Climatology of atmospheric PM10 concentration in the Po Valley

The limits to atmospheric pollutant concentration set by the European Commission provide a challenging target for the municipalities in the Po Valley, because of the characteristic climatic conditions and high population density of this region. In order to assess climatology and trends in the concentration of atmospheric particles in the Po Valley, a dataset of PM10 data from 41 sites across the Po Valley have been analysed, including both traffic and background sites (either urban, suburban or rural). Of these 41 sites, 18 with 10 yr or longer record have been analysed for long term trend in de-seasonalized monthly means, in annual quantiles and in monthly frequency distribution. A widespread significant decreasing trend has been observed at most sites, up to few percent per year, by Generalised Least Square and Theil-Sen method. All 41 sites have been tested for significant weekly periodicity by Kruskal–Wallis test for mean anomalies and by Wilcoxon test for weekend effect magnitude. A significant weekly periodicity has been observed for most PM10 series, particularly in summer and ascribed mainly to anthropic particulate emissions. A cluster analysis has been applied in order to highlight stations sharing similar pollution conditions over the reference period. Five clusters have been found, two gathering the metropolitan areas of Torino and Milano and their respective nearby sites and the other three clusters gathering north-east, north-west and central Po Valley sites respectively. Finally the observed trends in atmospheric PM10 have been compared to trends in provincial emissions of particulates and PM precursors, and analysed along with data on vehicular fleet age, composition and fuel sales. Significant basin-wide drop in emissions occurred for gaseous pollutants, contrarily to emissions of PM10 and PM2.5, whose drop resulted low and restricted to few provinces. It is not clear whether the decrease for only gaseous emissions is sufficient to explain the observed drop in atmospheric PM10, or if the low drop in particulate emissions is indeed due to the uncertainty in the emission inventory data for this species

Long-term trend and variability of atmospheric PM10 concentration in the Po Valley

The limits to atmospheric pollutant concentration set by the European Commission provide a challenging target for the municipalities in the Po Valley, because of the characteristic climatic conditions and high population density of this region. In order to assess climatology and trends in the concentration of atmospheric particles in the Po Valley, a data set of PM10 data from 41 sites across the Po Valley have been analysed, including both traffic and background sites (either urban, suburban or rural). Of these 41 sites, 18 with 10 yr or longer record have been analysed for long-term trend in deseasonalized monthly means, in annual quantiles and in monthly frequency distribution. A widespread significant decreasing trend has been observed at most sites, up to a few percent per year, by a generalized least squares and Theil–Sen method. All 41 sites have been tested for significant weekly periodicity by Kruskal–Wallis test for mean anomalies and by Wilcoxon test for weekend effect magnitude. A significant weekly periodicity has been observed for most PM10 series, particularly in summer and ascribed mainly to anthropic particulate emissions. A cluster analysis has been applied in order to highlight stations sharing similar pollution conditions over the reference period. Five clusters have been found, two encompassing the metropolitan areas of Turin and Milan and their respective nearby sites and the other three clusters gathering northeast, northwest and central Po Valley sites respectively. Finally, the observed trends in atmospheric PM10 have been compared to trends in provincial emissions of particulates and PM precursors, and analysed along with data on vehicular fleet age, composition and fuel sales. A significant basin-wide drop in emissions occurred for gaseous pollutants, contrarily to emissions of PM10 and PM2.5, whose drop was low and restricted to a few provinces. It is not clear whether the decrease for only gaseous emissions is sufficient to explain the observed drop in atmospheric PM10, or if the low drop in particulate emissions is indeed due to the uncertainty in the emission inventory data for this species

Trends and variability of atmospheric PM2.5 and PM10-2.5 concentration in the Po Valley, Italy

The Po Valley is one of the largest European regions with a remarkably high concentration level of atmospheric pollutants, both for particulate and gaseous compounds. In the last decade stringent regulations on air quality standards and on anthropogenic emissions have been set by the European Commission, including also for PM2.5 and its main components since 2008. These regulations have led to an overall improvement in air quality across Europe, including the Po Valley and specifically PM10, as shown in a previous study by Bigi and Ghermandi (2014). In order to assess the trend and variability in PM2.5 in the Po Valley and its role in the decrease in PM10, we analysed daily gravimetric equivalent concentration of PM2.5 and of PM10-2.5 at 44 and 15 sites respectively across the Po Valley. The duration of the times series investigated in this work ranges from 7 to 10 years. For both PM sizes, the trend in deseasonalized monthly means, annual quantiles and in monthly frequency distribution was estimated: this showed a significant decreasing trend at several sites for both size fractions and mostly occurring in winter. All series were tested for a significant weekly periodicity (a proxy to estimate the impact of primary anthropogenic emissions), yielding positive results for summer PM2.5 and for summer and winter PM10-2.5. Hierarchical cluster analysis showed moderate variability in PM2.5 across the valley, with two to three main clusters, dividing the area in western, eastern and southern/Apennines foothill sectors. The trend in atmospheric concentration was compared with the time series of local emissions, vehicular fleet details and fuel sales, suggesting that the decrease in PM2.5 and in PM10 originates from a drop both in primary and in precursors of secondary inorganic aerosol emissions, largely ascribed to vehicular traffic. Potentially, the increase in biomass burning emissions in winter and the modest decrease in NH3 weaken an otherwise even larger drop in atmospheric concentrations

Past and Future Precipitation Trend Analysis for the City of Niamey (Niger): An Overview

Despite the interest in detecting the extremes of climate in the West African Sahel, few studies have been specifically conducted on the Republic of Niger. This research focuses on past, present, and future precipitation trends for the city of Niamey through the combined assessment of WMO precipitation indices using RClimDex and the Standardized Precipitation Index. Past daily precipitation data were derived from a 60-year reconstructed meteorological dataset for the Niamey airport station for the period of 1950–2009 and validated through comparison with an observed time series at Niamey airport (1980–2012). Precipitation analysis confirms the literature’s findings, in particular, a decreasing trend in total precipitation over the period of 1950–2009, and a positive trend for data that spans over the period of 1980–2009, suggesting a precipitation recovery after the dry epoch (1968–1985), even if the deficit with the wettest years in the period of 1950–1968 has not been made up. Furthermore, WATCH-Forcing-Data-ERA-Interim projections, elaborated under RCP 4.5 and RCP 8.5 socio-economic conditions, show that precipitation will increase in the future. Therefore, the Nigerien population will benefit from increased rainfall, but will also have to cope with the exacerbation of both flood and drought risks due to a great interannual variability that can positively or negatively influence water availability

Analysis of the air pollution climate at a background site in the Po valley

The Po valley in northern Italy is renowned for its high air pollutant concentrations. Measurements of air pollutants from a background site in Modena, a town of 200 thousand inhabitants within the Po valley, are analysed. These comprise hourly data for CO, NO, NO2, NOx, and O3, and daily gravimetric equivalent data for PM10 from 1998\u20132010. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and auto-correlation and cross-correlation functions. CO, NO and NO2 exhibit a strongly traffic-related pattern, with daily peaks at morning and evening rush hour and lower concentrations over the weekend. Ozone shows an annual cycle with a peak in July due to local production; notwithstanding the diurnal cycle dominated by titration by nitrogen oxide, the decreasing long term trend in NO concentration did not affect the long term trend in O3, whose mean concentration remained steady over the sampling period. PM10 shows a strong seasonality with higher concentration in winter and lower concentration in summer and spring. Both PM10 and ozone show a marked weekly cycle in summer and winter respectively. Regressions of PM10 upon NOx show a consistently greater intercept in winter, representing higher secondary PM10 in the cooler months of the year. There is a seasonal pattern in primary PM10 to NOx ratios, with lower values in winter and higher values in summer, but the reasons are unclear

Photocatalytic-treated asphalt road in Copenhagen for urban NOx removal

Atmospheric nitrogen oxides ([Formula: see text] ) are key pollutants and short-lived climate forcers contributing to acid rain, photochemical smog, aerosol formation and climate change. Exposure to nitrogen dioxide ([Formula: see text] ) emitted mainly from transportation, causes adverse health effects associated with respiratory illnesses and increased mortality even at low concentration. Application of titanium dioxide ([Formula: see text] )-based photocatalysis in urban environment is a new air cleaning solution, activated by sunlight and water vapour to produce OH radicals, able to remove [Formula: see text] and other pollutants from the planetary boundary layer. This study is a large-scale evaluation of [Formula: see text] removal efficiency at a near-road environment with applied photocatalytic NOxOFF™ technology on an urban road west of Copenhagen, thus supporting local municipality in meeting their clean-air Agenda 2030. The photocatalytic NOxOFF™ granulate containing [Formula: see text] nanoparticles was applied on an asphalt road in July 2020 and ambient [Formula: see text] was measured during a six-month monitoring campaign. It is the first [Formula: see text] monitoring campaign carried out at this road and specific efforts have been devoted to evaluate the reduction in ambient [Formula: see text] levels with NOxOFF™-treated asphalt. Several methods were used to evaluate the photocatalytic effect, taking into account analysis limitations such as the short reference period prior to application and the highly uncertain measurement period during which SARS-CoV-2 lockdown measures impacted air quality. There was no statistically significant difference in [Formula: see text] concentrations between the reference period and the photocatalytic active period and NO removal efficiency resulted in [Formula: see text] (± 1.27). An upper limit removal of 17.5% [Formula: see text] was estimated using a kinetic tunnel model. While [Formula: see text] comparison with COPERT V street traffic model projection was roughly estimated to decrease by 39% (± 38%), although this estimate is subject to high uncertainty. The observed annual mean [Formula: see text] concentration complies with Frederiksberg clean-air Agenda 2030 and air quality standards. GRAPHICAL ABSTRACT: A graphical abstract illustrating the air cleaning properties of [Formula: see text] -based photocatalytic-treated asphalt [Image: see text

Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows

VERT (Vehicular Emissions from Road Traffic) is an R package developed to estimate traffic emissions of a wide range of pollutants and greenhouse gases based on traffic estimates and vehicle fleet composition data, following the EMEP/EEA methodology. Compared to other tools available in the literature, VERT is characterised by its ease of use and rapid configuration, while it maintains great flexibility in user input. It is capable of estimating exhaust, non-exhaust, resuspension, and evaporative emissions and is designed to accommodate future updates of available emission factors. In this paper, case studies conducted at both urban and regional scales demonstrate VERT's ability to accurately assess transport emissions. In an urban setting, VERT is integrated with the Lagrangian dispersion model GRAMM–GRAL and provides NOx concentrations in line with observed trends at monitoring stations, especially near traffic hotspots. On a regional scale, VERT simulations provide emission estimates that are highly consistent with the reference inventories for the Emilia-Romagna region (Italy). These findings make VERT a valuable tool for air quality management and traffic emission scenario assessment

Association between outdoor traffic air pollutants and spread of SARS-CoV-2 pandemic in Modena, Northern Italy

BACKGROUND AND AIM: Italy was the first European country severely affected by the SARS-CoV-2 pandemic, especially during the first wave in the North of the country. In particular, Modena is a city of Emilia-Romagna which is a region entirely included in the Po valley, one of European areas characterized by the heaviest air pollution levels due also to its orography. Previous studies yielded at a regional level suggested that higher air pollutant levels may increase both SARS-CoV-2 infection and mortality. METHODS: In this study, we further investigated the association between air pollutant exposure and spread of the SARS-CoV-2 using data collected from Modena municipality in the period February 2020-April 2021. We used traffic pollutant levels collected from an urban air quality monitoring station in the period January 2020-January 2021, including particulate matter (PM10), nitrogen oxides (NO2 and NOx), benzene, and black carbon (BC). We used a random-effects linear regression model within panel data analysis over the study period and we computed beta correlation coefficients (beta) with 95% confidence interval-CI between mean daily pollutant concentrations and SARS-CoV-2 daily positive cases diagnosed in Modena. RESULTS:We found a positive correlation between all traffic pollutants and SARS-CoV-2 cases, namely for PM10 beta was 1.23 (95%CI 1.00-1.46), lower for NOx (beta=0.66, 95%CI 0.56-0.75), and higher for NO2 (beta=1.95, 95%CI 1.59-2.31), benzene (beta=41.41, 95%CI 36.23-46.59), and BC (beta=5.95, 95%CI 1.19-10.72). CONCLUSIONS:Notwithstanding the limitations of use of aggregated data and potential the residual confounding, these findings seem to support the hypothesis that high levels of air pollution may favor the spread of SARS-CoV-2 infection, or alternatively that they reflect a higher mobility and number of social contacts that favor the spread of the infection. KEYWORDS: Air pollution, Traffic-related, Infectious diseases, Environmental epidemiology, Exposure assessmen