Vol.35 No.6
/
2016 / 12
/
pp. 575 - 586
嘉南地區細懸浮微粒濃度與氣象因子相關性分析:2006-2014
Correlations between atmospheric fine particulate matter and meteorological variables in the Chia-Nan Area of Taiwan, 2006-2014
作者
黃淑倫
*
(長庚科技大學嘉義分部護理學院護理系(所);長庚科技大學慢性疾病暨健康促進研究中心;長庚紀念醫院嘉義分院胸腔內科)
林裕清
(長庚紀念醫院嘉義分院胸腔內科;長庚科技大學嘉義分部呼吸照護系;長庚大學呼吸治療學系)
郭素娥
(長庚科技大學慢性疾病暨健康促進研究中心)
紀妙青
(長庚科技大學嘉義分部呼吸照護系)
林玠模
(長庚科技大學嘉義分部護理學院護理系(所);長庚紀念醫院嘉義分院胸腔內科;長庚大學醫學院臨床醫學研究所)
周姜廷
(長庚科技大學慢性疾病暨健康促進研究中心)
黃友珊
(長庚科技大學嘉義分部護理學院護理系(所))
黃淑倫
*
長庚科技大學嘉義分部護理學院護理系(所);長庚科技大學慢性疾病暨健康促進研究中心;長庚紀念醫院嘉義分院胸腔內科
林裕清
長庚紀念醫院嘉義分院胸腔內科;長庚科技大學嘉義分部呼吸照護系;長庚大學呼吸治療學系
郭素娥
長庚科技大學慢性疾病暨健康促進研究中心
紀妙青
長庚科技大學嘉義分部呼吸照護系
林玠模
長庚科技大學嘉義分部護理學院護理系(所);長庚紀念醫院嘉義分院胸腔內科;長庚大學醫學院臨床醫學研究所
周姜廷
長庚科技大學慢性疾病暨健康促進研究中心
黃友珊
長庚科技大學嘉義分部護理學院護理系(所)
中文摘要
目標:本研究探討嘉南地區大氣中細懸浮微粒(fine particulate matters, PM_(2.5))濃度與氣象因子相關性分析。方法:研究蒐集並分析2006-2014年行政院環保署空氣品質監測站PM_(2.5)與氣象資料(溫度、相對濕度、降雨量及風速)。研究區域為嘉南地區共計四縣市,分別為嘉義縣市(共3個測站:新港、朴子與嘉義),台南縣市(共4個測站:新營、善化、安南與台南)。以四分位數(25%、50%及75%)、平均值、最小值及最大值進行PM_(2.5)及氣象資料描述性資料分析。進一步以皮爾森積差相關(Pearson product correlation),探討PM_(2.5)濃度與氣象因子之相關性。結果:嘉南地區PM_(2.5)日平均38 μg/m^3,溫度日平均24℃,相對濕度日平均75%,累積降雨量日平均12.1 mm,風速日平均2.3 m/sec。嘉南地區PM_(2.5)濃度與溫度(r = -0.446)、相對濕度(r = -0.327)、累積降雨量(r = -0.279)與風速(r = -0.173)呈現統計上顯著負相關。此外,東北季風期間,風速與PM_(2.5)濃度之相關係數絕對值最大(r = -0.371)。非東北季風期間,溫度與PM_(2.5)濃度之相關係數絕對值最大(r = -0.525)。結論:嘉南地區PM_(2.5)濃度與氣象因子之風速與溫度相關性較高。
英文摘要
Objectives: This article explors corrections between the fine particulate matter (PM_(2.5)) level and meteorological variables in the Chia-Nan area of Taiwan. Methods: Data regarding PM_(2.5) and meteorological variables (i.e., temperature, relative humidity, rainfall, and wind speed) between 2006 and 2014 were obtained from Environmental Protection Administration monitoring stations. The region studied is located in 4 southwestern districts (Chiayi City, Chiayi County, Tainan City, and Tainan County) and includes 3 ambient air quality-monitoring stations in Chiayi (Chiayi, Xingan, and Puzi stations) and 4 stations in Tainan (Xinying, Shanhua, Annan, and Tainan stations). Quartiles (25%, 50%, and 75%) and mean, minimum, and maximum levels were used to describe the characteristics of PM_(2.5) and meteorological variables, respectively. The relationship between PM_(2.5) and meteorological variables was estimated using the Pearson product correlation. Results: During the study period, the overall mean daily average level of PM_(2.5), temperature, relative humidity, cumulative level of rainfall, and wind speed were 38 μg/m^3, 24°C, 75%, 12.1 mm, and 2.3 m/s, respectively. In the Chia-Nan area of Taiwan, PM_(2.5) was negatively correlated with temperature (r = -0.446), relative humidity (r = -0.327), cumulative rainfall (r = -0.279), and wind speed (r = -0.173). During the Northeast Monsoon period, the absolute value of the correlation between wind speed and PM_(2.5) level was the largest (r = -0.371). However, during the Non–Northeast Monsoon period, the absolute value of the correlation between temperature and PM_(2.5) concentrations was the largest (r = -0.525). Conclusions: Wind speed and temperature have higher correlations with PM_(2.5) levels than do relative humidity and cumulative rainfall in the Chia- Nan area of Taiwan.
中文關鍵字
嘉南地區 ; 細懸浮微粒 ; 氣象因子
英文關鍵字
Chia-Nan Area, fine particulate matter, meteorological variables