MULTIFRACTAL TEMPORALLY WEIGHTED DETRENDED CROSS-CORRELATION ANALYSIS OF PM10, NOX AND METEOROLOGICAL FACTORS IN URBAN AND RURAL AREAS OF HONG KONG
MULTIFRACTAL TEMPORALLY WEIGHTED DETRENDED CROSS-CORRELATION ANALYSIS OF PM10, NOX AND METEOROLOGICAL FACTORS IN URBAN AND RURAL AREAS OF HONG KONG
复制标题
香港城乡PM10、NOX与气象因素的多分形时间加权去趋势互相关分析
DOI：
10.1142/s0218348x21501668
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发表时间：
2021
影响因子：
4.7
通讯作者：
Zhou Yu
中科院分区：
文献类型：
--
作者：
Jiang Shan;Yu Zu-Guo;Anh Vo V.;Zhou Yu
了解其与一些相关因素的相关性对于空气污染过程的建模和预测至关重要。与传统的互相关分析相比，多重分形去趋势互相关分析（MFDCCA）由于其非平稳性而被认为是更适合分析空气污染物时间序列的方法。为了改善MFDCCA的缺点，提出了多重分形时间加权去趋势互相关分析（MF-TWXDFA）。在本研究中，我们应用MF-TWXDFA来研究污染物（[公式：见正文]和[公式：见正文]）与气象因素（温度、压力、风速（WS）和相对湿度（RH））之间的互相关性。 2005年1月1日至2014年12月31日香港城乡数据集的结果表明，城乡各污染物与气象因子对之间均存在多重分形互相关关系。与之前的MFDCCA结果不同，我们发现[公式：见正文]与（温度、压力）互相关的多重分形程度在城市地区更加明显。 [公式：见正文]与WS之间互相关的多重分形强度无论在城市还是农村都很弱。此外，MF-TWXDFA互相关系数[公式：见正文]可以捕捉污染物与气象因素之间的负相关关系。就[式：见正文]而言，[式：见正文]在这四个气象因素上，城市地区小于或接近农村地区。城乡[式：见文]不同气象因素的[式：见文]表现出更为复杂的规律。与MFDCCA相比，MF-TWXDFA可以提供更丰富的污染物与气象因素之间关系的信息，有利于进一步对空气污染过程进行建模和预测。
Understanding of its correlation to some relevant factors is of paramount importance for modeling and predication of the air pollution process. Compared with the traditional cross-correlation analysis, multifractal detrended cross-correlation analysis (MFDCCA) was argued to be a more suitable method to analyze air pollutant time series due to their non-stationarity nature. Multifractal temporally weighted detrended cross-correlation analysis (MF-TWXDFA) was proposed to improve the shortcomings of MFDCCA. In this study, we apply MF-TWXDFA to investigate the cross-correlation between pollutants ([Formula: see text] and [Formula: see text]) and meteorological factors (temperature, pressure, wind speed (WS) and relative humidity (RH)). The results on the dataset from 1 January 2005 to 31 December 2014 in urban and rural areas of Hong Kong show the existence of multifractal cross-correlation between all pairs of pollutants and meteorological factors in both urban and rural areas. Different from the previous MFDCCA results, we found that the multifractal degree of cross-correlation between [Formula: see text] and (temperature, pressure) is more obvious in urban area. The multifractal strength of cross-correlation between [Formula: see text] and WS is very weak in either urban or rural area. Furthermore, the MF-TWXDFA cross-correlation coefficient [Formula: see text] can capture negative correlation between pollutants and meteorological factors. For [Formula: see text], [Formula: see text] in urban area is less than or close to that in rural area with respect to these four meteorological factors. The [Formula: see text] of [Formula: see text] in urban and rural areas shows more complex patterns for varied meteorological factors. Compared with MFDCCA, MF-TWXDFA can provide much richer information about the relationships between pollutants and meteorological factors, which is beneficial to further modeling and prediction of the air pollution process.