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Waste collection reliability and service gaps in Sonipat city, Haryana

RahulSatvir Singh

Abstract

Reliable waste collection is essential for maintaining clean and manageable urban neighbourhoods. Waste collection services in Sonipat City, Haryana, were assessed through a 2025 survey covering 600 households, 60 sanitation workers and 20 municipal officers across 20 wards. Regular collection was reported by 55.50% of households, while 26.67% experienced irregular service and 17.83% reported no collection service. Among households receiving collection, 49.90% had daily pickup, whereas only 31.24% reported consistently fixed collection timing. Considerable differences appeared across wards, with regular collection ranging from 6.67% to 93.33%. Sanitation workers reported staff shortages, public non-cooperation, narrow streets, excessive workload and vehicle problems. Complaint handling also remained incomplete, as only 27.46% of 142 complainants reported full resolution. Better route management, predictable collection schedules, suitable vehicles and stronger complaint follow-up are required.

Full Text

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Introduction

A waste service is experienced through repeated visits, not through a coverage entry alone. Residents need to know whether a collector will arrive, how frequently pickup occurs and what happens when the visit is missed. Comparative research across cities treats collection as one part of a wider system that also depends on institutions and everyday service delivery (Wilson et al., 2012) [1] . This distinction matters when evaluating performance. The Waste Wise Cities Tool separates waste generated, collected and managed in controlled facilities. India's service-benchmarking handbook also distinguishes coverage, efficiency and other service indicators. (UN-Habitat, 2021). Studies in developing countries describe operational difficulty as a combination of finance, staffing, equipment and coordination. A Kenyan case study examines these municipal challenges, while broader work by Guerrero and colleagues considers the actors and conditions affecting waste-management performance. Such research cautions against treating an additional vehicle as a complete solution when the supporting organisation remains weak (Guerrero et al., 2013) [2] . Collection also has a physical geography. Routes pass through streets of different widths and serve premises with different access conditions. Guidance for developing countries stresses choosing collection arrangements suited to local conditions. Research in Yaoundé likewise places waste services within the city's practical and livelihood setting. These perspectives encourage attention to who can reach a collection point and who must make an extra effort to use it (Parrot et al., 2009) [3] . South Asian evidence gives particular importance to timing. A choice experiment in Bharatpur identified collection frequency, pickup timing and street cleanliness as valued service attributes. These are understandable household concerns because a nominal route is of limited use when residents cannot predict its arrival. The implication for survey design is to ask about availability, frequency and timing separately (Rai et al., 2019) [4] . Indian research connects weak collection with the wider difficulties of transport, treatment and disposal. Haryana's 2025 audit publication examined municipal waste management over an earlier audit period and raised planning and implementation concerns. That audit provides institutional context faced by every surveyed Sonipat household in 2025 (CAG, 2025) [5] .

Objective

Study area

The survey municipality lies in Sonipat district, Haryana, within the Delhi-linked urban region. Research on Sonipat-Kundli describes outward expansion and land transformation, creating a wider setting of established urban areas and growing peripheral development. The district's plain terrain and seasonal climate form the regional background, but neither district area nor the wider planning region is used as the denominator for this municipal survey (Verma et al., 2024) [6] . All results retain the 20-ward structure used at the administrative reference. Thirty households were covered in each ward. Ward numbers identify the comparison units. Figure 1 shows the survey location and its ward framework.

Methodology

The investigation used three separate schedules in a cross-sectional survey. Households were selected through a ward-stratified, multistage procedure: three residential clusters per ward and ten systematically selected households per cluster. An eligible adult familiar with waste disposal answered the household schedule. The worker sample comprised 20 sweepers, 20 door-to-door collectors, ten drivers or helpers and ten bin, transfer or disposal workers. Workers were selected through geographical and functional lists. Twenty officers or responsible functionaries were selected purposively by role. The analysis covered reported collection availability, frequency, timing, ward distribution, selected operational problems, route administration and complaint outcomes. Household denominators were 600 overall, 493 where collection existed and 142 among those who had complained. Worker and officer answers used denominators of 60 and 20. Percentages were recalculated from counts, and ward values used 30 households each. Multiple-response worker problems describe over-lapping experiences. The analysis is descriptive. Reporting states the study setting, sample, definitions and limitations explicitly, consistent with the transparency principles of observational-study reporting (von Elm et al., 2007) [7] . Collection was available to 493 households, but only 333 described it as regular. Irregular or unavailable service affected 267 households, or 44.50% of the full sample. Availability therefore gave a more favourable picture than reliability. (Table 1).

Results

Availability, frequency and timing

Ward differences in collection

Worker constraints and route administration

Staff shortage and public non-cooperation were each reported by 28 workers. Narrow streets affected 22, while 20 identified excessive workload. Vehicle shortages or damage and spillage were each selected by 17. The workload schedule provides context. The 20 door-to-door collectors reported serving an average of 417.90 households per day, with a standard deviation of 117.13. Their average was 2.55 trips daily. Source: Officer field schedule, 2025; author's calculations. N = 20 for each indicator.

Only five officers described fixed routes as fully operational; thirteen considered them partly operational. Full availability of route records was also reported by five officers. Together, these responses indicate a need to check the connection between planned routes, actual visits and accessible records. Among 142 complainants, 39 reported full resolution, 66 partial resolution and 37 no resolution. Full resolution therefore covered 27.46%, not the 73.94% obtained by combining full and partial outcomes. Elsewhere in the same question, 96 of all 600 households did not know where to complain. These results distinguish access to a channel, receipt of some action and complete resolution (Table 5).

Complaint outcomes

Discussion and service priorities

The survey points to a gap between being included in a service and receiving it predictably. This distinction fits the service attributes identified in Bharatpur and the performance-indicator approach examined by Teixeira and colleagues. For Sonipat, regularity, daily frequency and pickup timing should be tracked separately, using clearly stated denominators and a consistent recall period (Rai et al., 2019; Teixeira et al., 2014) [4,8] . GIS studies in Ipoh and fuel-oriented routing research demonstrate ways to examine collection networks, but their savings cannot be transferred directly to Sonipat. A local assessment would first need street access, actual stops, travel times, unloading delays and vehicle capacity. No claim of optimal routing is made from the present household responses (Malakahmad et al., 2014) [9] . Scheduling improvements also require reliable information. Johansson's modelling work examines how dynamic scheduling and routing can improve operations when suitable information is available. In Sonipat, a more immediate proposal is to connect each route with a named crew, an expected pickup window, a completion record and a procedure for missed visits. Advanced monitoring should follow, not replace, dependable basic records (Johansson, 2006) [10] . Worker and household cooperation deserve a place in that system. Experimental evidence from Nepal found benefits from combining information with inexpensive street bins, including improved disposal through collectors. This supports testing modest local changes. Trials in difficult routes should be evaluated with repeated observations. (Nepal et al., 2023) [11] .

Conclusion

Collection gaps in Sonipat were visible in reliability, timing, ward differences and complaint completion. Regular service reached 55.50% of sampled households, and fewer than one-third of served households reported consistently fixed timing. The weakest ward results warrant direct route verification, while worker and officer responses identify staffing, access, vehicles and records as practical areas for review. A clear pickup window, suitable equipment and verified complaint resolution offer specific priorities. Improvement must be demonstrated through repeated service checks rather than inferred from nominal coverage.

References

  1. Wilson DC, Rodic L, Scheinberg A, Velis CA, Alabaster G. Comparative analysis of solid waste management in 20 cities. Waste Management & Research. 2012;30(3):237-254.
  2. Guerrero LA, Maas G, Hogland W. Solid waste management challenges for cities in developing countries. Waste Management. 2013;33(1):220-232.
  3. Parrot L, Sotamenou J, Dia BK. Municipal solid waste management in Africa: Strategies and livelihoods in Yaoundé, Cameroon. Waste Management. 2009;29(2):986-995.
  4. Rai RK, Nepal M, Khadayat MS, Bhardwaj B. Improving municipal solid waste collection services in developing countries: A case of Bharatpur Metropolitan City, Nepal. Sustainability. 2019;11(11):3010.
  5. Comptroller and Auditor General of India. Performance audit on solid waste management in urban local bodies. In Composite Audit Report-Civil and PSUs, Government of Haryana (Report No. 2 of 2025, Chapter 2); 2025.
  6. Verma P, Jangra R, Kaushik SP. Geospatial measurement of urban sprawl and land transformation using multi-temporal datasets: A case study of Sonipat-Kundli urban agglomeration. Sustainable Environment. 2024;10(1):2366556.
  7. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. PLoS Medicine. 2007;4(10):e296.
  8. Teixeira CA, Avelino C, Ferreira F, Bentes I. Statistical analysis in MSW collection performance assessment. Waste Management. 2014;34(9):1584-1594.
  9. Malakahmad A, Bakri PM, Mokhtar MRM, Khalil N. Solid waste collection routes optimization via GIS techniques in Ipoh City, Malaysia. Procedia Engineering. 2014;77:20-27.
  10. Johansson OM. The effect of dynamic scheduling and routing in a solid waste management system. Waste Management. 2006;26(8):875-885.
  11. Nepal M, Karki Nepal A, Khadayat MS, Rai RK, Shyamsundar P, Somanathan E. Low-cost strategies to improve municipal solid waste management in developing countries: Experimental evidence from Nepal. Environmental and Resource Economics. 2023;84(3):729-752.
  12. Central Public Health and Environmental Engineering Organisation. Municipal solid waste management manual: Part I -An overview. Ministry of Urban Development, Government of India; 2016.
  13. Coffey M, Coad A. Collection of municipal solid waste in developing countries. UN-Habitat; 2010.
  14. Henry RK, Yongsheng Z, Jun D. Municipal solid waste management challenges in developing countries-Kenyan case study. Waste Management. 2006;26(1):92-100.
  15. Kumar S, Smith SR, Fowler G, Velis C, Kumar SJ, Arya S, Rena Kumar R, Cheeseman C. Challenges and opportunities associated with waste management in India. Royal Society Open Science. 2017;4(3):160764.
  16. Tavares G, Zsigraiova Z, Semiao V, Carvalho MG. Optimisation of MSW collection routes for minimum fuel consumption using 3D GIS modelling. Waste Management. 2009;29(3):1176-1185.
  17. United Nations Environment Programme. Global Waste Management Outlook 2024: Beyond an age of waste-Turning rubbish into a resource. 2024.
  18. United Nations Human Settlements Programme. Waste Wise Cities Tool: Step by step guide to assess a city's municipal solid waste management performance through SDG indicator 11.6.1 monitoring. 2021.
  19. How to cite this article: Rahul, Singh S. Waste collection reliability and service gaps in Sonipat city, Haryana. International Journal of Geography, Geology and Environment. 2026;8(9):205-210. doi: https://www.doi.org/10.22271/2706748
Municipal Solid Waste ManagementWaste Management and RecyclingUrban and Freight Transport LogisticsSonipatsanitation workerswaste collectionservice gapscomplaint handling
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