A novel computational solution to the health risk assessment of air pollution via joint toxicity prediction: A case study on selected PAH binary mixtures in particulate matters

Machine Learning-Based Hazard-Driven Prioritization of Features in Nontarget Screening of Environmental High-Resolution Mass Spectrometry Data

Nontarget high-resolution mass spectrometry screening (NTS HRMS/MS) can detect thousands of organic substances in environmental samples. However, new strategies are needed to focus time-intensive identification efforts on features with the highest potential to cause adverse effects instead of the most abundant ones. To address this challenge, we developed MLinvitroTox, a machine learning framework that uses molecular fingerprints derived from fragmentation spectra (MS2) for a rapid classification of thousands of unidentified HRMS/MS features as toxic/nontoxic based on nearly 400 target-specific and over 100 cytotoxic endpoints from ToxCast/Tox21. Model development results demonstrated that using customized molecular fingerprints and models, over a quarter of toxic endpoints and the majority of the associated mechanistic targets could be accurately predicted with sensitivities exceeding 0.95. Notably, SIRIUS molecular fingerprints and xboost (Extreme Gradient Boosting) models with SMOTE (Synthetic Minority Oversampling Technique) for handling data imbalance were a universally successful and robust modeling configuration. Validation of MLinvitroTox on MassBank spectra showed that toxicity could be predicted from molecular fingerprints derived from MS2 with an average balanced accuracy of 0.75. By applying MLinvitroTox to environmental HRMS/MS data, we confirmed the experimental results obtained with target analysis and narrowed the analytical focus from tens of thousands of detected signals to 783 features linked to potential toxicity, including 109 spectral matches and 30 compounds with confirmed toxic activity.

Toxicological Effects of Secondary Air Pollutants

Secondary air pollutants, originating from gaseous pollutants and primary particulate matter emitted by natural sources and human activities, undergo complex atmospheric chemical reactions and multiphase processes. Secondary gaseous pollutants represented by ozone and secondary particulate matter, including sulfates, nitrates, ammonium salts, and secondary organic aerosols, are formed in the atmosphere, affecting air quality and human health. This paper summarizes the formation pathways and mechanisms of important atmospheric secondary pollutants. Meanwhile, different secondary pollutants' toxicological effects and corresponding health risks are evaluated. Studies have shown that secondary pollutants are generally more toxic than primary ones. However, due to their diverse source and complex generation mechanism, the study of the toxicological effects of secondary pollutants is still in its early stages. Therefore, this paper first introduces the formation mechanism of secondary gaseous pollutants and focuses mainly on ozone's toxicological effects. In terms of particulate matter, secondary inorganic and organic particulate matters are summarized separately, then the contribution and toxicological effects of secondary components formed from primary carbonaceous aerosols are discussed. Finally, secondary pollutants generated in the indoor environment are briefly introduced. Overall, a comprehensive review of secondary air pollutants may shed light on the future toxicological and health effects research of secondary air pollutants.

A novel approach to predict the comprehensive EROD potency: Mechanism-based curve fitting of CYP1A1 activity by PAHs

Cytochrome P450 1A1 (CYP1A1) plays critical roles in polycyclic aromatic hydrocarbon (PAH) toxicity, including DNA adduction and ROS generation. Therefore, CYP1A1 activity quantified by the 7-ethoxyresorufin-O-deethylase (EROD) assay (named EROD potency) has been considered a typical biomarker of PAH exposure and toxicity. The EROD dose-response curve always presents a biphasic style, increasing at low concentrations and decreasing at high concentrations of PAHs, but relative effect potency (REP) commonly used in PAH risk assessment is only involved in the increasing phase. In this study, a full bell-shaped EROD curve fitting formula Eq. (1) was obtained by considering both CYP1A1 mRNA induction and enzyme inhibition to completely assess the EROD potency of PAHs. Correspondingly, in silico models of QSAR and docking methods successfully predicted the full EROD curves of PAHs, and the structure-activity relationship indicated that PAHs with heavy molecular weight and large diameter showed stronger EROD potency. Further EROD potency with predicted curve parameters (EC_50,ind and area index) was confirmed by the reported REP (R² = 0.697-0.977) and experimental data from human and mouse cells (R² = 0.700-0.804). This study provides a novel curve fitting for the EROD dose-response relationship and a prediction model for PAH EROD potency.

The Long Goodbye: Finally Moving on from the Relative Potency Approach to a Mixtures Approach for Polycyclic Aromatic Hydrocarbons (PAHs)

For the past several decades, a relative potency approach has been used to estimate the human health risks from exposure to polycyclic aromatic hydrocarbon (PAH) mixtures. Risk estimates are derived using potency equivalence factors (PEFs; also called relative potency factors [RPFs]), based on the ratio of selected PAHs to benzo[a]pyrene (BaP), expressed qualitatively by orders of magnitude. To quantify PEFs for 18 selected carcinogenic PAHs, a systematic approach with a priori and dose response criteria was developed, building on draft work by the US EPA in 2010 and its review by US EPA Science Advisory Board (SAB) in 2011. An exhaustive search for carcinogenicity studies that included both target PAHs and BaP with environmentally relevant exposure routes found only 48 animal bioassay datasets (mostly pre-1992 based on skin painting). Only eight datasets provided adequate low-response data, and of these only four datasets were appropriate for modeling to estimate PEFs; only benzo[b]fluoranthene and cyclopenta[c,d]pyrene had a PEF that could be quantified. Thus, current knowledge of PAH carcinogenicity is insufficient to support quantitative PEFs for PAH mixtures. This highlights the long-acknowledged need for an interdisciplinary approach to estimate risks from PAH mixtures. Use of alternative and short-term toxicity testing methods, improved mixture characterization, understanding the fate and bioavailability of PAH mixtures, and understanding exposure route-related differences in carcinogenicity are discussed as ways to improve the understanding of the risks of PAHs.

Chemical Characterization of Particulate Matter in the Renaissance City of Ferrara

Atmospheric aerosols are today a key issue in air pollution, mostly related to public health. Two test areas in Ferrara, one in the city center (urban location) and one in the industrial area (industrial location), were studied in June–July 2016 using the SEM technique to identify the environmental impact of some potential pollutant sources. Collection was performed using adhesive tapes applied on the surface of road signs, which allows to select particulate matter moving on air with diffusion movement and to exclude the particles usually deposed by the gravitational process. Dimensional characterization has shown that, usually, smaller particles tend to aggregate themselves in bigger polycrystalline particles with the geometric diameter of up to 10 μm. Micro-analytical data have revealed a wide heterogeneous range of compositions: more abundant silicate followed by carbonate, chlorine, sulphate, carbon, and organic. This preliminary study has highlighted that the Renaissance city of Ferrara is affected by an environmental problem linked to the presence of particulate matter induced by industrial activities, as is the case with some of the most polluted cities in the world. The observations and analytical data pointed out the need for further investigation to better define the features of the fine particulate matter. This will be useful to preserve the cultural heritage of this Medieval-Renaissance city.

Exposure to Particulate PAHs on Potential Genotoxicity and Cancer Risk among School Children Living Near the Petrochemical Industry

This study aimed to assess the association of exposure to particle-bound (PM_2.5) polycyclic aromatic hydrocarbons (PAHs) with potential genotoxicity and cancer risk among children living near the petrochemical industry and comparative populations in Malaysia. PM_2.5 samples were collected using a low-volume sampler for 24 h at three primary schools located within 5 km of the industrial area and three comparative schools more than 20 km away from any industrial activity. A gas chromatography-mass spectrometer was used to determine the analysis of 16 United States Environmental Protection Agency (USEPA) priority PAHs. A total of 205 children were randomly selected to assess the DNA damage in buccal cells, employing the comet assay. Total PAHs measured in exposed and comparative schools varied, respectively, from 61.60 to 64.64 ng m^-3 and from 5.93 to 35.06 ng m^-3. The PAH emission in exposed schools was contributed mainly by traffic and industrial emissions, dependent on the source apportionment. The 95th percentiles of the incremental lifetime cancer risk estimated using Monte Carlo simulation revealed that the inhalation risk for the exposed children and comparative populations was 2.22 × 10^-6 and 2.95 × 10^-7, respectively. The degree of DNA injury was substantially more severe among the exposed children relative to the comparative community. This study reveals that higher exposure to PAHs increases the risk of genotoxic effects and cancer among children.

Identification of structural properties influencing the metabolism of polycyclic aromatic hydrocarbons by cytochrome P450 1A1

Cytochrome P450 1A1 (CYP1A1) has served as a known metabolic enzyme that mediates the carcinogenesis of polycyclic aromatic hydrocarbons (PAHs). However, the structural mechanism involved in the metabolic capacity remains unclear. In this study, thirty-three calculated properties representing the physicochemical and electronic properties of PAH and PAH-CYP1A1 interactions were utilized to identify the key structural properties that affect metabolic processes, including binding ability, metabolic clearance, and mutagenicity, using a quantitative structure-activity relationship (QSAR) strategy combined with docking methods, QM/MM calculations and ab initio calculations. van der Waals interactions (glide vdw) appeared to be important for PAH binding to CYP1A1 and were mainly affected by the molecular weight and hydrophobic structures of PAHs. Interaction features between PAHs and heme, including the distance between iron and carbons of PAHs (Fe_C_min) and heme vdw, coordinately influence the metabolic clearance of PAHs. Furthermore, the electronic properties (ESP neg variance) appeared to be critical for the mutagenicity of PAHs by CYP1A1 through influencing epoxide metabolite formation. The QSAR models with these key properties provide a new perspective on the structural mechanism of PAH metabolism and provide a useful in silico tool for screening, classifying and predicting PAHs for their metabolism-related toxicities and risk assessment in the environment.

Spatial distribution of fine and coarse particulate matter during a southwest monsoon in Peninsular Malaysia

This study aimed to determine the spatial distribution of PM_2.5 and PM₁₀ collected in four regions (North, Central, South and East Coast) of Peninsular Malaysia during the southwest monsoon. Concurrent measurements of PM_2.5 and PM₁₀ were performed using a high volume sampler (HVS) for 24 h (August to September 2018) collecting a total of 104 samples. All samples were then analysed for water soluble inorganic ions (WSII) using ion chromatography, trace metals using inductively coupled plasma-mass spectroscopy (ICP-MS) and polycyclic aromatic hydrocarbon (PAHs) using gas chromatography-mass spectroscopy (GC-MS). The results showed that the highest average PM_2.5 concentration during the sampling campaign was in the North region (33.2 ± 5.3 μg m^-3) while for PM₁₀ the highest was in the Central region (38.6 ± 7.70 μg m^-3). WSII recorded contributions of 22% for PM_2.5 and 20% for PM₁₀ mass, with SO₄^2- the most abundant species with average concentrations of 1.83 ± 0.42 μg m^-3 (PM_2.5) and 2.19 ± 0.27 μg m^-3 (PM₁₀). Using a Positive Matrix Factorization (PMF) model, soil fertilizer (23%) was identified as the major source of PM_2.5 while industrial activity (25%) was identified as the major source of PM₁₀. Overall, the studied metals had hazard quotients (HQ) value of <1 indicating a very low risk of non-carcinogenic elements while the highest excess lifetime cancer risk (ELCR) was recorded for Cr VI in the South region with values of 8.4E-06 (PM_2.5) and 6.6E-05 (PM₁₀). The incremental lifetime cancer risk (ILCR) calculated from the PAH concentrations was within the acceptable range for all regions.

Ecological and human health risk assessment

The literature review presented in this paper includes the ecological and human health risk assessment in the form of receptors in the environment. The main objective of this review to highlight a summary of the many studies undertaken in the year 2019. The first part of the review covers the papers published on the health risk assessment related to human and ecological health. This article focuses on methods and tools utilized for the analysis of scientific studies and the data. The review provides main issues such as interpretation of data, uncertainty, and policies related to the management of risks. The ecological and human health risk assessment is divided into two main sections. Each of these sections presents in broad the risk assessment process namely pollution studies, remediation, and tools required for the management of natural resources and the environment.

Pathway-based assessment of single chemicals and mixtures by a high-throughput transcriptomics approach

The ever-increasing number of chemicals and complex mixtures demands a high-throughput and cost-effective approach for chemical safety assessment. High-throughput transcriptomics (HTT) is promising in investigating genome-scale perturbation of chemical exposure in concentration-dependent manner. However, the application of HTT has been limited due to lack of methodology for single chemicals and mixture assessment. This study aimed to evaluate the ability of a newly-developed human reduced transcriptomics (RHT) approach to assess pathway-based profiles of single chemicals, and to develop a biological pathway-based approach for benchmarking mixture potency using single chemical-based prediction model. First, concentration-dependent RHT were used to qualitatively and quantitatively differentiate pathway-based patterns of different chemicals, using three model toxicants, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), triclosan (TCS) and 5-Chloro-6-hydroxy-2,2',4,4'-tetrabromodiphenyl ether (5-Cl-6-OH-BDE-47). AHR-regulated genes and pathways were most sensitively induced by TCDD, while TCS and 5-Cl-6-OH-BDE-47 were much less potent in AHR-associated activation, which was concordant with known MoA of each single chemical. Second, two artificial mixtures and their components of twelve individual chemicals were performed with concentration-dependent RHT. Concentration addition (CA) and independent action (IA) models were used to predict transcriptional potency of mixtures from transcriptomics of individual chemicals. For overall bioactivity, CA and IA models can both predict potency of observed responses within 95% confidence interval. For specific biological processes, multiple biological processes such as hormone signaling and DNA damage can be predicted using CA models for mixtures. The concentration-dependent RHT can provide a powerful approach for qualitative and quantitative assessment of biological pathway perturbated by environment chemical and mixtures.

Air Pollution in Kazakhstan and Its Health Risk Assessment

Background:

Air pollution in Kazakhstan is caused by many factors and poses serious threats to public health. Ambient air in the cities of Kazakhstan is polluted due to mining and processing of mineral resources, oil and gas production, gasoline and diesel fuel motor vehicles, industrial enterprises.

Objective:

The study aim is to assess the air pollution degree in most significant settlements of Kazakhstan and define risk levels for the population health. Ambient air monitoring was conducted in 26 cities. Air pollution severity was assessed by the analysis results and processing of air samples taken at the stationary observation posts. Health risk assessment due to chemical factors was calculated according to the approved risk assessment methodology.

Findings:

There is high risk of acute adverse effects risk from suspended particles, oxides and dioxides of nitrogen and sulfur in almost all of the studied cities. The most unfavorable situation is in Ust-Kamenogorsk. Also, there is the adverse chronic effects risk caused by suspended particles exposure in majority of the studied cities. Extremely high chronic effects risk as a result of heavy metals exposure was detected in Ust-Kamenogorsk, Shymkent, Almaty, Taraz and Balkhash. Unacceptable carcinogenic risk levels have been determined for professional groups and the whole population with respect to cadmium in Shymkent, Almaty, Balkhash; arsenic in Shymkent, Almaty, Balkhash; lead in Taraz; chromium – in Shymkent, Aktobe, Almaty and Balkhash. Thus, the values of the hazard quotients and indices for acute and chronic exposure in most of the studied cities of Kazakhstan exceed the permissible level equal to 1.0.

Conclusion:

Due to the unacceptable risk levels in the cities it is strongly recommended to conduct a detailed study of the health status of the population depending on the air pollution.

Exploring the Occurrence and Temporal Variation of ToxCast Chemicals in Fine Particulate Matter Using Suspect Screening Strategy

Existence of emerging contaminants in the environment is of great importance for health risk assessment. The consensus on categories and numbers of the emerging contaminants in airborne fine particulate matter (PM_2.5) is still extremely deficient. In this study, an in-house data set was constructed containing 890 unique ToxCast (Phase I and Phase II) chemicals. Occurrence and temporal variation of the chemicals was investigated by a suspect screening workflow in 60 PM_2.5 samples from January to December of 2016 in Beijing. Eighty-nine compounds were identified in 12 substance categories, which covered a broad range of physicochemical properties. Quantification/semiquantification results showed that phthalates, phenols, and carboxylic esters were the three most predominant categories, with mean concentrations of 7.82, 4.42, and 4.11 ng/m³, respectively. Four diverse temporal variation patterns were discerned, which could be explained by correlations of chemical concentrations (or instrumental responses) with meteorological parameters. An extended retrospective suspect screening was also performed to reveal the presence of several analogues of the identified chemicals that were not included in the data set. Another 75 pollutants were tentatively recognized, and comparison of estimated composition profiles based on instrumental responses suggested the identified ToxCast chemicals are a notable subset of typical emerging contaminants. The results might facilitate ranking of organic pollutants with active biological effects in PM_2.5 samples.