Composting rural kitchen waste for nutrient recovery and runoff pollution mitigation: a Bayesian modeling approach.

Abstract

In China's ecologically sensitive Erhai Basin, open-dumped rural kitchen waste causes both nutrient loss and water quality degradation. Here we integrate household surveys, on-site composting experiments, and a Bayesian dual-pool wash-off model in a pilot case study of six villages. The model extends urban stormwater concepts to solid organic waste, providing probabilistic estimates of both nutrient recovery and pollution mitigation within a single framework. Results reveal substantial spatiotemporal variability in waste generation: total village-level kitchen waste varied approximately three-fold across villages, driven primarily by differences in permanent population, while per-capita rates were largely consistent (0.16-0.23 kg/person/day). On-site aerobic composting retained over two-thirds of initial total nitrogen and over 90% of initial total phosphorus, yet a supply-demand mismatch across villages limited fertilizer substitution to 10-73%. Under open-exposure conditions, kitchen waste contributed median annual loads of 64.6 kg N/yr (95% CI: 34.5-99.6) and 31.0 kg P/yr (95% CI: 17.0-48.6). Losses concentrated in the wet season and scaled with population, enabling spatial prioritization. As a single-basin pilot study, these probabilistic estimates provide a risk-based foundation for integrating nutrient recovery and runoff pollution mitigation in watershed management, though the findings require region-specific calibration and validation before broader application.