Characterisation of Faecal Sludge from Different Nature-Based Treatment Processes for Agricultural Application

Abstract

Nature-based systems predominantly treat faecal sludge in developing regions due to their cost-effectiveness and operational simplicity. These systems, including solid–liquid separation, anaerobic digestion, dewatering, phytofiltration, and composting produce, treated sludge with variable characteristics. However, application-specific characterisation of treated sludge from these systems remains limited, hindering evidence-based agricultural application. This study investigated thirty treated faecal sludge samples from unplanted drying beds, planted drying beds, and co-composting, with a focus on their soil application potential. Nonparametric statistical analysis revealed that treatment processes significantly influenced the key properties, including electrical conductivity, total organic carbon, total nitrogen, and potassium content. The co-compost yielded comparatively higher conductivity (4.9 dS/m) and potassium levels (1.09%) but lower total nitrogen (2.15%) and organic carbon contents (28%). Additionally, co-composted sludge exhibited a balanced nutrient profile with a wide range of micronutrients and high variability. Despite this variability, all samples met the Indian compost quality guidelines for heavy metals. The findings underscore the importance of treatment-specific characterisation to inform appropriate soil application rates and ensure safe use. This study contributes to the development of quality criteria and guidelines for use of faecal sludge in agriculture, particularly in regions such as India, where no regulatory framework currently exists for faecal sludge application.

1. Introduction

A significant portion of the population, particularly in developing regions such as India, relies on onsite sanitation systems (OSSs), including septic tanks and pit latrines due to limited access to the centralised sewage infrastructure. Between 2000 and 2022, the global urban sewer coverage remained relatively stable at approximately 63%, whereas the use of septic tank increased from 15% to 22%, highlighting the growing reliance on OSSs [1,2]. In India, OSS coverage is particularly extensive in rural areas and small towns, with around 60% of the rural population relying on OSS solutions as of 2020 [3]. Nature-based systems (NBSs), including drying beds, are widely adopted to treat faecal sludge (FS) in developing regions due to their cost-effectiveness and operational simplicity [4]. However, safe management and disposal of FS generated from these systems remain a challenge in developing regions [5].

Sustainable sanitation aims to treat waste while recovering nutrients for agricultural reuse, thus closing the loop in nutrient cycles and supporting Sustainable Development Goals (SDGs) 2 and 6 [6,7]. FS is increasingly recognised as a valuable source of plant nutrients that can improve soil fertility and reduce reliance on chemical fertilisers [8]. Several studies have reported the growing use of FS in agriculture across both developed and developing countries. Nevertheless, the potential of FS as a soil amendment is constrained by the lack of data on critical agronomic properties, which is crucial for the faecal sludge management (FSM) decision-making process [7,9]. The effective agricultural use of FS requires an understanding of its characteristics for appropriate soil application rates and regulations to ensure safety.

Existing studies have primarily focused on the characterisation of raw FS from containment systems or inflow sludge at treatment plants and not specifically on the final treated FS from the faecal sludge treatment plants (FSTPs) [10,11]. These studies emphasise basic treatment-related parameters such as pH, electrical conductivity (EC), biological oxygen demand (BOD), and chemical oxygen demand (COD). While useful for treatment system design and efficiency assessment, these indicators are not directly relevant for evaluating FS suitability for agricultural application [12,13,14]. Limited research has addressed the characterisation of final, treated faecal sludge specifically for soil application, including parameters such as bulk density, plant-available nutrients, and heavy metals. Most existing studies have focused on thermally treated sludge, with limited attention to nature-based treatment outputs [11]. Moreover, raw sludge samples tend to exhibit significant variability due to differences in containment sources, whereas final treated FS is more stable due to homogenisation during treatment, resulting in a stable nutrient profile [14]. Dewatered FS is preferred over raw sludge for agricultural use due its lower volume, improved handling, and reduced pathogen risk, making it more suitable for field application. Dewatered FS tends to have a more stable nutrient profile, improving soil structure and fertility when used as a fertiliser [14]. The lower moisture content in dewatered FS minimises the risk of eutrophication during runoff and inhibits pathogen survival, making it a safer option for agricultural application [11]. Therefore, characterising the final dewatered and treated FS from FSTPs for parameters relevant to soil application is needed to inform agricultural practices [11,14]. FS properties vary significantly with the treatment process [8,13], and characterisation must account for these variations. Hence, soil application-specific characterisation from different treatment systems is essential for evidence-based application strategies.

FS contains significantly higher levels of nutrients, solids, and contaminants compared to domestic wastewater sludge, necessitating detailed quality assessments for safe end use. However, current studies often lack comparative, application-specific FS quality data across treatment systems to support end use planning, particularly in an Indian context [15]. Studies have reported significant interplant variations in faecal sludge (FS) characteristics, highlighting the need for comparative datasets to support informed decision-making [16]. Moreover, disparities in India’s regulatory frameworks limit consistent characterisation and the selection of appropriate FS treatment technologies, posing a barrier to the development of safe reuse pathways [5].

Despite the growing recognition of faecal sludge (FS) as a resource, there remains a lack of agronomic benchmark data derived from real-world faecal sludge treatment plants (FSTPs), particularly those based on nature-based systems (NBSs). Existing studies often focus on thermally treated sludge or raw FS inputs, which do not reflect the characteristics of final, dewatered outputs that are more relevant for agricultural reuse. This gap is especially pronounced in the Indian context, where research has primarily addressed wastewater and solid waste management [2], and no formal quality guidelines exist for the agricultural use of FS. This study addresses this critical gap by systematically characterising treated FS from three widely implemented NBS-based treatment systems in India—unplanted drying beds, planted drying beds, and co-composting units—under operational conditions. By evaluating the agronomic parameters and compliance with existing standards, the study aims to assess the suitability of NBS-treated FS for safe and effective use in agriculture, thereby supporting evidence-based reuse practices and informing future regulatory frameworks.

In this context, the study evaluated critical parameters relevant to soil application, such as pH, electrical conductivity, bulk density, plant-essential nutrients, and heavy metals, to validate the suitability of these treatment by-products for agricultural use. By generating empirical evidence from real-world treatment plant outputs, the findings contribute to the development of quality criteria and standards for FS application in India and other developing contexts.

2. Materials and Methods

2.1. Treatment Processes

This study focused on nature-based treatment processes that operate without chemicals or with low/no electricity requirements. Faecal sludge was collected from household septic tanks and pit latrines located in peri-urban areas of Bengaluru, Karnataka.

2.1.1. Unplanted Drying Bed (UPDB)

Faecal sludge is first loaded into the screening chamber (Figure 1a), which removes solid waste and settles grits. Solid-liquid separation occurs in a settling tank, followed by a stabilisation reactor where sludge undergoes digestion with a retention time of 4 days. The stabilised sludge is then loaded onto a gravel-layered drying bed for dewatering. Sludge is removed after 18–20 days of drying, depending on the climatic conditions [12]. The entire process, including drying time, takes approximately one month, depending on the climatic conditions. The effluent is treated separately through a system consisting of a settler, anaerobic filter, planted gravel filter, and collection tank (Figure 1a).

2.1.2. Planted Drying Bed (PDB)

Faecal sludge is loaded onto a bed composed of layered filter media—gravel, sand, and soil—and planted with reeds and Canna indica (Figure 1b). Dewatering and stabilisation occur through a combination of physical filtration and biological mechanisms over a period of six months to one year, depending on the loading rate and climatic conditions [11]. The liquid fraction is treated separately using a process similar to that of the UPDB (Figure 1b).

2.1.3. Co-Composting

Dewatered sludge is co-composted with organic municipal solid waste in 1:2 ratio using the windrow method. Layers of dewatered sludge and municipal organic waste are formed into 6-foot-high heaps (Figure 1c), which are regularly turned to ensure uniform aeration and temperature distribution [17]. The composting process takes approximately two to three months, depending on the climatic conditions.

The duration of each treatment system reflects its operational design: the UPDB offers rapid dewatering and stabilisation, PDB provides longer-term stabilisation through plant-based treatment, and co-composting combines dewatered sludge with organic waste for nutrient-rich compost. These durations are integral to the study, as they reflect real-world treatment scenarios and the typical characteristics of their final outputs.

2.2. Sampling

A total of thirty treated FS samples were collected from three different treatment processes: UPDB (n = 10), PDB (n = 10), and co-composting units (n = 10) in Bengaluru, Karnataka (Figure 2), across ten operational cycles. The sample size was determined based on operational feasibility and aligns with international guidance, which emphasises that sample numbers should be based on study objectives, expected variability, and available resources [18]. This approach is consistent with prior FSM studies conducted under similar field and resource constraints [11]. The selected sample size (n = 10) was also informed by prior studies that reported large, treatment-driven differences in faecal sludge characteristics across treatment systems. These studies have demonstrated statistically significant effects of FS treatments on key parameters such as pH, electrical conductivity, nitrogen forms, and total organic carbon [19]. Based on these findings, a group size of 10 was considered sufficient to detect meaningful differences using nonparametric statistical methods, as is common in field-based FSM research.

UPDB samples were collected from the faecal sludge treatment plant (FSTP) in Devanahalli, Bengaluru, India (13°15′14.1″ N 77°42′27.7″ E). PDB samples were obtained from Kengeri, Bengaluru, India (12°55′06.3″ N 77°28′19.1″ E). Co-compost samples were also collected from the Devanahalli FSTP, where windrows were formed using layers of dewatered sludge and organic municipal waste. Co-composting aims to balance the carbon–nitrogen ratio by integrating dewatered faecal sludge with municipal organic waste, and the sampled material reflects the influence of these combined feedstocks.

Composite sampling was adopted by dividing each drying bed or compost pile into quarters and combining subsamples from each section to ensure representativeness and reduce spatial bias. The thoroughly mixed composite was divided into four equal parts; two opposite quarters were discarded, and the remaining two were recombined and mixed again until the desired quantity was obtained. Samples from all three treatment systems were collected across 10 operational cycles to capture temporal variability and provide a comprehensive analysis of the treated sludge characteristics. Standardised procedures, including sterile containers and consistent sampling protocols, were followed across all treatment sites. Composite sampling from multiple cycles and sites was employed to ensure representativeness and to provide a comprehensive analysis of the treated sludge [20].

All samples were collected at ambient temperature conditions (approximately 25–32 °C) and immediately stored in sterile, airtight containers. Samples were then transported to the laboratory in a cooler box with ice packs and were stored at 4 °C until analysis.

2.3. Analytical Methods

Data validation was ensured by following established standard operating procedures for all analytical methods, as described in the national guidelines, Fertiliser Control Order (FCO) 1985, and international guidelines, Food and Agricultural Organisation (FAO) 2008 [21,22]. Instruments such as the atomic absorption spectrophotometer (Agilent Technologies, AAS 280FS, Santa Clara, CA, USA), pH meter (Oakton pH 2700, Cole-Parmer, Maharashtra, India), and conductivity meter (Oakton CON 2700, Cole-Parmer, India) were calibrated before each use. Blanks and standard reference materials were run periodically to verify instrument accuracy. All measurements were conducted in triplicate, and average values were reported to minimise random error and enhance precision.

The total nitrogen content was determined using the Kjeldahl method, involving digestion with concentrated sulphuric acid and a catalyst at 400 °C until a clear solution was obtained (Gerhardt Digestion & Distillation Unit, Königswinter, Germany) [20]. The phosphorus (P) and potassium (K) contents were measured after dry ashing 10 g of oven-dried sample at 650–700 °C in a muffle furnace (Nabertherm, Lilienthal, Germany) for 6–8 h. Ash was dissolved in 25% HCl, filtered, and analysed using gravimetric methods for P and flame photometry (BWB Technologies, Newbury, UK) for K [23]. The total organic matter content was determined by loss on ignition in a muffle furnace (Nabertherm, Germany) at 650–700° C for 6–8 h, and total organic carbon was calculated as 58% of the total organic matter [24]. The C:N ratio was derived from the estimated total nitrogen and carbon values. Heavy metals, including iron (Fe), zinc (Zn), copper (Cu), manganese (Mn), nickel (Ni), lead (Pb), cadmium (Cd), and chromium (Cr), were analysed by atomic absorption spectrophotometry (Agilent Technologies, AAS 280FS, USA) after the digestion of 1.0 g of dried, ground sample with a triacid mixture on a hot plate at approximately 150 °C. The digested sample was filtered and diluted to 100 mL. Calibration was performed using NIST (National Institute of Standards and Technology) traceable standards, and elements were measured at their specific wavelengths [25]. The secondary macronutrients, calcium (Ca), magnesium (Mg), and sulphur (S), and the micronutrient boron (B) were analysed following FAO (2008) protocols [22]. Ca and Mg were determined by EDTA titration, sulphur by turbidity using UV–Vis spectrophotometry (Jenway 6850 UV–Vis, Cole-Parmer, India) at 420 nm, and boron by the azomethine-H colorimetric method at 420 nm [22]. The pH and electrical conductivity were measured by suspending samples in distilled water at a 1:5 (w/v) ratio. The pH suspension was shaken continuously for 2 h, and EC suspensions were stirred intermittently for 1 h before analysis using calibrated pH and EC meters (Oakton pH 2700 and CON 2700, Cole-Parmer, India). Bulk density was calculated using the cylinder method based on the weight and volume of dried sludge samples. All procedures adhered to the standards specified in the Fertilizer Control Order (FCO) 1985 (as amended up to February 2019) and FAO guidelines [21,22].

2.4. Statistical Analysis

Descriptive statistics were used to summarise FS characteristics across UPDB, PDB, and co-compost samples. The results were compared with previous studies and quality guidelines from the Fertiliser Control Order (FCO) and Solid Waste Management Rules 2016, India [26]. These standards apply to compost from organic waste, such as municipal solid waste and vegetable waste, and are used as a reference in the absence of FS-specific quality standards in India.

The normality of faecal sludge (FS) characteristics was assessed within each treatment group using both Q–Q plots and the Shapiro–Wilk test. The results indicated a mix of distribution patterns, with several variables exhibiting clear or borderline deviations from a normal distribution (Supplementary Materials, Figure S1). Given this variability and the small sample size (n = 10 per group), a two-tailed nonparametric Mann–Whitney U test was applied uniformly to detect significant differences among the three treatment processes at the 5% significance level (α = 0.05). Nonparametric methods offer a robust, distribution-free alternative that is particularly suitable when working with small samples and variable data distributions [27,28]. This approach is also consistent with established practices in previous studies characterising faecal sludge based on final properties [11,12,13]. All statistical analyses were conducted using RStudio (version 2024.09.1+394).

3. Results and Discussion

3.1. Characterisation of Faecal Sludge

Table 1. Summary of statistics for faecal sludge characteristics from UPDB, PDB, and co-compost. Sample (n) = 10 observations from each group.

Treatment Process	UPDB		PDB		Co-Compost		Literature Values from Previous Studies		Quality Guidelines *
Parameters	Mean	SD	Mean	SD	Mean	SD	Range	Source	FCO, 2016
pH	6.08	0.43	6.06	0.55	6.10	0.53	6.21–7.96	[10,19,29,30,31,32,33,34]	6.5–7.5
Conductivity (dsm−1)	1.91	0.58	1.03	0.56	4.58	2.95	0.11–7.6	[10,19,29,30,31,32,35]	4 (not more than)
Moisture content	58.7	8.40	60.40	19.60	31.80	13.70	5–97%	[10,19,29,32,33,36,37,38,39,40,41]	15.0–25.0
Bulk density (g/cm3)	0.48	0.04	0.60	0.29	0.52	0.13	1.05–1.06	[10,19]	<1.0
Total organic Carbon (%)	37.24	2.40	39.65	5.26	26.28	7.56	3.5–33.5	[19,32,35]	12 (min)
Total Nitrogen (N) (%)	3.14	0.88	2.91	0.58	1.99	0.63	1.05–17.83	[10,19,31,32,33,34,35,36,39,40,41]	0.8 (min)
Total Phosphate (%)	1.45	0.73	2.09	1.50	1.00	0.79	1–8.1	[19,29,30,31,32,33,36,38,39]	0.4 (min)
Total Potassium (%)	0.23	0.06	0.42	0.79	1.36	0.75	0.44–3.45	[19,29,31,32,33,36,38,39]	0.4 (min)
C: N ratio	12.81	3.84	14.02	2.37	13.28	1.61	9.86–22	[10,19,29,30,32,33]	<20
Arsenic as Ar, (mg/kg)	3.51	1.03	3.27	1.18	2.65	1.67	<0.01–2.8	[10,40]	10
Zinc as Zn, (mg/kg)	697.63	58.13	688.90	208.58	568.86	392.26	0.3–4946	[10,19,29,30]	1000
Copper as Cu, (mg/kg)	140.37	12.34	243.65	86.95	117.47	24.53	0.01–373	[10,19,29,30,31,40]	300
Lead as Pb, (mg/kg)	27.34	11.11	37.55	6.85	42.84	17.11	<0.1–189	[10,19,31,40]	100
Chromium as Cr, (mg/kg)	19.42	8.11	24.38	19.09	19.13	9.76	<0.01–485	[10,19,40]	50
Cadmium as Cd, (mg/kg)	1.34	0.30	2.19	0.43	3.88	2.19	0.9–20	[10,19]	5
Nickel as Ni, (mg/kg)	23.78	6.73	32.70	15.66	20.30	8.01	<0.1–30	[10,19,40]	50
Mercury as Hg, (mg/kg)	0.07	0.02	0.06	0.02	0.26	0.36	<0.9, <0.1	[10]	0.15
Total Calcium %	2.37	0.91	2.68	0.66	2.85	1.08	1.15–5	[19,29,33,36]	-
Total Magnesium %	0.58	0.32	0.68	0.39	0.79	0.60	0.634–4.074	[19,29,33,36]	-
Total Sulphur %	0.91	0.20	0.80	0.18	0.89	0.34	0.27–1.7	[29,33,34,36,37,39,40,41,42]	-
Total Iron %	14.35	43.12	0.65	0.27	0.91	0.49	0.44–37	[19,29,30,31]	-
Total Manganese (ppm)	434.42	155.94	479.41	167.54	422.30	151.74	0.03–2040	[19,29,30]	-
Boron as B (ppm)	50.92	5.55	67.38	26.96	82.94	30.68	-	-	-

* Compost quality standards as per the Fertiliser Control Order (FCO) and Solid Waste Management Rules 2016.

summarises the characterisation results for all UPDB, PDB, and co-compost samples. It also compares these study values to previous studies and to the compost quality guidelines from the Fertiliser Control Order (FCO) and Solid Waste Management Rules 2016, India [26]. The FCO and SWM Rules provide nationally accepted benchmarks for compost quality in India. While originally formulated for compost from municipal or vegetable waste, these guidelines serve as the most appropriate regulatory reference in the absence of faecal sludge-specific standards.

The pH values of all three treatments were slightly below the literature range (6.21–7.96) and FCO recommended range (6.5–7.5), yet they remained close to neutral, making them suitable for soil application. The slight acidity observed across all treatments is consistent with the nature of stabilised faecal sludge, which often exhibits acidic pH due to the formation of organic acids during anaerobic digestion and subsequent degradation processes [19]. The slightly acidic nature helps reclaim alkaline soils and support acid-tolerant crops. The electrical conductivity (EC) values were within the broader literature range (0.11–7.6 dS/m), with the co-compost showing a slightly higher value (4.58 dS/m) that is close to the guideline value. Comparatively higher EC values are attributed to mineralisation and the addition of nutrient-rich organic waste [19]. Similar observations were reported where EC values increased due to composting [43]. The variability observed in co-composted sludge underscores the need to understand feedstock characteristics and control composting conditions to achieve consistent product quality. Moisture content samples were comparable to prior studies (5–97%), with co-compost showing a lower moisture content (~32%), attributed to proper aeration and thermophilic composting conditions [44]. Moisture reductions have also been reported in composted FS, confirming the benefits of co-composting in enhancing product storability and reducing pathogen survival [45]. The bulk density (BD) across all the treatments was slightly below the literature range and within the limit specified by FCO (<1 g/cm³). Low BD improves the soil porosity and is beneficial for root penetration and aeration [19]. The relatively high variability in PDB sludge suggests a need for process standardisation to ensure product consistency.

Nutrient composition varied across treatments, impacting their suitability for soil amendment. The total organic carbon (TOC) content in UPDB (37%) and PDB (40%) were slightly higher than the literature values, while the co-compost (26%) fell within the reported ranges. All samples exceeded FCO’s minimum requirement (12%), indicating a higher organic matter content and strong potential to enhance the soil structure, water-holding capacity, and microbial activity. The total nitrogen (TN) content was highest in the UPDB and PDB samples (~3%), whereas the co-compost had a lower N content (2%), likely due to mineralisation and potential ammonia volatilisation. Nitrogen losses during aerobic composting are common and have been linked to raw material composition, the C/N ratio, and oxygen (O₂) concentration within the compost pile [46]. The total phosphorus (TP) values across all treatments were within the 1–8% range reported in earlier works. Lower TP values in co-compost (1%) is possibly due to phosphate binding during aerobic degradation. Hence, digested and composted faecal sludge is preferred over raw sludge to prevent eutrophication due to agricultural runoff [11]. Since phosphorous is one of the essential elements for plant growth, the P content in sludge makes it a valuable source for application. The potassium (K) content agreed with the values reported in previous studies for all the samples (0.44–3.5%), with higher K in the co-compost (1.4%) due to the addition of vegetable feedstock during composting. Hence, K-rich co-compost reduces the reliance on imported potassium fertilisers in India. The carbon-to-nitrogen (C:N) ratios were within the ideal range (10:1–20:1) for soil application and the limits specified by FCO (<20), with co-compost showing relatively less variability. Composting helps maintain consistency in the nutrient balance [19]. The carbon-to-nitrogen (C:N) ratio is crucial for microbial activity and nutrient cycling.

Macronutrient levels, including those of calcium (1–5%), magnesium (0.6–4%), and sulphur (0.27–1.7%), fell within the literature ranges and are vital for soil nutrient health. Ca in faecal sludge is essential for improving soil structure and plant growth, and Mg is an essential component of photosynthesis. Since sulphur is less abundant in soil and its presence in sludge helps synthesise proteins and enzymes in plants, these nutrients mirror the profiles of commonly used organic fertilisers such as agro-waste manure and poultry and farmyard manure [35,47], making FS an accessible alternative.

Micronutrients like Fe, Mn, B, Zn, and Cu were present in adequate concentrations and were within the literature values. Micronutrients are essential plant nutrients and can limit plant growth if they are not available in sufficient quantities. Although micronutrients are needed in trace amounts, their excess can be phytotoxic. The quality guidelines under FCO 2016 do not cover the standard set values for Fe, Mn, and B. Hence, the application rate should consider the soil status of these nutrients to avoid overapplications [1].

The heavy metal contents (Pb, Cr, Cd, and Ni) across all the treatment processes were within the literature values, except for arsenic in the PDB (3.3 mg/kg) and UPDB (3.5 mg/kg) sludge. The concentrations of heavy metals were within the limits set by the FCO, India 2016, except for mercury in the co-compost (0.26 mg/kg). However, all the heavy metal concentrations were within the limits set by the US Environmental Protection Agency (US EPA) quality guidelines for sludge [48]. The FCO, India guidelines (Table 1) are more stringent than the US EPA guidelines for heavy metals. Heavy metals can hinder anaerobic digestion by inhibiting the growth of bacteria and inactivating enzymes [49]. Manga et al. 2022 reported increased nutrients and heavy metals due to the concentration effect of significant matter degradation and thus a net dry weight loss [19]. However, during composting, the concentrations decrease by the end of the composting process due to the loss of heavy metals and nutrients through leaching. The variability in heavy metal content reinforces the importance of establishing treatment process-specific monitoring protocols for FS application at scale.

3.2. Critical Parameters for Soil Application

The results from the statistical analysis of the critical parameters for soil application are summarised in

Table 2. p-values of the Mann–Whitney U test for differences in faecal sludge properties for soil application among the three treatment processes.

Parameters	pH	Conductivity (dS/m)	Bulk Density (g/cm3)	Total Organic Carbon (%)	Total Nitrogen (%)	Total Phosphorous (%)	Total Potassium (%)	C:N Ratio
UPDB vs. PDB	0.850	0.007	0.494	0.064	0.219	0.393	0.045	0.280
UPDB vs. Co-compost	0.912	0.123	0.068	<0.001	0.012	0.226	<0.001	0.436
PDB vs. Co-compost	0.940	0.015	0.677	0.001	0.001	0.029	0.003	0.912

Mann–Whitney U Test, nUPDB = nPDB = nCo-compost = 10, and α = 0.05. Values in bold indicate significant differences.

. The median values for all the parameters are given in the Supplementary Materials (Table S1).

Figure 3 shows the results for pH, conductivity, bulk density, total organic carbon (TOC), total nitrogen (TN), total phosphorous (TP), total potassium (TK), and the C:N ratio.

A comparison of the median pH (Figure 3a) in FS revealed no significant difference in pH across all treatment comparisons (UPDB vs. PDB: p = 0.8501, UPDB vs. co-compost: p = 0.9118, PDB vs. co-compost: p = 0.9397), with pH values ranging between 5.29 and 7.20. The soil pH plays a crucial role in nutrient availability and microbial activity. The ideal pH for most crops is between 5.5 and 7.5, although some crops may tolerate or require pH levels outside this range [50]. Similar observations were reported by Manga et al. (2022) for FS products [19]. These findings suggest that the treatment processes used for faecal sludge do not alter the pH in ways that would affect its suitability for agricultural application.

Conductivity (Figure 3b) showed significant differences between UPDB and PDB (p = 0.0068), with median values of 1.8 and 0.70 dS/m, respectively, indicating that the treatment process impacts the ionic content and could influence nutrient availability. The UPDB vs. co-compost comparison did not yield a significant difference (p = 0.1230), while the PDB vs. co-compost comparison indicated a significant difference (p = 0.0147). These results imply that composting may increase the ionic content through mineralisation, elevating conductivity. Aouabe et al. (2025) similarly observed increased EC in composted FS due to the solubilisation of organic salts during aerobic degradation [43]. In the case of co-composting, such variability in EC may reflect differences in the degree of organic matter decomposition or the heterogeneity of feedstock inputs. Operational factors such as inconsistent turning frequency, moisture levels, or organic waste composition could influence the solute release and salt accumulation. As conductivity influences soil microbial communities and nutrient mobility, this parameter should be monitored to optimise soil health outcomes in field-scale applications [51].

Bulk density (Figure 3c) is a key indicator of soil compaction and affects soil aeration, root penetration, and water retention. The results revealed no significant differences (0.21–1.37 g/cm³) among the treatments (all p > 0.05), suggesting that the choice of treatment process did not significantly affect the soil physical structure in terms of compactness. Mathewos et al. (2025) also reported low BD values in FS, indicating its potential for improving soil physical characteristics [52]. Among treatments, co-composting showed slightly lower BD, which enhances its suitability for agricultural application by promoting better soil porosity [53]. In operational terms, bulk density variability may arise from inconsistent organic matter decomposition or moisture retention during composting, particularly in co-composting systems with heterogeneous feedstocks. This highlights the importance of process control in maintaining uniform compost quality for reliable field application.

Significant differences (p < 0.05) in the total organic carbon (TOC) content (Figure 3d) were observed between the UPDB (38%) and co-compost (29%) and between PDB (41%) and co-compost (29%). PDB retained more organic material, likely due to less decomposition in planted drying beds. In contrast, co-composting, being an aerobic process, promotes higher degrees of mineralisation and, hence, lesser TOC content. Reduced TOC in co-composted sludge is attributed to microbial breakdown of organics under high-temperature aerobic conditions [54]. The observed variability in TOC across co-compost samples (Figure 3d) may reflect uneven decomposition caused by fluctuations in the compost pile temperature, microbial activity, and retention time. These factors are often influenced by operational conditions such as turning frequency and moisture regulation. Ensuring consistent decomposition processes is critical to minimise batch-to-batch variation and produce a stable compost product with predictable organic carbon levels.

Total nitrogen (TN) (Figure 3e) is vital for plant growth and metabolism. The median total nitrogen (TN) concentrations (~3%) did not significantly differ between the UPDB and PDB (p = 0.2190). However, TN was significantly lower in co-compost samples (2%) with p = 0.0011 (PDB vs. co-compost) and p = 0.0115 (UPDB vs. co-compost). The relatively lower TN content in the co-compost treatment group (2%) could be due to N loss during composting through mineralisation and ammonia volatilisation [55,56]. Similar findings were reported by Sun et al. (2025), who observed nitrogen reduction during aerobic co-composting due to thermophilic degradation processes [46]. This has implications for scaling up co-composted FS use, as nutrient losses may necessitate enrichment or application rate adjustments.

The total phosphorus (TP) content (Figure 3f) did not significantly differ between the UPDB vs. PDB and UPDB vs. co-compost comparisons (all p values > 0.05), with TP values around 1.4%. However, the PDB vs. co-compost comparison showed a marginally significant difference (p = 0.0288), with PDB containing higher TP (1.65%) compared to the co-compost (0.84%). The plant biomass shed onto the planted drying beds during digestion might have contributed to the increased P level. The treatment methods may not significantly alter the phosphorus availability in the sludge, and all treatments retained agronomically useful TP levels for enhancing root development and seed formation [57].

Significant differences in the potassium (K) content (Figure 3g) were found among all treatments. Co-compost samples had the highest K content (1.09%) compared to UPDB (0.23%) and PDB (0.17%) (p < 0.05). This increase is attributed to the addition of organic waste in the compost feedstock. Notably, the co-compost group exhibited considerable variability in the K content (Figure 3g), which may reflect differences in the type and proportion of organic materials used—particularly potassium-rich food waste—as well as uneven leaching or solubilisation during composting. These operational inconsistencies can lead to unpredictable nutrient levels in the final product. This finding is pertinent for crops that are heavy potassium feeders, as soil treated with co-compost may increase their growth. Potassium is essential for the osmoregulation and activation of plant enzymes [58].

The C:N ratio (Figure 3h) did not significantly differ across treatments (p > 0.05), with values ranging from 12 (UPDB) to 13.4 (co-compost), indicating that these treatment processes do not substantially (p > 0.05) alter the carbon-to-nitrogen balance in the sludge. This stability suggests that all three processes do not significantly skew the carbon-to-nitrogen ratio in the treated sludge, which is crucial for microbial activity and nutrient cycling in soil. Considering the inherent variability in faecal sludge (FS) composition across batches, pre-application treatment through digestion and co-composting is recommended to ensure a more consistent nutrient balance for soil application. The co-compost samples exhibited several outliers (Figure 3h), likely due to inconsistencies in the composting conditions or feedstock composition. These deviations highlight the importance of maintaining operational consistency during co-composting to ensure product quality and nutrient predictability. In contrast, the PDB and UPDB samples showed fewer outliers, suggesting greater uniformity in these treatment processes. While anaerobic digestion enhances stability and reduces vector attraction by lowering volatile solids, co-composting offers additional benefits, including improved microbial activity, enhanced pathogen reduction, and greater stabilisation of organic matter due to the elevated temperatures achieved during the process [59]. These effects not only improve the soil structure but also promote microbial diversity, thereby enhancing nutrient cycling and long-term soil fertility, potentially making co-composted FS more beneficial in large-scale soil health programs [60,61].

3.3. Secondary Macronutrients

The results from the statistical analysis of calcium (Ca), magnesium (Mg), and sulphur (S) for soil application are summarised in

Table 3. p-values of the Mann–Whitney U test for differences in secondary macronutrients in the faecal sludge among the three treatment processes.

Parameters	Total Calcium %	Total Magnesium %	Total Sulphur %
UPDB vs. PDB	0.212	0.940	0.173
UPDB vs. Co-compost	0.353	0.364	0.850
PDB vs. Co-compost	0.971	0.912	0.570

Mann–Whitney U Test, nUPDB = nPDB = nCo-compost = 10, and α = 0.05.

. The scatter plot below illustrates the secondary macronutrient content of the faecal sludge (Figure 4).

The comparisons for Ca, Mg, and S revealed no significant differences between UPDB, PDB, and co-compost (p > 0.05 for all pairs; Table 3). Compared with the PDB and UPDB samples, the co-compost samples exhibited greater variability and frequent outliers, particularly for calcium and magnesium (Supplementary Materials Table S1). This variability likely results from the heterogeneous nature of feedstock composition and varying degrees of organic matter decomposition during composting. While these differences were not statistically significant (Table 3), they indicate that careful management is needed to ensure uniform nutrient profiles in the final product. The sulphur concentrations were relatively uniform across all treatments, indicating that the sulphur levels in the final sludge are largely unaffected by the treatment type. This consistency may be attributed to the inherent sulphur content of the original faecal sludge and organic inputs, which undergo minimal transformation during nature-based treatment processes. Sulphur plays an important role as a secondary macronutrient, essential for plant protein synthesis and enzymatic function. While uniform levels across treatments simplify nutrient planning, the overall sulphur availability may still vary depending on the feedstock composition and microbial activity during composting. In co-composting systems, for instance, differences in organic waste inputs could lead to batch-to-batch variations. Therefore, the periodic monitoring of sulphur concentrations remains important to ensure consistent nutrient delivery, particularly in regions where soils are prone to sulphur depletion.

Maintaining a balanced input of secondary macronutrients is critical to prevent soil imbalances and crop nutrient deficiencies. These findings reinforce the importance of nutrient monitoring and batch testing prior to land application, particularly when using co-composted FS, which may be subject to greater variability [62].

3.4. Micronutrients

The results from the statistical analysis of micronutrients boron (B), copper (Cu), manganese (Mn), and zinc (Zn) for soil application are summarised in

Table 4. p-values of the Mann–Whitney U test for differences in micronutrients in the faecal sludge among the three treatment processes.

Parameters	Total Manganese (ppm)	Boron as B (ppm)	Zinc as Zn, (mg/kg)	Copper as Cu, (mg/kg)
UPDB vs. PDB	0.796	0.353	0.280	0.002
UPDB vs. Co-compost	0.579	0.015	0.043	0.019
PDB vs. Co-compost	0.631	0.257	0.043	0.002

Mann–Whitney U Test, nUPDB = nPDB = nCo-compost = 10, and α = 0.05. Values in bold indicate significant differences.

. The scatter plot (Figure 5) shows the distribution of micronutrient concentrations in the sludge from the three treatment processes.

There was considerable variation within each group, particularly for zinc and copper (p < 0.05), indicating that the treatment method and sludge source influenced the micronutrient content (Table 4). Co-composted samples exhibited the greatest variability, especially for zinc, and included potential outliers (Figure 5), likely due to inconsistencies in composting conditions or inputs. Such inconsistencies are critical when scaling up sludge use in agriculture, as micronutrients like Cu and Zn, though essential for plant development, can be toxic at elevated concentrations. Elevated Cu levels, in particular, warrant monitoring, as repeated application may lead to long-term accumulation in soils. In contrast, manganese and boron showed a more uniform distribution across treatments, with no statistically significant differences except for B in the co-compost, which was slightly higher than in UPDB (p = 0.015). From an agronomic perspective, all four micronutrients are crucial for physiological plant functions. However, their beneficial effects depend on controlled application rates, as even small excesses of micronutrients like Cu and Zn can inhibit plant growth or alter the soil microbial balance [63,64]. These results highlight the need for consistent treatment processes, quality monitoring, and batch-specific nutrient profiling prior to field application. This is particularly relevant for co-compost, which, although nutrient-rich, may carry greater variability if not standardised.

3.5. Heavy Metals

The results from the statistical analysis of the heavy metals arsenic (Ar), lead (Pb), chromium (Cr), cadmium (Cd), nickel (Ni), and mercury (Hg) are summarised in

Table 5. p-values of the Mann–Whitney U test for differences in faecal sludge heavy metals among the three treatment processes.

Parameters	Arsenic (mg/kg)	Lead (mg/kg)	Chromium (mg/kg))	Cadmium (mg/kg))	Nickel (mg/kg)	Mercury (mg/kg)
UPDB vs. PDB	0.940	0.029	0.912	0.001	0.043	0.879
UPDB vs. Co-compost	0.075	0.041	0.971	<0.001	0.121	0.347
PDB vs. Co-compost	0.280	0.579	0.940	0.005	0.031	0.246

Mann–Whitney U test, nUPDB = nPDB = nCo-compost = 10, and α = 0.05. Values in bold indicate significant differences.

. Figure 6 illustrates the distribution of these elements across the three faecal sludge treatment processes.

There was significant variation in the concentrations of several heavy metals across treatments, particularly for lead and cadmium (p < 0.05), indicating that both the treatment method and input materials influenced the metal content (Table 5). The UPDB samples contained the lowest concentrations of Pb (26 mg/kg) and Cd (1.32 mg/kg) compared to PDB (Pb: 40 mg/kg, Cd: 2.07 mg/kg) and co-compost (Pb: 40 mg/kg, Cd: 3.10 mg/kg) (Supplementary Materials, Table S1), with significant differences observed among them (p < 0.05). The elevated levels in the co-compost are likely attributed to the varied feedstock materials used. The nickel levels also varied significantly, with PDB showing higher concentrations (31 mg/kg) than both UPDB (25 mg/kg) and co-compost (18 mg/kg) (p = 0.04 and p = 0.03, respectively). Arsenic, mercury, and chromium showed more consistent distributions, although occasional outliers were observed, particularly for nickel and chromium in the PDB and mercury in the co-compost (Figure 6). Despite the observed variability, all heavy metal concentrations remained within the permissible limits set by the Fertiliser Control Order (FCO) 2016 [26].

These findings highlight the influence of feedstock composition and operational control on heavy metal concentrations, especially in co-composted sludge. Variability in municipal waste inputs, insufficient screening of inorganic materials, and inconsistent composting conditions (e.g., moisture and temperature) may introduce fluctuations in the final metal content. Hence, routine heavy metal monitoring and batch-level profiling are essential to mitigate the long-term risks associated with cumulative metals such as cadmium and mercury [65].

The characteristics of faecal sludge are influenced by various factors such as sludge age in containment systems, emptying practices, connection to sewer networks, mixed wastewater streams, or only black water [66]. In co-composting, the variability in municipal wet waste feedstocks, composting conditions, and operational controls can introduce inconsistencies in final product content. For large-scale agricultural use, particularly in food crop systems, establishing standardised quality assurance protocols is essential to minimise health risks while maximising nutrient recovery.

4. Conclusions

This study evaluated treated faecal sludge from three commonly used nature-based treatment systems in developing regions—unplanted drying beds, planted drying beds, and co-composting—with a focus on their agricultural suitability. The findings demonstrate that treatment processes significantly influence sludge composition, particularly in terms of organic carbon, nitrogen, potassium, conductivity, and heavy metal concentrations. These compositional differences carry important implications for nutrient recovery, soil fertility, and the determination of safe and effective application rates.

A key challenge identified is the variability in sludge quality, particularly in co-composting systems, where differences in feedstock composition and composting conditions influence the consistency of the nutrient and metal content. This underscores the importance of characterising the final treated sludge and standardising treatment methods to ensure product quality and safety in agricultural use.

The study findings showed that faecal sludge products met most of the specifications outlined by the Fertiliser Control Order (FCO) in India, supporting their safe use in soil application. To enhance adoption, we recommend implementing faecal sludge treatment plant (FSTP)-level quality assurance protocols, including batch-wise nutrient profiling and heavy metal screening, prior to field application.

In addition, co-compost products could be promoted under the existing city compost marketing framework. Providing incentives or subsidies for farmers using co-compost, along with extending compost marketing assistance to include faecal sludge-derived products, would further support market uptake. Market development assistance for direct sales and co-branding with fertiliser companies could help integrate faecal sludge products into mainstream agri-input supply chains.

Beyond nutrient value, the broader implications of this research lie in the potential of treated faecal sludge to support sustainable agriculture by reducing the dependence on chemical fertilisers, enhancing soil health, and closing nutrient loops. However, scaling up its use requires the development of regulatory frameworks, nutrient quality benchmarks, and faecal sludge-specific guidelines for safe land application, particularly in contexts like India where such standards are still lacking. Furthermore, establishing basic certification schemes for treated sludge products would help build end user confidence and promote adoption. Policy frameworks should also incorporate monitoring protocols tailored to nature-based systems, accounting for their operational variability and regional feedstock characteristics.

Future research should assess the fate of pathogens, antibiotic resistance genes, and emerging contaminants in treated faecal sludge across different treatment technologies. This study lays the ground work for the further exploration of advanced options, such as electromechanical, thermal, and vermi-based treatment systems, which will be important for expanding the safe and context-appropriate reuse of faecal sludge. The evidence presented in this study contributes towards advancing both scientific understanding and policy development in the field of faecal sludge application.