Characterization and Statistical Analysis of Municipal Solid Waste for Recognising Suitable Waste Management Approach: A Case Study in the Semi-Urban Region of Thanamandi, J&amp;K, India

doi:10.21203/rs.3.rs-3559449/v1

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Characterization and Statistical Analysis of Municipal Solid Waste for Recognising Suitable Waste Management Approach: A Case Study in the Semi-Urban Region of Thanamandi, J&K, India

https://doi.org/10.21203/rs.3.rs-3559449/v1

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Solid waste is any material that is solid and has been discarded by the owner or user for being useless. According to estimates, 2.24 billion tonnes of solid garbage will be produced worldwide and 6–8 tonnes in the study area by the year 2024. Therefore, it is important to manage solid waste in a scientific manner. Thus, this study aims are to estimate the MSW generation rate in Thanamandi town, including the composition and statically represent the data obtained and possible solid waste management approach. It has been observed from the obtained result that 0.44kg per/c/day of solid waste has been generated from the study area out which vegetable waste is maximum followed by food waste and plastic. The obtained results of characterization of solid waste further used for development of interpolation maps. It suggested that recyclable waste has been generated in the area where high income group people are living in comparison to moderate- or lower-income groups. In addition, statistical analysis shows strong interrelation between vegetable and food waste as well as paper waste and plastic waste. Thus, to manage solid waste in the study area a holistic approach to solid waste management is required to deal with mixture of vegetable and food waste i.e., organic matter.

Solid Waste

Characterization

Statistical Analysis

Semi-Urban Area

Intensity Map

Solid waste is any material that is solid and has been discarded by the owner or user for being useless. Further, it can also be defined as waste products from animal, plant, or human activity that are disposed off. Urban solid waste is a mixture of household, construction waste, commercial wastes, hospital wastes etc (Sridevi et al., 2012). According to estimates, 2.24 billion tonnes of solid garbage will be produced worldwide year 2024. The annual trash generation is anticipated to rise by 73% from 2020 levels to 3.88 billion tonnes in 2050 due to growing urbanization and population growth. It is important to manage solid waste in scientific manner. Solid waste management is therefore the act of collecting, handling, and discarding solid waste that has been remaining because it has fulfilled its purpose and is no longer required (Abdel-Shafy and Mansour, 2018).The lack of efficiency of waste management practices leads to health hazards, unsightliness, blockage of drainage, unpleasantness. As population is increasing day by day the problem of waste disposal are becoming complex(Alam and Ahmade, 2013). Additionally, managing solid waste is challenging because of the population's rapid rise(Choudhary and Choudhary, 2019). Further, uncontrolled burning of MSW leads to urban air pollution(Harir et al., 2015). In addition, inadequate solid waste disposal is one of the main issues that developing nations is facing(Li et al., 2019).There are generally 3 methods for the disposal of MSW(Sharholy et al., 2008)includes sanitary landfill, incineration and recycling.

The lack of efficiency of proper waste disposal leads to health hazards, unsightliness, blockage of drains, unpleasantness(Duhan, 2022)(Giusti, 2009). In semi-urban areas, MSW can cause flooding during rainy season ,clog sewers and produce stagnant water for insect breeding(Ajmal, Tarar and Arshad, 2016). Many studies have been done on solid waste generation and its composition in various parts of India by various researchers but not much attention seems to have paid to the rapidly increasing solid waste in semi-urban boarder area. This study has been conducted in the semi-urban boarder area of J &K, India. The goal of this study is to estimate the MSW generation rate in Thanamandi town, including classification, composition, and statistical representation, as well as a viable solid waste management strategy for the studied area.

Study area, instrument used and analysis procedure have been discussed in the subsequent section of methodology.

2.1 Study Area

This study has been conducted on the Thanamandi area of District Rajouri. In the Union territory of Jammu & Kashmir's Rajouri district, Thanamandi is both as a town as well as municipal committee. In 2011 the total population of Thanamandi town is 62,283 that reaches upto 79,722 in 2022. It lies on 23 Kms away from Rajouri district lies on the Mughal Road between Rajouri and Bufliaz. Total area of Thanamandi tehsil is 149 km² including 144.51 km² rural area and 4.18 km² of urban area shown in Fig. 1.

2.2 Sample Collection

House to house collection system has been adopted for collection of solid waste from different area of study area. About 10Kg of municipal solid waste is collected from 25 pre-selected locations of Thanamandi town as shown in Fig. 2. The total amount of waste so collected is mixed thoroughly and then segregate in a proper appropriate manner. Further, the waste has been segregated on the basis of different composition of plastic waste, vegetable waste, fruit waste etc and finally calculates the total moisture content. The nature of solid waste is extremely diverse, and its composition varies with time and place(Katiyar, Suresh and Sharma, 2013)(Vijayakumar, Rao and Sivasubraminiyan, 2019).Whencollecting samples of municipal solid waste major collection sites are identified which arecovering a larger size of population in Thanamandi town.

2.3 Analysis Procedure

Segregation of solid waste has been done and then moisture content has been calculated for the collected solid waste. In addition, interpolation maps have been developed by using software Qgis. Furthermore, statistical analysis has been done for the analysis of result.

2.3.1 MSW Segregation

Segregation of waste is the process of separating different types of waste materials at the source or point of generation. It involves categorizing waste into different groups based on its composition and characteristics. Proper waste segregation is crucial for effective waste management and enables recycling, composting, and appropriate disposal(Zhang et al., 2022). Here are some common categories for waste segregation

2.3.2Moisture Content

The amount of water that is contained in solid waste is commonly referred to as its moisture content. It is a crucial factor to consider in waste management and can affect various aspects of waste handling, processing, and disposal. To assess the moisture content of solid waste, various methods can be used, such as gravimetric analysis, moisture meters, or moisture content estimation based on waste composition(Cheng and Hu, 2010). Therefore, understanding the moisture content of solid waste in your specific region or waste stream is essential for effective waste management and process optimization(Gu et al., 2017).

Characterization of solid waste involves identifying and quantifying various physical, chemical, and biological properties of the waste(Periathamby, Hamid and Khidzir, 2009). This information helps in understanding the waste composition, determining appropriate waste management strategies, and assessing the potential environmental impacts. Further, the characterization results have been used to develop interpolation maps using Qgis and statistical analysis has been to know the interrelation of generated solid waste.

3.1 Characterization of Solid Waste

Characterization of solid waste has been done on working days. Total 25 samples have been collected from selected locations of study area shown in table.1and figure.3. The total 39.35 kg of waste has been collected maximum waste has been found to be 4.32 kg at sampling location19 i.e; Laha followed by sampling location 18 (1.93 Kg) as shown in Table1. Further, maximum food waste has been found at sampling location 19 in which there is about 2.69 Kg followed by sampling point 18 with 0.69kg. The MSW generation per capita in India, according to one study, varies from 0.17 kg/person/day in small towns to roughly 0.62 kg/person/day in cities(James and Pandian, 2015)(Jabbari, 2016). Additionally, it was observe that higher income areas had lower percentages of organic waste and larger percentages of plastic waste when compared to low income areas in terms of per capita waste productions(Ozcan et al., 2016).According to a study on trash segregation by(Phu et al., 2020) food waste was predominant after paper and plastic, and proper separation and methods for recycling were lacking. Moreover, there was a lack of proper waste segregation practices in low lying rates. According to a another study by (Das et al., 2019) 35% of respondents said they would give food waste to waste pickers, 34% would give it to animals, and 20% would sell it to garbage collectors if it could be recycled. Further, (Mariyam et al., 2022) suggested that semi urban area of developing nations produced about 2,000,000 tons of solid waste annually and about 60% of MSW is organic and about 300 kg of waste is composed daily.

Table 1

Segregation of solid waste collected from selected location of study area.
Sample	No. of Family members	Total Waste (kg)	Food waste	Vegetable waste	Plastic waste	Paper waste	Textile waste
1	4	1.64	0.52	0.5	0.6	0.02	0
2	3	0.56	0.1	0.12	0.06	0.13	0.15
3	3	0.18	0.04	0	0.12	0.03	0
4	5	1.075	0.65	0.24	0.04	0.125	0.02
5	4	1.02	0.12	0.09	0.63	0.1	0.08
6	3	2.825	0.045	1.02	0	0.96	0.8
7	5	0.69	0.12	0	0.56	0	0
8	2	1.66	1.04	0.6	0.02	0	0
9	3	0.88	0.02	0.15	0.56	0.15	0
10	6	2.985	1.049	0.16	0.27	0.606	0.9
11	4	1.77	1.06	0.15	0.06	0.5	0
12	3	0.828	0.189	0.22	0.069	0.29	0.06
13	2	0.29	0.06	0.08	0	0.15	0
14	4	2.21	0.86	1.15	0	0.2	0
15	2	1.9	0.92	0.15	0.63	0	0.2
16	4	0.71	0.07	0.12	0	0	0.52
17	5	2.76	0.45	1.2	1.05	0.06	0
18	3	1.93	0.69	0.12	0.96	0	0.16
19	6	4.32	2.69	1.51	0.02	0.1	0
20	3	1.99	0.15	0	0.65	0.18	1.01
21	2	0.19	0.02	0	0.01	0.15	0
22	4	1.88	1.26	0.59	0.14	0	0
23	3	1.04	0.54	0.18	0.06	0.26	0
24	2	0.51	0.26	0	0.1	0.15	0
25	5	3.51	1.61	0.96	0.05	0	0.89

3.3 Moisture Content

It's important to note that the moisture content of solid waste can have significant implications for waste management processes(Arora, 2019). High moisture content can affect the efficiency of waste treatment and disposal methods, such as composting or incineration(Gupta et al., 1998). Additionally, moisture content can impact the weight and volume of waste which can have implications for transportation and landfill capacity. Therefore, regular monitoring and adjustment of waste management practices are necessary to optimize operations and minimize any potential negative impacts associated with moisture content. The maximum moisture content is found in sampling point 20 as shown in Table 2i.e., 76.25% followed by sampling point 19 in which the total moisture content was found to be 19%. From one of the study by(Environment and Climate Change Canada, 2017) it was found that the food waste generation rate is more as compare to paper as well as cardboard waste. Paper waste is 15.48%, cardboard waste is 18.86%, food waste is 23.41%, vegetable waste is 12.82%. According to Saxena et.al (2008) the increasing trend of moisture content were observed from the month of August to November(Saxena, Srivastava and Samaddar, 2010). Karadimas et al., (2018) suggested that the following rates of different types of wastes were found. Total organic waste was found to be 57.69%, package waste was 26.53%, parks and garden waste was found to be 2.93%, electrical and electronic waste was 1.23% and hazardous waste was 0.19% (Karadimas and Loumos, 2008).

Table 2

Moisture content of collected waste from selected locations of study area
S.No	Location/Area	Initial Weight (kg)	Final Weight (Kg)	Moisture content (%)
1	Bafliaz	1.64	0.004	63.02
2	Rajdhani	0.56	0.120	56.00
3	Shahdrasharief	0.18	0.043	34.00
4	Bharot	1.075	0.008	20.90
5	GambeerMughlan	1.02	0.002	48.00
6	Karyot	2.83	0.005	71.42
7	Dara	0.69	0.013	54.68
8	Dhowk	1.66	0.002	40.40
9	Nailli	0.88	0.186	12.00
10	Khablan	2.98	0.675	30.50
11	Palangar	1.77	0.870	65.40
12	Dhand Kote	0.83	0.003	33.90
13	Saj	0.29	0.340	67.20
14	Mangota	2.21	0.188	70.00
15	Danna	1.90	0.004	55.80
16	Nirojal	0.71	0.930	43.60
17	Nadian	2.76	0.006	76.00
18	Kothra	1.93	0.010	52.40
19	Laha	4.32	0.654	19.00
20	Samasamat	1.99	0.037	76.25
21	Naili	0.19	0.054	47.60
22	Manhal	1.88	0.009	39.60
23	Khanyalkote	1.04	0.230	28.60
24	Kals	0.51	0.004	14.00
25	Barhon	3.51	0.176	69.40

To represent the distribution and concentration of data points in the study area density map of Total waste, Food waste, Plastic, vegetables, fruit, paper, textile waste etc have been developed and discussed in the subsequent section.

4.1 Intensity Map of Total waste, Food waste, Plastic and Vegetable waste

Inverse Distance Weighing (IDW) was used to spatially interpolate the MSW produced at various sampling points, and QGIS 3.22.7 was used to create the spatial intensity map for the entire study, as shown in the Fig. 4. Below figure shows the intensity map of total waste, food waste, plastic and vegetable waste. Total waste was more in Laha town of 4.32gm whereas, minimum total waste was found in Shahdra Sharief of 0.18gm. The total waste that was generated was more in eastern and central part of the Thanamandi town and is due to the people with higher income group was residing in these areas as compare to other areas.In one of the paper by Baired et al.,(2016) it has been found that the low, middle income society generate organic waste of (64%,59%,54%) where as high income society generate 31% of paper and 28% of organic waste(Amasuomo and Baird, 2016). Further, form the interpolation map of plastic waste it was found that the plastic waste was generated more in Nadian town and is equal to 1.05gm whereas no plastic waste was generated in Karyot, Dara, Mangota villages as in these areas no plastic waste was found. This is because of the fact that Karyot, Dara, Mangota are rural areas where as Nadian is a semi-urban area. In addition, from the intensity map of paper it has been observe found that the maximum paper waste was generated in Khablan and is equal to 0.606gm where as in areas like Dara, Dhowk ,Dana as well as Nirojal no paper waste was found. As far as maximum textile waste is concern it was found in Barhon and is equal to 0.89gm where as no textile waste was found in areas like Naili, Manhal ,Khanyal Kote, Kals. Maximum textile waste was found in the southern part of the Thanamandi town.

To determine the linear relationship between the various categories, Pearson correlations were used to analyze the collected information. If two variables have a linear relationship, the p-value and coefficient r between − 1 and + 1 of a Pearson correlation coefficient show how significant the link is. It can only be used once its fundamental presumptions have been met. If the outcome is noteworthy, we conclude that there is a correlation. Figure.5 shows a relationship between total waste and vegetable waste and relation between total waste and food waste. These two variables have a positive association when total waste increases, so does the vegetable waste also increases. In this condition there exists a negative correlation between the two variables. This indicates that the scatter plot’s points closely resemble a straight line. If one variable increases nearly at the same rate that the other variables change, the relationship is said to be linear (Samuels, 2016). The strongest linear relationship occurs when the slope is 1. As a result, when one variable increases by one, the other variable increases by the same amount.

The analysis of the correlation matrix shown in figure.6 reveals that several positive relationships exist among the variables, with notable associations between family members and total waste, food waste and vegetable waste, and paper waste and textile waste.

Based on above obtained results of characterization of solid waste followed by interpolation maps and statistical analysis. A holistic approach to solid waste management is required to deal with mixture of vegetable and food waste i.e., organic matter. Best approach is source separation and education campaigns to encourage residents and businesses to segregate their organic waste at the point of generation. Followed by collection systems for efficiently gather organic waste, with separate bins or containers dedicated to it. Once collected, composting and digestion (anaerobic) facilities can be utilized to convert these organic materials into valuable resources like compost and biogas, reducing the burden on landfills and minimizing methane emissions. Moreover, community engagement and awareness programs can help foster a culture of responsible waste management in sub urban and rural area like Thanamandi. This integrated approach not only reduces the environmental impact but also promotes sustainability and resource recovery.

It has been concluded from the study that vegetable waste accounts for the majority of the 0.44 kg of solid trash produced daily in the research area, followed by food waste, plastic, and then other waste. Furthermore, interpolation maps revealed that compared to moderate- or lower-income groups, areas with high income group residents produced more recyclable garbage. Additionally, statistical study reveals a significant correlation between food and vegetable waste, paper waste, and plastic waste. Therefore, a holistic strategy to solid waste management is necessary to deal with the mixture of vegetable and food waste, or organic matter, in the study region.

Funding

We declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

We have no relevant financial or non-financial interests to disclose.

Author Contributions

Ms. Amreen Bhat handled the data collecting, analysis, and paper writing. The maps and graphs showing correlation have been created by Mr. Shahid Ul Islam. Dr. Pervez Alam and Dr. Nasir Rather wrote the manuscript's first draft.

Ethical Approval

Not Applicable

Consent to Participate

All authors whose names appear on the submission

1) made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; or the creation of new software used in the work;

2) drafted the work or revised it critically for important intellectual content;

3) agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Consent to Publish

All authors whose names appear on the submission are approved the version to be published.

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Editorial decision: Major Revision
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You are reading this latest preprint version

Characterization and Statistical Analysis of Municipal Solid Waste for Recognising Suitable Waste Management Approach: A Case Study in the Semi-Urban Region of Thanamandi, J&K, India

Status:

Version 1

Abstract

Figures

1. Introduction

2. Methodology

2.1 Study Area

2.2 Sample Collection

2.3 Analysis Procedure

2.3.1 MSW Segregation

2.3.2Moisture Content

3. Results and Discussion

3.1 Characterization of Solid Waste

3.3 Moisture Content

4. Intensity Maps of Solid Waste

4.1 Intensity Map of Total waste, Food waste, Plastic and Vegetable waste

5. Statistical analysis

6. Waste Management Approach

7. Conclusion

Declarations

References

Status:

Version 1