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Health impacts from TRAPs and carbon emissions in the projected electric vehicle growth and energy generation mix scenarios in Malaysia

Kwan SC, Zakaria SB, Ibrahim MF, Wan Mahiyuddin WR, Md Sofwan N, A Wahab MI, et al.

Environ Res, 2023 Jan 01;216(Pt 2):114524.
PMID: 36228692 DOI: 10.1016/j.envres.2022.114524

Road transport contributes over 70% of air pollution in urban areas and is the second largest contributor to the total carbon dioxide emissions in Malaysia at 21% in 2016. Transport-related air pollutants (TRAPs) such as NOx, SO2, CO and particulate matter (PM) pose significant threats to the urban population's health. Malaysia has targeted to deploy 885,000 EV cars on the road by 2030 in the Low Carbon Mobility Blueprint (LCMB). This study aims to quantify the health co-benefits of electric vehicle adoption from their impacts on air quality in Malaysia. Two EV uptake projections, i.e. LCMB and Revised EV Adoption (REVA) projections, and five electricity generation mix scenarios were modelled up to 2040. We used comparative health risk assessment to estimate the potential changes in mortality and burden of diseases (BoD) from the emissions in each scenario. Intake fractions and exposure-risk functions were used to calculate the burden from respiratory diseases (PM2.5, NOx, SO2, CO), cardiovascular diseases and lung cancer (PM2.5). Results showed that along with a net reduction of carbon emissions across all scenarios, there could be reduced respiratory mortality from NOx by 10,200 mortality (176,200 DALYs) and SO2 by 2600 mortality (45,400 DALYs) per year in 2040. However, there could also be additional 719 mortality (9900 DALYs) per year from PM2.5 and 329 mortality (5600 DALYs) from CO per year. The scale of reduction in mortality and BoD from NOx and SO2 are significantly larger than the scale of increase from PM2.5 and CO, indicating potential net positive health impacts from the EV adoption in the scenarios. The health cost savings from the reduced BoD of respiratory mortality could reach up to RM 7.5 billion per year in 2040. In conclusion, EV is a way forward in promoting a healthy and sustainable future transport in Malaysia.

Matched MeSH terms: Particulate Matter/toxicity
Traffic-Related Air Pollution (TRAP) in relation to respiratory symptoms and lung function of school-aged children in Kuala Lumpur

Suhaimi NF, Jalaludin J, Roslan NIS

Int J Environ Health Res, 2024 Mar;34(3):1384-1396.
PMID: 37160687 DOI: 10.1080/09603123.2023.2211020

Traffic-Related Air Pollution (TRAP) exposure has been connected to significant health impacts among children. A cross-sectional comparative study was conducted among school children in Malaysia to determine the relationship between their exposure to TRAP and respiratory health effects. Air monitoring was conducted in schools and residences, while the children's routines were investigated using a diary of daily activities. Respondents' background and respiratory symptoms were obtained from a validated questionnaire, while a spirometry test was performed to determine their lung function status. The distances between schools and residences from the had contributed to the higher concentration of air pollutants in this study, which had associations with the children's respiratory symptoms and lung function status. PM2.5 was the main predictor influencing the respondents' respiratory symptoms and lung function abnormalities. In conclusion, exposure of school children to a high TRAP level might increase their risk of getting respiratory symptoms and lung function reduction.

Matched MeSH terms: Particulate Matter/toxicity
Fulltext Exposure to Particulate PAHs on Potential Genotoxicity and Cancer Risk among School Children Living Near the Petrochemical Industry

Sopian NA, Jalaludin J, Abu Bakar S, Hamedon TR, Latif MT

Int J Environ Res Public Health, 2021 03 04;18(5).
PMID: 33806616 DOI: 10.3390/ijerph18052575

This study aimed to assess the association of exposure to particle-bound (PM2.5) polycyclic aromatic hydrocarbons (PAHs) with potential genotoxicity and cancer risk among children living near the petrochemical industry and comparative populations in Malaysia. PM2.5 samples were collected using a low-volume sampler for 24 h at three primary schools located within 5 km of the industrial area and three comparative schools more than 20 km away from any industrial activity. A gas chromatography-mass spectrometer was used to determine the analysis of 16 United States Environmental Protection Agency (USEPA) priority PAHs. A total of 205 children were randomly selected to assess the DNA damage in buccal cells, employing the comet assay. Total PAHs measured in exposed and comparative schools varied, respectively, from 61.60 to 64.64 ng m-3 and from 5.93 to 35.06 ng m-3. The PAH emission in exposed schools was contributed mainly by traffic and industrial emissions, dependent on the source apportionment. The 95th percentiles of the incremental lifetime cancer risk estimated using Monte Carlo simulation revealed that the inhalation risk for the exposed children and comparative populations was 2.22 × 10-6 and 2.95 × 10-7, respectively. The degree of DNA injury was substantially more severe among the exposed children relative to the comparative community. This study reveals that higher exposure to PAHs increases the risk of genotoxic effects and cancer among children.

Matched MeSH terms: Particulate Matter/toxicity
Fulltext Chronic airflow obstruction and ambient particulate air pollution

Amaral AFS, Burney PGJ, Patel J, Minelli C, Mejza F, Mannino DM, et al.

Thorax, 2021 12;76(12):1236-1241.
PMID: 33975927 DOI: 10.1136/thoraxjnl-2020-216223

Smoking is the most well-established cause of chronic airflow obstruction (CAO) but particulate air pollution and poverty have also been implicated. We regressed sex-specific prevalence of CAO from 41 Burden of Obstructive Lung Disease study sites against smoking prevalence from the same study, the gross national income per capita and the local annual mean level of ambient particulate matter (PM2.5) using negative binomial regression. The prevalence of CAO was not independently associated with PM2.5 but was strongly associated with smoking and was also associated with poverty. Strengthening tobacco control and improved understanding of the link between CAO and poverty should be prioritised.

Matched MeSH terms: Particulate Matter/toxicity
Fulltext The use of quantile regression to forecast higher than expected respiratory deaths in a daily time series: a study of New York City data 1987-2000

Soyiri IN, Reidpath DD

PLoS One, 2013;8(10):e78215.
PMID: 24147122 DOI: 10.1371/journal.pone.0078215

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths. Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal/temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1). The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2) This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept.

Matched MeSH terms: Particulate Matter/toxicity
Fulltext Biomarker as a research tool in linking exposure to air particles and respiratory health

Suhaimi NF, Jalaludin J

Biomed Res Int, 2015;2015:962853.
PMID: 25984536 DOI: 10.1155/2015/962853

Some of the environmental toxicants from air pollution include particulate matter (PM10), fine particulate matter (PM2.5), and ultrafine particles (UFP). Both short- and long-term exposure could result in various degrees of respiratory health outcomes among exposed persons, which rely on the individuals' health status.
METHODS: In this paper, we highlight a review of the studies that have used biomarkers to understand the association between air particles exposure and the development of respiratory problems resulting from the damage in the respiratory system. Data from previous epidemiological studies relevant to the application of biomarkers in respiratory system damage reported from exposure to air particles are also summarized.
RESULTS: Based on these analyses, the findings agree with the hypothesis that biomarkers are relevant in linking harmful air particles concentrations to increased respiratory health effects. Biomarkers are used in epidemiological studies to provide an understanding of the mechanisms that follow airborne particles exposure in the airway. However, application of biomarkers in epidemiological studies of health effects caused by air particles in both environmental and occupational health is inchoate.
CONCLUSION: Biomarkers unravel the complexity of the connection between exposure to air particles and respiratory health.

Matched MeSH terms: Particulate Matter/toxicity*
Risk of concentrations of major air pollutants on the prevalence of cardiovascular and respiratory diseases in urbanized area of Kuala Lumpur, Malaysia

Tajudin MABA, Khan MF, Mahiyuddin WRW, Hod R, Latif MT, Hamid AH, et al.

Ecotoxicol Environ Saf, 2019 Apr 30;171:290-300.
PMID: 30612017 DOI: 10.1016/j.ecoenv.2018.12.057

Rapid urbanisation in Malaysian cities poses risks to the health of residents. This study aims to estimate the relative risk (RR) of major air pollutants on cardiovascular and respiratory hospitalisations in Kuala Lumpur. Daily hospitalisations due to cardiovascular and respiratory diseases from 2010 to 2014 were obtained from the Hospital Canselor Tuanku Muhriz (HCTM). The trace gases, PM10 and weather variables were obtained from the Department of Environment (DOE) Malaysia in consistent with the hospitalisation data. The RR was estimated using a Generalised Additive Model (GAM) based on Poisson regression. A "lag" concept was used where the analysis was segregated into risks of immediate exposure (lag 0) until exposure after 5 days (lag 5). The results showed that the gases could pose significant risks towards cardiovascular and respiratory hospitalisations. However, the RR value of PM10 was not significant in this study. Immediate effects on cardiovascular hospitalisations were observed for NO2 and O3 but no immediate effect was found on respiratory hospitalisations. Delayed effects on cardiovascular and respiratory hospitalisations were found with SO2 and NO2. The highest RR value was observed at lag 4 for respiratory admissions with SO2 (RR = 1.123, 95% CI = 1.045-1.207), followed by NO2 at lag 5 for cardiovascular admissions (RR = 1.025, 95% CI = 1.005-1.046). For the multi-pollutant model, NO2 at lag 5 showed the highest risks towards cardiovascular hospitalisations after controlling for O3 8 h mean lag 1 (RR = 1.026, 95% CI = 1.006-1.047), while SO2 at lag 4 showed highest risks towards respiratory hospitalisations after controlling for NO2 lag 3 (RR = 1.132, 95% CI = 1.053-1.216). This study indicated that exposure to trace gases in Kuala Lumpur could lead to both immediate and delayed effects on cardiovascular and respiratory hospitalisations.

Matched MeSH terms: Particulate Matter/toxicity