632 particles/cm³). A total of 203,886 subjects (16%) lives in Rome within 50 m from a high traffic road and they experience the highest exposure levels (18,229 particles/cm³). The results will be used to estimate the long-term health effects of ultrafine particle exposure of participants in Rome.
•PNCs were measured directly outside 28 homes for three weeks in different seasons.•LUR models were developed using standard and enhanced GIS-derived predictor variables.•Traffic intensity, population density and urban green were the main predictors of UFP.•Building and street configuration variables improved LUR model performance.•PNC exposure at a fine spatial resolution was successfully assessed.
In 2011 the European Commission (EC) released specific ‘Guidelines’ describing the methods to quantify and subtract the contribution of natural sources from the PM10 values regulated by the European ...Air Quality Directive (2008/50/EC). This work investigates the applicability to Italy of the EC-Methodology suggested for desert-dust, describes main limitations encountered and proposes specific modifications embedded within a ‘revised-Methodology’ to extend/improve its use. The revised-Methodology capabilities are evaluated using original, chemically-resolved mineral-dust mass concentration measurements, showing better performances in predicting timing and absolute values of the desert-dust contribution to the daily-PM10 with respect to the current EC-approach. The revised-Methodology is then translated into an automatic (user-independent) tool tailored to the expected final-users. This tool is applied over Central Italy across a 3-year long period (2012–2014), and over the whole Italian country for a calendar year (2012). The derived results confirm and extend to Italian regions never addressed before some previously observed features of the desert-dust impact over the country, such as a clear latitudinal dependence of the desert-dust impact on the yearly average PM10 (from more than 5 μg/m3 to less than 0.5 μg/m3, going from south to north Italy). The modifications introduced within the revised-Methodology also suggest a non-negligible role of desert-dust resuspension in areas characterized by both high traffic levels and soil sealing (urban areas and along the major Italian routes). In the Rome area, such an effect is found to add a contribution of about 2 μg/m3 (i.e., of 20%) to the mean desert-dust load per dust day (about 10 μg/m3). At the national level, this effect contributes increasing the total number of desert-dust-driven exceedances of the PM10 daily limit value even in the northern regions, where the desert-dust impact on the PM10 yearly average is otherwise limited. These results also indicate the direction for possible mitigation strategies to be applied over impacted areas. The successful implementation of the revised-Methodology over Italy suggests it could represent a valid option for a nationwide standard procedure to quantify the desert-dust contribution to PM10, promoting the homogenisation of the relevant values annually reported to the EC.
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•European Commission Guidelines to assess impact of desert dust on PM10 are considered.•A revised-Methodology better assessing desert dust impact over Italy is proposed.•The revised-Methodology is validated and translated into an automatic tool.•Desert dust impact on PM10 loads over Italy is quantified.•Non negligible desert dust resuspension appears to affect high traffic areas.
The annual and diurnal behavior of the temperature differences in urban areas is important to predict the possible impacts of the future land-use development on climate change and air pollution in ...heavily populated areas. The behavior of the temperature as well as wind spatio-temporal differences in turn is strongly interconnected with the turbulent and radiative fluxes variability. A 3-year dataset from three automated micrometeorological stations run by the Regional Agency for Environment Protection of Lazio and located in and around the city of Rome is used. The distribution of the urban heat island intensity for the whole period of measurements peaks at 1 °C, but higher values are frequently registered especially referring to differences with the coastal site also due to the sea-breeze cooling effects. The city is generally drier and characterized by winds of lower intensity reaching their maximum 1 h later with the respect to the sub-urban/coastal sites during the afternoon. The micrometeorological data are also analyzed to estimate some key parameter characteristic of the terrain, which represents the main forcing in the numerical models for UHI estimates, such as the albedo, aerodynamics and atmospheric turbulence parameters.
•urban heat island; Rome; ultrasonic anemometer; micrometeorological parameters; sea-breeze.
In the period January–February 2014, observations were made at the Concordia station, Dome C, Antarctica to study atmospheric turbulence in the boundary layer using a high-resolution sodar. The ...turbulence structure was observed beginning from the lowest height of about 2 m, with a vertical resolution of less than 2 m. Typical patterns of the diurnal evolution of the spatio-temporal structure of turbulence detected by the sodar are analyzed. Here, we focus on the wavelike processes observed within the transition period from stable to unstable stratification occurring in the morning hours. Thanks to the high-resolution sodar measurements during the development of the convection near the surface, clear undulations were detected in the overlying turbulent layer for a significant part of the time. The wavelike pattern exhibits a regular braid structure, with undulations associated with internal gravity waves attributed to Kelvin–Helmholtz shear instability. The main spatial and temporal scales of the wavelike structures were determined, with predominant periodicity of the observed wavy patterns estimated to be 40–50 s. The horizontal scales roughly estimated using Taylor’s frozen turbulence hypothesis are about 250–350 m.
An experimental campaign, Study of the Atmospheric Boundary Layer Environmental at Dome C, was held during 2005 at the French-Italian station of Concordia at Dome C. Ground-based remote sensors, as ...well as in situ instrumentation, were used during the experimental campaign. The measurements allowed the direct estimation of the polar atmospheric boundary-layer height and the test of several parametrizations for the unstable and stable boundary layers. During the months of January and February, weak convection was observed while, during the polar night, a long-lived stable boundary layer occurred continuously. Under unstable stratification the mixing-layer height was determined using the sodar backscattered echoes and potential temperature profiles. The two estimations are highly correlated, with the mixing height ranging between 30 and 350 m. A simple prognostic one-dimensional model was used to estimate the convective mixing-layer height, with the correlation coefficient between observations and model results being 0.66. The boundary-layer height under stable conditions was estimated from radiosounding profiles as the height where the critical Richardson number is reached; values between 10 and 150 m were found. A visual inspection of potential temperature profiles was also used as further confirmation of the experimental height; the results of the two methods are in good agreement. Six parametrizations from the literature for the stable boundary-layer height were tested. Only the parametrization that considers the long-lived stable boundary layer and takes into account the interaction of the stable layer with the free atmosphere is in agreement with the observations.
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