Submerged zone and vegetation drive distribution of heavy metal fractions and microbial community structure: Insights into stormwater biofiltration system

Resilience of stormwater biofilters following the deposition of wildfire residues: Implication on downstream water quality management in wildfire-prone regions

Stormwater treatment systems such as biofilters could intercept and remove pollutants from contaminated runoff in wildfire-affected areas, ensuring the protection of water quality downstream. However, the deposition of wildfire residues such as ash and black carbon onto biofilters could potentially impair their stormwater treatment functions. Yet, whether and how wildfire residue deposition could affect biofilter functions is unknown. This study examines the impact of wildfire residue deposition on biofilter infiltration and pollutant removal capacities. Exposure to wildfire residues decreased the infiltration capacity based on the amount of wildfire deposited. Wildfire residues accumulated at the top layer of the biofilter, forming a cake layer, but scraping this layer restored the infiltration capacity. While the deposition of wildfire residues slightly changed the pore water geochemistry, it did not significantly alter the removal of metals and E. coli. Although wildfire residues leached some metals into pore water within the simulated root zone, the leached metals were effectively removed by the compost present in the filter media. Collectively, these results indicate that biofilters downstream of wildfire-prone areas could remain resilient or functional and protect downstream water quality if deposited ash is periodically scraped to restore any loss of infiltration capacity following wildfire residue deposition.

The effects of heavy rain on the fate of urban and agricultural pollutants in the riverside area around weirs using multi-isotope, microbial data and numerical simulation

The increase in extreme heavy rain due to climate change is a critical factor in the fate of urban and agricultural pollutants in aquatic system. Nutrients, including NO3- and PO43-, are transported with surface and seepage waters into rivers, lakes and aquifers and can eventually lead to algal blooms. δ15N-NO3-, δ18O-NO3-, and δ11B combined with hydrogeochemical and microbial data for groundwater and surface water samples were interpreted to evaluate the fate of nutrients in a riverside area around weirs in Daegu, South Korea. Most of the ions showed similar concentrations in the groundwater samples before and after heavy rain while concentrations of major ions in surface water samples were diluted after heavy rain. However, Si, PO43-, Zn, Ce, La, Pb, Cu and a number of waterborne pathogens increased in surface water after heavy rain. The interpretation of δ11B, δ15N-NO3-, and δ18O-NO3- values using a Bayesian mixing model revealed that sewage and synthetic fertilizers were the main sources of contaminants in the groundwater and surface water samples. δ18O and SiO2 interpreted using the Bayesian mixing model indicated that the groundwater component in the surface water increased from 4.4 % to 17.9 % during the wet season. This is consistent with numerical simulation results indicating that the direct surface runoff and the groundwater baseflow contributions to the river system had also increased 6.4 times during the wet season. The increase in proteobacteria and decrease of actinobacteria in the surface water samples after heavy rain were also consistent with an increase of surface runoff and an increased groundwater component in the surface water. This study suggests that source apportionment based on chemical and multi-isotope data combined with numerical modeling approaches can be useful for identifying main hydrological and geochemical processes in riverside areas around weirs and can inform suggestions of effective methods for water quality management.

Health Risk Assessments and Microbial Community Analyses of Groundwater from a Heavy Metal-Contaminated Site in Hezhou City, Southwest China

In industrial site groundwater, heavy metal pollution is relatively common, causing great harm to the surrounding environment and human health. To explore the relationships between the heavy metal concentration, health risks and microbial community distribution, the groundwater from a polluted site at an abandoned processing plant in Hezhou City, China, is taken as the research object. A health risk assessment model recommended by the United States Environmental Protection Agency (US EPA) is used for the evaluation, and high-throughput sequencing technology is used to analyze the characteristics of the microbial community in the groundwater. The results show that the heavy metal pollution levels of five monitoring wells are different. The monitoring well labelled HLJ2 is polluted by Cu, Mn, Ni and Cd, and the other four monitoring wells are polluted by As and Cd to varying degrees. The carcinogenic risk values of heavy metals in the groundwater environments of the five monitoring wells are all greater than the acceptable range, and only the noncarcinogenic risk value of the HLJ2 monitoring well exceeds 1, which greatly impacts health. The risks posed by the contaminants in the site groundwater through the ingestion route of drinking water are greater than those caused by the ingestion route of skin contact. The groundwater environments of the five monitoring wells contain Proteobacteria and Patescibacteria, indicating that these two bacteria have certain tolerances to heavy metal pollution. The microbial community composition varies between the monitoring wells, suggesting that different concentrations and types of heavy metal contamination promote different types of bacterial growth. Studies have shown that Proteobacteria have many heavy metal resistance genes, improving their tolerance in heavy metal-polluted environments; additionally, Proteobacteria can transport heavy metals, which is conducive to the restoration of polluted sites.