KR101653280B1 - Air Pollution Monitor Method - Google Patents

Abstract

A method for monitoring air pollution according to an embodiment of the present invention includes setting a target region as one or more sub-domains divided into grids, setting a measurement path of each sub-domain Measuring a degree of pollution of each of the lower domains along the measurement path; correcting the measured degree of pollution according to an urban background concentration and a weather condition at a measuring time; and a step of measuring the degree of pollution or a step of correcting the degree of pollution, And creating an air pollution map according to the measured pollution degree data or the corrected pollution degree data.

Description

{Air Pollution Monitor Method}

The present invention relates to a method for monitoring air pollution, and more particularly, to a method for monitoring air pollution capable of providing high-resolution and highly reliable air pollution information for a wide area.

Urban air pollutants include both gaseous substances such as nitrogen oxides and hydrocarbons, and particulate matter such as unburned carbon grains, which are emitted from automobiles, which are major pollutants in urban air, and are known to be very harmful to human body.

Particularly, the air pollution phenomena originating from automobiles are highly localized and characterized by local high concentration pollution (traffic hot spot). For this reason, it is important to grasp the distribution of urban air pollution and to manage the pollution degree of the high concentration pollution area with preference.

As a method of monitoring the air pollution degree, there is a method as disclosed in Patent Document 1 for observing air pollution degree in real time through an aircraft, and there is a method of marking each point as one point to indicate air pollution degree. Also, there is a method of predicting the air pollution degree through the meteorological data and the emission amount information for each pollutant source using the atmospheric modeling as in the non-patent document 1.

Since the above methods derive the air pollution level from only the data measured at a few sites, it is difficult to analyze the air pollution accurately. The reliability of estimations through atmospheric modeling, such as changes in emissions due to major pollutants such as automobiles and the effects of urban canyons, is greatly reduced, and verification of these is also very difficult.

Air pollution levels can show very different concentrations locally, and air pollution, especially measured in areas adjacent to roads, can be very high compared to the values measured in urban air pollution measuring stations. According to the conventional air pollution measurement method, the air pollution degree in the residential area and the city center may be different. Since the air pollution degree is derived by interpolating or extrapolating based on the data between the urban air pollution monitoring stations located several kilometers to several tens kilometers away, There is a problem that a large amount is generated.

In addition, since air pollutants are limited to PM ₁₀ , NO ₂ , CO, and SO ₂ , information on relatively sensitive air pollutants, which greatly affect the air pollution degree of the city, can not be visually displayed.

US 8560146 B2

3. Dispersion and Photochemical Oxidation of Gaseous Sulfur Compounds from Natural and Anthropogenic Causes around Coastal Areas. Korean Society for Atmospheric Environment Spring Conference, 2009.5, pp. 241-243.

It is an object of the present invention to provide an air pollution monitoring method capable of accurately monitoring urban air pollution at a high resolution in a city environment with many vehicles, will be.

Another object of the present invention is to provide an air pollution monitoring method which can be applied to a vehicle to be used as a mobile air pollution monitoring apparatus, and to realize a high-resolution detailed air pollution map based on actually measured data.

And it provides a visualization method of air pollution distribution at a glance at high resolution, and provides a method of monitoring air pollution which can be useful for various purposes in a space where effective air pollution control is required such as residential area, urban area, school district .

A method for monitoring air pollution according to an embodiment of the present invention includes the steps of setting a target region as one or more sub-domains divided into grids, setting a measurement path of each sub-domain, A step of correcting the measured degree of contamination according to an urban background concentration and a weather condition at the time of measurement and a step of measuring the degree of pollution or a step of correcting the degree of pollution, And creating an air pollution map.

Setting a peripheral point located in the target area before or after the step of setting the measurement path, and a common path setting step distributed over the entire target area,

Before or after the step of measuring the degree of contamination, it is possible to measure a weather condition or a pollution degree of a peripheral point of the target area and the common path.

(C _{bg (i)} ) at the time of measurement and the average urban background concentration (C _{bg ( avg )} ) within the measurement period from the weather condition or pollution degree data at the peripheral point of the target area,

Calculates a correction coefficient (x) of a power function (WS ^x ) of pollutant and wind speed from the gas phase state or pollution degree data of the common path,

The corrected contamination degree (C _c ) of the contamination degree (C _m ) measured according to the following formula 1 can be derived.

[식 1]

[Formula 1]

If the parameter indicative of the pollution, the particulate air _{pollutants, PM 10 (D p <10} μm) Concentration ^{(μg / m 3), PM} 2 .5 (D p <2.5 μm) Concentration (μg / m ^3), minimal tenant number concentration (particles / cm ^3), soot concentration (μg / m ^3), deposited in the alveoli available particle surface area density (μm ² / cm ³⁾ and particulate polycyclic one or more of the aromatic hydrocarbon concentration (ng / m ^3), and (Ppm), carbon dioxide concentration (ppm), nitrogen monoxide concentration (ppb), nitrogen dioxide concentration (ppb), sulfur dioxide concentration (ppb), ozone concentration (ppb) and hydrocarbon concentration (ppb) &Lt; / RTI &gt;

The step of preparing the air pollution map may calculate an air pollution map by inputting an average value, a standard deviation, and a number of measurement data of the measured or corrected pollution degree in the corresponding grid section.

The air pollution map can be calculated by displaying various colors according to the interval, such as the average value, the standard deviation, and the number of measurement data.

Setting the measurement path, setting a peripheral point located in the target area, or setting a common path distributed all over the target area includes: setting a spare path or a spare point according to basic map information; And setting the final path or the final point by modifying the preliminary path or the spare point according to the result measured according to the preliminary path or the preliminary point.

If the target area is an urban area, the surrounding area may be an urban air measuring area.

According to an embodiment of the present invention, it is possible to provide an air pollution monitoring method capable of accurately monitoring urban air pollution at a high resolution, particularly in an urban environment with many vehicles, for monitoring air pollution.

In addition, it can be used as a mobile air pollution monitoring device applied to a vehicle, and can provide an air pollution monitoring method capable of realizing high-resolution detailed air pollution map based on actually measured data.

And it provides a visualization method of air pollution distribution at a glance at high resolution, and provides a method of monitoring air pollution which can be useful for various purposes in a space where effective air pollution control is required such as residential area, urban area, school district can do.

1 is a flowchart schematically showing a method of monitoring air pollution according to a first embodiment of the present invention.
2 is a flowchart schematically showing a pollution degree correction method according to the first embodiment of the present invention.
3 is a flowchart schematically showing a method for monitoring air pollution according to a second embodiment of the present invention.
4 is a flowchart schematically showing a pollution degree correction method according to a second embodiment of the present invention.
FIG. 5 is a diagram illustrating a method of setting an object region and a sub-domain according to an embodiment of the present invention.
6 is a diagram illustrating a measurement path of a lower domain according to an embodiment of the present invention.
FIG. 7 is a flowchart illustrating an uncorrected contamination mapping process for one sub-domain according to an exemplary embodiment of the present invention. Referring to FIG.
8 is a diagram showing an uncorrected contamination map (a) and a corrected contamination map (b) of one sub-domain according to an embodiment of the present invention.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

1 is a flowchart schematically showing a method of monitoring air pollution according to a first embodiment of the present invention.

Referring to FIG. 1, an air pollution monitoring method according to a first embodiment of the present invention includes a domain setting step S10, a measurement path setting step S20, a pollution degree measuring step S30, a pollution degree correction step S50, And a map calculation step S60.

In the domain setting step (S10), a plurality of subdomains divided into a grid are set in the target area. To divide into sub-domains, information such as GPS (global positioning system) data of the target area is utilized.

In the measurement path setting step S20, a measurement path is set in each sub-domain. After a preliminary measurement is performed according to the set measurement path, the measurement path is corrected and supplemented to set up the measurement path over the interval of the lower domain.

In the pollution degree measurement step (S30), air pollution degree in each sub-domain is measured. In accordance with one embodiment of the present invention, in the case of particulate air _{pollutant, PM 10 (D p <10} μm) Concentration ^{(μg / m 3), PM} 2.5 (D p <2.5 μm) Concentration (μg / m ^3), minimal tenant number concentration (particles / cm ^3), soot concentration (μg / m ^3), possible deposits on alveolar particle surface area density (μm ² / cm ³⁾ and particulate polycyclic aromatic hydrocarbon concentration (ng / m ³⁾ at least one data of the . The concentration of carbon monoxide (ppm), carbon dioxide concentration (ppm), nitrogen monoxide concentration (ppb), nitrogen dioxide concentration (ppb), sulfur dioxide concentration (ppb), ozone concentration (ppb) &Lt; / RTI &gt;

But is not necessarily limited to, for example, various air pollutants that can be measured with a real-time measurement instrument having a time resolution of less than one minute.

The contamination degree measuring step S30 may measure the pollution degree using the portable device. For example, the pollution degree measuring step S30 measures a weather condition or a pollution degree of the measuring path or the measuring point.

According to one embodiment of the present invention, the data measured in the pollution degree measuring step S30 primarily processes data in consideration of GPS information, wind direction and wind speed information, response time of pollutant measuring equipment, and delay time.

The data measured in the pollution degree measuring step (S30) is used to create an uncorrected air pollution map in the contamination map calculating step (S60). In the domain setting step (S10), it is possible to divide into a grid form of the lower domains, and an air pollution map is created by inputting the average pollution degree, the standard deviation or the number of data for each lattice. In addition, the average pollution degree, standard deviation, or the number of data for each lattice are divided into sections and expressed in different colors according to each section, thereby expressing the air pollution degree visually on the map.

In the contamination degree correction step (S50), the pollution degree value is corrected. Generally, the range of the target area is wide, so in order to monitor the high-resolution air pollution, the pollution degree of the whole area should be measured over several days. In this case, however, since the sub-domains are measured on different days, that is, the measurement points of each domain are different, the contamination values must be corrected for accurate comparison with the other sub-domains. This is because the degree of contamination can be measured differently depending on the weather condition at the time of measurement, wind speed, and the like. The degree of pollution to be corrected here only considers the dilution effect of air pollution by wind speed.

In the pollution map calculation step (S60), an air pollution map corrected for each grid of the lower domains is prepared according to the corrected pollution degree value calculated by correcting the pollution degree.

2 is a flowchart schematically showing a pollution degree correction method according to the first embodiment of the present invention.

Referring to FIG. 2, the pollution degree correction method according to the first embodiment of the present invention includes a neighboring point setting step S110, a common path setting step S115, a measurement path setting step S120, a pollution degree measuring step S130, A contamination degree correction step (S150) and a contamination map calculation step (S160).

Check the urban background concentration of each pollutant by measurement of air pollution in the surrounding area (for example, the city air monitoring station in case the target area is the city) located in the target area. This is a very important factor in linking with the measured values of the urban air monitoring network. It is also a very important factor in clarifying the relationship between the ever-changing air pollutants and weather conditions.

Therefore, in the peripheral point setting step (S110) located in the target area, the measurement point is set around the target area, and the contamination degree of the corresponding point is measured in the pollution degree measuring step (S130).

The measurement points in the surrounding area should be a point where the influence of the surrounding vehicles can be minimized, and it can be set based on the aerial photographs of the map and the Internet, and can be supplemented by the preliminary measurement.

In the common route setting step (S115), it is intended to check the degree of pollution on the road in the main route covering the entire area of the target area. The influence on the air pollution concentration by the movement and diffusion of pollutants by the wind speed on the road is measured by the common path measurement. Due to the contamination measurement on the common path, the correction factor is compared with the known correction factor in the existing studies.

The common route can be selected based on the main road covering the entire area of the target area, and the route distance is set to a route that can complete the measurement within about 30 minutes. For example, it is possible to set a path that can measure the common route within 30 minutes at a speed of about 30 to 40 km / h in accordance with the traffic flow in the city center.

The common route can also be set using maps or aerial photographs, and can be supplemented by actual preliminary measurements.

The results of pollution measurements on the common path can be very useful when calibrating measurement data that deviates significantly from the overall tendency during the measurement period.

In the measurement path setting step S120, the path of the lower domain is set as described above. You can subdivide the subdomain into several grids and then partition the path to include the path corresponding to each grid.

The pollution degree measuring step S130 measures the pollution degree according to a point or a path set in a surrounding point setting step S110, a common path setting step S115 and a measurement path setting step S120.

In the contamination degree correction step (S150), the contamination degree measured in the lower domain is corrected. Specifically, the corrected degree of contamination is as follows.

Where C _c is the corrected contamination level, C _m is the measured contamination level, WS ^x is the power function of pollutant and wind speed, x is the correction factor, C _{bg (i)} is the urban background concentration at the time of measurement , And C _{bg ( avg )} is the average urban background concentration during the measurement period.

The measurement time and the mean urban background concentration of C _{bg (i)} and C _{bg ( avg )} are determined according to the degree of pollution measured in the surrounding area, and WS ^x is determined according to the relationship between pollution degree and wind speed in the set common route.

As corrected by the above method, the contamination levels of the measured sub-domains at different measurement times can be integrated and compared and contrasted. That is, the corrected contamination level can be input to the grid of each sub-domain to create a corrected contamination map.

And, it is possible to accurately compare and analyze the pollution degree of the lower domain measured at different measurement points through the corrected contamination map.

The high-resolution average air pollution degree of the area to be managed can be grasped at a glance through the air pollution monitoring method according to various embodiments of the present invention. In addition, since the pollution map can be visually expressed through the pollution mapping, it can be used effectively in a space requiring effective management such as a residential area, an inner city area, and a dense area.

In addition, it is possible to determine whether improvement of air pollution degree can be improved through periodic measurement, and it can be useful in various fields such as the cause of disease caused by air pollution.

In addition, more accurate data can be calculated compared with the conventional air pollution monitoring method through air pollution measurement or modeling through measurement at several points. As a result, accurate prediction and analysis of air pollution becomes possible.

3 is a flowchart showing an air pollution monitoring method according to a second embodiment of the present invention.

Referring to FIG. 3, in order to monitor air pollution, a target area is divided into one or more sub-domains divided into a grid, and a sub-domain of the target area is set (S10). First, an air pollution monitoring target area is selected, a sub domain is set using the GPS information on the map of the selected target area, and a grid for partitioning the lower domains is set.

Then, a measurement path of the sub-domains is set (S20). Set the measurement path through the grids in the sub-domain. Here, after the preliminary measurement is performed on the measurement path, the measurement path can be corrected and supplemented.

Once the measurement path is determined, the pollution degree of the lower domains is measured along the measurement path (S30). Then, using the pollution degree data values of the lower domains, the average pollution degree value of the grid is obtained and an uncorrected air pollution degree map is calculated (S61).

In general, since the area of the area for monitoring air pollution is wide, the concentration of the pollutant may vary depending on the weather condition every measurement day. Therefore, the pollution degree according to the weather condition should be corrected. The measured pollution degree is corrected according to the weather condition (S50).

Then, the corrected air pollution map is calculated in the same manner as the calculation method of the uncorrected air pollution map through the corrected pollution degree value (S63).

According to the above embodiment, the air pollution can be analyzed through the uncorrected air pollution map and the corrected air pollution map. However, the present invention is not necessarily limited to this, and it is possible to create and monitor only the corrected air pollution map without preparing the uncorrected air pollution map.

On the other hand, the pollution degree correction method according to the second embodiment of the present invention is shown in FIG.

Referring to FIG. 4, a neighboring point of a target area is set (S210), and a common path distributed over the target area is set (S220). The neighboring point setting and the common path setting may be set before or after setting the measuring path of Fig. 3 (S20).

Likewise, a preliminary measurement of a peripheral point or a common path can be made and corrected by correcting and supplementing a peripheral point or a common path.

The meteorological condition or the pollution degree can be measured along the peripheral point or the common path (S310, S320). The step S310 of measuring the weather condition and the pollution degree at the surrounding points and the step S320 of measuring the pollution degree on the common path can be performed before or after the step S30 of measuring the pollution degree of the lower domain. As an example, it is possible to obtain data that can be used to correct the concentration of contaminants that can be changed by the weather condition every day of measurement, before the pollution degree of the sub-domain is measured, and it can be directly applied to the measured lower domain contamination degree.

More specifically, the degree of contamination may vary depending on the urban background concentration, which may be determined by measuring the peripheral points of the target area to determine the background background concentration (C _{bg (i)} ) at the time of measurement The average urban background concentration (C _{bg ( avg )} ) can be calculated.

According to one embodiment, an urban meteorological station adjacent to the target area may be a peripheral point. As an example, the urban background concentration can be obtained using the data provided at the designated measuring station without measuring the degree of contamination.

Also, the pollution degree of the main road on the day where the air pollution degree can be greatly changed by the vehicle every day can be reflected through the measurement of the common path in the target area, and can be used to correct the pollution degree.

Through the measurement of the common path, the correction factor obtained on the urban main road can be compared with the known correction factor in the existing research. In addition, it is very important to judge the influence of air pollutant concentration due to the movement and diffusion of pollutants by the wind speed on actual roads. That is, the pollution degree (correction coefficient x) corrected through the following Equation 1 of the function (WS ^x ) of the power of the pollutant and wind speed on the actual road on the actual road can be calculated through the measurement of the common path (S50 ).

[식 1]

[Formula 1]

Through the measurement of the surrounding points and the common path, it is possible to correct the urban atmospheric background concentration and the air pollution level on the road, which can greatly increase or decrease the level of pollution due to daily changing weather conditions, especially wind speed. The corrected contamination level can then be used to generate a high-resolution contamination map.

5 (a) to 5 (d) are diagrams illustrating a method of setting a subdomain and a lattice in an object region according to an embodiment of the present invention.

FIG. 5 (a) shows an example of partitioning into 16 1 × 1 km sub-domains A to P in order to monitor air pollution in a target area of 4 × 4 km.

(B) shows a 1 × 1 km sub-domain divided by a grid of 0.5 × 0.5 km, and (c) and (d) show a grid of 0.5 × 0.5 km divided by a grid of 50 × 50 m FIG.

For example, the latitude and longitude information of the grid partitioned by using the GPS information is grasped, and the measurement path of the sub domain is set.

Actual measurements should be taken across all areas of the 4 x 4 km area. However, measuring the whole area in a day is very difficult in time. Therefore, the 16 sub-domains are planned to be the measurement target area of 1 day each, and the measurement (1 hour), the common path measurement (30 minutes) and the measurement on the measurement path of one sub- Time), so that a total of 16 days of measurement can be made.

FIG. 6 is a diagram illustrating a measurement path of a 1 × 1 km sub-domain according to an exemplary embodiment of the present invention.

As an example, air pollution monitoring devices can be mounted on mobile devices such as automobiles, and air pollution measurements can be made aiming at all possible paths that an air pollution monitoring device can enter. In order to increase the number of measurements in all possible paths, the measuring vehicle can measure the air pollution level through the measurement path at a speed of, for example, about 30 km / h or less. The measurement speed can be further increased or decreased, but in this case the data of the measurement points contained within the 50 x 50 m grid can be further reduced or increased.

Once this measurement is completed, the measured data can be processed and used to create an air pollution map.

FIG. 7 is a diagram illustrating an air pollution mapping process according to an exemplary embodiment of the present invention. Referring to FIG. Although the embodiment of FIG. 7 shows the uncorrected air pollution map generation process, it is not limited to this and can be used to create a corrected air pollution map.

FIG. 7A is a diagram showing that a 4 × 4 km target area is divided into 16 1 × 1 km sub-domains, FIG. 7B is a diagram showing a detailed map obtained through GPS information corresponding to the sub domain A, Fig. 7 (c) is a diagram showing the lower-level domain by dividing the 50 × 50 m grid into the average air pollution concentration.

More specifically, the contamination concentration can be expressed through information such as average air pollution concentration, standard deviation, and number of measurement data in the lattice space of 50 x 50 m.

The parameters of pollution degree measurement are PM ₁₀ ( D _p <10 μm) concentration (μg / m ³ ), PM _2.5 ( D _p <2.5 μm) concentration (μg / m ³ ) (particle / cm ³ ), soot concentration (μg / m ³ ), particle surface area concentration (μm ² / cm ³ ) that can be deposited on alveoli, and particulate polycyclic aromatic hydrocarbon concentration (ng / m ³ ) (Ppm), carbon dioxide concentration (ppm), nitrogen monoxide concentration (ppb), nitrogen dioxide concentration (ppb), sulfur dioxide concentration (ppb), ozone concentration (ppb) and hydrocarbon concentration (ppb) &Lt; / RTI &gt; Various air pollutants that can be measured with a real-time measuring instrument having a time resolution of less than one minute can be used as parameters for indicating air pollution degree.

The location information on the 50 × 50 m grid space can be generated as a grid file and the data input file can be generated by inputting the air pollution degree information corresponding to each grid space.

The air pollution degree values corresponding to the respective grids can be input and displayed on the basic map as shown in FIG. 7 (b), as shown in FIG. 7 (c). FIG. 7 is a numerical representation of the average concentration of nitrogen oxides in each lattice. However, the present invention is not limited thereto, and various parameters as described above may be applied thereto.

As shown in (d) of FIG. 7, the range of the degree of contamination can be divided into sections and expressed in color. FIG. 7 (e) shows the removal of the pollution level and the color representation. In FIG. 7F, the map of FIG. 7E is input to the corresponding sub-domain in the base map of the target area.

In this way, air pollution maps of the respective sub-domains can be created to grasp the air pollution degree (the nitrogen oxide pollution degree in the embodiment of FIG. 7) over the entire target area.

8 shows the uncorrected contamination map (a) and the corrected contamination map (b). Referring to FIG. 8, it can be seen that in the case of uncorrected contamination map (a), the difference between the detailed zones is large. However, this difference may be a substantial part, but it may be due to differences in weather conditions at the time of measurement. Clear analysis is difficult in this case.

In the case of the corrected contaminant map (b), it can be seen that the large changes between the detailed zones are reduced. Since it is corrected by reflecting the weather condition at the time of measurement, it can be seen that only the section in which the degree of contamination is clearly distinguished is clearly revealed.

In this way, an air pollution map can be created and the actual average concentration of each particulate and gaseous air pollutant can be visually and easily visualized. In addition, information such as the standard deviation of the air pollutants obtained in the lattice space and the number of measurement data can also be visually expressed. Accordingly, the management of the air pollution measurement data is facilitated, and the utilization can be increased.

Unlike the conventional method of measuring the air pollution degree different from the air pollution degree on the surface of the actual living space through the aircraft, the air pollution degree is measured on the surface of the actual living space, thereby providing more useful air pollution information.

In the case of the method of generating air pollution map using modeling, numerical simulation value is used instead of actual measurement value, so there is a problem that the accuracy is lowered. However, since the actual value is used in the present invention, . Also, it can be used as a method for verifying the modeling technique.

S10: Domain setup step
S20: Measurement path setting step
S30: Pollution degree measuring step
S50: Pollution degree correction step
S60: Pollution map calculation step
S61: Calculation of uncorrected contamination map
S63: Corrected contamination map calculation step
S110: Peripheral point setting step
S115: Common path setting step

Claims (8)

An air pollution monitoring device, comprising: setting an area of interest as one or more sub-domains separated by a grid;
The air pollution monitoring apparatus comprising: setting a measurement path of each sub-domain, a surrounding point located in the target area, and a common path distributed over the target area;
Wherein the air pollution monitoring device measures the pollution degree of each sub domain along the measurement path, the surrounding point of the target area, and the weather condition or pollution degree of the common path;
Correcting the pollution degree of the measured lower-level domain by reflecting the urban atmospheric background concentration and the on-the-road air pollution degree actually measured from the surrounding points of the target area and the common path; And
Wherein the air pollution monitoring device calculates an air pollution map according to the measured pollution degree data or the corrected pollution degree data after the step of measuring the pollution degree or the correction of the pollution degree.
delete The method according to claim 1,
The air pollution monitoring apparatus calculates an urban background concentration (C _{bg (i)} ) at the measurement time and an average urban background concentration (C _{bg (avg)} ) within the measurement period from the weather state or pollution degree data of the peripheral point of the target area and,
A correction coefficient (x) of a power function of contaminants and wind speed (WS ^x ) is calculated from the gas phase state or pollution degree data of the common path
(C _c ) of the pollution degree (C _m ) measured according to the following formula (1).

[Formula 1]
The method according to claim 1,
The parameter indicative of the degree of contamination is,
In the case of particulate air _{pollutant, PM 10 (D p <10} μm) Concentration ^{(μg / m 3), PM} 2.5 (D p <2.5 μm) Concentration (μg / m ^3), minimal tenant number concentration (particles / cm ³ ), A soot concentration (μg / m ³ ), a particle surface area concentration (μm ² / cm ³ ) that can be deposited on alveoli, and a particulate polycyclic aromatic hydrocarbon concentration (ng / m ³ )
In the case of gaseous air pollutants, the concentration of carbon monoxide (ppm), carbon dioxide concentration (ppm), nitrogen monoxide concentration (ppb), nitrogen dioxide concentration (ppb), sulfur dioxide concentration (ppb), ozone concentration (ppb) At least one of the atmospheric pollution monitoring method and the atmospheric pollution monitoring method.
The method according to claim 1,
The step of preparing the air pollution map includes:
Wherein the air pollution monitoring device calculates an air pollution map by inputting an average value, a standard deviation, or the number of measurement data of the measured or corrected pollution degree in the corresponding grid section.
6. The method of claim 5,
Wherein the air pollution monitoring device calculates an air pollution map by displaying the air pollution map in various colors according to the interval of the average value, the standard deviation, or the number of measurement data.
The method according to claim 1,
Setting a common path distributed over the measurement path, a surrounding point located in the target area, and the target area,
The air pollution monitoring apparatus comprising: setting a reserve path or a reserve point in accordance with basic map information; And
Wherein the air pollution monitoring apparatus includes a step of setting a final path or a final point by modifying a preliminary path or a preliminary point according to a result of measurement according to the preliminary path or the preliminary point.
8. The method of claim 1 or 7,
And if the target area is a city, the surrounding point is an urban air pollution monitoring station.

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