[Title of Invention] METHOD FOR ESTIMATING AMOUNT OF DUSTFALL, DEVICE FOR ESTIMATING AMOUNT OF DUSTFALL, AND PROGRAM FOR ESTIMATING AMOUNT OF DUSTFALL [Technical Field] [0001] The present invention relates to a dust fall estimating method, a dust fall estimating apparatus, and a computer program there for, which are based on the calculation result of dust advection-diffusion behavior in the air. Priority is claimed on Japanese Patent Application No. 2008-172501 filed on July 1,2008, the content of which is incorporated herein by reference. [Background Art] [0002] It is very important in estimating the influence of dust fall on local residents to calculate the dispersal behavior of dust particles emitted from a dust source (a generation source of powder dust and smoke dust) such as a plant smokestack due to wind and to estimate the amount of dust fall. [0003] Non-Patent Document 1 discloses the following method. It is assumed that the amount of dust fall depends on a one-dimensional distance between a dust source and a falling point. Expression 4 is calculated using a distance between the dust source and the falling point, a dust generation rate, a dust particle size distribution, a dust density, an effective dust generation height, and a wind direction and speed frequency distribution as input values. The amount of dust fall is estimated by multiplying the calculation result of Expression 4 by the wind direction and speed frequency distribution. Device and method of estimating an amount of dust fall based on an experimental formula or an empirical formula are proposed (see Patent Document 1). [0004] [Expression 4] [0005] Here, Q represents a dust generation strength (dust generation rate), He represents an effective dust generation height, w represents a terminal falling speed determined depending on a particle diameter, x represents a downwind distance between the dust source and the falling point, u represents a wind speed, T represents a gamma function, and C(x) represents an amount of dust fall. On the other hand, when it can be considered that a dispersed material has the same density as the density of a carrier gas, a three-dimensional Gaussian plume model is proposed. In this case, a dispersed material concentration at a three-dimensional position (x, y, z) can be calculated using Expression 5. [0006] [Expression 5] [0007] Here, x represents an arbitrary position in a coordinate axis (x axis) in the downwind direction from a dust source, y represents an arbitrary position on a coordinate axis (y axis) perpendicularly intersecting the x axis in a horizontal plane, z represents an arbitrary position in a coordinate axis (z axis) perpendicular to the horizontal plane formed by the x axis and the y axis, c(x, y, z) represents a dust concentration at a coordinate position (x, y, z), u represents a wind speed, Q represents a dust generation strength, σy and σz represent spreads of visible smoke in the y axis direction and the z axis direction, respectively, He represents an effective dust generation height, and y0 represents a coordinate position in the y axis where the dust source exists. The coordinate position in the x axis where the dust source exists is set to 0. [Background Documents] [Patent Documents] [0008] Patent Document 1: Japanese Unexamined Patent Application, First Publication No.2005-128691 [Non-Patent Documents] [0009] Non-Patent Document 1: C. H. Bosanquet et al., Proc Inst Mech Engrs, Vol. 162, p355(1950) Non-Patent Document 2: Meteorology of Wind, written by Kiyohide TAKEUCHI, published by the University of Tokyo Non-Patent Document 3: Manual of Chemical Engineering, Revised Edition 4 Non-Patent Document 4: Briggs G A. Plume rise, U.S. AEC (1969) [Summary of Invention] [Problems to be Solved by the Invention] [0010] However, in the estimating method disclosed in Non-Patent Document 1, it is assumed that the amount of dust fall depends on the one-dimensional distance between the dust source and the falling point. Accordingly, as shown in Fig. 1, when there exist dust source 1 and dust source 2 having the same distance between the dust source and the falling point, same dust generation strength, same dust particle size distribution, same dust density, and same effective dust generation height with respect to one falling point, it is assumed that the degree of contribution of dust source 1 and dust source 2 are equal to each other. However, dust particles actually turbulently diffuse in three-dimensional directions. Accordingly, there is a problem in that it is not possible to describe the fact that the degree of contribution of dust source 2 with the smaller distance from the falling point is greater than that of dust source 1. Since Expression 4 is an experimental formula published in 1950 by Bosanquet, there is a problem in that the precision of the formula depends on the experimental environment at the time of acquiring the experimental formula and thus its not suitably applicable to general problems. On the other hand, in the estimating method disclosed in Non-Patent Document 2, it is assumed that a dispersed material has the same density as a carrier gas. Since this assumption is not established for dust particles, it is not possible to estimate the behavior of dust particles with high precision by the use of the estimating method. [0011] The invention is made in consideration of the above-mentioned problems. A goal of the invention is to provide a method of estimating dust behavior precisely and closely following the theoretical principles of actual phenomena, compared with the known experimental formula. [Means for Solving the Problem] [0012] To accomplish the above-mentioned goal, aspects of the invention employ the following means. (1) According to an aspect of the invention, there is provided a dust fall estimating method comprising: a wind direction and speed information inputting step of acquiring time-series measured values of wind direction and speed for a predetermined period of time, dividing ranges of wind direction and speed into m and n sub categories, respectively, based on the time-series measured values, setting a representative wind speed for every sub category of the wind speed, preparing an min wind direction and speed frequency distribution by calculating frequencies of the time-series measured values included in the respective sub categories for the predetermined period of time, and inputting the representative wind speeds and the wind direction and speed frequency distribution as wind direction and speed information; a dust source information inputting step of inputting information about a dust source; a dust concentration calculating step of calculating a dust concentration c at a coordinate point using the wind direction and speed information and the dust source information; and a dust fall calculating step of calculating an amount of a dust fall at a falling point based on the dust concentration c. (2) In the dustfall estimating method according to (1), the dust concentration calculating step may include calculating the dust concentration c additionally using a reflection rate β of a dust on a earth surface. (3) In the dustfall estimating method according to (2), the dust source information inputting step may include inputting a coordinate of the dust source in a three-dimensional space, a dust generation strength Q of the dust source, a particle diameter of a dust, a density of the dust, and an effective dust generation height He from the dust source. (4) In the dustfall estimating method according to (3), the dust concentration calculating step may include calculating the dust concentration c(x, y, z) at a point (x, y, z) in a three-dimensional coordinate system using Expression 1,+ [Expression 1] where u represents a wind speed, Ky and Kz represent turbulent diffusion coefficients in y axis direction and z axis direction, respectively, w represents a terminal falling speed of dust particles, an x coordinate of the dust source is 0, and a y coordinate of the dust source is yo. (5) In the dustfall estimating method according to (2), the dustfall calculating step may include calculating the amount of the dustfall using Expression 2 or 3, [Expression 2] C(x,y)=wc(x,y,z = 0) (2) [Expression 3] C(x,y)=(l-β)-K1-dc(x,y,z = 0) (3) where c(x, y, z) represents the dust concentration at a point (x, y, z) in the three-dimensional coordinate system, c represents an amount of the dustfall, and Kz represents the turbulent diffusion coefficient in the z axis direction. (6) According to another aspect of the invention, there is provided a dustfall estimating apparatus including: a wind direction and speed information input unit acquiring time-series measured values of wind direction and speed for a predetermined period of time, dividing ranges of wind direction and speed into m and n sub categories, respectively, based on the time-series measured values, setting a representative wind speed for every sub category of the wind speed, preparing an mxn wind direction and speed frequency distribution by calculating frequencies of the time-series measured values included in the respective sub categories for the predetermined period of time, and inputting the representative wind speeds and the wind direction and speed frequency distribution as wind direction and speed information; a dust source information input unit inputting information about a dust source; a dust concentration calculating unit calculating a dust concentration c at a coordinate point using the wind direction and speed information and the dust source information; and a dustfall calculating unit calculating an amount of a dustfall at a falling point based on the dust concentration c. (7) According to another aspect of the invention, there is provided a dustfall estimating program including: a wind direction and speed information inputting step of acquiring time-series measured values of wind direction and speed for a predetermined period of time, dividing a range of wind direction and speed into m and n sub categories, respectively, based on the time-series measured values, setting a representative wind speed for every sub category of the wind speed, preparing an mxn wind direction and speed frequency distribution by calculating frequencies of the time-series measured values included in the respective sub categories for the predetermined period of time, and inputting the representative wind speeds and the wind direction and speed frequency distribution as wind direction and speed information; a dust source information inputting step of inputting information about a dust source; a dust concentration calculating step of calculating a dust concentration c at a coordinate point using the wind direction and speed information and the dust source information; and a dustfall calculating step of calculating an amount of a dustfall at a falling point based on the dust concentration c. (8) According to another aspect of the invention, there is provided a computer-readable recording medium having recorded thereon the dustfall estimating program according to (7). [Advantageous Effects of Invention] [0013] According to the configuration of (1), it is possible to estimate dust behavior precisely and closely following the theoretical principles of actual phenomena, compared with the known experimental formula. Accordingly, it is possible to quantitatively estimate how dust generated from a dust source has an influence on an urban area as dust fall. In addition, it is possible to acquire a facility design barometer for estimating the optimal scale of dust controlling facilities such as dust collectors. Particularly, even when the wind direction and speed in an area are not uniform, it is possible to accurately estimate dust behavior depending on the measured wind direction and speed. Since the wind direction and speed are divided into a specific number of sub categories for calculation, it is possible to reduce the amount of calculation. Therefore, it is possible to carry out the calculation on complex systems and to acquire significant estimation results. According to the configuration of (2), even when the effects of reflection and deposition of the dust on the earth's surface cannot be neglected depending on conditions such as the particle diameter of the dust, it is possible to accurately estimate the dust behavior. According to the configuration of (3), when the detailed characteristics of the dust source can be measured, it is possible to accurately estimate the dust behavior based on the characteristics. According to the configuration of (4), it is possible to accurately estimate the dust behavior based on the characteristics such as the wind speed, the turbulent diffusion coefficients, the terminal falling speed of the dust particles which are measured using a three-dimensional turbulent diffusion model. According to the configuration of (5), when the deposition resulting from the force of gravity cannot be neglected given a large particle diameter of dust or a high dust density, it is possible to accurately estimate the dust behavior. [Brief Description of Drawings] [0014] FIG. 1 is a diagram illustrating positional relations between a falling point and two dust sources. FIG. 2 is a diagram illustrating dust dispersal behavior from a dust source. FIG. 3 is a first flowchart illustrating calculations of a dust concentration and an amount of dustfall. FIG. 4 is a second flowchart illustrating the calculations of a dust concentration and an amount of dustfall. FIG 5 A is a diagram illustrating a diffusion of smoke by Pasquill-Gifford. FIG 5B is a diagram illustrating a diffusion of smoke by Pasquill-Gifford. FIG 6 is a diagram illustrating a concentration distribution of dispersed dust calculated using a method according to an embodiment of the invention, FIG. 7 is a diagram illustrating a concentration distribution of dispersed dust calculated using a Gaussian plume model. FIG. 8 is a diagram illustrating a dustfall distribution calculated using a method according to the embodiment of the invention. FIG. 9 is a diagram illustrating a dustfall concentration distribution calculated using Bosanquet's formula described in Non-Patent Document 1. FIG. 10 is a diagram illustrating values of the amount of dustfall measured by a deposit gauge. FIG. 11 is a diagram schematically illustrating the configuration of an apparatus according to the embodiment of the invention, FIG. 12 is a diagram illustrating the hardware configuration of a computer system serving as a dust concentration and dustfall estimating apparatus. [Embodiments of the Invention] [0015] In the invention, the dust dispersal behavior from a dust source to a falling point due to three-dimensional advection-diffusion behavior by wind is theoretically calculated based on the material balance of dust to estimate the amount of dustfall. Hereinafter, exemplary embodiments of the invention will be described with reference to the accompanying drawings. In an embodiment of the invention, as shown in Fig. 2, the dispersal of dust particles from a plant's smokestack as an example of a dust source is considered. The dust particles disperse about an x axis set to a downwind direction from an effective dust generation height He. It is assumed that the dust source is located at a position of x=0, the vertical direction is set as a z axis, and an axis intersecting the x axis in a horizontal plane is set as a y axis. [0016] The concentration of dust particles dispersing due to wind from a dust source is expressed by c(x, y, z). The material balance with respect to the concentration c(x, y, z) can be expressed as Expression 6. [0017] [Expression 6] [0018] In Expression 6, u represents the wind speed, the x axis is set as the center of the wind direction as described above, and it is assumed that the wind blows only in the x axis direction. The first term of the left side in Expression 6 represents the amount of dust particles dispersing due to the wind advection. The first term of the right side in Expression 6 represents the amount of dust particles dispersing in the y axis direction due to the turbulent diffusion. The second term of the right side in Expression 6 represents the amount of dust particles dispersing in the z axis direction due to the turbulent diffusion. The third term of the right side in Expression 6 represents the amount of dust particles deposited due to the force of gravity. Here, the amount of dust particles dispersing in the x axis direction due to the turbulent diffusion is smaller than the amount of dust particles dispersing in the x axis direction due to the wind advection and is assumed as being negligible. Ky and Kz represent the turbulent diffusion coefficients in the y axis direction and the z axis direction, respectively. [0019] Expression 7 represents a formula for setting a boundary condition of dust particles in the dust source. Q-δ(y-yo, z-He) represents that dust particles are generated with a dust generation strength Q from a position of x=0, y=yo, and z=He. 8 is a delta function. Here, the delta function is a real generalized function satisfying the condition of Expression 8. Here, the dust generation strength Q can be calculated by means such as a low volume sampler. [0020] [Expression 7] c(0,y,z)=Q.δ(y-y0,z-He) (7) [0021] [Expression 8] [0022] Expression 9 expresses a formula for setting a boundary condition of dust particles on the earth's surface. Here, β represents the reflection rate of dust particles on the earth's surface, where β=0 represents complete deposition and P=l represents complete reflection. β is a coefficient depending on the size of dust particles. In normal calculations, given that dust particles reaching and being on deposited on the earth's surface are the ones in most cases that are calculated, the approximation of β=0 does not cause any problem. When it is intended to accurately set the value of β, the amount of dustfall from a dust source such as a smokestack of which the dust generation rate, the effective dust generation height, and the dust particle diameter distribution are known is measured by means such as a deposit gauge. The value of β is roughly set so that the calculated amount of dustfall corresponds to the measured value of dustfall. [0023] [Expression 9] [0024] By solving Expression 6 based on the boundary conditions of Expression 7 and 9, Expression 1 is obtained. [0025] [Expression 1] [0026] The amount of dustfall C(x, y) at a falling point can be calculated using Expression 2 which is obtained by multiplying the terminal falling speed w of dust particles by the value, which is calculated using Expression 9, of the dust concentration c(x, y, z=0) at a planar coordinate point (x, y) on the earth's surface (z=0). [0027] [Expression 2] C(x,y)=w-c(x,y,z = 0) (2) [0028] When dustfalls in air due to the force of gravity, the force of gravity on dust is balanced with the buoyancy and thus the speed becomes constant with the lapse of time. This is referred to as "terminal falling speed", which can be calculated using Expression 10. [0029] [Expression 10] Here, ps represents the density of dust particles, pa represents the density of the atmosphere, dk represents the diameter of the dust particles corresponding to the flow type frequency k, and μ, represents a viscosity coefficient of the atmosphere. [0030] The amount of dustfall C(x, y) at the falling point can be calculated using Expression 3 in which the z derivative value of the dust concentration c(x, y, z=0) at a planar coordinate point (x, y) on the earth's surface (z=0) can be calculated using Expression 9 and Kz and (1-β) are multiplied. [0031] [Expression 3] C(x,y)=(l-0)-Kz-dc(x,y,z = O) (3) Here, Ky represents the turbulent diffusion coefficient in the z axis direction and (3 represents the reflection rate of particles on the earth surface. [0032] An example of the procedure of calculating an amount of dustfall using Expression 1 and 2 will be described below with reference to the flowcharts shown in FIGS. 3 and 4. First, a wind direction and speed information inputting step will be described. In the initial step, i.e., step S01, a wind direction and speed frequency distribution is calculated. Wind direction and speed data is divided into m wind direction categories and n wind speed categories based on the measured values of wind direction and speed for a predetermined period of time. The frequency by of data belonging to a category of wind speed i and wind direction j is calculated to form a nxm matrix. At this time, the total sum of the elements by in the matrix is adjusted to be 100%. The divisions of the wind direction data can be calculated in any of one or more orientations and can be set in consideration of orientation data available. Preferably, 16 orientations are employed and m=16 is set so as to correspond to AMeDAS data of the meteorological bureau. The divisions of the wind speed data can be calculated directly using the measured values of the wind speed. Preferably, the range between the minimum wind speed and the maximum speed for the predetermined period of time is divided into four or five categories of [light wind, weak wind, normal wind, and strong wind] or [light wind, weak wind, normal wind, strong wind, and super-strong wind] and n=4 or n=5 is set. The calculation is possible even when n is equal to or greater than 6, but the calculation is complicated in some cases. The representative wind speed is selected in each sub category of the wind speed. In selecting the representative wind speed, the wind speed having the largest frequency out of the wind speed data belonging to each sub category may be employed or the average of the wind speed data belonging to each sub category may be employed. It is preferable that an anemoscope and an anemometer are installed at a position not influenced by a surrounding obstacle such as a building. When a meteorological bureau is located in the vicinity, measured data of the meteorological bureau such as AMeDAS may be used. The period of time of measuring the wind direction and the wind speed is set to the same as the period of time of calculating the amount of dustfall. In the set period of time, the wind speed and direction sampling period is determined to determine the statistical amounts in the wind speed and direction frequency distribution. For example, when m=16 and n=4 are set and the period of time of 1 month is set, the wind speed and direction data can be picked up in a period of 1 hour. [0033] In step SO2, the initial value of the dustfall is set to zero. [0034] Next, a dust source information inputting step will be described. In step S03, dust source information is input. Specifically, the x-y coordinate (x=0, y=yo) of the dust source, the smokestack height H, the dust generation strength Q, the dust particle diameter d, the dust particle density p, the exhaust gas volume W, and an exhaust gas speed V are input. [0035] Next, a falling point information inputting step will be described. In step S04, the falling point information is input. Specifically, the coordinate (x, y) of the falling point where the amount of dustfall is estimated is input. The order of the wind direction and speed information inputting step, the dust source information inputting step, and the falling point information inputting step may not be fixed, but may be changed. [0036] Next, a dust concentration calculating step S100 shown in FIG 4 will be described. In this step, the dust concentration at the falling point is calculated using the information input in the above-mentioned steps. [0037] In step S05, the wind speed ui (representative wind speed) in each wind direction and speed frequency distributions bij is defined as a wind speed u used in the calculations in the subsequent steps. The wind speed u is used to calculate the effective dust generation height using Expression 11 and to calculate the dust concentration at the falling point using Expression 1. In step S06, when dust is emitted at a temperature higher than that of the ambient air of the smokestack of a plant or the like, the effective dust generation height He is calculated, for example, using Expression 11 based on the smokestack height H, the exhaust gas volume W, and the exhaust gas speed V input in step S03. [0038] [Expression 11] Here, H represents the smokestack height, Qe_ gas represents the exhaust gas volume, T1 represents the temperature of the atmosphere, ∆T represents the difference between the temperature of the exhaust gas and T1, g represents the gravitational acceleration, d0/dz represents the temperature gradient of the atmosphere (normally employing 0.03), w represents the terminal falling speed of particles, and u represents the wind speed. [0039] On the other hand, when the dust disperses due to wind, the situation in which dust is generated is recorded with a device such as a camera and the height where the dust has the maximum concentration is identified and determined from the darkness of a color, whereby the dust generation height is determined. The dust generation height is set as the effective dust generation height He. [0040] Regarding the dust particle diameter, a dust particle sample picked up with a low volume sampler is introduced into a particle diameter distribution measuring apparatus to measure the particle size distribution. The representative particle diameter is determined based on the measured particle size distribution by the use of the definition of the maximum frequency diameter and the like. The range of measured particle diameter may be divided into sub categories and the representative particle diameter of each sub category may be used as the dust particle diameter. In this case, the weight ratios of the dust particles existing in the sub categories of particle diameters are calculated in advance. The frequency distribution of each average particle diameter is calculated so that the total sum of weights is 100%. The total amount of dustfall is calculated by multiplying the amount of dustfall of each average particle diameter by the frequency distribution of each average particle diameter. The particle diameter distribution measuring apparatus may employ a deposition method or a light-transmitting method (for example, see Non-Patent Document 4). In step S07, the terminal falling speed w is calculated using Expression 10 based on the particle diameter d and the density p of the dust particles input in step S03. [0041] In step S08, the turbulent diffusion coefficients Ky and Kz are determined. Ky and Kz are set to values converted using Expression 12 based on the experimental values of the spreads of smoke ay and az measured by Pasquill-Gifford having carried out a tracer experiment on a plain in the USA as shown in FIGS. 5A and 5B (for example, see Non-Patent Document 4). [0042] [Expression 12] [0043] Here, signs A, B, C, D, E, and F in FIGS. 5A and 5B represent the stability of the atmosphere, where A represents a very unstable state, B represents an unstable state, C represents a slightly unstable state, D represents a medium state, E represents a stable state, and F represents a very stable state. The stability of the atmosphere is associated with the magnitudes of the turbulent diffusion coefficients Ky and Kz and the turbulent diffusion coefficients Ky and Kz decreases as the stability of the atmosphere increases in Figs. 5A and 5B. In step S09, the reflection rate β is input. [0044] In step S0 10, the dust particle concentration c(x, y, z=0) at a coordinate position (x, y) of the falling point with z=0 is calculated using Expression 1. [0045] A dustfall calculating step S200 will be described. In step S0 11, the amount of dustfall is calculated using Expression 2 based on the dust particle concentration c(x, y, z=0) calculated in step S0 10 and the terminal falling speed w of dust particles calculated in step S07. The amount of dustfall is defined as AC(x, y). [0046] In step S0 12, the calculated amount of dustfall AC(x, y) corresponding to the wind direction and speed frequency distribution bij and being calculated in step S01 1 is added to the amount of dustfall C(x, y). [0047] In step S013, when the conditions of i