Influence of Meteorological Parameters on Particle Pollution (PM2.5 and PM10) in the Tropical Climate of Port Harcourt, Nigeria

Abstract

Aims: This study explores the influence of meteorological parameters such as wind direction, wind speed, rainfall, air temperature and relative humidity on PM2.5 and PM10 concentration.
 Place and Duration of Study: The study was conducted in Woji, an urban area of Port Harcourt city in Nigeria, between May and December 2019 covering wet and dry season.
 Methodology: The PM10 and PM2.5 concentrations were monitored for 236 days using photometric laser based particulate monitor while meteorological parameters were collected using Misol weather station mounted 10m above ground at Woji monitoring location.
 Results: PM concentration for all the months under study were below USEPA 24-hr standard except the month of December with PM2.5 = 58.8 μg/m³ and PM10 = 164.5 μg/m³.
 The result showed a significant but positively strong correlation between PM2.5 and PM10 (r = 0.97, P < .001). The wind speed significantly influenced PM2.5 and PM10 concentration with a weak negative correlation (r = - 0.22 and -0.23) respectively at P < .001. Also, PM2.5 and PM10 concentration exhibited a weak negative but significant correlation with rainfall (r = - 0.05 and -0.05) and air temperature (r = - 0.12 and -0.14) respectively at P< .001. Relative humidity showed a weak negative but not significant correlation with PM2.5 concentration (r = - 0.01) while PM10 exhibited weak but significant correlation with relative humidity (r = 0.04).
 Conclusion: The PM concentration exceedances recorded in month of December could be attributed to dry dusty north east trade wind that comes with harmattan as well as high atmospheric stability which is associated with low wind speed. The study revealed that meteorological parameters such as temperature, wind speed and rainfall plays significant role in the reduction of particulate matter loading through air dispersion, atmospheric instability and washout process while relative humidity increases PM10 concentration.

Temperature, Humidity and Air Pollution Relationships during a Period of Rainy and Dry Seasons in Lagos, West Africa

“…The influences of the wind direction and speed, rainfall, ambient temperature and relative humidity on the PM 2.5 , and PM 10 concentration values were presented in a study at an urban site in Port Harcourt, West Africa [9]. It was reported that the wind speed, rainfall and ambient temperature all significantly affected the PM 2.5 , and PM 10 concentration values but with weak correlations.…”

Source apportionment of SPM by positive matrix factorization and PM2.5 analysis in an urban industrial area

“…Relative humidity (RH) showed negative correlation with SPM concentrations ( r = −0.16) indicating that moisture settles the suspended dust particles by wetting and preventing crustal soil particles re-suspension in the atmosphere (Kulshrestha et al , 2004; Khillare and Sarkar, 2012; Wang et al , 2019). Overall correlation between p.m. 2.5 and RH is 0.5 indicating not so significant relation between the two (Onuorah et al , 2019). Spatial and seasonal variations exist between p.m. 2.5 and RH (Yang et al , 2017), during summer there is no relationship observed between p.m. 2.5 and RH ( r = 0) and during winter insignificant relation is observed between p.m. 2.5 and RH ( r = 0.2).…”

A Quantitative Modeling and Prediction Method for Sustained Rainfall-PM2.5 Removal Modes on a Micro-Temporal Scale

“…Sustained rainfall processes are often concomitant by changes in the accompanying meteorological factors such as temperature, humidity, wind speed and direction, which will affect the removal effect to varying degrees [33]. Therefore, in this paper, we conside the effect and intensity of the existing influence factors [34][35][36][37], and balance the availabil ity of their own observational data and the predictability of future trends to establish a se of accompanying influence factors F, including the (i) direct factor (FD) to describe rainfal characteristics, and the (ii) indirect factor (FI) to describe environmental characteristics The factors and impact effects are shown in Table 1.…”