In this study, we have evaluated the efficiency of a chemical fractionation procedure for the characterization of both the water-soluble and the insoluble fraction of the main elemental components of particulate matter (PM) deposited on urban leaves. The proposed analytical approach is based on the chemical analysis of leaf washing solutions and membrane filters used for their filtration. The ionic concentration of leaf washing solutions was compared with their electrical conductivity, making it a valuable proxy for the quantification of the water-soluble and ionic fraction of leaf deposited PM. The chemical composition of both the water-soluble and the insoluble fraction of PM, resulting from this fractionation procedure, was compared with results obtained by scanning electron microscopy coupled with energy-dispersed X-Rays spectroscopy (SEM/EDX) and processed through chemometrics. Results obtained proved that the proposed approach is able to provide an estimation of total leaf deposited PM and it is highly reliable for the evaluation of the emission impact of different PM sources, being able to increase the selectivity of PM elemental components as specific source tracers; consequently providing useful information also for the assessment of human health risks.
Areas covered by seminatural grasslands have been in constant decline for decades in Europe. This trend is particularly strong for mountain territories, where such traditional agricultural practices as cattle grazing are no longer economically feasible. This study was conducted in the subalpine pasture of Cinte Tesino (TN, Italy), where local farmers have applied the following different management strategies: shorter and longer grazing durations during the season and a complete abandonment for the last 15 years. We aimed to study how these different management strategies impact the functioning and diversity of vegetation and the chemical and biological characteristics of the soil. Species richness was higher in plots subjected to longer grazing with a prevalence of D. caespitosa in terms of biomass share. A decline in species richness in abandoned plots was accompanied by an increase in the share of other graminoids in collected biomass. A concomitant increase in leaf N concentration and light availability in grazed plots resulted in higher photosynthetic efficiency in some species, as revealed by the δ13C of plant tissues. Soils under grazing were characterised by a higher concentration of total and extractable N, almost doubled microbial biomass C and increased extracellular enzymes activity, evidencing nutrient cycling mobilization. While the microbial pool was characterised by lower mineralization rates, C was lost from the soil with 15 years of abandonment. The longer grazing season demonstrated to be the most beneficial, promoting species richness, C accumulation and better soil microbial functioning. A change in soil pH from strongly acidic to moderately acidic with longer grazing is likely one of the important factors adding to the success in the functioning of primary producers and decomposers in this site.
Wildfires across the Mediterranean ecosystems are associated with safety concerns due to their emissions. The type of biomass determines the composition of particulate matter (PM) and gaseous compounds emitted during the fire event. This study investigated simulated fire events and analysed biomass samples of six Mediterranean species and litter in a combustion chamber. The main aims are the characterization of PM realized through scanning electron microscopy (SEM/EDX), the quantification of gaseous emissions through gas chromatography (GC-MS) and, consequently, identification of the species that are potentially more dangerous. For PM, three size fractions were considered (PM10, 2.5 and 1), and their chemical composition was used for particle source-apportionment. For gaseous components, the CO, CO2, benzene, toluene and xylene (BTXs) emitted were quantified. All samples were described and compared based on their peculiar particulate and gaseous emissions. The primary results show that (a) Acacia saligna was noticeable for the highest number of particles emitted and remarkable values of KCl; (b) tree species were related to the fine windblown particles as canopies intercept PM10 and reemit it during burning; (c) shrub species were related to the particles resuspended from soil; and (d) benzene and toluene were the dominant aromatic compounds emitted. Finally, the most dangerous species identified during burning were Acacia saligna, for the highest number of particles emitted, and Pistacia lentiscus for its high density of particles, the presence of anthropogenic markers, and the highest emissions of all gaseous compounds.
The normalized difference vegetation index (NDVI) is commonly used to detect spatiotemporal changes of vegetation cover. This study modeled the spatiotemporal changes of land cover on Pianosa Island, Italy, in the period 1999–2015, using the multi-temporal Landsat images. Since the end of the 1990s, the natural vegetation has been re-colonizing an area of abandoned agricultural land and the island is undergoing a process of re-naturalization in harsh (drought and hot) environmental conditions. Hence, it is an ideal test site to monitor the effects of anthropogenic and climatic stressors on vegetation dynamics under Mediterranean climate. In this work, we proposed a new statistical approach based on a pixel-by-pixel analysis of multi-temporal Landsat images. Mean (µ) and standard deviation (σ) values of the NDVI images taken in 2015 were used for the determination of the pixel thresholds (µ ± 3σ). The evaluation of land cover change was carried out by comparing the µ value of a single NDVI pixel for 2015 with the same pixel of different years of the study period. The results indicate that surface reflectance (SR) Landsat images are more suitable in detecting the vegetation dynamics on the island than the top of atmosphere (TOA) ones and highlight an increasing trend of vegetation cover on Pianosa Island, mainly during the early seven years following the land abandonment in all the main land cover classes: abandoned crops and pastures, Mediterranean macchia, and woodland. However, the abandoned agricultural and pasture areas showed a higher increase in the vegetation cover and a shift in the shape of the normalized frequency distribution of the SR NDVI data during the study period, suggesting that a colonization process from other vegetation classes is occurring (i.e., Mediterranean macchia and trees are colonizing the abandoned land, partly replacing herbaceous species). Our data highlight that the statistical approach applied in this study is suitable for detecting vegetation cover changes associated with anthropogenic and climatic drivers in a typical Mediterranean environment and could be proposed as a new methodological approach in several other land monitoring studies.
Particulate matter represents a serious hazard to human health, and air quality models contribute to the understanding of its dispersion. This study describes particulate matter with a ≤10 μm diameter (PM10) dynamics in an urban–industrial area, through the comparison of three datasets: modeled (TAPM—The Air Pollution Model), measured concentration (environmental control stations—ECS), and leaf deposition values. Results showed a good agreement between ECS and TAPM data. A steel plant area was used as a PM10 emissions reference source, in relation to the four sampling areas, and a distance/wind-based factor was introduced (Steel Factor, SF). Through SF, the three datasets were compared. The SF was able to describe the PM10 dispersion values for ECS and leaf deposition (r2 = 0.61–0.94 for ECS; r2 = 0.45–0.70 for leaf); no relationship was found for TAPM results. Differences between measured and modeled data can be due to discrepancies in one district and explained by a lack of PM10 inventory for the steel plant emissions. The study suggests the use of TAPM as a suitable tool for PM10 modeling at the urban scale. Moreover, tree leaves are a low-cost tool to evaluate the urban environmental quality, by providing information on whether and when data from leaf deposition can be used as a proxy for air pollution concentration. Further studies to include the re-suspension of particles as a PM10 source within emission inventories are suggested.
Addressing the planetary crisis associated with climate change, biodiversity loss, global pollution, and public health requires novel and holistic approaches. Here, we present the methodology and initial results of an experiment conducted in Rome within the framework of the National Biodiversity Future Center (NBFC) project, Spoke 6. The major objective of this study was to outline the planetary health approach as a lens to assess urban health. This transdisciplinary case study explored the relationship between urban traffic-related external exposome and pro-oxidative responses in humans and plants. This methodology is based on the integration of atmospheric dynamics modeling, state-of-the-art aerosol measurements, biomonitoring in human cohorts, in vitro cellular assays, and the assessment of functional trait markers in urban trees. The results indicate that short-term exposure to urban aerosols, even at low concentrations, triggers rapid oxidative and inflammatory responses in bronchial epithelial cells, modulates gene and miRNA expression, alters gut microbiota diversity, and induces functional trait changes in urban trees. This study also highlights the feedback mechanisms between vegetation and atmospheric conditions, emphasizing the role of urban greenery in modulating microclimate and exposure. The methodology and initial results presented here will be further analyzed in future studies to explore proof of a cause–effect relationship between short-term exposure to traffic-related environmental stressors in urban areas and oxidative stress in humans and plants, with implications for chronic responses. In a highly urbanized world, this evidence could be pivotal in motivating the widespread implementation of planetary health approaches for assessing urban health.