Kathmandu Valley (approximately 570 km 2 ) is the largest city and the capital of Nepal. In 1991, it had a population of 1.1 million. The population rose to nearly 2.5 million in 2011, with a population density of 4,386/km 2 . This is about 1.6 times the population density of an average Canadian urbanized area, which is 2,656/km 2 . The transportation sector is the largest source of air pollution in the valley. In 1990, there were 40,133 vehicles in the valley. This number reached 330,336 in 2011, an increase of 8-fold within 20 years. Recent data showed that there are 15,008 diesel and 315,328 gasoline vehicles. This paper determines the amount of carbon dioxide (CO 2 ) emitted by these vehicles. Vehicle data were collected from the Department of Motor Vehicles, Kathmandu, Nepal. The emission rate of each type of vehicle was collected from the vehicle manufacturers. The study showed that Kathmandu Valley had highest level of pollution in Nepal. The CO 2 emission from each type of vehicle also was calculated. Recommendations regarding improving the air quality of the valley are presented.
In 2012, 775 fatalities were recorded, and many more were injured at construction sites in the United States. Of these, 415 fatalities (54%) were due to fall, slips, and trips as well as being struck by falling objects. In order to decrease fatalities at construction sites to these types of events, the Occupational Safety and Health Administration (OSHA) provides Fall Prevention and OSHA-10 trainings to construction workers. Moreover, safety personnel monitor whether the workers use personal protective equipment (PPE) properly. Data shows that construction fatalities have decreased by 2% annually since 1994; however, the owners still are not satisfied with this result. Various studies have shown that fall is the biggest contributor for construction fatalities. One study showed that half of the fall fatalities were because the workers either had not used PPEs or had not used them properly. In addition, studies showed that, with proper use of hard hats, the fatalities due to fall, slips, trips, and being struck by falling objects could be reduced. This study developed and tested a hard-hat detection tool that uses image-processing techniques to identify whether workers are wearing hard hats. The tool dispatches warning messages if the workers do not use hard hats.
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