Integrating Household Characteristics, Mold Inspection and Remediation Data to Develop Localized Mold-Risk Profiles for Residential Buildings
摘要
Mold in residential buildings presents a significant threat to both occupant health and structural integrity, especially in older homes. Previous studies primarily focused on the health effects of mold, the environmental conditions that support its growth, and the influence of building materials and age. However, early detection and prevention of hidden mold remains a challenge, particularly in aging building stocks. This study investigates a localized mold-risk profile by integrating household characteristics, occupant awareness, and prevailing remediation practices. Seventeen homes in Southwest Chicago were studied using two complementary methods: (1) occupant surveys capturing housing characteristics, ventilation habits, and mold awareness and (2) classification of Mold Severity Index (MSI) from professional mold inspection and contractor remediation proposal reports. The inspection reports included air and surface mold sampling, with MSI determined based on colony-forming unit (CFU) concentrations: low (1–499 CFU/m3), medium (500–999 CFU/m3), and high (≥1000 CFU/m3). Mold confirmed by inspections was more prevalent in older homes with porous materials (i.e., wood and brick) and limited ventilation. Many residents (85%) were unaware of mold presence. Approximately 75% of the homes exhibited high mold levels requiring multiple remediation strategies. Nine contractor remediation proposals were analyzed using Latent Dirichlet Allocation (LDA), identifying three clusters of technical and procedural language reflecting key remediation themes and regulatory alignment. While the remediation proposals followed a standardized format, they varied in content, with common strategies including general mold removal, probiotic treatments, and dehumidification. This study contributes to helping community organizations and municipalities identify and map homes at risk of hidden mold growth.