Spatio-Temporal Modeling of PM2.5 Deposition for ARI Prevention in Enclosed Kitchens Using Python with Morris-Sobol and LHS

Sri Anggriani; Agung Laksono Yudho

doi:10.55681/armada.v4i10.4895

Authors

Sri Anggriani Promotion Health, Health Polytechnic of Malang, Ministry of Health, Indonesia
Agung Laksono Yudho Mechanical Engineering, State University of Malang, Indonesia

DOI:

https://doi.org/10.55681/armada.v4i10.4895

Keywords:

Acute respiratory infection, Particulate matter, Enclosed kitchens, Breathing-zone, Spatial-temporal

Abstract

Cooking emissions in enclosed kitchens require effective exposure controls relevant to acute respiratory infection (ARI) prevention. This study modeled the spatio-temporal transport and surface deposition of cooking-generated PM₂.₅ and compared interventions for reducing breathing-zone exposure. A Python-based computational framework coupled three-dimensional, size-resolved particle transport with a prescribed airflow field. Four 30-min scenarios, including 12 min of cooking, were evaluated: closed baseline, local exhaust, portable air cleaner, and combined control. Cumulative breathing-zone exposure was the primary outcome. Morris screening, Sobol analysis, and Latin hypercube sampling (LHS) were conducted using a separate reduced model. The spatial simulation showed heterogeneous concentrations and persistent post-cooking exposure. Cumulative exposure decreased from 28,694.3 µg·min m⁻³ at baseline to 7,082.5, 17,043.3, and 6,045.8 µg·min m⁻³ with local exhaust, air cleaning, and combined control, representing reductions of 75.3%, 40.6%, and 78.9%, respectively. Source-capture efficiency was the dominant parameter and explained 52.1% of reduced-model variance through its first-order Sobol index. LHS reproduced the intervention ranking of the spatial simulation. Source-directed extraction, supplemented by filtration and continued post-cooking operation, therefore offers a promising strategy for reducing PM₂.₅ exposure in enclosed kitchens and supporting ARI prevention.

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