The sampling sites, including roadsides and residential areas, were set up to collect ambient air and determine the volatile organic species it contained. For the roadside air, the average VOCs (volatile organic compounds) abundant at rush hour periods was two times that at non-rush hour periods. In the residential area, the VOC concentrationswere106 and 129 ppb during rush hour periods. The VOC concentration ratios of roadside and residential areas were in the range of 1.08–1.75 and the traffic emissions were related to the VOCs abundant in air. The highest VOC concentration was 168 ppb at midnight at residential sites and the VOC abundance could be two times that of roadside sites. This level of concentration could be attributed to the application of solvents and to human activity in a nearby motorcycle/vehicle maintenance plant, laundry rooms, etc. High abundant species were similar in both the roadside and residential air samples. These highly abundant species included toluene, acetone, acetonitrile, m,p-xylene and n-pentane, all of which can be emitted from traffic exhaust. Benzene, acrolein, formaldehyde, vinyl chloride and 1,3-butadiene were the main species with health impacts collected at both sites. In the micro-scale environment, the residential ambient air was affected by traffic flow from morning to night. In the midnight period, some local activities (a motorcycle/vehicle maintenance shop and laundry shops) affected the concentrations of certain VOCs (acetonitrile, toluene, hexane, 2-methylpentane, methyl cyclopentane and 3-methylpentane). The traffic and motor vehicles’ effects were determined, which could be useful for air quality management and strategy development in an urban area.
Air toxics, also well-known as hazardous air pollutants (HAPs), have significant health effects on human health and are of great concern. This paper studied a number of hazardous air pollutants in an industrial and metropolitan complex area in order to determine their ambient abundance and potential health impacts. The target pollutants in this study are benzene, formaldehyde, 1,3-butadiene, arsenic, 2,3,7,8-TCDD, and diesel particulate matter (DPM). A cancer risk assessment was conducted to determine the health effects of exposure to the six HAPs by using the AERMOD model. Results indicated that the emission of benzene, formaldehyde, 1,3-butadiene, arsenic and DPM was 184.5; 227.3; 68.0; 238, and 316 ton year-1 , respectively, and the emission of 2,3,7,8-TCDD was 4,994 mg-TEQ year-1. Benzene (86%), formaldehyde (69%), and 1,3-butadiene (77%) were mainly emitted from on-road mobile sources. Arsenic (70%) and 2,3,7,8-TCDD (about 100%) were mainly emitted from stationary sources and DPM was emitted from diesel engines, port operations and ocean-going vessels. Spatial air toxic distribution indicated that the highest concentration of DMP, benzene, formaldehyde, and 1.3-butadiene occurred on the highway and in the downtown district due to their high traffic volume. DPM occupied more than 80% of total cancer risk in the region, followed by 1,3-butadiene, benzene, formaldehyde, arsenic, and 2,3,7,8-TCDD. In the industrial and residential complex area, about 99% of the cancer risk stemmed from on-road vehicles and port operations due to hazardous air pollutant emissions, especially DPM. The control scenario was made huge efforts to reduce the emission, however the results indicated only reduced the overall cancer risk assessment by 10%-15%. Policy makers have to think carefully about whether implementing the kind of emissions regulations simulated in this control scenario will need to be enhanced with additional measures to further reduce the risk of air pollution for human health.
This study assesses the impact of a decrease in air quality and the risk of hospital admissions to a public hospital for chronic respiratory diseases for residents of Petaling Jaya, a city in the Greater Kuala Lumpur area in Malaysia. Data on hospital admissions for asthma, bronchitis, emphysema and other chronic obstructive pulmonary disease, weather conditions and the Malaysian Air Pollution Index, a composite indicator of air quality, were collated. An unconstrained distributed lag model to obtain risk of hospitalization for a 10 μg/m3 increase in the API. The lag cumulative effect for a 10 μg/m3 increase in the API was calculated to test for harvesting in the short term. Findings indicate that after an initial decrease in admissions (days 3 and 4), admissions increased again at day 7 and 8 and this relationship was significant. We therefore conclude that a 10 μg/m3 increase has a greater effect on admissions for respiratory health in the short term than a harvesting effect alone would suggest. These results suggest that while air quality is improving in the Greater Kuala Lumpur area, no level of air pollution can be deemed safe.
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