Investigating combustion derived runoff from solid waste dumpyard fire suppression activities: chemical profile and environmental risks

Abstract

In many developing countries, increasing waste volumes are often dumped in unlined, poorly managed sites that are prone to frequent fires. Firefighting typically involves excessive water spraying, which produces large volumes of combustion derived runoff (CDR), a toxic liquid similar to landfill leachate. This runoff can severely pollute nearby ecosystems. This study presents the first comprehensive field assessment of CDR from a municipal solid waste (MSW) fire under tropical conditions. It combines ecotoxicological indicators, spatial modelling, and risk evaluation tools, based on the Brahmapuram dumpyard fire breakout in Southern India as a case study. This site, located in a tropical region, received about 400 m³ of water per day during the fire to suppress flames and smoke. While previous studies have focused on air emissions or general leachate, the environmental impact of CDR, particularly its flow into soil and water, has remained largely unexamined. This research fills that gap by analyzing fire residues, CDR, soil, sediment, and nearby surface and groundwater for contamination. Results showed that CDR had characteristics of stabilized landfill leachate, with low biodegradability (BOD : COD ratio is 0.11) and high toxicity, making it difficult to treat using conventional biological processes. Soils exposed to CDR had extreme heavy metal contamination, with a pollution load index over 100. The leachate pollution index was lower than those in past reports due to the dilution effect of water spraying. However, the overall mass of trace metals reaching downstream areas was higher due to the large CDR volume. Spatial mapping confirmed heavy metal enrichment in CDR affected zones. Leachability tests also suggested that up to 25% of metals in fire residues could percolate over time, posing serious long-term risks to soil and water. The study calls for immediate updates to fire suppression strategies, including engineered containment, environmental monitoring, and post-incident leachate management to reduce long-term ecological harm.

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Environmental significance

Frequent fires at poorly managed municipal solid waste (MSW) dumpsites in developing countries pose serious but often overlooked environmental risks. This study identifies an underrecognized pollution pathway from excessive water spraying during fire control, which generates large volumes of combustion derived runoff (CDR). This runoff carries harmful pollutants into nearby soil, surface water, and groundwater. While most research has focused on air pollution and general leachate, the role of CDR in spreading contaminants remains poorly understood, especially in tropical regions. Using spatial modelling, this study found dangerously high levels of heavy metals in CDR affected areas. The large volume of CDR also increased the total mass of trace metals reaching downstream ecosystems. Leaching tests further showed that heavy metals from fire residues could continue to seep into the environment over time, posing long-term risks. The study emphasizes the urgent need for improved fire management strategies, including fire retardant foams, ABC extinguisher powder (used for Class A, Class B, and Class C fires), infrared based early detection, groundwater monitoring, and proper dumpsite reclamation. Without such measures, current practices may worsen both immediate and long-term environmental and health hazards.

1 Introduction

Ineffective waste management and its environmental repercussions have emerged as critical global challenges in an era marked by exponential population growth and rapid industrial expansion. The world generates about 2.01 billion tonnes of Municipal Solid Waste (MSW) annually, and in 2020, the global share of uncontrolled MSW disposal was 38% (810 million tonnes).¹ As per the Waste Atlas Report, 42 of the world's 50 biggest uncontrolled dumpsites are situated in or near populated urban areas, directly impacting the public and environmental health of approximately 64 million people.² Dumpsites are prone to fires due to poor maintenance and operation, deliberate burning of waste, the disposal of undetected smoldering materials, and the generation of flammable Landfill Gases (LFG) and heat via chemical and biological reactions at the surface and subsurface of the landfills. Landfill fires are episodic in nature and are a significant global concern; the Bhalswa, Okhla, and Ghazipur landfills in India, Delhi, reported 69, 35, and 29 major fire incidents, respectively, during the period 2018 to 2019.³ In Poland, fire occurrences in the largest landfills increased from 4 in 2010 to 23 in 2018, reflecting a fivefold rise within the period.⁴ Similarly, as per the National Fire Incident Reporting System, the United States recorded approximately 839 unique landfill fire incidents in 2001 with approximately 3 to 8 million US$ property loss.^5,6 Burned waste contains residuals in the form of ash and slag with a higher concentration of heavy metals, persistent organic pollutants (POPs such as dioxins, furans, and PCBs), and other organic and inorganic pollutants.^7,8

During fire breakouts, large volumes of water are applied to burning heaps to extinguish the flames, leading to the formation of Combustion Derived Runoff (CDR). Compared to landfill sites in temperate, cold, and arid regions, those in tropical climates exhibit higher leachate production due to increased precipitation and humidity.⁹ In this context, recurring landfill fires and the generation of CDR augment the negative effects on surrounding ecosystems.¹⁰ The annual leachate generation estimated for the landfills in humid and semiarid areas was 0.1483 m³ and 0.0793 m³ per year per ton of waste, respectively.¹¹ However, during fire incidents, multiple firefighting trucks may dispense hundreds of cubic meters of water to quickly suppress the flames, resulting in a leachate production rate higher than usual. CDR could contain a cocktail of inorganic and or organic toxins, such as heavy metals, persistent organic pollutants, polycyclic aromatic hydrocarbons (PAHs), and transformation products from incomplete combustion, and its unchecked release can cause ecosystem damage and human health risks through bioaccumulation, ingestion, and dermal exposures.¹² Latest technology interventions, such as class A foam surfactants, ABC extinguisher powder,¹³ and infrared or thermal sensors for early fire detection, have demonstrated potential in reducing environmental damage during such unintentional fire breakouts. However, water continues to be the most widely used fire suppressant because of its high boiling point, ease of availability, and cost-effectiveness.

The existing literature on landfill fire accidents mainly studies its impact on regional air quality.^8,14,15 Further leachate assessment studies are based on static or seasonal assessments, which do not capture the transient but intense pollution burst triggered by firefighting runoff.¹⁶ For instance, Sanga et al. investigated heavy metal leaching from unlined landfills, revealing significant risks to groundwater quality.¹⁷ The minimum and maximum Leachate Pollution Index (LPI) values reported for non-engineered landfills in tropical countries like India, Nigeria, Sri Lanka and Malaysia ranged from 8.5 to 44.1, 16.9 to 23.5, 24.8 to 34.0 and 13.9 to 16.6, respectively.^18–20 These studies focused on normal dump conditions, where leachate volume and composition differ significantly from those during a dumpyard fire breakout incident. The CDR can be 10 to 100 times higher in volume, causing higher migration potential. This volumetric effect, leading to higher downstream contamination, has not been addressed in the previous studies and represents a critical gap. Moreover, fire dousing activities involve water percolating through waste layers containing semi-burned materials and residues, posing a greater contamination risk than the leachate seeping from compacted or partially compacted municipal solid waste (MSW) layers under typical conditions. This highlights the urgent need for a scientific study on CDR and its effect on receiving environmental compartments.

The present study comprehensively evaluated the impact of extensive water dousing on the quality of combustion derived runoff and the resulting chemical pollution in downstream environmental compartments, including surface soil, sediment, surface water, and groundwater. The corresponding samples were collected after an accidental fire at a municipal solid waste (MSW) dumpyard at Brahmapuram, Kerala, India, located in a tropical climate zone. The massive fire accident that lasted for 12 to 13 days at the dumpyard is expected to cause huge land emissions of various organic and inorganic pollutants. Additionally, tropical climatic factors such as higher precipitation can exacerbate the leachate pollution at the site during monsoon seasons, which indicates that it is high time to establish baseline levels from such activities for potential long-term effect verification. Systematic onsite sampling was conducted in the fire incidental zone, followed by environmental level elucidation and statistical evaluation of environmental risk. The site was chosen based on the observations that CDR generated from this dumpyard has every possibility to percolate to the nearby ecologically sensitive zone, which included two river stretches (Kadambrayar and Chitra River) and a marshy land. The environmental risk in the region was estimated through various statistical indices such as the Leachate Pollution Index (LPI), Geoaccumulation Index (Igeo), Enrichment Factors (EF), and Pollution Load Index (PLI).^21,22 The Toxicity Characteristic Leaching Procedure (TCLP) and spatial models were used to predict future enrichment and dispersion patterns at the site, shedding light on the previously unexplored impact of dumpyard fires on hydro and lithospheric environments. This study aims to quantify the chemical characteristics and ecological risks of combustion derived runoff following landfill fire suppression in a tropical urban dumpyard, using spatial modelling and pollution indices to assess downstream contamination.

2 Materials and methods

2.1 Study area

The Brahmapuram MSW dumping site (9° 59′ 28′′ N, 76° 21′ 59′′ E) is located in the low-lying flood-prone catchment area of the river Kadambrayar and in close proximity to the Chitrapuzha in Kochi, the commercial capital of Kerala, India. Kerala experiences a humid tropical monsoon climate characterised by two principal rainfall seasons, the southwest monsoon (June to September) and the northeast monsoon (October to December), with annual rainfall exceeding 3000 mm.²³ Kochi, a coastal city on the western shore of India along the Arabian Sea, has a population that relies heavily on fish as a staple food.²⁴ Fishing communities also live near the Kadambra and Chithra rivers, where regular fishing activities take place. The region is covered with coastal alluvial soil of sandy texture with good porosity and permeability. These seasonal rainfall trends, combined with soil permeability and hydrological connectivity, significantly increase the potential of leachate generation and risk of downstream contamination.²⁵ In Brahmapuram, about 8.43 lakh tonnes of legacy waste were dumped in about 60 to 65 acres of land area, awaiting reclamation, about 17 Km from the city. Multiple fire accidents were reported in the legacy waste piles from 2010 onwards.⁸ The present study was carried out during a major fire accident that occurred at the dumpyard in March 2023, during the summer season. Comprehensive sampling was conducted between March and April, after the fire at the site had been fully extinguished. The site location and demarcated fire accident zone are shown in Fig. 1.

Fig. 1 Study area with sampling points.

2.2 Sample collection

2.2.1 Surface soil and MSW. Soil mixed with burned residues was sampled from the fire-hit area at the dumpyard as per the soil sampling and method of analysis by the Canadian Society of Soil Science.²⁶ A walk-through survey was conducted in the fire accident zone and marked the boundaries using a handheld GPS (Global Positioning System) unit. Further, the fire accident zone was divided into 20 100 m × 100 m spatial grids, of which samples were collected from 10 random grids to capture a range of burn intensities and variability in waste deposition across the site. For a stratified sampling, the selected grids were further divided into four 50 m × 50 m grids, and 2 grabs from each of the grids using the front loader Hitachi were sampled for composition analysis. Thus, a total of 80 representative samples were collected from the 10 selected grids for the composition analysis study. The compositional analysis of the samples was conducted at the site through manual segregation methods into six classes (Fig. 2(a)). Further, the samples were mixed in a relatively clean space, and through the coning and quartering method, about 20 kg was collected and brought to the laboratory for further analysis. They were reduced to 1 to 3 mm in size and grounded using mortar and pestle for Toxicity Characteristic Leaching Procedure (TCLP) studies.

Fig. 2 (a) Change in MSW compositions between prefire and postfire scenarios; (b) comparative composition of MSW in various Indian dumpyards.

Surface soil samples were also sampled from respective grids through the coning and quartering method and were sealed in a zip-lock cover for transportation and analysis. Fig. 1 shows the surface soil sampling locations in the Brahmapuram MSW dumpyard. The control point was situated at a playground area, with no open burning/dumping activity reported to the best of our knowledge (site locations given in Table S1). Samples were sundried, crushed with a clean mortar and pestle, homogenized and sieved (<2 mm), and then kept in airtight bags for further analysis.

2.2.2 Leachate, sediment, surface water, and groundwater. The sample was collected 2 weeks after complete fire suppression at the site. Two leachate streams were present in the dumpyard. The CDR samples were collected from both streams. Approx. 500 mL to 1 L of the sample was collected from 4 spots of each leachate stream and mixed to get two representative samples (CDR1 and CDR2). A total of four surface water samples were collected from a nearby surface water source (Kadambrayar). Out of these, three samples were collected along a 2 km downstream stretch of Kadambrayar (SW1, SW2, SW3), and another sample was collected from the upstream location (SW4). Groundwater sampling followed the Central Public Health and Environmental Engineering Organisation guidelines.²⁷ Four groundwater samples were collected: two from the downstream locations, one from the upstream location, and one from within the dumpyard site. Sediment samples were collected from 10 spots in the adjacent Kadambrayar along the 2 km stretch in the downstream direction. Bottom sediment grab samplers were used to collect the samples. The sampling spots were geospatially marked and are presented in Fig. 1. The sediment control sample was collected from the Kadambrayar approx. 1 km upstream of the Brahmapuram dumpyard. All the samples were stored at 4 °C till the analysis.

2.3 Laboratory analysis/analytical methods

Analysis was conducted at the NABL-accredited laboratory as per ISO/IEC 17025:2017 at CSIR-National Institute for Interdisciplinary Science and Technology, Thiruvananthapuram, Kerala, India. The detailed quality assurance and quality control (QA/QC) procedures implemented in the laboratory are outlined in the supplementary information. The physicochemical properties of the water and soil samples collected were analyzed as per standard methods in an ISO/IEC 17025:2017 accredited laboratory.^26,28 The pH (Eutech pH 2700), electrical conductivity, Salinity, and resistivity were measured using electrodes procured from HANNA (Model: HI5521). The turbidity of the water samples was measured using a nephelometric turbidity meter (Oakton). The total dissolved and suspended solids of the samples were analyzed gravimetrically. Sodium and Potassium concentrations in the collected samples were determined using a Flame photometer (Systronics Flame photometer 128). The chemical oxygen demand (COD) and biological oxygen demand (BOD) were determined using the dichromate oxidation method and a 5-day BOD test. The color and sulfate content were analyzed using spectrophotometric and turbidimetric methods using a spectrophotometer (UV 1800, Shimadzu). The samples for TKN were determined using a Kjeldahl analyzer (Behrotest S2 distiller, Behrotest Kjeldahl digestion unit, Behr Labor Technik, Germany). The total organic carbon (TOC), total carbon (TC), and total Nitrogen (TN) content of the samples were analyzed using a TOC analyzer ((Analytikjena multiN/C 3100). The phenol and nitrate contents were quantified using a continuous flow analyzer (SAN++^® Series continuous flow analyzer). The trace metals in the samples were analyzed with ICP MS (iCAP Qc, Thermo Scientific, USA).

2.4 Environmental risk assessment

2.4.1 Enrichment factor (EF). The enrichment factor was used to measure the expected impact of emission activities using metal concentration in soils/sediments. EF assesses the degree of enrichment and compares the contamination of different environmental media against a stable reference element. In this study, aluminium (Al) was used as GB (Geochemical Background) because of its geochemical stability, characterized by the absence of vertical mobility and/or degradation phenomena.²⁹ The enrichment factor was calculated by:

EF = (Metal/RE)_sample/(Metal/RE)_background (1)

where RE is the value of the metal, taken as the reference element, EF < 1 indicates no enrichment, EF < 3 is minor enrichment, EF = 3 to 5 is moderate enrichment, EF = 5 to 10 is moderately severe enrichment, EF = 10 to 25 is severe enrichment, EF = 25 to 50 is very severe enrichment, and EF > 50 is extremely severe enrichment.³⁰

2.4.2 Geo-accumulation index. The Geo-accumulation Index (Igeo), introduced by Muller in 1969, allows the assessment of soil/sediment contamination by comparing the current level with background levels.³¹

C _n is the concentration of the individual metal n, B_n is the Geochemical Background (GB) concentration value of the element n, and 1.5 is the background matrix correction factor included to correct possible background value variations due to natural processes. According to Muller, the Igeo for metal is classified as follows: uncontaminated (Igeo ≤ 0) (Class 0); uncontaminated to moderately contaminated (0 < Igeo ≤ 1 (Class 1); moderately contaminated (1 < Igeo ≤ 2) (Class 2); moderately to heavily contaminated 2 < Igeo ≤ 3) (Class 3); heavily contaminated (3 < Igeo ≤ 4) (Class 4); heavily to extremely contaminated (4 < Igeo ≤ 5) (Class 5); and extremely contaminated (Igeo ≥ 5) (Class 6).³¹

2.4.3 Pollution load index (PLI). The pollution load index (PLI) proposed by Tomlinson, an integrated index where the contamination status of all metals is expressed in one index, was used to determine the pollution status of metals in the soil at the site.³² It provides a cumulative indication of pollution caused by metals at sites. The PLI was obtained through the contamination factor (CF) of each heavy metal with respect to the background value. This parameter is expressed as:

CF is the contamination factor, and n is the number of metals. C_metal is the concentration of metals in soils/sediments, and C₀ is the concentration of metals in the reference material. CF < 1 indicates low contamination, 1 < CF < 3 moderate contamination, 3 < CF < 6 considerable contamination, and CF > 6 very high contamination.³³ The pollution load index is classified as no pollution (PLI < 1), moderate pollution (1 < PLI < 2), heavy pollution (2 < PLI < 3), and extremely heavy pollution (3 < PLI).

2.4.4 Leachate pollution index (LPI). The Leachate Pollution Index was used to quantify the contamination potential of the CDR. LPI was calculated as per the procedure given by Kumar and Alappat.²² 16 parameters were used for the estimation of LPI and were calculated using the equation:where W_i = the weight for the ith pollutant variable. P_i = the subindex value of the ith leachate pollutant variable, N = number of leachate pollutant variables used in calculating LPI.

2.5 Toxicity characteristics leaching procedure (TCLP)

USEPA Method 1311 was followed for the TCLP analysis.³⁴ The pH of the waste was observed to be 6.95, so extraction fluid 1 (a solution of glacial acetic acid and sodium hydroxide) was used as the charging fluid for the extraction procedure. The amount of extraction fluid added was determined using the following equation.

The mixture was placed in a 1 L extraction bottle and rotated at 30 rpm for 18 hours. Following extraction, the liquid extract was separated from the solid phase using vacuum filtration through a 0.8 μm glass fiber filter. The trace metal contents in the solutions were determined using ICP MS.

2.6 Statistical and geospatial analysis

GraphPad (version 10.2) was used for the statistical analysis and visualization of the results, and ArcMap (10.7) software was used for the spatial distribution mapping using the inverse distance weighted (IDW) interpolation technique. Spearman's correlation matrix was plotted to determine the associations among the trace metals of MSW, leachate, soil, and surface water samples. Additionally, the enrichment of trace metals in the soil and sediment samples around the dumpyard area was elucidated using a heatmap.

3 Results and discussion

3.1 MSW composition and surface soil contaminant levels

The results of the composition analysis of the MSW sample collected from the Brahmapuram dumpsite after the fire was extinguished are given in Fig. 2(a). Following the fire, there was a significant reduction in the biodegradable and paper fractions compared to the pre-fire MSW composition.³⁵ The pre-fire composition showed that paper contributed to 21.3% of the total waste. However, post-fire analysis showed a sharp decrease to 4.2%, indicating the high flammability of paper, which burns easily during fire breakout scenarios, while the proportion of ash and textiles increased. While plastic content in the total waste remained relatively unchanged, this was likely due to the partial burning of plastics and the persistence of melted plastic residues. The primary sources of plastic waste at the dumpsite were domestic as well as commercial disposals, predominantly comprising food packaging, bottles, and poly bags. Thin plastics, widely used in food and grocery packaging, were more prevalent than plastic containers, which should have contributed to the site's high flammability during the fire. The thermal degradation behavior of plastics follows a distinct pathway depending upon the physical and chemical composition. They primarily follow polymeric chain scission, side group reaction, and recombination degradation mechanisms. In the current scenario, the plastic waste was highly heterogeneous, consisting of a mixture of polyethylene terephthalate (PET), high-density polyethylene (HDPE), low-density polyethylene (LDPE), polystyrene, and various foreign materials. Such heterogeneity reduces the likelihood of a common degradation pathway, leading to greater residue formation. Additionally, the mixed composition causes a broader degradation range compared to individual plastics, while higher heating rates further increase residue by accelerating dissociation within a shorter reaction time.^36,37

Post fire textile waste consisted mostly of synthetic rather than natural fibers, sourced mainly from household items like clothing. Synthetic textiles tend to melt rather than burn completely, leaving solid residues that increase their relative presence in the waste. Additionally, leather, which is fire-resistant due to its dense structure and chemical treatments, remained largely unburned, further increasing its proportion. With the loss of combustible materials like paper and organics, the relative percentage of textiles, leather, and ash showed a rising trend. The miscellaneous fraction of the waste increased by 2818%. In the pre-fire, the miscellaneous fraction primarily included soil, construction, and demolition waste. However, in the post fire scenario, the accumulation of burned residues, unclassified debris, and ash resulted in this sharp rise. To understand broader trends, the study also compared the MSW composition of Brahmapuram with typical compositions from five zones of India (East, West, South, North, and Central India), as shown in Fig. 2(b). Generally, Indian (tropical) dumpyards contain a higher proportion of organic waste and inert materials, including soil, stones, and construction and demolition debris. This pattern was more aligned with the pre-fire composition at Brahmapuram.^38–43

The general soil characteristics of the collected samples are given in Table S2. The pH values of the samples ranged from 6.29 to 6.93, the conductivity levels of the samples varied between 0.91 and 3.17 mS cm⁻¹, and the moisture content of the samples was observed to be in the range of 24.2 to 41.9%. Salinity measurements spanned from 0.44 to 1.63 PSU. Regarding chloride concentration, the analysis generated a range of 56.8 to 511.2 mg L⁻¹. Total Kjeldahl Nitrogen (TKN) content in soil ranged from 1.01 to 14 g kg⁻¹, while COD (Chemical Oxygen Demand) values varied between 304.5 and 571.4 mg L⁻¹. The pH values were slightly lower than the previously reported values at the site (non-fire conditions).⁴⁴ The penetration of CDR, which contains dissolved organic acids, could be the reason for the relatively lower pH value.⁴⁵ The lower pH values can accelerate the mobilization of toxins to other environmental compartments. The salinity buildup, high nitrogen content, and COD levels are likely due to the dissolved salts and decomposition of nitrogen-rich substances, such as amino acids and proteins, in municipal solid waste. During microbial metabolism, organic nitrogen is converted into inorganic forms, contributing to elevated nitrogen levels in landfills.⁴⁶ The subsequent leaching of these compounds to nearby surface water sources via CDR could accelerate eutrophication, algal bloom formation, and DO level depletion.

Ministry of Environment, Forest and Climate Change, Govt of India issued soil screening levels for heavy metals were used to compare the site observed levels.⁴⁷ The observed concentrations were in the order of Zn > Co > Cr > Pb > V > Ni > Se > Cd > As (Table S3). Of the analyzed heavy metals, cadmium (1 to 5 times), lead (1.1 to 2 times), copper (18 to 70 times), zinc (up to 80 times), chromium (12 to 45 times), nickel (4 to 11 times), vanadium (2 to 6 times), selenium (22 to 52 times), and arsenic (2.5 to 6 times) had surpassed permissible limits. The higher levels of heavy metals were in tandem with previous studies reported from dumpyard soils.⁴⁸ The higher levels of metals in the dumpyard can be attributed to the indiscriminate dumping of heterogeneous waste, which contains different types of plastics, electronic wastes, food additives/preservatives, etc. Heavy metal contamination in soil can adversely affect the microorganisms residing in the soil, degrading the soil quality and also increasing the risk of groundwater contamination.⁴⁹ Moreover, high enrichment of heavy metals can also induce phytotoxicity and physiological stress in plants, and contribute to biomagnification, causing long-term ecological and human health risks.⁵⁰ The specific source identification of the trace metals was also attempted through group establishment based on correlation analysis and is discussed in Section 3.4.

3.2 CDR characteristics

Table S4 summarises the characteristics of CDR (CDR1 and CDR2) collected from the MSW dumpyard. The analysis was conducted in triplicate, in which the data presented is the average of each analyzed sample and was compared with the solid waste management rules, 2016 specified maximum levels for effluents that can be discharged into inland surface waters.⁵¹ The pH values recorded for the CDR (7.33 to 7.62) samples were within the standard range of 5.5 to 9. Among the studied parameters, suspended solids, total dissolved solids, BOD, COD, and TKN levels exceeded the acceptable maximum. BOD and COD values previously reported for the leachate samples were high, of the order 39 500 mg L⁻¹ and 57 300 mg L⁻¹, respectively.⁵²

The TDS and chloride values observed for CDR were about 4 times lower than the previously reported values of 14 490 mg L⁻¹ and 3010 mg L⁻¹, respectively. Similarly, the TKN was found to be about 50 times lower than the previously reported value of 6160 mg L⁻¹ under non-fire conditions.⁵² The BOD/COD ratio of the leachate is considered an indicator of biodegradability, and a high ratio indicates that the biological processes are more viable for treating the leachate.⁵² Previous studies at the Brahmapuram dumpyard reported BOD/COD ratios (biodegradability index) of 0.55 and 0.69, which lie in the biodegradable zone, suggesting that the leachate collected could be treated biologically.^52,53 However, the BOD/COD ratio in the present study was found to be 0.11, indicating relatively low biodegradability. Hence, the CDR was observed to be unsuitable for biological treatment due to its low biodegradability and toxic nature, which can inhibit microbial activity. The BOD/COD ratio decreases as the landfill ages and hence reflects the landfill maturity as well. A ratio ≤0.1 indicates that the leachate contains predominantly nonbiodegradable organic compounds.⁵⁴

In the study by Arunbabu et al., they reported the concentrations of heavy metals such as As (0.06 mg L⁻¹), Cr (0.13 mg L⁻¹), Fe (60.9 mg L⁻¹), Ni (0.531 mg L⁻¹), Pb (0.08 mg L⁻¹), Cu (0.18 mg L⁻¹), Zn (0.273 mg L⁻¹), and Hg (0.005 mg L⁻¹).⁵² In contrast, the concentrations observed in the present study were markedly lower by several orders such as arsenic at 0.001 mg L⁻¹ (60 times), chromium at 0.003 mg L⁻¹ (43 times), iron at 0.62 mg L⁻¹ (98 times), and nickel at 0.01 mg L⁻¹ (53 times). Furthermore, none of the measured heavy metals exceeded the permissible discharge limits set under the Solid Waste Management Rules (SWM, 2016)⁵¹ (Table S5). This significant reduction in concentration can likely be attributed to the dilution effect caused by intermittent water pumping during the fire suppression efforts. However, despite lower concentrations, the total pollutant load discharged into the environment increased due to the sheer volume of water used. This highlights an important yet overlooked issue: long-term environmental risk is influenced not only by pollutant concentrations but also by cumulative discharge rates. Developing a long-term sediment load index could help present this concern more effectively to scientific and regulatory agencies.

3.3 Contaminant levels in surface water, groundwater, and riverine sediments

3.3.1 Physicochemical characteristics of surface and groundwater. Assessing surface and groundwater quality is essential for understanding the environmental impact of contamination, particularly in the areas affected by open dumping. The presence of pollutants in water bodies can have significant ecotoxicological implications, necessitating thorough monitoring and regulatory compliance. In this study, the observed levels of physicochemical parameters and heavy metals of surface water samples were compared with CPCB's Water Quality Standards for Coastal Water marine outfalls⁵⁵ and are presented in Tables S4 and S5. A localized spike in BOD (450 mg L⁻¹), COD (2009.6 mg L⁻¹), fluoride (2.84 mg L⁻¹), and chloride (241.4 mg L⁻¹) near the fire accident site can be noticed. Elevated COD or BOD levels increase the aquatic oxygen demand, and the reduced oxygen levels can create hypoxic or anoxic conditions, leading to microbial stress that can shift the microbial population towards more anaerobic species. These conditions can have a significant negative impact on the fish population in the region, leading to habitat loss.^56,57 Although these levels remained below the permissible limits set by regulatory agencies, the CDR significantly impacted water quality and can act as a potential human exposure pathway. The high flow rate of the river likely diluted the contaminants to lower concentrations. However, this remains a concern for bioaccumulative pollutants, such as heavy metals, which can persist in aquatic ecosystems and can lead to human health impacts through ingestion.

The turbidity of surface water samples collected from the Kadambrayar by Robert et al. ranged from a minimum of 21.1 NTU to a maximum of 22.9 NTU.⁵³ In the present study, turbidity levels at four river sampling sites following the landfill fire were about 12 times higher than the previously reported maximum, highlighting the influence of the CDR. To further assess water quality trends, BOD data from the Central Pollution Control Board's (CPCB) regulatory monitoring reports were analyzed (NWMP Water quality data).⁵⁸ Between 2016 and 2022, the maximum recorded BOD levels in the Brahmapuram region of the Kadambrayar ranged from 2.9 to 6.7 mg L⁻¹. However, in this study, BOD levels showed a substantial increase, with minimum and maximum recorded values of 10 and 450 mg L⁻¹, respectively, near the CDR receiving area (Fig. 3). These findings underscore the urgent need for effective leachate management at the fire-affected site to prevent further contamination.

Fig. 3 Comparison of typical BOD levels in the Kadambrayar in the Brahmapuram region (2016 to 2022) with the values recorded after the dumpyard fire outbreak.

The results of the groundwater samples (GW1, GW1 DS, GW2 DS, and GW2 US) analyzed are summarised in Table S4. The observed levels were compared with the Indian Standard Drinking Water specifications, IS:10 500.⁵⁹ It was observed that the peculiar spikes in physicochemical parameters were not present in the groundwater samples analyzed. However, the samples were collected during the fire incident, and the percolation of leachates into underground layers is a slow process. Similar observations have been reported in the studies conducted elsewhere, around the dumpyards, where groundwater sources were not found to be severely contaminated.^60,61 Therefore, long term monitoring could identify any such spike and contribute to exposure risk mitigation.

3.3.2 Trace metal levels in surface and groundwater. The observed levels of trace metals in surface water and groundwater samples are presented in Table S5. As per the Central Pollution Control Board of India (CPCB) guidelines, acceptable levels were laid down only for three heavy metals – Cd (0.01 mg L⁻¹), Hg (0.01 mg L⁻¹), and Pb (0.01 mg L⁻¹) for surface water samples.⁵⁵ Cd and Pb were observed to be lower than the acceptable limit. However, Hg was observed to be above acceptable levels in all the samples analyzed, including the control sample. Moreover, at SW3, the Hg level was nearly twice as high as that observed at other sampling points, indicating that the CDR significantly contributed to Hg contamination in the river downstream. Siby and Jayamohan reported that heavy metal concentrations of the groundwater collected from the nearer sites in the dumpyard were Cu (0.22 mg L⁻¹ to 0.478 mg L⁻¹), Mn (0.14 to 2.36 mg L⁻¹), Cd (0.010 to 0.014), Ni (0.03 to 0.15 mg L⁻¹), Pb (0.01 mg L⁻¹), and Cr (0.03 mg L⁻¹), respectively.⁴⁴ In the present study, the mercury levels in the surface water samples ranged from 20 to 60 μg L⁻¹, while in groundwater it was below the LOQ. The observed levels of heavy metals in groundwater samples were also lower than the maximum permissible levels by IS:10 500, 2012 and WHO guidelines, indicating low/no disturbance to the groundwater compartment in the region by CDR.^59,62 The sampling points taken by the previous study were not geotagged in the paper and are, hence, not able to correlate with the current study observations. To further understand whether the downstream environmental levels will increase with time, leachable levels of trace metals in the legacy MSW were also analyzed and discussed in Section 3.6.

3.3.3 Sediment quality assessment. As a long-term pollutant repository, sediment can facilitate the persistence and transport of toxicants, which over time may have an impact on aquatic life, human health, and water quality. The sediment quality parameters from the dumpyard region are summarized in Table S6. A significantly higher accumulation of trace elements such as As, Pb, Cr, Cd, and Cu than in previously reported studies in the bottom sediments of Kadambrayar river near the Brahmapuram dumpyard can be noticed. As levels ranged from 81.5 to 201.5 mg kg⁻¹, about 25 times higher than the previously reported maximum concentration of 7.49 mg kg⁻¹.⁵³ Similarly, Pb concentrations (83.0 to 160.6 mg kg⁻¹) were nearly four times the previous maximum of 32.6 mg kg⁻¹.⁵³ Cr levels (1093.5 to 2737.6 mg kg⁻¹) far exceeded the earlier maximum of 205.5 mg kg⁻¹. Cd (1.7 to 128.9 mg kg⁻¹) and Cu levels (217.3 to 1080.2 mg kg⁻¹) were also significantly elevated compared to their previous maxima of 0.29 mg kg⁻¹ and 56.04 mg kg⁻¹, respectively. Additionally, unlike previous reports, Ni, V, Zn, Se, Co, Al, Fe, and Hg were detected at very high levels at the site, suggesting a significant influence from CDR. The average trace metal concentrations followed the order: Fe > Al > Ba > Zn > Cr > V > Ni > Cu > Se > As > Co > Pb > Cd > Ag > Hg. Further, the chloride, TKN, and COD values of the studied samples were also significantly high in the downstream locations of the fire accident zone. The combustion of MSW can result in the release of organic pollutants into the environment, leading to the accumulation of soluble organic compounds in CDR, and should have contributed to the increased COD levels in the sediment samples analyzed.^12,35

3.4 Correlation analysis

The Spearman rank correlation matrix was constructed for two groups of observed levels between the trace metal concentrations observed in different environmental matrices to identify group abundances (Table S7) and between trace metal patterns observed in different matrices to find the movement of trace metals at the site (Table S8). The strong positive correlations (r > 0.7) observed among toxic metals indicate common sources and environmental mobility or leachate infiltration to other environmental strata.⁶³ Significant positive correlations were observed between Pb and Cr (r = 0.83, p < 0.01), Ni (0.90, p < 0.01), and Ba (r = 0.82, p < 0.01), suggesting a common source relation to discarded electronics or batteries.⁶⁴ The r values between the trace metal patterns in different environmental compartments indicated that MSW, leachate, and soil samples were strongly correlated (r > 0.8, p < 0.01) with each other, implying that CDR has critical effects on trace metal movement across these compartments through leaching and runoff. Further, the surface water sample pattern did not have a significant correlation with MSW, soil, and CDR, possibly due to higher dilution rates and background levels.

3.5 Environmental risk assessment

3.5.1 Enrichment factor (EF) and geo-accumulation index (Igeo). Assessing metal contamination in soil and sediment is crucial for understanding the extent of environmental pollution and its potential risks. Open dumpsites can act as major sources of pollution, facilitating the accumulation and dispersal of toxic metals in soil and sediment through leachate infiltration and surface runoff. The geo-accumulation index (Igeo) and the enrichment factor (EF) provide valuable insights into the degree of contamination and the anthropogenic contributions from waste disposal activities. Fig. 4 represents the enrichment of trace metals in the collected soil and sediment samples around the dumpsites. The results indicated moderate to significant enrichment of metals, including Cd, Cr, Co, Pb, Ag, Ni, Cu, Zn, As, and Hg in sediments and significant enrichment in soil at the site. The geo-accumulation index (Igeo) classified Cd contamination in sediment samples as ranging from heavily to extremely contaminated, particularly in downstream locations of the dumpyard. The sample taken from the upstream location of the dumpyard remains uncontaminated, indicating the role of open dumpyards and CDR in polluting the surrounding ecosystem. Furthermore, the enrichment factor (EF) for Cd in sediment samples ranged from 3.63 to 41.50, indicating moderate to very high enrichment in downstream areas.

Fig. 4 Heat map of trace metal enrichment in soil and sediment samples collected from the Brahmapuram dumpyard.

In soil samples, the severity of cadmium (Cd) contamination was even greater, with concentrations significantly surpassing the background level (Bn) of 0.001 mg kg⁻¹ across all samples. The soil samples collected from the fire accident zones displayed EF values significantly greater than 40 for the metals cadmium (Cd), copper (Cu), silver (Ag), and zinc (Zn) and hence classified them as areas with extremely high enrichment. Furthermore, the enrichment factor (EF) for Cd is remarkably higher (>100) in all ten grids of fire accident sites, which is far above acceptable thresholds and represents an immediate concern due to its toxicity and environmental persistence. The geo-accumulation index (Igeo) for all the analyzed metals in the soil samples was notably higher than 5, categorizing them as extremely contaminated. Other heavy metals, including chromium (Cr), lead (Pb), nickel (Ni), arsenic (As), and mercury (Hg), exhibited widespread contamination, with Igeo values ranging from 7.06 to 10.63, further emphasizing the critical contamination status of the area. The previous studies reported that if the EF value is higher than 2, it is a clear indication of critical anthropogenic sources towards heavy metal pollution in a particular region.⁶⁵ This is found to be true in the present study as well. Both essential elements Cu (16.5 to 95.9), Zn (27.8 to 81.1), and Fe (1.3 to 2.4) and nonessential elements Cd (100.9 to 626.9), Cr (2.7 to 12.9), Pb (3.5 to 11.7), As (1.9 to 2.7), and Hg (6.9 to 15.8) showed much higher enrichment in the studied samples. The higher EF of Pb can be attributed to batteries, welding activities, sewage effluents, non-ferrous industries, and runoff waste materials, Cd to paints, plastics, glass, and ceramics waste, and Cr to electroplating, tanning, or other industry wastes in the dumpsite.^66–68

The Inverse Distance Weighting (IDW) interpolation method in the geospatial analysis was used to spatially model and predict the concentration levels of various trace metals in soil and sediment samples from the study area (Fig. 5). The resulting interpolated maps effectively illustrated the spatial variation in contamination, which aided visual analysis. The analysis revealed that contamination hotspots originate near the dumpyard and spread along the slope in the direction of CDR flow, eventually reaching the nearby river. Johar et al. reported that around the Bhalaswa landfill site, Delhi, there was heavy metal contamination up to a distance of 500 m from the landfill, and the contamination status decreased with distance from the landfill.⁶⁹ Similarly, Njagi et al. observed heavy metal concentrations in soil and water samples collected from the Kadhodeki dumpsite in Kenya, which were higher at the dumpsite and decreased away from the dumpsite.⁷⁰ In the present study, the downstream areas of the river exhibited much higher contamination than upstream locations, indicating the dispersal of pollutants from the dumpyard into nearby ecosystems. However, contamination levels decrease with distance, primarily due to dilution at the river bank. Despite this dilution effect, long-term accumulation remains a concern, necessitating continuous monitoring until complete site reclamation is achieved.

Fig. 5 Spatial distribution of the geo-accumulation index of trace metals in the dumpyard area.

3.5.2 Priority remediation zones for targeted interventions. The spatial assessment of heavy metal contamination involved a multi-step methodology utilizing geostatistical techniques within a Geographic Information System (GIS) environment. Initially, enrichment factor (EF) and geo-accumulation index (Igeo) values were calculated for each heavy metal at every sampled site around the Brahmapuram waste dumpyard. To derive continuous spatial representations, individual EF and Igeo values for each metal were interpolated across the study area, generating high resolution raster surfaces. To establish an overarching contamination risk, a “worst case scenario” approach was adopted: for each grid cell, the maximum EF and maximum Igeo values across all heavy metals were identified, resulting in a composite “Maximum EF” and “Maximum Igeo” raster. These maximum rasters were then used in the raster calculator to classify priority zones based on predefined thresholds: grid cells with a maximum EF > 50 and maximum Igeo > 5 were designated as “Hotspots”; areas with intermediate values (e.g., maximum EF > 10 and maximum Igeo > 1) were classified as “Medium Priority Zones”; and all remaining areas were categorized as “Low Priority Zones.” This analysis revealed that the “Hotspot” zone, covering an area of 0.681 square kilometers, extends approximately 1.5 kilometers from the waste dumpyard. The “Medium Priority” and “Low Priority” zones covered areas of 0.405 square kilometers and 0.007 square kilometers, respectively. The resulting categorical raster was finally converted into polygon features to facilitate clear thematic mapping and spatial analysis of contamination zones in ArcMap (Fig. 6). To mitigate further environmental impact, it is recommended that the highly contaminated soils be excavated and encapsulated in landfills to prevent further leaching. The medium priority zones can utilize phytoremediation/bioremediation to stabilize the metals.

Fig. 6 Heavy metal contamination priority zones and hotspot delineation around the brahmapuram waste dumpyard.

3.5.3 Pollution load index. The pollution load index simplifies the pollution data of an area into a single value, providing insight into the temporal distribution of metal pollution in soil and sediment samples.⁷¹ PLI values demonstrated severe contamination in the soil samples, with PLI > 5 signifying high levels of toxic metals. Tables S9 and S10 present the CF and PLI results. A contamination factor greater than 6 indicates extremely high pollution; here, the CF values of the calculated heavy metals like Cr, Ni, As, Cd, Hg, and Pb in soil samples have far exceeded the value. This highlights the severe pollution caused by these toxic metals at the site. The pollution load index of the trace metals in the soil samples was higher than in the sediment samples. In the case of sediment samples, all metals except Cd were < 6, indicating moderate contamination of these metals. The CF value of Cd is 63.8 at site 3, which denotes very high contamination. The PLI of sediment samples indicated that the studied area has a moderate pollution status, considering all the studied metals except cadmium. However, in the case of soil samples, the PLI value is >100 in all studied areas, indicating a high level of overall contamination. The value suggests that the soil is significantly impacted by pollutants and requires an immediate remediation mechanism.

3.5.4 Leachate pollution index. To estimate the leachate pollution ability in the Brahmapuram dumpyard region, the LPI value was calculated for the CDR samples using the method developed by Kumar and Alappat.²² The physicochemical characteristics of leachate, along with the parameters used for the calculation of LPI, such as pollutant weight factor (w_i) and subindex value (p_i), are given in Table 1. The CDR is characterized by high concentrations of TDS, TKN, COD, and BOD. After the fire breakout, the calculated LPI is 9.27 for the Brahmapuram dumpyard. This indicates that the leachate generated during the fire management activities of the dumpyard can contaminate the other environmental compartments within the plant vicinity, especially due to the absence of a proper liner system underneath the deposited waste in the dumpsite. Previously, the LPI value calculated for the Brahmapuram dumpyard by Arunbabu et al. was about 31.99.⁵² Similarly, the LPI values reported for other dumpyards in tropical countries were in the range of 13 to 37 (Fig. 7), and all the reported LPI values were higher than the value observed in this study. This difference is likely due to the dilution effect caused by the fire suppression activities. In Malaysian dumpsites, the reported LPI values ranged from 13.89 to 16.63, lower than those recorded in other tropical regions. This difference is likely attributed to the sampling period, which took place between September and October during the Southwest Monsoon in Malaysia.⁷² The increased rainfall during this period may have contributed to pollutant dilution, similar to the effect observed in CDR. According to a study by Abunama et al., landfills in humid climates generate approximately 0.15 m³ of leachate per tonne of waste annually.¹¹ In Brahmapuram, where around 8.43 lakh tonnes of waste are present, the estimated daily leachate generation is around 346.4 m³. An estimated quantity of 2.09 lakh tonnes of fire ridden MSW were accumulated at the end of fire suppression activities, utilizing the service of five heavy duty water pumps (capacity of 60 m³ per hour) to spray water onto the fire affected waste piles for about 80 minutes daily. Hence, an estimated 400 m³ per day of water was used for fire management activity, and assuming 80% of it will convert into CDR, an additional 320 m³ per day of leachate will be generated at the site, nearly doubling the total leachate generation. The leachate generation under normal conditions reported for the dumpsites in tropical climates was around 0.0004 m³ per ton per day. However, firefighting activities raised this volume by 0.002 m³ per ton per day, representing a fivefold increase in daily leachate generation. While this extensive water use may dilute contaminant concentrations in the leachate and lower the Leachate Pollution Index (LPI) value, the overall environmental impact remains high. The increased volume of leachate results in a greater total mass of eluted contaminants, posing a more significant environmental risk.

Table 1 Leachate pollution index of the Brahmapuram dumpyard

Sl No.	Parameter	Significance	Pollutant concentration	Pollutant weight (wi)	Subindex value (pi)	Overall leachate pollution (wi × pi)
a Total dissolved solids (TDS), total coliform (TC); the values of the pollutants are expressed in mg L^−1, except pH and TC.
1	COD	3.963	432	0.062	16	0.992
2	BOD	3.902	50	0.061	7	0.427
3	TC^a	3.289	5.5 × 10^2	0.052	55	2.86
4	Phenolic compounds	3.627	8.1 × 10^−3	0.057	5	0.285
5	pH	3.509	7.62	0.055	5	0.275
6	TKN	3.367	146	0.053	8	0.3975
7	Chlorides	3.078	944	0.048	8	0.384
8	TDS^a	3.196	3533	0.05	8	0.375
9	Pb	4.019	9.49 × 10^−6	0.063	5	0.315
10	Zn	3.585	6.08 × 10^−3	0.056	5	0.28
11	Fe	2.83	6.15 × 10^−1	0.045	5	0.225
12	Cu	3.17	1.90 × 10^−2	0.05	5	0.25
13	Ni	3.321	1.05 × 10^−2	0.052	5	0.26
14	Cr	4.057	3.01 × 10^−3	0.064	5	0.32
15	Hg	3.923	3.41 × 10^−5	0.062	5	0.31
16	As	3.885	1.31 × 10^−3	0.061	5	0.305
Sum				0.891		8.260
LPI value						9.27

---

Fig. 7 Comparison of LPI values reported for major open dumpyards in tropical countries with the calculated CDR Leachate pollution index value (LPI).^{19,20,52,72–79}

3.6 Leachable quantity estimation

The maximum available concentrations (MaxAc) of trace metals in MSW samples were estimated through complete digestion followed by ICP MS analysis, while leachable concentrations were assessed via the TCLP procedure.³⁴ The maximum available and leachable concentrations (using extraction fluid and distilled water) are detailed in Table S11 and Fig. 8. The available metal concentrations were significantly higher than their leachable fractions. Fig. 8 presents leachability as a percentage of the total available concentration, showing that up to 25% of trace metals in MSW can leach into the environment over time. Leaching was higher in the extraction fluid than in distilled water, indicating greater mobility of contaminants under the acidic or complex conditions created by combustion derived runoff (CDR). This agrees with the findings of Ishchenko at Pirna, Saxony, Germany, where municipal waste with higher organic matter and moisture showed greater heavy metal leachability.⁸⁰ In that study, cadmium (Cd) and chromium (Cr) were the most mobile, while lead (Pb) showed the lowest leachability. Another study by Afangideh et al. examined the leachability of heavy metals from the organic fraction of municipal solid waste, sewage sludge, and sawdust under different rainfall intensities.⁸¹ They reported copper (Cu) as the most leachable metal, while Cd, arsenic (As), and Pb were less mobile, demonstrating how rainfall and waste type influence leaching behavior. These results suggest that environmental factors such as rain and stormwater can accelerate leaching.

Fig. 8 Maximum available concentration (MaxAC) and the maximum leachable concentration in MSW samples using distilled water (M DW) and extraction fluid (M EF).

In the present study, arsenic (As) and Cd showed lower leachability, while several trace metals, including Pb, mercury (Hg), selenium (Se), gallium (Ga), nickel (Ni), zinc (Zn), and cesium (Cs), exhibited more than 15% leachability. This poses a serious risk to both surface water and groundwater. Sediment samples from downstream river sites already showed severe enrichment of Cd, Ba, Ag, Hg, Cu, and Zn. Therefore, even low leaching rates can cause significant environmental impacts. With continuous waste accumulation, contamination levels are expected to rise over time. Hence, urgent action is needed to reclaim legacy dumpyards and manage waste scientifically to prevent further environmental degradation.

3.7 Process/engineering improvements at waste management centers – study recommendations

3.7.1Strategic fire control and monitoring. Deployment of landfill gas monitoring systems for early fire detection and surfactant enhanced firefighting foams, applied judiciously, can improve fire suppression efficiency. During dousing operations, temporary containment systems such as geomembrane liners, subsurface drainage networks, or modular barriers should be installed to limit CDR runoff into ecologically sensitive zones.^5,82

3.7.2Pilot scale trials and cost benefit assessment. Site-based trials of firefighting foams should be carried out, with cost-benefit analyses to evaluate feasibility and preparedness as part of disaster response planning.

3.7.3Post fire residue management and dumpyard reclamation. Heterogeneous, partially combusted materials should be isolated and removed from recyclable waste streams. Fire residues must be disposed of in secure landfills, with the site undergoing remediation using techniques such as biocapping, in situ stabilization, or controlled excavation and systematic waste recovery. An account of study recommendations is given in Fig. 9.

Fig. 9 Process/engineering incorporation for postfire site management.

Post fire waste profiles typically show elevated levels of plastics, textiles, and leather, indicating an increased calorific value. This high energy fraction can serve as feedstock for waste to energy (WTE) facilities or be co-processed in cement kilns, offering both environmental and energy recovery benefits.⁸³

3.7.4Ecological risk evaluation and site monitoring. Before initiating redevelopment activities at the reclaimed landfill, a thorough ecological risk assessment needs to be conducted. Such longitudinal environmental monitoring shall be based on spatially distributed sampling points established in the current study covering surface soil, surface water, groundwater (upstream, onsite, downstream), and leachate. These baseline datasets are critical for tracking temporal variations and assessing the effectiveness of remediation efforts.

3.7.5Predictive modeling and regional adaptation. Monitoring long term site data through a harmonized sampling framework can support the development of predictive models to estimate CDR characteristics over time. Incorporating regional variables such as rainfall intensity, soil permeability, and temperature fluctuations into these models will allow site specific risk forecasting and adaptive waste management planning in vulnerable regions.

3.8 Study limitations and future prospects

This investigation was conducted in the immediate aftermath of a major landfill fire incident. Field sampling was constrained by significant safety risks, including the potential for recurring flare-ups and unstable site conditions due to waterlogging from extensive firefighting efforts. These operational challenges limited both the number and spatial distribution of samples collected. Further, the current study primarily focused on the assessment of heavy metal contamination, given the global regulatory emphasis on these pollutants in both developed and developing countries (World Health Organization, 2017).⁶² However, landfill leachate is known to harbor a broader spectrum of hazardous organic contaminants, including per and polyfluoroalkyl substances (PFAS), polychlorinated dibenzo para dioxins and dibenzofurans (PCDD/Fs), polycyclic aromatic hydrocarbons (PAHs), and pharmaceuticals and personal care products (PPCPs).^25,84 These compounds were not covered in the present assessment but are recognized as critical targets for future analytical verification.

Subsequent research will aim to develop predictive models for estimating leachate composition and volume based on site specific geographical and climatic parameters, such as rainfall intensity, topography, and seasonal temperature variations. Additionally, the potential for long term sediment loading and its role in contaminant transport and persistence within the surrounding ecosystem will be a key area for future investigation.

4 Conclusion

This study assessed the characteristics and environmental impacts of chemical combustion derived runoff (CDR) at the Brahmapuram dumpyard following a prolonged 12 to 13 day fire. Through systematic onsite sampling, laboratory analysis, and spatial evaluation, the study revealed significant contamination patterns across environmental media. Heavy metal concentrations were found to be substantially higher in soils and sediments compared to water bodies. Enrichment factor and geo-accumulation index analyses confirmed considerable accumulation of toxic metals such as Cd, Cr, Pb, Ni, As, and Hg, especially in surface soils and sediments. The pollution load index indicated the formation of contamination hotspots, suggesting long-term buildup of trace metals with potential exposure risks through sediment ingestion, agricultural irrigation, or bioaccumulation in aquatic organisms.

Post-fire waste composition showed a notable decline in biodegradable and paper fractions, accompanied by an increase in high calorific waste such as textiles, leather, and mixed materials. These findings are critical for planning recovery strategies such as biomining and waste to energy (WTE) projects, supporting the Sustainable Development Goal (SDG) of responsible consumption and production. Although immediate impacts on groundwater and surface water were limited, the CDR exhibited poor biodegradability, likely due to the presence of persistent and toxic compounds. Leaching studies showed that up to 25% of total trace metals in the waste could migrate into the environment, particularly under acidic conditions, which is common during monsoons in tropical regions. Fire suppression efforts using large volumes of water further intensified the mobilization of both fire related and preexisting contaminants, posing heightened risks to aquatic systems and public health.

These findings highlight the urgent need to revise landfill fire management protocols. Measures such as biocapping, in situ stabilization, and controlled excavation should be integrated into postfire management frameworks. The recommendations support key SDGs, including clean water and sanitation, by promoting safer solid waste practices and enabling resource recovery from legacy waste, thereby contributing to long term environmental and public health protection.

Conflicts of interest

There are no conflicts to declare.

Data availability

The authors herewith declare that the data supporting this article have been included as part of the SI. See DOI: https://doi.org/10.1039/d5em00343a.

Acknowledgements

The authors gratefully acknowledge financial support from the GEF-UNEP-NIP update project (GEF ID: 10978; GAP 318439), Department of Scientific and Industrial Research (DSIR), Government of India (DSIR/CRTDH/NIIST/2014) and Kerala State Pollution Control Board (GAP 318639) for this study (CSIR-NIIST Publication No: NIIST/2025/Mar/960). We thank Dr Joshy George, CSIR-NIIST, Thiruvananthapuram, for carrying out the ICPMS analysis for quantification of heavy metals. SVA expresses his deep sense of gratitude for the award of a research grant and fellowship under the CMNPF (A3/l218/2023). During the preparation of this manuscript, the authors used Grammarly in order to enhance the readability and language of the manuscript as part of the manuscript drafting policy of the institute. The authors have reviewed and edited the output and take full responsibility for the content of this publication.

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