基于2种采样方法的北京市夏季道路扬尘的监测及积尘负荷分布特征

为探究不同采样方法对积尘负荷结果的影响,使用样方采样法和以克论净车采样法采集2018年夏季样品的数据,对北京市3个行政区的11条道路扬尘样品进行现场监测,计算不同道路类型及不同车道的积尘负荷,并对积尘负荷的变化规律进行分析。结果表明:基于样方采样法和以克论净车采样法的北京市夏季不同道路类型积尘负荷从大到小顺序依次为次干道(0.46 g·m^(−2)、0.99 g·m^(−2))>支路(0.31 g·m^(−2)、0.88 g·m^(−2))>主干道(0.24 g·m^(−2)、0.78 g·m^(−2));2种采样方法所得积尘负荷差异的检验结果具有显著性(P=0.00<0.05)且存在线性关系;北京市夏季道路积尘负荷(0.34 g·m^(−2))稍高于天津市(0.24 g·m^(−2)),低于石家庄市(1.06 g·m^(−2))、乌鲁木齐市(0.96 g·m^(−2))和西安市(0.70 g·m^(−2));基于样方采样法和以克论净车采样法采集的不同城区道路积尘负荷水平排序为大兴区(0.39 g·m^(−2)、1.83 g·m^(−2))>朝阳区(0.38 g·m^(−2)、1.00 g·m^(−2))>东城区(0.26 g·m^(−2)、0.92 g·m^(−2)),朝阳区、东城区和大兴区积尘负荷差异的检验结果均不具有显著性(P>0.05);基于样方采样法的机动车慢车道与机动车快车道积尘负荷分别为0.04~1.30 g·m^(−2)和0.02~1.08 g·m^(−2);慢车道积尘负荷略高于快车道,但二者差异的检验结果不具有显著性(P=0.51>0.05)。本研究成果可为遴选道路扬尘采样方法、构建北京市道路扬尘排放清单和制定管控措施提供参考。

An EMD based method for detrending RR interval series without resampling

Slow trends in the RR interval(RRI) series should be removed in the preprocessing step to get a reliable result of heart rate variability(HRV) analysis. Re-sampling is required to convert the unevenly sampled RRI series into evenly sampled time series when using the widely accepted smoothness priors approach(SPA). Noise is introduced in this process and the information quality is thus compromised. Empirical mode decomposition(EMD) and its variants, were introduced to directly process the unevenly sampled RRI series. Besides, a RR interval model was proposed to fascinate the introduction of standard metrics for the evaluation of the detrending performance. Based on standard metrics including signal-to-noise-ratio in d B(ISNR), mean square error(EMS), and percent root square difference(DPRS), the effectiveness of detrending methods in RR interval analysis were determined. Results demonstrate that complementary ensemble EMD(CEEMD, a variant of EMD) based method has a higher ISNR, a lower EMS and a lower DPRS as well as a better RRI series detrending performance compared with the SPA method, which would in turn lead to a more accurate HRV analysis.