PURPOSES : The objective of this study was to evaluate the effectiveness of dust removal by dust removal vehicles by the measuring dust load and PM10 concentrations on the sidewalks of block pavements. METHODS : Field experiments were conducted to determine a dust removal method suitable for the sidewalk conditions, as identified through a literature review. Data collection was followed by the evaluation of the sidewalk dust load with removal vehicles and analysis of the PM10 content within a service road. Moreover, an economic analysis was conducted based on the social costs of dust reduction. RESULTS : When cleaning a sidewalk block by spraying water, the contaminants in small gaps in the block pavement could be reduced, providing a potential solution to void clogging. The dust on the surface of the sidewalk was suspended from a paved road with a high level of traffic volume. Using sidewalk dust removal vehicles with sweeping, spraying water, and inhalation reduced the dust load and PM10 contents by more than 2 and 0.07g/m2, respectively. CONCLUSIONS : According to the economic analysis of the development of dust removal vehicles for sidewalks, the cost-benefit analysis method shows an input effect of 0.4, but if the reduction amount of fine particles such as PM2.5, further experiments are necessary to address the atmospheric fine dust concentrations resulting from cleaning sidewalk block pavements.

The present study observed temperature in order to identify factors affecting temperature by zoning and to measure the intensity of their impact on temperature. The empirical results of analyzing observed data are as follows. In order to make up for multicollinearity, a problem in multiple regression analysis, and to give more specific explanations, this study conducted factor analysis and obtained desirable data with adequacy and statistical significance. In the correlation matrix, factors decreasing temperature were planted areas, water surfaces and grasslands, and those increasing temperature were bare grounds, paved areas, and building area. According to land cover patterns, commercial areas had the highest temperature lowering effect. Through the rotated component matrix, we found that factors are grouped into those decreasing temperature, those increasing temperature, and those with low significance in increasing or decreasing temperature. In order to solve the problem of multicollinearity in multiple regression analysis, we performed factor analysis between the land use patterns and temperature and confirmed the usability of factor analysis as a new analysis method in urban heat island.

The present study investigated the causes and intensity of the urban heat island phenomenon by the seasons according to the pattern of land use in Chungju City. Highest temperature and lowest moisture areas of the urban were very similar to the distribution of commercial districts, on the other hand, lowest temperature and highest moisture areas were distributed in manufacturing districts, green zones and the Hoam Lake. If appear at intensity of the distance from the outer circumference of commercial districts, wind direction and the rise of temperature, we could observe the remarkable expansion of high temperature from commercial districts toward residential districts around of downwind in all seasons. In case the effect of the wind was not significant as well, high temperature in commercial districts appeared tendency that a little spread to 1, 2 residential districts around. But checked up the intimate relations between the amount of moving heat and wind, when out of consideration that size of area was not much compared than residential areas of downwind affected by the wind. These phenomenon was relatively obvious in summer, the other side, in spring and autumn appeared a similar tendency.