Air quality pollutants and their relationship with meteorological variables in four suburbs of Greater Sydney, Australia

被引:0
作者
Khaled Haddad
Nicoletta Vizakos
机构
[1] Cumberland Council,
[2] Family First Chiropractic,undefined
来源
Air Quality, Atmosphere & Health | 2021年 / 14卷
关键词
Air quality pollutants; Meteorological variables; Generalised additive model; Trend level; Australia;
D O I
暂无
中图分类号
学科分类号
摘要
Meteorological variability plays a pivotal role in ambient air pollution. An in-depth analysis of air pollutants including meteorological variables in four suburbs of greater Sydney, Australia, was carried out for a continuous period of 24 months from January 2016 to 2018. Results revealed significant air quality problems with seasonal trends, for all six pollutants, in all suburbs. Maximum 24-h average PM10 concentrations for the four suburbs were 49.4, 55.3, 74.0 and 102.8 μg/m3 demonstrating severe PM10 air pollution events. NO2 concentrations exceeded national guideline limits and all four suburbs showed higher than recommended concentrations of O3. Generalised additive model analysis displayed varying dependencies between air pollutants and meteorological variables influenced by season and location. Different plots were used to interpret data in terms of meteorological variables. Generally, easterly and southerly winds led to the highest average concentrations of air pollutants for all suburbs. Extremes in air quality pollution concentrations were related to east and west winds and higher wind speeds (4–8 m/s). Wide variations existed in air pollutants between the 10th and 95th percentile values, especially PM10. Minimum and maximum concentration of all analysed pollutants occurred during low temperatures (11.7–18.4 °C) with the exception of ozone favouring higher temperatures (24–38 °C) during hotter months. Results show pollution formation varies in different seasons and suburbs, in relation to meteorological variables. This study can be used to mitigate, improve prediction and forecast accuracy of air pollution. Such studies open the possibilities to explore the effects of air quality and its impact on public health.
引用
收藏
页码:55 / 67
页数:12
相关论文
共 124 条
  • [1] Azmi SZ(2010)Trend and status of air quality at three different monitoring stations in the Klang Valley, Malaysia Air Qual Atmos Health 3 53-64
  • [2] Latif MT(2006)Multi-element analysis and characterization of atmospheric particulate pollution in Dhaka Aerosol Air Qual Res 6 334-359
  • [3] Ismail AS(2014)Characteristics of aerosol optical properties and meteorological parameters during three major dust events (2005–2010) over Beijing, China Atmos Res 150 129-142
  • [4] Juneng L(2012)Openair—an R package for air quality data analysis Environ Model Softw 27 52-61
  • [5] Jemain AA(2015)Characterization of Air Pollution Index and Its Affecting Factors in Industrial Urban Areas in Northeastern China Pol J Environ 24 4-139
  • [6] Begum BA(2011)Analysis of the relationship between O3, NO and NO2 in Tianjin, China Aerosol Air Qual Res 11 128-787
  • [7] Biswas SK(2015)Meteorological and urban landscape factors on severe air pollution in Beijing J Air Waste Manage Assoc 65 782-77
  • [8] Hopke PK(2015)Meteorological and seasonal influences in ambient air quality parameters of Dhaka city J Civ Eng 43 67-63
  • [9] Cohen DD(2009)Effect of climate change on air quality Atmos Environ 43 51-410
  • [10] Cao C(2019)How have the characteristics of air quality in a typical large Chinese city changed between 2011 and 2017? Air Qual Atmos Health 12 401-278