Receptor modelling of airborne particulate matter in the vicinity of a major steelworks site

PM2.5-bound trace metals in an urban area of Northern Mexico during the COVID-19 pandemic: characterization, sources, and health risk

Abstract

A field study was carried out in the Metropolitan Area of Monterrey (MAM), the second most populated city in Mexico, characterized by increasing urbanization, high traffic density, and intense industrial activity. These characteristics commonly present high concentrations of air pollutants leading to the degradation of air quality. PM2.5 was analyzed for heavy metals at two urban sites located within the MAM (Juarez and San Bernabe) in order to determine sources, health risk, morphology, and elemental content during the COVID-19 pandemic (autumn 2020 and spring 2021). Twenty-four-hour samples of PM2.5 were collected at each site during 30-day periods using high-volume equipment. Gravimetric concentrations and 11 metals were measured (Ca, Cd, Co, Cu, Fe, K, Mg, Mn, Ni, Cr, and Pb) by different analytical techniques (flame atomic absorption spectroscopy, graphite furnace atomic absorption spectroscopy, and inductively coupled plasma optical emission spectroscopy). Selected samples were analyzed by scanning electron microscopy-energy-disperse spectroscopy in order to characterize their morphology and elemental content. PM2.5 concentrations exceeded the Mexican standard and WHO guidelines in Juarez during spring 2021. Cu, Cd, and Co were highly enriched by anthropogenic sources, and Ni, K, Cr, and Pb had a moderate enrichment. Mg, Mn, and Ca were of crustal origin. Bivariate statistics and PCA confirmed that alkaline metals originated from crustal sources and that the main sources of trace metals included traffic emissions, resuspension from soil/road dust, steel industry, smelting, and non-exhaust emissions at both sites. Lifetime cancer risk coefficients did not exceed the permissible levels established by EPA and WHO, implying that local residents are not at risk of developing cancer. Non-carcinogenic risk coefficients revealed that there is a possible risk of suffering cardiovascular and respiratory diseases due to inhalation of cobalt at the study sites.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s11869-023-01372-7.

Spatial distribution and source apportionment of DTPA-extractable metals in soils surrounding the largest Serbian steel production plant

Despite presenting a practical approach for the characterization of the environmental risk of potentially toxic elements (PTEs) derived from steel production facilities, the analysis of the spatial distribution of bioavailable PTEs concentrations in the soil is frequently overlooked in the management of polluted sites. In this study, the diethylenetriaminepentaacetic acid (DTPA)-extractable forms of PTEs were investigated in soils surrounding the largest Serbian steel production plant. The correlation and geostatistical analysis indicated their pronounced variability suggesting the anthropogenic origin of most investigated elements, apparently from the steel production facility. The detailed visualization of variables and observations derived by self-organizing maps (SOMs) revealed the homologies in PTEs' distribution patterns, implying the common origin of some elements. These observations were confirmed by principal component analysis (PCA) and positive matrix factorization (PMF). The аpplied approach supports a comprehensive assessment of contaminated sites' ecological and health risks and provides a basis for soil remediation.

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.

The Content and Toxicological Risk Assessment of Trace Elemental Impurities (Pb and Cr) in Snacks from Ogun State, Southwestern Nigeria

The monitoring of food contamination by trace elemental impurities (TEIs) are major health challenges in developing countries. The present study evaluated the content and toxicological risk assessment of TEIs in commonly consumed snack/junk foods from Ogun State, Nigeria. TEIs (Pb and Cr) were determined in sixty snack food samples purchased from Ijebu Ode, Ogun State, southwestern Nigeria. The TEIs were analysed in quadruplicates using atomic absorption spectrometry with flame atomization. TEI data were subjected to simple descriptive and inferential statistics. The toxicological risk assessment of TEIs was evaluated for hazard quotient (HQ), hazard index (HI) and cancer risk (CR) using the United States Environmental Protection Agency-Integrated Risk Information System (USEPA-IRIS) model. Data showed the varying Pb levels of 8.22 ± 1.57 mg/kg in sausage to 12.25 ± 4.27 mg/kg in cocoyam chips higher than the permissible limit of the Codex Alimentarius of the Joint World Health Organization and Food and Agriculture Organization. The toxicological risk assessment revealed the HQs greater than 1.0 for Pb and Cr in most snack foods consumed by adults and children, indicating adverse health problems. The CRs of Pb (children) and Cr (adults and children) also breached the acceptable limit of 1.0 × 10^-4, signifying possible lifetime development of cancer. It is therefore necessary to periodically monitor the TEIs in snacks to protect the public health.

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.

Source attribution and quantification of atmospheric nickel concentrations in an industrial area in the United Kingdom (UK)

Pontardawe in South Wales, United Kingdom (UK), consistently has the highest concentrations of nickel (Ni) in PM₁₀ in the UK and repeatedly breaches the 20 ng m^-3 annual mean EU target value. Several local industries use Ni in their processes. To assist policy makers and regulators in quantifying the relative Ni contributions of these industries and developing appropriate emission reduction approaches, the hourly concentrations of 23 elements were measured using X-ray fluorescence alongside meteorological variables and black carbon during a four-week campaign in November-December 2015. Concentrations of Ni ranged between 0 and 2480 ng m^-3 as hourly means. Positive Matrix Factorization (PMF) was used to identify sources contributing to measured elements. Cluster analysis of bivariate polar plots of those factors containing Ni in their profile was further used to quantify the industrial processes contributing to ambient PM₁₀ concentrations. Two sources were identified to contribute to Ni concentrations, stainless-steel (which contributed to 10% of the Ni burden) and the Ni refinery (contributing 90%). From the stainless-steel process, melting activities were responsible for 66% of the stainless-steel factor contribution.

The Toxicological Risk Assessment of Trace Elements (Co, Cu, Fe, and Zn) in Snacks from Ijebu Ode, Ogun State, Southwest, Nigeria

Snacks or junk foods are a form of relatively small, packaged, ready-to-eat fast foods, usually taken not as a regular, but as a stopgap. However, contamination of snacks with trace elemental impurities may pose serious health risk to consumers. The main objective of the present study is to assess the toxicological risk of trace elements TEs (Co, Cu, Fe, and Zn) in commonly consumed snack/junk foods from Ijebu Ode, Ogun State, Southwest, Nigeria. A total of sixty snack food samples were purchased and assayed in replicates for Co, Cu, Fe, and Zn using atomic absorption spectrophotometer. Trace elements data were manipulated for simple descriptive and inferential statistics. The toxicological risk of metals was estimated for average daily dose (ADD), hazard quotient (HQ), hazard index (HI), and cancer risk (CR). Results showed Fe as the most abundant TE in the snacks showing insignificant mean concentrations (p > 0.05) varying from 38.10 ± 1.98 mg kg^-1 (potato chip) to 71.25 ± 14.68 mg kg^-1 (cashew nut). Cashew nut had the highest amounts of the TEs. The HQs of Co in all the snacks except corn flakes consumed by children were greater than the threshold limit of 1.0, indicating non-carcinogenic adverse effects. The CRs of Co in all the food samples exceeded the acceptable limit of 1.0 × 10^-4, suggesting possible development of cancer by the consumers. Co is a trace metal of health issues in the snack/junk foods. This study therefore recommends periodic monitoring and toxicological assessment of metals in snacks, especially the raw materials and processing feedstocks.

A review of the main strategies used in the interpretation of similar chemical profiles yielded by receptor models in the source apportionment of particulate matter

Receptor models have been widely used for the source apportionment of airborne particulate matter. However, in the last 10 years, the use of factor analysis-based models, such as PMF and UNMIX, has increased significantly. The results yielded by these models must be interpreted by users who must know all variables influencing the modeling, and without this knowledge, the probability of incorrect interpretation of the source profiles may increase, especially when two or more sources have similar chemical profiles. Concerning the quality of data, this work shows that a broad characterization of PM composition, including inorganic, organic, and mineralogical species can improve this process, avoiding misinterpretation and the attribution of mixed or unidentified sources. This work aims to provide readers with some answers for a question often risen during source apportionment studies: Which source markers should be used for better separation and interpretation of source profiles? This review shows there is no right answer for this because different strategies can be used for this purpose. Therefore, this review aims to compile and highlight qualitatively the key strategies already used by several experienced receptor models users, combining the use of inorganic, organic, and mineralogical markers of PM for better separation and interpretation of the profiles yielded by receptor models. Also, this work presents a compilation in tables of the main chemical species reported in the literature as markers for interpreting the source profiles.

Human health impact assessment and temporal distribution of trace elements in Copșa Mică- Romania

The present study aims to analyze the temporal variations of PM₁₀ and to assess the health risk indexes caused by trace elements from particulate matter (PM₁₀) via inhalation, ingestion, and dermal absorption by adults and children in Copșa Mică (Romania) during 2009–2019. The results revealed a high multi-annual mean concentration of PM₁₀ and trace elements. The analyzed air pollutants showed a decreasing trend during the studied years, therefore 44.11%, 43.48%, 36.07%, 16.02%, and 15.80% lower values were observed for As, Cd, Ni, PM₁₀, and Pb, respectively, due to environmental regulations. The daily exceedance percentage of Pb and Cd was very high, representing 21.74% and 11.26%, followed by PM₁₀ and As concentrations with 4.72% and 3.92%. The ratio between the trace element concentration measured in Copșa Mică and the country average was 2.46, 4.01, 2.44 and 10.52 times higher for As, Cd, Ni and Pb. The calculated Hazard Quotient values via inhalation were higher than the safe limit (1), which accounted 1.81, 3.89 and 4.52, for As, Cd and Ni, respectively, indicating that the trace elements might present a non-carcinogenic risk to both adults and children. Furthermore, the concentration of all studied trace elements in Copșa Mică showed cancer risk for adults via inhalation and dermal absorption as well.

[Contribution of Emissions from the Iron and Steel Industry to Air Quality in China]

Based on the data from a continuous emission monitoring systems network in 2015, this study analyzed the compliance rates of exhaust gas in the processes of China's iron and steel industry, and established a high-resolution steel plant emission inventory for China (HSEC, 2015), based on the bottom-up method. The contribution of emissions from the iron and steel industry to regional air quality was quantitatively simulated using a CAMx model. The results showed that in 2015, the total emissions of SO₂, NO_x, PM₁₀, PM_2.5, PCDD/Fs, VOCs, CO, BC, OC, EC, and F were 374800 t, 720500 t, 334800 t, 150300 t, 1.91 kg, 842900 t, 34788500 t, 6400 t, 8300 t, 800 t, and 7700 t, respectively. From a regional perspective, the iron and steel industry in Shanghai and Tianjin has the highest emission intensity per unit area and contributes a high proportion to regional air pollution. From a process perspective, in 2015, the exhaust concentration of flue gas in the main process gradually decreased, with a high compliance rate, and the emission factor significantly decreased to lower than that in the existing research results. From a species perspective, in 2015, NO_x emission from the steel industry contributed the most to regional air quality, and there is therefore a great emission reduction potential for NO_x.

Particle-Bound PAHs and Elements in a Highly Industrialized City in Southern Italy: PM2.5 Chemical Characterization and Source Apportionment after the Implementation of Governmental Measures for Air Pollution Mitigation and Control

The present study was aimed at determining airborne concentrations of PAHs, Nitro-/Oxy-PAHs and elements in industrial and urban areas of Taranto, a site of environmental risk in Southern Italy, after the issue of strategic measures for air pollution mitigation and control by the Italian Environment Ministry in 2012. A PM_2.5 sampling campaign was carried out from 9 to 28 December 2014 at eight receptor sites, two placed in the urban settlement and five included in the high spatial resolution fence monitoring network of the biggest European steel plant. The integration of collected data with meteorological parameters and source apportionment analysis by Positive Matrix Factorization and bivariate polar plots allowed to discriminate among emission sources and estimate their contributions. Evidence on the effect of distinct processes (homogenization, sintering) occurring inside the steel plant on airborne concentrations of PAHs and selected elements was provided. The impact of emissions from the steel plant “core” on the surrounding area was observed at receptor sites downwind to it. Moreover, the extent of the effectiveness of mitigation measures, partially applied at the moment of study’s beginning, was demonstrated by mean and peak pollutant concentrations at all receptor sites up to one order of magnitude lower than those documented prior to 2012.

Hourly Elemental Composition and Source Identification by Positive Matrix Factorization (PMF) of Fine and Coarse Particulate Matter in the High Polluted Industrial Area of Taranto (Italy)

In the framework of an extensive environmental investigation, promoted by the Italian Health Ministry, the ISPESL (Istituto Superiore per la Prevenzione e la Sicurezza del Lavoro) and the CNR (Consiglio Nazionale della Ricerca), aerosol samples were collected in Taranto (one of the most industrialized towns in southern Italy) with high time resolution and analyzed by PIXE. The samples were collected in two periods (February–March and June 2004) and in two different sites: an urban district close to the industrial area and a small town 7 km N-NW of Taranto. The use of ‘‘streaker’’ samplers (by PIXE International Corporation) allowed for the simultaneous collection of the fine (<2.5 μm) and coarse (2.5–10 μm) fractions of particulate matter. PIXE analyses were performed with a 3 MeV proton beam from the 3 MV Tandetron accelerator of the INFN-LABEC laboratory. Particulate emissions as well as their atmospheric transport and dilution processes change within a few hours, but most of the results in literature are limited to daily time resolution of the input samples that are not suitable for tracking these rapid changes. Furthermore, since source apportionment receptor models need a series of samples containing material from the same set of sources in different proportions, a higher variability between samples can be obtained by increasing the temporal resolution rather than with samples integrated over a longer time. In this study, the high time resolution of the adopted approach allowed us to follow in detail the changes in the aerosol elemental composition due to both the time evolution of the industrial emissions and the time changes in meteorological conditions, and thus, transport pathways. Moreover, the location of the sampling sites, along the prevalent wind direction and in opposite positions with respect to the industrial site, allowed us to follow the impact of the industrial plume as a function of wind direction. Positive matrix factorization (PMF) analysis on the elemental hourly concentrations identified eight sources in the fine fraction and six sources in the coarse one.

Contamination identification, source apportionment and health risk assessment of trace elements at different fractions of atmospheric particles at iron and steelmaking areas in China

China has the largest share of global iron and steel production, which is considered to play a significant contribution to air pollution. This study aims to investigate trace element contamination at different fractions of particulate matter (PM) at industrial areas in China. Three PM fractions, PM2.1-9.0, PM1.1-2.1 and PM1.1, were collected from areas surrounding iron and steelmaking plants at Kunming, Wuhan, Nanjing and Ningbo in China. Multiple trace elements and their bioavailability, as well as Pb isotopic compositions, were analysed for identification of contaminants, health risk assessment and source apportionment. Results showed that PM particles in the sites near industrial areas were associated with a range of toxic trace elements, specifically As, Cr(VI), Cd and Mn, and posed significant health risks to humans. The isotopic Pb compositions identified that coal and high temperature metallurgical processes in the steelmaking process were the dominant contributors to local air pollution in these sites. In addition to iron and steelmaking activities, traffic emissions and remote pollution also played a contributing role in PM contamination, confirmed by the differences of Pb isotopic compositions at each PM fraction and statistical results from Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) and Geometrical Analysis for Interactive Aid (GAIA). The results presented in this study provide a comprehensive understanding of PM emissions at iron and steelmaking areas, which helps to guide subsequent updates of air pollution control guidelines to efficiently minimise environmental footprint and ensure long term sustainability of the industries.

Uncommon chemical species in PM2.5 and PM10 and its potential use as industrial and vehicular markers for source apportionment studies

Chemical characterization of PM_2.5 and PM₁₀ is important to identify potential compounds that induce biological responses that translate into cardio-respiratory health problems. This study shows the reliability of the use of crystalline phases, identified in samples from receptor sites, as source markers, helping researchers to infer the main sources of air pollution, even without the use of receptor models. PM_2.5 and PM₁₀ samples were collected at two sites in an urban industrialized region located at southeast of Brazil and analyzed by Synchrotron X-ray Diffraction to identify crystalline compounds. Results show 5 PM₁₀ and PM_2.5 species not previously reported in the literature. We propose reaction mechanisms for these species and identify specific sources for each crystalline phase found: BaTiO₃ was found in PM₁₀ receptor samples and proved to be a vehicular marker formed during brake action; maghemite (γ-Fe₂O₃), pyracmonite [(NH₄)₃Fe(SO₄)₃], ammonium perchlorate (NH₃OHClO₄) and potassium ferrate (K₂Fe₂O₄) were found in PM_2.5 proved to be markers of industrial activities. The crystalline phases found in PM samples from receptor sites and the mechanisms of reactions showed the reliability of the use of crystalline phases as source markers in the identification of potential sources of air pollution without misinterpretation of the likely source.

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.

Environmental Pollution and Related Hazards at Agbara Industrial Area, Ogun State

This study aimed at assessing the environmental pollution and related hazards of industries at Agbara, Ogun State, Nigeria. A total of five sampling points were identified and selected at random. Environmental samples were collected on a weekly basis for duration of 10 weeks. Air pollutants measured were CO₂, CO, NO, NO_x, VOCs, H₂S, SO₂, NH₃, PM_2.5 andPM₁₀ using standard procedure. Dust and plant samples were also collected and analyzed for heavy metals (Pb, Cr, Cd, Cu and Zn) using the Atomic Absorption Spectrophotometer (AAS). Data was evaluated for descriptive and inferential statistics using SPSS for Windows version 22.0. Air pollution data were also subjected to SPE-risk model. The results of highest measured air parameters were: CO (5.50 ± 2.32 ppm), CO₂ (3.00 ± 2.05%), NO_x (0.90 ± 0.32 ppm), NO (0.60 ± 0.52 ppm), PM₁₀ (0.40 ± 0.52 mg/m³) and PM_2.5 (0.20 ± 0.42 mg/m³). The results of heavy metal concentrations in dust samples were: 57.40 ± 13.28 mg/kg for Cu, 45.36 ± 12.37 mg/kg for Cr, 22.80 ± 17.36 mg/kg for Zn, 13.76 ± 3.08 mg/kg for Pb and 0.32 ± 0.36 mg/kg for Cd. Metal concentrations in plants were: Cu (70.07 ± 16.24 mg/kg), Zn (67.69 ± 14.50 mg/kg), Cr (22.46 ± 9.35 mg/kg), Pb (13.76 ± 3.08 mg/kg) and Cd (2.25 ± 3.04 mg/kg). This study revealed the concentrations of CO₂, NO_x and NO higher than the World Health Organization (WHO) permissible standards while Pb, Cu, Cr, Cd and Zn values in dust samples were also found above the National Environmental Standards and Regulations Enforcement Agency (NESREA) and the WHO standards. Results of SPE-RISK model indicated that CO₂, CO, Pb, Cu and Zn posed the greatest health risks, while the Principal Component Analysis (PCA) indentified pollutant sources from industrial and vehicle exhaust.

Contributions of local and regional anthropogenic sources of metals in PM2.5 at an urban site in northern France

PM_2.5 have been related to various adverse health effects, mainly due to their ability to penetrate deeply and to convey harmful chemical components, such as metals inside the body. In this work, PM_2.5 were sampled at Saint-Omer, a medium-sized city located in northern France, in March-April 2011 and analyzed for their total carbon, water-soluble ions, major and trace elements. More specifically, the origin of 15 selected elements was examined using different tools including enrichment factors, conditional bivariate probability function (CBPF) representations, diagnostic ratios and receptor modelling. The results indicated that PM_2.5 metal composition is affected by both emissions of a local glassmaking factory and an integrated steelworks located at a distance of 35 km from the sampling site. For the first time, diagnostic ratios were proposed for the glassmaking activity. Therefore, metals in PM_2.5 could be attributed to the following anthropogenic sources: (i) local glassmaking industry for Sn, As, Cu and Cr, (ii) distant integrated steelworks for Ag, Fe, Cd, Mn, Rb and Pb, (iii) heavy fuel oil combustion for Ni, V and Co and (iv) non-exhaust traffic for Zn, Pb, Mn, Sb, and Cu. The impact of such sources on metal concentrations in PM_2.5 was assessed using a constrained receptor model. Despite their low participation to PM_2.5 concentration (2.7%), the latter sources were found as the main contributors (80%) to the overall concentration levels of the 15 selected elements in PM_2.5.

Heavy metals in industrially emitted particulate matter in Ile-Ife, Nigeria

Iron and steel smelting facilities generate large quantities of airborne particulate matter (PM) through their various activities and production processes. The resulting PM that contains a variety of heavy metals has potentially detrimental impacts on human health and the environment. This study was conducted to assess the potential health effects of the pollution from the heavy metals in the airborne PM sampled in the vicinity of secondary smelting operations in Ile-Ife, Nigeria. X-ray fluorescence (XRF) was used to determine the elemental concentration of Pb, Cr, Cd, Zn, Mn, As, Fe, Cu, and Ni in the size-segregated PM samples. Pollution Indices (PI) consisting of Contamination Factor (CF), Degree of Contamination (DC) and Pollution Index Load (PLI) and Target Hazard Quotient (THQ) were employed to assess the pollution risk associated with the heavy metals in the PM. CF, DC and PLI values were 3< CF <6, >32 and >1, respectively for the three sites, indicating deterioration of the ambient air quality in the vicinity of the smelter. The heavy metals in the airborne PM pose a severe health risk to people living in vicinity of the facility and to its workers. The diminished air quality with the associated health risks directly depends on the industrial emissions from steel production and control measures are recommended to mitigate the likely risks.

A review of AirQ Models and their applications for forecasting the air pollution health outcomes

Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects.

An intensive monitoring campaign of PAHs for assessing the impact of a steel plant

This study provided a useful approach for assessing the impact of industrial sources on surrounding, especially in a sensitive industrial area as Taranto (South of Italy). Taranto is one of the most industrialized Italian towns, where several emission sources operate simultaneously in proximity to the urban settlement. An intensive monitoring campaign of PAHs was carried out from January 28th to July 30th, 2011, in seven sites located in residential settlement around the industrial area and in the city center. The collected data were integrated with the information about wind direction and speed by means bivariate polarplot in order to characterize and localize the industrial sources. High BaP concentrations were detected especially when Benzene to Toluene ratio (B/T ratio) values excedeed 1 and all receptor sites were downwind to the steel plant. Moreover, in order to discriminate among PAH sources and quantify their contributions, a source apportionment analysis of the collected data was provided by means Principal component Analysis (PCA) and Positive Matrix Factorization (PMF) methods. Finally, the processing of PMF5.0 output by bivariate polar plot, confirmed the impact of steel plant on both industrial sites downwind the steel plant and the city center. B[a]P apportionment was quite similar for industrial and urban sites: the traffic source contributed only 11% and 24% to B[a]P measured at two sites, respectively. Therefore, the proximity of Taranto downtown to industrial pole makes negligible all other source contributions to PAH concentrations.

High time-resolved elemental components in fine and coarse particles in the Pearl River Delta region of Southern China: Dynamic variations and effects of meteorology

Hourly-resolved PM_2.5 and PM_10-2.5 samples were collected in the industrial city Foshan in the Pearl River Delta region, China. The samples were subsequently analyzed for elemental components and black carbon (BC). A key purpose of the study was to understand the composition of particulate matter (PM) at high-time resolution in a polluted urban atmosphere to identify key components contributing to extreme PM concentration events and examine the diurnal chemical concentration patterns for air quality management purposes. It was found that BC and S concentrations dominated in the fine mode, while elements with mostly crustal and oceanic origins such as Si, Ca, Al and Cl were found in the coarse size fraction. Most of the elements showed strong diurnal variations. S did not show clear diurnal variations, suggesting regional rather than local origin. Based on empirical orthogonal functions (EOF) method, 3 forcing factors were identified contributing to the extreme events of PM_2.5 and selected elements, i.e., urban direct emissions, wet deposition and a combination of coarse mode sources. Conditional probability functions (CPF) were performed using wind profiles and elemental concentrations. The CPF results showed that BC and elemental Cl, K, Fe, Cu and Zn in the fine mode were mostly from the northwest, indicating that industrial emissions and combustion were the main sources. For elements in the coarse mode, Si, Al, K, Ca, Fe and Ti showed similar patterns, suggesting same sources such as local soil dust/construction activities. Coarse elemental Cl was mostly from the south and southeast, implying the influence of marine aerosol sources. For other trace elements, we found vanadium (V) in fine PM was mainly from the sources located to the southeast of the measuring site. Combined with CPF results of S and V in fine PM, we concluded shipping emissions were likely an important elemental emission source.

Source insights into the 11-h daytime and nighttime fine ambient particulate matter in China as well as the synthetic studies using the new Multilinear Engine 2-species ratios (ME2-SR) method

Modeled results are very important for environmental management. Unreasonable modeled result can lead to wrong strategy for air pollution management. In this work, an improved physically constrained source apportionment (PCSA) technology known as Multilinear Engine 2-species ratios (ME2-SR) was developed to the 11-h daytime and nighttime fine ambient particulate matter in urban area. Firstly, synthetic studies were carried out to explore the effectiveness of ME2-SR. The estimated source contributions were compared with the true values. The results suggest that, compared with the positive matrix factorization (PMF) model, the ME2-SR method could obtain more physically reliable outcomes, indicating that ME2-SR was effective, especially when apportioning the datasets with no unknown source. Additionally, 11-h daytime and nighttime PM2.5 samples were collected from Tianjin in China. The sources of the 11-h daytime and nighttime fine ambient particulate matter in China were identified using the new method and the PMF model. The calculated source contributions for ME2-SR for daytime PM2.5 samples are resuspended dust (38.91 μg m(-3), 26.60%), sulfate and nitrate (38.60 μg m(-3), 26.39%), vehicle exhaust and road dust (38.26 μg m(-3), 26.16%) and coal combustion (20.14 μg m(-3), 13.77%), and those for nighttime PM2.5 samples are resuspended dust (18.78 μg m(-3), 12.91%), sulfate and nitrate (41.57 μg m(-3), 28.58%), vehicle exhaust and road dust (38.39 μg m(-3), 26.39%), and coal combustion (36.76 μg m(-3), 25.27%). The comparisons of the constrained versus unconstrained outcomes clearly suggest that the physical meaning of the ME2-SR results is interpretable and reliable, not only for the specified species values but also for source contributions. The findings indicate that the ME2-SR method can be a useful tool in source apportionment studies, for air pollution management.

Source identification and apportionment of PM2.5 and PM2.5-10 in iron and steel scrap smelting factory environment using PMF, PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM2.5 and PM2.5-10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m(3) for PM2.5 and 331.36, 190.01, and 184.60 μg/m(3) for PM2.5-10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM2.5-10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM2.5-10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.

The fractionation and geochemical characteristics of rare earth elements measured in ambient size-resolved PM in an integrated iron and steelmaking industry zone

Improved understanding of the fractionation and geochemical characteristic of rare earth elements (REEs) from steel plant emissions is important due to the unclear atmospheric signature of these elements and their adverse impact on human health and the environment. In this study, ambient particulate matter of different sizes was collected from one site in an integrated iron and steelmaking industrial zone (HG) and one urban background site with no direct industrial emissions (ZWY) during a 1-year sampling campaign in China. The total concentrations of REEs for TSP, PM10, and PM2.5 were 27.248, 14.989, 3.542 ng/m(3) in HG and 6.326, 5.274, 1.731 ng/m(3), respectively, in ZWY, which revealed the local influence of the steelmaking activities to the air quality. With respect to ZWY, the REEs in HG site are obviously fractionated in the coarser fraction, and LREEs account for more than 80 % of the total REE burden in all of the samples. Additionally, the REEs in HG and ZWY show a homogeneous trend with successively increased LREE/HREE ratios from the coarse particles to the fine particles. In our samples, La, Ce, Nd, and Sm are the most enriched rare earth elements, especially in the HG site. Moreover, ternary diagrams of LaCeSm indicate that the REEs in HG are potentially contributed by steelworks, carrier vehicles, coal combustion, and road dust re-suspension.

Quantifying the impact of PM2.5 and associated heavy metals on respiratory health of children near metallurgical facilities

The aim of this study was to link the concentrations of particulate matter with an aerodynamic diameter below 2.5 μm (PM2.5) and associated heavy metals with occurrence of wheezing and hospitalizations due to wheezing in 111 children who live near metallurgical plants in Targoviste City, Romania. A group of 72 children with high levels of immunoglobulin E (IgE) and eosinophils, as well as frequent wheezing episodes, was geolocated on digital thematic maps. Monitoring campaigns and medical assessments were performed over two consecutive years (2013-2014). The multiannual average concentrations of PM2.5 ranged from 4.6 to 22.5 μg m(-3), up to a maximum value of 102 μg m(-3). Significant correlations (p < 0.01) were observed between the locations of the children with respiratory issues and the PM2.5 multiannual average (r = 0.985) and PM2.5 maximum (r = 0.813). Fe, Ni, Cd, and Cr were the main marker elements of the emissions from steel production and metal-working facilities in the Targoviste area. The results support the hypothesis that increased PM2.5 levels directly influence wheezing symptom and asthma attacks in the analyzed group. IgE, eosinophils, and wheezing episodes may be considered key indicators with which to evaluate the adverse effects of PM2.5 air pollution on children's health.

PM2.5 source apportionment in a French urban coastal site under steelworks emission influences using constrained non-negative matrix factorization receptor model

The constrained weighted-non-negative matrix factorization (CW-NMF) hybrid receptor model was applied to study the influence of steelmaking activities on PM2.5 (particulate matter with equivalent aerodynamic diameter less than 2.5 μm) composition in Dunkerque, Northern France. Semi-diurnal PM2.5 samples were collected using a high volume sampler in winter 2010 and spring 2011 and were analyzed for trace metals, water-soluble ions, and total carbon using inductively coupled plasma--atomic emission spectrometry (ICP-AES), ICP--mass spectrometry (ICP-MS), ionic chromatography and micro elemental carbon analyzer. The elemental composition shows that NO3(-), SO4(2-), NH4(+) and total carbon are the main PM2.5 constituents. Trace metals data were interpreted using concentration roses and both influences of integrated steelworks and electric steel plant were evidenced. The distinction between the two sources is made possible by the use Zn/Fe and Zn/Mn diagnostic ratios. Moreover Rb/Cr, Pb/Cr and Cu/Cd combination ratio are proposed to distinguish the ISW-sintering stack from the ISW-fugitive emissions. The a priori knowledge on the influencing source was introduced in the CW-NMF to guide the calculation. Eleven source profiles with various contributions were identified: 8 are characteristics of coastal urban background site profiles and 3 are related to the steelmaking activities. Between them, secondary nitrates, secondary sulfates and combustion profiles give the highest contributions and account for 93% of the PM2.5 concentration. The steelwork facilities contribute in about 2% of the total PM2.5 concentration and appear to be the main source of Cr, Cu, Fe, Mn, Zn.

Chemical characterization of atmospheric particles and source apportionment in the vicinity of a steelmaking industry

The objective of this work was to provide a chemical characterization of atmospheric particles collected in the vicinity of a steelmaking industry and to identify the sources that affect PM10 levels. A total of 94 PM samples were collected in two sampling campaigns that occurred in February and June/July of 2011. PM2.5 and PM2.5-10 were analyzed for a total of 22 elements by Instrumental Neutron Activation Analysis and Particle Induced X-ray Emission. The concentrations of water soluble ions in PM10 were measured by Ion Chromatography and Indophenol-Blue Spectrophotometry. Positive Matrix Factorization receptor model was used to identify sources of particulate matter and to determine their mass contribution to PM10. Seven main groups of sources were identified: marine aerosol identified by Na and Cl (22%), steelmaking and sinter plant represented by As, Cr, Cu, Fe, Ni, Mn, Pb, Sb and Zn (11%), sinter plant stack identified by NH4(+), K and Pb (12%), an unidentified Br source (1.8%), secondary aerosol from coke making and blast furnace (19%), fugitive emissions from the handling of raw material, sinter plant and vehicles dust resuspension identified by Al, Ca, La, Si, Ti and V (14%) and sinter plant and blast furnace associated essentially with Fe and Mn (21%).

Analytical methods for assessing metal bioaccessibility in airborne particulate matter: A scoping review

In contrast to the existence of standardized methods to assess metal bioaccessibility via the gastrointestinal route, there are no widely-accepted, established in vitro testing protocols to measure elemental solubility in the human lung. This may be attributed, in part, to the difficulty associated with simulating the lung's complex in vivo conditions. The purpose of this review is two-fold: (1) to determine how the bioaccessibility of metals associated with ambient particulate matter (PM) in the human lung has been assessed in the literature, and (2) examine the suitability and biological relevance of applied methods for the measurement of metal bioaccessibility employed to date. The review revealed that limited attention has been paid to the development and application of biologically-relevant in vitro methods to measure elemental solubility in ambient PM as a proxy for bioaccessibility in the human lung. Few studies (n=14) used synthetic lung fluids to simulate in vivo conditions, with only half extracting samples at a biologically-relevant temperature of 37°C. There was limited evidence suggesting that the use of water is less effective as a leaching agent compared to simulated lung fluids. In sum, this scoping review highlights a critical need to develop standardized methods for the systematic assessment of elemental bioaccessibility via the respiratory route. Priority should be placed on the validation of biologically-relevant methods, including the use of leaching agents and extraction parameters used, which allow for testing to be conducted in a reliable, yet cost efficient, manner.