How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations.

Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44°30' N, 11°21' E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution.

How to use efficiently airborne criteria pollutants and radon-222 in source apportionment: A self-organizing maps approach.

Pollutant source apportionment represents one of the fundamental activities in environmental science. Several efficient chemometric tools are available to the scope, mostly based on multivariate techniques and usually applied to aerosol chemical speciation data. In the present work, an alternative source profiling method is proposed, based on the self-organizing maps (SOM) algorithm. Moreover, the dataset used includes typical criteria pollutants and physical parameters related to airborne particulate matter widely used as a complement of aerosol source apportionment and largely available at a higher time resolution than bulk aerosol samplings, allowing the information on the dynamic behavior of the local airshed to be extended. In this work, data was collected at a coastal location in NW Italy, between January and July 2012. Hourly concentrations of typical gaseous pollutants (SO2, NO, NO2, benzene, toluene, (m-p)-xylene, o-xylene), black-carbon and particle number concentrations by an optical particle sizer (OPS) were collected. The dataset was integrated with radon-222 activity concentration and meteorological parameters to enrich and refine the information obtained by SOM computation as well as to improve the air pollution source localization. Despite the lower specificity of criteria pollutants, the approach developed was capable of revealing distinct pollution sources such as the urban background traffic, the coal-fired power plant active at the time of the study, and the harbor, in agreement with previous PM-based source apportionment studies carried out locally, while enlightening peculiar dynamical conditions detectable at the sub-daily time scale. The application of the SOM algorithm, with the integration of meteorological parameters and atmospheric radon, proved to be very efficient in unveiling the air pollution sources.

The assessment of local geological factors for the construction of a Geogenic Radon Potential map using regression kriging. A case study from the Euganean Hills volcanic district (Italy).

The assessment of potential radon-hazardous environments is nowadays a critical issue in planning, monitoring, and developing appropriate mitigation strategies. Although some geological structures (e.g., fault systems) and other geological factors (e.g., radionuclide content, soil organic or rock weathering) can locally affect the radon occurrence, at the basis of a good implementation of radon-safe systems, optimized modelling at territorial scale is required. The use of spatial regression models, adequately combining different types of predictors, represents an invaluable tool to identify the relationships between radon and its controlling factors as well as to construct Geogenic Radon Potential (GRP) maps of an area. In this work, two GRP maps were developed based on field measurements of soil gas radon and thoron concentrations and gamma spectrometry of soil and rock samples of the Euganean Hills (northern Italy) district. A predictive model of radon concentration in soil gas was reconstructed taking into account the relationships among the soil gas radon and seven predictors: terrestrial gamma dose radiation (TGDR), thoron (220Rn), fault density (FD), soil permeability (PERM), digital terrain model (SLOPE), moisture index (TMI), heat load index (HLI). These predictors allowed to elaborate local spatial models by using the Empirical Bayesian Regression Kriging (EBRK) in order to find the best combination and define the GRP of the Euganean Hills area. A second GRP map based on the Neznal approach (GRPNEZ) has been modelled using the TGDR and 220Rn, as predictors of radon concentration, and FD as predictor of soil permeability. Then, the two GRP maps have been compared. Results highlight that the radon potential is mainly driven by the bedrock type but the presence of fault systems and topographic features play a key role in radon migration in the subsoil and its exhalation at the soil/atmosphere boundary.

Apportioning PM1 in a contrasting receptor site in the Mediterranean region: Aerosol sources with an updated sulfur speciation.

A multi-parametric experimental campaign was performed in Agri Valley (Basilicata, southern Italy) from July 2017 to January 2018. The investigated area, though basically rural and devoted to agricultural activities, hosts a huge on-shore oil reservoir, i.e. Centro Olio Val d'Agri (COVA), bringing substantial environmental modifications and impacts to the district landscape. Daily concentrations of PM1 aerosol samples, Equivalent Black Carbon and number size distributions were evaluated. Chemical aerosol speciation based on elemental and ion analyses were carried out and source apportionment by Positive Matrix Factorization (PMF) was applied to reconstruct PM1 source profile. The most significant emission sources found are torches from the oil treatment facility (37 % w/w), an unresolved factor constituted by soil resuspension, Saharan dust, and biomass burning (24 % w/w), ammonium sulphate (23 % w/w), emissions from the oil desulfurization (Claus process) (13 % w/w), and traffic + road dust (3 % w/w). SEM analysis on PM1 single particles allowed to confirm the finding from PMF including the occurrence of elemental sulfur associated with the Claus process. The novelty of the present study consists in the identification of this latter fingerprint.

Chemiluminescent fingerprints from airborne particulate matter: A luminol-based assay for the characterization of oxidative potential with kinetical implications.

In this study, a new chemiluminescent method based on the dependence of luminol light emission induced by free radicals in airborne particulate matter (PM) is proposed as a screening assay for the rapid characterization of samples from different sources based on their redox properties. This parameter is considered critical for assessing particulate matter toxicity and its impacts on human health. We propose a cell-free, luminescent assay to evaluate the redox potential of particulate matter directly on the filters employed to collect it. A joint chemometric approach based on Principal Component Analysis and Hotelling Analysis was applied to quickly sort out ambient particulate samples with a significantly different light emission profile caused by Luminol reaction. Based on Spearman correlation analysis, the association of the samples light emission intensity with their chemical composition and emission sources was attempted. The overall methodology was tested with certified reference materials and applied to two series of particulate matter samples previously subjected to thorough chemical speciation and subsequent source apportionment. The results show the effectiveness of the luminescent method, allowing the quick assessment of particulate matter oxidative potential, but providing further evidence on the complexity of the oxidative potential determination in this kind of samples. The chemometric processing of the whole dataset clearly highlights the distinct behavior among the two series of samples, the certificate standard reference materials, and the blank controls, supporting the suitability of the approach.

Particulate matter emission sources and meteorological parameters combine to shape the airborne bacteria communities in the Ligurian coast, Italy.

Aim of the present study is to explore how the chemical composition of particulate matter (PM) and meteorological conditions combine in shaping the air microbiome in Savona (Italy), a medium-size, heavily inhabited urban settlement, hosting a wide range of industrial activities. In particular, the air microbiome and PM10 were monitored over six months in 2012. During that time, the air microbiome was highly dynamic, fluctuating between different compositional states, likely resulting from the aerosolization of different microbiomes emission sources. According to our findings, this dynamic process depends on the combination of local meteorological parameters and particle emission sources, which may affect the prevalent aerosolized microbiomes, thus representing further fundamental tools for source apportionment in a holistic approach encompassing chemical as well as microbiological pollution. In particular, we showed that, in the investigated area, industrial emissions and winds blowing from the inlands combine with an airborne microbiome which include faecal microbiomes components, suggesting multiple citizens' exposure to both chemicals and microorganisms of faecal origin, as related to landscape exploitation and population density. In conclusion, our findings support the need to include monitoring of the air microbiome compositional structure as a relevant factor for the final assessment of local air quality.

Impacts of town characteristics on the changing urban climate in Vantaa.

In this work, the climatic impacts of modifying urban surface characteristics are examined for the medium-sized city of Vantaa, Finland, in the current climate and in a projected future climate of 2040-2069. In simulations with the SURFEX air-surface interaction model with a horizontal resolution of 500 m, the fraction of green spaces and relatively sparsely built suburban-type land use was increased at the expense of more densely built commercial and industrial areas. The influence of this land use intervention was found to be rather modest but comparable to the effects of the expected climate change under the RCP8.5 greenhouse gas scenario. For temperature, the climate change is the dominating effect, while wind speed is mainly controlled by surface characteristics. For relative humidity, climate change and the imposed intervention are of comparable importance. The results of this sensitivity study are intended to support policy makers by assessing the potential impact of altering the urban layout in order to improve thermal comfort or as a countermeasure to climate warming in a high-latitude city.

Deposition processes over complex topographies: Experimental data meets atmospheric modeling.

The present paper describes the assessment of the atmospheric deposition processes in a basin valley through a multidisciplinary approach based on the data collected within an extensive physico-chemical characterization of the soils, combined with the local meteorology. Surface soil cores were collected on a NNW-SSE transect across the Terni basin (Central Italy), between the Monti Martani and the Monti Sabini chains (956 m a.s.l.), featuring the heavily polluted urban and industrial enclave of Terni on its bottom. Airborne radiotracers, namely 210Pb and 137Cs, have been used to highlight atmospheric deposition. We observed an increased deposition flux of 210Pb and 137Cs at sites located at the highest altitudes, and the associated concentration profiles in soil allowed to evaluate the role of atmospheric deposition. We also obtained a comprehensive dataset of stable anthropogenic pollutants of atmospheric origin that showed heterogeneity along the transect. The behavior has been explained by the local characteristic of the soil, by seeder-feeder processes promoted by the atmospheric circulation, and was reconciled with the concentration profile of radiotracers by factor analysis. Finally, the substantial impact of the local industrial activities on soil profiles and the role of the planetary boundary layer has been discussed and supported by simulations employing a Lagrangian dispersion model.

Analysis of trends, periodicities, and correlations in the beryllium-7 time series in Northern Europe.

The activity concentrations of beryllium-7, a natural radiotracer that is considered as a tracer of the stratospheric-tropospheric exchange, shows a distinct behaviour in Northern Europe compared to the central and southern parts of the continent. In this study, we use the measurements collected at four sampling stations in Scandinavia (Ivalo, Umea, Kista, Risoe) between 2001 and 2010 and investigate their trends, periodicities and residuals with the aim to further understand the common features in the beryllium-7 data records in northern sampling sites. The beryllium-7 activity concentrations exhibit statistically significant positive trends that range from an average value of 1.50%/year to an average value of 2.96%/year. We detect a one-year periodicity in all the sites, and in the southernmost site, Risoe in Denmark, additional higher-frequency harmonics. In the residual time series, we find outliers that represent occurrences of extremely high beryllium-7 activity concentration. Cross-correlations of the beryllium-7 residuals across the four sites decrease with increasing distance; similarly, as indicated by local Hurst exponents the records exhibit long-range correlations that weaken towards the end of the investigated period. To investigate the causes of the detected trends, we also calculate correlations between beryllium-7 and factors related to its production, transport and removal from the atmosphere: in particular, cross-correlations of the beryllium-7 residuals with residuals in sunspot number, local temperature, atmospheric pressure and precipitation, as well as Arctic Oscillation index and North Atlantic Oscillation index. Most of the obtained correlations, however, are not statistically significant, highlighting the need to analyse a longer time period in order to evaluate the impact of different factors on the airborne beryllium-7 activity concentration.

Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models.

Green infrastructure (GI) in urban areas may be adopted as a passive control system to reduce air pollutant concentrations. However, current dispersion models offer limited modelling options to evaluate its impact on ambient pollutant concentrations. The scope of this review revolves around the following question: how can GI be considered in readily available dispersion models to allow evaluation of its impacts on pollutant concentrations and health risk assessment? We examined the published literature on the parameterisation of deposition velocities and datasets for both particulate matter and gaseous pollutants that are required for deposition schemes. We evaluated the limitations of different air pollution dispersion models at two spatial scales - microscale (i.e. 10-500 m) and macroscale (i.e. 5-100 km) - in considering the effects of GI on air pollutant concentrations and exposure alteration. We conclude that the deposition schemes that represent GI impacts in detail are complex, resource-intensive, and involve an abundant volume of input data. An appropriate handling of GI characteristics (such as aerodynamic effect, deposition of air pollutants and surface roughness) in dispersion models is necessary for understanding the mechanism of air pollutant concentrations simulation in presence of GI at different spatial scales. The impacts of GI on air pollutant concentrations and health risk assessment (e.g., mortality, morbidity) are partly explored. The i-Tree tool with the BenMap model has been used to estimate the health outcomes of annually-averaged air pollutant removed by deposition over GI canopies at the macroscale. However, studies relating air pollution health risk assessments due to GI-related changes in short-term exposure, via pollutant concentrations redistribution at the microscale and enhanced atmospheric pollutant dilution by increased surface roughness at the macroscale, along with deposition, are rare. Suitable treatments of all physical and chemical processes in coupled dispersion-deposition models and assessments against real-world scenarios are vital for health risk assessments.

Airborne particulate matter biotoxicity estimated by chemometric analysis on bacterial luminescence data.

In this work, PM10 samples previously subjected to thorough chemical speciation and receptor modelling, have been investigated for their bio-toxicity using an inhibition test based on bacterial luminescence modulation when in contact with airborne particulate samples. The variation of light emission intensity from a luminescent bacteria strain, the Photobacterium phosphoreum, is proposed as an efficient proxy for the quantification of bio-toxic effects induced by airborne particulate matter. PM10 samples characterized by definite levels of pollutants from the pertaining air shed were found to induce a decrease in the bacterial bioluminescence intensity, expressed as percentage of Inhibition Ratio (IR%). This behaviour suggests the decay of this energy-consuming activity because of a toxic effect. Cluster analysis on chemical composition and IR% data provides evidence of a statistically significant association between the adverse effects on living cells and the range of specific chemical species in PM10.

Assessment of lithogenic radioactivity in the Euganean Hills magmatic district (NE Italy).

The Euganean Hills of North East Italy have long been recognised as an area characterized by a higher than average natural radiation background. This is due to two main reasons: a) primary lithogenic radiation due to rhyolitic and trachytic outcrops, which are "acidic alkaline" magmatic rocks potentially enriched in uranium and thorium; b) secondary sources related to a geothermal field - widely exploited for spa tourism in the area since the Roman age - producing surface release of radon-enriched fluids. Though radioactivity levels in the Euganean district have been often investigated in the past - including recent works aimed at assessing the radiation doses from radon and/or total gamma radiation - no effort has been put so far into producing a thorough assessment linking radiation protection data to geological-structural features (lithology, faults, water, organic matter content, etc.). This work represents the first part of the interdisciplinary project "Geological and geochemical control on Radon occurrence and natural radioactivity in the Euganean Hills district (North-Eastern Italy)", aimed at producing detailed results of the actual radiation levels in connection mainly with lithological parameters. A detailed sampling strategy, based on lithostratigraphy, petrology and mineralogy, has been adopted. The 151 rock samples collected were analyzed by high resolution γ-ray spectrometry with ex situ HPGe detectors. Statistical and geostatistical analyses were performed, and outlier values of U and Th - possibly associated with anomalies in the geological formation - were identified. U, Th and K concentration maps were developed using both the entire database and then again after expunging the outliers; the two were then compared. In all maps the highest values can be associated to trachyte and rhyolite lithologies, and the lowest ones to sedimentary formations. The external dose due to natural radionuclides in the soil - the so called terrestrial gamma dose rate - has been calculated using the U, Th and K distribution measured in the bedrock samples.

Variation in airborne 134Cs, 137Cs, particulate 131I and 7Be maximum activities at high-altitude European locations after the arrival of Fukushima-labeled air masses.

The Fukushima-labeled air mass arrival, and later the cesium-134 (134Cs), cesium-137 (137Cs) and particulate iodine-131 (hereafter noted 131Ip) maximum levels were registered in Europe at different dates depending on the location. Most of those data were obtained at low-altitude sampling areas. Here, we compare the airborne levels registered at different high-altitude European locations (from 850 m to about 3500 m). The integrated 137Cs activity concentration was not uniform with regard to the altitude even after a long travel time/distance from Japan. Moreover, the relation of integrated 137Cs vs. altitude showed a linear decrease up to an altitude of about 3000 m. A similar trend was noticed for 131Ip (particulate fraction) while it increased above 3000 m. Comparison with 7Be activity concentration showed that, as far as the high altitude location is concerned, the 137Cs and 134Cs maximum concentrations corresponded to the 7Be maximum, suggesting downdraft movements from high tropospheric or stratospheric layers to be responsible for 137,134Cs increase and peak values. This was also confirmed by high potential vorticity and low relative humidity registered during the peak values.

Comparison of radioactivity data measured in PM10 aerosol samples at two elevated stations in northern Italy during the Fukushima event.

The follow-up of Fukushima radioactive plume resulting from the 11th March 2011 devastating tsunami is discussed for two Italian stations in the northern Apennines: Mt. Cimone (Modena) and Montecuccolino (Bologna). Radioactivity data collected at both stations are described, including comparison between local natural background of airborne particulate and artificial radioactivity referable to the arrival of the radioactive plume and its persistence and evolution. Analysis of back-trajectories was used to confirm the arrival of artificial radionuclides following atmospheric transport and processing. The Fukushima plume was first detected on 3rd April 2011 when high volume sampling revealed the presence of the artificial radionuclides (131)I, (137)Cs and (134)Cs. The highest activity concentrations of these nuclides were detected on 5th April 2011 at the Montecuccolino site. Fukushima radioactivity data at the two stations were usually comparable, suggesting a good vertical mixing of the plume; discrepancies were occasional and attributed to different occurrence of wet removal, typically characterized by a scattered spatial pattern. To understand the relevance to the local population of the extra dose due to the Fukushima plume, atmospheric activities of the related artificial nuclides were compared to those of the main natural radionuclides in ambient particulate, and found to be lower by over one order of magnitude. Radiation doses referable to Fukushima, maximized for a whole year occurrence at the highest activity level observed at our stations in the weeks affected by the Japanese plume, were estimated at 1.1 µSv/year.