Qualitative assessment of compost engendered from municipal solid waste and green waste by indexing method

ABSTRACT

The present study aims at quantification of the quality of three varieties of composts made from municipal solid waste, green waste and combined waste by critically evaluating their physicochemical attributes, effect on soil fertility and metal pollution risk. Each waste type was treated with effective micro-organisms to compare the compost quality using Quality Control Indices. The effect of microbial consortia on the wastes was prominent resulting in decreased pH levels and increased electrical conductivity. C/N ratio ranged between 14–24 for waste composts without microbial treatment, and 8–11 for microbial treated wastes. The fertility parameter was observed to be more in microbial treated waste composts. Also, heavy metals concentration in waste compost without effective microbial treatment was higher than the types given EM. Based on the fertility and clean indices, the treated and untreated municipal solid waste and combined waste compost belonged to class RU-1 and class D, respectively. Moreover, compost prepared from treated and untreated green waste belonged to classes B and C respectively. In general, the prepared CW and GW composts have medium to high fertilizing potential and are fit for domestic as well as commercial use. However, MSW compost is not fit for agricultural purposes as it didn’t improve soil fertility to a greater extent but can be used as a soil conditioner in limited quantity as it can cause metal toxicity. For this reason, proper segregation of inputs at the start of a composting process is necessary to improve its quality before being put to agricultural use as any unbalanced or unchecked content of mixed waste will affect the overall compost quality.

Implications: Significance of the work: The research dealt with different combinations of segregated wastes to analyze the best fit solid waste compost. Experiments were conducted on the actual landfill site area to simulate the conditions for the process. The manuscript provides evidence and other facts advocating the use of composting for waste management and ultimately reducing pollution caused by landfilling. It ought to cause a multiplier effect if the same is to be followed in other parts of the world, and thus working our way toward getting the Smart city project to fruition. The results of the study exhibit the differences in physiochemical nature of various types of composts. A treatment of microbial consortium with restrictions enabled a conducive atmosphere in the colonies to thrive faster and initiate the process of decomposition. We observed that treated samples converted faster into compost as compared to non-treated samples. We also observed the effect of treatment on fertility parameters of prepared compost samples. In general, it was found that the organic carbon and C/N ratio declined while the total nitrogen and total potassium was observed to increase with very little to no change in phosphorous content, with the inoculation of beneficial micro-organisms throughout the composting course. A reduction in the heavy metal levels was observed in samples treated with active micro-organisms. The compost classification into A, B, C, and D classes represents the quality of compost and further use in agricultural land on commercial levels. The quality index values were determined highest for green waste compost (GWC). The municipal solid waste compost (MSWC) exhibited lowest index values. Therefore, based on the quality index values, the utilization of GWC will aid in reutilizing the green waste and in boosting soil fertility and reduce the waste quantity generation rates. It’s also necessary to make compost making widespread among the farmers for a sustainable environment. The GWC has been considered as a sustainable option of waste management, being economically and ecologically viable.

Introduction

Municipal solid waste (MSW) collection and disposal is becoming more of an unmanageable and mounting problem at a global level (Alfaia, Costa, and Campos 2017). Socio-economic status, population density, and climate of a place are directly linked to the quantity and quality of MSW generation (Lee 2020; Xu, Victor, and Greenfield 2008). Massive amounts of MSW are produced daily, and a lack of appropriate low-cost technologies for its onsite treatment leads to uncontrolled dumping that is one of the main reasons for the degradation and instability of life-supporting environments (Bundela et al. 2010; Kumar et al. 2009; Makarichi et al. 2018). Poor MSW management poses high risk to public health especially in the developing countries like Africa (EMP 2003; Dladla, Shale, and Shale 2016), Cambodia (Seng, Fujiwara, and Spoann 2018), Thailand (Chiemchaisri, Juanga, and Visvanathan 2007) and many Southeast Asian countries viz., Nepal, Pakistan, Bangladesh, Sri Lanka and India respectively (Sharma, Ganguly, and Gupta 2018). It is reported that approximately 90% of waste generated in India is dumped in open fields (non-engineered landfills) leading to environmental pollution (Rana, Ganguly, and Gupta 2017) and posing serious health hazards (CPCB (Central Pollution Control Board) 2012; Rana, Ganguly, and Gupta 2018) while as disposal by composting accounts for only 5 to 6% (Gómez et al. 2008). The adeptness of India toward waste management practice is inadequate and crawling (Sharma, Ganguly, and Gupta 2019a.). In addition to this non-segregation of wastes and inaccurate methodology of composting techniques being carried out results in production of low quality compost thereby in hampering of its use as soil conditioner (Rawat, Ramanathan, and Kuriakose 2013; Saha, Panwar, and Singh 2010).

Currently, there are various emerging technologies that play a pivotal role for the better management of the MSW to neutralize their toxic effects and improve recovery for further uses (Athira, Bahurudeen, and Vishu 2020; Mbuligwe et al. 2002). The most capable MSW managing strategies include separation at source, valuable materials collection and recovery, volume reduction, composting and recycling (Drimili et al. 2020; Mbuligwe et al. 2002). Among them, composting for the management of biogenous constituents of MSW enhance the environmental quality and stability (Hashemimajd et al. 2004; Yourtchi, Hadi, and Darzi 2013). Compost is a good source of nitrogen, phosphorous and potassium (NPK), and micronutrients (copper, iron, and zinc) for plants (Malakahmad et al. 2017; Manohara, Belagali, and Ragothama 2017) and a stable soil conditioner (Ingelmo et al. 2012; Kabirinejad and Hoodaji 2012). In addition, compost in agricultural land is a low-cost alternative to open landfill disposal of MSW (Sharma, Ganguly, and Gupta 2018).

Composting MSW is a crucial subject for sustainable agricultural practices and effective resource management in India. Currently, the quality control rules for compost in India are not satisfactory in labeling general compost quality using existing empirical methods (Charnay 2005), self-heating test (FCQAO 1994) and Solvita® test (Brinton and Evans 2000). It is expected that classification of composts for its different applications such as growing of a high-value crop, food crops, non-food fiber, soil conditioner, and the establishment of lawns and reclamation/rehabilitation of mining areas should be well-elaborated (Mandal et al. 2014).

Therefore, quality control indices like fertility index (FI), and clean index (CI), are exercised to evaluate the overall quality of compost and their use in agricultural, remediation and reclamation activities (Saha, Panwar, and Singh 2010). Also, it aids in compost grading and identifying the correct compost use according to the quality grade. In present study, FI was evaluated using total organic content (TOC), N, P, K, C: N ratio. These parameters are assigned to a score value and a weighting factor based on the scientific knowledge on their role in improving soil productivity. CI was determined by considering the concentration and available information on known biological functions in organisms and the phytotoxicity and mammalian toxicity potential of the concerned metal. The superiority of MSW compost hinges on the waste configuration (Mandal et al. 2014; Saha, Panwar, and Singh 2010). Keeping in view the location, population, climate, fragile nature of the region, and composition of generated MSW in view, the current study focused on the characterization and classification of compost in accordance to fertilizing and polluting potential of the treated and untreated compost prepared from MSW, combined waste (CW) and green waste (GW) generated in Srinagar City.

Materials and methods

Study area

Srinagar is the summer capital of Jammu and Kashmir, the northernmost state of India. The city is situated at a geographical location point of 34°5′23″N; 74°47′24″E and an elevation of 5400 m (AMSL). Currently, Srinagar Municipal Corporation (SMC) has the mandate to conduct civic amenities in the city.

Quantity of MSW generated in Srinagar City

The MSW generated in Srinagar city is around 236,733 tons yearly, at a rate of approximately 435 tons/day during summer and 350 tons/day in winter. The standard normative estimation for the daily MSW generation in 2016 was 668 tons at an average daily per capita rate of 650 g with a varied waste constituent composition; compostable (biogenous) fraction (53.8%), recyclable (15.9%), and zero value waste (30.3%) (Table 1a). The chemical characteristics of waste at source and trenching ground are presented in Table 1b (SMC, 2016).

Table 1a. A comparative analysis of MSW generated in Srinagar

Waste constituent	CPCB – NEERI*	ERA**	TTPL	Average
Biogenous	61.77% (WM)	58.5%	41.19%	53.82%
Recyclables	17.76%	10.3%	19.54%	15.87%
Inert	20.47	31.2	39.27%	30.31%
Moisture	30% (WM)	25.88%	–	43%
Calorific value	1264 kcal/kg	1579 kcal/kg	–	1421 kcal/kg

*Central Pollution Control Board-National Environmental Engineering Research Institute, **Economic Reconstruction Agency (J&K) and TTPL: Tide Technocrats Private Limited

Table 1b. Chemical characteristics of waste at source and trenching ground

Location	Moisture (%)	Volatile solids %	C %	H %	N %	O %	S %	P2O5%	Ash %	Calorific Value Kcal/Kg	C/N ratio
At source	32.27	40.42	28.80	6.85	1.09	48.95	0.66	0.78	12.06	1800.93	27.03
At trenching ground	25.88	45.00	28.28	6.23	1.25	52.36	0.64	0.68	9.79	1579.43	23.47

The majority of this generated MSW typically remains scattered in open areas, which poses a danger to the health and quality of surrounding soil, water, and air (Kansal 2002). In the rainy season, MSW chokes drains making stagnant water a breeding ground for insects (Alam and Ahmade 2013)

Sample collection and preparation

After collection, waste was shifted for composting in a covered shed (shaded area) to protect it from rain and direct exposure to the sunlight. The composting was carried out by an open windrow composting method. Experimental setups established in the form of compost windrows (1 m³) enriched with bio-agents. Investigated parallel controls for each sampling waste viz., municipal solid waste, green waste, and combined waste was formed. Four replications were measured in each experiment using a randomized block design. The particulars for the effective micro-organisms enriched input mixtures are mentioned in Figure 1. The Shalimar microbial consortium used in our study was a mixture of lab prepared and locally isolated microbial strains of Pseudomonas, Azotobacter, and Bacillus genus.

Figure 1. Composition particulars in case of enrichment of input-mixtures by effective micro-organisms.

Water was applied to each setup until the moisture levels reached 60% in every compost heap. Sustaining of adequate moisture content and averting of excessive heat loss was ensured by covering the mounds of the composting matter with polythene sheets. The moisture levels were checked regularly and retained at 50–60% by adding water during the composting period. The assortments were turned at 3-day intervals to uphold porosity. The temperature was assessed randomly at different depths every day. After the visual and hand feel test, compost samples were drawn from pure windrows after 90 days and enriched windows after 75 days for analyzing physicochemical attributes. The representative samples (200 g from each compost type) were collected from the piles in air-tight polythene bags post mixing, followed by labeling. The samples were transferred to the laboratory and stored at 4°C for the supplementary examination. Samples were parched at room temperature, homogenized, sub-sampled by quartering, and crushed to pass through a 2 mm sieve. These samples were further subsampled for additional investigation.

Sample analysis

For analyzing quality parameters like pH, EC, TOC, N, P, and K, standard methods prescribed in APHA (2005) were adopted.

For the detection of heavy metals (cadmium, lead, zinc, copper, nickel, chromium), compost samples were dried at 105°C and then digested in a mixture of (5:1 v/v) of di-acid (HNO₃ and perchloric acid) solution and were analyzed using atomic absorption spectrophotometer (Agilent technologies USA, model 240FF) as per APHA (2005) standard procedures.

Fertility and clean index

Fertilizing potential and pollution potential can be used as a tool for quantitative evaluation of the quality of composts produced from municipal solid wastes (Saha, Panwar, and Singh 2010). The standards for “weighing factor” to fertility and heavy metal limits and “score value” for compost samples are listed in Table 2.

Table 2. Criteria for allocating “weighing factor” to fertility parameters, heavy metals, and “score values” to analytical data

Fertility parameters (% dry matter)	Score Value (Si)						Weighing factor (Wi)
	5	4	3	2	1	0
TOC	>20.0	15.1–20.0	12.1–15	9.1–12	<9.1	-	5
TN	>1.25	1.01–1.25	.81–1.0	0.51–0.80	<0.31	-	3
TP	>.60	0.41–0.60	0.21–0.40	0.11–0.20	<0.11	-	3
TK	>1.00	0.76–1.0	0.51–0.75	0.26–0.50	<0.26	-	1
C:N	<10.10	10.1–15	15.1–20	20.1–25	>25	-	3
Heavy metal (mg/kg DM)
Zn^2+	<151	151–300	301–500	501–700	701–900	>900	1
Cu^2+	<51	51–100	101–200	201–400	401–600	>600	2
Cd^2+	<0.3	0.30–0.60	0.70–1.0	1.10–2.0	2.0–4.0	>4.0	5
Pb^2+	<51	51–100	101–150	151–250	251–400	>400	3
Ni^2+	<21	21–40	41–80	81–120	121–160	>160	1
Cr^3+	<51	51–100	101–150	151–250	251–350	>350	3

The fertility index (FI) of compost samples was calculated by using Equation (1)(1) $\frac{FI=(\sum _n^{(j=1)}{S}_i{W}_i)}{(\sum _n^{(j=1)}{W}_i)}$(1) (Saha, Panwar, and Singh 2010).

(1) $\frac{FI=(\sum _n^{(j=1)}{S}_i{W}_i)}{(\sum _n^{(j=1)}{W}_i)}$(1)

Where “Si” is the score value and “Wi” is the weighing factor of the i^th fertility parameter of analytical data. A higher index represents higher fertilizing potential of compost for its use in soils for enrichment.

Similarly, the clean index (CI) was calculated by applying the Equation (2)(2) $\frac{CI=(\sum _n^{(j=1)}{S}_i{W}_i)}{(\sum _n^{(j=1)}{W}_i)}$(2) (Saha, Panwar, and Singh 2010).

(2) $\frac{CI=(\sum _n^{(j=1)}{S}_i{W}_i)}{(\sum _n^{(j=1)}{W}_i)}$(2)

Where S_j is the score value and W_j is the weighing factor of the j^th heavy metal of analytical data.

Composts with higher heavy metal concentrations attain lower value of clean index.

The summary of the research work is presented in pictorial form in Figure 2.

Figure 2. Pictorial summary of research work.

Results

Chemical characterization of MSW compost

The results obtained from each compost sample analysis were given in Table 3. The pH observed in the compost with effective microorganisms (EMs) varied from 7.28 and 8.45, while for without EMs compost, pH ranged between 8.36–8.75. On comparing the pH value with the FCO standards, the pH was found to be higher for a good number of compost samples. A general decrease in pH level was observed in compost samples treated with EM. EC for compost with EM ranged from (0.72– 1.39 dS/m), and for compost without EM it varied between (0.53–1.08 dS/m). Electrical conductivity (EC) of different composts treated with EM was observed to increase compared to EM untreated composts. EC levels in all compost samples (with and without EM) were well within the acceptable ranges of the FCO benchmark.

Table 3. Nutrient status and heavy metal content of the different compost combinations generated from MSWC, CWC and GWC

Parameters	MSWC		CWC		GWC		*FCO-2003
	Without EM	With EM	Without EM	With EM	Without EM	With EM
	Mean ±SD	Mean ±SD	Mean ±SD	Mean ±SD	Mean ±SD	Mean ±SD
pH	8.36 ± 0.06	7.90 ± 0.26	8.43 ± 0.28	7.28 ± 0.17	8.75 ± 0.19	8.45 ± 0.13	6.5–7.5
EC(dS/m)	0.53 ± 0.018	0.909 ± 0.024	1.08 ± 0.04	1.39 ± 0.0344	0.590 ± 0.034	0.720 ± 0.03	<4
TOC (% DM)	17.0 ± 1.09	13.00 ± 0.88	13.75 ± 1.71	13.60 ± 1.95	10.88 ± 0.85	5.25 ± 0.13	>12
N (% DM)	1.0 ± 0.03	2.00 ± 0.80	1.13 ± 0.10	1.66 ± 0.12	0.57 ± 0.06	1.01 ± 0.03	>0.8
P (% DM)	1.32 ± 10.80	0.98 ± 13.82	1.11 ± 91.29	1.03 ± 96.26	2.19 ± 281.3	1.77 ± 18.25	>0.4
K (% DM)	0.84 ± 0.06	0.84 ± 0.06	0.79 ± 0.02	0.81 ± 0.04	0.77 ± 0.04	0.79 ± 0.02	>0.4
C/N	16 ± 0.80	8 ± 0.50	14.±0.96	8 ± 0.5	24 ± 1.11	11 ± 0.53	20
Heavy metals (mg/kg DM)
Zn^2+	183.00 ± 2.75	154.00 ± 1.36	166.00 ± 1.08	73.00 ± 2.32	90.00 ± 1.26	75.13 ± 2.10	≤1000
Cu^2+	494.00 ± 4.99	391.00 ± 1.12	267.00 ± 6.22	135.00 ± 7.33	200.00 ± 6.06	165.00 ± 33.67	≤300
Cd^2+	3.00 ± 0.65	2.00 ± 0.66	2.20 ± 0.62	2.00 ± 0.63	1.00 ± 0.89	0.90 ± 1.07	≤5
Cr^3+	83.00 ± 1.00	79.00 ± 1.29	85.00 ± 0.84	81.00 ± 0.41	45.00 ± 1.25	35.13 ± 1.55	≤50
Ni^2+	18.00 ± 0.66	15.0 ± 0.51	11.00 ± 0.72	8.00 ± 0.95	8.00 ± 0.99	5.70 ± 1.19	≤50
Pb^2+	10.00 ± 1.19	10.00 ± 1.47	6.00 ± 0.62	6.00 ± 0.55	1.00 ± 0.01	1.00 ± 0.01	≤100

*Fertilizer Control Order of India (FCO, 2003), SD = Standard deviation, MSWC: Municipal solid waste compost, CWC; Combined waste compost and GWC: Green waste compost.

Nutrient content

The data obtained from analyzed compost samples showed that the TOC was highest (16.50%) for municipal solid waste compost followed by combined waste compost (CWC) 13.75% and lowest (10.88%) for green waste compost (GWC) without effective microorganisms (EM) treatment. The TOC of compost with EM showed incongruity as the highest value (13.60%) was obtained for CWC and lowest (5.25%) for GWC. The TOC was well within the range for all samples except GW compost. Furthermore, the total nitrogen increased for the composts treated with EM, within a range of 1.01 to 2.0%. It also varied between 0.57–1.13% in case of waste compost without EM treatment. Total nitrogen content on comparing with FCO values showed all are within acceptable ranges except for untreated GWC. Total phosphorus (TP) levels were observed between 0.11–0.22% in different compost types without EM treatment and ranged from 0.010 to 0.17% for composts which were treated with EM.

A clear difference was observed among values of total potassium (TK) with a range between 0.77–0.84% obtained for different waste composts without EM treatment and 0.79–0.84% in the case of waste composts with treated with EM (Table 3). C/N ratio is a vital consideration for the development of good quality compost and in the current study it was revealed that this ratio obtained from different waste composts had remarkable differences between them. It was observed to be varying between 14–24 for EM untreated waste composts while for EM treated waste composts the values were ranging from 8–11. In general, the C:N ratio was low for most compost samples.

Heavy metal contamination in composts

A total of six metals (Zn²⁺, Cu²⁺, Ni²⁺, Cr³⁺, Cd²⁺ and Pb²⁺) were analyzed in all the prepared compost types (Table 3). The range of concentrations for different metals in different compost categories with EM are as follows: Cd²⁺ (1.89–2.38 mg/kg DM), Pb²⁺ (6.15–10 mg/kg DM), Ni²⁺ (9.70–15.0 mg/kg DM), Cr³⁺ (69.13–80.88 mg/kg DM), and Cu²⁺ (73 to 153.70 mg/kg) DM. Likewise heavy metals content in compost types without EM treatment are as following: Cd²⁺ (2.2–2.86 mg/kg DM), Pb²⁺ (1.00–10.25 mg/kg DM), Ni²⁺ (11.35–18.28 mg/kg DM), Cr³⁺ (83.35–90.03 mg/kg DM), Zn²⁺ (139.83–183.25 mg/kg DM), and Cu²⁺ (267–494.25 mg/kg DM). On comparing the metal concentration values with the FCO standards, the metal concentration was well within the acceptable limits except for Cu²⁺, in both treated and untreated (MSW) compost and Cr³⁺ in MSW and combined waste compost.

FI and CI values

The FI and CI values of different waste compost with and without EM treatment are presented in Table 4. The calculated FI value for all compost types varied between 2.2 to 3.47 and exhibited the highest value (3.47) for GWC (with EM). Furthermore, the CI value observed was within the range of 2.80 to 4.06, with the highest value (4.06) observed for GWC with EM.

Table 4. Fertility and clean index determined from different treatments for degradation of different waste categories for their marketability and applicable in different areas

Compost category	Treatments	FI	CI	Class	Remarks
MSWC	Without EM	2.73	2.80	RU-1	Poor quality
	With EM	2.21	3.00	RU-1	Poor quality
GWC	Without EM	3.13	4.01	C	Good quality
	With EM	3.47	4.06	B	Very good quality
CWC	Without EM	3.27	3.00	D	Medium quality
	With EM	3.17	3.20	D	Medium quality
Standard
Quality Control Compliance
Complying for heavy metal parameters		>3.5	>4.0	A	Best quality. “High manurial value potential and low heavy metal content and can be used for high-value crops, such as in organic farming”
Complying with heavy metal parameters		3.1–3.5	>4.0	B	Very good quality. “Medium fertilizing potential and low heavy metal content”
Complying with heavy metal parameters		>3.5	3.1–4.0	C	Good quality. “High fertilizing potential and medium heavy metal content”
Complying with heavy metal parameters		3.1–3.5	3.1–4.0	D	Medium quality. “Medium fertilizing potential and medium heavy metal content”
Complying with heavy metal parameters		<3.1	–	RU-1	“Should not be allowed to enter market due to low fertilizing potential. However, these can be used as soil conditioners”

Discussions

The decrease in pH level was observed in EM treated compost samples due to ammonification and biomineralization of organic matter by the microbial activities (Pathak et al. 2012). The optimum pH for quality compost ranges from 6.5 to 7.5 (FCQAO 1994). Electrical conductivity (EC) is an important parameter to determine the quality of compost for its application as a soil conditioner. The application of EM had a relational impact on EC, which directly affected the mineralization of compost samples. Application of commercial microorganism consisting of consortia of beneficiary microbes appeared to increase the process of biomineralization (Jusoh, Manaf, and Latiff 2013).

Nutrient content

Fertility parameters like TOC and NPK were observed in all the prepared compost samples for agricultural purposes. These factors are indispensable to understand the compost characterization for its successfully application as a fertilizer. Observing the effect of EM treatment on fertility parameters of prepared compost types TOC and C/N ratio were seen to be declined generally in all compost types. In contrast, TN and TK levels were increased while as there was no change observed in phosphorous content throughout the composting course. The increase in nutrient content in compost is a direct result of applying microbial consortia, which enhanced the bio-mineralization of organic wastes (Rastogi, Nandal, and Khosla 2020). The carbon loss is observed because of the emission of CO₂ by the metabolic activities of microbes as well as from the decomposition process (Benito et al. 2003). Adding microbial inoculants improved the N levels (Pan, Dam, and Sen 2012).

Rahman et al. (2015) also observed a greater diminution in the TOC levels, C/N ratio and an increase in levels of total NPK content in the compost that supports the current study. Increased N levels were seen when mechanized compost was inoculated with Azotobacter and rock phosphate as reported by various authors (Rastogi, Nandal, and Nain 2019; Wang et al. 2016; Yang et al. 2015). Moreover, the process of inoculation of EM improves the nutrient levels of compost by increasing biomineralization (Fersi et al. 2019).

Heavy metal contamination in MSW composts

A decrease in the heavy metal content was observed in composts treated with EMs but the decrease did not exhibit any significant pattern. Microbial biomass provides a sink for intracellular aggregation or precipitation of metal compounds in and around cells (Fomina and Skorochod 2020; Gadd 2007), hyphae or other structures through biosorption to cell walls (Baldrian 2003), pigments, and extracellular polysaccharides (Fomina et al. 2007a, 2007b). Most microbial materials act as effective absorbent for metals (Aryal 2020; Wang and Chen 2009) and therefore microbial transformations of metals and minerals have the potential for pollution remediation (Igiri et al. 2018; Tarekegn, Salilih, and Ishetu 2020).

FI and CI values

According to FI and CI value, the classification of MSWC is based on marketability and usage. The compost classification into A, B, C, and D classes represent the quality of compost and their potential for agricultural use on a commercial level (Saha, Panwar, and Singh 2010). The index values were exhibited to be highest for compost made from green waste. Since, green waste compost (GWC) was prepared from the organic waste, comprising mainly of fruits, vegetables and straws as fertilizing agents. Furthermore, GWC was not mixed with any other type of solid waste therefore a negligible contamination by heavy metals (HMs) was observed (Corral-Bobadilla et al. 2019). MSWC exhibited the lowest index values (FI and CI).This could be due to metallic contamination and low content of organic ingredients. It is pertinent to mention that MSW contains a considerable concentration of HMs (Farrell and Jones 2009; Holanda and Johnson 2020).

Further, the compost prepared from mixed waste in the proportion of 1:1 had FI and CI values lower in comparison to GWC but higher than MSWC. This could be due to addition of some contaminants into it from municipal waste, thereby resulting in decrease of the value of quality index (Sahay et al. 2019). Comparing the values with the prepared MSW compost in Delhi (India), which has fertilizing potential (FI value<4) but also has heavy metal polluting potentials (CI value < desired value) due to excess heavy metal concentrations and not fit for any use (Mandal et al. 2014; Sharma, Ganguly, and Gupta 2019b). Saha, Panwar, and Singh (2010) analyzed compost from 36 cities and found that the fertilizing index varied from 1.8 to 4.2 with no significant difference between compost from big and small cities and found source-separated waste compost having 26% FI index and 35% CI. Likewise, composts prepared from source-separated biogenous wastes had the highest CI value, followed by partially segregated wastes (3.1) and mixed wastes (2.3).

Conclusion

Classifying compost based on fertilizing potential (FI) and pollution potential (CI) can be useful for identifying the quality grade of marketable compost. It could be helpful in providing information regarding the feasibility of prepared municipal compost for agricultural use and the compulsory treatment level afore applying. EM inoculated compost attains better quality and maturity with a less processing time. Compost quality is essentially computed to confirm the toxicity potential of compost toward plant. A number of heavy metals (from electronic and electrical waste mostly) can end up in compost accidentally. The probability of heavy metal presence in the compost is more when mixed or incompletely separated waste is administered in the compost windrow. In our study, the average concentrations of zinc, cadmium, lead, and nickel for different waste composts were within the acceptable ranges of the FCO criterion, although the average concentrations of copper and chromium surpassed the allowed limits of the FCO benchmark. In general, this study showed that the compost prepared from different waste types (GW, CW) have the medium quality to use while the compost from partially separated MSW is poor in quality to be used for agriculture. Composting with a mixture of reducing reagents and chelating reagents might intensify the eliminating efficacy of heavy metals from compost. But managing and utilizing the waste benefice more in a broader sense. Biological aerobic stabilization of organic matter can also be performed to obtain a product that can be beneficially applied to soil and agricultural land or to stabilize organic wastes of “not enough good quality” to be safely sent to a landfill. The utilization of green waste compost (GWC) will aid in reutilizing the green waste and boosting soil fertility, and reducing the waste quantity generation rates and burden on open landfills. It’s also necessary to make compost production widespread among the farmers for a sustainable environment and for controlling unmanageable waste, which otherwise is a breeding ground for animals as well as diseases. GWC has been considered as a sustainable option of waste management, being economically and ecologically viable.

Nomenclature

Table

MSW	Municipal Solid Waste
GW	Green Waste
CW	Combined Waste
MSWC	Municipal Solid Waste Compost
GWC	Green Waste Compost
CWC	Combined Waste Compost
FCO	Fertilizer Control Order
EM	Effective Micro-organisms
SMC	Srinagar Municipal Corporation
CI	Clean Index
FI	Fertility Index
TOC	Total Organic Carbon
C: N ratio	Carbon: Nitrogen Ratio
NPK	Nitrogen, Phosphorous, Potassium
EC	Electrical Conductivity
NEERI	National Environmental Engineering Research Institute
TTPL	Tide Technocrats Private Limited
ERA	Economic Reconstruction Agency
CPCB	Central Pollution Control Board
MT	Metric ton
SW	Solid waste

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary material

Supplemental data for this paper can be accessed on the publisher’s website.

Additional information

Notes on contributors

Mehvish Hameed

Mehvish Hameed a College of Agricultural Engineering, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India.

Rouf Ahmad Bhat

Rouf Ahmad Bhat Division of Environmental Science, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India.

Bashir Ahmad Pandit

Bashir Ahmad Pandit College of Agricultural Engineering, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India.

Shazia Ramzan

Shazia Ramzan Division of Soil Sciences, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India.

Zulaykha Khurshid Dijoo

Zulaykha Khurshid Dijoo Department of Environmental Science/ Center of Research for Development, University of Kashmir, Jammu and Kashmir, India.

Mushtaq Ahmad Wani

Mushtaq Ahmad Wani Division of Soil Sciences, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India.