کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1860832 | 1530560 | 2015 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک و نجوم (عمومی)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physics Letters A - Volume 379, Issues 45â46, 4 December 2015, Pages 2962-2969
Journal: Physics Letters A - Volume 379, Issues 45â46, 4 December 2015, Pages 2962-2969
نویسندگان
Chen-Hua Shen,