KR20190046418A - Development of System for EDCs Multimedia Fate and Transport Model, Using Ecotoxicity Monitoring Data - Google Patents

Abstract

The purpose of the present invention is to build ecotoxicity data for reducing exposure of EDCs and for making risk management measures and to provide an EDCs distribution model system based such data. According to the present invention, an EDCs multimedia distribution model system based on ecotoxicity monitoring data comprises: a data storage unit which comprises an ecotoxicity monitoring DB and a multimedia distribution model DB; an input data control unit which generates input data by corresponding to input contents of a system user; a multimedia distribution model driving unit which considers weather and geographic characteristics for dosage, deposition and concentration by behavior of EDCs materials in gases, liquids and particle forms to calculate according to changes of time and space (including media), and applies a distribution model in a Lagrangian particle model method considering uncertainty of turbulent flows; and a modelling result output control unit which combines a result of the multimedia distribution model driving unit with GIS data, and processes the same as images and displays the same.

Description

[0002] The present invention relates to a multi-media distribution system for EDCs based on ecotoxicity monitoring data,

The present invention relates to a multi-media distribution model system for EDCs for reducing exposure to endocrine disrupting chemicals (EDCs).

EDCs are defined as exogenous substances that affect the production, excretion, metabolism, binding, and action of normal hormones and cause adverse effects on the maintenance and development of homeostasis (US EPA, US EPA). The World Health Organization (WHO) defines EDCs as substances that can alter the action of the body's endocrine system and cause adverse effects on individuals, their offspring, or population.

WHO and the United Nations Environment Program (UNEP), for decades, have shown that ecosystemic comparisons can include ecosystem impacts such as reduced fertility and hatching rates of animals, male infertility, congenital genital anomalies, sexual dysfunction, The prevalence rate of decline is increasing globally, and chemical exposure has been shown to be an important cause of this phenomenon and disease growth.

There are a wide variety of substances known to cause endocrine disruptions in the environmental ecosystem and in the general population so far, and the effects of endocrine disrupting chemicals on newly used chemicals are constantly evolving, and the number of EDCs is steadily increasing.

EDCs have emerged as one of the top three environmental problems in the world because of the widespread concern that ecosystems and human endocrils can affect the species worldwide. The incidence of endocrine-related diseases due to exposure to EDCs results in significant social costs as well as personal health deterioration. For example, the social costs of childhood obesity and adult cardiovascular diseases caused by bisphenol A in food and beverage containers are estimated to reach $ 1.7 billion per year in the United States. Infertility, disability, developmental disorders, and endocrine disruption have been increasing rapidly in Korea, and this is one of the major challenges of future health and population policy in Korea.

The present invention relates to the construction of ecotoxicity data for reducing the exposure of EDCs and establishing a risk management countermeasure, and an EDCs distribution modeling system based on the data.

In order to solve the above-mentioned problems, an EDCs multi-media distribution model system based on ecotoxicity monitoring data includes a data storage unit including an ecotoxicity monitoring DB and a multi-media distribution model DB; An input data control unit for generating input data corresponding to input contents of a system user; The change of time and space (including media), taking into account the weather and geographical characteristics of Dosage, Deposition and Concentration due to the behavior of gas, liquid and particulate EDCs, A multi - media distribution model driver applying a distribution model of the Lagrangian particle model method considering the uncertainty of turbulence; And a model result output control unit that combines the results of the multi-media distribution model driving unit with the GIS data, processes the images, and displays the result.

The eco-toxicity monitoring DB includes actual monitoring data and ecotoxicological property data as basic data of the EDCs multi-media distribution model, and the multi-media distribution model DB includes EDCs substance information, weather information , Terrain information, and land cover information.

The EDCs material information of the multi-media distribution model DB shares data with the ecotoxicological property information, and the weather information among the multi-media distribution model DB utilizes the meteorological statistical data of the meteorological station for a certain period of time, And a digital elevation model (DEM) provided by the Geographical Survey Institute of Korea, and the land cover information of the multi-carrier distribution model DB is composed of 31 types of covering data.

The multi-media distribution model driving unit applies a Lagrangian particle dispersion model (LPDM) to allocate virtual particles at a predetermined ratio at an initial point of the EDCs material, And the position of the EDC material particles is tracked by the wind field and the medium.

INDUSTRIAL APPLICABILITY According to the present invention, exposure of EDCs can be reduced and risk management measures can be established by making it possible to cope with a chemical substance leakage accident by utilizing an indexed basic database.

1 is a system configuration diagram of an EDCs multi-media distribution model system (S) based on ecotoxicity monitoring data according to an embodiment of the present invention.
2 is a reference diagram illustrating actual monitoring data.
Figure 3 is a reference diagram illustrating some of the ecotoxicological property data.
Figure 4 is a reference diagram illustrating the overall process of a system according to the present invention.
5A to 5H are reference diagrams illustrating a processing result screen of a multi-media distribution model.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Embodiments of the present invention are provided to more fully describe the present invention to those skilled in the art, and the following embodiments may be modified in various other forms, The present invention is not limited to the following embodiments. Rather, these embodiments are provided so that this disclosure will be more thorough and complete, and will fully convey the concept of the invention to those skilled in the art.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a", "an," and "the" include plural forms unless the context clearly dictates otherwise. Also, " comprise " and / or " comprising " when used herein should be interpreted as specifying the presence of stated shapes, numbers, steps, operations, elements, elements, and / And does not preclude the presence or addition of one or more other features, integers, operations, elements, elements, and / or groups. As used herein, the term " and / or " includes any and all combinations of one or more of the listed items.

Although the terms first, second, etc. are used herein to describe various elements, regions and / or regions, it should be understood that these elements, components, regions, layers and / Do. These terms do not imply any particular order, top, bottom, or top row, and are used only to distinguish one member, region, or region from another member, region, or region. Thus, the first member, region or region described below may refer to a second member, region or region without departing from the teachings of the present invention.

Hereinafter, embodiments of the present invention will be described with reference to the drawings schematically showing embodiments of the present invention. In the figures, for example, variations in the shape shown may be expected, depending on manufacturing techniques and / or tolerances. Accordingly, embodiments of the present invention should not be construed as limited to any particular shape of the regions illustrated herein, including, for example, variations in shape resulting from manufacturing.

A method and system for responding to a chemical spill incident using an indexed basic database according to an embodiment of the present invention will be described with reference to the following drawings.

1 is a system configuration diagram of an EDCs multi-media distribution model system (S) based on ecotoxicity monitoring data according to an embodiment of the present invention.

1, an EDCs multi-media distribution model system S based on ecotoxicity monitoring data includes a data storage unit 110, an input data control unit 120, a multi-media distribution model driving unit 130, a model result output control unit 140, An output unit 150, and an input unit 160.

The data storage unit 110 includes an eco-toxicity monitoring DB 111 and a multi-media distribution model DB 112.

The eco-toxicity monitoring database 111 of the data storage unit 110 is used as a basic data of the EDCs multi-media distribution model and consists of actual monitoring data and ecotoxicological property data.

In the case of actual monitoring data, it is recorded in a database centered on the diameter of the target area, date and time of collection, collection medium, and harvest value.

FIG. 2 is a reference diagram illustrating actual monitoring data, and FIG. 3 is a reference diagram illustrating a part of ecotoxicological property data. In the case of ecotoxicological property data among the ecotoxicological monitoring DB (111), physical property information of the substances to be monitored for ecotoxicity is recorded, processed into a table form of the database, and constructed in the ecotoxicity monitoring DB 111.

The multi-media distribution model DB 112 among the contents of the data storage unit 110 stores and manages model input data performed by the multi-media distribution model driving unit 130.

Major components of the multi-media distribution model DB 112 include EDCs material information, weather information, topographic information, and land cover information.

The EDCs material information in the multi-media distribution model DB 112 shares data with the above-described ecotoxicity property information.

The meteorological information of the multi - media distribution model DB (112) utilizes the meteorological statistical data of the Meteorological Agency for the last 10 years.

The digital elevation model (DEM) of 100 m intervals provided by the Geographical Survey Institute applies the terrain information of the multi-media distribution model DB 112.

The land cover information of the multi-media distribution model DB 112 constitutes the input data by applying the 31 kinds of cover classification, and the detailed classification items are as shown in Table 1 below.

Category number Land cover classification 0 Ocean One Water (lakes, rivers, streams (inland water)) 2 Ice cal / glacer 3 Evergreen needleleaf tree 4 Deciduous needleleaf tree 5 Deciduous broadleaf tree 6 Evergreen broadleaf tree 7 Short grass 8 Tall grass 9 Desert 10 Semi-desert 11 Tundra (tundra) 12 Evergreen shrub 13 Deciduous shrub 14 Mixed woodland 15 Crop / mixed farming 16 Irrigated crop 17 Wetland (bog or marsh) 18 Evergreen needleleaf forest 19 Evergreen broadleaf forest 20 Deciduous needleleaf forest 21 Deciduous broadleaf forest 22 Mixed cover 23 Woodland 24 Wooded grassland 25 Closed shrubland 26 Open shrubland 27 Grassland 28 Cropland 29 Bare ground 30 Urban and built up

The input data control unit 120 generates input data to the multi-media distribution model driving unit 130 and automatically generates input data according to input contents of the system user.

The multidimensional distribution model driving unit 130 calculates the time and space (time, space, and time) based on the meteorological and geographical characteristics of Dosage, Deposition and Concentration due to the behavior of the gas, (Including media), and we apply the distribution model of the Lagrangian particle model method considering turbulence uncertainty.

The Lagrangian particle dispersion model (LPDM) applied to the multi-media distribution model driving unit 130 allocates virtual particles at a predetermined ratio at an initial point of the EDCs material, And the position of the EDC material particles is tracked by wind field and medium.

The following equation is applied to track the EDCs particle position.

In the above equation, x and y represent the horizontal coordinate having a perpendicular relationship to each other, and z indicates the vertical coordinate. U and V represent the average velocity of wind in the x and y directions, and W is the velocity in the vertical direction. U, v, w, denoted by a suffix in lower case, denotes the turbulent component. σt is the individual time interval for particle movement.

In this case, the turbulence velocity components in the vertical and horizontal directions are expressed by the Lagrangian auto-correlation (Ri, i = u, v, w) and the standard deviation of the turbulent velocity (σ i, , v, w).

In this equation, Ri (i = u, v, w) is a random number with an average of 0 and a standard deviation of 1. In the above equation, the third term on the right side of w '(t) is an additional term to prevent the abnormal accumulation of particles in the atmospheric boundary layer and near the surface where the standard deviation of the vertical direction turbulent velocity changes abruptly. On the other hand, the autocorrelation coefficient is calculated from the Lagrangian integral time scale (T Li).

When the positions of the individual particles distributed within the specific time distribution model region according to the reference time are calculated by applying the above equations, the number of the particles is counted and converted into the concentration according to the EDCs material characteristic.

The total computation time of the multi-media distribution model driving unit 130 is determined by the number of initial emission particles and the total number of computation periods according to the diffusion prediction unit time setting.

The number of emissive virtual particles can be changed by the user. The default value is 1000. EDCs In order to calculate the concentration distribution of EDCs, the distribution model is computed by looping the particles as many times as the number of particles. Therefore, when a large amount of particles are discharged at the source (leakage point), the calculation time increases in proportion to the number of particles.

In the case of the predicted unit time of the distribution model, the user can change it as well as the number of emitted particles, and the default value is 1 hour. Similar to the number of particles, the unit time is decreased to increase the number of computation intervals, and the computation time increases proportionally.

The multi-media distribution model driving unit 130 is configured such that the calculation process is performed within a maximum of 3 minutes in order to efficiently respond when a leakage accident occurs and timeliness of model results.

Input / output data related to the operation of the multi-media distribution model driver 130 are shown in Table 2 below.

Data classification Component Storage location I / O classification Initial Release Information Initial gas particle distribution location / total amount Multicast distribution model DB (112) input Initial Liquid Particle Location / Total Initial Liquid Particle Size Distribution A certificate Topographic data Multicast distribution model DB (112) input East-west wind North-south wind Vertical wind Temperatures Precipitation Friction speed Thermal turbulence velocity Temperature scale Ground temperature Mixed highs Atmospheric stability Multicast distribution model result Deposition amount (by time zone) Multicast distribution model DB (112) Print Concentration (by time frame) Dosage (Hourly)

The model result output control unit 140 combines the result of the multi-media distribution model driving unit 130 with the GIS data, performs image processing, and displays the result on the output unit 150.

The input unit 160 processes inputs of the system user.

FIG. 4 is a reference view illustrating an entire processing procedure of the system according to the present invention, and FIGS. 5A to 5H are reference views illustrating a processing result screen of a multi-media distribution model.

Although the embodiments of the present invention have been described above, the embodiments disclosed in the specification of the present invention do not limit the present invention. The scope of the present invention should be construed according to the following claims, and all the techniques within the scope of equivalents should be construed as being included in the scope of the present invention.

Claims (4)

A data storage unit including an ecotoxicity monitoring DB and a multi-media distribution model DB;
An input data control unit for generating input data corresponding to input contents of a system user;
The change of time and space (including media), taking into account the weather and geographical characteristics of Dosage, Deposition and Concentration due to the behavior of gas, liquid and particulate EDCs, A multi - media distribution model driver applying a distribution model of the Lagrangian particle model method considering the uncertainty of turbulence; And
Multidimensional distribution model A multicomputer distribution model system of EDCs based on ecotoxicity monitoring data including a model result output control unit that combines the results of the driving unit with the GIS data and displays it with image processing. The method according to claim 1,
The eco-toxicity monitoring DB includes the actual monitoring data and the ecotoxicological property data as basic data of the EDCs multi-media distribution model,
Wherein the multi-media distribution model DB includes EDCs material information, weather information, topographic information, and land cover information as model input data to be performed by the multi-media distribution model driving unit, based on the ecotoxicity monitoring data. The method of claim 2,
The EDCs material information among the multi-media distribution model DB shares data with the ecotoxicological property information,
The meteorological information of the multi-media distribution model database utilizes meteorological statistical data of the meteorological office for a certain period of time,
The terrain information of the multimodal distribution model DB is applied to a digital elevation model (DEM) provided by the Geographical Survey Institute of Korea,
The multicomponent distribution model system of EDCs based on the ecotoxicity monitoring data is characterized in that the land cover information among the above-mentioned multicomponent distribution model DB is composed of 31 types of covering classification. The method according to claim 1,
The multi-media distribution model driver includes:
By applying a Lagrangian particle dispersion model (LPDM), virtual particles are assigned at a constant rate at the initial point of the EDCs material, mass is given to each particle in consideration of the emission ratio of the particles, EDCs Multicellular distribution model system based on ecotoxicological monitoring data, characterized by the movement of material particles by wind field and media.

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