Identification of source areas of polycyclic aromatic hydrocarbons in Ulsan, South Korea, using hybrid receptor models and the conditional bivariate probability function

This study identifies the emission source areas for the atmospheric polycyclic aromatic hydrocarbons (PAHs) detected in Ulsan, South Korea. To achieve this, in addition to a conditional bivariate probability function...

A geostatistical approach to estimating source apportionment in urban and peri-urban soils using the Czech Republic as an example

Unhealthy soils in peri-urban and urban areas expose individuals to potentially toxic elements (PTEs), which have a significant influence on the health of children and adults. Hundred and fifteen (n = 115) soil samples were collected from the district of Frydek Mistek at a depth of 0–20 cm and measured for PTEs content using Inductively coupled plasma—optical emission spectroscopy. The Pearson correlation matrix of the eleven relevant cross-correlations suggested that the interaction between the metal(loids) ranged from moderate (0.541) correlation to high correlation (0.91). PTEs sources were calculated using parent receptor model positive matrix factorization (PMF) and hybridized geostatistical based receptor model such as ordinary kriging-positive matrix factorization (OK-PMF) and empirical Bayesian kriging-positive matrix factorization (EBK-PMF). Based on the source apportionment, geogenic, vehicular traffic, phosphate fertilizer, steel industry, atmospheric deposits, metal works, and waste disposal are the primary sources that contribute to soil pollution in peri-urban and urban areas. The receptor models employed in the study complemented each other. Comparatively, OK-PMF identified more PTEs in the factor loadings than EBK-PMF and PMF. The receptor models performance via support vector machine regression (SVMR) and multiple linear regression (MLR) using root mean square error (RMSE), R square (R2) and mean square error (MAE) suggested that EBK-PMF was optimal. The hybridized receptor model increased prediction efficiency and reduced error significantly. EBK-PMF is a robust receptor model that can assess environmental risks and controls to mitigate ecological performance.

The Microplastic Cycle: An Introduction to a Complex Issue

The microplastic cycle was originally and formally introduced and defined as a novel concept and paradigm for understanding plastic pollution and its fluxes across ecosystem reservoirs. This concept has now been expanded to include macroplastic particles and links all aspects of the fate, transport, and effects of plastic pollution, including source-receptor models in the environment, and expanded on previously established perspectives that viewed the plastic pollution issue in a less integrated manner. The value of this paradigm is that this perspective integrates three basic scientific spheres: environmental chemistry, biology (i.e., trophic transfer), and human health. The goal of this chapter is to introduce readers to the microplastic pollution problem and to outline the microplastic cycle as a concept and holistic paradigm for addressing this ubiquitous environmental and potential public health problem. The specific objectives of this chapter were to (1) introduce this volume and its chapters by outlining the microplastic pollution issue in the context of the entire plastic cycle; (2) evaluate fluxes of microplastics across different ecosystem compartments, including the atmosphere, lithosphere, hydrosphere. and biosphere, including humans; and (3) provide insights on public policy and potential solutions to the microplastic pollution problem.

Acute effects of the imidacloprid metabolite desnitro-imidacloprid on human nACh receptors relevant for neuronal signaling

Several neonicotinoids have recently been shown to activate the nicotinic acetylcholine receptor (nAChR) on human neurons. Moreover, imidacloprid (IMI) and other members of this pesticide family form a set of diverse metabolites within crops. Among these, desnitro-imidacloprid (DN-IMI) is of special toxicological interest, as there is evidence (i) for human dietary exposure to this metabolite, (ii) and that DN-IMI is a strong trigger of mammalian nicotinic responses. We set out here to quantify responses of human nAChRs to DN-IMI and an alternative metabolite, IMI-olefin. To evaluate toxicological hazards, these data were then compared to those of IMI and nicotine. Ca2+-imaging experiments on human neurons showed that DN-IMI exhibits an agonistic effect on nAChRs at sub-micromolar concentrations (equipotent with nicotine) while IMI-olefin activated the receptors less potently (in a similar range as IMI). Direct experimental data on the interaction with defined receptor subtypes were obtained by heterologous expression of various human nAChR subtypes in Xenopus laevis oocytes and measurement of the transmembrane currents evoked by exposure to putative ligands. DN-IMI acted on the physiologically important human nAChR subtypes α7, α3β4, and α4β2 (high-sensitivity variant) with similar potency as nicotine. IMI and IMI-olefin were confirmed as nAChR agonists, although with 2–3 orders of magnitude lower potency. Molecular docking studies, using receptor models for the α7 and α4β2 nAChR subtypes supported an activity of DN-IMI similar to that of nicotine. In summary, these data suggest that DN-IMI functionally affects human neurons similar to the well-established neurotoxicant nicotine by triggering α7 and several non-α7 nAChRs.

Measurement report: Receptor modeling for source identification of urban fine and coarse particulate matter using hourly elemental composition

The elemental composition of the fine (PM2.5) and coarse (PM2.5−10) fraction of atmospheric particulate matter was measured at an hourly time resolution by the use of a streaker sampler during a winter period at a Central European urban background site in Warsaw, Poland. A combination of multivariate (Positive Matrix Factorization) and wind- (Conditional Probability Function) and trajectory-based (Cluster Analysis) receptor models was applied for source apportionment. It allowed for the identification of five similar sources in both fractions, including sulfates, soil dust, road salt, and traffic- and industry-related sources. Another two sources, i.e., Cl-rich and wood and coal combustion, were solely identified in the fine fraction. In the fine fraction, aged sulfate aerosol related to emissions from domestic solid fuel combustion in the outskirts of the city was the largest contributing source to fine elemental mass (44 %), while traffic-related sources, including soil dust mixed with road dust, road dust, and traffic emissions, had the biggest contribution to the coarse elemental mass (together accounting for 83 %). Regional transport of aged aerosols and more local impact of the rest of the identified sources played a crucial role in aerosol formation over the city. In addition, two intensive Saharan dust outbreaks were registered on 18 February and 8 March 2016. Both episodes were characterized by the long-range transport of dust at 1500 and 3000 m over Warsaw and the concentrations of the soil component being 7 (up to 3.5 µg m−3) and 6 (up to 6.1 µg m−3) times higher than the mean concentrations observed during non-episodes days (0.5 and 1.1 µg m−3) in the fine and coarse fractions, respectively. The set of receptor models applied to the high time resolution data allowed us to follow, in detail, the daily evolution of the aerosol elemental composition and to identify distinct sources contributing to the concentrations of the different PM fractions, and it revealed the multi-faceted nature of some elements with diverse origins in the fine and coarse fractions. The hourly resolution of meteorological conditions and air mass back trajectories allowed us to follow the transport pathways of the aerosol as well.