Tricks and tracks in waste management with a special focus on municipal landfill leachate: Leads and obstacles

Examining biomedical waste management knowledge and training level among health care professionals in Saudi Arabia

BACKGROUND

The rapid development of medical care innovations and the use of newer technologies have resulted in a significant rise in the quantity of waste produced per patient within health care facilities. Biomedical waste in particular has emerged as a pressing concern due to its inherent propensity to pose health hazards and cause environmental harm. The World Health Organization has identified a lack of knowledge and training as primary factors contributing to the failure of Biomedical waste management (BMWM). Thus, our study sought to examine the relationship between BMWM level of knowledge and prior training among health care professionals (HCPs) in 4 different regions in Saudi Arabia.

METHODS

Our study used a cross-sectional design to investigate the BMWM level of knowledge and prior training among HCPs in 4 different regions in Saudi Arabia. Multiple linear and logistic regression was used to assess if Biomedical waste management (MBWM) knowledge and prior tanning are significantly associated with the demographics and professional characteristics of HCPs.

RESULTS

501 HCPs participated in the study. More than half were male, the majority fell within the age range of 24 to 36 years and held a bachelor's degree. The level of BMWM knowledge among HCPs was moderate (M = 31.14, SD = 4.89) and positively associated with HCPs' prior training in BMWM, workplace environment, and overall experience in the field. Only 26% of the HCPs had received prior BMWM training, and it varied considerably by sex, geographic location, and professional experience.

CONCLUSIONS

Our study demonstrates a moderate knowledge and lack of training in BMWM among HCPs in Saudi Arabia. Thus, we recommend a national strategy for incorporating infection prevention and control methods associated with BMWM into all health care programs. Furthermore, it is imperative for health officials to enact prompt and efficient surveillance measures, as well as conduct frequent training sessions for HCPs and support personnel.

Ecotoxicological impacts of landfill sites: Towards risk assessment, mitigation policies and the role of artificial intelligence

Waste disposal in landfills remains a global concern. Despite technological developments, landfill leachate poses a hazard to ecosystems and human health since it acts as a secondary reservoir for legacy and emerging pollutants. This study provides a systematic and scientometric review of the nature and toxicity of pollutants generated by landfills and means of assessing their potential risks. Regarding human health, unregulated waste disposal and pathogens in leachate are the leading causes of diseases reported in local populations. Both in vitro and in vivo approaches have been employed in the ecotoxicological risk assessment of landfill leachate, with model organisms ranging from bacteria to birds. These studies demonstrate a wide range of toxic effects that reflect the complex composition of leachate and geographical variations in climate, resource availability and management practices. Based on bioassay (and other) evidence, categories of persistent chemicals of most concern include brominated flame retardants, per- and polyfluorinated chemicals, pharmaceuticals and alkyl phenol ethoxylates. However, the emerging and more general literature on microplastic toxicity suggests that these particles might also be problematic in leachate. Various mitigation strategies have been identified, with most focussing on improving landfill design or leachate treatment, developing alternative disposal methods and reducing waste volume through recycling or using more sustainable materials. The success of these efforts will rely on policies and practices and their enforcement, which is seen as a particular challenge in developing nations and at the international (and transboundary) level. Artificial intelligence and machine learning afford a wide range of options for evaluating and reducing the risks associated with leachates and gaseous emissions from landfills, and various approaches tested or having potential are discussed. However, addressing the limitations in data collection, model accuracy, real-time monitoring and our understanding of environmental impacts will be critical for realising this potential.

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.

A review of existing methods for predicting leachate production from municipal solid waste landfills

Landfilling is one of the predominant methods of municipal solid waste (MSW) disposal worldwide, while the generation of leachate, a kind of toxic wastewater, is among the primary factors behind landfill instability and environmental contamination problems. Precise prediction of leachate production is crucial to landfill safety evaluation and design. This paper presents a comprehensive review of methods for predicting leachate production from MSW landfills. Firstly, compositional characteristics of MSW and leachate generation mechanism are analysed. Factors influencing leachate production are summarised based on the generation mechanism, including the components of MSW, climatic conditions, landfill structure, and environmental factors. Then, we classified the existing methods for predicting leachate production into four categories: water balance formula, water balance model, empirical formula, and artificial intelligence model methods. Advantages, disadvantages, and applicability of different leachate production prediction methods are compared and analysed. Furthermore, limitations in the existing leachate production prediction methods for MSW landfills and scope for future research are discussed.

Potential stimulation of nitrifying bacteria activities and genera by landfill leachate

With the increasing complexity of influent composition in wastewater treatment plants, the potential stimulating effects of refractory organic matter in wastewater on growth characteristics and genera conversion of nitrifying bacteria (ammonium-oxidizing bacteria [AOB] and nitrite-oxidizing bacteria [NOB]) need to be further investigated. In this study, domestic wastewater was co-treated with landfill leachate in the lab-scale reactor, and the competition and co-existence of NOB genera Nitrotoga and Nitrospira were observed. The results demonstrated that the addition of landfill leachate could induce the growth of Nitrotoga, whereas Nitrotoga populations remain less competitive in domestic wastewater operation. In addition, the refractory organic matter in the landfill leachate also would have a potential stimulating effect on the maximum specific growth rate of AOB genus Nitrosomonas (μmax, aob). The μmax, aob of Nitrosomonas in the control group was estimated to be 0.49 d-1 by fitting the ASM model, and the μmax, aob reached 0.66-0.71 d-1 after injection of refractory organic matter in the landfill leachate, while the maximum specific growth rate of NOB (μmax, nob) was always in the range of 1.05-1.13 d-1. These findings have positive significance for the understanding of potential stimulation on nitrification processes and the stable operation of innovative wastewater treatment process.

Pb(ΙΙ), Cd(ΙΙ), and Mn(ΙΙ) adsorption onto pruning-derived biochar: physicochemical characterization, modeling and application in real landfill leachate

The aim of this study was to systemically evaluate how different pyrolysis temperatures (400, 550, and 700 °C) and particle sizes (1-2 mm and 63-75 µm) were influenced biochar evolution, made from urban pruning waste, during pyrolysis process and to establish their relationships with biochar potential for removal of lead (Pb), cadmium (Cd), and manganese (Mn) from real municipal solid waste landfill leachate. The effects of pH (2-7), contact time (30-300 min) and adsorbent dosage (0.1-5 g L-1) on heavy metals removal were also examined. The results showed that physicochemical properties of biochar were greatly influenced by pyrolysis temperature. Particle size, however, showed little influence on biochar characteristics (p > 0.05). The yield, volatile matter, hydrogen and oxygen contents, and surface functional groups decreased consistently with increasing pyrolysis temperature. An increase in the pH, electrical conductivity, ash, fixed carbon, and specific surface area values was also found. In biochar samples formed at high temperatures (i.e., 550 and 700 °C), Fourier transform infrared spectroscopy-FTIR studies confirmed the increase in aromaticity. Field emission scanning electron microscopy-FESEM images showed differences in the microporous structure and lower size pores at higher temperatures. Biochar pyrolyzed at 700 °C with a particle size of 63-75 µm (i.e., Lv700-63) showed the highest removal efficiency performance. Pb and Cd ions were completely removed (100%) by 0.2 g L-1 Lv700-63 at 7.0 pH and contact times of 120 and 90 min, respectively. The maximum percentage removal of Mn was 86.20% at optimum conditions of 0.2 g L-1 Lv700-63 dosage, 7.0 pH, and 180 min contact time. The findings suggests that the surface complexation, π-electron coordination, and cation exchange were the dominant mechanisms for the Pb, Cd, and Mn removal onto Lv700-63.

Optimizing leachate treatment with titanium oxide-impregnated activated carbon (TiO2@ASC) in a fixed-bed column: characterization, modeling, and prediction study

This research focused on the application of a fixed bed column filled with immobilized titanium oxide-loaded almond shell carbon (TiO2@ASC) for the treatment of leachate. The adsorption performance of synthesized TiO2@ASC in fixed bed column is analyzed using adsorption experiments and modeling study. The characteristics of synthesized materials are determined by several instrumental techniques like BET, XRD, FTIR, and FESEM-EDX. The flow rate, initial concentration of COD and NH3-N, and bed height were optimized to determine the effectiveness of leachate treatment. The linear bed depth service time (BDST) plots equations with a correlation coefficient of greater than 0.98 confirmed the model's accuracy for COD and NH3-N adsorption in column structure. The adsorption process was found to be well predicted by an artificial neural network (ANN) model with a root mean square error of 0.0172 and 0.0167 for COD and NH3-N reduction, respectively. The immobilized adsorbent was regenerated using HCl and was found to be reusable for up to three cycles, promoting material sustainability. This study is aimed to contribute towards SDG 6 and SDG11 by United Nations Sustainable Development Goals.

Optimal pre-treatment of moderately old landfill leachate at the pilot-scale treatment plant using the combined aerobic biochemical and reagent method

Landfill leachates contain highly concentrated pollutants, and their uncontrolled discharge poses significant risks to the public health and environment. This study validated a pilot-scale two-stage aerobic biochemical and reagent method for the pre-treatment of moderately old landfill leachate at a pilot-scale treatment plant with a capacity of 400 L per day. The kinetic curves of key pollutants were described using two-factor dimensionless exponential equations, allowing for predicting maximally achievable treatment effects during the first aerobic biochemical stage. The optimal duration of aerobic biochemical pre-treatment was determined based on the concept of limiting pollutant content and minimizing operating costs for the two-stage process. Reagent-based leachate pre-treatment using the modified Fenton method was verified in a batch reactor. Optimal concentrations and dosages of reagent solutions, including polyacrylamide, aluminium sulphate, ferrous sulphate, and hydrogen peroxide, were found to comply with Ukrainian regulations for wastewater discharge into sewerage networks. Key pollution indicators of pre-treated leachate, such as NH₄⁺-N (13.4-15.5 mg × L^-1), TKN (25.7-30.2 mg × L^-1), BOD_tot (71.8-76.9 mg × L^-1), and COD (390-459 mg × L^-1), meet the required standards.