An investigation on mobility of heavy metals for assessing the reusability of soil-like material reclaimed from mining of municipal solid waste dumpsites

Exploring the microbe-mediated biological processes of BTEX and toxic metal(loid)s in aging petrochemical landfills

Aging petrochemical landfills serve as reservoirs of inorganic and organic contaminants, posing potential risks of contamination to the surrounding environment. Identifying the pollution characteristics and elucidating the translocation/ transformation processes of typical contaminants in aging petrochemical landfills are crucial yet challenging endeavors. In this study, we employed a combination of chemical analysis and microbial metagenomic technologies to investigate the pollution characteristics of benzene, toluene, ethylbenzene, and xylene (BTEX) as well as metal(loid)s in a representative aging landfill, surrounding soils, and underlying groundwater. Furthermore, we aimed to explore their transformations driven by microbial activity. Our findings revealed widespread distribution of metal(loid)s, including Cd, Ni, Cu, As, Mn, Pb, and Zn, in these environmental media, surpassing soil background values and posing potential ecological risks. Additionally, microbial processes were observed to contribute significantly to the degradation of BTEX compounds and the transformation of metal(loid)s in landfills and surrounding soils, with identified microbial communities and functions playing key roles. Notably, co-occurrence network analysis unveiled the coexistence of functional genes associated with BTEX degradation and metal(loid) transformation, driven primarily by As, Ni, and Cd. These results shed light on the co-selection of resistance traits against BTEX and metal(loid) contaminants in soil microbial consortia under co-contamination scenarios, supporting microbial adaptive evolution in aging petrochemical landfills. The insights gained from this study enhance our understanding of characteristic pollutants and microbial transformation processes in aging landfills, thereby facilitating improved landfill management and contamination remediation strategies.

Prediction models for bioavailability of Cu and Zn during composting: Insights into machine learning

Bioavailability assessment of heavy metals in compost products is crucial for evaluating associated environmental risks. However, existing experimental methods are time-consuming and inefficient. The machine learning (ML) method has demonstrated excellent performance in predicting heavy metal fractions. In this study, based on the conventional physicochemical properties of 260 compost samples, including compost time, temperature, electrical conductivity (EC), pH, organic matter (OM), total phosphorus (TP), total nitrogen, and total heavy metal contents, back propagation neural network, gradient boosting regression, and random forest (RF) models were used to predict the dynamic changes in bioavailable fractions of Cu and Zn during composting. All three models could be used for effective prediction of the variation trend in bioavailable fractions of Cu and Zn; the RF model showed the best prediction performance, with the prediction level higher than that reported in related studies. Although the key factors affecting changes among fractions were different, OM, EC, and TP were important for the accurate prediction of bioavailable fractions of Cu and Zn. This study provides simple and efficient ML models for predicting bioavailable fractions of Cu and Zn during composting, and offers a rapid evaluation method for the safe application of compost products.

Landfill leachate a potential challenge towards sustainable environmental management

The increasing amount of waste globally has led to a rise in the use of landfills, causing more pollutants to be released through landfill leachate. This leachate is a harmful mix formed from various types of waste at a specific site, and careful disposal is crucial to prevent harm to the environment. Understanding the physical and chemical properties, age differences, and types of landfills is essential to grasp how landfill leachate behaves in the environment. The use of Sustainable Development Goals (SDGs) in managing leachate is noticeable, as applying these goals directly is crucial in reducing the negative effects of landfill leachate. This detailed review explores the origin of landfill leachate, its characteristics, global classification by age, composition analysis, consequences of mismanagement, and the important role of SDGs in achieving sustainable landfill leachate management. The aim is to provide a perspective on the various aspects of landfill leachate, covering its origin, key features, global distribution, environmental impacts from poor management, and importance of SDGs which can guide for sustainable mitigation within a concise framework.

Concentration, speciation and risk effects of multiple environmentally sensitive trace elements in respirable fine-grained fly ash

Respirable fine-grained fly ash (RFA) is captured very inefficiently by existing air purification devices of power plant, leading to increasing concerns regarding their migration and subsequent interaction with body due to fine particle size and its complex toxic composition. Trace elements of RFA in three groups with five different sizes between 8-13 µm were analyzed in terms of available concentration, speciation and risk effects. The concentration, pollution level and ecological risk level of elements in RFA were related to particle sizes. Chronic non-carcinogenic effect risk (NER) and carcinogenic effect risk (CER) were negatively correlated with particle size. The individual weight of exposed subjects, corresponding trace elements concentration and ingestion rate in RFA were three significant variables influencing CER. NER and CER had a tenfold exaggerated effect when calculated using total element concentration of RFA. In addition to individual differences and exposure conditions, trace element properties, speciation and available concentration were the dominant factor responsible for ecological and environmental effects of trace elements in RFA, following the order As>Ni, Mn>Cr>Pb>Cu>Zn. Results of this work highlight the effects and differences of trace elements in RFA on ecology and health, and provide a basis for further pollution control and human health warning.

Identification and assessment of appropriate remediation management techniques for the recovery of soil-like material produced in landfill mining

Landfill mining has received major attention in recent years for the reclamation of waste disposal sites, including in developing countries such as India where significant efforts are being made to manage sites in this way. The bulk of the material obtained from landfill mining consists of fine-grained soil-like material (SLM) but its direct reuse in off-site applications is restricted due to the presence of harmful heavy metals, soluble salts and other pollutants. In this study, appropriate techniques for managing SLM to permit recovery and reuse are assessed. As a result, experimental investigation explores the efficacy of two remediation techniques considered appropriate for SLM management: electrokinetic remediation and phytoremediation. These were applied to SLM from a recently mined landfill and their ability to reduce heavy metal and other soluble salt burdens assessed. Electrokinetic remediation has shown considerable potential to mobilise and transport heavy metals and soluble salts through and from the SLM over an eight-week period. Phytoremediation experiments also demonstrated mobilisation and uptake of metals from the SLM over a similar duration although relatively low amounts were recovered as a result of the low biomass produced over this period. Both technologies have demonstrated potential for recovery of metals from SLM, as well as recovering the SLM itself as a potential resource.