Work

Advancements in understanding emission characteristics, data-driven olfactory-chemical measurements, and health impacts of the emerging odor pollution

Year: 2025

Type: article

Abstract: Odor pollution presents a multi-scale challenge to global environmental governance, with significant gaps in measurement reliability, temporal mismatches between emission patterns and regulatory standards, and acknowledgment of the undervaluation of its associated health risks. Analytical data reveal that odor concentrations vary over three to four orders of magnitude across different emission sources. These discrepancies are exacerbated by inconsistencies in measurement protocols, which hinder the establishment of standardized regulatory benchmarks. At present, there are inherent uncertainties in human olfactory thresholds and variability in sensor responses. To address this, recent field studies in hybrid monitoring methodologies, integrating human sensory evaluation with instrumental analysis, have improved predictive accuracy by 30–50 %. Notably, municipal waste disposal facilities are identified as primary contributors to odor emissions, often exhibiting pronounced diurnal peaks. Monitoring data show that 65–80 % of landfills exceed permissible odor thresholds, correlating with odor complaints representing ‌∼30 % of urban environmental grievances‌. Health risk assessments further indicate that 15–25 % of industrial odor sources‌ emit carcinogenic compounds exceeding the acceptable risk threshold (e.g., a lifetime cancer risk of 1 × 10 −6 ), equating to at least one case per million exposed individuals. Despite this, fewer than 10 % of regulatory frameworks explicitly prioritize odor-related carcinogens, underscoring a critical disconnect between risk quantification and policy implementation. To address these gaps, this work advocates for the development of high-sensitivity sensor networks for real-time detection of trace-level odorants, establishment of health-based exposure limits for prioritized carcinogenic odorants, and implementation of predictive models to quantify the synergistic effects of odorant mixtures.

Source: Environment International

DOI: 10.1016/j.envint.2025.109596