Waste stream characteristics must be understood to tackle waste management problems in Kathmandu Metropolitan City (KMC), Nepal. Three-stage stratified cluster sampling was used to evaluate solid waste data collected from 336 households in KMC. This information was combined with data collected regarding waste from restaurants, hotels, schools and streets. The study found that 497.3 g capita(-1) day(-1) of solid waste was generated from households and 48.5, 113.3 and 26.1 kg facility(-1) day(-1) of waste was generated from restaurants, hotels and schools, respectively. Street litter measured 69.3 metric tons day(-1). The average municipal solid waste generation rate was 523.8 metric tons day(-1) or 0.66 kg capita(-1) day(-1) as compared to the 320 metric tons day(-1) reported by the city. The coefficient of correlation between the number of people and the amount of waste produced was 0.94. Key household waste constituents included 71% organic wastes, 12% plastics, 7.5% paper and paper products, 5% dirt and construction debris and 1% hazardous wastes. Although the waste composition varied depending on the source, the composition analysis of waste from restaurants, hotels, schools and streets showed a high percentage of organic wastes. These numbers suggest a greater potential for recovery of organic wastes via composting and there is an opportunity for recycling. Because there is no previous inquiry of this scale in reporting comprehensive municipal solid waste generation in Nepal, this study can be treated as a baseline for other Nepalese municipalities.

In Nepal, full-fledged environmental legislation was rare before the democratic constitution of 1990. The first law covering the environment and sustainability was the Environment Protection Act 1997. While the Solid Waste Act was introduced in 1987, the problem of solid waste management still surfaces in Kathmandu. In order to understand the bedrock of this unrelenting failure in solid waste management, the manuscript digs deeper into policy implementation by dissecting solid waste rules, environmental legislations, relevant local laws, and solid waste management practices in Kathmandu, Nepal. A very rich field study that included surveys, interviews, site visits, and literature review provided the basis for the article. The study shows that volumes of new Nepalese rules are crafted without effective enforcement of their predecessors and there is a frequent power struggle between local government bodies and central authority in implementing the codes and allocating resources in solid waste management. The study concludes that Kathmandu does not require any new instrument to address solid waste problems; instead, it needs creation of local resources, execution of local codes, and commitment from central government to allow free exercise of these policies.

Relatively few studies have been performed to characterize municipal solid waste (MSW) at household level. This is due in part to the difficulties involved with collecting the data and selecting an appropriate statistical sample size. The previous studies identified in this paper have used statistical tools appropriate for analysing data collected at a material recovery facility or landfill site. This study demonstrates a statistically sound and efficient approach for characterizing MSW at the household level. Moreover, a household approach also allowed for consideration of the socio-economic conditions, level of waste generation, geography, and demography. The study utilized two-stage cluster sampling within strata in Kathmandu Metropolitan City (KMC) to measure MSW for 2 weeks. In KMC, the average household solid waste generation was 161.2 g capita ^—1 day^{— 1}with an average generation rate between 137.7 and 184.6 g capita^—1 day^—1 for a 95% confidence interval and 14.5% relative margin of error. The results show a positive relation between income and waste production rate. Organic waste was the biggest portion of MSW, and hazardous waste was the smallest of the total. Sample size considerations suggest that 273 households are required in KMC to attain a 10% relative margin of error with a 95% confidence interval.