School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Department of Civil, Construction and Environmental Engineering, North Carolina State University, Raleigh, NC, USA.
J Air Waste Manag Assoc. 2021 Jul;71(7):815-829. doi: 10.1080/10962247.2021.1924311.
Prescribed burning (PB) is a prominent source of PM in the southeastern US and exposure to PB smoke is a health risk. As demand for burning increases and stricter controls are implemented for other anthropogenic sources, PB emissions tend to be responsible for an increasing fraction of PM concentrations. Here, to quantify the effect of PB on air quality, low-cost sensors are used to measure PM concentrations in Southwestern Georgia. The feasibility of using low-cost sensors as a supplemental measurement tool is evaluated by comparing them with reference instruments. A chemical transport model, CMAQ, is also used to simulate the contribution of PB to PM concentrations. Simulated PM concentrations are compared to observations from both low-cost sensors and reference monitors. Finally, a data fusion method is applied to generate hourly spatiotemporal exposure fields by fusing PM concentrations from the CMAQ model and all observations. The results show that the severe impact of PB on local air quality and public health may be missed due to the dearth of regulatory monitoring sites. In Southwestern Georgia PM concentrations are highly non-homogeneous and the spatial variation is not captured even with a 4-km horizontal resolution in model simulations. Low-cost PM sensors can improve the detection of PB impacts and provide useful spatial and temporal information for integration with air quality models. R of regression with observations increases from an average of 0.09 to 0.40 when data fusion is applied to model simulation withholding the observations at the evaluation site. Adding observations from low-cost sensors reduces the underestimation of nighttime PM concentrations and reproduces the peaks that are missed by the simulations. In the future, observations from a dense network of low-cost sensors could be fused with the model simulated PM fields to provide better estimates of hourly exposures to smoke from PB.: Prescribed burning emissions are a major cause of elevated PM concentrations, posing a risk to human health. However, their impact cannot be quantified properly due to a dearth of regulatory monitoring sites in certain regions of the United States such as Southwestern Georgia. Low-cost PM sensors can be used as a supplemental measurement tool and provide useful spatial and temporal information for integration with air quality model simulations. In the future, data from a dense network of low-cost sensors could be fused with model simulated PM fields to provide improved estimates of hourly exposures to smoke from prescribed burning.
计划火烧（PB）是美国东南部空气中 PM 的主要来源，暴露在 PB 烟雾下会对健康造成危害。随着对燃烧的需求增加，以及对其他人为来源的控制更加严格，PB 排放往往会导致 PM 浓度的比例不断增加。在这里，为了量化 PB 对空气质量的影响，使用低成本传感器来测量佐治亚州西南部的 PM 浓度。通过将其与参考仪器进行比较，评估了使用低成本传感器作为补充测量工具的可行性。还使用了一个化学输送模型（CMAQ）来模拟 PB 对 PM 浓度的贡献。将模拟的 PM 浓度与来自低成本传感器和参考监测器的观测结果进行比较。最后，应用数据融合方法通过融合来自 CMAQ 模型和所有观测的 PM 浓度来生成每小时时空暴露场。结果表明，由于监管监测站点的缺乏，可能会错过 PB 对当地空气质量和公共健康的严重影响。在佐治亚州西南部，PM 浓度高度不均匀，即使在模型模拟中使用 4 公里的水平分辨率，也无法捕捉到空间变化。低成本 PM 传感器可以提高对 PB 影响的检测，并为与空气质量模型集成提供有用的时空信息。当将数据融合应用于模型模拟并保留评估站点的观测值时，与观测的回归 R 值从平均 0.09 增加到 0.40。添加来自低成本传感器的观测值可以减少夜间 PM 浓度的低估，并再现模拟错过的峰值。在未来，来自低成本传感器的密集网络的观测值可以与模型模拟的 PM 场融合，以提供更好的计划火烧烟雾的每小时暴露估计值。
