Validation of the UPAS+: A filter-based air sampler coupled with a suite of real-time sensors

UPAS 的验证：基于过滤器的空气采样器与一套实时传感器相结合

基本信息

批准号：
10312360
负责人：
Sheryl Magzamen
金额：
$ 93.41万
依托单位：
ACCESS SENSOR TECHNOLOGIES, LLC
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-08-01 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10312360
关键词：
Accelerometer Adoption Aerosols Air Pollution Airborne Particulate Matter Architecture Area Atmospheric Pressure Award Behavior Breathing Calibration California Carbon Black Charge Communities Computer software Computers County Coupled Coupling Data Data Analyses Data Science Devices Disease Dust Environmental Risk Factor Epidemiology Exposure to Gases Goals Gold Health Home Human Humidity In Situ Individual Location Measurement Measures Metals Monitor Morbidity - disease rate National Institute of Environmental Health Sciences Noise Organophosphates Outcome Output Participant Particulate Particulate Matter Pattern Performance Pesticides Phase Planets Pollution Process Reference Standards Research Research Personnel Running Rural Rural Community Sampling Small Business Innovation Research Grant Source Techniques Technology Temperature Time Ultrasonics Urban Community Validation Visualization Visualization software Weight Work air sampling base burden of illness coarse particles cohort cost data complexity data quality data visualization design environmental justice exposed human population fine particles human morbidity human mortality improved instrument light weight member mortality new technology novel open data open source particle personal exposure monitor premature prototype quality assurance sensor sensor technology time resolved data tool wearable device web based interface

项目摘要

Particulate matter air pollution is a major contributor to the global burden of disease and the leading environmental risk factor for premature morbidity and mortality on the planet. Human exposure to particulate air pollution is largely estimated using data from stationary outdoor monitors installed in heavily populated areas. These data might not reflect exposures in rural communities or vulnerable subpopulations. Further, there is evidence that these data do not capture the unique exposure of a given individual, who likely spends most of their time indoors and transitions between multiple locations (e.g., home, work) throughout the day. Therefore, a need exists to improve our understanding of how the timing and magnitude of human exposure to particulate air pollution relates to specific sources as well as individual behaviors or tasks. The goal of this SBIR Phase IIB project is to improve our ability to assess human exposure to PM (and subsequent health outcomes) by coupling a real-time sensor with a filter-based sampler (for in-situ gravimetric validation) in a small, lightweight, quiet, wearable device. This coupling will improve our ability to estimate time- and location-resolved PM exposure for outdoor, indoor, and personal exposure monitoring. To help users harness the data from this device, we will develop data analysis and visualization software using a popular, open-source platform (the R Statistical Software Project). To validate device performance and to evaluate its usefulness to the research and environmental justice communities, we propose a field demonstration in rural and urban communities in the San Joaquin Valley of California—an area known to suffer from high levels of fine (PM2.5) and coarse (PM10) particulate matter pollution.

特定物质空气污染是造成全球疾病负担和领先的主要贡献者地球上过早病态和死亡率的环境风险因素。使用在广受欢迎的地区固定的固定室外监视器的数据估计污染。这些数据可能不会反映农村社区或脆弱的亚种群的暴露这些数据没有捕获给定个人的证据，他们可能花费大部分他们的时间在室内和整天多个位置（例如家庭，工作）之间的过渡。需要提高我们对人类对颗粒的时间和程度的理解的理解空气污染涉及详细信息作为个人行为或任务。 SBIR阶段IIB项目的目标是改善我们的我们的状况，以评估人类对PM的接触（Andd 随后的健康结果）通过将实时传感器与基于过滤器的采样器耦合验证）在小型，轻巧，安静的可穿戴设备中。和位置分辨的PM暴露于室内，室内和个人曝光监控利用设备的数据，我们将使用流行的，开源平台（R统计软件项目）。对研究和环境正义社区的有用性，我们提出了农村的现场演示和加利福尼亚圣华金山谷的城市社区 - 纳雷亚（Narea）（PM2.5）和粗（PM10）颗粒物质进行了询问。