Estimating Trends of Mean Monthly Ozone Emission in Urbanised Areas of Malaysia

Akeem Olawale Olaniyia, A. M. Abdullaha, Mohammad Firuz Ramlia, Hosea Kato Mandea, Deborah Babarinsab
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Abstract

Abstract A 21 year (1992 – 2012) daily ozone emission data of a highly urbanised district in Malaysia was analysed with the aim of estimating the trend of ozone emission and relating this trend to the socio – economic and climatic characteristics of the area. Daily ozone emission dataset used in this study were obtained from the World Ozone and Ultraviolet Data Centre (WOUDC). The data were aggregated to obtain the mean monthly emission data. Descriptive and inferential statistical analyses were conducted to describe the datasets. Trend of the ozone emission was estimated with the use of MANN - KENDALL test. The magnitude of the trend was derived by the use of ordinary least-square fitting and the significance of trend was also tested with the use of MANN-KENDALL tool. The results of the statistical analysis indicated that the highest ozone emission occurred during the south western monsoon (May to August) period and these mean monthly ozone emission differed significantly over the study period. The trend analysis indicated a yearly decrease of between 0.069 ppt to 9.45 ppt for all the months except for the month of June when the predicted ozone concentration increased between 0.403 ppt and 0.414 ppt over 2020 to 2100. Furthermore, the results indicated that the ozone emission datasets yielded good estimates (predictive power of over 90%) with polynomial regression model. It could be concluded that the results of this study provided useful evidence for the importance of the climatic factors such as ambient air temperature, relative humidity on ozone formation. More so, this study could be useful in developing baseline information for assessing the health impact of ozone emission and for urban airshed modelling.
估计马来西亚都市化地区每月平均臭氧排放量的趋势
摘要:本文分析了马来西亚一个高度城市化地区21年(1992 - 2012)的每日臭氧排放数据,目的是估计臭氧排放的趋势,并将这种趋势与该地区的社会经济和气候特征联系起来。本研究使用的日臭氧排放数据集来自世界臭氧和紫外线数据中心(WOUDC)。将数据汇总得到月平均排放量数据。对数据集进行描述性和推断性统计分析。利用MANN - KENDALL试验估计了臭氧排放的趋势。使用普通最小二乘法拟合得出趋势的大小,并使用MANN-KENDALL工具检验趋势的显著性。统计分析结果表明,西南季风期(5 ~ 8月)臭氧排放量最高,月平均臭氧排放量在研究期间差异显著。趋势分析表明,在2020年至2100年期间,除6月份预测臭氧浓度增加在0.403 ~ 0.414 ppt之间外,其余月份的年下降幅度在0.069 ~ 9.45 ppt之间。结果表明,利用多项式回归模型对臭氧排放数据集进行了较好的估计,预测能力在90%以上。本研究结果为环境温度、相对湿度等气候因子对臭氧形成的重要性提供了有益的证据。更重要的是,这项研究可能有助于制定基线信息,以评估臭氧排放对健康的影响,并有助于建立城市空气棚模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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