KR20170033147A - Apparatus and method for generating greenhouse gas distribution data across administrative regions - Google Patents
Apparatus and method for generating greenhouse gas distribution data across administrative regions Download PDFInfo
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- KR20170033147A KR20170033147A KR1020150131112A KR20150131112A KR20170033147A KR 20170033147 A KR20170033147 A KR 20170033147A KR 1020150131112 A KR1020150131112 A KR 1020150131112A KR 20150131112 A KR20150131112 A KR 20150131112A KR 20170033147 A KR20170033147 A KR 20170033147A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3504—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing gases, e.g. multi-gas analysis
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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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
- G06Q50/06—Electricity, gas or water supply
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/84—Greenhouse gas [GHG] management systems
Abstract
The present invention relates to an apparatus and a method for generating greenhouse gas distribution data. The apparatus for generating greenhouse gas distribution data according to an embodiment of the present invention includes a spatial distribution analyzing unit for analyzing a spatial distribution of greenhouse gas concentrations based on greenhouse gas concentrations of a plurality of sample points in a target region and positional information of the sample points, ; A concentration estimator for estimating a greenhouse gas concentration at another point in the target region based on the spatial distribution; And a zone concentration calculation unit for calculating a greenhouse gas concentration of the zone in the target zone based on at least one of the sample point and the other point.
Description
The present invention relates to an apparatus and a method for generating greenhouse gas distribution data.
The right to discharge greenhouse gases such as carbon dioxide, methane, nitrous oxide, hydrogen fluoride, perfluorocarbon, and sulfur hexafluoride, which are the main causes of global warming, for a certain period of time is called carbon emission rights. According to the Kyoto Protocol, compulsory Parties should reduce carbon dioxide emissions by an average of 5% from 2008 to 2012, based on 1990 emissions. Countries or entities that fail to implement them should purchase their carbon credits elsewhere and fulfill their obligations.
To trade carbon credits, the emissions of greenhouse gases must be accurately estimated. The method of estimating the emission of greenhouse gases, in particular, carbon dioxide, has been proposed as a method of indirect measurement based on the direct measurement method and the fuel usage amount. Currently, most CO2 emissions estimates are based on indirect estimations based on energy use or input, which limits accuracy.
In particular, this indirect estimation method overlooks the greenhouse gas emitted or absorbed in nature, and there is a problem that the application methods and standards are different according to the type of industry, and the comparative evaluation between them is impossible and there is no uniformity.
In Korea, the global atmospheric monitoring station is operated at Anmyeon-do and Jeju-do in Taean-gun, Chungcheongnam-do to monitor the emission of carbon dioxide from the ground. However, since there are only about 120 such stations in the world, There are considerable limitations in the use of this data as basic data for transactions between carbon credits.
An object of the present invention is to provide an apparatus and method for generating a greenhouse gas distribution data capable of accurately and reliably calculating a greenhouse gas emission amount over a wide area.
It is an object of the present invention to provide an apparatus and a method for generating a greenhouse gas distribution data that can grasp the scale of emission of greenhouse gases by region, for example, administrative districts.
The apparatus for generating greenhouse gas distribution data according to an embodiment of the present invention includes a spatial distribution analyzing unit for analyzing a spatial distribution of greenhouse gas concentrations based on greenhouse gas concentrations of a plurality of sample points in a target region and positional information of the sample points, ; A concentration estimator for estimating a greenhouse gas concentration at another point in the target region based on the spatial distribution; And a zone concentration calculation unit for calculating a greenhouse gas concentration of the zone in the target zone based on at least one of the sample point and the other point.
The greenhouse gas concentration of the sample point may comprise: an average concentration of atmospheric carbon dioxide of the sample point obtained from the near-infrared satellite image of the subject area.
The near-infrared satellite image of the target area may include a satellite image of the northern hemisphere temperate zone from March to June.
The spatial distribution analyzer may calculate a spatial variability of the greenhouse gas concentration according to the position of the sample point in the target area.
Wherein the spatial distribution analyzing unit sets an effective concentration range based on an actual value of the greenhouse gas concentration measured at the reference point in the target area and sets a sample point where the greenhouse gas concentration is out of the effective concentration range among the plurality of sample points It can be excluded from the calculation of the spatial variability.
Wherein the concentration estimator is configured to: determine a weight for each sample point based on a variogram model corresponding to the calculated spatial variability; and calculate the calculated spatial variability based on the weight and the greenhouse gas concentration of the sample point, The greenhouse gas concentration at the other point can be calculated according to a kriging algorithm corresponding to the kriging algorithm.
Wherein the concentration estimator is configured to determine a weight for each sample point based on a spherical variogram model and calculate the concentration of each of the sample points based on the weight and the greenhouse gas concentration of the sample point based on a universal kriging algorithm, Can be calculated.
Wherein the zone concentration calculating section obtains a boundary of the previously designated zone from the map data of the target zone and calculates an average value of the greenhouse gas concentration of at least one of the sample point and the other point located in the boundary, Of the greenhouse gas concentration.
The greenhouse gas distribution data generation device may further include a greenhouse gas distribution map generation unit that graphically displays an area surrounded by the boundary in the target area with a degree to which the greenhouse gas concentration of the corresponding administrative area belongs.
A method for generating greenhouse gas distribution data according to an embodiment of the present invention includes analyzing a spatial distribution of a greenhouse gas concentration based on a greenhouse gas concentration of a plurality of sample points in a target area and a position of the sample point; Estimating a greenhouse gas concentration at another point in the target area based on the spatial distribution; And calculating a greenhouse gas concentration of the zone within the target zone based on at least one of the sample point and the other point.
The greenhouse gas concentration of the sample point may comprise: an average concentration of atmospheric carbon dioxide of the sample point obtained from the near-infrared satellite image of the subject area.
The near-infrared satellite image of the target area may include a satellite image of the northern hemisphere temperate zone from March to June.
The step of analyzing the spatial distribution of the greenhouse gas concentration may include: calculating the spatial variability of the greenhouse gas concentration according to the position of the sample point in the target area.
Wherein the step of analyzing the spatial distribution of the greenhouse gas concentration comprises the steps of: setting an effective concentration range based on an actual value of the greenhouse gas concentration measured at a reference point in the target area, before calculating the spatial variability; And excluding the sample point at which the greenhouse gas concentration out of the effective concentration range among the plurality of sample points is excluded.
The step of estimating the greenhouse gas concentration of the other point includes the steps of: determining a weight for each sample point based on a variogram model corresponding to the calculated spatial variability; And calculating the greenhouse gas concentration at the other point according to the kriging algorithm corresponding to the calculated spatial variability based on the weight and the greenhouse gas concentration of the sample point.
Wherein determining the weights comprises: determining a weight for each sample point based on a spherical variogram model, wherein calculating the greenhouse gas concentration at the other point comprises: And calculating the greenhouse gas concentration at the other point in accordance with a general kriging algorithm based on the gas concentration.
Wherein the step of calculating the greenhouse gas concentration of the zone comprises the steps of: obtaining a boundary of a pre-designated administrative zone from map data of the target zone; Calculating an average value of the greenhouse gas concentration of at least one of the sample point and the other point located in the boundary; And determining the average value as the greenhouse gas concentration of the administrative zone.
The greenhouse gas distribution data generation method may further include the step of graphically representing an area surrounded by the boundary in the target area with a grade to which the greenhouse gas concentration of the administrative area belongs.
The method for generating greenhouse gas distribution data according to an embodiment of the present invention may be implemented by a computer-executable program and recorded on a computer-readable recording medium.
The method for generating greenhouse gas distribution data according to an embodiment of the present invention may be implemented by a computer program stored in a medium for execution in combination with the computer.
According to the embodiment of the present invention, it is possible to accurately and reliably calculate the greenhouse gas emission amount over a wide area.
According to the embodiment of the present invention, it is possible to grasp the emission amount of greenhouse gas by region, for example, administrative district.
1 is an exemplary block diagram of an apparatus for generating greenhouse gas distribution data according to an embodiment of the present invention.
FIG. 2 is an exemplary diagram showing a target region to which a greenhouse gas concentration distribution is to be determined, sample points in the target region, and a carbon dioxide concentration thereof according to an embodiment of the present invention.
3 is an exemplary diagram illustrating a greenhouse gas concentration distribution of a target area calculated according to an embodiment of the present invention.
4 is an exemplary diagram illustrating a greenhouse gas concentration distribution by administrative area in a subject area according to an embodiment of the present invention.
5 is an exemplary diagram illustrating prediction errors calculated based on a greenhouse gas concentration at another sample point for a greenhouse gas concentration distribution of an object region calculated according to an embodiment of the present invention.
6 is an exemplary flowchart of a method for generating greenhouse gas distribution data according to an embodiment of the present invention.
7 is an exemplary flowchart for explaining a process of analyzing the spatial distribution of greenhouse gas concentrations according to an embodiment of the present invention.
FIG. 8 is an exemplary flowchart illustrating a process of calculating the greenhouse gas concentration at another point according to an embodiment of the present invention.
9 is an exemplary flow chart illustrating a process for calculating the greenhouse gas concentration of a zone in accordance with an embodiment of the present invention.
Other advantages and features of the present invention and methods of achieving them will become apparent with reference to the embodiments described below in detail with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. Is provided to fully convey the scope of the invention to those skilled in the art, and the invention is only defined by the scope of the claims.
Unless defined otherwise, all terms (including technical or scientific terms) used herein have the same meaning as commonly accepted by the generic art in the prior art to which this invention belongs. Terms defined by generic dictionaries may be interpreted to have the same meaning as in the related art and / or in the text of this application, and may be conceptualized or overly formalized, even if not expressly defined herein I will not.
The terminology used herein is for the purpose of illustrating embodiments and is not intended to be limiting of the present invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification. As used herein, the terms' comprise 'and / or various forms of use of the verb include, for example,' including, '' including, '' including, '' including, Steps, operations, and / or elements do not preclude the presence or addition of one or more other compositions, components, components, steps, operations, and / or components. The term 'and / or' as used herein refers to each of the listed configurations or various combinations thereof.
It should be noted that the terms such as '~', '~ period', '~ block', 'module', etc. used in the entire specification may mean a unit for processing at least one function or operation. For example, a hardware component, such as a software, FPGA, or ASIC. However, '~ part', '~ period', '~ block', '~ module' are not meant to be limited to software or hardware. Modules may be configured to be addressable storage media and may be configured to play one or more processors. ≪ RTI ID = 0.0 >
Thus, by way of example, the terms 'to', 'to', 'to block', 'to module' may refer to components such as software components, object oriented software components, class components and task components Microcode, circuitry, data, databases, data structures, tables, arrays, and the like, as well as components, Variables. The functions provided in the components and in the sections ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ' , '~', '~', '~', '~', And '~' modules with additional components.
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings attached hereto.
1 is an exemplary block diagram of an
1, the greenhouse gas distribution
The
In the process of generating greenhouse gas distribution data according to an embodiment of the present invention, the
Data or programs necessary for generating greenhouse gas distribution data according to an embodiment of the present invention may be stored in the
In addition, the greenhouse gas distribution data generated according to the embodiment of the present invention may be outputted through the
According to the embodiment of the present invention, the greenhouse gas concentration of the sample point used as the basic data for generating the greenhouse gas distribution data for the target area by the greenhouse gas distribution
The near-infrared satellite image is an image photographed by the satellite according to the intensity of the near-infrared rays radiated from the atmosphere. The greenhouse gas concentration of the sample point is obtained by filtering noise from the satellite image, The average concentration of carbon dioxide in the atmosphere.
FIG. 2 is an exemplary diagram showing a target region to which a greenhouse gas concentration distribution is to be determined, sample points in the target region, and a carbon dioxide concentration thereof according to an embodiment of the present invention.
According to the embodiment of the present invention, the near-infrared satellite image of the target area may include a satellite image photographed in the temperate zone of the northern hemisphere, and a satellite image photographed from March to June.
Northeast Asian regions such as Korea, Japan, and China belong to the temperate zone of the northern hemisphere, which is influenced by southeasterly wind in summer and northwesterly wind in winter. Therefore, this climate zone is relatively less influenced by seasonal winds in the spring and fall, and the tendency of greenhouse gases emitted from one point in the target area to move to other points decreases, but in autumn, the amount of greenhouse gas It may not be reflected in the image. Therefore, the embodiment of the present invention can utilize the satellite image photographed from March to June corresponding to spring.
The carbon dioxide concentration of the sample points (circles in the map) shown in FIG. 2 is XCO 2 (column-averaged) obtained from a GOSAT (Greenhouse gases Observing Satellite) satellite image taken from March to June of each year from 2009 to 2012 CO 2 concentration) data. Hereinafter, the process of calculating the carbon dioxide distribution data of the target region using the XCO 2 data will be described.
The
According to one embodiment, the spatial
Specifically, the
At this time, according to the embodiment of the present invention, the spatial
The lower limit value and the upper limit value of the effective concentration range may be set to a predetermined margin value before and after the actual measurement value. According to an embodiment, the effective concentration range may be set to either the lower limit value or the upper limit value.
As described above, the embodiment of the present invention can obtain more objective and reliable GHG data by reflecting not only the observation data obtained from the satellite image but also the actual data at the reference point in the calculation of the GHG distribution over a wide area.
Next, the
Here, the variogram is a measure for the similarity of data at a certain distance, and is calculated as an expected value of squaring the difference between data separated by a certain distance h as follows.
Here, 2 γ (h) is the variogram function, Z (·) is a greenhouse gas concentration of the sample points, h is the distance between the sample points.
According to the embodiment of the present invention, the
Also, according to the embodiment of the present invention, the
3 is an exemplary diagram illustrating a greenhouse gas concentration distribution of a target area calculated according to an embodiment of the present invention.
Referring to FIG. 3, a carbon dioxide concentration distribution over the entire target region can be obtained by estimating the carbon dioxide concentration at other points in the target region based on the carbon dioxide concentration at the sample point shown in FIG. In FIG. 3, the target region is divided into four carbon dioxide concentration ranges, but the number of classes used to represent the carbon dioxide distribution is not limited thereto.
According to the embodiment, the calculated greenhouse gas distribution data of the target area can be verified in comparison with the greenhouse gas concentration at another sample point.
4 is an exemplary diagram showing prediction error calculated based on the greenhouse gas concentration at another sample point for the greenhouse gas concentration distribution of the target area calculated according to an embodiment of the present invention.
According to this embodiment, the prediction error of the greenhouse gas concentration distribution can be obtained by calculating a Root Mean Square Prediction Error (RMSPE) for each of the other points.
Referring to FIG. 4, the greenhouse gas concentration distribution calculated as shown in FIG. 3 has a prediction error ranging from 0.001 to 2.9 ppm, and most of the target region shows a prediction error close to the minimum error value of 0.001 ppm.
The zone
According to one embodiment of the present invention, the zone
For example, when Kyushu of Japan is designated as the administrative area to be analyzed in the object area, the zone
1, the greenhouse gas distribution
5 is an exemplary diagram illustrating a greenhouse gas concentration distribution by administrative area in a subject area according to an embodiment of the present invention.
Referring to FIG. 5, the greenhouse gas distribution
In FIG. 5, the GHG concentrations in the respective administrative districts are classified into four grades, but the number of grades is not limited thereto.
The embodiments of the present invention described above enable more objective and reliable estimates of greenhouse gas emissions compared to conventional emission factor based greenhouse gas emissions. In addition, it is possible to consider the distribution over a wide area of the greenhouse gas, so that the regional distribution of the greenhouse gas (for example, the distribution by the administrative district) can be objectively compared, thereby providing reliable basic data for the carbon emission trading of each region.
6 is an exemplary flowchart of a
The greenhouse gas distribution
6, the greenhouse gas distribution
According to one embodiment of the present invention, the greenhouse gas concentration of the sample point may comprise an average concentration of atmospheric carbon dioxide in the sample point obtained from the near-infrared satellite image of the object area.
In this case, the near-infrared satellite image of the target area may include a satellite image photographed from March to June in the northern hemisphere temperate region.
FIG. 7 is an exemplary flowchart for explaining a process (S210) of analyzing the spatial distribution of greenhouse gas concentrations according to an embodiment of the present invention.
Referring to FIG. 7, analyzing the spatial distribution of the greenhouse gas concentration (S210) may include calculating a spatial variability of the greenhouse gas concentration according to the location of the sample point in the target region (S211) .
In this case, the step of analyzing the spatial distribution of the greenhouse gas concentration (S210) may include calculating the effective concentration range based on the measured value of the greenhouse gas concentration measured at the reference point in the target area, before the step (S211) (S201) of excluding a sample point at which the greenhouse gas concentration is out of the effective concentration range among the plurality of sample points (S202).
FIG. 8 is an exemplary flowchart illustrating a process (S220) of calculating a greenhouse gas concentration at another point according to an embodiment of the present invention.
Referring to FIG. 8, the step S220 of estimating the greenhouse gas concentration at the other point includes a step S221 of determining a weight for each sample point based on the variogram model corresponding to the calculated spatial variability, And calculating a greenhouse gas concentration at another point in accordance with the kriging algorithm corresponding to the calculated spatial variability based on the weight and the greenhouse gas concentration of the sample point (S222).
According to an embodiment of the present invention, the step of determining the weight (S221) may include a step of determining a weight for each sample point based on the spherical variogram model.
The step (S222) of calculating the greenhouse gas concentration at the other point may include calculating the greenhouse gas concentration at another point based on the weight and the greenhouse gas concentration at the sample point according to a general kriging algorithm have.
9 is an exemplary flowchart illustrating a process (S230) of calculating a greenhouse gas concentration of a zone according to an embodiment of the present invention.
Referring to FIG. 9, the step S230 of calculating the greenhouse gas concentration of the zone includes a step S231 of obtaining the boundary of the previously designated administrative zone from the map data of the target zone, (S232) calculating an average value of at least one greenhouse gas concentration among the points, and determining (S233) the average value as the greenhouse gas concentration of the administration area.
Referring to FIG. 1 again, the greenhouse gas distribution
The greenhouse gas distribution
While the present invention has been described with reference to the exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. Those skilled in the art will appreciate that various modifications may be made to the embodiments described above. The scope of the present invention is defined only by the interpretation of the appended claims.
10: Greenhouse gas distribution data generation device
110: input unit
120:
121: Spatial distribution analysis unit
122:
123: Zone concentration calculating section
124: Greenhouse gas distribution map generation unit
130:
140:
Claims (11)
A concentration estimator for estimating a greenhouse gas concentration at another point in the target region based on the spatial distribution; And
A zone concentration calculating unit for calculating a greenhouse gas concentration of the zone within the target zone based on at least one of the sample point and the other point;
And a greenhouse gas distribution data generation unit for generating greenhouse gas distribution data.
The greenhouse gas concentration at the sample point is:
And an average concentration of atmospheric carbon dioxide of the sample point obtained from the near-infrared satellite image of the target region.
The near-infrared satellite image of the target region is:
A greenhouse gas distribution data generator comprising a satellite image taken in March to June in the northern hemisphere temperate zone.
Wherein the spatial distribution analyzer comprises:
Wherein the spatial variability of the greenhouse gas concentration according to the position of the sample point in the target area is calculated.
Wherein the spatial distribution analyzer comprises:
Setting an effective concentration range based on an actual value of the greenhouse gas concentration measured at a reference point in the target area and calculating a sample point at which the greenhouse gas concentration out of the effective concentration range among the plurality of sample points is calculated from the calculation of the spatial variability A greenhouse gas distribution data generator for excluding greenhouse gases.
Wherein the concentration estimator comprises:
Determining a weight for each sample point based on a variogram model corresponding to the calculated spatial variability,
And calculates a greenhouse gas concentration of the other point according to a kriging algorithm corresponding to the calculated spatial variability based on the weight and the greenhouse gas concentration of the sample point.
Wherein the concentration estimator comprises:
Based on the spherical variogram model, weights are determined for each sample point,
And a greenhouse gas concentration data generator for calculating a greenhouse gas concentration at the other point according to a universal kriging algorithm based on the weight and the greenhouse gas concentration of the sample point.
Wherein the zone concentration calculating section comprises:
Obtaining a boundary of a predetermined designated area from the map data of the target area and calculating an average value of the greenhouse gas concentration of at least one of the sample point and the other point located in the boundary, The greenhouse gas distribution data generation device.
Further comprising a greenhouse gas distribution map generation unit for graphically representing an area surrounded by the boundary in the target area with a gradation to which the greenhouse gas concentration of the corresponding administrative zone belongs.
Estimating a greenhouse gas concentration at another point in the target area based on the spatial distribution; And
Calculating a greenhouse gas concentration of the zone within the subject area based on at least one of the sample point and the other point;
And generating the greenhouse gas distribution data.
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| KR1020150131112A KR101733026B1 (en) | 2015-09-16 | 2015-09-16 | Apparatus and method for generating greenhouse gas distribution data across administrative regions |
| PCT/KR2016/010218 WO2017048002A1 (en) | 2015-09-16 | 2016-09-09 | Apparatus and method for generating greenhouse gas distribution data on administrative district basis |
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| KR1020150131112A KR101733026B1 (en) | 2015-09-16 | 2015-09-16 | Apparatus and method for generating greenhouse gas distribution data across administrative regions |
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| US7440871B2 (en) * | 2002-12-09 | 2008-10-21 | Verisae, Inc. | Method and system for tracking and reporting emissions |
| KR20110017816A (en) * | 2009-08-14 | 2011-02-22 | 한국전자통신연구원 | System and method for monitoring greenhouse gas |
| KR20140002380A (en) * | 2012-06-29 | 2014-01-08 | 박재현 | Method, system and computer-readable recording media for providing information on greenhouse gas emission of building |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101998778B1 (en) * | 2018-01-03 | 2019-10-01 | 경북대학교 산학협력단 | Apparatus and method for generating greenhouse gas distribution data |
| KR20220009272A (en) * | 2020-07-15 | 2022-01-24 | 경북대학교 산학협력단 | Method for measuring carbon emission using roof image of aerial picture and system for measuring carbon emission |
| KR102351118B1 (en) * | 2021-04-02 | 2022-01-17 | 아주대학교산학협력단 | Method for evaluating the suitability for power generation using biogas, server and system using the same |
| US11519853B2 (en) | 2021-04-02 | 2022-12-06 | Ajou University Industry-Academic Cooperation Foundation | Method for evaluating the suitability for power generation using biogas, server and system using the same |
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| KR101733026B1 (en) | 2017-05-08 |
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