Al-Hamdan Mohammad Z, Crosson William L, Limaye Ashutosh S, Rickman Douglas L, Quattrochi Dale A, Estes Maurice G, Qualters Judith R, Sinclair Amber H, Tolsma Dennis D, Adeniyi Kafayat A, Niskar Amanda Sue
Universities Space Research Association, National Aeronautics and Space Administration, Marshall Space Flight Center, National Space Science and Technology Center, Huntsville, AL 35805 , USA.
J Air Waste Manag Assoc. 2009 Jul;59(7):865-81. doi: 10.3155/1047-3289.59.7.865.
This study describes and demonstrates different techniques for surface fitting daily environmental hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 microm (PM2.5) for the purpose of integrating respiratory health and environmental data for the Centers for Disease Control and Prevention (CDC) pilot study of Health and Environment Linked for Information Exchange (HELIX)-Atlanta. It presents a methodology for estimating daily spatial surfaces of ground-level PM2.5 concentrations using the B-Spline and inverse distance weighting (IDW) surface-fitting techniques, leveraging National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectrometer (MODIS) data to complement U.S. Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM2.5 from the EPA database for the year 2003 as well as PM2.5 estimates derived from NASA's satellite data. Hazard data have been processed to derive the surrogate PM2.5 exposure estimates. This paper shows that merging MODIS remote sensing data with surface observations of PM,2. not only provides a more complete daily representation of PM,2. than either dataset alone would allow, but it also reduces the errors in the PM2.5-estimated surfaces. The results of this study also show that although the IDW technique can introduce some numerical artifacts that could be due to its interpolating nature, which assumes that the maxima and minima can occur only at the observation points, the daily IDW PM2.5 surfaces had smaller errors in general, with respect to observations, than those of the B-Spline surfaces. Finally, the methods discussed in this paper establish a foundation for environmental public health linkage and association studies for which determining the concentrations of an environmental hazard such as PM2.5 with high accuracy is critical.
本研究描述并展示了不同的技术，用于对空气动力学直径小于或等于2.5微米的颗粒物（PM2.5）的每日环境危害数据进行曲面拟合，目的是为疾病控制与预防中心（CDC）的健康与环境信息交换关联（HELIX）-亚特兰大试点研究整合呼吸健康与环境数据。它提出了一种使用B样条和反距离加权（IDW）曲面拟合技术来估计地面PM2.5浓度每日空间曲面的方法，利用美国国家航空航天局（NASA）的中分辨率成像光谱仪（MODIS）数据来补充美国环境保护局（EPA）的地面观测数据。该研究使用了EPA数据库中2003年的环境PM2.5测量值以及从NASA卫星数据得出的PM2.5估计值。已对危害数据进行处理，以得出替代的PM2.5暴露估计值。本文表明，将MODIS遥感数据与PM2.5的地面观测数据合并，不仅能提供比单独任何一个数据集更完整的PM2.5每日表征，而且还能减少PM2.5估计曲面中的误差。本研究结果还表明，尽管IDW技术可能会引入一些数值伪影，这可能归因于其插值性质，即假设最大值和最小值仅能出现在观测点处，但就观测而言，每日IDW PM2.5曲面的误差总体上比B样条曲面的误差小。最后，本文讨论的方法为环境公共卫生关联和相关研究奠定了基础，对于此类研究而言，高精度确定诸如PM2.5等环境危害的浓度至关重要。
