Air quality in the Olona Valley and in vitro human health effects

Metallic nanoparticle contamination from environmental atmospheric particulate matter in the last slab of the trophic chain: Nanocrystallography, subcellular localization and toxicity effects

Atmospheric particulate material (PM) from mining and steel industries comprises several metallic contaminants. PM₁₀ samples collected in a Brazilian region with a recognized influence of the steel and iron pelletizing industries were used to investigate metallic nanoparticle incorporation into human fibroblast cells (MRC-5). MRC-5 cells were exposed to 0 (control, ultrapure water), 2.5, 5, 10, 20 and 40 μg PM₁₀ mL^-1, for 24 h. Cytotoxic and genotoxic dose-response effects were observed on lysosome and DNA structure, and concentrations high as 20 and 40 μg PM₁₀ mL^-1 induced elevated cell death. Ultrastructure analyses showed aluminosilicate, iron, and the emerging metallic contaminants titanium, bismuth, and cerium nanoparticles were incorporated into lung cells, in which the nanocrystallography analysis indicated the bismuth as Bi₂O₃. All internalized metallic nanoparticles were free and unbound in the cytoplasm and nucleus thereby indicating bioavailability and potential interaction to biological processes and cellular structures. Pearson's correlation analysis showed Fe, Ni, Al, Cr, Pb and Hg as the main cytotoxic elements which are associated with the stainless steel production. The presence of internalized nanoparticles in human lung cells exposed to environmental atmospheric matter highlights the need for a greater effort by regulatory agencies to understand their potential damage and hence the need for future regulation, especially of emerging metallic contaminants.

Cytotoxic and Transcriptomic Effects in Avian Hepatocytes Exposed to a Complex Mixture from Air Samples, and Their Relation to the Organic Flame Retardant Signature

Assessing complex environmental mixtures and their effects is challenging. In this study, we evaluate the utility of an avian in vitro screening approach to determine the effects of passive air sampler extracts collected from different global megacities on cytotoxicity and gene expression. Concentrations of a suite of organic flame retardants (OFRs) were quantified in extracts from a total of 19 megacities/major cities in an earlier study, and levels were highly variable across sites. Chicken embryonic hepatocytes were exposed to serial dilutions of extracts from the 19 cities for 24 h. Cell viability results indicate a high level of variability in cytotoxicity, with extracts from Toronto, Canada, having the lowest LC50 value. Partial least squares (PLS) regression analysis was used to estimate LC50 values from OFR concentrations. PLS modeling of OFRs was moderately predictive of LC50 (p-value = 0.0003, r² = 0.66, slope = 0.76, when comparing predicted LC50 to actual values), although only after one outlier city was removed from the analysis. A chicken ToxChip PCR array, comprising 43 target genes, was used to determine effects on gene expression, and similar to results for cell viability, gene expression profiles were highly variable among the megacities. PLS modeling was used to determine if gene expression was related to the OFR profiles of the extracts. Weak relationships to the ToxChip expression profiles could be detected for only three of the 35 OFRs (indicated by regression slopes between 0.6 and 0.5 when comparing predicted to actual OFR concentrations). While this in vitro approach shows promise in terms of evaluating effects of complex mixtures, we also identified several limitations that, if addressed in future studies, might improve its performance.

Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy)

Background: the Lombardy region in Italy was the first area in Europe to record an outbreak of COVID-19 and one of the most affected worldwide. As this territory is strongly polluted, it was hypothesized that pollution had a role in facilitating the diffusion of the epidemic, but results are uncertain. Aim: the paper explores the effect of air pollutants in the first spread of COVID-19 in Lombardy, with a novel geomatics approach addressing the possible confounding factors, the reliability of data, the measurement of diffusion speed, and the biasing effect of the lockdown measures. Methods and results: all municipalities were assigned to one of five possible territorial classes (TC) according to land-use and socio-economic status, and they were grouped into districts of 100,000 residents. For each district, the speed of COVID-19 diffusion was estimated from the ambulance dispatches and related to indicators of mean concentration of air pollutants over 1, 6, and 12 months, grouping districts in the same TC. Significant exponential correlations were found for ammonia (NH₃) in both prevalently agricultural (R² = 0.565) and mildly urbanized (R² = 0.688) areas. Conclusions: this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH₃. As NH₃ could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated.

Estimating PM2.5 concentrations via random forest method using satellite, auxiliary, and ground-level station dataset at multiple temporal scales across China in 2017

Fine particulate matter with aerodynamic diameters less than 2.5 μm (PM_2.5) poses adverse impacts on public health and the environment. It is still a great challenge to estimate high-resolution PM_2.5 concentrations at moderate scales. The current study calibrated PM_2.5 concentrations at a 1 km resolution scale using ground-level monitoring data, Aerosol Optical Depth (AOD), meteorological data, and auxiliary data via Random Forest (RF) model across China in 2017. The three ten-folded cross-validations (CV) methods including sample-based, time-based, and spatial-based validation combined with Coefficient Square (R²), Root-Mean-Square Error (RMSE), and Mean Predictive Error (MPE) have been used for validation at different temporal scales in terms of daily, monthly, heating seasonal, and non-heating seasonal. Finally, the distribution map of PM_2.5 concentrations was illustrated based on the RF model. Some findings were achieved. The RF model performed well, with a relatively high sample-based cross-validation R² of 0.74, a low RMSE of 16.29 μg × m^-3, and a small MPE of -0.282 μg × m^-3. Meanwhile, the performance of the RF model in inferring the PM_2.5 concentrations was well at urban scales except for Chengyu (CY). North China, the CY urban agglomeration, and the northwest of China exhibited relatively high PM_2.5 pollution features, especially in the heating season. The robustness of the RF model in the present study outperformed most statistical regression models for calibrating PM_2.5 concentrations. The outcomes can supply an up-to-date scientific dataset for epidemiological and air pollutants exposure risk studies across China.

Adjuvant contributes Roundup's unexpected effects on A549 cells

Roundup® (RDP) is one of the most representative glyphosate-based herbicides (GBHs), which extensive use increases pressure on environmental safety and potential human health risk. The aim of this study was to investigate whether the adjuvant polyethoxylated tallow amine (POEA) or the herbicidal active ingredient glyphosate isopropylamine salt (GP) in formulation confers RDP cytotoxicity. We demonstrated that RDP and POEA could inhibit the proliferation of human lung A549 cells. Intracellular biochemical assay indicated that collapse of mitochondrial membrane, release of cytochrome c into cytosol, activation of caspase-9/-3, cleavage of poly (ADP-ribose) polymerase (PARP), oxidative DNA damage, DNA single-strand breaks and double-strand breaks are occurred in RDP and POEA treated A549 cells, not occurred in GP treated A549 cells. We conclude that the RDP's effect of apoptosis and DNA damage on human A549 cells is related to the presence of adjuvant POEA in formulation, independent of the herbicidal active ingredient GP. This study would enrich the theoretical basis of the RDP toxicity effects and attract attention on potential human health and environmental safety threat caused by adjuvant.

Estimation of spatially continuous daytime particulate matter concentrations under all sky conditions through the synergistic use of satellite-based AOD and numerical models

Satellite-derived aerosol optical depth (AOD) products are one of main predictors to estimate ground-level particulate matter (PM₁₀ and PM_2.5) concentrations. Since AOD products, however, are only provided under high-quality conditions, missing values usually exist in areas such as clouds, cloud shadows, and bright surfaces. In this study, spatially continuous AOD and subsequent PM₁₀ and PM_2.5 concentrations were estimated over East Asia using satellite- and model-based data and auxiliary data in a Random Forest (RF) approach. Data collected from the Geostationary Ocean Color Imager (GOCI; 8 times per day) in 2016 were used to develop AOD and PM models. Three schemes (i.e. G1, A1, and A2) were proposed for AOD modeling according to target AOD data (GOCI AOD and AERONET AOD) and the existence of satellite-derived AOD. The A2 scheme showed the best performance (validation R² of 0.74 and prediction R² of 0.73 when GOCI AOD did not exist) and the resultant AOD was used to estimate spatially continuous PM concentrations. The PM models with location information produced successful estimation results with R² of 0.88 and 0.90, and rRMSE of 26.9 and 27.2% for PM₁₀ and PM_2.5, respectively. The spatial distribution maps of PM well captured the seasonal and spatial characteristics of PM reported in the literature, which implies the proposed approaches can be adopted for an operational estimation of spatially continuous AOD and PMs under all sky conditions.

Mutagenic and genotoxic effects induced by PM0.5 of different Italian towns in human cells and bacteria: The MAPEC_LIFE study

Particulate matter (PM) is considered an atmospheric pollutant that mostly affects human health. The finest fractions of PM (PM_2.5 or less) play a major role in causing chronic diseases. The aim of this study was to investigate the genotoxic effects of PM_0.5 collected in five Italian towns using different bioassays. The role of chemical composition on the genotoxicity induced was also evaluated. The present study was included in the multicentre MAPEC_LIFE project, which aimed to evaluate the associations between air pollution exposure and early biological effects in Italian children. PM₁₀ samples were collected in 2 seasons (winter and spring) using a high-volume multistage cascade impactor. The results showed that PM_0.5 represents a very high proportion of PM₁₀ (range 10-63%). PM_0.5 organic extracts were chemically analysed (PAH_s, nitro-PAH_s) and tested by the comet assay (A549 and BEAS-2B cells), MN test (A549 cells) and Ames test on Salmonella strains (TA100, TA98, TA98NR and YG1021). The highest concentrations of PAHs and nitro-PAHs in PM_0.5 were observed in the Torino, Brescia and Pisa samples in winter. The Ames test showed low mutagenic activity. The highest net revertants/m³ were observed in the Torino and Brescia samples (winter), and the mutagenic effect was associated with PM_0.5 (p < 0.01), PAH and nitro-PAH (p < 0.05) concentrations. The YG1021 strain showed the highest sensitivity to PM_0.5 samples. No genotoxic effect of PM_0.5 extracts was observed using A549 cells except for some samples in winter (comet assay), while BEAS-2B cells showed light DNA damage in the Torino, Brescia and Pisa samples in winter, highlighting the higher sensitivity of BEAS-2B cells, which was consistent with the Ames test (p < 0.01). The results obtained showed that it is important to further investigate the finest fractions of PM, which represent a relevant percentage of PM₁₀, taking into account the chemical composition and the biological effects induced.

Delineation of 3D dose-time-toxicity in human pulmonary epithelial Beas-2B cells induced by decabromodiphenyl ether (BDE209)

Due to frequent detection in environment as well as in the human body, the adverse effects of decabromodiphenyl ether (BDE209) have been extensively studied in the past few years. However, information regarding the inhalation toxicity of BDE209 to humans is currently limited. In this study, the cytotoxicity, cell damage, and inflammation markers including IL-6, IL-8, and TNF-α in the Beas-2B cell line induced by BDE209 were measured using a central composite design. Results showed that as BDE209 concentrations (5-65 μg mL^-1) and exposure time (6-30 h) were increased, cell viability sharply decreased from 99.7% to 29.7% and LDH activity increased from 0.1% to 13.1%. Furthermore, expression of IL-6, IL-8 and TNF-α transcripts were enhanced from 4.7 to 29.1 fold, 3.4-68.9 fold, and 2.8-47.0 fold, respectively, and the concentration of IL-6 and IL-8 proteins increased from 5.4 to 16.7 pg mL^-1 and 71.0-550.0 pg mL^-1, respectively. Results indicate that BDE209 exposure can inhibit cell viability, increase LDH leakage, and upregulate the transcript (mRNA) and protein levels of inflammatory markers of IL-6 and IL-8 in Beas-2B cells. Moreover, these effects were both dose- and time-dependent, and dose and time had a synergistic effect - enhancing toxicity when in combination. Cell density affected both LDH activity and IL-8 release but had little effect on cell activity and IL-6 release in the Beas-2B cells. In contrast, TNF-α protein was not detected but its mRNA expression level was upregulated. This study will provide a reference for human health risk assessment, especially for the toxic damage that BDE209 exposure can elicit in the respiratory tract.

Risk assessment of occupational exposure to benzene using numerical simulation in a complex geometry of a reforming unit of petroleum refinery

There has been an increasing concern about the continuous and the sudden release of volatile organic pollutants from petroleum refineries and occupational and environmental exposures. Benzene is one of the most prevalent volatile compounds, and it has been addressed by many authors for its potential toxicity in occupational and environmental settings. Due to the complexities of sampling and analysis of benzene in routine and accidental situations, a reliable estimation of the benzene concentration in the outdoor setting of refinery using a computational fluid dynamics (CFD) could be instrumental for risk assessment of occupational exposure. In the present work, a computational fluid dynamic model was applied for exposure risk assessment with consideration of benzene being released continuously from a reforming unit of a refinery. For simulation of benzene dispersion, GAMBIT, FLUENT, and CFD post software are used as preprocessing, processing, and post-processing, respectively. Computational fluid dynamic validation was carried out by comparing the computed data with the experimental measurements. Eventually, chronic daily intake and lifetime cancer risk for routine operations through the two seasons of a year are estimated through the simulation model. Root mean square errors are 0.19 and 0.17 for wind speed and concentration, respectively. Lifetime risk assessments of workers are 0.4-3.8 and 0.0096-0.25 per 1000 workers in stable and unstable atmospheric conditions, respectively. Exposure risk is unacceptable for the head of shift work, chief engineer, and general workers in 141 days (38.77%) in a year. The results of this study show that computational fluid dynamics is a useful tool for modeling of benzene exposure in a complex geometry and can be used to estimate lifetime risks of occupation groups in a refinery setting.