Characterization and within-site variation of environmental metal concentrations around a contaminated site using a community-engaged approach

The Influence of Arsenic Co-Exposure in a Model of Alcohol-Induced Neurodegeneration in C57BL/6J Mice

Both excessive alcohol consumption and exposure to high levels of arsenic can lead to neurodegeneration, especially in the hippocampus. Co-exposure to arsenic and alcohol can occur because an individual with an Alcohol Use Disorder (AUD) is exposed to arsenic in their drinking water or food or because of arsenic found directly in alcoholic beverages. This study aims to determine if co-exposure to alcohol and arsenic leads to worse outcomes in neurodegeneration and associated mechanisms that could lead to cell death. To study this, mice were exposed to a 10-day gavage model of alcohol-induced neurodegeneration with varying doses of arsenic (0, 0.005, 2.5, or 10 mg/kg). The following were examined after the last dose of ethanol: (1) microglia activation assessed via immunohistochemical detection of Iba-1, (2) reactive oxygen and nitrogen species (ROS/RNS) using a colorimetric assay, (3) neurodegeneration using Fluoro-Jade® C staining (FJC), and 4) arsenic absorption using ICP-MS. After exposure, there was an additive effect of the highest dose of arsenic (10 mg/kg) in the dentate gyrus of alcohol-induced FJC+ cells. This additional cell loss may have been due to the observed increase in microglial reactivity or increased arsenic absorption following co-exposure to ethanol and arsenic. The data also showed that arsenic caused an increase in CYP2E1 expression and ROS/RNS production in the hippocampus which could have independently contributed to increased neurodegeneration. Altogether, these findings suggest a potential cyclical impact of co-exposure to arsenic and ethanol as ethanol increases arsenic absorption but arsenic also enhances alcohol's deleterious effects in the CNS.

A practical method for identifying key factors in the distribution and formation of heavy metal pollution at a smelting site

Smelting activities are the main pathway for the anthropogenic release of heavy metals (HMs) into the soil-groundwater environment. It is vital to identify the factors affecting HMs pollution to better prevent and manage soil pollution. The present study conducted a comprehensive investigation of HMs in soil from a large abandoned Zn smelting site. An integrated approach was proposed to classify and quantify the factors affecting HMs pollution in the site. Besides, the quantitative relationship between hydrogeological characteristics, pollution transmission pathways, smelting activities and HMs pollution was established. Results showed that the soils were highly contaminated by HMs with a pollution index trend of As > Zn > Cd > Pb > Hg. In identifying the pollution hotspots, we conclude that the pollution hotspots of Pb, As, Cd, and Hg present a concentrated distribution pattern. Geo-detector method results showed that the dominant driving factors for HMs distribution and accumulation were the potential pollution source and soil permeability. Additionally, the main drivers are variable for different HMs, and the interaction among factors also enhanced soil HMs contamination. Our analysis illustrates how the confounding influences from complex environmental factors can be distilled to identify key factors in pollution formation to guide future remediation strategies.

Using community science for detailed pollution research: a case-study approach in Indianapolis, IN, USA

Heavy metal contamination in urban environments, particularly lead (Pb) pollution, is a health hazard both to humans and ecological systems. Despite wide recognition of urban metal pollution in many cities, there is still relatively limited research regarding heavy metal distribution and transport at the household-scale between soils and indoor dusts-the most important scale for actual human interaction and exposure. Thus, using community-scientist-generated samples in Indianapolis, IN (USA), we applied bulk chemistry, Pb isotopes, and scanning electron microscopy (SEM) to illustrate how detailed analytical techniques can aid in interpretation of Pb pollution distribution at the household-scale. Our techniques provide definitive evidence for Pb paint sourcing in some homes, while others may be polluted with Pb from past industrial/vehicular sources. SEM revealed anthropogenic particles suggestive of Pb paint and the widespread occurrence of Fe-rich metal anthropogenic spherules across all homes, indicative of pollutant transport processes. The variability of Pb pollution at the household scale evident in just four homes is a testament to the heterogeneity and complexity of urban pollution. Future urban pollution research efforts would do well to utilize these more detailed analytical methods on community-sourced samples to gain better insight into where the Pb came from and how it currently exists in the environment. However, these methods should be applied after large-scale pollution screening techniques such as portable X-ray fluorescence (XRF), with more detailed analytical techniques focused on areas where bulk chemistry alone cannot pinpoint dominant pollution mechanisms and where community scientists can also give important metadata to support geochemical interpretations.

In vitro and in silico bioaccessibility of urban dusts contaminated by multiple legacy sources of lead (Pb)

Lead contamination from gasoline, paint, pesticides, and smelting have unique chemical structures. Recent investigations into Pb speciation in urban soils and dusts from multiple sources have revealed emerging forms which differ from the initial sources. This results from reactions with soil constituents leading to transformation to new forms for which the bioaccessibilities remain uninvestigated. We investigated the in vitro and in silico bioaccessibility of these emerging forms in three physiologically relevant milieux: artificial lysosomal fluid (ALF), simulated epithelial lung fluid (SELF), and simulated gastric fluid (SGF). Species were validated using extended X-ray absorption fine structure spectroscopy. Results highlight diverse bioaccessibilities which are form and compartmentally-dependent. In ALF the bioaccessibility trend was humate-bound Pb (86%) > hydrocerussite (79%) > Fe oxide-bound Pb (47%) > galena (10%) > pyromorphite (4%) > Mn oxide-bound Pb (2%). Humate-bound Pb, hydrocerussite, Fe and Mn oxide-bound Pb were 100% bioaccessible in SGF while pyromorphite and galena were 26%, and 8%, respectively. Bioaccessibility in SELF was very low (< 1%) and significantly lower than ALF and SGF (p < 0.001). In silico bioaccessibilities modeled using equilibrium solubilities in extraction solutions were in good agreement with empirical measurements. These emerging forms of Pb have a wide range of bioaccessibilities that can influence their toxicity and impact on human health.

Using Community Science to Better Understand Lead Exposure Risks

Lead (Pb) is a neurotoxicant that particularly harms young children. Urban environments are often plagued with elevated Pb in soils and dusts, posing a health exposure risk from inhalation and ingestion of these contaminated media. Thus, a better understanding of where to prioritize risk screening and intervention is paramount from a public health perspective. We have synthesized a large national data set of Pb concentrations in household dusts from across the United States (U.S.), part of a community science initiative called "DustSafe." Using these results, we have developed a straightforward logistic regression model that correctly predicts whether Pb is elevated (>80 ppm) or low (<80 ppm) in household dusts 75% of the time. Additionally, our model estimated 18% false negatives for elevated Pb, displaying that there was a low probability of elevated Pb in homes being misclassified. Our model uses only variables of approximate housing age and whether there is peeling paint in the interior of the home, illustrating how a simple and successful Pb predictive model can be generated if researchers ask the right screening questions. Scanning electron microscopy supports a common presence of Pb paint in several dust samples with elevated bulk Pb concentrations, which explains the predictive power of housing age and peeling paint in the model. This model was also implemented into an interactive mobile app that aims to increase community-wide participation with Pb household screening. The app will hopefully provide greater awareness of Pb risks and a highly efficient way to begin mitigation.

Evaluation of redevelopment priority of abandoned industrial and mining land based on heavy metal pollution

Heavy metal contamination in soil is an important factor affecting the determination of safe redevelopment methods for industrial and mining land. In this paper, the soil environment of a typical mining city in northern China was taken as the research object, 148 surface soil samples were collected and the contents of heavy metals were measured. The health risk classification criteria for heavy metal contamination of soils and the method of priority assessment for redevelopment were used. The results showed that: the risk of potential utilization types of heavy metals in the abandoned industrial and mining land is different. When the utilization type is agricultural land, the soil environmental quality is good as a whole, and a small number of plots are polluted by cadmium (Cd)and mercury (Hg); When the land use type is construction land, the risk of heavy metal pollution comes from chromium (Cr); The priority of development in this study area is as follows: agricultural land > construction land > ecological land.