KR101967250B1 - System for detecting the large-scale transport of haze and method - Google Patents

Abstract

The present invention relates to a wide area mobile smoke detection system and a method thereof and, specifically, to a wide area mobile smoke detection system wherein in order to detect smoke, a meteorological satellite BTD boundary value range to which a ground PM10 and PM2.5 mass concentration are applied, is calculated, and a method thereof. The present invention calculates the meteorological satellite BTD boundary value range to which the ground PM10 and PM2.5 mass concentrations are applied, thereby being capable of accurately detecting the occurrence and movement of smoke in a wide area.

Description

BACKGROUND OF THE INVENTION Field of the Invention [0001] The present invention relates to a wide-

The present invention relates to a wide-area mobile fog detection system and method using meteorological satellite data, and more specifically, to detect a fogging range, a boundary value range in which the ground PM10 and PM2.5 mass concentrations are applied to the temperature difference of the satellite- And more particularly, to a wide area mobile mist detection system and a method thereof.

China's rapid economic growth and industrialization have resulted in increased use of fossil fuels, resulting in increased emissions of air pollutants. Recently, China consumes about 3 billion tons of fossil fuel every year. It burns 2774kt, 1842kt, and 994kt of TSP, PM10, and PM2.5, respectively, from the combustion of fossil fuels. The emission of these particulate pollutants is influenced by the atmospheric migration of syn -

Efforts are being made to develop ground observation networks and meteorological satellite observation methods to observe the yellow dust moving widely in the Yellow Sea region. Through the development and application of RGB synthetic image analysis, it is discriminating the wide range of moving air pollution such as dust and dust. Also, BTD (Brightness Temperature Difference) of 11μm and 12μm infrared channel corresponding to the window region of the atmosphere is used to discriminate volcanic ash and cloud distributed widely and is also used for detecting yellow dust.

The Korea Meteorological Administration applied the BTD method to the NOAA satellite Advanced High Resolution Radiometer (AVHRR) data to discriminate between yellow dust and cloud at a boundary value of -0.7 ° K. The Korea Meteorological Administration (KMA) has also applied the yellow sand detection method using BT1 of IR1 (11 μm) and IR2 (12 μm) infrared channels to Cheonanian weather satellite. The effects of BTD on surface temperature, release rate, satellite zenith angle, etc. should be considered. Therefore, the background threshold value (BTD, BTV) is calculated to compensate for the disadvantages of the BTD method using the difference between BTD and BTV.

However, in this method, it is difficult to distinguish between dust and haze, so that a technology capable of more clearly detecting the global movement of the haze is required.

Korean Patent Publication No. 10-2010-0011549 (published on Mar. 2, 2010)

It is an object of the present invention to provide a wide area mobile fog detection system and method which can accurately detect generation and movement of wide fog by clearly distinguishing fog from weather satellite data.

In order to achieve the above object, the present invention provides a method for detecting a wide range of mobile fogging, the method comprising: detecting a BTD (Brightness Temperature Difference) of a detection date; detecting a Background Threshold Value (BTV) a BTD calculation unit for calculating BTD based on the BTD of the detection date and BTD based on the BTV, and a BTD calculation unit for detecting a global mobile mist based on the BTD, PM2.5 mass concentration, and PM10 mass concentration, And a wide-area mobile fog detection unit.

Wherein the detection date BTD operation unit includes a detection date satellite data acquisition module for acquiring weather satellite data of the detection date, and a weather data acquisition module for determining whether the reflectance of the channel 1 (Ch1) is less than 25 (Ch5) to the channel 4 (Ch4) of the weather satellite data at the detection date from which the cloud pixel is removed when the reflectivity of the channel 1 (Ch1) is less than 25, And a detection date BTD computation module for computing BTD *.

The past BTV operation unit includes a past satellite data acquisition module for acquiring past weather satellite data, which is weather satellite data for the last 5 days including the detection date, a past cloud pixel removal module for removing the cloud pixels from the past weather satellite data, A channel 4 maximum brightness temperature acquisition module for comparing the past weather satellite data of the five days from which the cloud pixels have been removed to obtain a maximum brightness temperature of the channel 4 (Ch4) A channel 5 brightness temperature acquisition module for acquiring a channel 5 brightness temperature of the time at which the maximum brightness temperature of the channel 4 (Ch4) is acquired in the module, and a maximum brightness of the channel 4 (Ch4) obtained from the channel 4 maximum brightness temperature acquisition module And a past BTV computation module for computing the BTV by subtracting the channel 5 brightness temperature obtained in the channel 5 brightness temperature acquisition module at a temperature.

이다.The BTD computed in the BTD computation unit

to be.

When the BTD is not less than -0.1 DEG K and less than 0.6 DEG K in the daytime, -0.2 DEG K or more and 0.3 DEG K or less in the nighttime, and the PM2.5 / PM10 mass concentration ratio is 0.4 or more in the daytime, When the BTD is not more than -0.7 占 이며, the PM10 is not less than 190 占 퐂 m- ³ and the PM2.5 / PM10 mass concentration ratio is less than 0.4, it is determined that the case of yellow dust is observed.

Further, the present invention provides a method for detecting BTD (Brightness Temperature Difference) of a detection date to detect a wide-area mobile fogging (BTD) Computing BTD based on the BTD of the detection date and the BTV, computing BTD based on BTD, PM2.5 mass concentration and PM10 mass concentration, And detecting extraneous mobile mobile fog.

Computing a BTD (Brightness Temperature Difference) of a detection date for detecting a wide area mobile fog includes the steps of obtaining weather satellite data of the detection date by a detection day satellite data acquisition module, (Ch1) is less than 25 in order to remove cloud pixels from the current weather satellite data, and when the reflectance of the channel 1 (Ch1) is less than 25, The BTD computation module computes the detection date BTD (BTD *) by subtracting channel 5 (Ch5) from channel 4 (Ch4) of the weather satellite data of the detection date from which the cloud pixel has been removed.

The step of calculating the BTV (Background Threshold Value of BTD) of a certain past including the detection date may include calculating the past weather satellite data, which is the weather satellite data of the last 5 days including the detection date, A step of removing a cloud pixel from a past cloud pixel removal module in the past weather satellite data, comparing the past weather satellite data of the five days after the cloud pixel is removed, Obtaining a maximum brightness temperature of the channel (Ch4) by the channel 4 maximum brightness temperature acquisition module; obtaining a maximum brightness temperature of the channel 4 (Ch4) in the channel 4 maximum brightness temperature acquisition module, Obtaining a brightness temperature of the channel 5 at a maximum brightness temperature of the channel 4 (Ch4) obtained from the channel 4 maximum brightness temperature acquiring module; And the BTV computing module calculates the BTV by subtracting the channel 5 brightness temperature obtained from the module.

이다.The BTD calculated in the step of calculating the BTD of the detection date and the BTD operation unit BTD based on the BTV,

to be.

Wherein the BTD is -0.1 DEG K or more and 0.6 DEG K or less in the daytime and -0.2 DEG C in the nighttime based on the BTD, PM2.5 mass concentration, and PM10 mass concentration, Determining whether the BTD is less than or equal to -0.7 占 이며 and the PM10 is less than or equal to 190 占 퐂 or less; and when the PM2.5 / PM10 mass concentration ratio is 0.4 or more, ^-3 and the PM2.5 / PM10 mass concentration ratio is less than 0.4, it is judged that the global mobile mist detector is judged to be a dust case.

The present invention can accurately detect occurrence and movement of global fumes by calculating the boundary value range applying the ground PM10 and PM2.5 mass concentrations and applying it to the BTD.

1 is a conceptual diagram of a wide area mobile mist detection system according to the present invention;
Fig. 2 is a map showing the Pa-dori measuring station in Taean-gun, Chungcheongnam-do, and the measuring station in Cheongju-si, Chungbuk, where the wide-area mobile moving mist detection system according to the present invention is applied.
Figs. 3 to 7 are graphs of daily average concentration change of PM10 measured daily on the ground in Taean and Cheongju from 2011 to 2015. Fig.
8 to 10 are monthly PM10 and PM2.5 mass concentration fluctuation graphs in Taean and Cheongju during 2011 and 2015, respectively.
Figs. 11 and 12 are graphs showing anomalies of PM10 and PM2.5 monthly average mass concentrations in Taean and Cheongju during 2011-2015 except for the case of sandstorms.
FIG. 13 is a NOAA 19 satellite RGB composite image observed at 1322 LST on May 31, 2015. FIG.
FIG. 14 is a view of the image of FIG.
FIG. 15 is a graph showing the PM10 and PM2.5 mass concentrations and the altitude variation of the atmospheric boundary layer measured in the Cheongju River from May 30 to June 1, 2014.
Figs. 16 and 17 are diagrams for analyzing the isothermal backward trajectory reaching 100 m in Cheongju during the past three days from the NOAA satellite observation time of the case of dust case and the case of dust case.
Figure 18 is a BTD * distribution diagram for the Yellow Sea region in Figure 13;
FIG. 19 is a BTD * distribution diagram for the inland including Taean and Cheongju in FIG. 13; FIG.
Figures 20 and 21 are graphs comparing BTD and PM2.5 / PM10 mass ratios in the Cheongju area of NOAA 19 satellite measurement times for 2006 and 2015, respectively.
FIG. 22 shows the NOAA 19 meteorological satellite data of 1322 LST on 31 May 2014 BTD *.
FIG. 23 shows the NOAA 19 weather satellite data of 1322 LST on May 31, 2014.
FIG. 24 shows the BTD of NOAA 19 meteorological satellite data of 1322 LST on May 31,
Figure 25 shows BTD with PM10 and PM2.5 / PM10 applied on NOAA 19 meteorological satellite data of 1322 LST on May 31, 2014.
FIG. 26 shows the MODIS AOD. NOAA 19 weather satellite data of 1322 LST on 31 May 2014.
FIG. 27 shows the results of the OMI AI. NOAA 19 weather satellite data of 1322 LST on May 31,
FIG. 28 is an RGB composite image of 1255 LST NOAA 19 weather satellite data on February 3, 2011. FIG.
FIG. 29 shows the BTD of 1255 LST NOAA 19 weather satellite data on February 3, 2011;
Fig. 30 shows the MODIS AOD. Data of 1255 LST NOAA 19 weather satellite data on Feb. 3,
31 is a flowchart of a wide area mobile mist detection method according to the present invention.

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

It will be apparent to those skilled in the art that the present invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, It is provided to let you know. Like reference numerals refer to like elements throughout.

1 is a conceptual diagram of a wide area mobile mist detection system according to the present invention.

As shown in FIG. 1, the wide area mobile fog detection system according to the present invention includes a detection date BTD calculation unit 100 for calculating a detection date BTD, a past BTV calculation unit 100 for calculating a certain BTV including a detection date, A BTD operation unit 300 for calculating a BTD based on the BTD of the detection date and the past BTV, and a wide area mobile mist detection unit 400 for detecting a wide mobile fog based on the BTD.

The detection date BTD operation unit 100 calculates the BTD based on the weather satellite data on the day when it wants to detect the global mobile fog. Here, the present embodiment defines the BTD computed by the BTD computation unit 100 as a detection date BTD (BTD *). In addition, the detection date BTD calculation unit 100 includes a detection date satellite data acquisition module 110 for acquiring weather satellite data of a detection date, a detection day cloud pixel removal module 110 for determining the reflectance to remove the cloud pixels from the weather satellite data, (120), and a detection date BTD computation module (130) for computing the BTD of the detection date.

The detection date satellite data acquisition module 110 acquires the polar orbital weather satellite data on the day when it wants to detect the wide mobile fog. Polar orbit weather satellites can cover the entire surface of the earth with the rotation of the earth, while traversing the northern and southern polar orbits of the earth's north and south poles. This embodiment illustrates a US NOAA satellite as the polar orbit meteorological satellite, and the detection date satellite data acquisition module 110 acquires weather satellite data from the NOAA satellite. However, the present invention is not limited thereto, and the detection date satellite data acquisition module 110 may acquire satellite data from the TIROS satellite, the NIMBUS satellite, and the ESSA satellite in addition to the NOAA satellite. The acquired satellite data is composed of channel 1 (ch1) in a wavelength range of 0.58 to 0.68 탆, channel 2 (ch2) in a wavelength range of 0.725 to 1.10 탆, channel 3 (ch3) in a wavelength range of 3.55 to 3.93 탆, A channel 4 (ch4) in the 11.3 mu m area, and a channel 5 (ch5) in the wavelength 11.5 to 12.5 mu m area.

The detection date cloud pixel removal module 120 removes the cloud pixels from the weather satellite data obtained from the detection date satellite data acquisition module 110. To do this, the detection day cloud pixel removal module 120 removes cloud pixels through cloud detection using channel 1 (Ch1) of the weather satellite data. Specifically, the detection day cloud pixel removal module determines whether the reflectivity of channel 1 (Ch1) is less than 25 in the satellite data. When the reflectivity of the channel 1 (Ch1) is less than 25, the pixels having the reflectance lower than 25 are removed to remove the cloud pixels, and then the detection date BTD calculation module 130, which will be described later on the basis of the weather satellite data, And computes the detection date BTD.

The detection date BTD calculation module 130 calculates the detection date BTD based on the weather satellite data of the detection date obtained from the detection date satellite data acquisition module 110. Here, the calculation of the detection date BTD (BTD *) is performed by using channel 4 (Ch4) and channel 5 (Ch5) and removing channel 5 (Ch5) to channel 4 (Ch4) . At this time, if the reflectivity of the channel 1 (Ch1) is less than 25 in the above-described detection date and clouds pixel removal module 120, the channel 5 (Ch5) is added to the channel 4 (Ch4) And calculates the detection date BTD (BTD *). However, if there is no cloud pixel when the reflectivity of the channel 1 (Ch1) is 25 or more in the detection day cloud pixel removal module 120, the detection day satellite data acquisition module 110 acquires (BTD *) by subtracting channel 5 (Ch5) from channel 4 (Ch4) in the meteorological satellite data.

In the past, the BTV computing unit 200 finds clean pixels in the past satellite data and calculates a BTV (Background Threshold Value of BTD). That is, the past BTV operating unit 200 calculates the BTV based on the weather forecast satellite data within five days from the day when it wants to detect wide-area mobile fog. The BTV computing unit 200 includes a past satellite data acquisition module 210, a past cloud pixel removal module 220, a channel 4 maximum brightness temperature acquisition module 230, a channel 5 brightness temperature acquisition module 240, And a past BTV computation module 250.

The past satellite data acquisition module 210 acquires the latest 5-day polar orbital weather satellite data including the day on which to detect wide-area mobile fog. Here, the weather satellite data acquired by the past data acquisition module 210 is defined as a past satellite data.

The past cloud pixel removal module 220 removes cloud pixels from the past satellite data acquired by the past satellite data acquisition module 210. [ To this end, the past detection day cloud pixel removal module 120 utilizes channel 1 (Ch1) of satellite data to remove cloud pixels through cloud detection. That is, the past cloud pixel removal module 220 removes pixels having a reflectivity lower than 25 when the reflectance of the channel 1 (Ch1) is less than 25 in the past satellite data to remove the cloud pixels.

The channel 4 maximum brightness temperature acquisition module 230 acquires the maximum brightness temperature of channel 4 (Ch4) in the past satellite data from which the cloud pixels have been removed. This can be performed by acquiring the temperature at which the brightness of the channel 4 (Ch4) is the maximum at the same position and at the same time in the past satellite data of 5 days.

The channel 5 brightness temperature acquisition module 240 obtains the channel temperature of the channel 5 (Ch5) of the maximum brightness temperature pixel of the channel 4 (Ch4) obtained from the channel 4 maximum brightness temperature acquisition module 230, Obtain the brightness temperature.

The past BTV calculation module 250 calculates the brightness of the channel 4 obtained in the channel 4 maximum brightness temperature acquisition module 230 and the channel 4 acquired in the channel 5 brightness temperature acquisition module 240, 5 (Ch5).

The BTD calculation unit 300 calculates a BTD (Brightness Temperature Difference) based on the detection date BTD (BTD *) calculated in the BTD calculation unit 100 and the past BTV calculated in the past BTV calculation unit 200 . Here, the calculated BTD can be obtained by subtracting BTV from the detection date BTD (BTD *) as shown in Equation (3) below.

The wide-area mobile fog detection unit 400 detects the wide-area mobile fog based on the BTD calculated in the BTD operation unit 300 and the boundary value. The global mobile mist detecting unit 400 detects the BTD and the global mobile mist based on the PM2.5 / PM10 mass concentration ratio.

Table 1 is a reference table for distinguishing fog and dust in a wide-area mobile mist detection system according to the present invention.

division PM10 PM2.5 / PM10 BTD Fog example (ADC) - 0.4 or more Weekly -0.1 ˚K or more and 0.6 ˚K or less
Night -0.2 ˚ K or more and 0.3 ˚K or less Yellow Sand Case (NDC) 190 ㎍ m ^-3 or higher Less than 0.4 Day and night
-0.7 ˚K or less

Referring to Table 1, the broad-band mobile mist detector 400 has a PM2.5 / PM10 mass concentration ratio of 0.4 or more, a BTD of -0.1 占 K K to 0.6 占 K in the daytime and a -0.2 占 K O ˚K or less. When the PM10 is greater than 190 占 퐂 m < ^-3 > and the PM2.5 / PM10 mass concentration ratio is less than 0.4 and the BTD is less than -0.7 占 K, That is, the present invention determines the range of the BTD value by determining the case (the case of haze and the case of the dust case) corresponding to PM10 and PM2.5 range.

FIG. 2 is a map showing the Pa-dori measuring station of Taean-gun, Chungcheongnam-do, and the measuring station of Cheongju-si, Chungbuk, where the wide-area mobile moving mist detection system according to the present invention is applied. Figs. 3 to 7 are graphs of daily average concentration change of PM10 measured on the ground in Cheongju and Taean from 2011 to 2015. Fig.

The present invention utilizes PM10 and PM2.5 mass concentration data from observatories located in the western coastal area and the central inland rural area of central Korea for 2011 ~ 2015 to apply the wide area mobile mist detection system. 2, the Tae-ahn (36.74 ° N, 126.13 ° E) survey site located in the westernmost coast of central Korea is operated by the Ministry of Environment and is located in Cheongju, Cheongju, 36.58 ° N, 127.37 ° E) is operated by the Korea Atmospheric Environment Research Institute, a commissioned observatory of the Korea Meteorological Administration. The observation points in Taean and Cheongju are located at almost the same latitude and can measure the global movement of fog from the Yellow Sea to the central inland of Korea.

In Cheongju river, TSP and PM2.5 mass concentration are measured as well as PM10 mass concentration. In the Ministry of Environment, PM10 mass concentration as fine dust is defined as the atmospheric environment standard, and since 2015, PM2.5 mass concentration as super fine dust is applied as the atmospheric environment standard. In Taean, PM2.5 mass concentration was not measured and PM10 mass concentration was utilized. Although the Ministry of Environment sets the average concentration of PM10 at 100 μgm ^-3 as the atmospheric environment standard, it sets the daily average PM10 mass concentration of 81 μg ^-3 or more as 'bad level' in the fine dust forecasting class. Therefore, we analyzed the case of daily average PM10 mass concentration of 81 ㎍ m ^-3 or more measured in Taean and Cheongju in 2011 ~ 2015. Taean can measure the concentration of air pollutants flowing into Korea when widespread fog in eastern China spreads to Korea through the Yellow Sea. In addition, there are no large cities and industrial areas from Taean to Cheongju, 120km inland from the west.

Figs. 3 to 7 show the PM10 daily mean concentration and PM2.5 / PM10 mass concentration ratio variation measured in Taean and Cheongju in 2011-2015. 5 years PM10 mass concentration of Taean and Cheongju each ^{45.7 ± 11.3㎍m -3, 36.5 ± 8.1㎍m} -3, showing a higher level of concentration in eastern China near the Taean region. The correlation between daily average of PM10 measured in Taean and Cheongju was 0.67 ~ 0.81. The PM10 mass concentration daily fluctuations at two observation sites with low regional particulate emissions are largely influenced by the synoptic atmospheric transport. In the northern China and Mongolia deserts and reflectors, naturally occurring dusts in the dry dust have a relatively low PM2.5 mass concentration in total suspended dust, but the PM2.5 mass concentration is relatively high in anthropogenic air pollution due to fossil fuel combustion . Therefore, the fluctuation of the PM10 mass concentration and the PM2.5 / PM10 mass concentration ratio in Taean and Cheongju is reflected from the influence of yellow dust and fog which are different sources from the atmospheric transfer of the syngeneic scale from China.

In particular, in January 2013, the worst fog occurred in eastern China in 60 years, and in February 2014 there was a large fog. Therefore, PM10 is also increasing in January 2013 and February 2014 in South Korea's Taean and Cheongju. In addition, the yellow dust occurring in northern China and Mongolia causes a sudden increase in PM10 mass concentration due to synovial migration. Seasonally, PM10 mass concentration fluctuates in winter to spring.

8 to 10 are graphs of monthly PM10 and PM2.5 mass concentration fluctuations in Taean and Cheongju during 2011 and 2015, respectively.

8 and 9, the PM10 and PM2.5 mass concentrations are all high in winter to spring and fluctuate less in summer due to the influence of the North Pacific Ocean base. In the PM10 mass concentration except for the yellow dust case, high fluctuation from winter to spring indicates that the influx of fine dust from China is more than summer. The PM2.5 mass concentration is also high in winter to spring, but the influence of PM2.5 mass concentration by the dust is relatively small. In addition, PM2.5 / PM10 mass concentration ratio is lower than that in summer because PM10 mass concentration is high in spring and March ~ May. The reason why Taean's seasonal fluctuation is larger than that of Cheongju is because it is directly affected by air pollution emitted from China. Fig. 10 is a monthly variation of the day-average PM10 mass concentration of 81 占 m m ^-3 or more measured in Taean and Cheongju rivers. In winter and spring, case work has changed a great deal, and there are few cases in June and August. In particular, there are no cases in Cheongju due to the effects of the North Pacific high pressure and frequent rainfall in July ~ August, but cases are occurring in July in Taean, which is close to the source.

11 and 12 are anomalies for the PM10 and PM2.5 monthly average mass concentrations in the Taean and Cheongju rivers, except for the case of sandstorms, between 2011 and 2015.

11 and 12, the PM10 monthly average anomalies of Taean and Cheongju do not show seasonal fluctuations. The positive and negative anomaly monthly fluctuations indicate that the influence of fog due to long-distance movement is affecting the year-round. The PM10 and PM2.5 mass concentrations measured at Cheongju show negative anomaly averages for 2011 to 2012, but positive anomalies are shown for 2013 to 2015. In particular, in January 2013 and February 2014, not only the PM10 measured in Cheongju but also the PM2.5 mass concentration showed a high amount of anomalies due to the wide and continuous fog occurring in China.

FIG. 13 is a NOAA 19 satellite RGB composite image observed at 1322 LST on May 31, 2015, and FIG. 14 is an image obtained by removing a cloud pixel from the image of FIG. Fig. 15 is a graph showing the PM10 and PM2.5 mass concentrations and the altitude variation of the atmospheric boundary layer measured in the Cheongju River from May 30 to June 1, 2014. In Figure 13, the red box (a) is (36 ° -37 ° N, 124.5 ° -126.0 ° E) and (b) is (36 ° -37 ° N, 126.0 ° -127.5 ° E).

Referring to FIG. 13, it was observed that the influence of global fogging was spreading from north to south-east of the Sanjudi Peninsula of East China across the Yellow Sea to the central part of Korea. Also, Fig. 14 shows a cloud image, which is an image excluding cloud pixels, and there is no cloud pixel on the Korean peninsula.

Referring to Figure 15, the altitude of the atmospheric boundary layer was calculated at NOAA Air Resources Laboratory. 31st day under the influence of a broad-based mobile haze compared to 30 and May, PM10, an average mass concentration of PM2.5 was increased in each 96㎍m ^-3, 46 ㎍m ^-3. In particular, May 31 days Maximum PM10, PM2.5 mass concentration was 154㎍m ^{-3, -3} 73㎍m each 1600 LST. On May 31, the altitude of the atmospheric boundary layer increased to 1463 m at 1500 LST, and the global mobility increases the surface mass concentration by vertical mixing at the surface ~ 1460 m height range. The 1400 LST at which the NOAA 19 satellite was observed had a PM10 mass concentration of 121 m m ^-3 . On June 1, PM10 and PM2.5 mass concentrations were decreasing.

We selected a case where both the daily average of PM10 mass concentration and the time average of NOAA satellite observation time are more than 81 ㎍ m ^-3 in Taean and Cheongju during 2011 ~ 2015 and two points are not removed as cloud pixels. Except for the case where the cloud is affected at two points on the same day. In addition, when the yellow dusts in northern China and Mongolia arrived in Taean and Cheongju, the cases of PM10 mass concentration of 190 ㎍ m ^-3 were selected.

Figs. 16 and 17 are diagrams showing an isothermal backward trajectory analysis for reaching 100 m in the Cheongju River during the past three days from the NOAA satellite observation time of the case of dust case and the case of dust case.

Table 2 summarizes the daily average of the PM10 mass concentrations and the time-averaged NOAA satellite observations for the selected days in Taean and Cheongju.

Dust Pollution type Case Nr. Date Tae-ahn Gang-nae PM10
(M m ^-3 day ^-1 ) PM10
(M m ^-3 hr ^-1 ) PM10
(M m ^-3 day ^-1 ) PM10
(M m ^-3 hr ^-1 ) Fog example
(ADC) One 2011-02-03 108 115 87 98 2 2011-02-04 166 193 106 132 3 2011-02-05 145 129 91 82 4 2011-02-06 131 109 - - 5 2011-02-07 - - 93 84 6 2011-02-08 110 123 - - 7 2012-01-09 - - 84 95 8 2012-01-18 - - 104 126 9 2012-03-28 - - 83 104 10 2012-04-09 - - 94 97 11 2013-01-13 - - 128 133 12 2013-03-07 102 107 95 85 13 2013-04-04 91 83 104 113 14 2013-05-12 - - 91 88 15 2014-01-17 147 172 102 110 16 2014-02-22 80 95 85 91 17 2014-02-24 147 145 113 110 18 2014-02-25 125 88 125 105 19 2014-02-26 178 202 - 20 2014-05-31 91 107 96 121 21 2015-06-13 88 103 82 118 Average 122 127 98 105 Yellow sandstones
(NDC) One 2011-05-01 255 354 204 308 2 2015-02-22 279 203 - - 3 2015-02-23 - - 361 331 4 2015-03-22 203 279 - - Average 246 279 283 320

PM10 mass concentration is lower than that of sandstorms and PM10 mass concentration in Taean, which is close to China emission source, is higher than that in Cheongju. The cases of Hwangsu have exceeded the atmospheric environment standard (100 ㎍ m ^-3 day ^-1 ) both in Taean and Cheongju. However, 71% in Taean and 39% in Cheongju exceed the atmospheric environmental standards. 16 and 17, unlike the yellow dust occurring in Mongolia in northern China, fogging occurs in the eastern part of China. Also, the case of fogging is moving from Korea to the South, across the Yellow Sea at a slower pace than the yellow dust.

FIG. 18 is a BTD * distribution diagram for the Yellow Sea region in FIG. 13, and FIG. 19 is a BTD * distribution diagram for the inland including Taean and Cheongju in FIG. 20 and 21 are graphs comparing BTD and PM2.5 / PM10 mass ratio in Taean of NOAA 19 satellite measurement time with respect to the day of fire detection and inside Cheongju.

The dust mainly consists of particles with a particle size of 2.5 μm or more, but artificially generated fog mainly consists of particles with a particle size of less than 2.5 μm. Therefore, in the BTD analysis of Chollian satellite, the particle is set to -0.5 ° K as the boundary value of the large yellow sand detection. Fume and general atmospheres with smaller particle size than yellow dust particles are observed at BTD above -0.5 ° K. Referring to FIGS. 18 and 19, BTD * is distributed over 0 ° K mostly over the ocean and inland. Therefore, to detect the distribution of atmospheric fumes using NOAA satellite BTD, the boundary value range of BTD should be calculated. The case study of Table 2 was selected to select the range of NOAA satellite BTD boundary value using the ground PM10 mass concentration for large-scale fog movement from China. Referring to FIGS. 20 and 21, BTD is distributed in a range of -0.4 to 1.5 ° K in the daytime and -0.6 to 1.2 ° K in the nighttime. However, the PM2.5 / PM10 mass concentration ratio is higher than 0.4 because of the composition ratio of PM2.5 mass concentration, and BTD is mainly -0.1 ~ 0.6 ° K (25 ~ 75%) in the daytime and -0.2 ~ It is distributed in 0.3 ° K (25 ~ 75%). Therefore, by applying the PM2.5 / PM10 mass concentration ratio in the fog example, the smoke BTD range is calculated as -0.1 to 0.6 ° K (25 to 75%) in the daytime and -0.2 to 0.3 ° K (25 to 75% can do.

However, in Figures 20 and 21, the BTD of the dust samples of 190 占 m m ^-3 or more is distributed in an average of? 0.7 ㅀ K or less. The PM2.5 / PM10 mass concentration ratio is smaller than 0.4 and the BTD is smaller than -0.7 ° K. The Korea Meteorological Administration does not apply BTV to NOAA satellite BTD, but it sets a boundary value of -0.7 ° K for yellow dust detection. In this study, the boundary value for the detection of yellow dust can be estimated to be -0.7 ° K when the PM10 and PM2.5 / PM10 mass concentration ratios are applied.

22 is BTD * of NOAA 19 weather satellite data of 1322 LST on May 31, 2014, and FIG. 23 is BTV of NOAA 19 weather satellite data of 1322 LST on May 31, 2014. 24 is BTD of NOAA 19 meteorological satellite data of 1322 LST on May 31, 2014, and FIG. 25 is BTD of NOAA 19 meteorological satellite data of NOAA 19 meteorological satellite data of 1322 LST on May 31, 2014, with PM10 and PM2.5 / to be. 26 is a MODIS AOD of NOAA 19 weather satellite data of 1322 LST on May 31, 2014, and FIG. 27 is an OMI AI of NOAA 19 weather satellite data of 1322 LST on May 31, 2014.

Referring to Figs. 22 to 27, on May 31, Yumu from the Sanjibang Peninsula of China is crossing the Yellow Sea to the west of the central part of Korea. Figures 24 and 25 are consistent with the aerosol distribution of MODIS AOD and OMI AI. In particular, the distribution of haze in the northern Manchurian region of the Korean peninsula is also present. However, in FIG. 24, an area smaller than -0.5 DEG K is overlaid on the Korean inland and the Sea of Japan, but this part is improved in FIG.

Fig. 28 is an RGB composite image of 1255 LST NOAA 19 weather satellite data on February 3, 2011, and Fig. 29 is BTD of 1255 LST NOAA 19 weather satellite data on Feb. 3, 2011. Fig. 3 days 1255 LST MODIS AOD of NOAA 19 weather satellite data.

Referring to FIG. 28 to FIG. 30, in the RGB composite image, global fogging on the Yellow Sea flows into the central part of Korea. Average PM10 mass concentration was measured in Taean rice wine and intravitreal were respectively 108㎍m ^-3, 87㎍m ^-3. To 19 each NOAA 115㎍m ^-3, 98㎍m ^-3 in rice wine and has Taean cavity satellite observation time indicates a higher concentration in Taean. In BTD, fog is widely distributed not only in the Yellow Sea but also in the central inland of Korea, the East Sea, and the South Sea. MODIS AOD also shows high aerosol distribution from the Sanjudi Peninsula of China to the Yellow Sea and the central part of Korea. In the East Sea and the South Sea, the distribution of aerosols coinciding with BTD is low.

As a result, the concentrations of PM10 and PM2.5 measured at Taean metrology center on the western coast of central central part of Korea and in the Cheongju area of the central rural area during the period from 2011 to 2015, mass concentrations have shown a higher level of concentration in each 45.7 ± 11.3㎍m to ^-3, 36.5 ± 8.1㎍m ^-3, China Taean close to the eastern region. The correlation between daily average of PM10 measured in Taean and Cheongju was 0.67 ~ 0.81. The PM10 mass concentration daily fluctuations at two observation sites with low regional particulate emissions reflected the effects of synovial atmospheric transport.

The concentration of PM10 mass in the Taean and Cheongju rivers, except for the case of DSS, is high in winter and spring, indicating that the amount of fine dust from China is higher than in summer. The PM2.5 mass concentration was also high in winter to spring, but the effect of PM2.5 mass concentration by the dust was relatively small. We analyzed the monthly fluctuation of the case day with a daily average PM10 mass concentration of 81 ㎍ m ^-3 or more, which is defined as the 'bad level' in the Taean and Cheongju rivers. There were many cases of work in winter and spring, and few cases in June and August. In particular, there were no cases in Cheongju due to the effects of the North Pacific high pressure and frequent precipitation in July ~ August, but cases occurred in July in Taean near the source.

In order to observe the movement of fog in the eastern part of China, boundary value range of PM2.5 / PM10 applied to NOAA satellite infrared BTD method was calculated. The PM2.5 / PM10 measured on the ground was applied to the BTD method used for the detection of Chollian satellite DSS. PM10 mass concentration in fog example was not higher than 200 ㎍ m ^-3 , but BTD was mainly distributed in the range of -0.4 ˚ K to 1.5 ˚ K during the day and -0.6 ˚ K to 1.2 ˚ K at night there was. PM2.5 / PM10 mass concentration ratio is more than 0.4 and BTD is mainly -0.1 ~ K ~ 0.6 ~ K (25 ~ 75%) in the daytime because the composition ratio of PM2.5 mass concentration below 2.5μm particle size is high. , And -0.2˚K to 0.3˚K (25 to 75%) at night. Therefore, the BTD of the fogging case ranges from -0.1˚K to 0.6˚K (25 to 75%) during the day and from -0.2˚K to 0.3˚K (25 to 75%) at night to the BTD boundary value range . Also, the BTD of sandstones with a PM10 mass concentration of 190 m m ^-3 hr ^-1 or more showed a range of less than -0.7 ˚ K. In addition, PM2.5 / PM10 mass concentration ratio of sandstorm cases was lower than 0.4, and BTD was lower than -0.7˚K. Therefore, the BTD boundary value for the detection of yellow dust was set to -0.7˚K.

As described above, the present invention compares the image with the BTD boundary value range, the RGB composite image, the MODIS AOD, and the OMI AI image for the haze case. As a result, the range of BTD distributions for the occurrence and migration of global fog in Eastern China was consistent with the high value range of AOD and AI. Also, in the RGB composite image, it is difficult to discriminate the haze on the continent, but the BTD of the present invention is clearly distinguished.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A wide area mobile fog detection method according to the present invention will be described with reference to the drawings. The overlapping description with the description of the wide area mobile mist detection system according to the present invention described above will be omitted or briefly explained.

31 is a flowchart of a wide area mobile mist detection method according to the present invention.

As shown in FIG. 31, the wide-area mobile moving fire detection method according to the present invention includes a step S1 of calculating a detection date BTD, a step S2 calculating a past BTV, a step S3 calculating a BTD, And detecting (S4-1, S4-2) a wide mobile fog by applying PM2.5 and PM10.

The step S1 of computing the detection date BTD computes the BTD based on the weather satellite data of the detection date, which is the date on which the detection BTD operation unit desires to detect the global mobile fog. The step S1 of calculating the detection date BTD includes a step S1-1 of obtaining weather satellite data of a detection date, a step S1-2 of removing cloud pixels by determining the reflectivity of the channel 1, Lt; RTI ID = 0.0 > (S1-3) < / RTI >

Step S1-1 of acquiring the weather satellite data of the detection date acquires the polar orbital weather satellite data on the day when the detection date satellite data acquisition module desires to detect the global mobile mist.

In step S1-2, the cloud pixel removal module removes the cloud pixels from the detection day weather satellite data acquired in the step S1-1 of acquiring the weather satellite data of the detection date. This can be done using channel 1 (Ch1) of the weather satellite data.

 It is judged whether the reflectivity of channel 1 (Ch1) is less than 25 in detection weather satellite data. In addition, pixels having a reflectance lower than 25 are removed to remove the cloud pixels.

The step S1-3 of calculating the detection date BTD is based on the detection day weather satellite data in which the cloud pixels are removed when the reflectivity of the channel 1 (Ch1) is less than 25 in the step S1-2 of removing the cloud pixels, The detection date BTD calculation module calculates the detection date BTD (BTD *), which is shown in Equation (1).

In the step S2 of calculating the past BTV, the BTV calculation unit finds clean pixels in the past satellite data and calculates BTV. To this end, the step S2 of calculating the past BTV includes obtaining the past weather satellite data S2-1, removing the past cloud pixels S2-2, obtaining the maximum brightness temperature of the channel 4 A step S2-3, a step S2-4 of obtaining the brightness temperature of the channel 5, and a step S2-4 of calculating the BTD.

In the step S2-1 of obtaining the past weather satellite data, the latest 5 day extreme-orbit weather satellite data including the date when the past data acquisition module desires to detect the wide-area mobile fog obtains the past satellite data.

In the step S2-2 of removing the past cloud pixels, when the reflectance of the channel 1 (Ch1) is less than 25 in the past satellite data, the past cloud pixel removal module removes pixels having a reflectance lower than 25 in the past satellite data, Remove.

The step S2-3 of acquiring the maximum brightness temperature of the channel 4 acquires the maximum brightness temperature of the channel 4 (Ch4) from the channel 4 maximum brightness temperature acquisition module in the past satellite data from which the cloud pixels have been removed. This can be achieved by obtaining the temperature at which the brightness of the channel 4 (Ch4) is the maximum at the same position in the same time among the past satellite data of 5 days in the channel 4 maximum brightness temperature acquisition module.

The step S2-4 of obtaining the brightness temperature of the channel 5 is a step of obtaining the maximum brightness temperature of the channel 4 (Ch4) in the step S2-3 of obtaining the maximum brightness temperature of the channel 4, The brightness temperature of channel 5 (Ch5) is acquired by the channel 5 brightness temperature acquisition module in the past satellite data of the channel 5 (Ch5).

In step S2-4, the BTV computing module obtains the maximum brightness temperature of the channel 4. In the step S2-3, the maximum brightness temperature is obtained from the channel 4 (Ch4) and the brightness temperature of the channel 5 In step S2-4, BTD is calculated based on the channel 5 (Ch5) in which the brightness temperature is obtained.

The step of calculating the BTD (S3) calculates the BTD based on the detection date BTD (BTD *) calculated in the BTD calculation unit on the detection date and the past BTV calculated in the past BTV calculation unit.

The steps S4-1 and S4-2 of detecting the mobile fog by applying PM2.5 and PM10 are performed by using the BTD calculated in the step S3 of calculating BTD and the mass concentration ratios of PM2.5 and PM10 The global mobile mist detection part detects the wide mobile fog. In this case, the wide-area moving fog detection unit judges that the PM2.5 / PM10 mass concentration ratio is 0.4 or more and that the BTD is less than -0.1 DEG K and 0.6 DEG K in the daytime and -0.2 DEG K or more and 0.3 DEG K or less in the nighttime do. When the PM10 is greater than 190 占 퐂 m < ^-3 > and the PM2.5 / PM10 mass concentration ratio is less than 0.4 and the BTD is less than -0.7 占 K,

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the present invention as defined by the appended claims. You will understand.

100: Detection date BTD calculation unit 110: Detection date satellite data acquisition module
120: detection date cloud pixel removal module
130: Detection date BTD calculation module 200: Past BTV calculation unit
210: past satellite data acquisition module 220: past cloud pixel removal module
230: Channel 4 maximum brightness temperature acquisition module
240: Channel 5 brightness temperature acquisition module 250: Past BTV calculation module
300: BTD arithmetic unit 400: Wide area mobile mist detector

Claims (10)

(1) for acquiring weather satellite data of a detection date for detecting a wide-area mobile fog when the reflectance of channel 1 (Ch1) is less than 25 to remove cloud pixels from the weather satellite data of the detection date A detection day cloud pixel removal module for removing a pixel having a reflectance lower than 25 as a cloud pixel and a detection date cloud pixel removal module for removing a cloud pixel from the detection date weather satellite data, And a BTD calculation module for calculating a detection date BTD (BTD *) by subtracting the detection date BTD (BTD *) from the detection date BTD (BTD *), thereby calculating a BTD (Brightness Temperature Difference)
A past satellite data acquisition module for acquiring past meteorological satellite data, which is a meteorological satellite data of recent past predetermined days including the detection date, and a past satellite meteorological satellite module, A past cloud pixel removal module for removing the cloud pixels by removing the cloud pixels, and comparing the past weather satellite data of recent past including the detection date of the cloud pixels to the maximum value of the channel 4 (Ch4) A channel 4 maximum brightness temperature acquisition module for acquiring the brightness temperature, a channel 5 brightness temperature of the time when the maximum brightness temperature of the channel 4 (Ch4) is acquired in the channel 4 maximum brightness temperature acquisition module, A channel 5 brightness temperature acquisition module that acquires a channel 5 maximum brightness temperature acquisition module and a channel 5 maximum brightness temperature acquisition module, And a past BTV computation module for computing the BTV by subtracting the channel 5 brightness temperature obtained from the channel 5 brightness temperature acquisition module at the maximum brightness temperature of channel 4 (Ch4) A past BTV calculation unit for calculating a past BTV (Background Threshold Value of BTD)
A BTD operation unit for calculating BTD based on the BTD of the detection date and the BTV,
And a wide area mobile fog detecting unit for detecting a wide area mobile fog based on the BTD, PM2.5 mass concentration, and PM10 mass concentration. delete delete The method according to claim 1,
The BTD, which is calculated in the BTD calculation unit,

A wide area mobile fog detection system. 5. The method of claim 4,
The wide-area mobile moving mist detecting unit detects,
When the BTD is less than -0.1 DEG K and less than 0.6 DEG K during the day and less than -0.2 DEG K and less than 0.3 DEGK in the nighttime and the PM2.5 / PM10 mass concentration ratio is 0.4 or more,
Wherein the BTD is less than -0.7 占 이며, the PM10 is greater than 190 占 퐂 m- ^3, and the PM2.5 / PM10 mass concentration ratio is less than 0.4. The method of claim 1, further comprising the steps of: acquiring a weather satellite data of a detection day to detect a wide-area mobile misting; acquiring a weather satellite data acquisition module of the detection date; , Removing the cloud pixels by removing pixels having a reflectivity of less than 25, and removing channel 5 (Ch5) from channel 4 (Ch4) of the weather satellite data of the detection date from which the cloud pixels have been removed Calculating a BTD of a detection date including calculating a detection date BTD (Brightness Temperature Difference, BTD *);
Wherein the past satellite data acquisition module acquires the past weather satellite data, which is the weather satellite data of the past predetermined day including the detection date, and the step of obtaining the past weather satellite data when the reflectance of the channel 1 (Ch1) Of the past cloud weather data including the detection date from which the cloud pixel has been removed is compared with the past weather satellite data of the past past one day, The maximum brightness temperature of the channel 4 (Ch4) is obtained from the channel 4 maximum brightness temperature acquisition module, the maximum brightness temperature of the channel 4 (Ch4) is obtained from the channel 4 maximum brightness temperature acquisition module, (4) obtained at the channel 4 maximum brightness temperature acquiring module, and the maximum brightness temperature of the channel 4 Computing a BTV of a certain past including a step of calculating a BTV (Background Threshold Value of BTD) by subtracting the channel 5 brightness temperature obtained in the base temperature acquisition module;
Calculating a BTD operation unit BTD based on the BTD of the detection date and the BTV, and
And detecting a global mobile fog based on the BTD, PM2.5 mass concentration, and PM10 mass concentration. delete delete The method according to claim 6,
The BTD calculated in the step of calculating the BTD of the detection date and the BTD operation unit BTD based on the BTV,

A method for detecting a wide range of mobile moving fog. 10. The method of claim 9,
The step of detecting a global mobile fog based on BTD, PM2.5 mass concentration and PM10 mass concentration,
When BTD is less than -0.1˚K and less than 0.6˚K during the daytime, -0.2˚C to 0.3˚K at nighttime, and the PM2.5 / PM10 mass concentration ratio is more than 0.4, , ≪ / RTI &
Wherein the BTD is -0.7 占 이하 or less, the PM10 is 190 占 퐂 m- ³ or more, and the PM2.5 / PM10 mass concentration ratio is less than 0.4, the wide- Detection method.

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