Spatial and Temporal Variation of Particulate Matter Around Lagos Environs

Abodunrin Oluwasayo Peter
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Abstract

Air monitoring is very essential for characterizing health risks, formulating cost-effective abatement strategies, creating and enforcing appropriate air quality standards, and as well as healthy urban planning. This study investigates the spatial and temporal variation of aerosol pollution in Lagos environs, Nigeria. Selected sampling locations were Computer Village (CV), Oshodi Garage (OG), Magodo Estate (MG), and Caleb International College (CIC). Associated anthropogenic activities were the basis for the selection of the sampling location. Measurements of particulate matters were undertaken by employing the AEROCET 531S device in these selected residential, academic, and commercial environments across Lagos State. The measurements were taken at approximately 2 m from the ground in each sampling location. Data analysis and visualization were executed with python to enhance the visualization of the spatial and temporal distribution of the different particulate matter within and across the locations. A pronounced gradient of the particulate matter concentrations (µg/m3) was observed across the study area. The study outcome demonstrates that particulate matter distribution is dominated by PM10 in all locations under consideration. The proportions of fine particles to coarse particles in these environments were low ranging from 0.027 – 0.277 in CV, 0.018 – 0.395 in OG, 0.080 – 0.291 in MG, and 0.028 – 0.272 in CIC. Findings from this study established the dominance of coarse particles assumed to be contributed by cement dust, coal dust, flour, paint spray, pollen, cloud droplets, etc.
拉各斯周边颗粒物时空变化特征
空气监测对于确定健康风险特征、制定具有成本效益的减少战略、制定和执行适当的空气质量标准以及健康的城市规划至关重要。研究了尼日利亚拉各斯周边地区气溶胶污染的时空变化特征。选定的采样地点是计算机村(CV), Oshodi车库(OG), Magodo庄园(MG)和Caleb国际学院(CIC)。相关的人为活动是选择采样地点的依据。在拉各斯州选定的住宅、学术和商业环境中,采用AEROCET 531S设备对颗粒物进行测量。测量是在每个采样地点离地面约2米的地方进行的。使用python执行数据分析和可视化,以增强不同位置内和跨位置的不同颗粒物的时空分布的可视化。在整个研究区域观察到明显的颗粒物浓度梯度(µg/m3)。研究结果表明,在所有考虑的地点,颗粒物分布以PM10为主。细颗粒与粗颗粒的比值较低,CV为0.027 ~ 0.277,OG为0.018 ~ 0.395,MG为0.080 ~ 0.291,CIC为0.028 ~ 0.272。这项研究的结果确定了粗颗粒的优势,这些粗颗粒被认为是由水泥粉尘、煤尘、面粉、油漆喷雾、花粉、云滴等造成的。
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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