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A study of relationship among the suspended particles and meteorological factors at downstrem of Jhuoshei River
|關鍵字:||Regression Analysis;Correlation Analysis;PM10;PM2.5;迴歸分析;相關分析;懸浮微粒;PM10;PM2.5||Project:||水土保持學報, Volume 44, Issue 4, Page(s) 391-406.||摘要:||
In recent years due to the rapid development of Taiwan's economy, the scope of development has expanded gradually. Some were extended to the river region. Building the large engineering structures (such as weirs or dams) in the middle-stream and upstream area has a great impact on the downstream areas. It even becomes the major source of suspended particles in the atmosphere: PM10 (particle size less than 10 microns) and PM2.5 (particle size less than 2.5 micron particles). In this study, the data are collected from Lunbei, Taixi, and Douliu air quality monitoring stations in the downstream of Jhuoshei River. First, summary statistics are obtained. Then, regression analysis and correlation analysis are performed on the data to explore the relationship among PM10 (and PM2.5) and the weather factors (i.e., atmospheric temperature, relative humidity, and wind speed). Regression models are built to explain the variation of PM10 (and PM2.5) using atmospheric temperature, relative humidity, and wind speed as explanatory variables. Refined regression models are also built by dividing the data into three groups according the wind speed obtained from fuzzy C-means clustering. Most of the models increase their explanatory power dramatically. The results of correlation analysis show that PM10 and PM2.5 are highly positive correlated. The correlation of relative humidity and PM10 is higher than the other two factors. However, the correlation of any of the three factors and PM2.5 is not very high. The conclusions may server as a good reference to further of aeolian dust.
近年來由於台灣經濟之快速發展，導致開發範圍逐漸擴大，甚至擴展至河道區域，而於河道之中上游建築如堰壩之大型工程構造物對下游地區影響很大，甚至成為大氣中懸浮微粒 PM10 (即粒徑小於 10 微米的顆粒)與 PM2.5 (即粒徑小於 2.5 微米的顆粒)的主要來源。本研究蒐集濁水溪下游崙背、台西和斗六空氣品質監測站資料，以摘要統計、線性迴歸分析和相關性分析之技術，分別探討 PM10 及 PM2.5 與大氣溫度、相對濕度、風速等氣象因子之關係。分析說明空氣懸浮微粒隨著時間與氣象因子而有所變化，且空間位置不同也會有其特性，並利用模糊群集分析將風速分為三群後，其解釋能力最高可提升約 16%。而 PM10 及 PM2.5 有高度正相關，PM10 與氣象因子中之相對濕度相關性較高，但 PM2.5 與各氣象因子間相關性之差異不大。其獲得之結論可做為進一步之揚塵研究的參考。
|Appears in Collections:||第44卷 第04期|
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