Evaluation and Prediction of PM10 and PM2.5 from Road Source Emissions in Kuala Lumpur City Centre

Azhari, Azliyana; Halim, Nor Diana Abdul; Mohtar, Anis Asma Ahmad; Aiyub, Kadaruddin; Latif, Mohd Talib; Ketzel, Matthias

doi:10.3390/su13105402

Cited by 13 publications

(7 citation statements)

References 69 publications

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“…Particulate matter (PM) is considered one of the most harmful components of ambient pollutants to humans [ 3 ]. Recent studies in the city of Kuala Lumpur, Malaysia demonstrated that PM pollution in this area is greatly contributed by vehicle emissions [ 4 , 5 , 6 , 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

The Influence of Environmental Polycyclic Aromatic Hydrocarbons (PAHs) Exposure on DNA Damage among School Children in Urban Traffic Area, Malaysia

Hisamuddin

Jalaludin

Bakar

et al. 2022

IJERPH

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This study aimed to investigate the association between particulate PAHs exposure and DNA damage in Malaysian schoolchildren in heavy traffic (HT) and low traffic (LT) areas. PAH samples at eight schools were collected using a low volume sampler for 24 h and quantified using Gas Chromatography-Mass Spectrometry. Two hundred and twenty-eight buccal cells of children were assessed for DNA damage using Comet Assay. Monte-Carlo simulation was performed to determine incremental lifetime cancer risk (ILCR) and to check the uncertainty and sensitivity of the estimated risk. Total PAH concentrations in the schools in HT area were higher than LT area ranging from 4.4 to 5.76 ng m−3 and 1.36 to 3.79 ng m−3, respectively. The source diagnostic ratio showed that PAHs in the HT area is pyrogenic, mainly from diesel emission. The 95th percentile of the ILCR for children in HT and LT area were 2.80 × 10−7 and 1.43 × 10−7, respectively. The degree of DNA damage was significantly more severe in children in the HT group compared to LT group. This study shows that total indoor PAH exposure was the most significant factor that influenced the DNA damage among children. Further investigation of the relationship between PAH exposure and genomic integrity in children is required to shed additional light on potential health risks.

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Section: Introductionmentioning

confidence: 99%

The Influence of Environmental Polycyclic Aromatic Hydrocarbons (PAHs) Exposure on DNA Damage among School Children in Urban Traffic Area, Malaysia

Hisamuddin

Jalaludin

Bakar

et al. 2022

IJERPH

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“…This study utilizes hourly historical air quality dataset which consisting of six air pollutant parameters namely particulate matter (PM2.5 and PM10), sulphur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), ozone (O 3 ) and carbon monoxide (CO) from two air quality monitoring stations located in Kuala Lumpur, Malaysia. Kuala Lumpur is Malaysia's capital city, the country's most developed and densely populated city 26 . The reason for selecting such datasets is because Kuala Lumpur the capital city of Malaysia with the highest rate of industrial activities, urbanization and traffic congestion.…”

Section: Methodsmentioning

confidence: 99%

PM2.5 forecasting for an urban area based on deep learning and decomposition method

Zaini

Ean

Ahmed

et al. 2022

Sci Rep

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Rapid growth in industrialization and urbanization have resulted in high concentration of air pollutants in the environment and thus causing severe air pollution. Excessive emission of particulate matter to ambient air has negatively impacted the health and well-being of human society. Therefore, accurate forecasting of air pollutant concentration is crucial to mitigate the associated health risk. This study aims to predict the hourly PM2.5 concentration for an urban area in Malaysia using a hybrid deep learning model. Ensemble empirical mode decomposition (EEMD) was employed to decompose the original sequence data of particulate matter into several subseries. Long short-term memory (LSTM) was used to individually forecast the decomposed subseries considering the influence of air pollutant parameters for 1-h ahead forecasting. Then, the outputs of each forecast were aggregated to obtain the final forecasting of PM2.5 concentration. This study utilized two air quality datasets from two monitoring stations to validate the performance of proposed hybrid EEMD-LSTM model based on various data distributions. The spatial and temporal correlation for the proposed dataset were analysed to determine the significant input parameters for the forecasting model. The LSTM architecture consists of two LSTM layers and the data decomposition method is added in the data pre-processing stage to improve the forecasting accuracy. Finally, a comparison analysis was conducted to compare the performance of the proposed model with other deep learning models. The results illustrated that EEMD-LSTM yielded the highest accuracy results among other deep learning models, and the hybrid forecasting model was proved to have superior performance as compared to individual models.

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“…Environmental aspects provide a significant role in increasing the global incidence of respiratory diseases perceived in recent decades [ 61 , 62 ]. In particular, asthma and nasal conjunctivitis mostly contribute to the global issue of diseases, with a world urban health incidence of schoolchildren of 5–20% and 0.8–39.7%, respectively [ 63 , 64 ].…”

Section: Literature Reviewsmentioning

confidence: 99%

Urban Air Pollution and Greenness in Relation to Public Health

Bikis

2023

Journal of Environmental and Public Health

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Background. Air pollution is the result of economic growth and urbanization. Air pollution has been progressively recognized as a serious problem for cities, through widespread effects on health and well-being. There is less concern from stakeholders about greenness and air pollution mitigating factors in an urban area. This research targeted to indicate the spatial dissemination of greenery, air quality levels (PM2.5, PM10, CO2, and AQI), and exposure to air quality-related health risks for the people in the urban area. Method. The data were collected by measuring air quality at transportation stations and manufacturing industries with Air visual pro, then observing and mapping greenness in the city within the administrative boundary by GIS (street greenery, forest, availability of greenness in the manufacturing industry), and lastly questionnaire and interview were employed for air quality-related health issues. Then, the air quality data were analyzed by using USAQI standards and health messages. Both quantitative and qualitative research approach had employed to explore air pollution levels, availability of greenness, and air quality-related health issues. Moreover, Health questionnaires and greenness were correlated with air quality levels by a simple linear regression model. Result. The result indicated that there was unhealthy air quality in the transportation and manufacturing industries. The measured air quality showed in a range of 50.13–96.84 μg/m3 of PM2.5, 645–1764 ppm of CO2, and 137–179 Air quality index (AQI). The highest mean of PM2.5 and air quality concentrations at Addis Ababa transportation stations and manufacturing sites ranged between 63.46 and 104.45 μg/m3 and 179–326, respectively. It was observed with less street greenery and greenness available in residential, commercial areas, and manufacturing industries. The pollution level was beyond the limit of WHO standards. The result has shown a health risk to the public in the city, particularly for drivers, street vendors, and manufacturing industry employees. Among 480 respondents, 57.92% experienced health risks due to air pollution by medical evidence. Conclusion. High health risks due to industries and old motor vehicles in the city need to be reduced by introducing policies and strategies for low-carbon, minimizing traveling distance, encouraging high occupancy vehicles, and promoting a green legacy in the street network and green building.

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Evaluation and Prediction of PM10 and PM2.5 from Road Source Emissions in Kuala Lumpur City Centre

Cited by 13 publications

References 69 publications

The Influence of Environmental Polycyclic Aromatic Hydrocarbons (PAHs) Exposure on DNA Damage among School Children in Urban Traffic Area, Malaysia

The Influence of Environmental Polycyclic Aromatic Hydrocarbons (PAHs) Exposure on DNA Damage among School Children in Urban Traffic Area, Malaysia

PM2.5 forecasting for an urban area based on deep learning and decomposition method

Urban Air Pollution and Greenness in Relation to Public Health

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