Putri Anis Syahira Mohamad Jamil, Nur Athirah Diyana Mohammad Yusof, Karmegam Karuppiah This email address is being protected from spambots. You need JavaScript enabled to view it., Irniza Rasdi, Juliana Jalaludin, Shamsul Bahri Mohd Tamrin, Vivien How, Sivasankar Sambasivam, Nurul Maizura Hashim

Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia



Received: February 26, 2020
Revised: June 30, 2020
Accepted: July 21, 2020

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Mohamad Jamil, P.A.S., Mohammad Yusof, N.A.D., Karuppiah, K., Rasdi, I., Jalaludin, J., Mohd Tamrin, S.B., How, V., Sambasivam, S. and Hashim, N.M. (2020). Malaysian Traffic Police in Highly Populated Areas: Is it Safe Working Outdoors on a Daily Basis? Aerosol Air Qual. Res. 20: 2003–2011. https://doi.org/10.4209/aaqr.2020.02.0080


  • Traffic police mainly work on regulating traffic flow in congested junctions.
  • They are exposed to unhealthy air for long hours of working outdoors.
  • PM10 concentration recorded above the Malaysian standard every year.
  • The increasing trends in number of vehicles can be seen every year in both states.
  • A strong positive correlation of vehicles on road is seen with CO, O3 and NO2.


Previous studies have reported on the increment in the concentration levels of outdoor air pollution affecting the lung functions among traffic police as they work outdoors, on an average, for 12 hours daily. This paper provides an analysis of the outdoor air pollutant trends. It is novel in considering how it can be used to understand the impact on the 1,149 Malaysian Traffic Police in the states of Kuala Lumpur (KL) and Johor Bahru (JB). The study used 165, 604 data from a nine-year database (2009–2017) of selected Malaysian air monitoring stations in KL and JB. The statistical analysis showed that the yearly trends of PM10 were above the Malaysian Ambient Air Quality Guideline (MAAQG) standard while the SO2, O3, NO2, and CO readings were below the standard. An increasing trend was noticed in the total number of vehicles in both states from 2009 to 2017. All the pollutants were positively correlated with each other, indicating that most of the pollutants are from similar sources. There is a strong positive correlation between the total number of vehicles and CO, NO2, and O3. This study proves the trends and consequences of outdoor air pollutants coupled with the rise in the number of vehicles that can affect respiratory health and well-being of the traffic police personnel. As a resolution to this, an efficient risk control such as air monitoring system for traffic police is necessary. The findings of this study will facilitate its usefulness to the authorities, management, policymakers, and researchers in the years ahead.

Keywords: Traffic-related air pollutant; Air quality; Hazardous air pollutants; Respiratory health; PM10.


The primary task of traffic police personnel in Malaysia, according to the Police Act of 1967, is to monitor and regulate the traffic flow of public roads and the enforcement of the Road Transport Act 1987 (Police Act 1967). Hence, they are required to work outdoors for long periods (8–16 hours) (ILO, 2012). The Traffic Police in the Point Duty Unit mainly works on regulating the traffic flow in congested junctions all around the city centres and outskirts across the country. As the traffic flow tends to be heavy regularly, the need for traffic police to regulate traffic flow is important (Muhammad et al., 2012). The details of the traffic police tasks in the Point Duty Unit and the flow of traffic are shown in Table 1. This study concentrates on traffic police in Kuala Lumpur (KL) and Johor Bahru (JB) as both states have one of the busiest city centres in Malaysia with a large population (Mohamad Jamil et al., 2018).

Table 1. Job description of traffic police in Point Duty Unit.Coincide, the average concentrations of SO2, O3, NO2 and CO recorded from 2009 to 2017 were below the revised MAAQG standard of 2020 (Figs. 3–6). As can be seen, the highest concentrations of SO2 were recorded in 2017 for both states. SO2 is usually the product of industrial activities and motor vehicles predominantly from diesel-engine trucks and buses (Pereira et al., 2007; Azmi et al., 2010). The peak could relate to an increase in the release of SO2 by existing or newly developed power stations due to increasing demands of energy supply in the country (Salahudin et al., 2013; Energy Commission Malaysia, 2019). Meanwhile, an observation of O3, NO2 and CO, their trends are almost similar annually and were below the MAAQG standard of 2020. These findings are also in similar with the previous work by Norela et al. (2004, 2010).

Due to the heavy traffic load, the traffic police personnel are often exposed to outdoor air pollutants which affect their respiratory health. The health impacts of these air pollutants are, namely, Chronic Obstructive Pulmonary Disorder (COPD), wheezing, lung cancer, and heart disease (Kelly and Fussel, 2015). A study by Azhari et al. (2018) stated that the exposure to trace gases in the atmosphere might lead to acute and chronic effects on respiratory and even cardiovascular hospitalisation.

Despite all the studies on the air quality and its impact, the previous works have not addressed the current situation experienced by the Malaysian Traffic Police. This study was intended to discuss the critical situation in the working area (KL and JB) of Malaysian Traffic Police in Point Duty Unit.


The states of KL and Johor are chosen as the study areas since these states have among the busiest city centres in Malaysia. The city centres are KL and JB respectively as shown in Fig. 1 according to their territory. A wide range of air quality data is also available for these two states. The primary body responsible for collecting, analysing, and presenting the air quality data is the Department of Environment (DOE), Malaysia. The air quality data in Malaysia is managed by a private entity (Alam Sekitar Sdn Bhd (ASMA)) who has been contracted by the DOE. The air quality data are monitored daily on a 24-hour basis from an air quality monitoring station. As postulated by the World Health Organization (WHO), the monitored air pollutants are particulate matter with a size of less than 10 microns in diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ground-level ozone (O3) (DOE, 1997). A nine-year database from 2009 to 2017 was sourced from the DOE and further analysed for trends of the outdoor air pollutants. The transportation data (number of vehicles by road) from 2009 to 2017 was obtained from the Malaysian Road Transport Department and validated by Department of Statistics Malaysia (2017). All the statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) version 22. For all the statistical analyses, the p-value of < 0.05 as the significance level was used. The research covered the data collected from 2009 to 2017. This large range was used to ensure that all possible research done in this field was covered.

Fig. 1. Study area
Fig. 1. 
Study area.

Fig. 3. Average SO2 concentrations (2009–2017).
Fig. 3
Average SO2 concentrations (2009–2017).

Fig. 4. Average O3 concentrations (2009–2017).
Fig. 4
Average O3 concentrations (2009–2017).

Fig. 5. Average NO2 concentrations (2009–2017).
Fig. 5.
 Average NO2 concentrations (2009–2017).

Fig. 6. Average CO concentrations (2009–2017).
Fig. 6.
 Average CO concentrations (2009–2017).


Air Quality Data in KL and Johor

Fig. 2 illustrates the trends of PM10 (24-hour average time) in KL and Johor from 2009 to 2017. The data was compared with the Malaysian Ambient Air Quality Guideline (MAAQG) standard of 2020, as shown in Table 2. Findings show that average PM10 concentration was above the MAAQG standard every year from 2009 to 2017. The release of PM10 is primarily by the industrial sector (Salahudin et al., 2013) and this explains the high concentration of PM10 in both states as both KL and Johor are central to many industrial and business operations (Azmi et al., 2010). Meanwhile, the highest average concentration of PM10 recorded was in 2015 for both states. This finding is believed to occur as a result of 2015 Haze episodes in Malaysia, deemed to be the worst after 1997 Haze due to prolonged haze lasting over two months (DOE, 2015).

Fig. 2. Average PM10 concentrations (2009–2017).
Fig. 2.
 Average PM10 concentrations (2009–2017).

Table 2. New Malaysian Ambient Air Quality Guideline (MAAQG) standard (Source: DOE, 1997).

O3 is a secondary gas made up of nitrogen oxides (NOx) and volatile organic compound (VOC) by photochemical responses involving the sunlight and heat from its precursor pollutants (Anderson et al., 2010; Chelani, 2013). The combination of high temperature and pressure of fuel oxidises the nitrogen in the gas to generate NO2 with enough oxygen (Anderson et al., 2010). Apart from that, industrial processes also produce NO2 as a by-product (Ling et al., 2014). NO2 is also emitted from open burning, domestic fuel sources, and long-range air pollutants from transportation sources (Rajab et al., 2011). CO is a colourless, odourless, and toxic air pollutant, which is produced by the incomplete combustion of carbon. The largest contributors of CO in the atmosphere are vehicular gas emissions (Transportation Research Board and National Research Council, 2002). However, these major air pollutants were also affected by the surface of meteorological conditions which are unaccounted for in this study. Nonetheless, the current work can ascertain the trends of air pollutants in both KL and Johor to understand the impact towards Malaysian Traffic Police in these areas.

Total Number of Vehicles on the Road

Due to the rapid industrialisation, it can be anticipated that the number of vehicles on the road to increase annually and indirectly play a major role in the gas emissions from traffic (Chen et al., 2019). This fact is supported by the latest data from the Road Transport Department of Malaysia from 2010 to 2014 (Department of Statistics Malaysia, 2015) which shows that the total number of vehicles in each state is led by KL (4.6 million in 2014) and Johor (2.3 million in 2014) with the largest number of vehicles on the road (Fig. 7). Specifically, the total number of vehicles in KL and Johor from 2009 to 2017 is shown in Fig. 8 (Road Transport Department, Malaysia, 2017). The increasing trend of the number of vehicles can be seen growing each year with the latest number in 2017 exceeding 6.4 million vehicles in KL and 3.6 million in Johor. This finding is in agreement with a similar finding reported by other researchers. Previous studies (Abdullah et al., 2012; Salahudin et al., 2013) showed that high levels of air pollutants are probably associated with motor vehicle emissions.

Fig. 7. Number of Vehicles on Road by state (2010–2014)
Fig. 7.
 Number of Vehicles on Road by state (2010–2014). 

Fig. 8. Number of vehicles on road in KL and Johor (2009–2017).
Fig. 8.
 Number of vehicles on road in KL and Johor (2009–2017).

Correlation between All the Air Pollutants

Table 3 shows the correlation between all the air pollutants, where a significant positive correlation can be found in all the parameters with each other. In this present study, PM10 has a moderate positive correlation with CO (r = 0.347, p < 0.01) and a low positive correlation with O3 (r = 0.220, p < 0.01), NO2 (r = 0.245, p < 0.01) and SO2 (r = 0.220, p < 0.01). Additionally, CO is found to have a moderate positive correlation with SO2 (r = 0.522, p < 0.01) and a low positive correlation with O3 (r = 0.217, p < 0.01) and NO2 (r = 0.236, p < 0.01), while O3 has a moderate positive correlation with NO2 (r = 0.427, p < 0.01) and a low positive correlation with SO2 (r = 0.257, p < 0.01). NO2 is found to be in a moderate positive correlation with SO2 (r = 0.533, p < 0.01). These findings are in line with several previous studies (Mansouri et al., 2011; Rahman et al., 2015) which found all the parameters positively correlated with each other. The significant correlations revealed that the pollutants might have similar or overlapping origins (Kumar and Joseph, 2006; Lee et al., 2018). However, further work would be needed to assess this matter.

Table 3. Correlation between all the air pollutants.

Correlation between the Number of Vehicles and All the Pollutants Concentrations

Table 4 shows the correlation between the number of vehicles and the average concentrations of all the pollutants. This study reports strong positive correlations of the total number of vehicles on the road with CO (r = 0.876, p < 0.01), O3 (r = 0.847, p < 0.01), and NO2 (r = 0.868, p < 0.01). As for SO2 and PM10, the correlations are found to be not significant. Certain factors can explain the non-correlation findings between SO2 and PM10 with the number of vehicles. This fact might due to initiation of EURO-2M fuel usage that reduces the amount of SO2 released into the environment since 2009 (Abdullah et al., 2012; Mohamed Binyehmed et al., 2016). Meanwhile, PM10 level of concentration in Malaysia is conformed to the burning of biomass in neighbouring countries (Sentian et al., 2018) and is easily manipulated by other factors, along with weather and monsoon directions (Verma and Desa, 2008; Barmpadimos et al., 2011; Mohamad et al., 2015; Rahman et al., 2015). As a whole, however, more work is required to examine the key sources of each type of pollutant in detail.

Table 4. Correlation between the air pollutants and number of vehicles.

Nevertheless, the findings from present study coincide with a previous study (Zakaria et al., 2019) which suggested that the concentration of the pollutants rises with the number of traffic count on the road and originates from the source where the sampling of pollutants was made. Another study in Malaysia (Tajudin et al., 2019) also reported a positive correlation between the number of vehicles and air pollutants. As the air pollutants are mostly emitted from motor vehicles (Abdullah et al., 2012), this proves that the number of vehicles on the road affects the concentration of pollutants. From the present study, the air pollutants namely, CO, O3 and NO2, increases with the total number of vehicles on the road. Hence, by working outdoor for long hours, the traffic police personnel are directly exposed to the harmful air pollutants.

Exposure Level among Traffic Police Personnel

The traffic police personnel enforce the transportation legislation, policies, and agreements for commercial and non-commercial vehicles using Malaysian roads. Exposure to dust and outdoor pollutants without any preventive measure has possibly caused the traffic police personnel to be highly susceptible to a decrease in pulmonary functions over time (Mohamad Jamil et al., 2018). When travelling or standing along the roads with heavy traffic, significantly during the rush hours, the traffic police personnel are exposed directly to traffic-related air pollution, which could eventually lead to health complications.

A previous study by the same author among the traffic police in Kuala Lumpur were found to be exposed to a high PM2.5 concentration at a personal level which is from 12.4 µg m3 to 55.3 µg m3 in 8 working hours with the mean level at 28.7 ± 11.1 µg m3 (Mohamad Jamil, 2016). Compared to the Malaysian Ambient Air Quality Guideline (MAAQG), the mean of PM2.5 reported does not exceed the 24-hour value of 35 µg m3 (DOE, 2015). Muhammad et al. (2012) recorded a relatively lower mean value of PM2.5 at 22.33 ± 8.54 µg m3 in a study among traffic police in Kuala Lumpur back in 2012. A current study by Fandi et al. (2020) reported that extended exposure to benzene and ethylbenzene increases the risk of adverse health effects among traffic police.

As shown in Table 5, there are a few studies that have reported on the exposure to air pollutants among Malaysian traffic police in their working environment. From this, it is clear that traffic police are working in an unfavourable situation for their health. However, these police officers have no other options as they need to fulfil their duties in order to preserves the public safety. Hence, all the key stakeholders must take immediate action for this matter.

Table 5. Studies on exposure to air pollutants among traffic police.


This work was devoted to ascertaining the air quality in the working area (KL and Johor) among Malaysian Traffic Police at their Point Duty and recognising the impacts it carries. This work also determines the total number of vehicles on the road and their relationship with air pollutants. This study revealed that the average concentrations of PM10 were above the MAAQG revised standard of 2020, whereas SO2, NO2, O3 and CO recorded below the standard. The increasing trends in the number of vehicles can be seen every year from 2009 to 2017 in both KL and Johor. All the pollutants are found to be positively correlated with each other. The average concentrations of CO, NO2, and O3 increased with the total number of vehicles.

As a consequence, the outdoor air quality is decreased and directly affects outdoor workers, particularly traffic police at their point of duty. Based on the results from this study, it would be timely and prudent for the bodies and management of the Royal Malaysian Police to begin strategising and formulating an effective plan to monitor the exposure of their officers to the harmful pollutants in the outdoor air. For future work, an efficient individual monitoring system for exposure to air pollution may be a better resolution in order to control and manage the adverse air exposure during work. The data from this present study will facilitate its usefulness to the related authorities, management, policymakers, and researchers in the years ahead.


The authors are thankful to the Royal Malaysian Police (RMP) for their support and guidance in preparing this article. Appreciation is also due to the Department of Environment, Malaysia, for the provision of the air quality database. This study is supported by the Putra Graduate Initiative of Universiti Putra Malaysia (IPS UPM), Vote No: 9640200, the Ministry of Education Malaysia (MOE) Fundamental Research Grant Scheme (FRGS), Vote No: 5524770 and the Graduate Research Fellowship (GRF) of Universiti Putra Malaysia (UPM).


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