Source-Context Differences in Particulate Matter Removal Dynamics of Urban Forests: Evidence from Two-Year Field Measurements

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Urban forests (UFs) are increasingly promoted as a nature-based solution for mitigating particulate matter (PM) pollution, yet their removal performance can vary depending on surrounding emission sources and environmental conditions. Here, we quantified the particulate matter reduction efficiency (PMRE) of UFs located near roads, industrial complexes, and urban areas, together with background forests in South Korea, based on field observations during the late autumn–spring period across two consecutive years (November–May in 2021–2022 and 2022–2023). We applied vector autoregression (VAR) to examine the dynamic relationships between PMRE and meteorological and air pollutant variables across eight representative sites. The results revealed that PM mitigation dynamics were strongly particle-size-dependent and context-specific. Across all sites, ΔPM10 RE was predominantly self-driven, explaining over 90% of its own variance, whereas fine-particle dynamics showed stronger interdependence. In particular, ΔPM2.5 RE consistently acted as a key mediator, accounting for up to 70%–80% of the variation in ΔPM1.0 RE depending on source context. Industrial-complex-adjacent UFs exhibited the strongest cross-variable interactions, while urban-core UFs were largely governed by intrinsic mitigation processes. Roadside UFs showed site-specific responses associated with CO and temperature variability. Notably, PMRE responses exhibited damped oscillation patterns across all source contexts, converging toward equilibrium over time, indicating stabilization of mitigation performance following disturbance events. These findings demonstrate that urban forest air-quality benefits are highly context dependent and governed by particle-size-specific dynamics. Our results provide evidence-based guidance for designing and managing urban forests, emphasizing the need for source-specific strategies and prioritization of PM2.5-oriented mitigation, particularly in industrial and roadside environments where fine-particle interactions are strongest.

키워드

particulate matterpollutant-specific characteristicspollution reduction efficiencySouth Koreaurban foresturban forest designvector autoregression modelAIR-QUALITYVEGETATIONTREES
제목
Source-Context Differences in Particulate Matter Removal Dynamics of Urban Forests: Evidence from Two-Year Field Measurements
저자
Lee, BobaeSou, Hong-DuckPark, SeoncheolPark, Chan-Ryul
DOI
10.3390/f17050588
발행일
2026-05
유형
Article
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