Leachate Samples Research Articles

Degradation of ammonaical nitrogen (NH3-N) in leachate by zinc oxide loaded activated carbon: Process parameters modelling and optimization through RSM design

In this study, NH3-N will be removed from a leachate sample using a zinc oxide (ZnO) nanocomposite that is combined with corncob-activated carbon. A simple impregnation and pyrolysis procedure was used to create the nanocomposite, and BET, XRD, and FTIR studies were used to validate its creation. Under optimized conditions pH 7, temperature 30°C, adsorbent dose 1.50 g/50 L, and a contact time of 160 min, resulting the highest NH3-N removal efficiency of 73.5 %. The experimental data were successfully fitted to various isotherms (Hill, Koble–Corrigan, Redlich–Peterson, Khan and Toth) and Pseudo-second-order kinetics were found suitable for NH3-N reduction. Furthermore, the lower value of RMSE (0.47) obtained through RSM-CCD indicated a minimal difference between the experimental (73.5 %) and model-based (71.2 %) removal percentages of NH3-N, confirming the model's suitability for adsorption method. The promising results of the adsorption study provide valuable insights and indicating the potential of nanocomposite material for sustainable leachate treatment.

PENGOLAHAN LINDI (LEACHEATE) DENGAN METODE MOVING BED BIOFILM REACTOR (MBBR) DENGAN PROSES AEROBIK-ANOKSIK UNTUK MENURUNKAN KONSENTRASI COD, TSS, DAN AMONIA

Lindi mempunyai kandungan bahan organik, TSS, dan ammonia yang tinggi. Moving Bed Biofilm Reactor (MBBR) merupakan salah satu pengolahan biologi yang dapat menurunkan konsentrasi yang terkandung di air lindi. Tujuan dari penelitian ini untuk mengetahui kemampuan MBBR dalam menurunkan kandungan bahan organik, TSS, dan ammonia, dengan menggunakan variasi waktu detensi proses aerobik-anoksik dan media lekat. Reaktor di operasikan secara batch. Variasi media yang digunakan adalah kaldness K1 dan K3, sedangkan waktu detensi aerobik 14,5 jam - anoksik 10 jam dan aerobik 10 jam - anoksik 7 jam. Hasil yang didapatkan menunujukkan bahwa MBBR dapat digunakan untuk mengolah lindi. Penurunan konsentrasi COD, TSS, dan Ammonia paling baik terjadi pada media K1 waktu detensi aerobik 14,5- anoksik 10 jam dengan penyisihan mencapai 74,8%, 93,14%, dan 83,72%.

Groundwater sulfate in the Pearl River Delta driven by urbanization: Spatial distribution, sources and factors

Groundwater sulfate contamination becomes a big concern in urbanized areas where urbanization expansion continues. This study investigates the spatial distribution of sulfate in shallow groundwater of the Pearl River Delta (PRD) where urbanization has lasted for more than 40 years, and discusses sources and factors for groundwater sulfate contamination in various aquifers and areas with different land-use types by using hydrochemistry and principal component analysis. A total of 330 groundwater samples, 19 river samples, and 9 landfill leachate samples were collected from the PRD. The results show that groundwater SO42− concentration in the PRD is up to 857.57 mg/L, and the SO42−-rich (>150 mg/L) groundwater accounts for 7.27%. SO42−-rich groundwater in the coastal alluvial aquifers is 3.8 times that in the alluvial-proluvial aquifers, while fissured and karst aquifers are absence of SO42−-rich groundwater. In coastal alluvial aquifers, SO42−-rich groundwater in urbanized areas is 8.5 times that in peri-urban areas. By contrast, in alluvial-proluvial aquifers, SO42-rich groundwater just occurs in urbanized areas rather than other areas. Exogenous input driven by urbanization is the primary factor for SO42−-rich groundwater in the PRD. The occurrence of SO42−-rich groundwater in urbanized and peri-urban areas of the PRD is mainly attributed to the industrial wastewater infiltration and acid precipitation. Lateral flow from rivers is another prominent source for SO42-rich groundwater in the PRD. As a consequence, in order to reduce the emergence of SO42−-rich groundwater in areas of accelerated urban expansion such as the PRD, strengthening the treatment and supervision of wastewater from township enterprises and waste gas from industrial enterprises is recommended.

Water table effect on phosphorus solubility in biosolids‐amended soils

AbstractThe predominantly coarse texture of Florida Spodosols, limited P‐holding capacity, and fluctuating water table present major challenges for management of P, particularly in agricultural areas receiving biosolids. This study evaluated the impacts of water table level on P fate in Spodosols with contrasting P‐management histories. Treatments were a combination of soils with different biosolids histories (control [no biosolids], intermediate and high [biosolids‐P loads of 567 and 706 kg P ha−1, respectively]) and two moisture regimens (drained and flooded [water table at the depth of spodic horizon or 2 cm above soil surface, respectively]). Soil samples (A, E, and B horizons) were packed into PVC columns (96 cm tall, 11 cm in diameter), mimicking the soil profile. Leachate and pore water samples were collected at 2‐week intervals for 20 weeks. Regardless of treatment, proportion of P leached was low (∼0.2% total P mass). This was due to the significant P storage provided by the spodic horizon. Despite elevated soil P levels, Al and Fe added with biosolids reduced P solubility by as much as 55% compared with the control. Although flooding increased P leaching due to the reductive dissolution and hydrolysis of Al‐P and Fe‐P compounds, moisture regimen effects were generally negligible and inconsistent. Soil P storage capacity has been used as a risk assessment tool to determine biosolids‐P applications; however, our data demonstrated that additional field studies are needed to validate this concept, particularly its applicability and interpretation in biosolids‐amended soils that contain appreciable amounts of Fe‐ and Al‐organic complexes.

Identifying potential toxic organic substances in leachates from tire wear particles and their mechanisms of toxicity to Scenedesmus obliquus

Tire wear particles (TWPs) are increasingly being found in the aquatic environment. However, there is limited information available on the environmental consequences of TWP constituents that may be release into water. In this study, TWP leachate samples were obtained by immersing TWPs in ultrapure water. Using high-resolution mass spectrometry and toxicity identification, we identified potentially toxic organic substances in the TWP leachates. Additionally, we investigated their toxicity and underlying mechanisms. Through our established workflow, we structurally identified 13 substances using reference standards. The median effective concentration (EC50) of TWP leachates on Scenedesmus obliquus growth was comparable to that of simulated TWP leachates prepared with consistent concentrations of the 13 identified substances, indicating their dominance in the toxicity of TWP leachates. Among these substances, cyclic amines (EC50: 1.04–3.65 mg/L) were found to be toxic to S. obliquus. We observed significant differential metabolites in TWP leachate-exposed S. obliquus, primarily associated with linoleic acid metabolism and purine metabolism. Oxidative stress was identified as a crucial factor in algal growth inhibition. Our findings shed light on the risk posed by TWP leachable substances to aquatic organisms.

Quantification and molecular characterization of intact rotavirus species A (RVA) in municipal solid waste leachate.

Leachate comprises a solid waste decomposition product found fresh in collection trucks or as an effluent in landfills. This study aimed to assess the occurrence, concentrations, and genetic diversity of intact rotavirus species A (RVA) in solid waste leachate. Leachate samples were concentrated by ultracentrifugation, treated with propidium monoazide (PMA), and exposed to LED photolysis. Treated and untread samples were extracted using the QIAamp Fast DNA Stool mini kit, and nucleic acids were screened for RVA employing a Taqman® Real-time PCR. The PMA RT-qPCR method detected RVA in eight out of nine truck samples and in 15.40% (2/13) of the landfill leachate samples. The RVA concentrations in the PMA-treated samples ranged from 4.57×103 to 2.15×107 genomic copies (GC) 100 mL-1 in truck leachate and from 7.83×103 to 1.42×104 GC 100 mL-1 in landfill samples. Six truck leachate samples were characterized as RVA VP6 genogroup I2 by partial nucleotide sequencing. The high intact RVA detection rates and concentrations in truck leachate samples indicate potential infectivity and comprise a warning for solid waste collectors concerning hand-to-mouth contact and the splash route.

Investigating Landfill Leachate and Groundwater Quality Prediction Using a Robust Integrated Artificial Intelligence Model: Grey Wolf Metaheuristic Optimization Algorithm and Extreme Learning Machine

The likelihood of surface water and groundwater contamination is higher in regions close to landfills due to the possibility of leachate percolation, which is a potential source of pollution. Therefore, proposing a reliable framework for monitoring leachate and groundwater parameters is an essential task for the managers and authorities of water quality control. For this purpose, an efficient hybrid artificial intelligence model based on grey wolf metaheuristic optimization algorithm and extreme learning machine (ELM-GWO) is used for predicting landfill leachate quality (COD and BOD5) and groundwater quality (turbidity and EC) at the Saravan landfill, Rasht, Iran. In this study, leachate and groundwater samples were collected from the Saravan landfill and monitoring wells. Moreover, the concentration of different physico-chemical parameters and heavy metal concentration in leachate (Cd, Cr, Cu, Fe, Ni, Pb, Mn, Zn, turbidity, Ca, Na, NO3, Cl, K, COD, and BOD5) and in groundwater (Cd, Cr, Cu, Fe, Ni, Pb, Mn, Zn, turbidity, EC, TDS, pH, Cl, Na, NO3, and K). The results obtained from ELM-GWO were compared with four different artificial intelligence models: multivariate adaptive regression splines (MARS), extreme learning machine (ELM), multilayer perceptron artificial neural network (MLPANN), and multilayer perceptron artificial neural network integrated with grey wolf metaheuristic optimization algorithm (MLPANN-GWO). The results of this study confirm that ELM-GWO considerably enhanced the predictive performance of the MLPANN-GWO, ELM, MLPANN, and MARS models in terms of the root-mean-square error, respectively, by 43.07%, 73.88%, 74.5%, and 88.55% for COD; 23.91%, 59.31%, 62.85%, and 77.71% for BOD5; 14.08%, 47.86%, 53.43%, and 57.04% for turbidity; and 38.57%, 59.64%, 67.94%, and 74.76% for EC. Therefore, ELM-GWO can be applied as a robust approach for investigating leachate and groundwater quality parameters in different landfill sites.

Ammoniacal Nitrogen Contaminant in Water of Kaliori Landfill Area in Banyumas

Kaliori Landfill is one of the inactive landfills in Banyumas Regency. The presence of garbage and a full leachate pond in the area is feared to pollute the waters around the landfill. One of the water quality parameters is ammoniacal nitrogen (NH3-N) based on Government Regulation of the Republic of Indonesia Number 82 in 2001. The aim of this research was to find the quality of water in landfill area based on ammoniacal nitrogen parameter. The water studied was one sample of leachate, two samples of river water and five samples of ground water in the landfill area with a radius less than 1 kilometers. Spectrophotometry method was used to find NH3-N concentration. Based on the test results, leachate and ground water have reach ammoniacal nitrogen quality standard, there were <2.0 mg/L and <0.5 mg/L respectively. Meanwhile, the ammoniacal nitrogen in river water was >2.5 mg/L, they have exceeded the established quality standards.

A case study of environmental pollution by pathogenic bacteria and metal(oid)s at Soran Landfill Site, Erbil, Iraqi Kurdistan Region.

Environmental pollution is a serious issue all around the world, especially when it is caused by metal(oid)s and pathogenic microorganisms. This study reports here for the first time on the contamination of soil and water with metal(oid)s and pathogenic bacteria directly resulting from the Soran Landfill Site. Soran landfill is a level 2 solid waste disposal site that lacks leachate collection infrastructure. The site is potentially an environmental and public hazard caused by metal(oid)s content and significantly dangerous pathogenic microorganisms through leachate release into the soil and nearby river. This study reports on the levels of the metal(oid)s content of As, Cd, Co, Cr, Cu, Mn, Mo, Pb, Zn, and Ni obtained by inductively coupled plasma mass spectrometer in soil, leachate stream mud, and leachatesamples. Five pollution indices are used to assess potential environmental risks. According to the indices, Cd and Pb contamination is significant, whereas As, Cu, Mn, Mo, and Zn pollution is moderate. A total of 32 isolates of bacteria were defined from soil, leachate stream mud, and liquid leachate samples: 18, 9, and 5, respectively. Moreover, 16s rRNA analysis suggested that the isolates belong to three enteric bacterial phyla of Proteobacteria, Actinobacteria, and Firmicutes. The closest GenBank matches of 16S rDNA sequences indicated the presence of the genera: Pseudomonas, Bacillus, Lysinibacillus, Exiguobacterium, Trichococcus, Providencia, Enterococcus, Macrococcus, Serratia, Salinicoccus, Proteus, Rhodococcus, Brevibacterium, Shigella, Micrococcus, Morganella, Corynebacterium, Escherichia, and Acinetobacter. The identity percentage was mostly between 95%-100%. The results of this study show the levels of microbiological and geochemical contamination of soils, surface and potentially ground water with harmful microorganisms and toxic metal(oid)s originating specifically from Soran landfill leachate which subsequently incorporated into the surrounding environment, creating thus a considerable health and environmental risk.

Application of peanut shell ash in geosynthetic clay liners to reduce the Zinc contamination in leachate

Human health is seriously harmed by heavy metal contamination. Municipal solid waste disposal facilities are one of the most preferred options that contaminate the land and the groundwater. The liquid produced by the anaerobic oxidation of solid waste in landfills is known as leachate. The leachate contains organic, inorganic, and heavy metals depending upon the type of waste. The main issue in developing nations is the pollution of ground and surface water caused by the generation of leachate. Most heavy metals are carcinogenic in nature and Zinc (Zn) is one of the heavy metals present in the leachate. Kanpur (Uttar Pradesh, India) is a highly polluted city with 1500 Metric tons of waste generated per day. A leachate sample was collected for the study area and its Physico-chemical composition was analyzed. The concentration of Zn was found as 11.47 mg/l in the leachate sample which is more than two times the permissible limit of 5.0 mg/l. The objective of this study is to reduce the Zn concentration of leachate samples after passing through a modified Geosynthetic Clay Liner (GCL). The modified geosynthetic clay liner was developed by adding different proportions (0%, 5%, 10%, 15%, 20%, 25%, and 30%) of Peanut Shell Ash (PSA) with encapsulated Sodium Bentonite (Na-B) in commercial GCL. The efficiency of Zn removal from wastewater using peanut shells has been evaluated. In this study, it has attempted to find the best proportion of Na-B and PSA as encapsulated material of GCL to reduce the concentration of Zn.

Effect of biosolids amendment on the fate and mobility of non-steroidal anti-inflammatory drugs (NSAIDs) in a field-based lysimeter cell study

Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used globally to treat and prevent illness. Biosolids change physico-chemical characteristics of soil and can affect the mobility of NSAIDs. A field-based lysimeter study evaluated the effect of three rates (0, 7, and 28 Mg ha−1) of alkaline treated biosolids (ATB) on the leaching potential of naproxen (NPX), ibuprofen (IBF), and ketoprofen (KTF) over 34 days in a sandy loam textured soil. Although all three NSAIDs in the lysimeter cells vertically migrated to deeper soil depths after spiking, the sum of all NPX, IBF, and KTF detected in the leachate samples from all treatments were only 0.03%, 0.02%, and 0.04% of the initial spiking mass to the surface soil, respectively. A mass balance analysis indicated a low accumulation of these compounds in the soil at the end of the study (Day 34) from all treatments with only 4.8%, 0.5%, and 0.7% of initial spiked NPX, IBF, and KTF, respectively. Application of ATB significantly increased soil pH and organic matter (OM) content of the soils but did not impact retention of the compounds in the soil profile. Overall, all three NSAIDs in the present study presented low mobility in the loamy sand textured agricultural soil.

Leaching of select per-/poly-fluoroalkyl substances, pharmaceuticals, and hormones through soils amended with composted biosolids

The use of organic amendments to enhance soil health is increasingly being identified as a strategy to improve residential landscapes while also reducing the need for external inputs (e.g., fertilizers, irrigation). Composted biosolids are a re-purposed waste product that can be used in organic amendments to improve the overall sustainability of a municipality by enhancing residential soil carbon content while simultaneously reducing waste materials. However, the biosolids-based feedstock of these compost products has the potential to be a source of organic contaminants. We conducted a laboratory-based soil column experiment to evaluate the potential for different commercially available compost products to act as a source of emerging organic contaminants in residential landscapes. We compared two biosolids-based compost products, a manure-based compost product, and a control (no compost) treatment by irrigating soil columns for 30 days and collecting daily leachate samples to quantify leaching rates of six hormones, eight pharmaceuticals, and seven per- and polyfluoroalkyl substances (PFAS). Detection of hormones and pharmaceuticals was rare, suggesting that compost amendments are likely not a major source of these contaminants to groundwater resources. In contrast, we detected three of the seven PFAS compounds in leachate samples throughout the study. Perfluorohexanoic acid (PFHxA) was more likely to leach from biosolids-based compost treatments than other treatments (p < 0.05) and perfluorobutane sulfonate (PFBS) was only detected in biosolids-based treatments (although PFBS concentrations did not significantly differ among treatments). In contrast, perfluorooctanoic acid (PFOA) was commonly detected across all treatments (including controls), suggesting potential PFOA experimental contamination. Overall, these results demonstrate that commercially available composted biosolids amendments are likely not a major source of hormone and pharmaceutical contamination. The detection of PFHxA at significantly higher concentrations in biosolids treatments suggests that biosolids-based composts may act as sources of PFHxA to the environment. However, concentrations of multiple PFAS compounds found in leachate in this study were lower than concentrations found in known PFAS hotspots. Therefore, there is potential for environmental contamination from PFAS leaching from composted biosolids, but leachate concentrations are low which should be considered in risk-benefit analyses when considering whether or not to use composted biosolids as an organic amendment to enhance residential soil health.

A landfill serves as a critical source of microplastic pollution and harbors diverse plastic biodegradation microbial species and enzymes: Study in large-scale landfills, China

Microplastics (MPs) are emerging pollutants. Landfills store up to 42% of worldwide plastic waste and serve as an important source of MPs. However, the study of MPs distribution and the plastic biodegradation potential in landfills is limited. In this study, the distribution of abundance, size, morphology and polymer type of MPs and plastics biodegradation species in refuse samples along landfill depths were extensively investigated within a large-scale landfill in Shenzhen, China. In addition, plastics biodegradation enzymes were evaluated in seven Chinese large-scale landfills leachate. MPs distribution pattern was investigated in all refuse samples. The abundance of MPs in refuse samples varied between 81 and 133 items/g. The size of MPs in all samples varied between 0.03 and 5 mm, and the average sizes were 1.2 mm ± 0.1 mm. The main morphology and polymer type were fragments and cellophane, respectively. Landfill depth was significantly negatively correlated with the relative abundance of MPs size 1–5 mm (p < 0.05) and was positively correlated with the relative abundance of MPs size < 0.2 mm (p < 0.05), suggesting that plastics were broken down during municipal solid waste decomposition. The multiple regression on matrices analysis further showed the landfill depths and plastic morphology significantly impact the MPs distribution. The strains, Lysinibacillus massiliensis (with relative abundance of 1.8%) for low-density polyethylene and polystyrene biodegradation, and Pseudomonas stutzeri (0.1%) for low density polythene and polypropylene biodegradation, were detected on the plastic surface with high relative abundance. Furthermore, 75 plastic degradation species and their associated 31 enzymes (breakdown 24 plastics) were discovered in seven landfills leachate samples.

Rapid and versatile colorimetric sensor based on luminescent bacterium for water comprehensive toxicity detection

In this study, a high-efficiency colorimetric sensor for water toxicity assessment was successfully constructed by the visual analysis with naked eyes and the high-throughput measurement with a microplate reader. The bioluminescent Photobacterium phoshoreum T3 spp. (T3) and Prussian blue (PB) were used as model bacterium and indicator of the colorimetric sensor, respectively. In order to accurately detect acute toxicities of wastewater, the experimental conditions, concentrations of cells, K3[Fe(CN)6] and NaCl, reaction temperature and time, were optimized to be OD600 = 2, 8 mM, 1.2%, 26.5 °C and 25 min, respectively. Then several samples of simulated wastewater containing Hg2+, Cd2+, Zn2+, 3,5-dichlorophenol (DCP) and formaldehyde (HCHO) were tested. The composite biotoxicity of dry battery leachate and real water sample was also evaluated. The IC50 values of Hg2+, Cd2+, Zn2+ and DCP obtained were 3.60, 1.56, 0.96 and 11.77 mg L−1, respectively. Moreover, a toxic unit (TU) model was applied to evaluate the binary complex toxicity of Hg2+ + Cd2+, Hg2+ + Zn2+ and DCP + Zn2+, which showed antagonistic effects. The work demonstrates that the promising high-efficiency sensor can detect quickly and sensitively the single and joint toxicities of multi-pollutants in water, which possesses extensive potentials in field of toxicity detection.

Humic acid recovery from stabilized leachate: Characterization and interference with chemical oxygen demand-colour removal.

Heterogeneous combinations of organic compounds (humic acid (HA) and fulvic acid) are the prime factor for the high concentration of colour and chemical oxygen demand (COD) in semi-aerobic stabilized landfill leachate. These organics are less biodegradable and cause a severe threat to environmental elements. Microfiltration and centrifugation processes were applied in this study to investigate the HA removal from stabilized leachate samples and its corresponding interference with COD and colour. The three-stage extraction process recovered a maximum of 1412 ± 2.5 mg/L (Pulau Burung landfill site (PBLS) leachate), 1510 ± 1.5 mg/L (Alor Pongsu landfill site (APLS leachate) at pH 1.5 and 1371 ± 2.5 mg/L (PBLS) and 1451 ± 1.5 mg/L (APLS) of HA (about 42% of the total COD concentration) at pH 2.5, which eventually indicates the process efficiency. Comparative characteristics analysis of recovered HA by scanning electron microscopy, energy-dispersive X-ray, X-ray photoelectron spectroscopy, and Fourier transform infrared significantly indicate the existence of identical elements in the recovered HA compared with the previous studies. The higher reduction (around 37%) in ultraviolet (UV) absorbance values (UV254 and UV280) in the final effluent indicates the elimination of aromaticity and conjugated double-bond compounds from leachate. Moreover, 36 and 39% COD and 39 and 44% colour removal exhibit substantial interference.

The Leaching Behavior of Zinc Oxide in Medical Waste of Dental Clinics

Zinc Oxide is an indispensable substance in the field of dental treatment. It is used daily and intensively in all governmental and private dental clinics, leading to the disposal of very high concentrations of zinc with waste and eventually in landfill sites as a final destination for solid waste removal. This indicates the urgent need to investigate its behavior upon disposal due to the surrounding conditions. Approximately 4195 g of mixed dental waste samples were collected from (17) healthcare centers in Baghdad Al-Karkh. The leaching behavior of ZnO powder was investigated through batch reactors using makeup dental solid waste samples. The ZnO leaching was tested with 3 conditions; acidic, alkaline, and Ionic Strength (IS). The acidic condition was considered the most hazardous condition compared with basic and salinity due to the increasing tendency of ZnO to release Zn ion within waste leachate. In solutions with low pH, the dissolution of ZnO tends to produce zinc ions due to the attack of the ZnO surface by proton. In solutions of pH more than 9, the degradation of zinc oxide produces hydroxide complexes. Increasing (IS) decreased zinc concentration in leachate samples with time by promoting solids aggregation, decreasing the repulsive forces of ZnO particles, and accumulating in the bottom of reactors.

Sorptive removal of per- and polyfluoroalkyl substances (PFAS) in organic-free water, surface water, and landfill leachate and thermal reactivation of spent sorbents

This study evaluated the performance of five commercially available granular activated carbons (GACs) derived from different sources for the removal of short-chain and long-chain per- and polyfluoroalkyl substances (PFAS) from raw and pretreated landfill leachate using ozonation to break down organic substances. The adsorption isotherms of PFAS on GAC in organic-free water and surface water were also established to understand the effect of water chemistry. The results demonstrated that bituminous GACs have the highest adsorption capacity compared to GACs made from coconut shells and lignite coal. The GAC adsorption of PFAS in landfill leachate was two orders of magnitude lower than that in surface water. Pretreatment of leachate by ozonation moderately increased the adsorption of PFAS on GAC. This is the first time that PFAS isotherm data are available for mainstream GACs in raw and pretreated landfill leachate samples. Such data can be used to design a GAC treatment system for removing PFAS from leachate. Furthermore, our results showed that GAC contaminated with PFAS in landfill leachate could be effectively regenerated using conventional muffle and tube furnaces, indicating that the presence of other substances in the leachate has no significant impact on the reactivation of the GAC. Lastly, the results indicate that induction heating is an efficient and rapid method for thermally reactivating GAC contaminated with various PFAS.

Assessment of Contamination Potential in Okhla Landfill, New Delhi by using Leachate Pollution Index

Landfill leachate generation from a landfill site is one of the main problems for both developed and developing countries around the world. Leachates liberated from the site contain various organic, inorganic, heavy metals, and sometimes hazardous chemical and organic pollutants, which are the origin of the deterioration of air and water quality in its vicinity. The present attempt was performed to assess seasonal variation of the leachate quality, and also determine three sub-indices of leachate which are LPIorg, LPIin, and LPIhm, and the overall LPI of operational, uncontrolled landfills in South Delhi by using leachate pollution index (LPI). Around twenty-five (25) parameters were analyzed during pre-monsoon, monsoon, and post-monsoon seasons from the collected leachate samples. Out of twenty-five pollutants, COD, BOD, NH4-N, EC, and TDS were found beyond the set standard limit in all seasons. Other pollutants like TKN, TSS, TCB, and Cl were also found in high concentrations. Arsenic (As) concentration was found beyond permissible during post-monsoon. The concentration of lead (Pd) in the pre and post-monsoon season was observed beyond the standard limit. Sub-LPI indices in the pre-monsoon season were observed as LPIorg 82.0, LPIin 40.8, and LPIhm 6.9, and likewise, Sub-LPI in monsoon season were LPIorg 81.4, LPIin 25.5, and LPIhm 5.2 and Sub-LPI post-monsoon season was calculated as LPIorg 90.5, LPIin 30.2 and LPI hm 6.2. Almost in all the seasons, LPIorg i.e. organic pollutants was dominated then followed by LPIin, and LPIhm. The overall LPI value of the study area during the pre-monsoon, monsoon and post-monsoon was 32.5, 28.2 and 32.0, respectively. It was observed that overall LPI (calculated) was maximum during pre-monsoon followed by post-monsoon and monsoon. LPI value was beyond the standard limit, except for LPI hm, which was below the standards. It was recommended that more waste-to-energy plants and decentralized waste segregation units need to be set up, to avoid direct dumping of all mixed waste in the landfill sites.

SARS-CoV-2 surveillance-based on municipal solid waste leachate in Brazil.

Municipal solid waste leachate-based epidemiology is an alternative viral tracking tool that applies fresh truck leachate as an early warning of public health emergencies. This study aimed to investigate the potential of SARS-CoV-2 surveillance based on solid waste fresh truck leachate. Twenty truck leachate samples were ultracentrifugated, nucleic acid extracted, and real-time RT-qPCR SARS-CoV-2 N1/N2 applied. Viral isolation, variant of concern (N1/N2) inference, and whole genome sequencing were also performed. SARS-CoV-2 was detected on 40% (8/20) of samples, with a concentration from 2.89 to 6.96 RNA Log10 100mL-1. The attempt to isolate SARS-CoV-2 and recover the whole genome was not successful; however, positive samples were characterized as possible pre-variant of concern(pre-VOC), VOC Alpha (B.1.1.7) and variant of interest Zeta (P.2). This approach revealed an alternative tool to infer SARS-CoV-2 in the environment and may help the management of local surveillance, health, and social policies.

Efficient Monitoring of Microbial Communities and Chemical Characteristics in Incineration Leachate with Electronic Nose and Data Mining Techniques

Incineration leachate is a hazardous liquid waste that requires careful management due to its high levels of organic and inorganic pollutants, and it can have serious environmental and health implications if not properly treated and monitored. This study applied a novel electronic nose to monitor the microbial communities and chemical characteristics of incineration leachate. The e-nose data were aggregated using principal component analysis (PCA) and T-distributed stochastic neighbor embedding (TSNE). Random forest (RF) and gradient-boosted decision tree (GBDT) algorithms were employed to establish relationships between the e-nose signals and the chemical characteristics (such as pH, chemical oxygen demand, and ammonia nitrogen) and microbial communities (including Proteobacteria, Firmicutes, and Bacteroidetes) of the incineration leachate. The PCA-GBDT models performed well in recognizing leachate samples, achieving 100% accuracy for the training set and 98.92% accuracy for the testing data without overfitting. The GBDT models based on the original data performed exceptionally well in predicting changes in chemical parameters, with R2 values exceeding 0.99 for the training set and 0.86 for the testing set. The PCA-GBDT models also demonstrated superior performance in predicting microbial community composition, achieving R2 values above 0.99 and MSE values below 0.0003 for the training set and R2 values exceeding 0.86 and MSE values below 0.015 for the testing set. This research provides an efficient monitoring method for the effective enforcement and implementation of monitoring programs by utilizing e-noses combined with data mining to provide more valuable insights compared with traditional instrumental measurements.