Airborne Heavy Metals Research Articles

Source and spatial distribution of airborne heavy metal deposition studied using mosses as biomonitors in Yancheng, China.

Naturally growing mosses have been successfully used as biomonitors of atmospheric heavy metal (HM) deposition. In recent years, with rapid economic development, environmental pollution in Yancheng, a coastal city in central Jiangsu Province, China, has become increasingly serious. However, to date, there have been no reports on atmospheric HM deposition in Yancheng. In this study, we investigated the HM concentrations and Pb isotopes in the moss Haplocladium microphyllum (Hedw.) Broth. from Yancheng and analyzed their main sources. The concentrations of HM in mosses from Yancheng were higher than those recorded in other studies of mosses from HM smelting regions and pollution-free areas of Eurasia and Alaska. The contamination factor value suggested that the pollution level of Cd was the highest. The pollution load index indicated that the studied area was severely contaminated with Cd, Cr, Pb, Zn, V, Ni, and Cu. Positive matrix factorization was employed to identify the contamination sources of HM and apportion their source contributions in mosses. The contributions of the natural source, together with manufacturing and construction, metal processing and chemical industries, traffic emissions and fuel burning in industrial activities, and agricultural activities, accounted for 53%, 33%, 12%, and 2%, respectively. The Pb isotopic ratios in the mosses (1.125-1.164 for 206Pb/207Pb, 2.059-2.148 for 208Pb/206Pb) further proved that metal processing and traffic emissions were the main sources of Pb contamination. These results are useful for developing various effective measures to prevent and reduce atmospheric HM deposition in Yancheng.

Airborne heavy metals and blood pressure: Modification by sex and obesity in the MMDA traffic enforcers’ health study

Epidemiological studies have linked exposure to heavy metals and increased blood pressure (BP). We conducted a repeated measures study to examine the associations between airborne heavy metals and BP, and we looked at effect modification by participant characteristics. We assessed blood cadmium (B–Cd), lead (B–Pb), and mercury (B–Hg), and studied measurements of systolic (SBP) and diastolic (DBP) blood pressure on 140 traffic enforcers from the Metropolitan Manila Development Authority Traffic Enforcers’ Health Study. Linear mixed-effects models with random subject-specific intercepts were fitted to estimate the effect of B-CD, B–Pb, and B–Hg exposure on the percent change in mean SBP and DBP, adjusting for potential confounding factors. Moreover, effect modification by sex and obesity were assessed. B–Pb and B–Cd concentrations were related to increased BP. A unit (1.0 μg/dL) increase in B–Pb was associated with 2.5% [95% confidence interval (CI): 1.3–3.7] and 2.1% (95% CI: 0.7–3.5) increases in mean SBP and DBP, respectively. A similar result was observed for the effect of B–Cd on SBP (2.2% increase, 95% CI: 0.6–3.7) but not on DBP (0.9% increase, 95% CI: −0.9–2.7). However, no association between B–Hg and BP was observed. The associations between B–Pb and both DBP and SBP were stronger among males (SBP: 2.7% increase, 95% CI: 1.5–4.0; DBP: 2.3% increase, 95% CI: 0.8–3.7) versus females, or traffic enforcers who were nonobese (SBP: 2.8% increase, 95% CI: 1.5–4.2; DBP: 2.9% increase, 95% CI: 1.3–4.4) versus obese. In summary, B–Pb and B–Cd are associated with increased BP. B–Pb may both increase SBP and DBP among male, or nonobese traffic enforcers.

Biomagnetic monitoring combined with support vector machine: a new opportunity for predicting particle-bound-heavy metals

Biomagnetic monitoring includes fast and simple methods to estimate airborne heavy metals. Leaves of Osmanthus fragrans Lour and Ligustrum lucidum Ait were collected simultaneously with PM10 from a mega-city of China during one year. Magnetic properties of leaves and metal concentrations in PM10 were analyzed. Metal concentrations were estimated using leaf magnetic properties and meteorological factors as input variables in support vector machine (SVM) models. The mean concentrations of many metals were highest in winter and lowest in summer. Hazard index for potentially toxic metals was 5.77, a level considered unsafe. The combined carcinogenic risk was higher than precautionary value (10−4). Ferrimagnetic minerals were dominant magnetic minerals in leaves. Principal component analysis indicated iron & steel industry and soil dust were the common sources for many metals and magnetic minerals on leaves. However, the poor simulation results obtained with multiple linear regression confirmed strong nonlinear relationships between metal concentrations and leaf magnetic properties. SVM models including leaf magnetic variables as inputs yielded better simulation results for all elements. Simulations were promising for Ti, Cd and Zn, whereas relatively poor for Ni. Our study demonstrates the feasibility of prediction of airborne heavy metals based on biomagnetic monitoring of tree leaves.

Spatial biomonitoring of airborne heavy metals emitted from a steel recycling plant

PurposeThe study investigated the heavy metal flux around the vicinity of a steel recycling factory using passive biomonitoring technique with several pollution indices to assess the quality of the ambient environment.Design/methodology/approachThe vegetation around the facility was identified, and the most abundant species were selected for analysis. The collected samples were dried, milled, sieved and analyzed for elemental composition using energy dispersive X-ray fluorescence (ED-XRF). Pollution indices were used to quantitatively assess the data.FindingsResults show that maximum contamination occurs at the vicinity of factory. Generally, the deterioration of the ambient air around the vicinity of the steel recycling plant decreases with increasing distance from the steel recycling plant. However, for the radius considered in this study – 1 km, the ambient air at 1 km of the steel recycling facility is quickly deteriorating, and there is an urgent need for measures to mitigate the air quality impact of the steel recycling facility.Originality/valueThe study shows that the metal recycling process emits high levels of heavy metals to the environment, and there is an urgent need for personal protective equipment for the human population working in and around the close proximity of the recycling plant.

Chemical content and source apportionment of 36 heavy metal analysis and health risk assessment in aerosol of Beijing.

The concentration levels of 36 airborne heavy metals and atmospheric radioactivity in total suspended particulate (TSP) samples were measured to investigate the chemical characteristics, potential sources of aerosols, and health risk in Beijing, China, from September 2016 to September 2017. The TSP concentrations varied from 6.93 to 469.18μg/m3, with a median of 133.97μg/m3. The order for the mean concentrations of heavy metals, known as hazardous air pollutants (HAPs), was as follows: Mn > Pb > As > Cr > Ni > Se > Cd > Co > Sb > Hg > Be; Non-Designated HAPs Metals: Ca > Fe > Mg > Al > K > Na > Zn > P > Ba > Ti > Cu > Sr > B > Sn > I > V > Rb > Ce > Mo > Cs > Th > Ag > U > Pt. The median concentration of As was higher than China air quality standard (6ng/m3). The gross α and β concentration levels in aerosols were (1.84 ± 1.59) mBg/m3 and (1.15 ± 0.85) mBg/m3, respectively. The enrichment factor values of Cu, Ba, B, Ce, Tl, Cs, Pb, As, Cd, Sb, Hg, Fe, Zn, Sn, I, Mo, and Ag were higher than 10, which indicated enriched results from anthropogenic sources. Pb, As, and Cd are considered to originate from multiple sources; fireworks released Ba during China spring festival; Fe, Ce, and Cs may come from stable emissions such as industrial gases. The health risks from anthropogenic metals via inhalation, ingestion, and dermal pathway were estimated on the basis of health quotient as well as the results indicated that children faced the higher risk than adults during the research period. For adults, the health risk posed by heavy metals in atmospheric particles was below the acceptable level.

Metallic air pollutants and breast cancer heterogeneity

BackgroundEmerging evidence suggests airborne metals may be associated with breast cancer risk. However, breast cancer is heterogenous and associations with heavy metals vary by subtype. Heavy metals possess both carcinogenic and xenoestrogenic properties which may be related to different tumor etiologies. Therefore, we tested for etiologic heterogeneity, using a case-series approach, to determine whether associations between residential airborne metal concentrations and breast cancer differed by tumor subtype. MethodsBetween 2005 and 2008, we enrolled incident breast cancer cases into the Breast Cancer Care in Chicago study. Tumor estrogen and progesterone receptors status was determined by medical record abstraction and confirmed immunohistochemically (N = 696; 147 ER/PR-negative). The 2002 USEPA's National Air Toxics Assessment census-tract estimates of metal concentrations (antimony, arsenic, beryllium, cadmium, chromium, cobalt, lead, manganese, mercury, nickel and selenium) were matched to participants' residences of the same year. Adjusted logistic regression models were used to examine whether the airborne heavy metal associations differed by tumor ER/PR status. Principal component analysis was performed to assess associations by metal co-exposures. ResultsComparing the highest and lowest quintiles, higher concentrations of antimony (odds ratio[OR]: 1.8, 95% confidence interval[CI]: 0.9, 3.7, P-trend: 0.05), cadmium (OR: 2.3, 95% CI: 1.2, 4.4, P-trend: 0.04) and cobalt (OR: 2.0, 95% CI: 0.9, 4.4, P-trend: 0.04) were associated with ER/PR-negative breast cancer. Mixture analysis using principal components suggested co-exposures to multiple airborne heavy metals may drive associations with tumor receptor status. ConclusionsAmong women diagnosed with breast cancer, metallic air pollutants were associated with increased odds of developing ER/PR-negative breast cancer.

Biosurface properties and lead adsorption in a clone of Sphagnum palustre (Mosses): Towards a unified protocol of biomonitoring of airborne heavy metal pollution

Although mosses are widely used for active biomonitoring of air pollution, a unified protocol for their treatment before exposure in bags is still lacking. Here we used field- and laboratory-grown Sphagnum palustre L. moss, respectively, treated by EDTA and devitalized by oven drying at 100 °C, to elaborate a consistent procedure of metal and proton adsorption on moss surfaces. Acid-base titrations and Pb2+ adsorption experiments at different pH values and Pb2+ concentrations in solution were performed with both field-collected and laboratory cloned mosses. Devitalization and EDTA treatments did not produce any measurable difference in terms of H+ and Pb2+ adsorption capacities of moss surfaces. The stability constants for Pb2+ adsorption onto moss surfaces as a function of pH (pH-dependent adsorption edge) and at constant pH (5.5 and 6.5) as a function of Pb2+ concentration (“langmuirian” adsorption isotherm) were rather similar between different treatments. A Linear Program Modeling (LPM) of adsorption reactions revealed high similarity of adsorption constants regardless of treatments for both field-grown and cloned mosses. Therefore, in view of the use of S. palustre clone for biomonitoring lead in the environment, we recommend devitalization at 100 °C as unique treatment to perform with the aim to preserve the biomonitor before and after its exposure in bags.

National environmental quality assessment and monitoring of atmospheric heavy metal pollution - A moss bag approach

As airborne pollution is recognised as the single largest environmental health hazard in Europe, the necessity to develop effective systems for monitoring and reducing the level of air pollutants, becomes imperative. The paper describes a tested and implemented long-term biomonitoring system for airborne heavy metals at a national scale. Moss bags (Hylocomium splendens) were exposed in 142 monitoring stations designated in Romania, and the content of Pb, Cd, Ni and As was quantified using inductively coupled plasma mass spectrometry. The results revealed that the accumulation of heavy metals exceeded the established thresholds, marking high pollution levels in 8.8% of samples for As, in 5.63% samples for Cd, in 3.17% samples for Pb, and in 0.35% samples for Ni. The maximum heavy metal concentration was 113.77 mg kg−1 dry weight for Pb, 44.93 mg kg−1 dry weight for Ni, 14.68 mg kg−1 dry weight for As, and 3.88 mg kg−1 dry weight for Cd, with several overlaps for at least two metals, thus marking pollution hotspots. In order to process, summarise and communicate the obtained data, a software named BioMonRo has been developed as the core part of a complex monitoring and warning-informative system. The software is able to generate heavy metal pollution maps and specific reports, depicting the levels and patterns of distribution, which can be automatically sent to a number of interested recipients. The results show that the developed national system is functional, cost-effective, and could be successfully used for long-term monitoring of airborne heavy metals.

Chemical speciation and health risks of airborne heavy metals around an industrial community in Nigeria

Quantification of PM2.5 (particulate matter <2.5 µm) bound heavy metals and their potential health risks were carried out around a cement manufacturing company in Ewekoro, Nigeria. The PM2.5 samples were collected using Environtech gravimetric sampler. A four-staged sequential extraction procedure was used to fractionate PM2.5 bound chromium (Cr), lead (Pb), aluminum (Al), copper (Cu), and silver (Ag), and further analyzed using inductively coupled plasma mass spectrometry. Chemical speciation results reveal bioavailable levels of Pb (4.05 µg/m3), Cr (10.75 µg/m3), Al (16.47 µg/m3), Cu (4.38E-01 µg/m3), and Ag (1.22E-02 µg/m3) in the airborne particulates. Pb and Cr levels exceeded the World Health Organization allowable limit of 0.5 and 2.5E-05 µg/m3, respectively. The labile phases showed strong indication of the presence of Cr and Cu metal. Excess cancer risks exposure for adults, outdoor workers and children were higher than the acceptable risk target level of 1E-06. Non-carcinogenic health risk estimated using hazard quotients (HQs) and hazard indices (HIs) showed ingestion route within the safe level of HI <1 implying no adverse effect while inhalation route exceeded the safe level for all receptors. Enforcement of pollution control by authorized agencies, and screening of greenbelts as sinks for air pollutants is strongly recommended.

Leaf magnetic properties as a method for predicting heavy metal concentrations in PM2.5 using support vector machine: A case study in Nanjing, China

The aim of this study was to establish a method for predicting heavy metal concentrations in PM2.5 (particulate matter with a diameter of less than 2.5 μm) using support vector machine (SVM) models combined with magnetic properties of leaves. In this study, PM2.5 samples and the leaves of three common evergreen tree species were collected simultaneously during four different seasons in Nanjing, China. A SVM algorithm was used to establish models for the prediction of airborne heavy metal concentrations based on leaf magnetic properties, with or without meteorological factors and pollutant concentrations as input variables. Results showed that the annual average PM2.5 concentration was 58.47 μg/m3. PM2.5 concentrations, leaf magnetic properties, and nearly all airborne heavy metals had higher concentrations in winter than in spring, summer, or fall. Ferrimagnetic minerals preponderant in dust-loaded leaves were sampled from the three tree species. Models using magnetic properties of leaves from Ligustrum lucidum Ait and Osmanthus fragrans Lour yielded better prediction effects than those based on the leaves of Cedar deodara G. Don, showing relatively higher correlation coefficient (R) values and lower errors in both training and test stages. Fe and Pb concentrations were well-simulated by the prediction models, with R values > 0.7 in both training and test stages. By contrast, the concentrations of V, Co, Sb, Tl, and Zn were relatively poor-simulated, with most R values < 0.7 in both training and test stages. Predictions for the main urban areas of Nanjing showed that the highest heavy metal concentrations occurred near industrial and traffic pollution sources. Our results provide a cost-effective approach for the prediction of airborne heavy metal concentrations based on the biomagnetic monitoring of tree leaves.

Determination of selected heavy metals in airborne particles in industrial area: A baseline study

This study focuses on airborne heavy metal pollution in the industrial area. Eight points from Paka and Gebeng Industrial Area respectively were selected for this study within two monsoon seasons. The samples were analysed for heavy metals (Cd, As, Cu, Fe, Ni, Pb, and Zn) by using inductively coupled plasma mass spectrometry (ICP-MS). The results showed that the mean concentration value of As, Pb and Cd for Paka were 5.0 ng/L ± 1.0, 107.0 ng/L ± 88.2, and 10.0 ng/L ± 7.5, respectively and Gebeng were 3.5 ng/L ± 1.5, 69.3 ng/L ± 59.3 and 5.1 ng/L ± 3.8, respectively in the southwest monsoon - much higher than the target value by European Commission in Directive 2004/107/EC and Directive 2008/50/EC. It could be concluded that the industrial and transportation emission were the major source of heavy metals in the atmosphere along the Paka and Gebeng Industrial Area.

Mosses Are Better than Leaves of Vascular Plants in Monitoring Atmospheric Heavy Metal Pollution in Urban Areas

Mosses and leaves of vascular plants have been used as bioindicators of environmental contamination by heavy metals originating from various sources. This study aims to compare the metal accumulation capabilities of mosses and vascular species in urban areas and quantify the suitability of different taxa for monitoring airborne heavy metals. One pleurocarpous feather moss species, Haplocladium angustifolium, and two evergreen tree species, Cinnamomum bodinieri Osmanthus fragrans, and substrate soil were sampled in the urban area of different land use types in Wuhan City in China. The concentrations of Ag, As, Cd, Co, Cr, Cu, Mn, Mo, Ni, V, Pb, and Zn in these samples were analyzed by inductively coupled plasma mass spectrometry. The differences of heavy metals concentration in the three species showed that the moss species was considerably more capable of accumulating heavy metals than tree leaves (3 times to 51 times). The accumulated concentration of heavy metals in the moss species depended on the metal species and land use type. The enrichment factors of metals for plants and the correlations of metals in plants with corresponding metals in soil reflected that the accumulated metals in plants stemmed mostly from atmospheric deposition, rather than the substrate soil. Anthropogenic factors, such as traffic emissions from automobile transportation and manufacturing industries, were primarily responsible for the variations in metal pollutants in the atmosphere and subsequently influenced the metal accumulation in the mosses. This study elucidated that the moss species H. angustifolium is relatively more suitable than tree leaves of C. bodinieri and O. fragrans in monitoring heavy metal pollution in urban areas, and currently Wuhan is at a lower contamination level of atmospheric heavy metals than some other cities in China.

Developing a novel warning-informative system as a tool for environmental decision-making based on biomonitoring

Biomonitoring, i.e. using plant species for measuring pollution levels, has been previously explored in several locations using various protocols and organisms in the search for effective strategies and practices for monitoring and reducing the levels of pollution.Here we present a tested and functional cost-effective method of using the foliar accumulation of tree species to develop a system for the long-term monitoring of airborne heavy metal bioaccumulation at a large, national scale. A total number of 1230 leaf samples have been collected during a vegetation season in 410 sampling locations scattered across Romania. Concentration levels were determined using an inductively coupled plasma mass spectrometer. Data from literature were used as reference values for the natural concentration of heavy metals in plants. Values exceeding these levels were considered as indicators of pollution, and used to define pollution thresholds. The maximum amounts measured in the collected samples were 152 mg kg−1 dry weight for lead, 25.65 mg kg−1 dry weight for cadmium, 65.51 mg kg−1 dry weight for nickel and 4.81 mg kg−1 dry weight for arsenic.For analysing and communicating the findings, the BioMonRo software has been developed as a novel tool for warning-informing and decision-making. The software, now implemented by the Ministry of Environment for monitoring environmental quality, uses concentration data to build up national heavy metal pollution maps and can generate reports, which are automatically sent to various stakeholders. Based on our findings, we consider that tree species are efficient biomonitors, and similar methods could be successfully used in extensive biomonitoring programmes (national, regional or European), and for informing authorities.

Airborne heavy metals in two cities of North Rhine Westphalia – Performing inhalation cancer risk assessment in terms of atmospheric circulation

The main objective of this study was to examine the levels of four heavy metals (As, Cd, Pb and Ni) in PM10 samples collected in two urban background stations in Dortmund and Bielefeld, in relation to atmospheric circulation. Pollution roses, Conditional Probability Function (CPF) roses and backward air mass trajectory clusters were used to identify air currents associated with the importation of PM10 and of the included metal constituents. In addition, PM10, NO2, SO2, O3, As, Cd, Ni and Pb concentrations were analyzed by a Principal Component Analysis (PCA) to reveal major local emission sources of PM10 metal content. Traffic was the main emitter of PM10, As, Cd, and Pb in both cities, highlighting the existence of non-negligible lead quantities in unleaded gasoline, whilst nickel emissions were associated with heavy fuel oil combustion in industries and primarily for domestic heating. The created CPF roses and trajectory clusters were in good agreement, clearly revealing that eastern air currents enriched the locally produced PM10 load with additional aerosols from Eastern Europe. The concentrations of arsenic and cadmium were also enhanced by the arrival of air parcels from the East, indicating the anthropogenic origin of the exogenous aerosols due to combustion. The induced cancer risk (CRinh) for adults, due to inhalation of individual metal constituents, was also estimated in terms of atmospheric circulation, indicating higher risk in Dortmund than in Bielefeld. CRinh values for arsenic exceeded the limit of 1 × 10−6 in both cities, primarily during the influence of eastern circulation.

Abstract 2305: Residential airborne heavy metal concentrations and breast cancer characteristics

Abstract Background: Ambient air metal concentrations have recently been implicated in the etiology of breast cancer. Previous studies have shown airborne concentrations of arsenic and cadmium are associated with the development of estrogen receptor-negative tumors. This study aims to replicate these findings and examine the role of other toxic and essential heavy metals. Methods: Participants were women who were diagnosed with breast cancer in Chicago between 2005 and 2008. We examined estrogen and progesterone receptor-negative (ER-/PR-) and high-grade tumors as markers of aggressive breast cancer, and estimated 15-year markers of exposure of 11 heavy metals. Exposures were calculated using census tract-level airborne concentrations from the National-scale Air Toxics Assessment and participants’ residential histories. We adjusted all models for socioeconomic status and reproductive factors. Results: We found that prevalent ER-/PR- tumors were associated with increased residential exposure to airborne concentrations of antimony (Q4 vs Q1: OR= 1.81; 95% CI: 0.95, 3.44; Ptrend= 0.04), cobalt (Q4 vs Q1: OR= 2.37; 95% CI: 1.26, 4.45; Ptrend &amp;lt; 0.01), manganese (Q4 vs Q1: OR= 2.55; 95% CI: 1.24, 5.24; Ptrend= 0.04), and selenium (Q4 vs Q1: OR= 1.85; 95% CI: 1.03, 3.29; Ptrend= 0.05), and also identified marginally significant trends for arsenic (Ptrend= 0.06), chromium (Ptrend= 0.08), lead (Ptrend= 0.08), and mercury (Ptrend= 0.07). We did not identify any overall associations with high-grade tumors, however when stratifying by menopausal status we found that antimony (Q4 vs Q1: OR= 6.97, 95% CI: 1.61-30.19) and arsenic (Q4 vs Q1: OR= 6.97, 95% CI: 1.61-30.19) were associated with prevalent high-grade tumors in premenopausal women only. Discussion: This study found further support for a role of airborne arsenic concentrations, and novel evidence implicating other airborne estrogen-pathway disrupting metal concentrations, in the development of aggressive breast cancer subtypes. Additionally, this is the first study to implicate heavy metal exposure in the etiology of high-grade tumors. These results suggest that long-term, low-dose exposures to certain heavy metals play a role in the etiology of aggressive breast cancer characteristics. Airborne exposures have the ability to affect large populations and findings from this and similar studies have large public health implications. Citation Format: Jacob K. Kresovich, Serap Erdal, Maria Argos, Hua Yun Chen, Peter H. Gann, Garth H. Rauscher. Residential airborne heavy metal concentrations and breast cancer characteristics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2305. doi:10.1158/1538-7445.AM2017-2305

Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses

Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM2.5 concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75 μg/m3. Nearly all elements had higher concentrations in industrial areas, and in winter among the four seasons. Anthropogenic elements such as Pb, Zn, Cd and Cu showed larger percentages in the fine fraction (ø≤2.5 μm), whereas the crustal elements including Al, Ba, Fe, Ni, Sr and Ti showed larger percentages in the coarse fraction (ø > 2.5 μm). SVM showed a higher training correlation coefficient (R), and lower mean absolute error (MAE) as well as lower root mean square error (RMSE), than MLR and BP-ANN for most metals. All the three methods showed better prediction results for Ni, Al, V, Cd and As, whereas relatively poor for Cr and Fe. The daily airborne metal concentrations in 2015 were then predicted by the fully trained SVM models and the results showed the heaviest pollution of airborne heavy metals occurred in December and January, whereas the lightest pollution occurred in June and July.

Using Moss to Assess Airborne Heavy Metal Pollution in Taizhou, China.

Bryophytes act as bioindicators and bioaccumulators of metal deposition in the environment. To understand the atmospheric deposition of heavy metals (cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn)) in Taizhou, East China, samples of moss (Haplocladium microphyllum) were collected from 60 sites selected by a systematic sampling method during the summer of 2012, and the concentrations of these heavy metals were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES). The results suggested that the concentrations of these metals varied moderately among different sites, indicating a similar contamination level for each element throughout the monitoring region. The mean values under investigation were higher than those from neighboring cities, such as Wuxi, Xuzhou, and Nanjing, and much higher than those in Europe based on a 2010 survey. Significant (p < 0.01) correlations were identified among some of the heavy metals, suggesting that these originated from identical sources. There was no statistically significant correlation between Hg and all the other elements. Spatial distribution maps of the elements over the sampled territory were created using Arc-GIS 9.0. The potential ecological risk index indicated that the air was heavily polluted by Cd and Hg, and that there was a considerable potential ecological risk from all the heavy metals studied.

Combined toxic effect of airborne heavy metals on human lung cell line A549.

Many studies have demonstrated that heavy metals existing as a mixture in the atmospheric environment cause adverse effects on human health and are important key factors of cytotoxicity; however, little investigation has been conducted on a toxicological study of a metal mixture from atmospheric fine particulate matter. The objective of this study was to predict the combined effects of heavy metals in aerosol by using in vitro human cells and obtain a suitable mixture toxicity model. Arsenic, nickel, and lead were selected for mixtures exposed to A549 human lung cancer cells. Cell proliferation (WST-1), glutathione (GSH), and interleukin (IL)-8 inhibition were observed and applied to the prediction models of mixture toxicity, concentration addition (CA) and independent action (IA). The total mixture concentrations were set by an IC10-fixed ratio of individual toxicity to be more realistic for mortality and enzyme inhibition tests. The results showed that the IA model was statistically closer to the observed results than the CA model in mortality, indicating dissimilar modes of action. For the GSH inhibition, the results predicted by the IA and CA models were highly overestimated relative to mortality. Meanwhile, the IL-8 results were stable with no significant change in immune reaction related to inflammation. In conclusion, the IA model is a rapid prediction model in heavy metals mixtures; mortality, as a total outcome of cell response, is a good tool for demonstrating the combined toxicity rather than other biochemical responses.

Study on Airborne Heavy Metals in Industrialized Urban Area of Delhi, India.

This study assessed the concentrations of airborne heavy metals (HMs) in particulate matter with a cutoff size of 10µm (i.e., PM10) in an industrialized urban area (Naraina Industrial Area) of New Delhi, India. The samples were collected from January to December, 2011. The annual mean concentrations of selected HMs were as follows As (0.002 ± 0.002), Cd (0.030 ± 0.020), Co (0.003 ± 0.002), Cr (0.170 ± 0.081), Cu (0.183 ± 0.120), Fe (4.774 ± 1.889), Mn (0.258 ± 0.145), Ni (0.170 ± 0.146), Pb (0.345 ± 0.207) and Zn (1.806 ± 1.042)µg/m3. The seasonal trend for HMs followed the order postmonsoon > winter > premonsoon > monsoon. Principal component analysis-multiple linear regression (PCA-MLR) suggested the three major emission sources: industrial emission (70 %), mobile and stationary combustion sources (16 %), and suspended/re-suspended dust (14 %). Mean seasonal concentrations of PM10 exceeded both the 24-hour and annual Indian National Ambient Air Quality Standards (NAAQS) of 60 and 100µg/m3, respectively, in all four seasons. Mean seasonal Ni concentrations in Delhi ambient air also exceeded the 24-h annual NAAQS of 0.020µg/m3 during all four seasons. Mean Pb concentrations exceeded the annual NAAQS of 0.50µg/m3 only during the post monsoon season. The high levels of Ni- and Pb-contaminated PM10 would appear to present the possibility of significant health risks.

The Impact of Cadmium on Photosynthetic Performance and Secondary Metabolites in the Lichens Parmelia sulcata, Flavoparmelia caperata and Evernia prunastri

Abstract Lichens are one of the most common air quality bioindicators. Airborne heavy metal pollution causes various physiological changes in lichens, but sensitivity to metal pollution is species specific. In this research, three lichen species (Parmelia sulcata, Flavoparmelia caperata and Evernia prunastri) were exposed to cadmium (50 mg L−1) in laboratory conditions. Photosynthetic efficiency of photosystem II and content of secondary metabolites were determined after one, three and eight days of exposure. In all investigated species treatment of lichen thalli with cadmium significantly changed Fv/Fm and RFd only after eight days of exposure. Quantification of metabolites showed a decreased content of the medullary depsidones salazinic acid (in P. sulcata) and protocetraric acid (in F. caperata) but increased content of cortical depside atranorin (in P. sulcata) and dibenzofurane usnic acid (in F. caperata) after cadmium exposure. However, no changes in secondary metabolites were found in E. prunastri. Results show that investigated species are relatively resistant to short-term cadmium-exposure and that secondary metabolites could have an important role in the protection of primary metabolism from negative cadmium impacts, at least in some species.