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Redevelopment of brownfield sites into open public spaces can expose people to volatile organic compounds (VOCs) emitted from subsurface contamination. Conventional risk assessments rely on low-frequency sampling and static average concentrations, which systematically miss the transient peak-exposure episodes that define the reasonable maximum exposure. To address this gap, we developed a daily resolution, meteorologically driven modeling framework to assess outdoor VOC exposure at a repurposed industrial brownfield site in northern China over a full annual cycle. Simulated VOC concentrations varied by approximately one to two orders of magnitude and were validated against bimonthly field measurements. Results showed that subsurface VOC emission fluxes are governed jointly by soil temperature and soil moisture; once the volatilized vapors reach the ground surface, their atmospheric dispersion and dilution are further controlled by local wind speed. Using the daily resolution record, we then identified distinct meteorological precursor patterns that reliably precede extreme exposure events, and captured them with a logistic regression model built on four forecast-available predictors: air temperature, cumulative rainfall, wind speed, and the 2-day change in wind speed. Preferentially sampling these meteorologically identified episodes can provide representative data for accurate determination of long-term exposure and risk assessment and offer a days-ahead early warning capability for triggering intensified monitoring and institutional controls.
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Yang et al. (2026) studied this question.
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