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Calibration and Evaluation of PUF-PAS Sampling Rates across the Global Atmospheric Passive Sampling (GAPS) Network

机译:全球大气被动采样(GAPS)网络中PUF-PAS采样率的校准和评估

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摘要

Passive air samplers equipped with polyurethane foam (PUF-PAS) are frequently used to measure persistent organic pollutants (POPs) in ambient air. Here we present and evaluate a method to determine sampling rates (RS), and the effective sampling volume (Veff), for gas-phase chemical compounds captured by a PUF-PAS sampler deployed anywhere in the world. The method uses a mathematical model that requires only publicly available hourly meteorological data, physical-chemical properties of the target compound, and the deployment dates. The predicted RS is calibrated from sampling rates determined from 5 depuration compounds (13C PCB-9, 13C PCB-15, 13CPCB-32, PCB-30, and d6-γ-HCH) injected in 82 samples from 24 sites deployed by the Global Atmospheric Passive Sampling (GAPS) network around the world. The dimensionless fitting parameter, gamma, was found to be constant at 0.267 when implementing the Integrated Surface Database (ISD) weather observations and 0.315 using the Modern Era Retrospective-Analysis for Research and Applications (MERRA) weather dataset. The model provided acceptable agreement between modelled and depuration determined sampling rates, with 13C PCB-9, 13C PCB-32, and d6-γ-HCH having mean percent bias near zero (±6%) for both weather datasets (ISD and MERRA). The model provides inexpensive and reliable PUF-PAS gas-phase RS and Veff when depuration compounds produce unusual or suspect results and for sites where the use of depuration compounds is impractical, such as sites experiencing low average wind speeds, very cold temperatures, or remote locations.
机译:配备聚氨酯泡沫(PUF-PAS)的被动式空气采样器通常用于测量环境空气中的持久性有机污染物(POPs)。在这里,我们介绍并评估一种方法,以确定由部署在世界任何地方的PUF-PAS采样器捕获的气相化合物的采样率(RS)和有效采样量(Veff)。该方法使用的数学模型仅需要公开的每小时气象数据,目标化合物的物理化学性质以及部署日期。预测的RS是根据从5种净化化合物( 13 C PCB-9, 13 C PCB-15, 13 CPCB- 32个,PCB-30和d6-γ-HCH)分别由全球大气无源采样(GAPS)网络在24个地点部署的82个样品注入。在实施综合表面数据库(ISD)气象观测时,发现无因次拟合参数gamma恒定为0.267,而对于研究和应用现代时代回顾性分析(MERRA)天气数据集,其无因次拟合参数gamma恒定为0.315。该模型在建模和净化确定的采样率之间提供了可接受的一致性,其中 13 C PCB-9, 13 C PCB-32和d6-γ-HCH具有平均百分比偏差对于两个天气数据集(ISD和MERRA),都接近零(±6%)。当净化化合物产生异常或可疑的结果时,以及在不宜使用净化化合物的场所(例如平均风速低,温度极低或偏远的场所),该模型可提供廉价且可靠的PUF-PAS气相RS和Veff位置。

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