Source apportionment and health risk assessment among specific age groups during haze and non-haze episodes in Kuala Lumpur, Malaysia

Nor Azura Sulong; Mohd Talib Latif; Md Firoz Khan; Norhaniza Amil; Matthew J Ashfold; Muhammad Ikram Abdul Wahab; Kok Meng Chan; Mazrura Sahani

doi:10.1016/j.scitotenv.2017.05.153

Source apportionment and health risk assessment among specific age groups during haze and non-haze episodes in Kuala Lumpur, Malaysia

Sci Total Environ. 2017 Dec 1:601-602:556-570. doi: 10.1016/j.scitotenv.2017.05.153. Epub 2017 May 31.

Authors

Nor Azura Sulong¹, Mohd Talib Latif², Md Firoz Khan³, Norhaniza Amil⁴, Matthew J Ashfold⁵, Muhammad Ikram Abdul Wahab⁶, Kok Meng Chan⁶, Mazrura Sahani⁶

Affiliations

¹ School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia.
² School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia; Institute for Environment and Development (Lestari), Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia. Electronic address: talib@ukm.my.
³ Centre for Tropical Climate Change System, Institute of Climate Change, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia.
⁴ Environmental Technology Division, School of Industrial Technology, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia.
⁵ School of Environmental and Geographical Sciences, University of Nottingham Malaysia Campus, 43500 Semenyih, Selangor, Malaysia.
⁶ Environmental Health and Industrial Safety Program, School of Diagnostic Science and Applied Health, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur, Malaysia.

PMID: 28575833
DOI: 10.1016/j.scitotenv.2017.05.153

Abstract

This study aims to determine PM_2.5 concentrations and their composition during haze and non-haze episodes in Kuala Lumpur. In order to investigate the origin of the measured air masses, the Numerical Atmospheric-dispersion Modelling Environment (NAME) and Global Fire Assimilation System (GFAS) were applied. Source apportionment of PM_2.5 was determined using Positive Matrix Factorization (PMF). The carcinogenic and non-carcinogenic health risks were estimated using the United State Environmental Protection Agency (USEPA) method. PM_2.5 samples were collected from the centre of the city using a high-volume air sampler (HVS). The results showed that the mean PM_2.5 concentrations collected during pre-haze, haze and post-haze periods were 24.5±12.0μgm^-3, 72.3±38.0μgm^-3 and 14.3±3.58μgm^-3, respectively. The highest concentration of PM_2.5 during haze episode was five times higher than World Health Organisation (WHO) guidelines. Inorganic compositions of PM_2.5, including trace elements and water soluble ions were determined using inductively coupled plasma-mass spectrometry (ICP-MS) and ion chromatography (IC), respectively. The major trace elements identified were K, Al, Ca, Mg and Fe which accounted for approximately 93%, 91% and 92% of the overall metals' portions recorded during pre-haze, haze and post-haze periods, respectively. For water-soluble ions, secondary inorganic aerosols (SO₄^2-, NO₃^- and NH₄⁺) contributed around 12%, 43% and 16% of the overall PM_2.5 mass during pre-haze, haze and post-haze periods, respectively. During haze periods, the predominant source identified using PMF was secondary inorganic aerosol (SIA) and biomass burning where the NAME simulations indicate the importance of fires in Sumatra, Indonesia. The main source during pre-haze and post-haze were mix SIA and road dust as well as mineral dust, respectively. The highest non-carcinogenic health risk during haze episode was estimated among the infant group (HI=1.06) while the highest carcinogenic health risk was estimated among the adult group (2.27×10^-5).

Keywords: Biomass burning; Carcinogenic and non-carcinogenic health risk; PM(2.5) aerosols; PMF; Transboundary smoke haze.

MeSH terms

Air Pollutants / analysis*
Air Pollution / statistics & numerical data*
Cities
Environmental Exposure / analysis*
Environmental Exposure / statistics & numerical data
Fires
Humans
Malaysia
Particulate Matter / analysis
Risk Assessment*
Trace Elements / analysis

Substances

Air Pollutants
Particulate Matter
Trace Elements