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.

Impact of weather and pollution on the rate of cerebrovascular events in a large metropolitan area.

BACKGROUND: Despite mounting evidence, there is uncertainty on the impact of the interplay between weather and pollution features on the risk of acute cerebrovascular events (CVE). We aimed at appraising role of weather and pollution on the daily risk of CVE. METHODS: Anonymized data from a hub CVE center in a large metropolitan area were collected and analyzed according to weather (temperature, pressure, humidity, and rainfall) and pollution (carbon monoxide [CO], nitrogen dioxide [NO2], nitrogen oxides [NOX], ozone [O3], and particulate matter [PM]) on the same and the preceding days. Poisson regression and time series analyses were used to appraise the association between environmental features and daily CVE, distinguishing also several subtypes of events. RESULTS: We included a total of 2534 days, with 1363 days having ≥1 CVE, from 2012 to 2017. Average daily rate was 1.56 (95% confidence interval: 1.49; 1.63) for CVE, with other event rates ranging between 1.42 for stroke and 0.01 for ruptured intracranial aneurysm. Significant associations were found between CVE and temperature, pressure, CO, NO2, NOX, O3, and PM <10 µm (all P<0.05), whereas less stringent associations were found for humidity, rainfall, and PM <2.5 µm. Time series analysis exploring lag suggested that associations were stronger at same-day analysis (lag 0), but even environmental features predating several days or weeks were significantly associated with events. Multivariable analysis suggested that CO (point estimate 1.362 [1.011; 1.836], P=0.042) and NO2 (1.011 [1.005; 1.016], P<0.001) were the strongest independent predictors of CVE. CONCLUSIONS: Environmental features are significantly associated with CVE, even several days before the actual event. Levels of CO and NO2 can be potentially leveraged for population-level interventions to reduce the burden of CVE.

Cluster analysis of weather and pollution features and its role in predicting acute cardiac or cerebrovascular events.

BACKGROUND: Despite mounting evidence, the impact of the interplay between weather and pollution features on the risk of acute cardiac and cerebrovascular events has not been entirely appraised. The aim of this study was to perform a comprehensive cluster analysis of weather and pollution features in a large metropolitan area, and their association with acute cardiac and cerebrovascular events. METHODS: Anonymized data on acute myocardial infarction (AMI) and acute cerebrovascular events were obtained from 3 tertiary care centers from a single large metropolitan area. Weather and pollution data were obtained averaging measurements from several city measurement stations managed by the competent regional agency for enviromental protection, and from the Metereological Center of Italian Military Aviation. Unsupervised machine learning was performed with hierarchical clustering to identify specific days with distinct weather and pollution features. Clusters were then compared for rates of acute cardiac and cerebrovascular events with Poisson models. RESULTS: As expected, significant pairwise correlations were found between weather and pollution features. Building upon these correlations, hierarchical clustering, from a total of 1169 days, generated 4 separate clusters: mostly winter days with low temperatures and high ozone concentrations (cluster 1, N.=60, 5.1%), days with moderately high temperatures and low pollutants concentrations (cluster 2, N.=419, 35.8%), mostly summer and spring days with high temperatures and high ozone concentrations (cluster 3, N.=673, 57.6%), and mostly winter days with low temperatures and low ozone concentrations (cluster 4, N.=17, 1.5%). Overall cluster-wise comparisons showed significant differences in adverse cardiac and cerebrovascular events (P<0.001), as well as in cerebrovascular events (P<0.001) and strokes (P=0.001). Between-cluster comparisons showed that cluster 1 was associated with an increased risk of any event, cerebrovascular events, and strokes in comparison to cluster 2, cluster 3 and cluster 4 (all P<0.05), as well as AMI in comparison to cluster 3 (P=0.047). In addition, cluster 2 was associated with a higher risk of strokes in comparison to cluster 4 (P=0.030). Analysis adjusting for season confirmed the increased risk of any event, cerebrovascular events and strokes for cluster 1 and cluster 2. CONCLUSIONS: Unsupervised machine learning can be leveraged to identify specific days with a unique clustering of adverse weather and pollution features which are associated with an increased risk of acute cardiovascular events, especially cerebrovascular events. These findings may improve collective and individual risk prediction and prevention.

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.

The effect of Covid-19 lockdown on airborne particulate matter in Rome, Italy: A magnetic point of view.

Between 9 March and 18 May 2020, strict lockdown measures were adopted in Italy for containing the COVID-19 pandemic: in Rome, despite vehicular traffic on average was more than halved, it was not observed a evident decrease of the airborne particulate matter (PM) concentrations, as assessed by air quality data. In this study, daily PM10 filters were collected from selected automated stations operated in Rome by the regional network of air quality monitoring: their magnetic properties - including magnetic susceptibility, hysteresis parameters and FORC (first order reversal curves) diagrams - were compared during and after the lockdown, for outlining the impact of the COVID-19 measures on airborne particulate matter. In urban traffic sites, the PM10 concentrations did not significantly change after the end of the lockdown, when vehicular traffic promptly returned to its usual levels; conversely, the average volume and mass magnetic susceptibilities approximately doubled, and the linear correlation between volume magnetic susceptibility and PM10 concentration became significant, pointing out the link between PM10 concentrations and the increasing levels of traffic-related magnetic emissions. Magnetite-like minerals, attributed to non-exhaust brakes emissions, dominated the magnetic fraction of PM10 near urban traffic sites, with natural magnetic components emerging in background sites and during exogenous dusts atmospheric events. Magnetic susceptibility constituted a fast and sensitive proxy of vehicular particulate emissions: the magnetic properties can play a relevant role in the source apportionment of PM10, especially when unsignificant variations in its concentration levels may mask important changes in the traffic-related magnetic fraction. As a further hint, increasing attention should be drawn to the reduction of brake wear emissions, that are overcoming by far fuel exhausts as the main particulate pollutant in traffic contexts.

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.

Interplay between COVID-19, pollution, and weather features on changes in the incidence of acute coronary syndromes in early 2020.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused an unprecedented change in the apparent epidemiology of acute coronary syndromes (ACS). However, the interplay between this disease, changes in pollution, climate, and aversion to activation of emergency medical services represents a challenging conundrum. We aimed at appraising the impact of COVID-19, weather, and environment features on the occurrence of ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) in a large Italian region and metropolitan area. METHODS AND RESULTS: Italy was hit early on by COVID-19, such that state of emergency was declared on January 31, 2020, and national lockdown implemented on March 9, 2020, mainly because the accrual of cases in Northern Italy. In order to appraise the independent contribution on changes in STEMI and NSTEMI daily rates of COVID-19, climate and pollution, we collected data on these clinical events from tertiary care cardiovascular centers in the Lazio region and Rome metropolitan area. Multilevel Poisson modeling was used to appraise unadjusted and adjusted effect estimates for the daily incidence of STEMI and NSTEMI cases. The sample included 1448 STEMI and 2040 NSTEMI, with a total of 2882 PCI spanning 6 months. Significant reductions in STEMI and NSTEMI were evident already in early February 2020 (all p<0.05), concomitantly with COVID-19 spread and institution of national countermeasures. Changes in STEMI and NSTEMI were inversely associated with daily COVID-19 tests, cases, and/or death (p<0.05). In addition, STEMI and NSTEMI incidences were associated with daily NO2, PM10, and O3 concentrations, as well as temperature (p<0.05). Multi-stage and multiply adjusted models highlighted that reductions in STEMI were significantly associated with COVID-19 data (p<0.001), whereas changes in NSTEMI were significantly associated with both NO2 and COVID-19 data (both p<0.001). CONCLUSIONS: Reductions in STEMI and NSTEMI in the COVID-19 pandemic may depend on different concomitant epidemiologic and pathophysiologic mechanisms. In particular, recent changes in STEMI may depend on COVID-19 scare, leading to excess all-cause mortality, or effective reduced incidence, whereas reductions in NSTEMI may also be due to beneficial reductions in NO2 emissions in the lockdown phase.

Impact of temporary traffic bans on the risk of acute coronary syndromes in a large metropolitan area.

BACKGROUND: Strong epidemiologic evidence has highlighted the role of pollution, on top of adverse climate features, as a novel cardiovascular risk factor. However, mechanistic proof that reducing pollution may be beneficial to prevent atherothrombotic events is limited. We aimed at appraising the impact of temporary traffic bans in a large metropolitan area on the risk of acute coronary syndromes. METHODS: Aggregate and anonymized data from 15 tertiary cardiac care centers were obtained detailing precoronavirus disease 2019 (COVID-19) daily cases of ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI), including those treated with percutaneous coronary intervention (PCI). Data on pollutants and climate were sought for the same days. Mixed level regression was used to compare the week before vs after the traffic ban (Fortnight analysis), the 3 days before vs. after (Weekly analysis) and the Sunday before vs. after (Sunday analysis). RESULTS: A total of 8 days of temporary traffic bans were included, occurring between 2017 and 2020, totaling 802 STEMI and 1196 NSTEMI in the Fortnight analysis, 382 STEMI and 585 in the Weekly analysis, and 148 STEMI and 210 NSTEMI in the Sunday analysis.Fortnight and Sunday analyses did not disclose a significant impact of traffic ban on STEMI or NSTEMI (all P>0.05). Conversely, Weekly analysis showed non-significant changes for STEMI, but a significant decrease in daily NSTEMI when comparing the 3 days before the traffic ban with the ban day (P=0.043), as well as the 3 days before vs. the 3 days after the ban (P=0.025). No statistically significant effect of traffic ban was found at Fortnight, Weekly or Sunday analyses for daily mean concentrations of benzene, carbon monoxide, nitric oxide, nitrogen dioxide, ozone, sulfur dioxide, particulate matter (PM) <2.5 µm or PM <10 µm (all P>0.05). However, minimum daily concentrations showed a significant reduction of ozone during the ban in comparison to the week preceding it (P=0.034), nitric oxide during the ban in comparison to the 3 days preceding it (P=0.046), and an increase in benzene during the ban in comparison to the Sunday before (P=0.039). CONCLUSIONS: Temporary traffic ban may favorably reduce coronary atherothrombotic events, and in particular NSTEMI, even if not globally and immediately impacting on environmental pollution. Further controlled studies are required to confirm and expand this hypothesis-generating results.

342 Impact of temporary traffic bans on the risk of acute coronary syndromes in a large metropolitan area.

Aims: Strong epidemiologic evidence has highlighted the role of pollution, on top of adverse climate features, as a novel cardiovascular risk factor. However, mechanistic proof that reducing pollution may be beneficial to prevent atherothrombotic events is limited. We aimed at appraising the impact of temporary traffic bans in a large metropolitan area on the risk of acute coronary syndromes. Methods and results: Aggregate and anonymized data from 15 tertiary cardiac care centers were obtained detailing pre-coronarivus disease 2019 (COVID-19) daily cases of ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI), including those treated with percutaneous coronary intervention (PCI). Data on pollutants and climate were sought for the same days. Mixed level regression was used to compare the week before vs. after the traffic ban (Fortnight analysis), the 3 days before vs. after (Weekly analysis) and the Sunday before vs. after (Sunday analysis). A total of 8 days of temporary traffic bans were included, occurring between 2017 and 2020, totaling 802 STEMI and 1196 NSTEMI in the Fortnight analysis, 382 STEMI and 585 in the Weekly analysis, and 148 STEMI and 210 NSTEMI in the Sunday analysis. Fortnight and Sunday analysis did not disclose a significant impact of traffic ban on STEMI or NSTEMI (all P > 0.05). Conversely, Weekly analysis showed non-significant changes for STEMI but a significant decrease in daily NSTEMI when comparing the 3 days before the traffic ban with the ban day (P = 0.043), as well as the 3 days before vs. the 3 days after the ban (P = 0.025). No statistically significant effect of traffic ban was found at Fortnight, Weekly or Sunday analyses for daily mean concentrations of benzene, carbon monoxide, nitric oxide, nitrogen dioxide, ozone, sulfur dioxide, particulate matter (PM) <2.5 µm or PM < 10 µm (all P > 0.05). However, minimum daily concentrations showed a significant reduction of ozone during the ban in comparison to the week preceding it (P = 0.034), nitric oxide during the ban in comparison to the 3 days preceding it (P = 0.046), and an increase in benzene during the ban in comparison to the Sunday before (P = 0.039). Conclusion: Temporary traffic bans may favorably reduce coronary atherothrombotic events, and in particular NSTEMI, even if not globally and immediately impacting on environmental pollution. Further controlled studies are required to confirm and expand this hypothesis-generating results.

339 Interplay between COVID-19, pollution, and weather features on changes in the incidence of acute coronary syndromes in early 2020.

Aims: Coronavirus disease 2019 (COVID-19) has caused an unprecedented change in the apparent epidemiology of acute coronary syndromes (ACS). However, the interplay between this disease, changes in pollution, climate, and aversion to activation of emergency medical services represents a challenging conundrum. We aimed at appraising the impact of COVID-19, weather, and environment features on the occurrence of ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) in a large Italian region and metropolitan area. Methods and results: Italy was hit early on by COVID-19, such that state of emergency was declared on January 31, 2020, and national lockdown implemented on March 9, 2020, mainly because the accrual of cases in Northern Italy. In order to appraise the independent contribution on changes in STEMI and NSTEMI daily rates of COVID-19, climate and pollution, we collected data on these clinical events from tertiary care cardiovascular centers in the Lazio region and Rome metropolitan area. Multilevel Poisson modeling was used to appraise unadjusted and adjusted effect estimates for the daily incidence of STEMI and NSTEMI. The sample included 1448 STEMI and 2040 NSTEMI, with a total of 2882 PCI spanning 6 months. Significant reductions in STEMI and NSTEMI were evident already in early February 2020 (all P < 0.05), concomitantly with COVID-19 spread and institution of national countermeasures. Changes in STEMI and NSTEMI were inversely associated with daily COVID-19 tests, cases, and/or death (P < 0.05). In addition, STEMI and NSTEMI incidences were associated with daily NO2, PM10, and O3 concentrations, as well as temperature (P < 0.05). Multi-stage and multiply adjusted models highlighted that reductions in STEMI were significantly associated with COVID-19 data (P < 0.001), whereas changes in NSTEMI were significantly associated with both NO2 and COVID-19 data (both P < 0.001). Conclusion: Reductions in STEMI and NSTEMI in the COVID-19 pandemic may depend on different concomitant epidemiologic and pathophysiologic mechanisms. In particular, recent changes in STEMI may depend on COVID-19 scare, leading to excess all-cause mortality, or effective reduced incidence, whereas reductions in NSTEMI may also be due to beneficial reductions in NO2 emissions in the lockdown phase.

Combined magnetic, chemical and morphoscopic analyses on lichens from a complex anthropic context in Rome, Italy.

Native and transplanted lichens were analyzed as bioaccumulators of airborne particulate matter (PM) in an eastern district of Rome, Italy, where frequent fraudulent fires are set to recover metals, mostly copper, from waste electrical and electronic equipment (WEEE). The presence of native lichens was scarce, due to the drought of spring-summer 2017, thus, sampling was extended to a neighboring area for toughening the dataset to a similar context. The magnetic analyses revealed intense properties connected to the anthropic complexity of the zone, where industrial, traffic and arson-related dusts are emitted and bio-accumulated. Magnetic and chemical analyses were compared, leading to significant linear correlations between the concentration dependent magnetic parameters (susceptibility, saturation magnetization and saturation remanence) and the concentration of heavy metals, among which copper, chrome, lead and zinc. Moreover, selected magnetic particles were chemically and morphologically characterized by Scanning Electron Microscope and Energy Dispersion System microanalyses. Magnetic particles resulted incorporated into the lichens' tissues and their composition, morphology and grain size strongly supported their anthropogenic, mostly combustion-related, origin. Even if, given the complexity of the area, it was not feasible to fully discriminate the multiple anthropogenic sources, magnetic biomonitoring of lichens, especially when combined with microtextural and compositional analyses, confirmed to be an excellent methodology for a rapid characterization of environmental pollution.