Temporal and spatial variability of indoor air volatile organic compound (VOC) concentrations can complicate vapor intrusion (VI) assessment and decision-making. Indicators and tracers (I&T) of VI, such as differential temperature, differential pressure, and indoor radon concentration, are low-cost lines of evidence to support sampling scheduling and interpretation of indoor air VOC sampling results. This study compares peak indoor air chlorinated VOC concentrations and I&T conditions before and during those peak events at five VI sites. The sites differ geographically and in their VI conceptual site models (CSM). Relative to site-specific baseline values, the results show that cold or falling outdoor temperatures, rising cross slab differential pressures, and increasing indoor radon concentrations can predict peak VOC concentrations. However, cold outdoor air temperature was not useful at one site where elevated shallow soil temperature was a better predictor. Correlations of peak VOC concentrations to elevated or rising barometric pressure and low wind speed were also observed with some exceptions. This study shows how the independent variables that control or predict peak indoor air VOC concentrations are specific to building types, climates, and VI CSMs. More I&T measurements at VI sites are needed to identify scenario-specific baseline and peak related I&T conditions to improve decision-making.

中文翻译：

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在蒸汽侵入研究中观察室内空气挥发性有机化合物浓度峰值之前的条件

室内空气挥发性有机化合物 (VOC) 浓度的时间和空间变化可能会使蒸汽侵入 (VI) 评估和决策复杂化。VI 的指标和示踪剂 (I&T)，例如温差、压差和室内氡浓度，是支持采样计划和室内空气 VOC 采样结果解释的低成本证据线。本研究比较了五个 VI 站点的峰值事件之前和期间的峰值室内空气氯化 VOC 浓度和 I&T 条件。这些站点在地理位置和 VI 概念站点模型 (CSM) 方面有所不同。相对于特定地点的基线值，结果表明寒冷或室外温度下降、跨板压差上升和室内氡浓度增加可以预测 VOC 浓度峰值。然而，在浅层土壤温度升高是一个更好的预测指标的地方，冷的室外空气温度并没有用处。除了一些例外，还观察到峰值 VOC 浓度与气压升高或上升和低风速的相关性。本研究显示了控制或预测室内空气 VOC 峰值浓度的自变量如何特定于建筑类型、气候和 VI CSM。需要在 VI 站点进行更多 I&T 测量，以确定特定场景的基线和峰值相关 I&T 条件，以改进决策。本研究显示了控制或预测室内空气 VOC 峰值浓度的自变量如何特定于建筑类型、气候和 VI CSM。需要在 VI 站点进行更多 I&T 测量，以确定特定场景的基线和峰值相关 I&T 条件，以改进决策。本研究显示了控制或预测室内空气 VOC 峰值浓度的自变量如何特定于建筑类型、气候和 VI CSM。需要在 VI 站点进行更多 I&T 测量，以确定特定场景的基线和峰值相关 I&T 条件，以改进决策。