Contribution of micro-PIXE to the characterization of settled dust events in an urban area affected by industrial activities

Strawberry Plant as a Biomonitor of Trace Metal Air Pollution-A Citizen Science Approach in an Urban-Industrial Area near Lisbon, Portugal

A biomonitoring study of air pollution was developed in an urban-industrial area (Seixal, Portugal) using leaves of strawberry plants (Fragaria × ananassa Duchesne ex Rozier) as biomonitors to identify the main sources and hotspots of air pollution in the study area. The distribution of exposed strawberry plants in the area was based on a citizen science approach, where residents were invited to have the plants exposed outside their homes. Samples were collected from a total of 49 different locations, and their chemical composition was analyzed for 22 chemical elements using X-ray Fluorescence spectrometry. Source apportionment tools, such as enrichment factors and principal component analysis (PCA), were used to identify three different sources, one geogenic and two anthropogenic (steel industry and traffic), besides plant major nutrients. The spatial distribution of elemental concentrations allowed the identification of the main pollution hotspots in the study area. The reliability of using strawberry leaves as biomonitors of air pollution was evaluated by comparing them with the performance of transplanted lichens by regression analysis, and a significant relation was found for Fe, Pb, Ti, and Zn, although with a different accumulation degree for the two biomonitors. Furthermore, by applying PCA to the lichen results, the same pollution sources were identified.

Source apportionment of PM2.5 before and after COVID-19 lockdown in an urban-industrial area of the Lisbon metropolitan area, Portugal

The lockdowns held due to the COVID-19 pandemic conducted to changes in air quality. This study aimed to understand the variability of PM_2.5 levels and composition in an urban-industrial area of the Lisbon Metropolitan Area and to identify the contribution of the different sources. The composition of PM_2.5 was assessed for 24 elements (by PIXE), secondary inorganic ions and black carbon. The PM_2.5 mean concentration for the period (December 2019 to November 2020) was 13 ± 11 μg.m^-3. The most abundant species in PM_2.5 were BC (19.9%), SO₄ ^2- (15.4%), NO₃ ^- (11.6%) and NH₄ ⁺ (5.3%). The impact of the restrictions imposed by the COVID-19 pandemic on the PM levels was found by comparison with the previous six years. The concentrations of all the PM_2.5 components, except Al, Ba, Ca, Si and SO₄ ^2-, were significantly higher in the winter/pre-confinement than in post-confinement period. A total of seven sources were identified by Positive Matrix Factorisation (PMF): soil, secondary sulphate, fuel-oil combustion, sea, vehicle non-exhaust, vehicle exhaust, and industry. Sources were greatly influenced by the restrictions imposed by the COVID-19 pandemic, with vehicle exhaust showing the sharpest decrease. Secondary sulphate predominated in summer/post-confinement. PM_2.5 levels and composition also varied with the types of air mass trajectories.

Citizens' Perception on Air Quality in Portugal-How Concern Motivates Awareness

This study aimed to understand the knowledge of Portuguese citizens about air quality and the extent to which the concerns about specific environmental problems can motivate their acquaintance of information. Moreover, this study also allowed to understand which information about air quality needs further dissemination to provide the citizens with all the available tools and the correct knowledge. For this, a national online survey about air quality perception was conducted, where 1131 answers were obtained and two different populations were compared: the general population and a sub-population from an urban-industrial area of Lisbon metropolitan area that had experienced frequent air pollution events in the past. Air pollution was considered the environmental topic of higher concern among this sub-population (61.4%), while in the general population it ranked thirdly (27.4%). Generally, the sub-population showed higher knowledge about air quality than the general population, with 61% being able to identify at least one air pollutant. The perception of the local air quality was also very different between populations, with 61% of the sub-population considering it poor or very poor, while only 14% of the general population had the same perception, which highlights the different levels of concern between populations. A weak knowledge about air pollutants (50% of the general population could not identify any air pollutant) and an erroneous perception of the contribution of the different pollution sources to air quality levels were found. More than 50% of the respondents of both populations were considered to not have enough information regarding the air quality in their area of residence, with the national air quality database being unknown to almost everyone. Overall, strong efforts should be made to increase the awareness about the importance of air quality, which may promote a higher acceptance of the implementation of future actions to improve air quality.

Spatial Distribution of Air Pollution, Hotspots and Sources in an Urban-Industrial Area in the Lisbon Metropolitan Area, Portugal-A Biomonitoring Approach

This study aimed to understand the influence of industries (including steelworks, lime factories, and industry of metal waste management and treatment) on the air quality of the urban-industrial area of Seixal (Portugal), where the local population has often expressed concerns regarding the air quality. The adopted strategy was based on biomonitoring of air pollution using transplanted lichens distributed over a grid to cover the study area. Moreover, the study was conducted during the first period of national lockdown due to COVID-19, whereas local industries kept their normal working schedule. Using a set of different statistical analysis approaches (such as enrichment and contamination factors, Spearman correlations, and evaluation of spatial patterns) to the chemical content of the exposed transplanted lichens, it was possible to assess hotspots of air pollution and to identify five sources affecting the local air quality: (i) a soil source of natural origin (based on Al, Si, and Ti), (ii) a soil source of natural and anthropogenic origins (based on Fe and Mg), (iii) a source from the local industrial activity, namely steelworks (based on Co, Cr, Mn, Pb, and Zn); (iv) a source from the road traffic (based on Cr, Cu, and Zn), and (v) a source of biomass burning (based on Br and K). The impact of the industries located in the study area on the local air quality was identified (namely, the steelworks), confirming the concerns of the local population. This valuable information is essential to improve future planning and optimize the assessment of particulate matter levels by reference methods, which will allow a quantitative analysis of the issue, based on national and European legislation, and to define the quantitative contribution of pollution sources and to design target mitigation measures to improve local air quality.