KR101813627B1 - Method for predicting annual exposure dose of radon and apparatus for reducing radon automatically using the same method - Google Patents

Method for predicting annual exposure dose of radon and apparatus for reducing radon automatically using the same method Download PDF

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KR101813627B1
KR101813627B1 KR1020160011426A KR20160011426A KR101813627B1 KR 101813627 B1 KR101813627 B1 KR 101813627B1 KR 1020160011426 A KR1020160011426 A KR 1020160011426A KR 20160011426 A KR20160011426 A KR 20160011426A KR 101813627 B1 KR101813627 B1 KR 101813627B1
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radon
concentration
annual
average concentration
average
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KR20170090728A (en
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이철민
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서경대학교 산학협력단
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/0001—Control or safety arrangements for ventilation
    • F24F11/0017—
    • F24F11/0086—
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
    • G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
    • G01T1/16—Measuring radiation intensity
    • G01T1/17—Circuit arrangements not adapted to a particular type of detector
    • G01T1/178—Circuit arrangements not adapted to a particular type of detector for measuring specific activity in the presence of other radioactive substances, e.g. natural, in the air or in liquids such as rain water
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • G06Q50/265—Personal security, identity or safety
    • F24F2011/003—

Abstract

A method for predicting the annual exposure dose of radon based on the average concentration of radon measured during a season and an apparatus for automatically reducing the radon using the method, , A mathematical predictive model that shows the relationship between the average concentration of radon measured during a period, the correction factor of a season, and the annual effective dose of radon exposed to a resident, By calculating the annual effective dose of radon, it is possible to estimate the annual exposure dose of radon and to calculate reliable risk of lung cancer occurrence as well as accurate annual exposure dose considering residency characteristics of residents.

Description

FIELD OF THE INVENTION [0001] The present invention relates to a method for predicting the annual exposure dose of radon and an apparatus for automatically reducing the radon using the method.

A method for predicting the annual exposure dose of radon based on the average concentration of radon measured during a season and an apparatus for automatically reducing the radon using the method.

Radon is one of the natural radioactive materials including uranium and radium, and it is the main carcinogen that threatens the health of the residents by causing lung cancer by daily exposure from the living environment such as indoor air. The World Health Organization (WHO) and the US Environmental Protection Agency (USEPA) recommend that radon be the main causative agent of lung cancer after smoking and should be managed in indoor air. Radon is present in outdoor air or groundwater, but most of it is occupied by indoor air (about 95%). Radon is generated from the infiltration through the gaps between the buildings and the radium contained in the building materials, Lt; / RTI >

Various methods have been developed worldwide to reduce the incidence of lung cancer due to radon exposure. In the development of these various methods, evaluation of the actual amount of radon exposed to the occupants, ie, evaluation of the indoor air radon concentration and evaluation of the effective dose by exposure to radon, are inevitable developmental steps. Short- The radon concentrations obtained through the process are applied. However, considering that the adverse health effects of radon are a chronic disease, lung cancer development, the development of health impact assessment by radon requires measurement of long term cumulative exposure to radon during the year.

It is not feasible to investigate long - term cumulative concentration of radon for a year in a residential area where people live. Therefore, we are evaluating effective doses and risk of lung cancer by exposure to radon only through short - term global survey. In a country where the four seasons change for a year, the indoor environment, like the outdoor environment, also changes according to the seasonal weather. For example, radon concentration in indoor air is detected higher than other seasons due to chimney effect in winter, and indoor air has lower radon concentration than other seasons due to frequent ventilation in summer. These changes can lead to uncertainty in evaluating the effective dose due to radon exposure and the risk of lung cancer. This means that the radon concentration varies greatly depending on the time of measurement of the radon concentration, which may cause uncertainty in evaluating the effective dose due to radon exposure and the risk of lung cancer.

The Government of the Republic of Korea recommends the use of a three-month cumulative concentration survey as a process test method for the investigation of indoor airborne concentrations in residential areas. The national survey of large-scale radon concentrations has also been continuously conducted for a particular season, winter. Although large data on the concentration of radon in many residential environments have been established through the recommendation of national measurement methods and large-scale radon concentration survey at the national level, the above-mentioned reasons are used to evaluate the radon dose and the health impact assessment It is a very poor situation.

It is possible to calculate reliable risk of lung cancer occurrence by solving the uncertainty of lung cancer risk assessment based on short-term radon concentration survey, and it is possible to calculate accurate annual exposure dose considering residents' And to provide a method for predicting the annual exposure dose of radon. It is also an object of the present invention to provide an apparatus for automatically reducing radon using the method. Further, the present invention is not limited to the above-described technical problems, and another technical problem may be derived from the following description.

According to an aspect of the present invention, there is provided a method of estimating an annual exposure dose of radon, comprising: receiving a time at which a resident resides in a residence; Receiving an average concentration of radon measured in the settlement during any one of a plurality of seasons in the area where the settlement is located; A mathematical prediction model representing a relation between the residence time, the average concentration of radon measured during the one of the seasons, the correction coefficient of the one season, and the annual effective dose of radon exposed to the resident, Substituting the inputted average radon concentration; And predicting the annual exposure dose of radon by calculating the annual effective dose of radon exposed to the resident from the mathematical prediction model in which the residence time and the radon average concentration are substituted.

Wherein estimating the annual exposure dose of the radon comprises estimating an average concentration of radon for one year by applying a correction coefficient of the one season to the average concentration of radon measured during the one season according to the mathematical prediction model, By applying the residence time to the estimate of the average concentration of radon during the year, the annual effective dose of radon exposed to the resident can be calculated. Wherein predicting the annual exposure dose of the radon comprises: subtracting a constant value of the background concentration from the average concentration of radon measured during the one season, multiplying the result of the subtraction by the correction coefficient of the one of the seasons, The average concentration of the radon during the year can be estimated by adding the constant value of the background concentration to the result of the calculation.

Wherein the step of receiving the residence time comprises receiving the residence time of the resident on average at the residence for one day and predicting the annual exposure dose of the radon to estimate the average concentration of radon during the year, The annual effective dose of radon exposed to the resident can be calculated by multiplying the residence coefficient, which is a value obtained by dividing the time occupied in the residence on the average for a day, by the total time per day, and the proportional constant. The proportional constant may be a value of an equilibrium factor between radon and radon progeny in the indoor air, a value of the dose conversion factor for converting the unit of the average concentration of the radon into the effective dose unit of the radon, and the total time of the year have.

The correction factor is proportional to the value obtained by adding the average concentration of radon in the indoor air measured monthly over a period of 12 months divided by the average concentration of the radon in the indoor air measured in the month during the one season can do. The correction factor for any one of the seasons can be derived from an equation representing the relationship between the background concentration of the habitat, the correction factor of the season, the average concentration of radon over n months, and the average concentration of radon during 12 months .

According to another aspect of the present invention, there is provided an apparatus for automatically reducing radon contained in air by using a method of predicting the annual exposure dose of the radon, comprising: An exhaust fan for reducing the concentration of radon contained in the air in the room by discharging the air into the upper outer space; And a controller for controlling the operation of the exhaust fan based on the predicted annual exposure dose of the radon according to a method of predicting the annual exposure dose of the radon. The controller may set the daily operation time of the exhaust fan every year according to the predicted annual exposure dose of the radon and increase / decrease the daily operation time according to each season. The apparatus for automatically reducing radon further includes a radon sensor installed in a room of the building for detecting the concentration of radon in the room air, The daily operation time of the fan can be set to one year and the daily operation time can be increased or decreased according to the size of the radon concentration detected by the radon sensor.

The mathematical prediction model can be used to estimate the annual exposure dose of radon based on the average concentration of radon measured during any one season, so that the annual dose of radon can be applied to the calculation of the risk of lung cancer by exposure to radon. It is possible to solve the uncertainty of the lung cancer risk evaluation based on the short term radon concentration survey, so that reliable lung cancer risk can be calculated, and radon reduction measures can be established considering the annual exposure dose of radon. Can be prevented. In particular, since the annual exposure dose of radon is estimated considering the residence time of residents, accurate annual exposure dose can be calculated considering the residence characteristics of resident by residence environment.

In addition, since the average concentration of radon in three months used as the process test method for indoor radon measurement can be used to predict the annual exposure dose of radon, the average concentration of radon in each region In fact, it is not necessary to measure the concentration of radon in the indoor air because it can utilize the Big Data. In this case, it is possible to prevent the economic loss due to the purchase of the expensive radon sensor and the time loss due to the measurement of the radon concentration for 3 months have. In addition, it is possible to transmit quantitative information to the national healthcare and environmental management agencies for the evaluation of the risk of reliable lung cancer caused by exposure to radon by using the results of such big data utilization.

1 is a block diagram of a radon reduction apparatus according to an embodiment of the present invention.
Fig. 2 is a configuration diagram of the controller 60 shown in Fig.
3 is a flow chart of a radon annual average exposure dose predicting method according to an embodiment of the present invention.
4 is a flowchart of the calculation process of the correction coefficient for one season in step 33 shown in FIG.
5 is a flowchart of a calculation process of the mathematical prediction model in step 33 shown in FIG.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. The radon concentration is expressed as becquerel (Bq) or picocuria (pCi). Becquerel is an international standard unit of radioactive material, which indicates the amount of radiation that is emitted once from the nucleus in one second, ie, one radioactive decay occurs for one second. The concentration of radon in air is expressed as Bq / ㎥ or pCi / L, and 1 pCi / L is equivalent to 37 Bq / ㎥. According to the indoor air quality recommendation standard in Article 6 of the "Act on the Indoor Air Quality Control of Multi-use Facilities, etc.", the concentration of radon in the indoor air is recommended to be 148 Bq / ㎥ or less. The embodiments described below are based on a method of predicting the annual exposure dose of radon which is exposed to a resident of a residence based on the average concentration of radon measured during a season in any place of residence, Quot; radon annual exposure dose prediction method "and" radon reduction device ".

1 is a block diagram of a radon reduction apparatus according to an embodiment of the present invention. 1, the radon reduction device according to the present embodiment includes an intake pipe 10, a connection pipe 20, an exhaust fan 30, an exhaust pipe 40, a radon sensor 50, and a controller 60 . The intake pipe 10 is positioned below the bottom surface 110 of the building 100 in the residence and sucks air flowing into the room of the building 100. 1, the intake pipe 10 may be installed on the ground 120 in a space between the bottom surface 110 of the building 100 and the ground 120. As shown in FIG. The connection pipe 20 connects the intake pipe 10 and the exhaust fan 30. The exhaust fan 30 sucks the air flowing into the room of the building 100, that is, the inside air of the intake tube 10, and discharges it to the outside space above the building, thereby reducing the concentration of radon contained in the room air. The exhaust pipe (40) discharges the air discharged from the exhaust fan (30) to the upper external space of the building (100).

The radon sensor 50 is installed in a room of the building 100 to detect the concentration of radon contained in the air in the room. The controller 60 controls the operation of the exhaust fan 40 based on the predicted annual exposure dose of radon according to the method described below. Conventionally, since the operation of the exhaust fan 30 is controlled based on the radon concentration detected by the radon sensor 50, installation of an expensive radon sensor 50 is required, and when the radon sensor 50 fails, There is a problem that the exhaust fan 40 can be always turned on or off. According to the present embodiment, since the controller 60 basically controls the operation of the exhaust fan 40 based on the annual exposure dose of the radon, it is not necessary to install the radon sensor 50 necessarily, Since the operation of the exhaust fan 40 can be controlled based on the annual exposure dose of the radon even in the event of the failure of the radon sensor 50, the health hazards of the occupant due to the insufficient operation of the exhaust fan 30 And it is possible to prevent energy waste and noise pollution due to excessive operation of the exhaust fan 30. [

The controller 60 may set the daily operation time of the exhaust fan 40 in accordance with the magnitude of the annual exposure dose of the radon predicted according to the method described below and increase / decrease the daily operation time according to each season. Otherwise, the controller 60 sets the daily operating time of the exhaust fan 40 year by year according to the predicted annual exposure dose of the radon according to the method described below, and sets the daily running time by the radon sensor 50 And can be increased or decreased according to the magnitude of the detected radon concentration. The controller 60 turns the exhaust fan 40 on or off based on the daily operation time thus increased or decreased. The former can implement the radon abatement apparatus at low cost as an embodiment that does not require the radon sensor 50 but can not cope with the real time change of the radon concentration due to the change of the living environment due to the fact that the actual concentration of the radon is not considered . On the other hand, the latter can cope with the real-time change in radon concentration due to changes in the environment of the residence, but an expensive radon sensor 50 should be installed.

Fig. 2 is a configuration diagram of the controller 60 shown in Fig. 2, the controller 60 is comprised of a processor 61, a storage 62, a user interface 63, and a power supply signal generator 64. [ As shown in FIG. 1, a storage 62 stores a program for predicting the annual exposure dose of radon to a resident of a residence based on the average concentration of radon measured during any one season in a habitat. The controller 60 can control the operation of the exhaust fan 30 in accordance with this prediction program by the processor 61 executing the prediction program stored in the storage 122. [ The user interface 63 receives the residence time at the residence and the average concentration of radon measured during a certain season from the user and sends it to the processor 61. The power supply signal generator 64 generates a power supply signal to be supplied from the power supply 200 to the exhaust fan 30 under the control of the processor 61 and supplies the generated power supply signal to the exhaust fan 30 to drive the exhaust fan 30.

3 is a flow chart of a radon annual average exposure dose predicting method according to an embodiment of the present invention. Referring to FIG. 3, the radon annual average exposure dose predicting method according to the present embodiment is composed of the steps performed by the controller 60 as follows. As shown in FIG. 2, the storage 62 stores a program for predicting the average radon exposure per year. The radon annual average exposure dose prediction method shown in FIG. 3 may be performed by the processor 61 of the controller 60 executing a prediction program stored in the storage 62. [

 In step 31, the controller 60 receives the user's residence time from the user through the user interface 63. The controller 60 may receive the time when the resident resides in the residence on average on average for one year, but for the convenience of the user, the resident receives an average residence time in the residence during the day. In step 32, the controller 60 receives the average concentration of radon measured at the residence during any one of a plurality of seasons in the area where the residence is located from the user through the user interface 63. In step 33, the controller 60 computes a mathematical prediction of the relationship between the resident's residence time, the average concentration of radon measured during a season, the correction factor of a season, and the annual effective dose of radon exposed to a resident Assign the residence time entered in step 31 and the radon average concentration entered in step 32 to the model.

In step 34, the controller 60 estimates the annual exposure dose of the radon by calculating the annual effective dose of the radon exposed to the resident from the mathematical prediction model in which the residence time and the average radon concentration are substituted in step 33. [ In more detail, the controller 60 estimates the average concentration of radon for one year by applying a seasonal correction factor to the average concentration of radon measured during a season according to a mathematical prediction model, By applying residence time to the estimate of the average concentration of radon, one can calculate the annual effective dose of radon exposed to residents. The thus calculated annual effective dose can be provided to the user through the user interface 63. [ How to construct the mathematical prediction model used to calculate the annual effective dose of radon and how to determine the correction coefficient specifically will be described in detail with reference to FIGS. 4 and 5 below.

Considering that typical health adverse effects due to radon exposure are lung cancer, a chronic disease, it is required to measure cumulative long-term exposure to radon during one year in health impact assessment for radon. It is not feasible to investigate long - term cumulative concentration of radon for a year in a residential area where people live. Therefore, we are evaluating effective doses and risk of lung cancer by exposure to radon only through short - term global survey. In a country where the four seasons change for a year, the indoor environment, like the outdoor environment, also changes according to the seasonal weather. In winter, radon concentration in indoor air is higher than other seasons due to the effect of chimney. On the other hand, in the summer, frequent ventilation causes lower indoor air radon concentrations than other seasons. These changes can lead to uncertainty in evaluating the effective dose due to radon exposure and the risk of lung cancer.

Generally, it is recommended to calculate the cumulative concentration of radon in three months by the process test method of radon measurement indoors. As described above, the radon concentration in the indoor air is seasonally different. Therefore, the uncertainty of the annual exposure dose of radon, which is an essential data in the evaluation of the health effect of radon due to the difference in the average concentration of radon according to the measurement period during the year, The reliability of the evaluation of the risk of lung cancer occurrence is reduced. According to this example, radon exposure is estimated by predicting the annual exposure dose of radon based on the average concentration of radon measured during a 3 months period, that is, the average concentration of radon measured during a season, , It is possible to calculate the risk of lung cancer occurrence as well as to establish the measures against radon reduction considering the annual exposure dose of radon, Lung cancer, a chronic disease, can be prevented.

In particular, since the annual exposure dose of radon is estimated considering the residence time of residents, accurate annual exposure dose can be calculated considering the residence characteristics of resident by residence environment. In addition, in this example, since the average concentration of radon in three months used as a process test method for indoor radon measurement can be used to predict the annual exposure dose of radon, It may not be necessary to actually measure the concentration of radon in the room air because it can utilize the big data such as the average concentration. In this case, the economic loss due to the purchase of the expensive radon sensor 50 and the measurement of the radon concentration for 3 months It is possible to prevent a temporal loss according to the present invention. In addition, it is possible to transmit quantitative information to the national healthcare and environmental management agencies for the evaluation of the risk of reliable lung cancer caused by exposure to radon by using the results of such big data utilization.

4 is a flowchart of the calculation process of the correction coefficient for one season in step 33 shown in FIG. Referring to FIG. 4, the calculation process of the correction coefficient according to the present embodiment includes the following steps. The controller 60 may calculate the correction coefficient in the step 33 by carrying out these steps and store it in the storage 62 or the designer of the other computer or the controller 60 may perform these steps in advance to calculate the correction coefficient in step 33 And may be stored in the storage 62. While the following description assumes that these steps are performed by the controller 60, it will be appreciated by those skilled in the art that other embodiments may be practiced by other computer or designer of the controller 60 I can understand it. The units of all radon concentrations appearing below are Bq / m < 3 > and will be omitted in order to prevent the characteristics of the present embodiment from being blurred due to scrambling of unit display.

In step 41 controller 60 Equation time in accordance with a first location of the building during the T, that is the average concentration of M i of the radon which is exposed to a resident of the residence i construction for the background density of the residence C o, wherein the time T The sum of the terms of the average concentration of radon in the indoor air of the room. In the equation (1), the background concentration C o means the outdoor air radon concentration in the residential building. t 1 means the start of the measurement of the radon concentration in the indoor air, and t 2 means the end of the measurement of the radon concentration in the indoor air. That is, T = t 2 -t 1 . f i (t) is a time function representing the concentration of radon in the indoor air in settlement i and is always greater than zero. As shown in Equation 1, the average concentration of the radon in the indoor air at the residence i for the time T can be calculated by dividing the value obtained by integrating f i (t) during the time T by the time T. [

Figure 112016009960027-pat00001

In step 42, the controller 60 calculates a time function s (t) of indoor radon concentration in the room air at a period of 12 months with a time function f i (t) representing the radon concentration in the indoor air at the residence i according to the following equation (2) And the weight h i of the residence i. In Equation (2), s (t) is a time function representing the concentration of radon in typical indoor air, which varies from 12 months in a typical residential environment. h i is a weight that compensates for the difference between the typical indoor air radon concentration and the indoor air at home i.

Figure 112016009960027-pat00002

In step 43, the controller 60 calculates the time function f i (t) from the terms of the equation of the average concentration M i of radon generated in step 41 according to the following equation (3) with the time function s (t) by replacing the multiplication of h i and generates an equation representing the mean levels M i of radon as a background concentration C o of wherein the time function s (t) and the average term summation of the weighted h i multiplication for a time T. As shown in Equation (3), the average of the multiplication of the time function s (t) and the weight h i during the time T can be calculated by dividing the value obtained by integrating s (t) h i during the time T by the time T . Thus, the expression of the average concentration of radon M i as a time function s (t) representing the typical indoor air radon concentration over a period of 12 months in a typical residential environment indicates that the variation pattern of radon concentration with seasonal variation The assumption is common.

Figure 112016009960027-pat00003

In step 44, the controller 60 moves the term of the background concentration C o of the right side of the equation of the average concentration M i of the radon generated in step 43 to the left side according to the following equation (4) . Accordingly, the multiplication of the time function s (t) and the weight h i of the residence i is transformed into a summation of its respective logs.

Figure 112016009960027-pat00004

In step 45, the controller 60 integrates the time function s (t) for the time T among the terms of the logarithmic equation generated in step 44 according to the following equation (5) and divides the time function s and n mean density M (n) of radon in the average concentration of M i of radon during the time T by replacing a value summing the average concentration of radon in the room air measured on a monthly basis during the months divided by n n months . In Equation (5), j is any one of 1 to 12. For example, j = 1 represents January.

Figure 112016009960027-pat00005

In Step 46 the controller 60 and then wherein the residence of the average concentration of M (n) of radon in the n-month period by removing the log from the both sides of the log equation converted in step 45 in accordance with equation (6) background concentration C o i From the sum of the average concentrations of radon measured monthly in n months starting from j j, divided by n, and the product of the multiplication terms of the weight h i . Steps 41 to 46 show the average radon average M i for the time T from the equation representing the sum of the terms of the background concentration C 0 and the average concentration of the radon in the building during the time T from the equation The concentration M (n) is the sum of the values of the background concentration C o and the value obtained by dividing the value of the average concentration of radon measured in months over n months starting from j j in residence i by n and the multiplication of the weight h i And the equation is expressed as.

Figure 112016009960027-pat00006

In step 47, the controller 60 sets j to "1" and n to "12" in the equation of the average concentration M (n) of radon for n months generated in step 46 according to the following equation The average concentration M (12) of the 12-month period was calculated by dividing the value of the background concentration C o by the sum of the average concentration of radon measured monthly in the period of 12 months and the sum of the term of multiplication of h i . Thus, the average concentration M (12) of radon over a 12-month period can be calculated from the sum of the average concentrations of radon measured monthly over the entire year, ie, 12 months.

Figure 112016009960027-pat00007

In step 48, the controller 60 calculates the average radon concentration M (12) of the 12-month period calculated in step 47 according to the following equation (8) The value obtained by dividing the value obtained by dividing the average concentration of radon in the indoor air by 12 and the multiplication of the weight h i by subtracting the background concentration C o from the average concentration M (n) of the radon during n months, By substituting the multiplication of the correction factor f j, n , the background concentration C o , the correction factor f j, n , the average concentration of radon M (n) for n months and the average concentration M (12) Create an equation representing the relationship. Equation 8 shows the average concentration M (n) -C o of the radon in the room air measured over n months, that is, the average concentration M (3) -C o of the indoor air measured during one season, Multiplication of the factor f j, 3 results in the assumption that the average concentration of radon in the room air measured over a year is estimated.

Figure 112016009960027-pat00008

In step 49, the controller 60 calculates the correction factor f j, n of a season from the equation of the average concentration M (12) of radon for 12 months generated in step 48 according to the following equation (9) And the average concentration of radon in the indoor air measured monthly over a period of 12 months is divided by the sum of the average concentration of the radon in the indoor air measured for n months, And the multiplication of the division result of the latter and the division result of the latter. That is, a value obtained by dividing a value obtained by adding the average concentration of radon in n months in equation (6 ) to n (n) - C o among the items of the equation of the average concentration M (12) replacing the multiplication of the weight h i, and M (12) - C o the following formula by substituting the 12-month radon multiplication of the average concentration of summing the values of the value and weighting h i, divided by 12, the for in equation 79 , That is , the equation of the correction coefficient f j, n of one season can be derived. The correction coefficient f j, n of any one season can be calculated using the equation (9).

Figure 112016009960027-pat00009

5 is a flowchart of a calculation process of the mathematical prediction model in step 33 shown in FIG. Referring to FIG. 5, the calculation process of the mathematical prediction model according to the present embodiment includes the following steps. The controller 60 may calculate the mathematical prediction model in step 33 and store the mathematical prediction model in the storage 62 by performing these steps or may perform the steps in advance by a designer of the other computer or controller 60, May be calculated and stored in the storage 62. While the following description assumes that these steps are performed by the controller 60, it will be appreciated by those skilled in the art that other embodiments may be practiced by other computer or designer of the controller 60 I can understand it.

As described above, the correction factor f j, n of a certain season is the background concentration C o , the correction factor f j, n , the average concentration M (n) of radon during n months, M (12) , and this correction factor is the sum of the average concentrations of radon in the room air measured monthly over a period of 12 months, It is proportional to the value divided by the sum of the average concentrations of radon. During 2010 ~ 2011, the Ministry of Environment conducted repeated measurements for 4 months at each branch for 3 months, ie, one season, for each of the four seasons. By substituting such big data in Equation (9), the seasonal correction coefficient can be calculated.

In the following description, the correction coefficient for spring is set to "a", the correction coefficient for summer is set to "b", and the correction coefficient for fall is set to "quot; c "and the winter correction coefficient is denoted by" d ". The average radon concentration of 7.62 ± 4.11Bq / m 3 in the outdoor air measured by an electrostatic radon monitor over 26 months from December 1999 to January 2002 in Seoul, Korea In the following, the constant value of the background concentration required to calculate the annual average concentration of radon is set to 7 Bq / m 3 .

In step 51, the controller 60 calculates the sum of the average concentrations of the radon in the indoor air measured monthly from January to the 12th month in the residence i in equation (8) according to the following equation (10) By dividing into four sections, the average concentration of radon M (12) for 12 months was calculated as the mean concentration of radon measured during spring M spring , the mean concentration of radon measured during summer M summer , and the average concentration of radon measured during autumn M fall , The mean value of the radon measured during winter M winter is subtracted from the constant 7 of the background concentration and the four terms corresponding to the result of each subtraction multiplied by the correction factor of the corresponding season and the constant value 7 The sum of the terms of In this equation, the average concentration of radon in three months measured by the process test method of radon measurement can be substituted, so that it is easy to utilize the existing big data.

Figure 112016009960027-pat00010

The controller 60 estimates the average concentration of radon for one year by substituting the average concentration of radon measured during one season and calculating a correction coefficient other than the correction coefficient corresponding to the season to 0 . That is, the controller 60 subtracts the constant value of the background concentration from the average concentration of radon measured during one season according to Equation (10), multiplies the result of the subtraction by a correction coefficient of a certain season, The average concentration of radon over a year can be estimated by adding a constant value of the background concentration to the result. For example, if the average concentration of radon measured during the summer is substituted into equation (10), the correction coefficients a, c, and d are set to zero except for the correction coefficient b. In this case, the controller 60 subtracts the constant value 7 of the background concentration from the average concentration M summer of the radon measured during the summer , multiplies the result of the subtraction by the summer correction coefficient b, The average concentration of radon for one year can be estimated by adding a constant value of 7.

The dosimetric approach is to evaluate the possibility of lung cancer by radon exposure using the biological approach to assess the likelihood of developing lung cancer based on biological theory and the statistical analysis of epidemiological data at each stage of lung cancer development by radiation exposure In order to utilize the abundant epidemiological data for the atomic bomb survivors in evaluating the possibility of lung cancer development by radon exposure compared to the empirical approach, the present embodiment adopts a dose-based approach. The United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) calculates annual effective doses by exposure to radon through the application of dose conversion factors in accordance with this dose approach.

In step 52, the controller 60 calculates the annual effective dose E of the radon exposed to the occupant according to the following equation (11) proposed by the United Nations Radiation Effects Research Committee: radon concentration Q, the equilibrium factor between radon and radon progeny F, , The dose conversion factor K for converting the unit of the dose into the effective dose unit of the radon, and the total residence time T of the year. In Equation (11), the unit of the radon concentration Q is Bq / m 3 , the equilibrium factor F is an anonymous number, the total time T of the year is the total number of residues Δt x the total annual time (8760h), and the unit of the dose conversion coefficient K is mSv (Bq h h m -3 ) -1 . The residence coefficient Δt is an anonymous number, divided by the total time of day, ie 24h, on the average resident residing in the residence during the day.

Figure 112016009960027-pat00011

In step 53, the controller 60 substitutes the value of the equilibrium factor F, the value of the dose conversion factor K, and the value of the total time T of the year into the equation of the annual effective dose E of the radon generated in step 52, . The United Nations Scientific Committee on the Effects of Radiation has proposed a value of 0.5 and 0.6 for the equilibrium factor F in indoor and outdoor fields in 1977, In addition, the United Nations Scientific Committee on the Effects of Radiation has proposed a dose conversion factor, Q, of 8.7 nSv (Bq h h m m -3 ) -1 for both indoors and outdoors in the 1982 report. Therefore, in this embodiment, the value of the equilibrium factor F is set to 0.4, and the value of the dose conversion factor Q is set to 9 nSv (Bq h hm -3 ) -1 . 0.4 x 0.000009 x 8760 is about 0.032, the following equation (12) can be calculated.

Figure 112016009960027-pat00012

In step 54, the controller 60 replaces the average concentration M (12) of the radon for 12 months from the items of the equation of the annual effective dose E calculated in step 53 with the seasonally divided equations in step 51, From the equation of effective dose E, the residence coefficient of residents Δt, the average concentration of radon measured during one season (M spring , M summer , M fall , or M winter ), the correction factor (a, Or d), and the annual effective dose E of the radon exposed to the occupant, i.e., equation (13).

Figure 112016009960027-pat00013

The controller 60 calculates the annual effective dose of radon exposed to the occupant from the average concentration of radon measured during any one season, that is, a mathematical prediction model that allows to calculate the annual exposure dose, Subtracting the constant value 7 of the background concentration from the average concentration of radon measured during the season, multiplying the result of the subtraction by the correction coefficient of the season, and adding a constant value 7 of background concentration to the result of the multiplication, , The annual effective dose of radon exposed to residents can be calculated by multiplying the estimate of the average concentration of radon over a year by the residence coefficient Δt and the proportional constant 0.032. Here, the proportional constant 0.032 is a value obtained by multiplying the value of the equilibrium factor F, the value of the dose conversion factor Q, and the total time of one year, as described above.

The present invention has been described with reference to the preferred embodiments. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

10 ... intake tube
20 ... connector
30 ... exhaust fan
40 ... exhaust pipe
50 ... Radon sensor
60 ... controller
61 ... processor
62 ... storage
63 ... User Interface
64 ... power signal generator

Claims (10)

The controller receiving the residence time in the residence of the resident;
The controller receiving an average concentration of radon measured in the habitat during any one of a plurality of seasons of an area where the habitat is located;
Wherein the controller is further operable to calculate a mathematical predictive model representing a relationship between the residence time, the average concentration of radon measured during the one of the seasons, the correction coefficient of the one of the seasons, and the annual effective dose of radon exposed to the occupant, Time and the input average radon concentration; And
Wherein the controller includes estimating an annual exposure dose of radon by calculating an annual effective dose of radon exposed to the occupant from the mathematical prediction model in which the residence time and the radon average concentration are substituted,
The correction factor is proportional to the value obtained by adding the average concentration of radon in the indoor air measured monthly over a period of 12 months divided by the average concentration of the radon in the indoor air measured in the month during the one season Wherein the radon dose is calculated as a function of time. The method according to claim 1,
Wherein estimating the annual exposure dose of the radon comprises estimating an average concentration of radon for one year by applying a correction coefficient of the one season to the average concentration of radon measured during the one season according to the mathematical prediction model, Wherein the annual effective dose of radon exposed to the occupant is calculated by applying the residence time to an estimate of the average concentration of radon during the one year. 3. The method of claim 2,
Wherein predicting the annual exposure dose of the radon comprises: subtracting a constant value of the background concentration from the average concentration of radon measured during the one season, multiplying the result of the subtraction by the correction coefficient of the one of the seasons, And estimating an average concentration of radon during the year by adding a constant value of the background concentration to the result of the calculation. The method of claim 3,
The step of receiving the residence time may include receiving the residence time of the resident on an average basis during the day,
The step of predicting the annual exposure dose of the radon multiplies the estimate of the average concentration of radon during the year by the residence coefficient and the proportional constant, which is the value obtained by dividing the average residence time of the resident in the residence for one day by the total day time Thereby calculating the annual effective dose of radon exposed to the occupant. 5. The method of claim 4,
The proportional constant is a value obtained by multiplying the value of the equilibrium factor between the radon and the radon progeny in the indoor air, the value of the dose conversion factor for converting the unit of the average concentration of the radon into the effective dose unit of the radon, and the total time of one year A method for predicting the annual exposure dose of radon characterized. delete 6. The method of claim 5,
The correction coefficient of the one season is derived from an equation representing the relationship between the background concentration of the settlement, the correction coefficient of the season, the average concentration of radon during n months, and the average concentration of radon during 12 months To estimate the annual exposure dose of radon. An apparatus for automatically reducing radon contained in air in a room using the method of claim 1,
An exhaust fan for reducing the concentration of radon contained in the indoor air by sucking the air flowing into the indoor space of the building of the residence and discharging the air to the upper outer space of the building; And
And a controller for controlling the operation of the exhaust fan based on the predicted annual exposure dose of radon according to the method of claim 1. 9. The method of claim 8,
Wherein the controller sets the daily operation time of the exhaust fan every year according to the predicted annual exposure dose of the radon and increases / decreases the daily operation time according to each season. 9. The method of claim 8,
Further comprising a radon sensor installed in a room of the building for detecting the concentration of radon in the indoor air of the building,
Wherein the controller sets the daily operation time of the exhaust fan every year according to the predicted exposure dose of the radon per year and increases or decreases the daily operation time according to the radon concentration detected by the radon sensor. A radon abatement device.
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