The interrelationships between air quality, land cover change, and road networks in the Lagos megacity have not been explored. Globally, there are knowledge gaps in understanding these dynamics, especially using remote sensing data. This study used multi-temporal and multi-spectral Landsat imageries at four epochs (2002, 2013, 2015, and 2020) to evaluate the aerosol optical thickness (AOT) levels in relation to land cover and road networks in the Lagos megacity. A look-up table (LUT) was generated using Py6S, a python-based 6S module, to simulate the AOT using land surface reflectance and top of atmosphere reflectance. A comparative assessment of the method against in situ measurements of particulate matter (PM) at different locations shows a strong positive correlation between the imagery-derived AOT values and the PMs. The AOT concentration across the land cover and road networks showed an increasing trend from 2002 to 2020, which could be explained by urbanization in the megacity. The higher concentration of AOT along the major roads is attributed to the high air pollutants released from vehicles, including home/office generators and industries along the road corridors. The continuous rise in pollutant values requires urgent intervention and mitigation efforts. Remote sensing-based AOT monitoring is a possible solution.
This study aims to determine the inorganic and carbonaceous components depending on the seasonal variation and size distribution of urban air particles in Kuala Lumpur. Different fractions of particulate matter (PM) were measured using a Nanosampler from 17 February 2017 until 27 November 2017. The water-soluble inorganic ions (WSIIs) and carbonaceous components in all samples were analysed using ion chromatography and carbon analyser thermal/optical reflectance, respectively. Total PM concentration reached its peak during the southwest (SW) season (70.99 ± 6.04 μg/m3), and the greatest accumulation were observed at PM0.5-1.0 (22%-30%, 9.55 ± 1.03 μg/m3) and PM2.5-10 (22%-25%, 10.34 ± 0.81 μg/m3). SO42-, NO3- and NH4+ were major contributors of WSIIs, and their formation was favoured mainly during SW season (80.5% of total ions). PM0.5-1.0 and PM2.5-10 exhibited the highest percentage of WSII size distribution, accounted for 28.4% and 13.5% of the total mass, respectively. The average contribution of carbonaceous species (OC + EC) to total carbonaceous concentrations were higher in PM0.5-1.0 (35.2%) and PM2.5-10 (26.6%). Ultrafine particles (PM<0.1) consistently indicated that the sources were from vehicle emission while the SW season was constantly dominated by biomass burning sources. Using the positive matrix factorization (PMF) model, secondary inorganic aerosol and biomass burning (30.3%) was known as a significant source of overall PM. As a conclusion, ratio and source apportionment indicate the mixture of biomass burning, secondary inorganic aerosols and motor vehicle contributed to the size-segregated PM and seasonal variation of inorganic and carbonaceous components of urban air particles.
This study aims to determine the composition of surfactants in the lake surface microlayer, rainwater, and atmospheric aerosols in the area surrounding Lake Chini, Pahang. Surfactants in the lake surface microlayer were taken from seven different stations around the lake, while samples of rainwater were taken from five different sampling stations. The samples of atmospheric aerosols were collected from the Lake Chini Research Centre which is in close proximity to the lake. The colorimetric analysis method was used to determine the composition and concentration of anionic surfactants as methylene blue active substances (MBAS) and cationic surfactants as disulphine blue active substances (DBAS). The concentration of anionic surfactants, as MBAS, in the surface microlayer ranged between 0.08 to 0.23 μmol L(-1), while the range of concentration of cationic surfactants as DBAS ranged from 0.09 to 0.11 μmol L(-1). The concentration of MBAS was higher in rainwater when compared to surfactants in the lake surface microlayer. The high concentration of surfactants in the fine mode of atmospheric aerosols suggests that natural and anthropogenic sources of surfactants contribute to the atmospheric surfactants.
Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.
This study aims to determine the source apportionment of surfactants in marine aerosols at two selected stations along the Malacca Straits. The aerosol samples were collected using a high volume sampler equipped with an impactor to separate coarse- and fine-mode aerosols. The concentrations of surfactants, as methylene blue active substance and disulphine blue active substance, were analysed using colorimetric method. Ion chromatography was employed to determine the ionic compositions. Principal component analysis combined with multiple linear regression was used to identify and quantify the sources of atmospheric surfactants. The results showed that the surfactants in tropical coastal environments are actively generated from natural and anthropogenic origins. Sea spray (generated from sea-surface microlayers) was found to be a major contributor to surfactants in both aerosol sizes. Meanwhile, the anthropogenic sources (motor vehicles/biomass burning) were predominant contributors to atmospheric surfactants in fine-mode aerosols.
Satellite observations for regional air quality assessment rely on comprehensive spatial coverage, and daily monitoring with reliable, cloud-free data quality. We investigated spatiotemporal variation and data quality of two global satellite Aerosol Optical Depth (AOD) products derived from MODIS and VIIRS imagery. AOD is considered an essential atmospheric parameter strongly related to ground Particulate Matter (PM) in Southeast Asia (SEA). We analyze seasonal variation, urban/rural area influence, and biomass burning effects on atmospheric pollution. Validation indicated a strong relationship between AERONET ground AOD and both MODIS AOD (R2 = 0.81) and VIIRS AOD (R2 = 0.68). The monthly variation of satellite AOD and AERONET AOD reflects two seasonal trends of air quality separately for mainland countries including Myanmar, Laos, Cambodia, Thailand, Vietnam, and Taiwan, Hong Kong, and for maritime countries consisting of Indonesia, Philippines, Malaysia, Brunei, Singapore, and Timor Leste. The mainland SEA has a pattern of monthly AOD variation in which AODs peak in March/April, decreasing during wet season from May-September, and increasing to the second peak in October. However, in maritime SEA, AOD concentration peaks in October. The three countries with the highest annual satellite AODs are Singapore, Hong Kong, and Vietnam. High urban population proportions in Singapore (40.7%) and Hong Kong (21.6%) were associated with high AOD concentrations as expected. AOD values in SEA urban areas were a factor of 1.4 higher than in rural areas, with respective averages of 0.477 and 0.336. The AOD values varied proportionately to the frequency of biomass burning in which both active fires and AOD peak in March/April and September/October. Peak AOD in September/October in some countries could be related to pollutant transport of Indonesia forest fires. This study analyzed satellite aerosol product quality in relation to AERONET in SEA countries and highlighted framework of air quality assessment over a large, complicated region.
The rapid spread of the SARS-CoV-2 in the COVID-19 pandemic had raised questions on the route of transmission of this disease. Initial understanding was that transmission originated from respiratory droplets from an infected host to a susceptible host. However, indirect contact transmission of viable virus by fomites and through aerosols has also been suggested. Herein, we report the involvement of fine indoor air particulates with a diameter of ≤ 2.5 µm (PM2.5) as the virus's transport agent. PM2.5 was collected over four weeks during 48-h measurement intervals in four separate hospital wards containing different infected clusters in a teaching hospital in Kuala Lumpur, Malaysia. Our results indicated the highest SARS-CoV-2 RNA on PM2.5 in the ward with number of occupants. We suggest a link between the virus-laden PM2.5 and the ward's design. Patients' symptoms and numbers influence the number of airborne SARS-CoV-2 RNA with PM2.5 in an enclosed environment.
A study was done to determine the concentrations of surfactants on the sea-surface microlayer and in atmospheric aerosols in several coastal areas around the Malaysian peninsula. The concentrations of surfactants from the sea-surface microlayer (collected using rotation drum) and from aerosols (collected using HVS) were analyzed as methylene blue active substances and disulphine blue active substances through the colorimetric method using a UV-vis spectrophotometer. The results of this study showed that the average concentrations of surfactants in the sea-surface microlayer ranged between undetected and 0.36+/-0.34 micromol L(-1) for MBAS and between 0.11+/-0.02 and 0.21+/-0.13 micromol L(-1) for DBAS. The contribution of surfactants from the sea-surface microlayer to the composition of surfactants in atmospheric aerosols appears to be very minimal and more dominant in fine mode aerosols.
This study aims to determine the concentrations of surfactants in the surface microlayer (SML), subsurface water (SSW) and fine mode aerosol (diameter size
Size-segregated airborne fine (PM2.1) and coarse (PM>2.1) particulates were measured in an urban environment over central Indo-Gangetic plain in between 2015 and 2018 to get insights into its nature, chemistry and sources. Mean (±1σ) concentration of PM2.1 was 98 (±76) μgm-3 with a seasonal high during winter (DJF, 162 ± 71 μgm-3) compared to pre-monsoon specific high in PM>2.1 (MAMJ, 177 ± 84 μgm-3) with an annual mean of 170 (±69) μgm-3. PM2.1 was secondary in nature with abundant secondary inorganic aerosols (20% of particulate mass) and water-soluble organic carbon (19%) against metal enriched (25%) PM>2.1, having robust signature of resuspensions from Earth's crust and road dust. Ammonium-based neutralization of particulate acidity was essentially in PM2.1 with an indication of predominant H2SO4 neutralization in bisulfate form compared to Ca2+ and Mg2+-based neutralization in PM>2.1. Molecular distribution of n-alkanes homologues (C17-C35) showed Cmax at C23 (PM2.1) and C18 (PM>2.1) with weak dominance of odd-numbered n-alkanes. Carbon preference index of n-alkanes was close to unity (PM2.1: 1.4 ± 0.3; PM>2.1: 1.3 ± 0.4). Fatty acids (C12-C26) were characterized with predominance of even carbon with Cmax at n-hexadecanoic acid (C16:0). Low to high molecular weight fatty acid ratio ranged from 2.0 (PM>2.1) to 5.6 (PM2.1) with vital signature of anthropogenic emissions. Levoglucosan was abundant in PM2.1 (758 ± 481 ngm-3) with a high ratio (11.6) against galactosan, emphasizing robust contribution from burning of hardwood and agricultural residues. Receptor model resolves secondary aerosols and biomass burning emissions (45%) as the most influential sources of PM2.1 whereas, crustal (29%) and secondary aerosols (29%) were found responsible for PM>2.1; with significant variations among the seasons.
While past studies have detected heavy metals in aerosols emitted from electronic cigarettes (ECIG), they have provided little information detailing the practical implications of the findings to the Malaysian population due to variations between products. The aims of this study were to analyse heavy metals of interest (HMOI) in the aerosols emitted from selected ECIG and to evaluate potential health risks by referring to the permissible daily exposure (PDE) from inhalational medications defined by the United States Pharmacopeia Chapter 232. All four HMOI were detected in aerosols emitted from the selected ECIG in Sarawak. Among the four, Cr was present at the highest median levels (6.86 ng/m3), followed by Ni (0.30 ng/m3), Pb (0.19 ng/m3) and Cd (0.01 ng/m3). Five out of 100 combinations (5%) of ECIG and ECIG liquids were found to emit Cr that exceed the recommended PDE. Future studies examining more heavy metal variants, using a larger sample size and different analytical techniques to compare various ECIGs are recommended.
Terrestrial anionic surfactants (AS) enter the marine environment through coastal region. Despite that, in general limited knowledge is available on the coastal AS transfer pathway. This paper aims to assess the distributions and exchange of AS in the Peninsular Malaysia coastal environments, adjacent to the southern waters of South China Sea and Strait of Malacca. An assessment case study was conducted by a review on the available data from the workgroup that span between the year 2008 and 2019. The findings showed that AS dominated in the sea surface microlayer (SML, 57%) compared to subsurface water (SSW, 43 %). AS were also found to have dominated in fine mode (FM, 71 %) compared to coarse mode (CM, 29 %) atmospheric aerosols. SML AS correspond to the SSW AS (p < 0.01); however, highest enrichment factor (EF) of the SML AS was not consistent with highest SSW AS. Direct AS exchange between SML and FM and CM was not observed. Furthermore, the paper concludes AS mainly located in the SML and FM and could potentially be the main transfer pathway in the coastal environment.
In this study, we assess the intense pollution episode of June 2013, in Riau province, Indonesia from land clearing. We relied on satellite retrievals of aerosols and Carbon monoxide (CO) due to lack of ground measurements. We used both the yearly and daily data for aerosol optical depth (AOD), fine mode fraction (FMF), aerosol absorption optical depth (AAOD) and UV aerosol index (UVAI) for characterizing variations. We found significant enhancement in aerosols and CO during the pollution episode. Compared to mean (2008-2012) June AOD of 0.40, FMF-0.39, AAOD-0.45, UVAI-1.77 and CO of 200 ppbv, June 2013 values reached 0.8, 0.573, 0.672, 1.77 and 978 ppbv respectively. Correlations of fire counts with AAOD and UVAI were stronger compared to AOD and FMF. Results from a trajectory model suggested transport of air masses from Indonesia towards Malaysia, Singapore and southern Thailand. Our results highlight satellite-based mapping and monitoring of pollution episodes in Southeast Asia.
This study was conducted to determine the composition and source apportionment of surfactant in atmospheric aerosols around urban and semi-urban areas in Malaysia based on ionic compositions. Colorimetric analysis was undertaken to determine the concentrations of anionic surfactants as Methylene Blue Active Substances (MBAS) and cationic surfactants as Disulphine Blue Active Substances (DBAS) using a UV spectrophotometer. Ionic compositions were determined using ion chromatography for cations (Na(+), NH4(+), K(+), Mg(2+), Ca(2+)) and anions (F(-), Cl(-), NO3(-), SO4(2-)). Principle component analysis (PCA) combined with multiple linear regression (MLR) were used to identify the source apportionment of MBAS and DBAS. Results indicated that the concentrations of surfactants at both sampling sites were dominated by MBAS rather than DBAS especially in fine mode aerosols during the southwest monsoon. Three main sources of surfactants were identified from PCA-MLR analysis for MBAS in fine mode samples particularly in Kuala Lumpur, dominated by motor vehicles, followed by soil/road dust and sea spray. Besides, for MBAS in coarse mode, biomass burning/sea spray were the dominant source followed by motor vehicles/road dust and building material.