Landis Matthew S, Long Russell W, Krug Jonathan, Colón Maribel, Vanderpool Robert, Habel Andrew, Urbanski Shawn P
US EPA, Office of Research and Development, Research Triangle Park, NC, USA.
Jacobs Technology Inc., Research Triangle Park, NC, USA.
Atmos Environ (1994). 2021;247. doi: 10.1016/j.atmosenv.2020.118165.
Wildland fires can emit substantial amounts of air pollution that may pose a risk to those in proximity (e.g., first responders, nearby residents) as well as downwind populations. Quickly deploying air pollution measurement capabilities in response to incidents has been limited to date by the cost, complexity of implementation, and measurement accuracy. Emerging technologies including miniaturized direct-reading sensors, compact microprocessors, and wireless data communications provide new opportunities to detect air pollution in real time. The U.S. Environmental Protection Agency (EPA) partnered with other U.S. federal agencies (CDC, NASA, NPS, NOAA, USFS) to sponsor the Wildland Fire Sensor Challenge. EPA and partnering organizations share the desire to advance wildland fire air measurement technology to be easier to deploy, suitable to use for high concentration events, and durable to withstand difficult field conditions, with the ability to report high time resolution data continuously and wirelessly. The Wildland Fire Sensor Challenge encouraged innovation worldwide to develop sensor prototypes capable of measuring fine particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO), and ozone (O) during wildfire episodes. The importance of using federal reference method (FRM) versus federal equivalent method (FEM) instruments to evaluate performance in biomass smoke is discussed. Ten solvers from three countries submitted sensor systems for evaluation as part of the challenge. The sensor evaluation results including sensor accuracy, precision, linearity, and operability are presented and discussed, and three challenge winners are announced. Raw solver submitted PM sensor accuracies of the winners ranged from ~22 to 32%, while smoke specific EPA regression calibrations improved the accuracies to ~75-83% demonstrating the potential of these systems in providing reasonable accuracies over conditions that are typical during wildland fire events.
野火会释放大量空气污染，这可能对附近人员（如急救人员、附近居民）以及下风方向的人群构成风险。迄今为止，由于成本、实施复杂性和测量精度等因素，在事故发生时快速部署空气污染测量能力受到限制。包括小型化直读传感器、紧凑型微处理器和无线数据通信在内的新兴技术为实时检测空气污染提供了新机会。美国环境保护局（EPA）与其他美国联邦机构（疾病控制与预防中心、美国国家航空航天局、国家公园管理局、美国国家海洋和大气管理局、美国林务局）合作，发起了野火传感器挑战赛。EPA和合作组织都希望推动野火空气测量技术更易于部署，适用于高浓度事件，并且耐用，能够经受住恶劣的野外条件，具备连续且无线报告高时间分辨率数据的能力。野火传感器挑战赛鼓励全球创新，以开发能够在野火事件期间测量细颗粒物（PM）、一氧化碳（CO）、二氧化碳（CO₂）和臭氧（O₃）的传感器原型。文中讨论了使用联邦参考方法（FRM）仪器与联邦等效方法（FEM）仪器来评估生物质烟雾中性能的重要性。来自三个国家的十名参赛者提交了传感器系统作为挑战赛的一部分进行评估。展示并讨论了传感器评估结果，包括传感器的准确性、精度、线性度和可操作性，并宣布了三名挑战赛获胜者。获胜者提交的原始PM传感器精度范围约为22%至32%，而针对烟雾的EPA回归校准将精度提高到约75%至83%，这表明这些系统在野火事件典型条件下提供合理精度的潜力。
