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.
Particulate matter (PM) emissions from vegetation and peat fires in Equatorial Asia cause poor regional air quality. Burning is greatest during drought years, resulting in strong inter-annual variability in emissions. We make the first consistent estimate of the emissions, air quality and public health impacts of Equatorial Asian fires during 2004–2015. The largest dry season (August—October) emissions occurred in 2015, with PM emissions estimated as 9.4 Tg, more than triple the average dry season emission (2.7 Tg). Fires in Sumatra and Kalimantan caused 94% of PM emissions from fires in Equatorial Asia. Peat combustion in Indonesian peatlands contributed 45% of PM emissions, with a greater contribution of 68% in 2015. We used the WRF-chem model to simulate dry season PM for the 6 biggest fire years during this period (2004, 2006, 2009, 2012, 2014, 2015). The model reproduces PM concentrations from a measurement network across Malaysia and Indonesia, suggesting our PM emissions are realistic. We estimate long-term exposure to PM resulted in 44 040 excess deaths in 2015, with more than 15 000 excess deaths annually in 2004, 2006, and 2009. Exposure to PM from dry season fires resulted in an estimated 131 700 excess deaths during 2004–2015. Our work highlights that Indonesian vegetation and peat fires frequently cause adverse impacts to public health across the region.
Exposure to fine particulate-bound toxic metals in ambient air poses adverse effects to human. This study aims to determine the spatial variability in heavy metals in PM2.5 samples, for identifying their potential sources and to perform health risk modelling. PM2.5 samples were collected using a high-volume sampler on a 24 h basis from three sites in Johor areas in Malaysia from January to March 2019. Metals were initially extracted using microwave-assisted digestion and the metal concentrations were analyzed using inductively coupled plasma mass spectroscopy. Overall, the abundant metals in PM2.5 among the metals analyzed were Zn with mean 29.92 ng/m3 and Se with mean 27.02 ng/m3. The sources of PM-bound metals were identified using absolute principal component score with multiple linear regression. The major contribution was noted from vehicle emission (41%). Other potential sources for the metals in PM2.5 were from coal-fired power plants (34%) and oil refineries and industrial emission (4%), leaving 22% of metals undefined. From the health risk analysis, the hazard quotient (HQ) and excess lifetime cancer risk (ELCR) values of the metals were within the tolerance level. The trend for HQ values was Co < Zn < Pb < Cu < Ni < As for adolescents and Co < Zn < Cu < Pb < Ni < As for adult age, whereas for ELCR values, the trends were the same for both adolescent and adult age groups as Pb < Ni < As. Few of the toxic metals showed comparatively high HQ values that might be a risk in long-term exposure. Considering the highest noted contribution from vehicular emissions, it is advised to raise public awareness to practice carpooling and use public transportation to reduce emissions from vehicular sources.
This paper describes the application of principal component analysis (PCA) and artificial neural network (ANN) to predict the air pollutant index (API) within the seven selected Malaysian air monitoring stations in the southern region of Peninsular Malaysia based on seven years database (2005-2011). Feed-forward ANN was used as a prediction method. The feed-forward ANN analysis demonstrated that the rotated principal component scores (RPCs) were the best input parameters to predict API. From the 4 RPCs, only 10 (CO, O 3 , PM 10 , NO 2 , CH 4 , NmHC, THC, wind direction, humidity and ambient temp) out of 12 prediction variables were the most significant parameters to predict API. The results proved that the ANN method can be applied successfully as tools for decision making and problem solving for better atmospheric management.
The COVID-19 pandemic has plunged the world into uncharted territory, leaving people feeling helpless in the face of an invisible threat of unknown duration that could adversely impact the national economic growths. According to the World Health Organization (WHO), the SARS-CoV-2 spreads primarily through droplets of saliva or discharge from the mouth or nose when an infected person coughs or sneezes. However, the transmission of the SARS-CoV-2 through aerosols remains unclear. In this study, computational fluid dynamic (CFD) is used to complement the investigation of the SARS-CoV-2 transmission through aerosol. The Lagrangian particle tracking method was used to analyze the dispersion of the exhaled particles from a SARS-CoV-2-positive patient under different exhale activities and different flow rates of chilled (cooling) air supply. Air sampling of the SARS-CoV-2 patient ward was conducted for 48-h measurement intervals to collect the indoor air sample for particulate with diameter less than 2.5 μm. Then, the reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was conducted to analyze the collected air sample. The simulation demonstrated that the aerosol transmission of the SARS-CoV-2 virus in an enclosed room (such as a hospital ward) is highly possible.
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