Development of a Cost Management Method for Road Snow Removal
in Cold, Snowy Regions
Shigeyuki NAKAMAE
Manager for Budget
Office of Expressway Planning,
Road Bureau, City of Yokohama
1-1 Minato-cho, Naka-ku, Yokohama
231-0017 Japan
Fax: +81-45-662-3945
E-mail: kohama.lg.jp Fumihiro HARA, Dr. Eng.
Director
Hokkaido Development Engineering Center S1-E2-11 Chuo-ku, Sapporo
060-0051 Japan
FAX: +81-11-271-5366
E-mail: jp
Shin-ei TAKANO, Dr. Eng.
Associate Professor
Graduate School of Engineering, Hokkaido University,
N13-W8 Kita-ku, Sapporo
060-8628 Japan
FAX: +81-11-706-6205
E-mail: shey@eng.hokudai.ac.jp Takahiro OKAWADO
Senior Chief Rearcher
Hokkaido Development Engineering Center S1-E2-11 Chuo-ku, Sapporo
060-0051 Japan
FAX: +81-11-271-5366
E-mail: jp
Junichi OSHIMA
高中英语自我介绍Chief Rearcher
Snow Rearch Center
1-3-17 Nihombashihoridome-cho,Chuo-ku, Tokyo, 103-0012 Japan
FAX: +81-3-6740-2942
E-mail: jp
Abstract :The reduction of snow removal expenditures is a pressing need for governments in Japan. Reducing snow removal expenditures at the national government level requires the following: 1) analysis of the cost structure, 2) development of a method for comparing costs among regions, and 3) development of cost reduction standards.
拥抱和接吻
冰心作品集We studied methods for objectively determining the cost effectiveness of snow removal, toward inter-regional comparison that has been regarded as difficult. To this end, we developed a model us a linear regression line of "unit cost of snow removal" (UCSR) that is bad on the relationship between snow removal costs and cumulative snowfall. This study prents how the model has been developed and discuss its applicability by using actual snow removal records. We also examine applicability of the model when the data from which the model is derived include tho for an extremely snowy year and an unusually less snowy year.
Key Words: snow removal, reduction of expenditures, budget, UCSR, cost reduction standards 1.INTRODUCTION
Many of Japan’s large cities are in snowy regions, and snow removal plays an important role
in curing smooth road traffic in winter (FIGURE 1). Studies have addresd various aspects of roa
d snow removal. As the first study in Japan on the economic benefit of road snow removal, Igarashi et al . measured that benefit. They further suggested a method for deploying snow removal machinery such as to minimize the “total snow removal cost.” Sakai et al . calculated the benefit of snow removal by dividing the mitigation of economic loss achieved by snow removal by the snow removal cost.
Figure 1 Snowfall of major cities in Japan and overas
There are recent studies that focus on beneficiaries’ awareness for the rvice level of snow removal to find a solution for cost reduction. From this viewpoint, issues including the demand for snow remo
val, residents’ willingness to pay and residents’ satisfaction levels for snow removal have been discusd.
Most of the studies on snow removal addresd economic benefits, or ud questionnaire surveys to address public involvement or customer satisfaction. Very few in-depth studies have addresd the cost structure of snow removal by the Japane government.
As for the cost reduction efforts for infrastructure management including snow removal in the U.S.A. and other countries, Baroga, E.V . propod to measure performance-bad rvice levels to u it for budget and resource allocations; and Lindy, al . focud work conditions including geography and climate that are different by work site to realize efficient resource allocation for snow removal. Other than tho for snow removal, efforts including the bridge management system have been made to optimize budget allocation for infrastructure management. However, there em to be few studies on a model that enables efficient snow removal budget and resource allocations on the basis of cost structure analys as well as of inter-regional comparisons of the time-ries data of snow removal costs.
To reduce snow removal cost at the national level, it is necessary to 1) analyze the structure of snow
removal cost, 2) develop a method for inter-regional comparison of such cost, and 3) t standards for cost reduction. Inter-regional comparison of snow removal cost has been regarded as very complicated, becau the cost varies with snowfall amount, air temperature, Japan a Pacific ocean ＳａｐｐｏｒｏＴｏｋｙｏＮａｇｏｙａＯｓａｋａＫｙｏｔｏCold, snowy region Cold region ＮｉｉｇａｔａＡｏｍｏｒｉHokkaido Tohoku Region
Hokuriku Region Kanto Region Chubu Region Kinki Region
Chugoku Region
snow texture and other natural phenomena; with the degree of development (e.g., urbanized vs. rural); and with the demand for snow control, including how accustomed the road urs are to snowfall. This paper reports on the development of an objective evaluation method to estimate snow removal cost by clarifying the relationship between snow removal cost and cumulative snowfall, both of which are relatively easy to obtain, and on how inter-regional comparison of snow removal costs is possible by using the developed estimation method. The applicability of the model is also verified by comparing the snow removal costs estimated by the model with the actual snow removal costs expended. Further, the applicability of the model when the snow removal data from which the model is derived include tho for an extremely snowy year and an unusually less snowy year is examined.
The winter of 2005-2006 (FY 2005) was the first in 43 years with extremely heavy snowfall in Japan, and the Japan Meteorological Agency designated it “the Heavy Snowfall of 2006” (FY2005). Prefectural and municipal snow removal budgets were exhausted, and the Ministry of Land, Infrastructure and Transport (MLIT) responded to local governments’ requests by increasing snow removal subsidies. On that occasion, MLIT was asked to objectively estimate snow removal costs by using data such as snowfall and length of road designated for snow removal. However, no method for such estimation had been established.
Then, MLIT has adopted the method, a unit cost of snow removal (UCSR) line model (hereinafter: UCSR-line model) introduced in this study for allocating public snow removal budget since FY 2005.
顾虑的近义词
2. BUDGETARY SYSTEM FOR SNOW REMOV AL IN JAPAN
Out of Japan’s total road length of 1.2 mil. km (744 thou. miles), municipal roads account for about 84%. The length of national roads under the direct control of the national government accounts for a mere 1.9% of the total. The length of roads in the cold, snowy areas that account for about 60% of Japan’s land area is about 41.6 thou. km (25.79 thou. miles). The national government fully finances snow removal for national highways, including expressways, and partially subsidizes snow removal f
or national highways under the control of prefectures and prefectural roads in areas designated as snowy and cold by The Special Measures Law for Ensuring Road Traffic in Snowy and Cold Areas (The SCA Law) (Figure 2).
The national government covers snow removal costs for nationally managed national highways. The national government subsidizes snow removal costs for prefecturally managed national highways and prefectural roads in areas designated as snowy and cold by The SCA Law. The law states that the national government shall subsidize prefectures for two thirds of the cost of snow removal, with the prefecture covering the remaining third. At prent, the national government’s subsidy for roads in areas that are designated as snowy and cold by the law amounts to about 70 billion yen ($583 million ($1/ ¥120), FY 2007). National revenues for this subsidy include tho from the national gas tax, the automobile tonnage tax and the automobile acquisition tax. Tho revenues, who disburment is limited to road-related projects, amount to about 5.6 trillion yen ($47 billion, FY 2007).
Each prefecture’s snow removal costs are financed from the prefectural general account and the prefectural special account. The revenue sources for the prefectural special account includes the light oil wholesale tax, who disburment is limited to road-related projects.
7,389km
22,000km
32,000km
128,700km
992,700km蔓越莓片
东坡书院Figure 2 Roads in Japan and their budgets
3.UCSR-LINE MODEL DERIVED BY THE RELATIONSHIP BETWEEN CUMULATIVE SNOWFALL AND SNOW REMOV AL COST
How the UCSR-line model has been developed is introduced here.
Generally, the snow removal cost for roads (hereinafter: snow removal cost) consists of the costs for 1) roadway snow removal, 2) sidewalk snow removal, 3) anti-freezing agent application and 4) snow hauling and miscellaneous.
Various explanatory variables can be considered for the costs. The variables include road length, road width, snowfall amount, road surface condition, snow removal frequency and amount of hauled snow.
However, obtaining all the data is quite difficult; conquently, clarifying the relationship between all the variables and the snow removal costs is impractical.
Thus, we tried to calculate snow removal cost by using data such as cumulative snowfall and length of road designated for snow removal, which are relatively easy to obtain.
按图索骥Two kinds of data reprent the amount of snowfall: snowfall per snowfall event, and annual snowfall. Snow removal deployment is launched in respon to each day’s snowfall. When we examine the cost for snow removal, it is appropriate to u cumulative snowfall.
The structure of snow removal cost is complicated, as shown above. The cost varies depending on the snowfall, as expresd in the following equation.
p=f(x)(1)
Where, p is snow removal cost and x is cumulative snowfall.
This function is expected to plot as an upward-sloping line, becau snow removal cost increas with increas in cumulative snowfall. The total snow removal cost, however,
includes costs that are independent of snowfall amount, including the cost for anti-freezing agent application and fixed operating costs. The function has terms that change and terms that do not change (constant terms) with changes in cumulative snowfall.
If we assume that a linear regression model can describe the relationship between snow removal cost and cumulative snowfall, then the snow removal cost can be expresd by Equation 2.
p=f(x)=ax+b (2)
Where p is snow removal cost, x is cumulative snowfall, a is a coefficient expressing snow removal cost per centimeter of cumulative snowfall and b is a coefficient of snow removal cost that does not depend on the cumulative snowfall of the area where the snow removal is conducted. The snow removal cost expresd in the above equation includes the cost for hauling snow, which increas in stepwi increments with increas in cumulative snowfall (FIGURE 3(2)).
The snow removal cost includes a cost that changes in stepwi increments, and it is thought that the line that express the relationship between snow removal cost and cumulative snowfall is not a simple line. However, when the cost for hauling snow does not dominate the total snow removal cost, it is considered that a linear approximation can describe the relationship between snow remova
l cost and cumulative snowfall (FIGURE 3(3)).
Figure 3 Costs for snow removal and snow hauling vs. cumulative snowfall
Next, we examine the relationship between the UCSR and cumulative snowfall.
The UCSR, which is obtained by dividing the annual snow removal cost (p, (million yen)) by the length of road with snow removal (L (km)) and cumulative snowfall (x (cm)), is expresd as follows.
y=p/L/x (3)
The length of road with snow removal is the length of routes that are designated as tho who sno
w removal costs are shared by the national and prefectural governments under The SCA Law. The road length can be treated as a constant becau it does not change with changes in cumulative snowfall (x).
一想天开From Equations (2) and (3), we obtain:
y=f(x)/L/x
=(ax+b)/L/x =(a+b/x)/L (4)
