Leachate originating from municipal solid waste landfills poses a serious contamination threat to public health. The study performed a bio-physicochemical characterization of leachate from two landfills in Oman, i.e., Multaqa landfill leachate (MLL) and Barka landfill leachate (BLL) before and after rainfall. Samples were characterized for 92 parameters. Additionally, the leachate pollution index (LPI) was estimated to assess the expected contamination levels and potential environmental health risks. The study found a high value of the leachate parameters without any rainfall incidents. Pearson correlations (±ve) are seen at more than 90% in all cases, which is a strong association (r>0.75) for the measured parameters in both MLL and BLL. Rainfall significantly reduced the concentrations of organic contaminants and solids in leachate due to dilution. The study revealed about 18%–29% and 14%–28% reductions in the LPI sub-index for organic and inorganic contaminants, respectively, after rainfall. The overall LPI values were higher compared with similar findings from the literature. Such deviations could be attributed to the unsegregated nature of solid waste, resulting in the formation of contaminants or from the disposal of a high volume of solid waste in a smaller area. Therefore, the study recommends efficient management strategies for landfills to reduce potential leachate groundwater contamination.

  • Bio-physicochemical leachate characterization of municipal solid waste landfills.

  • Sustainable leachate management due to its toxicity and recalcitrant properties.

  • Substantial reduction of leachate pollutant after rainfall event compared with summer.

  • LPI showed significant information to associate pollution with atmospheric variable.

  • Strategic approaches pertinent to leachate management and safeguarding public health.

The impact of municipal landfill leachates on groundwater resources has received global attention, especially in most arid nations, due to the lack of freshwater bodies in these countries (Mishra et al. 2019; Kogbara et al. 2020). Leachate generation from municipal landfills will be exacerbated as the number and storage capacities of these landfills keep increasing in response to rising urban populations and economic activities (Luo et al. 2020). Considering their highly concentrated nature and toxicity characteristics, infiltration of leachates to soil and groundwater aquifers poses a severe threat to public health (Baderna et al. 2019; Przydatek 2019). Ahmed et al. (2018) reported high concentrations of heavy metals (Cr 1.840 mg/L, Cu 0.602 mg/L, Pb 0.305 mg/L, and Ni 1.225 mg/L) in leachate samples as a potential cause of groundwater and soil contamination.

Al Raisi et al. (2014) also reported similarly high levels of leachate contaminants (Fe 39.250 mg/L, Pb 0.130 mg/L, and Ni 0.773 mg/L) produced from lead batteries, lead-mixed paints, plastics, and pipe waste from landfill sites. In addition, another study has indicated the presence of a carcinogenic compound called organophosphorus flame retardant (4,807 ng/L) in municipal leachate (Deng et al. 2018). Thus, considering its mode of transport, untreated leachate could dissipate into soil biota and also be transported to nearby agricultural lands, urban areas and ultimately aquifers to cause contamination (Naveen et al. 2017).

To protect groundwater resources and human health from leachate contamination, it is imperative to better understand its physico-chemical and biological characteristics before treatment design processes (Al Raisi et al. 2014). Determination of an optimum treatment train for landfill leachates will require a comprehensive knowledge of contaminants in the leachate. Organic and inorganic compounds could sometimes pose synergistic effects with other compounds such as phenols, pesticides, heavy metals, and ammonium ions within the leachate (Öman & Junestedt 2008). For example, Naveen et al. (2017) characterized the leachate and suggested a suitable treatment system to reduce its adverse effects on the environment. However, leachate characteristics and concentrations effectively depend on weather conditions (e.g., precipitation, temperature, and relative humidity), solid waste type, landfill design, operational procedures, and waste decomposition (Singh et al. 2016; Somani et al. 2019). The study is a usual scenario of the Gulf region (Muscat, Sultanate of Oman is the location of study), where unsegregated solid waste disposal produces concentrated leachate due to the presence of various pollutants. Therefore, it rapidly damages groundwater quality and ultimately affects human health and the ecosystem (Alkassasbeh et al. 2009; Emenike et al. 2012).

To the best of our knowledge, minimal studies have been conducted on the comprehensive characterization of municipal landfill leachates in arid urban landfills, specifically in Oman, where municipal landfills are affected by natural rainfall. The current study will also provide a better understanding of leachate properties in similar arid/semi-arid areas of Australia (Adelaide), the United States (Phoenix), and Greece (Athens), including other arid Asia countries. Therefore, the study aimed to characterize the bio-physicochemical properties of Multaqa landfill leachate (MLL) and Barka landfill leachate (BLL) in Muscat, Oman. Both the landfills receive municipal solid waste (MSW) from Muscat and Barka city, respectively. The study also investigated the effect of rainfall on the leachate's physical, chemical, and biological properties. Furthermore, the leachate pollution index (LPI) from the two landfills with and without rainfall incidents has been investigated. Thereby, the study disclosed an in-depth understanding of leachate properties and the effect of dilution by rainfall to identify the best leachate management practices and treatment systems.

Study area

The study took place in Muscat, the capital city of Oman, with a population of 3.9 million. Muscat has both arid and semi-arid climates with annual precipitation levels of >100 mm, which occurs intermittently between December and April (57%–82%) (Kwarteng et al. 2009). The data implies that the rainfall does not occur continuously during the periods of December to April. Within the specified period, there are still several weeks without rainfall, considered as dry periods. Ambient temperature and humidity are in the range 23.10–40 °C and 30%–90%, respectively (NCSI 2018). It is estimated that the country generates more than 1.7 million tons of MSW annually, with more than 50% coming from Muscat. Also, the per capita generated waste is >1.2 kg/day, resulting in 4,700 tonnes of MSW production per day. Figure 1 shows the location of the two landfills in Muscat city with the neighboring country.

Figure 1

Location of Barka and Al-Multaqa landfills in Muscat, Oman.

Figure 1

Location of Barka and Al-Multaqa landfills in Muscat, Oman.

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Description of the municipal landfills

There are two major municipal landfills, namely Multaqa landfill and Barka landfill. These two landfills serve as the central MSW collection and disposal systems in the Muscat Governorate. Both landfills are equipped with leachate collection systems in closed cells of collected waste. MLL is mainly pumped into a leachate treatment plant. The remaining small amount is retained into ponds to reduce its environmental impacts. The BLL, on the other hand, overflows into ponds, which then evaporates. Such open evaporation can affect human health through inhalation of toxic gases such as ammonia (NH3) and hydrogen sulfide (H2S) and contaminate groundwater through seepage (Al-Wahaibi et al. 2021). In addition, both landfills have been built with high-density polyethylene (HDPE) geomembrane liner to protect leachate infiltration into the groundwater/soil. Since the intensity and duration of rainfall in Oman are not significant compared with tropical countries, the rainfall duration, including past events, has not shown any overflow of leachates, rather than dilution. The construction of a leachate treatment plant on the Multaqa landfill is underway. However, no treatment plants have yet been started on the Barka landfill.

The most common MSW includes food, plastics, paper/cardboard, and textile waste. The detailed waste classifications of the two landfill sites that contributed to the leachate generation are shown in Figure 2. In this study, the leachate samples were collected from these landfill locations. The Multaqa landfill (23° 33′ 89″ N, 58° 44′ 91″ E) has a total volume of 1,700,000 m3 (waste storage cell-2), where total waste received is almost 1,000 tonnes per day. The Barka landfill (23° 59′ 79″ N, 58° 17′ 79″ E) has a total capacity of 2,800,000 m3 (waste storage cell-2), receiving waste of about 1,600 tonnes per day. Therefore, it is considered the largest landfill in Oman.

Figure 2

Various types of MSW collected at Multaqa and Barka landfills that contribute to leachate generation (EcoMENA Be'ah 2013; MSWM 2017).

Figure 2

Various types of MSW collected at Multaqa and Barka landfills that contribute to leachate generation (EcoMENA Be'ah 2013; MSWM 2017).

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Leachate sampling

Leachate samples were collected from the two landfill sites (a schematic sketch of the landfill is shown in Figure 3) over a period of three months (January 2019–April 2019). Thirty-six leachate samples were collected to evaluate the quality. Out of this, 18 samples were collected during the period when rainfall did not occur. An additional 18 samples were collected from each landfill after six days of rainfall to assess the impact of rainfall on leachate dilution.

Figure 3

(a) Schematic sketch of the landfill with leachate collection system, (b) Al-Multaqa landfill leachate collection pond, and (c) Barka landfill leachate collection pond.

Figure 3

(a) Schematic sketch of the landfill with leachate collection system, (b) Al-Multaqa landfill leachate collection pond, and (c) Barka landfill leachate collection pond.

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The maximum daily rainfall levels for Multaqa (3.05 mm) and Barka (55.88 mm) landfill sites were recorded with an already installed high-resolution dual spoon rain gauge sensor (Model: ECRN-100). Leachate samples were stored in 2 L clean glass bottles. In addition, 100 mL leachate samples were collected in sterilized bottles for microbial analyses. The sample preparation and physicochemical analysis were carried out in the Environmental Engineering Laboratory at Sultan Qaboos University, Oman. Sample collection, preservation, and analysis were conducted through standard methods (APHA 2005) of examining water and wastewater, as recommended by the American Public Health Association (APHA).

pH, electrical conductivity and dissolved solids analysis

The pH measurement was carried out by the potentiometric method using Mettler Toledo equipment. The electrical conductivity (EC) measurements were taken using a conductivity meter (model WTW InoLab 7310), capable of measuring conductivity with an error not exceeding 1% or 1 μmho/cm. For total dissolved solids (TDS), a well-mixed sample was filtered through a standard 47 mm glass fiber filter paper. The filtrate solids are evaporated to dryness in a weighed dish and dried to a constant weight at 180 °C. The increase in dish weight represented the amount of TDS. For total suspended solids (TSS), the residue retained on the filter after TDS separation was dried to a constant weight at 103–105 °C. Therefore, an increase in the filter weight represented the TSS. Total volatile solids (TVS) and total fixed solids (TFS) were determined as TSS on the filter paper after being kept in a furnace at 550 °C for five minutes. TVS evaporated from the upper surface of filter paper and the rest was weighed as TFS.

Chemical and biological oxygen demand analysis

Chemical oxygen demand (COD) was determined using the APHA 5220C closed reflux titrimetric method, where 1–2 mL samples were taken in 10 mL borosilicate culture tubes. Then 0.167 M potassium chromate (K2Cr2O7) of known volume and 2 mL of sulfuric acid reagent were added to the tubes. Silver sulfate was added to concentrated sulfuric acid (at 5.5 g/kg sulfuric acid) and digested on a hotplate for two hours at 150 oC. The tubes were cooled and titrated with 0.05M ferrous ammonium sulfate (FAS) solution with ferroin indicator. Samples were digested on a HACH COD reactor at 150 oC for two hours.

Biochemical oxygen demand (BOD5) was measured by the APHA 5210B five-day BOD5 test, using a known volume of the sample placed in a 300 mL incubator bottle. The water was aerated with four solutions, phosphate buffer, magnesium sulfate, calcium chloride, and ferric chloride solutions (the volume of each solution added was 1 mL/L). Solutions added into the incubator bottle were filled up to the brim of a Winkler BOD bottle. On the first day, dissolved oxygen (DO1) was measured and placed in an incubator at 20 °C for five days. On the fifth day, the dissolved oxygen (DO5) of the sample was measured. The five-day BOD was measured using the equation, BOD5=(DO1DO5)/P, where P is the decimal volumetric fraction of the sample used in the BOD experiment. DO was measured using a Martini instrument (model MI 190) and DO/temperature bench meter (model Hanna H9145).

Total extractable petroleum hydrocarbons analysis

Total petroleum hydrocarbons (TPH) were monitored following an amended APHA 6630C liquid–liquid extraction method. This method was employed to determine total organics in the liquid sample. First, a 2 L sample was extracted into 2 L×50 mL (methylene chloride) and 2 L×25 mL (dichloromethane, CH2Cl2), respectively, in a separator funnel. The extract was collected and dried using anhydrous granular sodium sulfate, filtered. Then a concentration was obtained by using a Buchi rotary evaporator. The sample weight was then gravimetrically determined.

Total organic carbon analysis

Total organic carbon (TOC) was determined using the APHA 5310B combustion infrared method. A total carbon analyzer (SKALAR FormacsHT) was injected with the sample into a heated reaction chamber (825 °C) packed with an oxidative catalyst. The carbon dioxide gas (CO2) produced in the reaction from organic and inorganic carbons was transported by carrier-gas (Zero Air) streams. It was measured employing a nondispersive infrared analyzer. The instrument was calibrated with organic carbon standards (100–500 mg C/L) and inorganic carbon standards (20–200 mg C/L). Because total carbon and inorganic carbon were measured, TOC concentration was obtained by the difference between the two.

Heavy metal, anion, and cation analysis

Trace elements were analyzed using an optical emission spectrometer (VARIAN 710 ES–ICP). Standards of heavy metals at varying concentrations (0.1 ppm, 0.5 ppm, 1.0 ppm, 5.0 ppm, and 10.0 ppm) were used for developing the calibration equation. Moreover, heavy metals of the leachate, namely calcium (Ca), magnesium (Mg), copper (Cu), chromium (Cr), nickel (Ni), zinc (Zn), manganese (Mn), iron (Fe), lead (Pb), and strontium (Sr) were analyzed based on the standard methods (APHA 2005) using the atomic absorption spectroscopy (AAS) method and a Perkin Elmer atomic absorption spectrophotometer (model A Analyst 300). In addition, sodium (Na+) and potassium (K+) were determined using a microprocessor flame photometer (FP – 902 PG) via the standard methods of APHA (2005).

Moreover, anions such as fluoride (F), chloride (Cl), bromide (Br), nitrate (NO3), nitrite (NO2), phosphate (PO42−), and sulfate (SO42−) were measured by ion chromatography (IC) (881 IC pro Metrohm) and a professional sample processor (Model 858) following standard methods of APHA (2005).

Nitrogen and ammonia nitrogen analysis

Total Kjeldahl nitrogen (TKN) was determined using 4% boric acid, 40% sodium hydroxide dosage, mixed indicators, and titrating with 0.25N hydrochloric acid (HCl) after TKN steam distillation with a Unit Pro-Nitro-S JP SELECTA instrument (the equipment measured within 0.2–200 mg of nitrogen and programmed distillation time with >99.5% nitrogen recovery from the sample). Ammonia-nitrogen (NH3-N) was determined by quantitative analysis with a UV/Vis spectrophotometer (model LAMBDA EZ210) using the phenate method, i.e., mixing of phenol solution, nitroprusside, and an oxidizing agent was used to develop color which could be recognized spectrophotometrically with nanometers (Model 650) to detect the ammonia-nitrogen concentration in the sample. Phosphates were determined in the form of orthophosphates, polyphosphate and total phosphate by the filter paper digestion method. The solution was prepared as 32 mL of sulfuric acid mixed with 12.8 g of potassium persulfate and filled with deionized water up to 100 mL. The same solution was used for the digestion process.

Coliforms analysis

The Colilert test was used as a microbiology test to quantify total coliforms (T-Coli) and Escherichia coli (E. coli) in the form of the most probable number (MPN), with results in 24 hours. The MPN table was provided with a Quanti-TrayTM instrument to determine the number. Yellow wells indicated T-Coli and a yellow well with fluorescent lights represented the E. coli bacteria in the leachate sample. Scanning electron microscopy (SEM) was used to identify different microbes present in the leachate sample.

Leachate pollution index (LPI)

In this study, 92 parameters were determined to characterize the leachate's physical, chemical, and biological properties. Among the parameters analyzed, 18 parameters were employed to calculate the leachate pollution index (LPI) following methods described in Kumar & Alappat (2005b). The parameters used for determining the organic-LPI (LPIo) were COD, BOD5, phenolic compounds, and total coliform bacteria. Similarly, the parameters used for determining the inorganic-LPI (LPIi) were pH, TKN, ammonium nitrogen, TDS, and chlorides; and the same for ascertaining heavy metal-LPI (LPIhm) were total chromium, lead, mercury, arsenic, cyanide, zinc, nickel, copper, and iron (Kumar & Alappat 2005b). The sub-LPIs were calculated using the weighted linear sum aggregation function given in Equation (1):
formula
(1)
In Equation (1), LPI was the weighted additive leachate pollution index, n was the total number of leachate pollutants, wi was the weight of the ith pollutant, and pi was the sub-index score of the ith leachate pollutant variable. Equation (1) was derived using 18 parameters (mentioned above), where. The values of pi for different leachate parameters were obtained from sub-index average curves developed for each parameter (given in Kumar & Alappat (2005b)). The overall LPI was calculated from the aggregation of the three sub-LPIs (i.e., LPIo, LPIi, and LPIhm) using Equation (2). The overall LPI was considered for accurate estimation of expected leachate pollution by field professionals. The coefficients of individual sub-LPIs in Equation (2) were derived from the weight factors of the 18 parameters included in the overall LPI, and their contribution to each sub-LPI:
formula
(2)

Statistical analysis

Pearson correlation analysis was conducted to determine the causality relationship and degree of association among the measured contaminant levels present in the leachate. The correlation coefficient (r) values of r>0.7, 0.5<r<0.7, and <0.5 denoted strong, moderate, and weak correlation, respectively (Maiti et al. 2016; Vahabian et al. 2019). The analysis was conducted using Microsoft® Excel Software (version 2016).

Landfill leachate characterizations

Landfill leachate samples were characterized to assess the leachate quality, including the effects of rainfall events on each measured parameter. The summary statistics of all the measured physicochemical and biological parameters are given in Tables 14. Leachate samples were collected during the dry period and six days after a rainfall event. The dry period samples were denoted by MLL and BLL, whereas the samples after rainfall were denoted as Multaqa rainfall-affected landfill leachate (MRALL) and Barka rainfall-affected landfill leachate (BRALL).

Table 1

Chemical characteristics of leachate samples collected from Multaqa and Barka landfills

Characterization parametersUnitsMLLBLLMRALLBRALL
pH – 8.54±0.2 8.26±0.1 8.25±0.1 8.21±0.1 
Conductivity, EC mS/cm 54.1±0.7 60.86±1.1 15.25±0.5 20.59±1.2 
Total coliform MPN <1 2,275±250.2 2,692±47 2,741±77.6 
Escherichia coli, E. coli MPN <1 <1 410.33±7.5 422±14 
COD mgO2/L 33,600±300 28,000±20 3,600±20 3,950±36.1 
BOD5 mgO2/L 13,200±600 11,700±150 2,400±10 2,805±75.7 
Ammonia nitrogen, NH3-N mg/L 4,655±81 4,173.43±5.1 562.9±3 663.57±4.6 
Total Kjeldahl nitrogen, TKN mg/L 1.02±0.2 0.758±0.2 0.12±0.1 0.27±0.1 
Sodium, Na+ mg/L 6,610±65.6 7,620±5 1,864±8.5 1,984±9.2 
Potassium, K+ mg/L 4,280±20 4,980±18 1,288±2.6 1,489±3 
Total carbon, TC mg/L 13,975.8±32.6 12,599.5±5.5 2,096.83±11.5 2,347.77±36.4 
Inorganic carbon, IC mg/L 3,859±125 4,487±2 746.5±8 845.47±9.3 
Total organic carbon, TOC mg/L 10,118.5±10.3 8,112.83±11 1,351±6.6 1,575.63±15.2 
Fluoride, F mg/L 5.12±0.1 1.545±0.1 – 1.148±0.1 
Chloride, Cl mg/L 7,636.8±17.5 10,336.38±124.5 2,139.86±8 3,628.83±26.8 
Bromide, Br mg/L 22.9±0.2 22.653±0.1 7.15±0.1 12.94±0.2 
Nitrate, NO3 mg/L – 34.917±0.1 – 17.38±0.8 
Nitrite, NO2 mg/L – – – – 
Phosphate, PO43– mg/L 39.8±0.2 16.63±0.1 68.17±0.2 27.62±0.8 
Sulphate, SO42– mg/L 129.8±0.3 36.19±0.2 416.86±2 132.34±4.2 
Ortho-phosphates, OP mg/L 0.713±0.1 0.95±0.5 0.54±0.3 0.66±0.2 
Poly-phosphates, PP mg/L 8.15±0.2 4.91±0.3 0.35±0.1 3.61±0.1 
Total phosphates, TP mg/L 8.86±0.2 5.86±0.1 0.89±0.1 4.27±0.2 
Magnesium, Mg mg/L 157.88±0.9 308.61±5.9 61.11±0.9 132.79±1.3 
Calcium, Ca mg/L 109.32±0.1 34.54±0.6 143.69±0.7 80.05±2 
Strontium, Sr mg/L 0.468±0.2 0.588±0.1 0.58±0.1 2.37±0.5 
Iron, Fe mg/L 26.47±0.7 16.69±1.2 10.19±0.4 9.64±0.2 
Manganese, Mn mg/L 1.16±0.3 0.65±0.2 0.60±0.5 0.75±0.1 
Copper, Cu mg/L 1.83±0.4 2.426±0.4 1.96±0.2 6.41±0.4 
Zinc, Zn mg/L 1BDL 1BDL 1BDL 1BDL 
Chromium, Cr mg/L 10.42±0.2 10.41±0.6 9.54±0.1 7.29±0.1 
Nickle, Ni mg/L 1BDL 1BDL 1BDL 36.29 
Lead, Pb mg/L 1BDL 1BDL 1BDL 1BDL 
Aluminum, Al mg/L 1BDL 1BDL 0.679 1BDL 
Boron, B mg/L 0.697±1.8 BDL BDL 8.21±0.1 
Phosphorus, P mg/L 1.06±0.8 0.72±0.6 7.35±0.7 20.59±1.2 
Titanium, T mg/L 1BDL 1BDL 0.08±0.9 2,741.33±77.6 
Mercury, Hg mg/L 1BDL 1BDL 1BDL 422±14 
Arsenic, As mg/L 1BDL 1BDL 1BDL 1BDL 
Cyanide, CN mg/L 1BDL 1BDL 1BDL 1BDL 
Thallium, Tl mg/L 1BDL 1BDL 0.54±0.7 1BDL 
Characterization parametersUnitsMLLBLLMRALLBRALL
pH – 8.54±0.2 8.26±0.1 8.25±0.1 8.21±0.1 
Conductivity, EC mS/cm 54.1±0.7 60.86±1.1 15.25±0.5 20.59±1.2 
Total coliform MPN <1 2,275±250.2 2,692±47 2,741±77.6 
Escherichia coli, E. coli MPN <1 <1 410.33±7.5 422±14 
COD mgO2/L 33,600±300 28,000±20 3,600±20 3,950±36.1 
BOD5 mgO2/L 13,200±600 11,700±150 2,400±10 2,805±75.7 
Ammonia nitrogen, NH3-N mg/L 4,655±81 4,173.43±5.1 562.9±3 663.57±4.6 
Total Kjeldahl nitrogen, TKN mg/L 1.02±0.2 0.758±0.2 0.12±0.1 0.27±0.1 
Sodium, Na+ mg/L 6,610±65.6 7,620±5 1,864±8.5 1,984±9.2 
Potassium, K+ mg/L 4,280±20 4,980±18 1,288±2.6 1,489±3 
Total carbon, TC mg/L 13,975.8±32.6 12,599.5±5.5 2,096.83±11.5 2,347.77±36.4 
Inorganic carbon, IC mg/L 3,859±125 4,487±2 746.5±8 845.47±9.3 
Total organic carbon, TOC mg/L 10,118.5±10.3 8,112.83±11 1,351±6.6 1,575.63±15.2 
Fluoride, F mg/L 5.12±0.1 1.545±0.1 – 1.148±0.1 
Chloride, Cl mg/L 7,636.8±17.5 10,336.38±124.5 2,139.86±8 3,628.83±26.8 
Bromide, Br mg/L 22.9±0.2 22.653±0.1 7.15±0.1 12.94±0.2 
Nitrate, NO3 mg/L – 34.917±0.1 – 17.38±0.8 
Nitrite, NO2 mg/L – – – – 
Phosphate, PO43– mg/L 39.8±0.2 16.63±0.1 68.17±0.2 27.62±0.8 
Sulphate, SO42– mg/L 129.8±0.3 36.19±0.2 416.86±2 132.34±4.2 
Ortho-phosphates, OP mg/L 0.713±0.1 0.95±0.5 0.54±0.3 0.66±0.2 
Poly-phosphates, PP mg/L 8.15±0.2 4.91±0.3 0.35±0.1 3.61±0.1 
Total phosphates, TP mg/L 8.86±0.2 5.86±0.1 0.89±0.1 4.27±0.2 
Magnesium, Mg mg/L 157.88±0.9 308.61±5.9 61.11±0.9 132.79±1.3 
Calcium, Ca mg/L 109.32±0.1 34.54±0.6 143.69±0.7 80.05±2 
Strontium, Sr mg/L 0.468±0.2 0.588±0.1 0.58±0.1 2.37±0.5 
Iron, Fe mg/L 26.47±0.7 16.69±1.2 10.19±0.4 9.64±0.2 
Manganese, Mn mg/L 1.16±0.3 0.65±0.2 0.60±0.5 0.75±0.1 
Copper, Cu mg/L 1.83±0.4 2.426±0.4 1.96±0.2 6.41±0.4 
Zinc, Zn mg/L 1BDL 1BDL 1BDL 1BDL 
Chromium, Cr mg/L 10.42±0.2 10.41±0.6 9.54±0.1 7.29±0.1 
Nickle, Ni mg/L 1BDL 1BDL 1BDL 36.29 
Lead, Pb mg/L 1BDL 1BDL 1BDL 1BDL 
Aluminum, Al mg/L 1BDL 1BDL 0.679 1BDL 
Boron, B mg/L 0.697±1.8 BDL BDL 8.21±0.1 
Phosphorus, P mg/L 1.06±0.8 0.72±0.6 7.35±0.7 20.59±1.2 
Titanium, T mg/L 1BDL 1BDL 0.08±0.9 2,741.33±77.6 
Mercury, Hg mg/L 1BDL 1BDL 1BDL 422±14 
Arsenic, As mg/L 1BDL 1BDL 1BDL 1BDL 
Cyanide, CN mg/L 1BDL 1BDL 1BDL 1BDL 
Thallium, Tl mg/L 1BDL 1BDL 0.54±0.7 1BDL 

MLL: Multaqa landfill leachate; BLL: Barka landfill leachate; MRALL: Multaqa rainfall-affected landfill leachate; BRALL: Barka rainfall affected landfill leachate; BDL: below detection limit (the range for heavy metals less than 0.0001 mg/L, and for anions i.e. fluorides, nitrate, nitrite, less than 0.1 mg/L).

Table 2

Organic pollutant levels detected from Multaqa and Barka landfill sites

Organic pollutants (mg/L)MLLBLL
4-Methyl-2-pentanone722 0.542 0.336 
Toluene 0.371 0.377 
Cyclotrisiloxane, hexamethyl 1.539 0.686 
Cyclohexanol 0.348 0.313 
N-(n-propyl) acetamide 0.352 0.455 
l-Thretol/1,2,3,4-tetrahydroxybutane 0.342 0.637 
Bentazones 0.441 0.040 
Phenol 0.736 3.709 
Benzene, ethoxy-(phenetole) 2.068 1.099 
Hexanamide 1.373 4.801 
N-methyl-2-pyrrolidone (NMP) 0.727 3.611 
Linalool oxide 0.976 1.938 
2-Acetylpyrrole 1.343 2.467 
p-Cresol 1.967 0.624 
1,3-Pentanediol, 2,2,4-trimethyl 1.100 1.514 
Di-butyl tin 1.163 1.713 
2-Piperidinone, 1-methyl- 0.994 1.799 
alpha-Terpineol 3.405 7.166 
1,3,3-Trimethyl-2-oxabicyclo[2.2.2]octan-6-ol 1.069 1.305 
1,8-Terpin hydrate 0.467 0.385 
Nicotine 2.085 7.650 
Lindane 0.078 3.745 
Skatol 1.191 2.167 
Penta-bromodiphenyl ether 1.901 2.264 
Tetra-bromobisphenol-A 5.456 5.336 
Chlorinated-benzene 2.795 4.916 
N-methyloxindole 0.569 3.445 
Diethyl phthalate 4.911 5.070 
2-Pyrene 3.537 3.350 
MCPPs (Mecoprop) 0.605 3.325 
Resins, thermoset 7.042 3.397 
9-Hexadecenoic acid 2.868 0.910 
Palmitic acid 7.036 0.919 
3,5-di-tert-butyl-4-hydroxyphenylpropionic acid 5.737 2.456 
Brimstone (octasulfur) 8.116 0.999 
Oleic acid 0.524 1.107 
1-(4-Hydroxyphenyl)-2-(3-hydroxyphenyl)ethane 2.264 1.085 
Bisphenol A 6.948 2.719 
Hexanedioic acid, bis(2-ethylhexyl) ester 0.136 1.098 
Pentacosane 2.142 0.927 
Bis(2-ethylhexyl) phthalate (DEHP) 0.083 2.473 
Hexacosane 1.869 0.757 
1,6-Trichloropropanes 2.584 1.269 
Phosphine, chlorodimethyl 2.788 1.595 
Squalene 3.597 1.247 
Nonacosane 1.817 0.798 
Organic pollutants (mg/L)MLLBLL
4-Methyl-2-pentanone722 0.542 0.336 
Toluene 0.371 0.377 
Cyclotrisiloxane, hexamethyl 1.539 0.686 
Cyclohexanol 0.348 0.313 
N-(n-propyl) acetamide 0.352 0.455 
l-Thretol/1,2,3,4-tetrahydroxybutane 0.342 0.637 
Bentazones 0.441 0.040 
Phenol 0.736 3.709 
Benzene, ethoxy-(phenetole) 2.068 1.099 
Hexanamide 1.373 4.801 
N-methyl-2-pyrrolidone (NMP) 0.727 3.611 
Linalool oxide 0.976 1.938 
2-Acetylpyrrole 1.343 2.467 
p-Cresol 1.967 0.624 
1,3-Pentanediol, 2,2,4-trimethyl 1.100 1.514 
Di-butyl tin 1.163 1.713 
2-Piperidinone, 1-methyl- 0.994 1.799 
alpha-Terpineol 3.405 7.166 
1,3,3-Trimethyl-2-oxabicyclo[2.2.2]octan-6-ol 1.069 1.305 
1,8-Terpin hydrate 0.467 0.385 
Nicotine 2.085 7.650 
Lindane 0.078 3.745 
Skatol 1.191 2.167 
Penta-bromodiphenyl ether 1.901 2.264 
Tetra-bromobisphenol-A 5.456 5.336 
Chlorinated-benzene 2.795 4.916 
N-methyloxindole 0.569 3.445 
Diethyl phthalate 4.911 5.070 
2-Pyrene 3.537 3.350 
MCPPs (Mecoprop) 0.605 3.325 
Resins, thermoset 7.042 3.397 
9-Hexadecenoic acid 2.868 0.910 
Palmitic acid 7.036 0.919 
3,5-di-tert-butyl-4-hydroxyphenylpropionic acid 5.737 2.456 
Brimstone (octasulfur) 8.116 0.999 
Oleic acid 0.524 1.107 
1-(4-Hydroxyphenyl)-2-(3-hydroxyphenyl)ethane 2.264 1.085 
Bisphenol A 6.948 2.719 
Hexanedioic acid, bis(2-ethylhexyl) ester 0.136 1.098 
Pentacosane 2.142 0.927 
Bis(2-ethylhexyl) phthalate (DEHP) 0.083 2.473 
Hexacosane 1.869 0.757 
1,6-Trichloropropanes 2.584 1.269 
Phosphine, chlorodimethyl 2.788 1.595 
Squalene 3.597 1.247 
Nonacosane 1.817 0.798 

MLL: Multaqa landfill leachate; BLL: Barka landfill leachate.

Table 3

Comparison of different types of solids present in the leachate sample collected at two landfill sites i.e., MLL–BLL and MRALL–BRALL

Solids analysisLandfill leachate solids analysis results
UnitsMLLBLLMRALLBRALL
Total dissolved solids (TDS) mg/L 24,210 36,246.5 5,216 5,787 
Total suspended solids (TSS) mg/L 1,270 1,212.5 120 133.34 
Total volatile solids (TVS) mg/L 605 577.5 24 28.67 
Total fixed solids (TFS) mg/L 665 635 96 102 
Total solids (TS) mg/L 26,750 38,671.5 5,456 6,051 
Solids analysisLandfill leachate solids analysis results
UnitsMLLBLLMRALLBRALL
Total dissolved solids (TDS) mg/L 24,210 36,246.5 5,216 5,787 
Total suspended solids (TSS) mg/L 1,270 1,212.5 120 133.34 
Total volatile solids (TVS) mg/L 605 577.5 24 28.67 
Total fixed solids (TFS) mg/L 665 635 96 102 
Total solids (TS) mg/L 26,750 38,671.5 5,456 6,051 

*MLL: Multaqa landfill leachate; BLL: Barka landfill leachate; MRALL: Multaqa rainfall-affected landfill leachate; BRALL: Barka rainfall affected landfill leachate.

Table 4

Summation of individual leachate pollution indices, organic, inorganic, heavy metals and combinations of all pollutants to estimate the overall leachate pollution index for the two landfill sites with rainfall-affected leachate

IndicesParameterswiMLLpiwi piBLLpiwi piMRALLpiwi piBRALLpiwi pi
LPIo – Organic compounds COD 0.267 33,600 85 22.69 28,000 80 21.36 3,600 48 12.81 3,950 58 15.48 
BOD5 0.263 13,200 65 17.09 11,700 62 16.30 2,400 42 11.04 2,805 44 11.57 
Phenolic compounds 0.246 69.49 40 9.84 65.575 38 9.34 – – – – – – 
Total coliforms 0.224 1.12 2,419.6 76 17.02 2,692 80 17.92 2,741.3 82 18.37 
     50.74   64.02   41.77   45.42 
LPIi – Inorganic compounds pH 0.214 8.54 1.07 8.26 1.07 8.25 4.8 1.02 8.21 4.8 1.02 
TKN 0.206 1.02 1.03 0.758 3.7 0.76 0.12 1.3 0.26 0.27 1.35 0.278 
NH3-N 0.198 4,655 100 19.80 4,173.43 100 19.80 562.90 45 8.91 663.57 48 9.50 
TDS 0.195 24,210 42 8.19 36,246.50 65 12.67 5,216 100 19.50 5,787 100 19.50 
Chloride, (Cl0.187 7,636.80 48 8.98 10,336.38 80 14.96 2,139.86 20 3.74 3,628.83 27 5.04 
     39.07   49.26   33.43   35.34 
LPIhm – Heavy metals Chromium, (Cr) 0.125 10.42 65 8.12 10.41 60 7.50 9.54 60 7.50 7.29 55 6.870 
Lead, (Pb) 0.123 0.0001 0.123 0.0001 0.123 0.0001 0.123 0.0001 0.123 
Mercury, (Hg) 0.121 0.0001 0.121 0.0001 0.121 0.0001 0.121 422 100 12.10 
Arsenic, (As) 0.119 0.0001 0.119 0.0001 0.119 0.0001 0.119 0.0001 0.119 
Cyanide, (CN) 0.114 0.0001 0.114 0.0001 0.114 0.0001 0.114 0.0001 0.114 
Zinc, (Zn) 0.110 0.0001 0.110 0.0001 0.110 0.0001 0.110 0.0001 0.110 
Nickel, (Ni) 0.102 0.0001 0.102 0.0001 0.102 0.0001 0.102 36.29 100 10.20 
Copper, (Cu) 0.098 1.83 0.490 2.43 0.780 1.96 0.490 6.41 12 1.176 
Iron, (Fe) 0.088 26.47 1.5 0.132 16.69 1.1 0.096 10.19 0.95 0.090 9.64 0.82 0.072 
    9.43 9.07 8.77 30.88 
Overall LPI (LPIoverall) = 0.232×LPIo + 0.257×LPIi + 0.511×LPIhm 
LPIoverall   26.63 32.14 22.76 35.40 
IndicesParameterswiMLLpiwi piBLLpiwi piMRALLpiwi piBRALLpiwi pi
LPIo – Organic compounds COD 0.267 33,600 85 22.69 28,000 80 21.36 3,600 48 12.81 3,950 58 15.48 
BOD5 0.263 13,200 65 17.09 11,700 62 16.30 2,400 42 11.04 2,805 44 11.57 
Phenolic compounds 0.246 69.49 40 9.84 65.575 38 9.34 – – – – – – 
Total coliforms 0.224 1.12 2,419.6 76 17.02 2,692 80 17.92 2,741.3 82 18.37 
     50.74   64.02   41.77   45.42 
LPIi – Inorganic compounds pH 0.214 8.54 1.07 8.26 1.07 8.25 4.8 1.02 8.21 4.8 1.02 
TKN 0.206 1.02 1.03 0.758 3.7 0.76 0.12 1.3 0.26 0.27 1.35 0.278 
NH3-N 0.198 4,655 100 19.80 4,173.43 100 19.80 562.90 45 8.91 663.57 48 9.50 
TDS 0.195 24,210 42 8.19 36,246.50 65 12.67 5,216 100 19.50 5,787 100 19.50 
Chloride, (Cl0.187 7,636.80 48 8.98 10,336.38 80 14.96 2,139.86 20 3.74 3,628.83 27 5.04 
     39.07   49.26   33.43   35.34 
LPIhm – Heavy metals Chromium, (Cr) 0.125 10.42 65 8.12 10.41 60 7.50 9.54 60 7.50 7.29 55 6.870 
Lead, (Pb) 0.123 0.0001 0.123 0.0001 0.123 0.0001 0.123 0.0001 0.123 
Mercury, (Hg) 0.121 0.0001 0.121 0.0001 0.121 0.0001 0.121 422 100 12.10 
Arsenic, (As) 0.119 0.0001 0.119 0.0001 0.119 0.0001 0.119 0.0001 0.119 
Cyanide, (CN) 0.114 0.0001 0.114 0.0001 0.114 0.0001 0.114 0.0001 0.114 
Zinc, (Zn) 0.110 0.0001 0.110 0.0001 0.110 0.0001 0.110 0.0001 0.110 
Nickel, (Ni) 0.102 0.0001 0.102 0.0001 0.102 0.0001 0.102 36.29 100 10.20 
Copper, (Cu) 0.098 1.83 0.490 2.43 0.780 1.96 0.490 6.41 12 1.176 
Iron, (Fe) 0.088 26.47 1.5 0.132 16.69 1.1 0.096 10.19 0.95 0.090 9.64 0.82 0.072 
    9.43 9.07 8.77 30.88 
Overall LPI (LPIoverall) = 0.232×LPIo + 0.257×LPIi + 0.511×LPIhm 
LPIoverall   26.63 32.14 22.76 35.40 

MLL: Multaqa landfill leachate; BLL: Barka landfill leachate; MRALL: Multaqa rainfall-affected landfill leachate; BRALL: Barka rainfall affected landfill leachate; wi – weight factors; pi – sub-index values for each pollutant. Units: COD and BOD – mgO2/L, phenolic compounds – mg/L, total coliform – MPN/100 mL, chlorides – mg/L, TKN – mg/L, ammonia-nitrogen – mg/L, heavy metals – ppm, and trace elements – ppm.

pH, electrical conductivity and total dissolved solids

The pH level were consistent in both MLL (8.54) and BLL (8.26) before rainfall. It was unchanged (8.2) for both landfills even after the rainfall event (Table 1). The decomposition of MSW produced ammonia, which ultimately formed ammonia (NH4+) and hydroxyl (OH) ions to cause alkalinity, thereby raising pH levels to 8 (Zeng et al. 2013). The pH in both MLL and BLL did not change after rainfall because the water molecules also underwent dissociation to produce both hydrogen ions (H+) and hydroxide ions (OH), thereby neutralizing their acidity/alkalinity effects on the leachate. The EC levels were low in MLL (54.1 mS/cm) compared with BLL (60.8 mS/cm). After the rainfall, they reduced significantly to 15.25 mS/cm and 20.59 mS/cm, respectively, due to the dilution of the dissolved organic matter and inorganic minerals present. Thus, due to mineralization, the high EC levels contribute to the leachate's high pollutant load and provide beneficial support for plant growth and improve soil biota (Ishak et al. 2016). TDS levels were very high in BLL (36,247 mg/L) compared with those in MLL (24,210 mg/L) due to the high percentage of food waste in the MSW of the former compared with the latter (Figure 2). As far as water quality and treatments were concerned, rainfall played an essential role. It reduced the TDS (mg/L) levels (Table 3) by about 78%–84% through dilution. A decrease in TDS contents reduces the eutrophication in water bodies that cause death to aquatic organisms (Umar et al. 2010). Also, it enhances wastewater treatment efficiency due to the leachate's reduced turbidity levels (Nor Nazrieza et al. 2015). Table 5 provides the regulatory standards for leachate and industrial waste disposal that are required to protect the environment and public health from contamination. Table 5 shows that except for the pH (6–9) and the EC (2,700 μS/cm) values for both landfills (MLL and BLL) before and after the rainfall events, all other measured parameters exceeded the regulatory standards (US EPA 2000).

Table 5

Summary of leachate/industrial waste disposal regulatory standards

ParameterMaximum discharge limitsReferenceNotes
BOD5 20 MECA (1993)  Wastewater discharge regulation of Oman 
COD 200 
Total N – 
TDS 2,000 
Total coliform – 
Faecal coliform (MPN) 1,000 
EC (μS/cm) 2,700 
SO42− 400 
Mg 150 
2.0 
Fe 5.0 
Na 300 
Cl 650 
Li 0.07 
Al 5.0 
pH 6–9 US EPA (2000)  Maximum daily concentration limits of landfill discharge 
TSS 88 
BOD5 220 
NH3-N 10 
Ag 0.43 
As 1.1 
Cr 1.1 
Phenols 0.048 
Zn 0.535 
Cd 0.69 Goverment of Ontario (2021)  Leachate disposal requirements 
Pb 0.69 
Hg 0.15 
Ni 3.98 
Vanadium 4.3 
Antimony 1.9 
Ba 1.2 
Cu – 
CN 0.86 
Thallium 1.4 
Be 0.82 
ParameterMaximum discharge limitsReferenceNotes
BOD5 20 MECA (1993)  Wastewater discharge regulation of Oman 
COD 200 
Total N – 
TDS 2,000 
Total coliform – 
Faecal coliform (MPN) 1,000 
EC (μS/cm) 2,700 
SO42− 400 
Mg 150 
2.0 
Fe 5.0 
Na 300 
Cl 650 
Li 0.07 
Al 5.0 
pH 6–9 US EPA (2000)  Maximum daily concentration limits of landfill discharge 
TSS 88 
BOD5 220 
NH3-N 10 
Ag 0.43 
As 1.1 
Cr 1.1 
Phenols 0.048 
Zn 0.535 
Cd 0.69 Goverment of Ontario (2021)  Leachate disposal requirements 
Pb 0.69 
Hg 0.15 
Ni 3.98 
Vanadium 4.3 
Antimony 1.9 
Ba 1.2 
Cu – 
CN 0.86 
Thallium 1.4 
Be 0.82 

Major cation and ammonia analysis

Significant cation concentrations of the leachates before rain versus after the rainfall event for MLL and BLL are summarized in Table 1. The results show that for MLL, Mg, Fe, Mn, and Cr concentrations reduced due to rainfall, whereas Ca, Sr, Cu, Zn concentrations were increased in MLL after rainfall (Table 1). A similar situation occurred in BLL samples where concentration levels of certain cations such as Mg, Fe, and Cr were reduced, while Ca, Sr, Mn, and Cu concentrations increased after rain (Table 1). These findings are consistent with the study conducted by Mavakala et al. (2016), which reported an increase in major cation concentration during the dry season compared with the rainy season. Thus, the increase and decrease in concentrations of the leachate cations for both landfills (MLL and BLL) were due to seasonal climatic (precipitation and temperature) fluctuations, waste compositions, landfill age, and design (Kjeldsen et al. 2002). Despite the fact that the rainfall showed the stability of the leachate's properties, the higher cation concentrations in the leachate could be attributed to their old age (Christensen et al. 2001).

Both landfill leachate samples had similar concentration levels of Na+ and K+ before the rainy season. Thus, there was a more than five times reduction in concentrations after the rainfall event (Table 1). Studies have shown that optimum levels of Na+ and K+ are vital for the improvement of nervous systems. However, high concentrations can cause renal disorder and cardiovascular–circulatory disease (Mor et al. 2006). High K+ affects freshwater resources through leachate plume pollution, as it contains traces of pesticides and insecticides, directly causing kidney and heart failure, and diabetes problems (Naveen et al. 2017). A large amount of calcium causes groundwater hardness, but at acceptable concentrations in water it helps to promote strong bones and teeth. Also, the right proportion of K+ helps to improve soil salinity and it is a vital microelement for developing plant cell walls (Ellis 1980).

The concentration levels of NH3-N in leachate samples before rain were similar for both landfills, and these reduced drastically (more than five times) after the rain (Table 1). Such reductions could be attributed to the release of gaseous NH3 into the atmosphere due to rainfall events. It should be noted that NH3-N can liberate (NH4+) to affect the marine ecosystem adversely due to nitrogen fixation and can damage the internal tissues of aquatic organisms at elevated levels (Mor et al. 2006). To meet the effluent discharge guidelines, major cations such as Mg were high in MLL (157.88±0.9 mg/L) and BLL (308.61±5.9 mg/L) samples prior to the rainfall event, but they were found to be low after rainfall at 61.11±0.9 mg/L and 132.79±1.3 mg/L, respectively, compared with the regulatory standard (150 mg/L). The results in Table 1 could not meet discharge limits for Fe (5.0 mg/L) and Na (300 mg/L), but Al and Zn were observed to be very low when compared with the standards of 5.0 and 0.535 mg/L, respectively. Similarly, the concentration levels of NH3-N were very high prior to and after the rainfall events in both leachates, making it difficult to meet the effluent discharge limit of 10 mg/L (US EPA 2000, Table 5).

Major anions analysis

The study also assessed major anion (F, Cl, Br, NO3, NO2, PO43– and SO42–) concentrations in leachates from both landfills (Table 1). The Cl concentration in BLL was higher than that in MLL. However, all other anion concentrations were very low for both landfills. The Cl levels in the BLL sample may be due to leakages from household, urban, and commercial septic tanks (Mor et al. 2006). In addition, most soluble wastes such as organic, construction, and demolition wastes may increase SO42– levels (Venkatesan & Swaminathan 2009). While anion concentration has a vital role in plant growth by decomposing organic substances, high levels in landfills could contribute to groundwater contamination via infiltration and percolation (Loizidou & Kapetanios 1993). When comparing the anions with the discharge limits (Table 5), it was found that some of the major anions (i.e., F, Cl, SO42−) were high. The concentrations of SO42− for both leachates were lower than the MECA (1993) limit (SO42− = 400 mg/L) except the rainfall-affected leachate samples for MLL (Table 1), which were found higher than the limit. This showed that not all the major anions present in the leachate samples posed a threat to the environment.

COD and BOD5

Several studies have revealed that BOD5/COD ratios are an essential determinant of landfill age. Thus a ratio of 0.63 reflects that the landfill is controlled under biological and biochemical activities (Naveen et al. 2013). In this current study, comparison is made of BOD5/COD ratios of MLL (0.39) and BLL (0.42) without rain with a study conducted by Hui (2005); Naveen et al. (2017) has indicated the age of the two landfills is within 5–10 years. The indicated lifetimes confirm the actual ages of both MLL (nine years) and BLL (five years) landfills. The action of rainfall on reducing BOD5 levels could be an indicator of pre-treatment techniques for improving highly polluted leachates. In this study, COD and BOD5 were used to quantify the organic matter contents in the leachates. The higher COD levels found in both leachate samples are consistent with the amount of organic waste dumped into the two landfills (Figure 2). Thus, the high BOD5 (MLL=13,200 mgO2/L, BLL=11,700 mgO2/L) found in leachates is likely to cause local greenhouse gas (GHG) emissions if the current landfill conditions are not improved (Naveen et al. 2017). However, after rainfall, the significant reduction in COD and BOD5 levels has indicated that dilution of leachates improves wastewater quality and reduces potential GHG emissions. The BOD5 increases with high microbial activity. It has been observed that maximum BOD5 starts from normal landfilling to maximum values between almost six months to 2.5 years. It is highly recommended to change the disposal of solid waste at high temperatures and anaerobic conditions (Sriram et al. 2017; Ryue et al. 2020). COD measures the oxygen used to oxidize organic wastes into inorganic constituents (Bhalla et al. 2012), quantifying the chemical toxicity and oxidizable toxins (Enitan et al. 2018). The measured COD and BOD5 levels obtained in this study were more than 150 to 500 times higher than the disposal limits of 200 mg/L and 20 mg/L, respectively, recommended by MECA (1993) (Table 5). These cause serious disposal challenges as they may contaminate aquatic and terrestrial ecosystems and require on-site treatment before disposal.

Organic pollutants and TOC

Among the major organic compounds that were characterized and quantified in both landfill leachates are aliphatic-phenolics, toluene, benzene, polyaromatic hydrocarbons, cyclohexanol, n-propyl, linalool oxides, cresols, skatol, hexadecenoic-palmitic-oleic and bisphenols (Table 2). It can be observed that there is a likelihood of these compounds leaching into the groundwater aquifers as plumes due to their relatively high concentration levels at both landfills. For example, there were high levels of hexanamide (4.801 mg/L), 2-pyrrolidinone methyl (3.611 mg/L), and nicotine (7.650 mg/L) in BLL. Similarly, MLL also recorded other organic pollutants such as brimstone (8.116 mg/L), bisphenol A (6.948 mg/L), and squalene (3.597 mg/L). Compounds such as hexanamide and N-Methyl-2-pyrrolidone (NMP) can severely damage the skin and the nervous system, respectively, on exposure. NMP is commonly used in textiles, resins, and metal-coated plastic products (Viel et al. 2008). The study found that NMP content was very high in BLL compared with MLL. The reason for these high NMP levels could be that BLL is currently receiving waste materials with high NMP contents from unsegregated waste materials and storing a large volume of segregated waste in a smaller area.

Table 2 summarizes the presence of similar organics in leachates in the form of monoaromatic and halogenated hydrocarbons (i.e., benzene, toluene, ethylbenzene, and xylenes), which are known to be potential causes of cancer (Jayawardhana et al. 2019). The reported concentration levels may be attributed to many pesticide and insecticide pollutants from BLL due to its frequent collection of agricultural and fertilizer material wastes (Figure 2). Also, compounds such as phenols and halogens from landfill leachates could cause freshwater contamination since they can easily seep into groundwater aquifers, especially considering their recalcitrant and non-biodegradability properties (Öman & Rosqvist 1999). Sulfur (octasulfur, S8) was found to be seven times higher in MLL (8.116 mg/L) compared with BLL (0.099 mg/L) and could cause both heart and kidney failures similar to bisphenol A, and squalene, known aromatic-dioxin hydrocarbons that cause cancer and skin problems (Öman & Junestedt 2008; Huang et al. 2012) (Table 2).

The study also determined similar concentrations of total carbon (TC), inorganic carbon, and TOC in both MLL and BLL (Table 1). However, there was more than 90% reduction in organic and inorganic carbon levels in the collected leachate samples after the rainfall event. High TOC could evolve from a high but variable amount of food, paper, and green waste from these landfills (Figure 2). Also, the higher concentration of TOC in leachate is due to the decomposition of organic and non-decomposed materials. Such higher TOC may increase the total alkalinity when the leachate plume seeps out into groundwater. However, groundwater contamination is enhanced by organic and inorganic components presented in the landfill leachate (Kale et al. 2010).

Microbiological contamination

Qualitative and quantitative assessments of microbiological levels of leachate samples (MLL and BLL) were carried out for the two landfills before and after rainfall events by measuring both T-Coli and E. coli concentrations in terms of the most probable number per 100 mL (MPN/100 mL). The results showed that both T-Coli and E. coli levels before rainfall were 1 MPN/100 mL except for the BLL samples, which indicated a T-Coli concentration of 2,275 MPN/100 mL. However, after rainfall, there was a rapid growth in the leachates' microbial levels in both landfill samples, especially for E. coli. Microbial characterization revealed that MLL (Figure 4(a)–4(c)) did not contain coliform bacteria but rather large colonies of bacteria species such as coccus, mycobacteria, and Spirillum sp.

Figure 4

Various types of microorganisms identified in leachate samples originating from MSW were collected from landfill sites Multaqa, MLL (a, b, c) and Barka, BLL (d, e, f).

Figure 4

Various types of microorganisms identified in leachate samples originating from MSW were collected from landfill sites Multaqa, MLL (a, b, c) and Barka, BLL (d, e, f).

Close modal

On the other hand, microbial characterization of BLL (Figure 4(d)–4(f)) showed highly contained tetrads, staphylococci, and spore-forming rod-like bacteria. T-Coli was higher in BLL than in MLL, which might be due to the presence of large fractions of decomposed food and yard wastes in the MSW mixture (Figure 2). Also, the rapid growth of E. coli in both leachate samples after rainfall could be due to dormancy of the bacteria caused by the harsh environmental (e.g., high temperature and humidity) stress of Muscat (Niven et al. 2008). Thus, after the rainfall event, suitable environmental conditions could have prevailed and favored the growth of E. coli (Tryland et al. 2011). Thus, the increase in bacterial number after rainfall was consistent with similar findings from the literature (Hill et al. 2006; Santiago-Rodriguez et al. 2012; Tornevi et al. 2014). E. coli in rain-diluted leachate is crucial as it can contaminate the groundwater aquifer through infiltration and percolation of the leachate plume and may pose severe health risks to humans and animals exposed to the groundwater resources (Adeyemi et al. 2007). Despite the rapid increase of E. coli after rainfall, the concentrations were still lower than the MECA (1993) limit of 1,000 MPN (Table 5).

Heavy metals

Heavy metals were analyzed for both MLL and BLL, including rainfall-affected samples, as presented in Table 1. The study found heavy metal concentrations (before rain vs after rainfall) for Fe (26.47 vs 10.19 mg/L), Mn (1.16 vs 0.600 mg/L), and Cr (10.42 vs 9.54 mg/L) to be high for MLL samples. Similar high concentrations of heavy metals were observed in BLL samples despite their differences in MSW proportions (%) (Figure 2). However, Zn, Ni, and Pb might be present in leachates in low concentrations; therefore, most of them were found below detection limits (BDL) after AAS analysis. Chromium concentrations were similar in both landfill leachate samples. Generally, it was observed that rainfall events slightly reduced a few heavy metal concentrations from both landfill leachates and increased the concentrations of most metals that were low before the rainfall. This increment may be due to the accumulation of metals carried in by the land surface runoff into the landfill leachates during the rainfall. Though some metal concentrations were very low or BDL, they might still threaten plant and animal health through the contamination of groundwater resources (Bulut & Baysal 2006). For example, highly toxic metals, i.e., As, CN, Hg, and Ni, were assessed to be BDL. However, they might affect fauna and flora life even in their low concentrations (Aziz et al. 2004). According to the Agency for Toxic Substances and Diseases Registry (ATSDR), Cr and Hg could cause cardiovascular diseases, impair liver cells, and cause nerve and gastrointestinal problems, if ingested even in low concentrations (ATSDR 2011). Although heavy metals can be toxic at low concentrations, the increased concentration of certain metals (i.e., Fe) plays a vital role in plant growth through biochemical reactions (i.e., chlorophyll synthesis and enzymatic activities) (Morrissey & Guerinot 2009; Rout & Sahoo 2015). The heavy metals in leachates were compared with international discharge limits (Table 5). None of them was found higher than the disposal limits recommended by the Government of Ontario (2021) for Pb (0.69 mg/L), Hg (0.15 mg/L), Ni (3.98 mg/L) and As (1.1 mg/L). However, the concentration of Cr exceeded the limits (i.e., 1.1 mg/L) in samples of both leachates collected from MLL and BLL in all cases. Therefore, an immediate investigation is required to identify the cause of the high Cr in both landfills.

Solids analysis

The leachate samples from the two landfills (MLL and BLL) were analyzed for TDS, TSS, TVS, TFS, and TS. Samples collected before and after rainfall events were analyzed to assess the effect of rainfall on solids content. The leachates indicate high solids concentrations (Table 3), which might be due to the landfill waste's high organic matter composition. Both TDS and TSS levels were higher in BLL samples when compared with those of MLL samples, which may be linked to the higher food waste and green waste contents in the Barka landfill (Figure 2). However, there were substantial reductions of solids concentrations after rainfall events leading to TDS and TSS reaching equivalent concentrations for both landfill leachates (Table 3). In addition to dilution, the reductions in TSS content may be due to the action of biological activities via aeration (Bashir et al. 2009). Interestingly, the concentration levels of both TFS and TVS in the leachate samples before and after rainfall showed similar trends for both landfill sites. The increased concentration of TDS, TFS, TS, and TVS shows the degree of mineralization and ultimately determines the turbidity. Also, contamination of surface water by the leachates can affect the survival of phytoplankton and other green algae communities as the leachate will reduce the photosynthetic activities of the organisms due to high turbidity levels (Hussein et al. 2019). Also, TS in the form of xenobiotic, fulvic, and humic acids could be severely harmful to natural aquifers through leachate plume seepage, affecting groundwater quality (Hussein et al. 2019).

Most previous studies on leachate characterization have focused on the TDS concentration. Very few studies have considered the concentration of TSS, TVS, TFS, and TS (Mor et al. 2018; Hussein et al. 2019; Vahabian et al. 2019). The current study revealed that the TDS values in all samples exceeded the disposal limits (i.e., 2,000 mg/L) (MECA 1993, Table 5). These results were consistent with the results obtained by Vahabian et al. (2019) (23,050 mg/L), Mishra et al. (2019) (1,820–2,825 mg/L) and Somani et al. (2019) (10,666–24,644 mg/L). The rapid reduction in TDS for MLL (5,216 mg/L) and BLL (5,787 mg/L) after rainfall was due to the dilution of leachate (Table 3).

Correlation analysis

The correlation matrix of the analytical results for both landfill leachates (MLL and BLL) before and after rainfall is shown in the Supplementary Material (S1–S4). It is observed that most of the r values were strong (r>0.9) and perfect (r=1) with a significant amount of data shown to be positive (+) and negative (–). For example, EC showed perfect and strong correction with COD (r=1), Na (r=0.99), TOC (r=0.97), Ca (r=0.97) for raw MLL (S1). For the rainfall-affected MLL, the concentration of NH3-N showed a perfect correlation of r=1 with T-Coli, E. coli, COD, BOD5, TDS and TS (S2). Similarly, the raw (S3) and rainfall-affected (S4) BLL showed positive but strong and perfect r values. However, very few parameters showed a weak correlation between negative and positive r values (S1–S4). The level of association among the measured parameters in this study was consistent with the studies conducted by Vahabian et al. (2019) and Sharma et al. (2020), where strong correlations were equally observed. The strong correlations observed for the contaminants imply that removing such contaminants needs technology to handle fixed contaminant loading, while the weak correlations for the contaminants imply that removing such contaminants from leachate needs technology that can handle variable contaminant loading. Therefore, the correlation matrix is fundamental in designing and selecting the best treatment options for the landfill leachate in terms of fixed and variable influent contaminant loading.

Leachate pollution index (LPI)

LPI is a metric used to evaluate the degree of leachate contamination potentiality in municipal landfill sites, signifying the effectiveness of certain pollutants before leachate treatment and management practices (Mor et al. 2018). In this study, LPI was calculated using field samples from MLL and BLL, including rainfall-affected leachates. LPI values of specific contaminant classes, including organics (LPIo), inorganics (LPIi), and heavy metals (LPIhm), have been estimated and expressed in terms of pollutant rating (wipi) in Table 4.

LPI – organic compounds (LPIo)

LPIo combines organic matter constituents, agricultural waste, and various synthetic organic components, including volatile organics, surfactants, insecticides, and pesticides used for agricultural purposes. Interestingly, there were about 18% and 29% reductions in LPIo values of the rainfall-affected leachate samples for MLL and BLL, respectively (Table 4). This considerable reduction in LPIo for both landfills was due to significant reductions in COD and BOD5 values in their respective leachates after the rainfall event (Table 1). The LPIo value for BLL was higher than for MLL before rainfall, which was linked to its higher fraction of organic waste (e.g., food waste) in solid waste (Figure 2).

LPI – inorganic compounds (LPIi)

The LPIi estimation was based on variations in pH values and the concentration levels of NH3-N, TKN, TDS, and Cl in both landfills, as clearly illustrated in Table 1. BLL showed a higher LPIi of 49.26 compared with MLL of 39.07 because the former received a higher proportion of food waste than the latter (Figure 2). The higher proportion of food waste contributed significantly to higher TDS and NH3-N concentrations, causing a higher LPIi value. However, the rainfall-affected LPIi values were found to be low for both MLL (33.43) and BLL (35.33). They were unaffected by other parameters (Zeng et al. 2013). Moreover, the leachate plume containing TDS and Cl could cause groundwater contamination and pose problems during biological treatments. Furthermore, the estimated LPIi could be used to assess the impact of inorganic components in landfill leachates.

LPI – heavy metals (LPIhm)

Similarly, LPIhm for various heavy metals and trace elements in leachates from both landfills was assessed to understand their contamination levels. LPIhm was estimated by considering highly toxic pollutants like Cr, Pb, Hg, As, CN, Zn, Ni, Cu, and Fe, as detailed in Table 4. Both MLL and BLL showed similar LPIhm values (Table 4) due to the similarities of inorganic compounds and synthetic materials present in the Multaqa landfill and Barka landfill. The similar LPIhm values of MLL and BLL could also be due to their similarities in the amount of metal waste (3% in Multaqa landfill vs 5% in Barka landfill) present in both landfills. After rainfall, a very high LPIhm value of 30.88 was recorded for BLL, which was unusual and could be attributed to the infiltration of nearby stormwater carrying a high amount of heavy metals and waste materials, thereby elevating the original metal levels in the leachates. However, it should be noted that although LPIhm has lower values than LPIo and LPIi, it can still cause severe environmental damage compared with the later ones due to their carcinogenic and non-degradable properties (ATSDR 2011).

Estimation of overall leachate pollutant index (LPIoverall)

The overall leachate pollution index (LPIoverall) was calculated by estimating individual sub-indices (pi) to the characterized pollutants in MLL and BLL (including rainfall-affected samples), using pi as reported by Kumar & Alappat (2005b). The pi values were multiplied with the significant weight (wi) of each pollutant, as described in Table 4 (Salami et al. 2015; Ofomola et al. 2017). The LPIoverall is estimated by the summation of sub-group LPI as derived from Equation (2). The study found that the LPIoverall was affected by rainfall events (Figure 5). The LPIoverall value decreased in the leachates due to rainfall in the Multaqa landfill, whereas the LPIoverall value in the Barka landfill leachates increased after rainfall (Figure 5). A significant increase in the LPIhm value after rainfall was mostly responsible for an increase in the LPIoverall value of BLL. On the other hand, LPIoverall reduction in the MLL was due to the dilution of leachates following a rainfall event.

Figure 5

Individual leachate pollution indices and the estimation of overall leachate pollution index for MLL, BLL and rainfall-affected (MRALL, BRALL) landfill leachates.

Figure 5

Individual leachate pollution indices and the estimation of overall leachate pollution index for MLL, BLL and rainfall-affected (MRALL, BRALL) landfill leachates.

Close modal

LPI values from this study can be used as indicators to assess the groundwater contamination potential of leachates generated within the domain of unlined landfill sites as the generated leachate could percolate into water bodies through soil (Ismail et al. 2015). Large LPI values consist of high ranges of COD, BOD5, heavy metals, and trace elements. It should be noted that the LPIoverall does not necessarily determine the degree of contamination of leachates but depends on the toxicity properties of individual contaminants. For example, this study recorded low values for LPIhm compared with LPIo and LPIi but could present higher contamination to aquatic ecosystems and human health than the latter (Boateng et al. 2019; Borjac et al. 2019). As shown in Table 6, a study in Malaysia reported an overall LPIoverall of 13.89 and 15.28 for leachates produced in closed and active landfills, respectively, which was significantly lower than that observed in the current study (Hussein et al. 2019). Interestingly, the rainfall-affected LPIoverall values from this study (Figure 5) were still higher than from many studies reported in the literature, especially in many developing countries (Arunbabu et al. 2017; Mishra et al. 2019; Parvin & Tareq 2021). However, the LPI values obtained for MLL before (LPIoverall = 26.63) and after rainfall (LPIoverall = 22.76) events were lower than the values reported by Rana et al. (2017) (LPIoverall = 27) and Arunbabu et al. (2017) (LPIoverall = 31). It should be noted that the LPI value was affected by several factors, including waste composition, age of the landfill and climatic condition (i.e., temperature, humidity, and rainfall levels). However, the LPI value from this study could be used as a guideline to modify landfill design to reduce the contamination potential of leachates generated in the future (Kumar & Alappat 2005a).

Table 6

Comparison of LPI values of current study with different international studies

LocationLandfill typeLPI valuesReferences
Ulu Maasop, Malaysia Active, 36 years old, rural area 15.28 Hussein et al. (2019)  
Kampung Keru, Malaysia Closed, 29 years old, urban area 13.89 Hussein et al. (2019)  
Kerala, India Active, urban 31.99 Arunbabu et al. (2017)  
Ramma, India Rural, active 15.62 Mishra et al. (2019)  
Mohali, India Urban 27 Rana et al. (2017)  
Hanoi, Vietnam Urban, active 24.7 Hoai et al. (2021)  
Warri, Nigeria Urban, active 6.37–7.43 Godwin & Oghenekohwiroro (2016)  
Mutuail, Bangladesh Active 19.81 Parvin & Tareq (2021)  
Current study: Active, urban   
BLL – 32.14  
BRALL – 35.40  
MLL – 26.63  
MRALL – 22.76  
LocationLandfill typeLPI valuesReferences
Ulu Maasop, Malaysia Active, 36 years old, rural area 15.28 Hussein et al. (2019)  
Kampung Keru, Malaysia Closed, 29 years old, urban area 13.89 Hussein et al. (2019)  
Kerala, India Active, urban 31.99 Arunbabu et al. (2017)  
Ramma, India Rural, active 15.62 Mishra et al. (2019)  
Mohali, India Urban 27 Rana et al. (2017)  
Hanoi, Vietnam Urban, active 24.7 Hoai et al. (2021)  
Warri, Nigeria Urban, active 6.37–7.43 Godwin & Oghenekohwiroro (2016)  
Mutuail, Bangladesh Active 19.81 Parvin & Tareq (2021)  
Current study: Active, urban   
BLL – 32.14  
BRALL – 35.40  
MLL – 26.63  
MRALL – 22.76  

The concentrations of different contaminants in the leachate and the atmospheric conditions should be considered to reduce the toxicity and hazard potential of generated leachates through suitable treatment options. Figure 6 illustrates the possible combinations or routes of treatment schemes for leachates produced under different atmospheric conditions (rainy and sunny). The rainfall-mixed leachate could be suitably treated using biological and adsorption techniques because of its low pollutant density and low toxicity. Young leachate is effectively treated by biological treatment. However, removing ammonia nitrogen from old leachate requires nitrification, denitrification, and a membrane filtration process (Mandal et al. 2017). Adsorption by granular activated carbon reported a significant removal of COD (90%) and heavy metals (80%–96%) (Alshameri et al. 2018). Therefore, the adsorption process can be suitable to treat young leachate after rainfall events following the necessary optimization. Instead of commercial adsorbents, natural clay minerals can be tested for diluted leachate to adsorb high concentration ammonium-nitrogen using a shorter contact time (Huang et al. 2018).

Figure 6

Possible routes for leachate treatment in different atmospheric conditions.

Figure 6

Possible routes for leachate treatment in different atmospheric conditions.

Close modal

In contrast, highly toxic leachate received on sunny days can be treated by advanced oxidation processes (AOPs) and membrane filtration. Also, advanced oxidation by hydrogen peroxide (H2O2) hydroxyl radical generation, ozonation (O3), and the integration of O3/H2O2 (Bokare & Choi 2014) has demonstrated a significant reduction of COD and organic matter by 50%–70% and 90%, respectively (Gandhi & Mok 2014). Moreover, ultraviolet, electron beam or photo-catalyst, Fenton and photo-Fenton processes have the potential to decontaminate pathogens from highly contaminated leachate (Maekawa et al. 2014; Qin et al. 2015; Hadjltaief et al. 2016). Membrane technologies, such as reverse osmosis, nanofiltration, ultrafiltration, and microfiltration, can also be applied for effective separation of environmental pollutants from concentrated leachates.

This study examined the leachate characteristics from two active landfills (MLL and BLL) from Muscat, Oman, including the effect of rainfall on the measured parameters. The study illustrated high ranges of organics, ammonia-nitrogen, ions, total phosphate, heavy metals, and trace elements. A significant reduction in these leachate parameters, especially in EC, BOD5, COD, and TOC, was observed due to the action of rainfall for both landfills. The most highly toxic heavy metals (Pb, Ni, Hg, As, and CN) were BDL, and their concentration variations due to rainfall were not linear. All solids analysis, especially for TDS, TSS and TVS, also decreased in value due to rainfall. However, the decrease among different solids was not linear. Contrastingly, the leachate's microbial (T-Coli and E. coli) levels were low before the rainfall but later elevated to high concentrations after the rain. More than 90% correlation data revealed the strong (positive and negative) association (r>0.75) among the measured parameters for both raw and rainfall-affected samples obtained from MLL and BLL. LPI values were assessed to understand the detrimental effects of the leachate contaminants on the aquatic ecosystem, soil biota, and public health. The study found significant reductions in LPI value for organic and inorganic contaminants for both landfills after rainfall. For heavy/trace metals, the LPI value generally remained unchanged or increased due to possible contamination from an outside source. The overall LPI values of the study were higher compared with other similar studies from the literature. These could be attributed to the unsegregated nature of the solid wastes from both landfills, resulting in new contaminants from the primary ones to increase the pollution index levels. Monitoring the LPI values can efficiently manage the landfills by reducing potential contamination and selecting appropriate leachate treatment options, thereby protecting groundwater and safeguarding public health.

None.

The authors wish to extend their appreciation to Sultan Qaboos University (SQU), Muscat, Oman, for the financial support through His Majesty's Trust Fund (SR/ENG/CAED/17/01) and The Research Council fund (RC/RG-ENG/CAED/19/01). SQU has granted scholarship support for PhD student.

All relevant data are included in the paper or its Supplementary Information.

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