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Satellite-Based Estimation of Hourly PM2.5 Concentrations Using a Vertical-Humidity Correction Method from Himawari-AOD in Hebei

机译:基于Himawari-AOD垂直湿度校正法的卫星小时PM2.5浓度估算

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摘要

Particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) is related to various adverse health effects. Ground measurements can yield highly accurate PM2.5 concentrations but have certain limitations in the discussion of spatial-temporal variations in PM2.5. Satellite remote sensing can obtain continuous and long-term coverage data, and many previous studies have demonstrated the relationship between PM2.5 and AOD (aerosol optical depth) from theoretical analysis and observation. In this study, a new aerosol product with a high spatial-temporal resolution retrieved from the AHI (the Advance Himawari Imager) was obtained using a vertical-humidity correction method to estimate hourly PM2.5 concentrations in Hebei. The hygroscopic growth factor (f(RH)) was fitted at each site (in a total of 137 matched sites). Meanwhile, assuming that there was little change in f(RH) at a certain scale, the nearest f(RH) of each pixel was determined to calculate PM2.5 concentrations. Compared to the correlation between AOD and PM2.5, the relationship between the “dry” mass extinction efficiency obtained by vertical-humidity correction and the ground-measured PM2.5 significantly improved, with r coefficient values increasing from 0.19–0.47 to 0.61–0.76. The satellite-estimated hourly PM2.5 concentrations were consistent with the ground-measured PM2.5, with a high r (0.8 ± 0.07) and a low RMSE (root mean square error, 30.4 ± 5.5 μg/m3) values, and the accuracy in the afternoon (13:00–16:00) was higher than that in the morning (09:00–12:00). Meanwhile, in a comparison of the daily average PM2.5 concentrations of 11 sites from different cities, the r values were approximately 0.91 ± 0.03, and the RMSEs were between 13.94 and 31.44 μg/m3. Lastly, pollution processes were analyzed, and the analysis indicated that the high spatial-temporal resolution of the PM2.5 data could continuously and intuitively reflect the characteristics of regional pollutants (such as diffusion and accumulation), which is of great significance for the assessment of regional air quality.
机译:空气动力学直径小于2.5μm(PM2.5)的颗粒物与各种不良健康影响有关。地面测量可以产生高度准确的PM2.5浓度,但是在讨论PM2.5的时空变化时有一定的局限性。卫星遥感可以获取连续的和长期的覆盖数据,并且许多先前的研究已经通过理论分析和观察证明了PM2.5和AOD(气溶胶光学深度)之间的关系。在这项研究中,使用垂直湿度校正方法估算了河北省每小时的PM2.5浓度,从AHI(先进的Himawari成像仪)获得了一种具有高时空分辨率的新型气溶胶产品。吸湿生长因子(<数学xmlns:mml =“ http://www.w3.org/1998/Math/MathML” id =“ mm1”溢出=“ scroll”> f RH )安装在每个站点(总共137个匹配站点)中。同时,假定 < mi mathvariant =“ normal”> f RH 在一定范围内,最接近的 f RH 来计算PM2.5浓度。与AOD和PM2.5的相关性相比,通过垂直湿度校正获得的“干”质量消光效率与地面测量的PM2.5之间的关系得到了显着改善,r系数值从0.19–0.47增加到0.61– 0.76。卫星估算的每小时PM2.5浓度与地面测量的PM2.5一致,具有较高的r(0.8±0.07)和较低的RMSE(均方根误差为30.4±5.5μg/ m 3 < / sup>)值,并且下午(13:00–16:00)的准确性高于早晨(09:00–12:00)的准确性。同时,通过比较不同城市的11个站点的日平均PM2.5浓度,r值约为0.91±0.03,RMSE在13.94和31.44μg/ m 3 之间。最后,对污染过程进行了分析,分析表明,PM2.5数据的高时空分辨率可以连续直观地反映区域污染物的特征(如扩散和积累),对于评估污染具有重要意义区域空气质量

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