Source apportionment by positive matrix factorization on elemental concentration obtained in PM10 and biomonitors collected in the vicinities of a steelworks

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.

Spatial distribution and source apportionment of heavy metal(loid)s in urban topsoil in Mianyang, Southwest China

Spatial distributions and sources of some commonly concerned heavy metal(loid)s (HMs, As, Ba, Cr, Co, Cu, Ni, Pb, Mn, Zn, and V) in topsoil of Mianyang city, a typical medium-sized emerging industrial city in Southwest China, were determined to explore the influences of anthropogenic activities on the urban environment. The contents of the 10 HMs in 101 topsoil samples were analyzed using an X-ray fluorescence spectrometer, and their sources were analyzed by positive matrix factorization and statistical analysis. The spatial distributions of the HMs and the source contributions were mapped using GIS technology. The results showed that the mean contents of Ba, Cr, Cu, and Zn in the topsoil were significantly higher than their background values. Industrial activities resulted in high contents of Ba, Zn, Cu, and Cr. As, Co, Ni, and V that primarily came from natural sources; Pb, Cr, Cu, and Zn were chiefly derived from a mixed source of industry and traffic; and Ba and Mn primarily originated from industrial sources. Natural sources, mixed sources, and industrial sources contributed 32.6%, 34.4%, and 33.0% of the total HM contents, respectively. Industrial sources and mixed sources of industry and traffic were the main anthropogenic sources of HMs in the urban topsoil and should be the focus of pollution control.

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.

First-Time Source Apportionment Analysis of Deposited Particulate Matter from a Moss Biomonitoring Study in Northern Greece

Moss biomonitoring is a widely used technique for monitoring the accumulation of trace elements in airborne pollution. A total of one hundred and five samples, mainly of the Hypnum cupressiforme Hedw. moss species, were collected from the Northern Greece during the 2015/2016 European ICP Vegetation (International Cooperative Program on Effects of Air Pollution on Natural Vegetation and Crops) moss survey, which also included samples from the metalipherous area of Skouries. They were analyzed by means of neutron activation analysis, and the elemental concentrations were determined. A positive matrix factorization (PMF) model was applied to the results obtained for source apportionment. According to the PMF model, five sources were identified: soil dust, aged sea salt, road dust, lignite power plants, and a Mn-rich source. The soil dust source contributed the most to almost all samples (46% of elemental concentrations, on average). Two areas with significant impact from anthropogenic activities were identified. In West Macedonia, the emissions from a lignite power plant complex located in the area have caused high concentrations of Ni, V, Cr, and Co. The second most impacted area was Skouries, where mining activities and vehicular traffic (probably related to the mining operations) led to high concentrations of Mn, Ni, V, Co, Sb, and Cr.

Investigating the impacts of coal-fired power plants on ambient PM2.5 by a combination of a chemical transport model and receptor model

Aimed at evaluating the impacts of coal-fired power plants on urban air quality and human health, a one-month intensive observation campaign was conducted in a typical polluted city located in the 2 + 26 city cluster (Beijing, Tianjin and 26 other cities) of the North China Plain in December 2017. The observation results illustrated that the coal-fired power plant in this city increased the monthly average fine particulate matter (PM_2.5) concentration by ~5% at the city scale. The impacts differed under various diffusion conditions. A three-dimensional nested air quality condition model (the Nested Air Quality Perdition Model System or NAQPMS) with source apportionment was employed to analyze the impacts. The results indicated that power plants had the largest effect on regional air quality during the severe-pollution period, while any influence could be ignored during periods with excellent dissipation under robust winds. PM_2.5 contributed by the power plant mainly occurred below 150 m, diffused 100 km away, and reached a level of approximately 5 μg m^-3 during the light-pollution period. During the accumulation period, the plume reached a height of 500 m, diffused to the downwind area approximately 100 km away within half a day, and contributed at most 40 μg m^-3 to PM_2.5. The affected area expanded to 250 km during the severe-pollution period, and the contribution to PM_2.5 was at least 10 μg m^-3 at different distances. The affected height reached approximately 500 m, with PM_2.5 exceeding 10 μg m^-3, mainly constrained below 150 m. Overall, regional integrated control strategies should be implemented for the power plants in the 2 + 26 city cluster during pollution episodes to further improve air quality.

Biomonitoring of environmental pollution in the vicinity of iron and steel smelters in southwestern Nigeria using transplanted lichens and mosses

This study identified specific emission sources of atmospheric pollution in the vicinity of two secondary iron and steel smelting factories in Osun state, southwestern Nigeria, using transplanted biomonitors. A total of 120 biomonitors consisting of lichen and moss were grown under a controlled environment and later transplanted to the surroundings of each factory for monitoring of air pollutants for 3 months in both wet and dry seasons. The elemental contents (K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Rb and Sr) of the biomonitors were determined by X-ray florescence (XRF) spectroscopy. The source identification was performed by applying positive matrix factorization (PMF) receptor modelling approach using the elemental data set from the two smelters. Among the measured elements, Fe had the highest average concentration in the lichen and moss samples as well as in both seasons. The average concentrations of Co, Ni, Cu, Zn, As and Br were low. The varying average elemental concentrations of lichen and moss reflect the pattern of impact of smelting on atmospheric airborne pollution around the factories. The four factors resolved by PMF and their respective contributions were metal processing (39.0%), Fe source (28.0%), crustal/soil (22.0%) and road dust (11.0%) for moss and Fe source (34.0%), crustal/soil (26.0%), coal combustion (25.0%) and road dust (15.0%) for lichen. The study showcases lichen and moss as cheaper and yet efficient uninterrupted monitoring tools of air pollution sources associated with iron and steel smelting industrial activities.