Search

Over the last decades, the concern about air pollution has increased significantly, especially in urban areas. Active sampling of air pollutants requires specific instrumentation not always available in all the laboratories. Passive sampling has a lower cost than active alternatives but still requires efforts to cover extensive areas. The use of biological systems as passive samplers might be a solution that provides information about air pollution to assist decision-makers in environmental health and urban planning. This study aims to employ subaerial biofilms (SABs) growing naturally on façades of historical and recent constructions as natural passive biomonitors of atmospheric heavy metals pollution. Concretely, SABs spontaneously growing on constructions located in a tropical climate, like the one of the city of Barranquilla (Colombia), have been used to develop the methodological approach here presented as an alternative to SABS grown under laboratory conditions. After a proper identification of the biocolonizers in the SAB through taxonomic and morphological observations, the study of the particulate matter accumulated on the SABs of five constructions was conducted under a multi-analytical approach based mainly on elemental imaging studies by micro Energy Dispersive X-ray fluorescence spectrometry (μ-EDXRF) and Scanning Electron Microscopy coupled with Energy Dispersive X-ray spectrometry (SEM-EDS) techniques, trying to reduce the time needed and associated costs. This methodology allowed to discriminate metals that are part of the original structure of the SABs, from those coming from the anthropogenic emissions. The whole methodology applied assisted the identification of the main metallic particles that could be associated with nearby anthropogenic sources of emission such as Zn, Fe, Mn, Ni and Ti by SEM-EDS and by μ-EDXRF Ba, Sb, Sn, Cl and Br apart others; revealing that it could be used as a good alternative for a rapid screening of the atmospheric heavy metals pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In analytical chemistry, biomonitoring is known as the methodology, which consider the use of living organisms to monitor and assess the impact of different contaminants in a known area. This type of monitoring is a relatively inexpensive method and easy to implement, being a viable alternative to be developed in sites where there is no infrastructure/instruments for a convenctional air quality monitoring. These organisms, having the capability to monitor the pollution, are also known as passive biomonitors (PBs), since they are able to identify possible contamination sources without the need of any additional tool. In this work, a multianalytical methodology was applied to verify the usefulness of naturally growing Grimmia genus mosses as PBs of atmospheric heavy metals pollution. Once mosses were identified according to their morphology and taxonomy, thei ability to accumulate particulate matter (PM) was determined by SEM. EDS coupled to SEM also allowed to identify the main metallic particles deposited and finally, an acid digestion of the mosses and a subsequent ICP-MS study define more precisely the levels of metals accumulated on each collected moss. The study was focused on six sampling locations from the Bilbao Metropolitan area (Biscay, Basque Country, north of Spain). The experimental evidences obtained allowed to propose naturally growing Grimmia genus as PB of atmospheric heavy metals pollution and to identify the anthropogenic sources that contribute to the emission of the airborne particulate matter rich in metals, evaluating in this sense the atmospheric heavy metals pollution of the selected locations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Speciation of respirable particles is becoming increasingly important from an epidemiological and analytical point of view to determine the potential effects of air pollution on human health. For this reason, current laws and analytical sampling methods focus on particle size, as it turns out to be the main factor for the greater or lesser penetration into the airways. In this sense, particles of less than 10 μm in diameter (<10 μm), referred to as PM 10 , are the particles that have a higher capacity for access to the respiratory tract and, therefore, more significant effect on them. In this sense, one of the most important factors that have a key role in the PM 10 atmospheric pollution effect is the dispersion effect with the direct influence of natural effects such as wind, rain, topography apart from others. In this work, PM 10 data extracted from the Basque Government environmental stations (19 sampling points) in the Biscay province (Basque Country, north of Spain) were combined with the results obtained from the use of self-made passive samplers (SMPS) in the same sampling points areas and subsequently, the sample analysis with a non-invasive elemental technique (Scanning Electron Microscope coupled to Energy Dispersive X-ray Spectrometry) was carried out. Thanks to this methodology, it was possible to determine a wide variety of metals in PM 10 such as Al, Fe, Cr, Ni, Pb, Zn, Ti, etc. Most of them present as oxides and others as part of natural aggregations such as quartz, aluminosilicates, phosphates etc., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Machu Picchu is an archaeological Inca sanctuary from the 15th century, located 2430 m above the sea level in the Cusco Region, Peru. In 1983, it was declared World Heritage Site by UNESCO. The surroundings and soils from the entire archaeological site are carefully preserved together with its grass parks. Due to the importance of the archaeological city and its surroundings, the Decentralized Culture Directorate of Cusco-PAN Machu Picchu decided to carry out a careful monitoring study in order to determine the ecological status of the soils. In this work, elemental and molecular characterization of 17 soils collected along the entire park was performed by means of X-ray Diffraction (XRD) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) after acidic digestion assisted by microwave energy. Thanks to the combination of these analytical techniques, it was possible to obtain the mineral composition and metal concentrations of all soils from these 17 sampling points. Finally, different statistical treatments were carried out in order to confirm the ecological status of the different sampling points from Machu Picchu archaeological site concluding that soils are not impacted., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Soils around coal mining are important reservoir of hazardous elements (HEs), nanominerals, and ultrafine compounds. This research reports and discusses the soil concentrations of HEs (As, Cd, Cr, Cu, Ni, Pb, and Zn) in coal residues of abandoned mines. To assess differences regarding environmental impact and risk assessment between coal abandoned mines from the Santa Catarina state, eighteen coal cleaning rejects with different mineralogical and chemical composition, from eight abandoned mines were collected. Nanominerals and ultra-fine minerals from mining-contaminated areas were analyzed by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and high-resolution transmission electron microscope (HR-TEM), providing new information on the mineralogy and nano-mineralogy of these coal residues. The total contents of 57 elements (HEs, alkali metals, and rare earth elements) were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The calculation of NWACs (Normalized Average Weighted Concentration), together with the chemometric analysis by Principal component analysis (PCA) confirmed the variability of the samples regarding their city and their mine of origin. Moreover, the results confirmed the existence of hotspots in mines near urban areas., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The extent of vertical contamination is intimately related to the soil solution and surface chemistry of the soil matrix with reference to the metal and waste matrix in question. The present research demonstrated the impact that the dissolved CO2 of the meteoric waters, which acidify the environment with pH values below 4, has in the increase of the metal mobility. Although under the given conditions the Zn remains mainly dissolved, the initial PbS and ZnS have evolved into newly formed secondary carbonates and sulphates (i.e., hydrozincite, gunningite, hydrocerussite) that can be found in the efflorescences. The chemical simulation done on the weathering of the original sulphide ores for the formation of these secondary minerals has proved the transient storage mainly of Pb. Nonetheless, many of the minerals formed inside the galleries will be easily dissolved in the next rains and release in an ionic form to the groundwater. The analytical procedure exposed has been proved to be useful not only for the characterization of AMD but also for the prediction of the mobility of metals., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Chemometrics are increasingly used in environmental monitoring studies, but are still far from being accepted as routine tools by field specialists. The multivariate character of usually highly correlated environmental data recommends the use of advanced chemometrics as part of the analytical methodology in order to get information on the basic structure of data. In this work, we have applied a battery of non-supervised (Principal Component Analysis (PCA)) and supervised (k-Nearest Neighbour (k-NN), Soft Independent Modelling of Class Analogies (SIMCA), Linear Discriminant Analysis (LDA) and Artificial Neural Networks (ANNs)) multivariate techniques on a specific environmental dataset. The dataset consists on the concentration of 14 elements (Al, As, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Sn, V and Zn) in 95 sediments collected at eight different locations of the estuary of the Nerbioi-Ibaizabal River (Bilbao, Basque Country) during 12 sampling campaigns conducted every 3 months between 2005 and 2008. The study aims to present a simple methodology of general applicability which may result in a flexible and practical tool to assess chemical pollution in sediments of a given specific site., (Copyright © 2011 Elsevier Ltd. All rights reserved.)