A spatial indicator of environmental and climatic vulnerability in Rome.

BACKGROUND: Urban areas are disproportionately affected by multiple pressures from overbuilding, traffic, air pollution, and heat waves that often interact and are interconnected in producing health effects. A new synthetic tool to summarize environmental and climatic vulnerability has been introduced for the city of Rome, Italy, to provide the basis for environmental and health policies. METHODS: From a literature overview and based on the availability of data, several macro-dimensions were identified on 1,461 grid cells with a width of 1 km2 in Rome: land use, roads and traffic-related exposure, green space data, soil sealing, air pollution (PM2.5, PM10, NO2, C6H6, SO2), urban heat island intensity. The Geographically Weighted Principal Component Analysis (GWPCA) method was performed to produce a composite spatial indicator to describe and interpret each spatial feature by integrating all environmental dimensions. The method of natural breaks was used to define the risk classes. A bivariate map of environmental and social vulnerability was described. RESULTS: The first three components explained most of the variation in the data structure with an average of 78.2% of the total percentage of variance (PTV) explained by the GWPCA, with air pollution and soil sealing contributing most in the first component; green space in the second component; road and traffic density and SO2 in the third component. 56% of the population lives in areas with high or very high levels of environmental and climatic vulnerability, showing a periphery-centre trend, inverse to the deprivation index. CONCLUSIONS: A new environmental and climatic vulnerability indicator for the city of Rome was able to identify the areas and population at risk in the city, and can be integrated with other vulnerability dimensions, such as social deprivation, providing the basis for risk stratification of the population and for the design of policies to address environmental, climatic and social injustice.

Lessons learnt for air pollution mitigation policies from the COVID-19 pandemic: The Italian perspective.

Policies to improve air quality need to be based on effective plans for reducing anthropogenic emissions. In 2020, the outbreak of COVID-19 pandemic resulted in significant reductions of anthropogenic pollutant emissions, offering an unexpected opportunity to observe their consequences on ambient concentrations. Taking the national lockdown occurred in Italy between March and May 2020 as a case study, this work tries to infer if and what lessons may be learnt concerning the impact of emission reduction policies on air quality. Variations of NO2, O3, PM10 and PM2.5 concentrations were calculated from numerical model simulations obtained with business as usual and lockdown specific emissions. Both simulations were performed at national level with a horizontal resolution of 4 km, and at local level on the capital city Rome at 1 km resolution. Simulated concentrations showed a good agreement with in-situ observations, confirming the modelling systems capability to reproduce the effects of emission reductions on ambient concentration variations, which differ according to the individual air pollutant. We found a general reduction of pollutant concentrations except for ozone, that experienced an increase in Rome and in the other urban areas, and a decrease elsewhere. The obtained results suggest that acting on precursor emissions, even with sharp reductions like those experienced during the lockdown, may lead to significant, albeit complex, reduction patterns for secondary pollutant concentrations. Therefore, to be more effective, reduction measures should be carefully selected, involving more sectors than those related to mobility, such as residential and agriculture, and integrated on different scales.

Multiannual assessment of the desert dust impact on air quality in Italy combining PM10 data with physics-based and geostatistical models.

Desert dust storms pose real threats to air quality and health of millions of people in source regions, with associated impacts extending to downwind areas. Europe (EU) is frequently affected by atmospheric transport of desert dust from the Northern Africa and Middle East drylands. This investigation aims at quantifying the role of desert dust transport events on air quality (AQ) over Italy, which is among the EU countries most impacted by this phenomenon. We focus on the particulate matter (PM) metrics regulated by the EU AQ Directive. In particular, we use multiannual (2006-2012) PM10 records collected in hundreds monitoring sites within the national AQ network to quantify daily and annual contributions of dust during transport episodes. The methodology followed was built on specific European Commission guidelines released to evaluate the natural contributions to the measured PM-levels, and was partially modified, tested and adapted to the Italian case in a previous study. Overall, we show that impact of dust on the yearly average PM10 has a clear latitudinal gradient (from less than 1 to greater than 10 µg/m3 going from north to south Italy), this feature being mainly driven by an increased number of dust episodes per year with decreasing latitude. Conversely, the daily-average dust-PM10 (≅12 µg/m3) is more homogenous over the country and shown to be mainly influenced by the site type, with enhanced values in more urbanized locations. This study also combines the PM10 measurements-approach with geostatistical modelling. In particular, exploiting the dust-PM10 dataset obtained at site- and daily-resolution over Italy, a geostatistical, random-forest model was set up to derive a daily, spatially-continuous field of desert-dust PM10 at high (1-km) resolution. This finely resolved information represent the basis for a follow up investigation of both acute and chronic health effects of desert dust over Italy, stemming from daily and annual exposures, respectively.

Impact of environmental pollution and weather changes on the incidence of ST-elevation myocardial infarction.

BACKGROUND: Environmental pollution and weather changes unfavorably impact on cardiovascular disease. However, limited research has focused on ST-elevation myocardial infarction (STEMI), the most severe yet distinctive form of acute coronary syndrome. METHODS AND RESULTS: We appraised the impact of environmental and weather changes on the incidence of STEMI, analysing the bivariate and multivariable association between several environmental and atmospheric parameters and the daily incidence of STEMI in two large Italian urban areas. Specifically, we appraised: carbon monoxide (CO), nitrogen dioxide (NO2), nitric oxide (NOX), ozone, particulate matter smaller than 10 µm (PM10) and than 2.5 µm (PM2.5), temperature, atmospheric pressure, humidity and rainfall. A total of 4285 days at risk were appraised, with 3473 cases of STEMI. Specifically, no STEMI occurred in 1920 (44.8%) days, whereas one or more occurred in the remaining 2365 (55.2%) days. Multilevel modelling identified several pollution and weather predictors of STEMI. In particular, concentrations of CO (p = 0.024), NOX (p = 0.039), ozone (p = 0.003), PM10 (p = 0.033) and PM2.5 (p = 0.042) predicted STEMI as early as three days before the event, as well as subsequently, and NO predicted STEMI one day before (p = 0.010), as well as on the same day. A similar predictive role was evident for temperature and atmospheric pressure (all p < 0.05). CONCLUSIONS: The risk of STEMI is strongly associated with pollution and weather features. While causation cannot yet be proven, environmental and weather changes could be exploited to predict STEMI risk in the following days.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions.

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

Morbidity and mortality of people who live close to municipal waste landfills: a multisite cohort study.

BACKGROUND: 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. METHODS: 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)]. RESULTS: 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). CONCLUSIONS: 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.

Mortality and morbidity in a population exposed to multiple sources of air pollution: A retrospective cohort study using air dispersion models.

BACKGROUND AND AIMS: A landfill, an incinerator, and a refinery plant have been operating since the early 1960s in a contaminated site located in the suburb of Rome (Italy). To evaluate their potential health effects, a population-based retrospective cohort study was conducted using dispersion modeling for exposure assessment. METHODS: A fixed cohort was enrolled in the Rome Longitudinal Study in 2001, mortality and hospitalizations were followed-up until 2010. Exposure assessments to the landfill (H2S), the incinerator (PM10), and the refinery plant (SOX) were performed for each subject using a Lagrangian dispersion model. Individual and small-area variables were available (including exposures levels to NO2 from traffic and diesel trucks). Cox regression analysis was performed (hazard ratios, HRs, 95% CI) using linear terms for the exposures (5th-95th percentiles difference). Single and bi-pollutant models were run. RESULTS: The cohort included 85,559 individuals. The estimated annual average exposures levels were correlated. H2S from the landfill was associated with cardiovascular hospital admissions in both genders (HR 1.04 95% CI 1.00-1.09 in women); PM10 from the incinerator was associated with pancreatic cancer mortality in both genders (HR 1.40 95% CI 1.03-1.90 in men, HR 1.47 95% CI 1.12-1.93 in women) and with breast morbidity in women (HR 1.13 95% CI 1.00-1.27). SOx from the refinery was associated with laryngeal cancer mortality in women (HR 4.99 95% CI 1.64-15.9) and respiratory hospital admissions (HR 1.13 95% CI 1.01-1.27). CONCLUSIONS: We found an association of the pollution sources with some cancer forms and cardio-respiratory diseases. Although there was a high correlation between the estimated exposures, an indication of specific effects from the different sources emerged.

[Morbidity in a population living close to urban waste incinerator plants in Lazio Region (Central Italy): a retrospective cohort study using a before-after design]. / Stato di salute della popolazione residente nei pressi dei termovalorizzatori del Lazio: uno studio di coorte retrospettivo con approccio pre-post.

BACKGROUND: the body of evidence on health effects of residential exposure to urban waste incinerators suggests association with reproductive outcomes and some cancers, but the overall evidence is still limited. OBJECTIVES: we evaluated the impact of two incinerators on hospital admissions for respiratory and cardiovascular diseases in a cohort of people living nearby two incineration plants in Lazio Region (Central Italy) using a before-and-after design. METHODS: the study area was defined as the 7-km radius around the incinerators. People who were resident in the area from 1996 to 2008 were enrolled in a retrospective longitudinal study. All addresses were geocoded. A Lagrangian dispersion model (SPRAY) for PM10 (ng/m³) was used for incinerators exposure assessment. Average annual concentration of background PM10 (µg/m³) was estimated on a regional basis by means of RAMS and FARM models. Both PM10 exposures were estimated at the residential address. All subjects were followed for hospital admissions in the period before (1996-2002) and after (2003-2008) the activation of the plants. The association between exposure to emissions from incinerators and hospitalizations in the two periods was estimated using the multivariate Cox model (for repeated events), adjusting for age, area-level socioeconomic status, distance from industries, traffic roads and highways. An interaction term between the period of follow-up (before or after the activation of the plants) and the exposure levels was used to test the effect of the incinerators. RESULTS: 47,192 subjects resident in the study area were enrolled. No clear association between pollution exposure from incinerators and cause-specific morbidity of residents in highest concentration areas was found when compared to the reference group. However, an effect of PM10 on respiratory diseases and chronic obstructive pulmonary disease was suggested. The effect was due to excesses of hospitalizations for the same causes among men living in highest exposure areas in respect to the reference group (hazard ratio - HR: 1.26; 95%CI 0.99-1.60, and HR: 1.86; 95%CI 1.04-3.33, respectively). There were associations between exposure to background pollution from other sources and hospitalizations for diseases of the circulatory system (HR: 1.08; 95%CI 1.03-1.13) and respiratory diseases (HR: 1.07; 95%CI 1.02-1.11) (for a unitary increment of PM10, µg/m³). CONCLUSIONS: living in areas with high PM10 levels due to incinerators was associated with increased morbidity levels for respiratory disorders among men. The study area is critical from an environmental point of view, hence an epidemiological surveillance is recommended.

Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies.

BACKGROUND: Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. OBJECTIVES: Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. METHODS: The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area. RESULTS: The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5. CONCLUSIONS: LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5.

[Air pollution in an urban area nearby the Rome-Ciampino city airport]. / Inquinamento atmosferico in un'area urbana limitrofa all'aeroporto di Roma-Ciampino.

OBJECTIVES: to assess air pollution spatial and temporal variability in the urban area nearby the Ciampino International Airport (Rome) and to investigate the airport-related emissions contribute. DESIGN AND SETTING: the study domain was a 64 km2 area around the airport. Two fifteen-day monitoring campaigns (late spring, winter) were carried out. Results were evaluated using several runs outputs of an airport-related sources Lagrangian particle model and a photochemical model (the Flexible Air quality Regional Model, FARM). MAIN OUTCOME MEASURES: both standard and high time resolution air pollutant concentrations measurements: CO, NO, NO2, C6H6, mass and number concentration of several PM fractions. 46 fixed points (spread over the study area) of NO2 and volatile organic compounds concentrations (fifteen days averages); deterministic models outputs. RESULTS: standard time resolution measurements, as well as model outputs, showed the airport contribution to air pollution levels being little compared to the main source in the area (i.e. vehicular traffic). However, using high time resolution measurements, peaks of particles associated with aircraft takeoff (total number concentration and soot mass concentration), and landing (coarse mass concentration) were observed, when the site measurement was downwind to the runway. CONCLUSIONS: the frequently observed transient spikes associated with aircraft movements could lead to a not negligible contribute to ultrafine, soot and coarse particles exposure of people living around the airport. Such contribute and its spatial and temporal variability should be investigated when assessing the airports air quality impact.

[Residential cohort approach in industrial contaminated sites: the ERAS Lazio project]. / Lo studio di coorte di popolazione in aree a forte pressione ambientale: il programma ERAS Lazio.

The population-based cohort study is the best design for assessing the possible health effects resulting fromliving in contaminated sites. The ERAS (Epidemiology,Waste disposal, Environment and Health) Project was established to study the health of people living in close proximity to urban solid waste treatment (RU) plants in Lazio. It was conducted using an integrated approach, which consisted in studying mortality and hospital discharges of residential cohorts surrounding urban waste treatment plants. The level of exposure of each address was assigned using pollution dispersion models and studying the effects on mortality and hospital discharges. Further studies were conducted on residents of areas adjacent to waste disposal sites (includingMalagrotta in Rome), incinerators andmechanical biological treatment plants. The final version of the ERAS Report is available at www.eraslazio.it. The residential cohort approach and the combination of environmental and health-related information proved invaluable in the assessment of the health impact of solid waste treatment in Lazio.