Author
Nurul Amalin Fatihah Kamarul Zaman
Bio: Nurul Amalin Fatihah Kamarul Zaman is an academic researcher from Universiti Teknologi Malaysia. The author has contributed to research in topics: AERONET & Air quality index. The author has an hindex of 4, co-authored 11 publications receiving 252 citations.
Papers
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TL;DR: The lockdown of anthropogenic activities due to COVID-19 has led to a notable decrease in AOD over SEA and in the pollution outflow over the oceanic regions, while a significant decrease in tropospheric NO2 was observed over areas not affected by seasonal biomass burning.
232 citations
TL;DR: In this paper, the authors developed empirical models for PM10 estimation from space over Malaysia using aerosol optical depth (AOD550) and meteorological (surface temperature, relative humidity and atmospheric stability) data (retrieved or estimated) from Moderate Resolution Imaging Spectroradiometer (MODIS) during the period 2007-2011.
64 citations
TL;DR: In this article, the authors summarize and discuss the results of previous studies that investigated the aerosol properties over Malaysia by means of various instrumentation and techniques, focusing on the use of remote sensing data to examine atmospheric aerosols.
34 citations
23 citations
TL;DR: In this paper, the authors used machine-learning (ML) models like Random Forest (RF) and Support Vector Regression (SVR) to estimate the PM2.5 concentrations across Malaysia using satellite AOD (aerosol optical depth) observations.
Abstract: Southeast Asia (SEA) is a hotspot region for atmospheric pollution and haze conditions, due to extensive forest, agricultural and peat fires. This study aims to estimate the PM2.5 concentrations across Malaysia using machine-learning (ML) models like Random Forest (RF) and Support Vector Regression (SVR), based on satellite AOD (aerosol optical depth) observations, ground measured air pollutants (NO2, SO2, CO, O3) and meteorological parameters (air temperature, relative humidity, wind speed and direction). The estimated PM2.5 concentrations for a two-year period (2018–2019) are evaluated against measurements performed at 65 air-quality monitoring stations located at urban, industrial, suburban and rural sites. PM2.5 concentrations varied widely between the stations, with higher values (mean of 24.2 ± 21.6 µg m−3) at urban/industrial stations and lower (mean of 21.3 ± 18.4 µg m−3) at suburban/rural sites. Furthermore, pronounced seasonal variability in PM2.5 is recorded across Malaysia, with highest concentrations during the dry season (June–September). Seven models were developed for PM2.5 predictions, i.e., separately for urban/industrial and suburban/rural sites, for the four dominant seasons (dry, wet and two inter-monsoon), and an overall model, which displayed accuracies in the order of R2 = 0.46–0.76. The validation analysis reveals that the RF model (R2 = 0.53–0.76) exhibits slightly better performance than SVR, except for the overall model. This is the first study conducted in Malaysia for PM2.5 estimations at a national scale combining satellite aerosol retrievals with ground-based pollutants, meteorological factors and ML techniques. The satisfactory prediction of PM2.5 concentrations across Malaysia allows a continuous monitoring of the pollution levels at remote areas with absence of measurement networks.
19 citations
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TL;DR: Overall, existing knowledge shows that the COVID-19 crisis entails an excellent opportunity for planners and policy makers to take transformative actions towards creating cities that are more just, resilient, and sustainable.
610 citations
TL;DR: The authors' analysis shows decline in PM2.5 concentration due to lockdown, mainly due to less movement of people to keep “social distancing” to control the spread of CORONA-19, which reflects the efforts made in the cities to curb theSpread of infection, that improve air quality.
310 citations
TL;DR: The lockdown of anthropogenic activities due to COVID-19 has led to a notable decrease in AOD over SEA and in the pollution outflow over the oceanic regions, while a significant decrease in tropospheric NO2 was observed over areas not affected by seasonal biomass burning.
232 citations
TL;DR: Investigating impacts of COVID-19 mitigation measures on ambient air quality in five Indian cities using in-situ measurements from 2015 to 2020 indicated improvements in air quality may be considered a temporary lockdown benefit as revitalising the economy could reverse this trend.
190 citations
TL;DR: Delhi's air quality has improved with a significant reduction in primary pollutants, however, an increase in O3 was observed, and the changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations.
187 citations