Spatiotemporal correlation of urban pollutants by long-term measurements on a mobile observation platform.

We conducted a three-year campaign of atmospheric pollutant measurements exploiting portable instrumentation deployed on a mobile cabin of a public transport system. Size selected particulate matter (PM) and nitrogen monoxide (NO) were measured at high temporal and spatial resolution. The dataset was complemented with measurements of vehicular traffic counts and a comprehensive set of meteorological covariates. Pollutants showed a distinctive spatiotemporal structure in the urban environment. Spatiotemporal autocorrelations were analyzed by a hierarchical spatiotemporal statistical model. Specifically, particles smaller than 1.1 µm exhibited a robust temporal autocorrelation with those at the previous hour and tended to accumulate steadily during the week with a maximum on Fridays. The smallest particles (mean diameter 340 nm) showed a spatial correlation distance of ≈600 m. The spatial correlation distance reduces to ≈ 60 m for particle diameters larger than 1.1 µm, which also showed peaks at the stations correlated with the transport system itself. NO showed a temporal correlation comparable to that of particles of 5.0 µm of diameter and a correlating distance of 155 m. The spatial structure of NO correlated with that of the smallest sized particles. A generalized additive mixed model was employed to disentangle the effects of traffic and other covariates on PM concentrations. A reduction of 50% of the vehicles produces a reduction of the fine particles of -13% and of the coarse particle number of -7.5%. The atmospheric stability was responsible for the most significant effect on fine particle concentration.

Airborne bacteria and persistent organic pollutants associated with an intense Saharan dust event in the Central Mediterranean.

In this paper, we present a comprehensive taxonomic survey of the bacterial community and accurate quantification of polycyclic aromatic hydrocarbons (PAHs) associated with an intense Saharan dust advection, which impacted Central Mediterranean area in the whole 2014-2015 period. This work is part of an intensive field campaign at the EMEP regional background site of Monte Martano (Central Italy), considered well representative of long-range transport in the Central Mediterranean area. 22 samples have been characterized in their provenance region and have been considered for the chemical and biological characterization. The event described in the present paper was exceptionally intense at the sampling site allowing a detailed evaluation of the dust load on a regional scale, an estimation of the impact of PAH based on the Toxic Equivalency Factor methodology and a thorough characterization of the airborne bacterial fraction performed by High Throughput Sequencing approach. Afterward, we cultured viable bacteria and evaluated several enzymatic activities and conducted UV survival tests. Principal findings include: (i) the striking evidence that, during the Saharan dust event, a highly diverse and abundant bacterial community was associated with PAH concentrations higher than the yearly mean; (ii) the tangible presence of cultivable microbes; (iii) the proof that the isolates recovered from Saharan dust had the potential to be metabolically active and that almost all of them were able to persist following UV radiation exposure. Comparisons of results for the present case study with mean values for the 2014-2015 experimental campaign are presented. The bacterial community and chemical speciation associated with the Saharan dust advection were specific and very different from those associated with other air masses. The particular case of North-Western Atlantic, which represents one of the most typical advection route reaching the sampling site is discussed in detail.

Functional exploratory data analysis for high-resolution measurements of urban particulate matter.

In this work we propose the use of functional data analysis (FDA) to deal with a very large dataset of atmospheric aerosol size distribution resolved in both space and time. Data come from a mobile measurement platform in the town of Perugia (Central Italy). An OPC (Optical Particle Counter) is integrated on a cabin of the Minimetrò, an urban transportation system, that moves along a monorail on a line transect of the town. The OPC takes a sample of air every six seconds and counts the number of particles of urban aerosols with a diameter between 0.28 µm and 10 µm and classifies such particles into 21 size bins according to their diameter. Here, we adopt a 2D functional data representation for each of the 21 spatiotemporal series. In fact, space is unidimensional since it is measured as the distance on the monorail from the base station of the Minimetrò. FDA allows for a reduction of the dimensionality of each dataset and accounts for the high space-time resolution of the data. Functional cluster analysis is then performed to search for similarities among the 21 size channels in terms of their spatiotemporal pattern. Results provide a good classification of the 21 size bins into a relatively small number of groups (between three and four) according to the season of the year. Groups including coarser particles have more similar patterns, while those including finer particles show a more different behavior according to the period of the year. Such features are consistent with the physics of atmospheric aerosol and the highlighted patterns provide a very useful ground for prospective model-based studies.