A new method for atmospheric dust source tracing based on dust activity state constraints

Abstract

The present invention proposes a method for tracing the source of atmospheric dust based on the constraint of dust activity state. Belonging to the field of atmospheric environment, the method first collects the vertical aerosol type profile data obtained from the observation data, and selects dust samples in the atmosphere. Then, the atmospheric dust source tracing algorithm is used to trace the dust samples by judging the dust activity state. Specifically, the backward trajectory of the 168-hour air mass of each dust grid sample is tracked. When the air mass passes through a desert cluster, the height of the air mass is lower than the top height of the dust layer of the desert cluster. At the same time, the dust emission rate of the desert cluster and the dust column mass density of the air mass at this time exceed the threshold. It is considered that the desert cluster has a high potential to contribute to dust. This method provides a new perspective and tool for the study of external sources of dust in the regional atmosphere.

Description

Technical Field

[0001] The invention belongs to the field of atmospheric environment, and more specifically relates to a method for tracing the source of atmospheric dust in a study area based on the constraints of dust activity status. Background Art

[0002] Dust aerosol is one of the most important components of atmospheric aerosols. It mainly originates from wind erosion in arid and semi-arid areas and the Gobi Desert area with severe desertification. It can change the energy balance and water cycle of the atmospheric system through direct and indirect aerosol effects. As the main component of tropospheric aerosols, dust aerosols have a very important impact on the energy budget system of the entire earth system, as well as the ecological cycle and water cycle. The changes in the physical and chemical properties of aerosols during long-distance transport are considered to be one of the important pathways of the global biogeochemical cycle. Therefore, long-distance transport of dust is an important link in studying the impact of dust aerosols on the global atmospheric environment and climate change, and has important reference value for understanding the biogeochemical balance between the atmosphere, biosphere, hydrosphere and human sphere.

[0003] However, the current understanding of the external sources of dust in the atmosphere is still very limited. Most previous studies have used air mass backward trajectory models to indirectly infer the sources of dust. However, these methods ignore the fact that backward trajectories only simulate the movement of air masses and cannot reflect whether the air masses have the potential to carry dust, so there are certain errors and uncertainties. Therefore, new methods for studying the external sources of dust in the atmosphere and tracing the source analysis are of great significance for further studying and understanding the climate effects of dust aerosols. This patent proposes an atmospheric dust tracing method based on the constraints of dust activity state. This method uses an atmospheric dust tracing algorithm and data collection to accurately analyze and track the sources of dust aerosols in the study area, which helps to improve the accuracy and reliability of the understanding of external sources of dust. Summary of the invention

[0004] The present invention aims to solve the problem of limited knowledge of the dust sources in the study area, as well as the problems caused by uncertainty and error. Through the proposed method of tracing the dust sources in the study area based on the dust activity state constraint, the source of dust aerosols in the study area can be more accurately identified and tracked, thereby improving the accuracy and reliability of the understanding of the external sources of dust in the study area.

[0005] In order to achieve the above object, the present invention is implemented by adopting the following technical scheme: the method comprises:

[0006] Data collection and processing: collect and process aerosol type profile data provided by observations in the study area to select dust samples in the study area;

[0007] Collect and process data on dust emissions, dust column mass density, and dust layer top height from desert clusters to determine potential sources of dust;

[0008] The dust source tracing algorithm in the atmosphere is used to first calculate the 168-hour backward trajectory of each dust grid sample, and then constrain the dust emission, dust column mass density, and dust layer top height data of the desert source to determine whether the dust source has the potential to transport dust to the study area.

[0009] In one scenario, the data collected identified dust in the atmosphere from the ground to an altitude of 10,200 meters above the study area at a grid resolution of 1°×1°×300 meters.

[0010] In one scenario, the dust sample data collection in the study area selects data layers with cloud-aerosol discrimination CAD scores between -70 and -100 to ensure that the dust samples are accurate.

[0011] In one scheme, the dust sample data collection in the study area uses the extinction quality control mark Ext_QC to ensure the accurate acquisition of the aerosol extinction coefficient, and uses high-quality satellite observation data with Ext_QC values ​​of 0, 1, 2, 16 and 18.

[0012] In one scheme, the atmospheric dust source tracing algorithm establishes four data sets, including: hourly dust emission rate, dust column mass density, hourly planetary boundary layer height and lunar dust layer top height.

[0013] In one scenario, four potential long-range desert clusters were defined based on the climatological characteristics of dust emissions; the desert clusters are located in Eastern Central Asia, Western Central Asia, West Asia-South Asia, and the Middle East-North Africa;

[0014] If an air mass moving along its backward trajectory passes through a desert cluster and its altitude is lower than the top of the dust layer at the location of the desert cluster, and at this time the dust emission rate and the dust column mass density of the air mass at the location of the air mass exceed the threshold, then it is considered that the air mass has a high probability of transporting dust to the Qinghai-Tibet Plateau.

[0015] In one solution, in order to prevent the air mass from rebounding after touching the ground during the backward trajectory simulation, the backward trajectory is terminated when the air mass height is lower than the planetary boundary layer height.

[0016] In one scheme, for a dust sample, if more than 80% of the trajectory segments that meet the atmospheric dust source tracing algorithm standards come from the same source area, the sample is considered to be mainly contributed by this area; otherwise, it is classified as a mixed sample.

[0017] Beneficial effects of the present invention:

[0018] The present invention can improve the accuracy and reliability of our understanding of the source of dust aerosols by tracking and analyzing the sources of dust in detail and accurately, and thus can produce more accurate expectations for climate change in this area, which is helpful for related climate research and prediction. At the same time, since dust particles have an important impact on the optical properties of the atmosphere, radiation balance and human health, etc., accurate source tracing analysis can also help to better understand and prevent these problems, enhance the public's understanding of environmental issues, and improve environmental awareness, thereby having a positive impact on the sustainable development of society. In addition, the method of the invention can also be promoted and applied to other areas of the world with frequent dust activities, providing a powerful tool for global sandstorm research and early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of the present invention;

[0020] Figure 2 A schematic diagram is provided to summarize the method of the present invention;

[0021] Figure 3 The spatial distribution of the occurrence frequency (left) and the corresponding dust load fraction (right) of dust samples from the Bukong Desert cluster over the Qinghai-Tibet Plateau;

[0022] Figure 4 Spatial distribution of dust sample frequencies contributing to the subregional divisions and major desert clusters. DETAILED DESCRIPTION

[0023] In order to facilitate understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Typical embodiments of the present invention are provided in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in the present invention. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0024] Unless otherwise defined, all technical and scientific terms used in the present invention have the same meanings as those understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0025] Embodiment 1:

[0026] like Figure 1 As shown, the method for tracing the source of atmospheric dust in the study area based on the constraint of dust activity state includes:

[0027] S1. Data collection and processing: Collect and process aerosol type profile data provided by observations in the study area to select dust samples in the study area.

[0028] The "Active Cloud-Aerosol Lidar" (CALIOP) carried on the "Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation" (CALIPSO) can provide vertical aerosol backscattering, extinction coefficient and depolarization ratio data. Its advantage is that it can accurately distinguish dust aerosols from other types of aerosols. Therefore, the present invention uses the 12-year (2007-2018) aerosol profile product (APro) to extract dust and polluted dust aerosol data over the Qinghai-Tibet Plateau.

[0029] S2. Collect and process data on dust emissions, dust column mass density, and dust layer top height of desert clusters to determine potential sources of dust.

[0030] Figure 2 (a) Schematic diagram of the atmospheric dust source tracing algorithm, showing the backward trajectory (black line), starting point (red dot) and end point (green dot). The dotted lines represent the top of the dust layer (blue), the planetary boundary layer (green) and the dust column mass density threshold (orange), respectively. Dust emissions from the desert are represented by arrows, and the dust column mass density values ​​are represented by orange columns. (b) The Qinghai-Tibet Plateau study area is marked with a blue box. The black lines represent the backward trajectories of the two dust samples, and the solid lines represent the specific backward trajectories detailed in (c). The green line represents the CALIOP trajectory. (c) Similar to (a), but showing the actual situation of the two dust sample cases. (d) Vertical profile of aerosol type, corresponding to the trajectory in (b).

[0031] The Qinghai-Tibet Plateau is defined as the area with an altitude of more than 2,500 meters ( Figure 2 ). Dust in the atmosphere within the altitude range of 3000m to 10200m over the Qinghai-Tibet Plateau is identified with a grid resolution of 1°×1°×300m. In order to identify dust aerosols with high accuracy, the present invention selects data layers with cloud-aerosol discrimination (CAD) scores between -70 and -100. In addition, the extinction quality control flag (Ext_QC) is used to ensure the accurate acquisition of the aerosol extinction coefficient, and only high-quality satellite observation data with Ext_QC values ​​of 0, 1, 2, 16 and 18 are used.

[0032] After strict quality control of the data, the airspace over the Tibetan Plateau was sampled by grid. During the sampling process, if the number of aerosol profiles in a grid is too small, the observation results are not representative. Therefore, grids with no less than 7 profiles were selected for sampling. In order to ensure that there is sufficient dust content in the selected grid samples, if dust is detected in more than 30% of the profiles in the horizontal direction and more than 50% of the layers in the vertical direction, the grid is identified as a dust grid. Because the dust emitted by the Tibetan Plateau itself is mainly concentrated on the surface, in order to minimize the impact of local dust on the Tibetan Plateau, we only consider dust grid samples above the planetary boundary layer height (PBLH). The locations of these dust grid samples and the time when the dust appeared were used as the starting point for the back-trajectory analysis.

[0033] S3. Using the dust source tracing algorithm in the atmosphere, first calculate the 168-hour backward trajectory of each dust grid sample, and then constrain the dust emission of the desert source, the mass density of the dust column, the height of the top of the dust layer and other conditions to determine whether the dust source has the potential to transport dust to the study area.

[0034] Figure 2 A detailed schematic diagram of the atmospheric dust source tracing algorithm is provided. Based on the calculation of the 168-hour backward trajectory of each dust grid sample on the Qinghai-Tibet Plateau, the present invention analyzes in detail the dust activity state in the air when the backward trajectory air mass passes through the source area. In the analysis process, we used the dust activity state data provided by CALIPSO and MERRA-2.

[0035] To assess the potential for dust transport from the source to the Tibetan Plateau, four datasets were established: hourly dust emission rate from MERRA-2, dust column mass density, hourly planetary boundary layer height, and monthly dust layer top height calculated from CALIPSO data. In addition, four potential long-range desert clusters were defined based on the climatological characteristics of dust emission rates. These desert clusters are located in eastern Central Asia, western Central Asia, West Asia-South Asia, and the Middle East-North Africa.

[0036] Subsequently, if the air mass moving along its backward trajectory passes through a desert cluster and its height is lower than the top height of the dust layer of the desert cluster, and at this time the dust emission rate and the dust column mass density of the air mass at this location exceed the threshold, then it is considered that the air mass has a high probability of transporting dust to the Qinghai-Tibet Plateau. Figure 2 This is shown in a for scenario A. The other scenarios do not have much transport potential due to the low mass density of the dust column (scenario B), insufficient dust emission (scenario C), or the air mass altitude is higher than the dust layer top altitude (scenario D). In addition, to prevent errors caused by the air mass rebounding after touching the ground, we truncate the backward trajectory when the air mass altitude is lower than the planetary boundary layer altitude.

[0037] Figure 2 Schematic diagram of the method overview. (a) Schematic diagram of the atmospheric dust source tracing algorithm, showing the backward trajectory, starting point and end point. The dashed lines represent the top of the dust layer, the planetary boundary layer and the dust column mass density threshold, respectively. Dust emissions from deserts are represented by arrows, and dust column mass density values ​​are represented by columns. (b) The Qinghai-Tibet Plateau study area is marked with a solid line frame. The black lines represent the backward trajectories of two dust samples, and the solid lines represent the specific backward trajectories detailed in (c). (c) Similar to (a), the actual situation of two dust sample cases is shown. (d) Vertical profile of aerosol type, corresponding to the gray CALIPSO trajectory in (b).

[0038] Figure 2 c shows the results of two dust samples analyzed using the atmospheric dust source tracing algorithm. Using this method, we believe that the dust samples in April 2008 came from West Asia and South Asia, and the backward trajectory of its air mass passed through the region and met all dust activity criteria ( Figure 2 b and Figure 2 c2). In addition, CALIPSO observed a significant dust layer when the air mass passed over the West Asia-South Asia desert cluster ( Figure 2 d2). As for the dust sample in December 2018, although its air mass passed through western Central Asia ( Figure 2 b), but there is no obvious dust activity in the area, so the dust sample is not from western Central Asia. CALIPSO observations also confirm this conclusion. No dust aerosols were detected when the air mass passed through western Central Asia ( Figure 2 d1). Such samples that fail to meet the standards of the atmospheric dust source tracing algorithm will not be included in the statistical analysis of the study. Through these two cases, the accuracy of the algorithm's tracing results has been proven to a certain extent.

[0039] By tracing the source of atmospheric dust in the study area based on the constraints of dust activity status, we found the spatial heterogeneity of foreign dust in the atmosphere over the Qinghai-Tibet Plateau. Figure 3 The dust sample occurrence frequency and dust load fraction from different external dust sources obtained by the atmospheric dust source tracing algorithm are shown. The eastern Central Asia, western Central Asia, and West Asia-South Asia desert clusters contribute more significantly to the dust over the Qinghai-Tibet Plateau. In the northeast of the Qinghai-Tibet Plateau, the eastern Central Asian desert cluster is the most contributing external source. The dust sample occurrence frequency and dust load fraction in eastern Central Asia are about 0.6, and the highest place can exceed 0.9 ( Figure 3 a). Previous studies have also determined that the desert cluster in eastern Central Asia is the main source of dust in the northern part of the Qinghai-Tibet Plateau based on the analysis of model results. In the northwest of the Qinghai-Tibet Plateau, western Central Asia is the most important source of external dust, with the frequency of occurrence and dust load fraction of dust samples being about 0.5, and exceeding 0.8 in some areas ( Figure 3b). In the southwest of the Qinghai-Tibet Plateau, the West Asia-South Asia desert cluster is the largest external source. Here, the frequency and dust load fraction of dust samples from the West Asia-South Asia desert cluster are about 0.25, and the maximum value exceeds 0.5 ( Figure 3 c). In addition, dust from the Middle East-North Africa desert cluster affects the southern part of the Qinghai-Tibet Plateau through long-range transport, but its relative contribution is lower than that of other desert clusters ( Figure 3 d). In addition, mixed samples refer to samples where multiple desert clusters contribute to dust transport, mainly distributed in the eastern part of the Qinghai-Tibet Plateau ( Figure 3 e).

[0040] Figure 3 The spatial distribution of the dust sample occurrence frequency (left) and the corresponding dust load fraction (right) from the non-empty desert clusters over the Qinghai-Tibet Plateau: from (a) Eastern Central Asia, (b) Western Central Asia, (c) West Asia-South Asia, (d) Middle East-North Africa, (e) multiple desert clusters. The sample occurrence frequency and dust load fraction (f) of each grid are calculated as f = N desert / N, where N is the number of dust samples from all dust samples (the total dust load of dust samples), N desert is the number of dust samples from a certain desert cluster (the total dust load from a certain desert cluster)

[0041] The present invention divides the Qinghai-Tibet Plateau into three sub-regions ( Figure 4 The relative contribution of external desert sources to the dust in the atmosphere over the Qinghai-Tibet Plateau was studied. The northwestern Qinghai-Tibet Plateau is mainly affected by the western Central Asian desert cluster. More than 53% of the dust samples in this sub-region come from western Central Asia, and the average dust load of these samples exceeds 32 mg / m 2 Among them, the Karakum Desert is the most contributing external desert source in the region. 42.2% of the dust samples come from this desert, and the average dust load of the dust samples is 32.9 mg / m 2 The northeastern part of the Qinghai-Tibet Plateau is mainly affected by the eastern desert cluster of Central Asia. 55% of the dust samples in this sub-region come from eastern Central Asia. The Taklimakan Desert is the most foreign desert in the eastern desert cluster of Central Asia that contributes the most to the Qinghai-Tibet Plateau, with a relative contribution of 49.6%. The average dust load of its samples is 48.3 mg / m 2 The southwestern sub-region of the Qinghai-Tibet Plateau is mainly affected by the dust from West Asia to South Asia. The dust samples contributed by the West Asia-South Asia desert cluster account for 32% of the sub-region, with an average dust load of 27.8 mg / m 2 The Thar Desert in West Asia and South Asia is the largest external desert source in the region, with a relative contribution of 16.4% and an average dust load of 32.1 mg / m 2 .

[0042] Table 1. Relative contributions of desert clusters and major allochthonous deserts to atmospheric dust in the Tibetan Plateau region.

[0043]

[0044] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0045] It should be understood that the detailed description of the technical solutions of the present invention by means of the preferred embodiments is illustrative rather than restrictive. A person skilled in the art may modify the technical solutions described in the embodiments, or replace some of the technical features by equivalents, based on reading the specification of the present invention; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A new method for atmospheric dust source tracing based on dust activity state constraints, characterized by: The method includes: Data collection and processing: collect and process aerosol type profile data provided by observations in the study area to select dust samples in the study area; Collect and process data on dust emissions, dust column mass density, and dust layer top height from desert clusters to determine potential sources of dust; The dust source tracing algorithm in the atmosphere is used to first calculate the 168-hour backward trajectory of each dust grid sample, and then constrain the dust emission, dust column mass density, and dust layer top height data of the desert source to determine whether the dust source has the potential to transport dust to the study area; The dust source tracing algorithm in the atmosphere establishes four data sets, including: hourly dust emission rate, dust column mass density, hourly planetary boundary layer height and lunar dust layer top height; Four potential long-range desert clusters are defined based on the climatological characteristics of dust emissions; the desert clusters are located in eastern Central Asia, western Central Asia, West Asia-South Asia, and the Middle East-North Africa. If an air mass moving along its backward trajectory passes through a desert cluster and its height is lower than the height of the dust layer top at the location of the desert cluster, and the dust emission rate and dust column mass density at the location of the air mass exceed the threshold, it is considered that the air mass has a high probability of transporting dust to the Qinghai-Tibet Plateau; In order to prevent the air mass from rebounding after touching the ground during the backward trajectory simulation, the backward trajectory is terminated when the height of the air mass is lower than the height of the planetary boundary layer; For a dust sample, if more than 80% of the trajectory segments that meet the standards of the atmospheric dust source tracing algorithm come from the same source area, the sample is considered to be mainly contributed by this source area; otherwise, it is classified as a mixed sample.

2. According to claim 1, a new method for tracing the source of atmospheric dust based on the constraints of dust activity state is characterized by: The data were collected over the study area and dust in the atmosphere from the ground to an altitude of 10,200 m was identified at a grid resolution of 1° × 1° × 300 m.

3. The new method for atmospheric dust source tracing based on dust activity state constraints according to claim 1 is characterized by: The data collection of dust samples in the study area selected data layers with cloud-aerosol distinction CAD scores between -70 and -100 to ensure that the dust samples are accurate.

4. The new method for tracing the source of atmospheric dust based on dust activity state constraints according to claim 1 is characterized by: The data collection of dust samples in the study area uses the extinction quality control mark Ext_QC to ensure the accurate acquisition of the aerosol extinction coefficient, and uses high-quality satellite observation data with Ext_QC values ​​of 0, 1, 2, 16 and 18.

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