Bioaerosol monitoring and response strategy optimization method for complex pollution treatment area

Abstract

The invention discloses a biological aerosol monitoring and response strategy optimization method for a complex pollution treatment area, and relates to the technical field of air quality detection. Comprising the following steps: determining a to-be-detected area, collecting pollution source characteristics and distribution information of the to-be-detected area, and collecting environment background data and meteorological data; monitoring point positions and monitoring time of main areas and time periods covering pollutant discharge are determined; selecting biological aerosol monitoring equipment; optimizing a sampling mode and a sampling process, and collecting a biological aerosol sample; analyzing to obtain the particle size of the biological aerosol and continuous and real-time concentration change of biological factors in the air; processing to obtain the change conditions of the distribution characteristics and the change trend of the biological aerosol on different time and space scales; and interpreting and analyzing to obtain a biological aerosol emission source, a transmission path and influence factor information. The biological aerosol monitoring and treatment decision of the complex pollution treatment area can be guided, the treatment effect is improved, and the environment quality is protected.

Description

Technical Field

[0001] The present invention relates to the field of air quality detection technology, and in particular to a method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas. Background Art

[0002] Monitoring bioaerosols within complex pollution control areas is a key task in environmental protection and air quality management. Bioaerosols, tiny airborne particles, can carry and spread pathogens, bacteria, fungi, and other harmful substances, posing potential risks to human health and environmental safety. The traditional international standard bioaerosol sampling method—the culture medium-Anderson impactor single-point sampling method—has been used for over 50 years for bioaerosol sample collection and cultivation and is widely adopted in many research and monitoring projects. However, with the increasing demand for more in-depth research and practical applications of bioaerosols, the limitations of this method in complex pollution control areas are becoming increasingly apparent. Specifically, the traditional single-point sampling method can only assess bioaerosol emissions from a single sampling point, failing to provide a comprehensive picture of bioaerosol emissions across the entire area and failing to truly reflect the distribution characteristics of bioaerosols within the area. Furthermore, this method requires tedious sample collection and cultivation processes, which are time-consuming, labor-intensive, and costly. Especially in complex pollution control areas, monitoring multiple sampling points becomes difficult and cannot meet the rapid and accurate requirements for qualitative and quantitative analysis of bioaerosols. In addition to the above limitations, the traditional international standard bioaerosol sampling method has other problems. For example, the sampling rate of this method is usually low, which may lead to missing or inaccurate monitoring data. In addition, this method is also prone to decomposition and changes of microorganisms during the sampling and cultivation process, which interferes with the monitoring results. Especially in complex pollution control areas, monitoring data may be affected by various environmental factors such as local meteorology and weather, further affecting the accuracy of monitoring.

[0003] Therefore, how to provide a bioaerosol monitoring and response strategy optimization method for complex pollution control areas to achieve comprehensive monitoring and evaluation of bioaerosols in the entire complex area is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0004] In view of this, the present invention provides a method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas, which can comprehensively understand the characteristics, distribution and concentration changes of bioaerosols within the complex pollution control areas, and provide a scientific basis and support for the monitoring, evaluation and control of bioaerosols.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas includes the following steps:

[0007] S1. Determine the area to be tested, collect pollution source characteristics and distribution information in the area to be tested, and collect environmental background data and meteorological data;

[0008] S2. Analyze the pollution source characteristics and distribution information of the area to be measured in S1, and determine the monitoring points and monitoring time covering the main areas and time periods of pollutant emissions;

[0009] S3. Select bioaerosol monitoring equipment for complex pollution control areas based on the equipment's technical specifications, sampling flow control, particle size distribution sampling capacity, sampling duration, and energy consumption;

[0010] S4. Use the monitoring equipment in S3 to optimize the sampling method and sampling process to collect bioaerosol samples;

[0011] S5. Analyze the bioaerosol samples collected in S4 to obtain the particle size of the bioaerosol and the continuous and real-time concentration changes of biological factors in the air;

[0012] S6. Process the particle size of the bioaerosols and the continuous and real-time concentration changes of biological factors in the air in S5 to obtain the distribution characteristics and change trends of the bioaerosols at different time and space scales;

[0013] S7. Interpret the particle size of bioaerosols in S5 and the continuous and real-time changes in the concentration of biological factors in the air, and conduct a comprehensive analysis in combination with environmental background data and meteorological data to obtain information on bioaerosol emission sources, transmission paths and influencing factors.

[0014] In the above method, optionally, the pollution source characteristics and distribution information in S1 include the pollution source distribution and diffusion path, emission scale and activity level, impact range and sensitive areas; environmental background data include but are not limited to temperature, humidity, wind direction and wind speed; meteorological data include but are not limited to air pressure and rainfall.

[0015] In the above method, the specific content of S2 is optional:

[0016] Based on the geographical environment, meteorological conditions, and climate characteristics surrounding the area to be tested, the transmission and diffusion paths of pollutants are determined, and the locations of monitoring points are preliminarily preset in combination with wind direction, terrain, and emission height; the locations of monitoring points are selected based on the emission volume and activity level of the pollution sources; the locations of monitoring points are ultimately determined based on environmental sensitivity assessments and the distribution of population, ecological, and water resource factors, combined with sensitive areas and key affected areas; and the monitoring time is determined based on the activity time, periodic emissions, and seasonal variation characteristics of the pollution sources, ensuring that the monitoring time covers the key periods of pollution source activity and changes in different seasons.

[0017] In the above method, optionally, the bioaerosol monitoring equipment in S3 includes but is not limited to a liquid impact sampler, a solid impact sampler, a cyclone sampler, a filter sampler, a centrifugal sampler and an electrostatic sampler.

[0018] The above method is optional. In S4, the sampling method and sampling process are optimized. Specifically, the grid division method is adopted to divide the entire area to be tested into multiple small grids, and each small grid represents a small area; based on the characteristics and distribution information of the pollution sources in the area to be tested, the bioaerosol escape points in each small area are determined; and the monitoring equipment in S3 is used to collect bioaerosol samples at the points in each small grid area.

[0019] The above method optionally includes analyzing the bioaerosol sample collected in S4 using Mie scattering and ultraviolet induced fluorescence as analysis methods.

[0020] As can be seen from the above technical solutions, compared with the prior art, the present invention provides a method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas, which has the following beneficial effects:

[0021] (1) The present invention divides the area into multiple small areas and collects samples in each small area by accurately locating the main emission points, thus achieving efficient sampling. This sampling strategy can improve sampling efficiency and obtain more accurate and representative bioaerosol samples.

[0022] (2) The present invention integrates Mie scattering and ultraviolet-induced fluorescence as methods for bioaerosol analysis. These two methods complement each other and can provide comprehensive and accurate analysis results. Real-time analysis is performed using a portable integrated device, eliminating the need to return samples to the laboratory for processing, saving time and improving analysis efficiency.

[0023] (3) This invention emphasizes the comprehensive analysis of monitoring data with environmental background data, meteorological data, and other data. By correlating bioaerosol concentration and particle size data with environmental factors and meteorological conditions, information such as bioaerosol emission sources, transmission paths, and influencing factors is revealed. This comprehensive analysis method provides a scientific basis for monitoring and evaluating bioaerosols in complex pollution control areas, and can optimize control strategies and improve control effectiveness.

[0024] (4) The present invention provides a feasible, accurate, and efficient solution for detecting bioaerosols in complex pollution control areas through efficient sampling strategies, multi-method analysis, and comprehensive data analysis. Through the implementation of the present invention, representative sample data can be quickly acquired, and comprehensive assessment of bioaerosol distribution, emission source characteristics, and transmission paths within complex pollution control areas can be provided. This will help guide bioaerosol monitoring and control decision-making in complex pollution control areas, improve control effectiveness, and protect environmental quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0026] Figure 1 This is a flow chart of the method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas disclosed in the present invention. DETAILED DESCRIPTION

[0027] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0028] In this application, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. The terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or apparatus comprising the element.

[0029] Reference Figure 1 As shown, the present invention discloses a method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas, comprising the following steps:

[0030] S1. Determine the area to be tested, collect pollution source characteristics and distribution information in the area to be tested, and collect environmental background data and meteorological data;

[0031] S2. Analyze the pollution source characteristics and distribution information of the area to be measured in S1, and determine the monitoring points and monitoring time covering the main areas and time periods of pollutant emissions;

[0032] S3. Select bioaerosol monitoring equipment for complex pollution control areas based on the equipment's technical specifications, sampling flow control, particle size distribution sampling capacity, sampling duration, and energy consumption;

[0033] S4. Use the monitoring equipment in S3 to optimize the sampling method and sampling process to collect bioaerosol samples;

[0034] S5. Analyze the bioaerosol samples collected in S4 to obtain the particle size of the bioaerosol and the continuous and real-time concentration changes of biological factors in the air;

[0035] S6. Process the particle size of the bioaerosol and the continuous and real-time concentration change information of the biological factors in the air in S5 to obtain the distribution characteristics and change trends of the bioaerosol at different time and space scales;

[0036] S7. Interpret the particle size of bioaerosols and the continuous and real-time concentration change information of biological factors in the air in S5, and conduct a comprehensive analysis in combination with environmental background data and meteorological data to obtain information on bioaerosol emission sources, transmission paths and influencing factors.

[0037] Furthermore, the pollution source characteristics and distribution information in S1 include the distribution and diffusion path of pollution sources, emission scale and activity level, impact range and sensitive areas; environmental background data include but are not limited to temperature, humidity, wind direction and wind speed; meteorological data include but are not limited to air pressure and rainfall.

[0038] Furthermore, S2 determines the monitoring points and monitoring times covering the main areas and time periods of pollutant emissions, judges the pollutant transmission and diffusion paths based on the geographical environment, meteorological conditions, and climate characteristics surrounding the area to be measured, and preliminarily presets the locations of the monitoring points in combination with wind direction, terrain, and emission height; selects the locations of the monitoring points based on the emission volume and activity level of the pollution sources; determines the locations of the monitoring points by giving priority to sensitive areas and key affected areas based on environmental sensitivity assessments and the distribution of population, ecology, and water resources; and determines the monitoring time based on the activity time, periodic emissions, and seasonal variation characteristics of the pollution sources to ensure that the monitoring time covers the key periods of pollution source activity and seasonal variations.

[0039] Furthermore, the bioaerosol monitoring equipment in S3 includes but is not limited to liquid impact samplers, solid impact samplers, cyclone samplers, filter samplers, centrifugal samplers and electrostatic samplers.

[0040] Furthermore, the sampling method and sampling process are optimized in S4, specifically the grid division method, which divides the entire area to be tested into multiple small grids, each small grid representing a small area; based on the characteristics and distribution information of the pollution sources in the area to be tested, the main bioaerosol escape points in each small area are determined; and the monitoring equipment in S3 is used to collect bioaerosol samples at the points in each small grid area.

[0041] Furthermore, the bioaerosol samples collected in S4 were analyzed using Mie scattering and UV-induced fluorescence as analytical methods.

[0042] Specifically, this method utilizes Mie scattering and ultraviolet-induced fluorescence (UV-LIF) as analytical methods. A portable integrated device employing these methods draws airborne bioaerosol particles into the device via a vacuum pump, enabling accurate, real-time analysis of bioaerosol particle size, concentration, and other data at the sampling point. Mie scattering determines bioaerosol particle size by measuring the intensity and directional distribution of scattered light. UV-LIF utilizes specific fluorescence signals in bioaerosols, stimulating these signals and measuring their intensity to assess bioaerosol concentration. These two methods complement each other, providing accurate and comprehensive bioaerosol analysis results. Using a portable integrated device for analysis allows for real-time analysis of bioaerosol samples, eliminating the need to return samples to the laboratory for processing. By drawing airborne bioaerosol particles into the device via a vacuum pump, critical data such as particle size and concentration can be quickly obtained at the sampling point. This portable integrated device offers the advantages of portability and ease of operation, making it suitable for field monitoring and rapid response scenarios.

[0043] Example 1:

[0044] A method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas includes the following steps:

[0045] a) Analysis of Pollution Source Characteristics and Distribution: To ensure comprehensive and representative monitoring, we first analyzed the characteristics and distribution of pollution sources in the region. Through thorough investigation and analysis of factors such as source characteristics, emission scale, and activity, we determined appropriate monitoring locations and times. These locations and times were selected to cover the main areas and time periods of pollutant emission, enabling comprehensive regional monitoring and assessment of bioaerosols.

[0046] b) Monitoring Equipment Selection: Select high-quality monitoring equipment that meets the required accuracy, sensitivity, and stability. By comprehensively considering factors such as the equipment's technical specifications, sampling flow control, particle size distribution sampling capacity, sampling duration, and energy consumption, ensure that the equipment selected is suitable for bioaerosol monitoring within the complex pollution control area. The selected equipment should be able to accurately detect bioaerosol composition and concentration, improving the reliability and accuracy of monitoring data.

[0047] c) Determination of sampling methods: By optimizing the sampling method and sampling process, representative bioaerosol samples can be collected quickly and accurately to meet monitoring requirements.

[0048] d) Analysis method: Mie scattering and ultraviolet-induced fluorescence (UV-LIF) are used as analysis methods. In this method, aerosol particles generated by the airflow generated by a vacuum pump are irradiated by a narrow beam laser after passing through an aerosol sampler, thereby generating scattered light. For aerosol particles containing fluorescent substances, the excitation of the laser will lead to the generation of excited fluorescence. These scattered light and excited fluorescence are received by a scattered light detector and a fluorescence detector, respectively. By applying Mie scattering and UV-induced fluorescence, we can detect the particle size of bioaerosols and achieve continuous, real-time monitoring of the concentration changes of biological factors (such as bacteria, spores, viruses, toxins, etc.) in the air.

[0049] e) Data Processing and Interpretation: Proper processing and interpretation of the acquired monitoring data are performed to gain a comprehensive understanding and accurate assessment of bioaerosol pollution. Data processing utilizes statistical analysis methods, data models, or artificial intelligence algorithms to analyze and interpret monitoring data. These methods can reveal the distribution characteristics and trends of bioaerosols at different temporal and spatial scales. Data interpretation integrates monitoring data with environmental background data, meteorological data, and other data to reveal information on bioaerosol emission sources, transmission pathways, and influencing factors.

[0050] Example 2:

[0051] This embodiment is a preferred implementation of embodiment 1. In step a), appropriate monitoring points and monitoring times are determined by fully investigating and analyzing factors such as the characteristics, emission scale and activity level of the pollution source. These investigations and analyses mainly conduct field investigations on points where bioaerosols may escape within complex areas, and preliminarily estimate the degree of escape of bioaerosols at the escape points to understand the key factors that may cause bioaerosol escape. This investigation process helps to more accurately select monitoring points and determine monitoring times. Accurately selecting monitoring points is the key to ensuring that the monitoring results are representative and reliable. By investigating and analyzing the characteristics of the pollution sources, including factors such as characteristics, emission scale and activity level, potential bioaerosol escape points can be identified. These points are key locations that may cause bioaerosol escape, and field investigations on them can better understand their escape conditions and possible influencing factors. During the field investigation, on-site environmental data can be collected, environmental conditions can be observed, and a preliminary estimate of the degree of escape of bioaerosols at the escape points can be made. These data and estimation results can be used for further analysis and judgment to guide the selection of monitoring points and decisions on monitoring time.

[0052] Example 3:

[0053] This embodiment is a preferred implementation of embodiment 1. In step b), high-quality monitoring equipment that meets the requirements in terms of accuracy, sensitivity and stability is selected. The purpose of selecting equipment that meets the requirements in terms of accuracy, sensitivity and stability is to be able to accurately measure the real-time concentration and particle size distribution changes of bioaerosols in complex areas to ensure that the measured data can represent a common phenomenon in the area. The selection of high-quality monitoring equipment is crucial for accurate and reliable monitoring of bioaerosols. These devices should be accurate, that is, they should be able to provide accurate concentration and particle size measurement results to ensure the credibility of the monitoring data. At the same time, the sensitivity of the equipment is required to be high, and it can detect lower concentrations of bioaerosols and accurately measure their particle size distribution. In addition, the equipment needs to be stable to ensure the stability and comparability of the measurement results during long-term continuous monitoring. The selected equipment can quickly and in real time measure the changes in the concentration and particle size distribution of bioaerosols, and can provide accurate basic data support for subsequent monitoring data analysis and research.

[0054] Example 4:

[0055] This embodiment is a preferred implementation of embodiment 1. In step c), an efficient sampling method is provided. By optimizing the sampling method and sampling process, it can be used to quickly and accurately collect representative bioaerosol samples to meet monitoring requirements. In order to ensure that the collected bioaerosol samples are representative, the present invention divides the entire complex sampling area into multiple small areas through a grid division method, and each small grid represents a small area. According to the field survey results in step a), the main bioaerosol escape points in each small area are determined. These points are key positions that may have a significant impact on the bioaerosol concentration and characteristics of the area. Using the high-quality monitoring equipment selected in step b), bioaerosol samples are collected at the points in each small grid area. During the sampling process, the optimized sampling process should be followed to ensure that the sample collection process is fast and accurate, and the representativeness of the samples is maintained. These sampling samples can reflect the concentration and characteristics of the bioaerosols in each grid area, providing an important basis for subsequent data analysis and evaluation.

[0056] Example 5:

[0057] This embodiment is a preferred implementation of Example 1. In step d), Mie scattering and ultraviolet-induced fluorescence (UV-LIF) are used as analysis methods. A portable integrated device using this method draws airborne bioparticles into the device via a vacuum pump, enabling accurate, real-time analysis of bioaerosol particle size, concentration, and other data at the sampling point. Mie scattering determines bioaerosol particle size by measuring the intensity and directional distribution of scattered light. UV-LIF utilizes specific fluorescence signals in bioaerosols, stimulating these signals and measuring their intensity to assess bioaerosol concentration. These two methods complement each other, providing accurate and comprehensive bioaerosol analysis results. Using a portable integrated device for analysis allows for real-time analysis of bioaerosol samples, eliminating the need to return samples to the laboratory for processing. By drawing airborne bioparticles into the device via a vacuum pump, critical data such as particle size and concentration can be quickly obtained at the sampling point. This portable integrated device offers the advantages of portability and ease of operation, making it suitable for field monitoring and rapid response scenarios.

[0058] Example 6:

[0059] This embodiment is a preferred implementation of Example 1. In step e), data interpretation involves comprehensive analysis of the monitoring data with environmental background data, meteorological data, and other data to reveal information about bioaerosol emission sources, transmission paths, and influencing factors. Because bioaerosol concentration and particle size are easily affected by environmental factors and meteorological conditions, this embodiment advocates comprehensive analysis of the monitoring data with environmental background data and meteorological data. Environmental background data includes information such as ambient temperature, humidity, wind direction, and wind speed, while meteorological data includes information such as air pressure and rainfall. Comprehensive analysis of these data allows for a better understanding of bioaerosol emission sources, transmission paths, and influencing factors within the monitored area. During data analysis, this embodiment requires correlation of bioaerosol concentration and particle size data with the environmental factors and meteorological conditions at the time of sampling. This analytical approach facilitates a deeper understanding of bioaerosol distribution characteristics and accurately assesses the extent to which environmental and meteorological factors influence them. Comprehensive analysis can reveal the temporal and spatial distribution patterns of bioaerosols within this complex region, providing a scientific basis for further pollution control and environmental protection efforts.

[0060] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas, characterized by: The following steps are involved: S1. Determine the area to be tested, collect pollution source characteristics and distribution information in the area to be tested, and collect environmental background data and meteorological data; S2. Analyze the pollution source characteristics and distribution information of the area to be measured in S1, and determine the monitoring points and monitoring time covering the main areas and time periods of pollutant emissions; S3. Select bioaerosol monitoring equipment for complex pollution control areas based on the equipment's technical specifications, sampling flow control, particle size distribution sampling capacity, sampling duration, and energy consumption; S4. Use the monitoring equipment in S3 to optimize the sampling method and sampling process to collect bioaerosol samples; S5. Analyze the bioaerosol samples collected in S4 to obtain the particle size of the bioaerosol and the continuous and real-time concentration changes of biological factors in the air; S6. Process the particle size of the bioaerosols and the continuous and real-time concentration changes of biological factors in the air in S5 to obtain the distribution characteristics and change trends of the bioaerosols at different time and space scales; S7. Interpret the particle size of bioaerosols in S5 and the continuous and real-time changes in the concentration of biological factors in the air, and conduct a comprehensive analysis in combination with environmental background data and meteorological data to obtain information on bioaerosol emission sources, transmission paths and influencing factors.

2. The method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas according to claim 1 is characterized in that: The pollution source characteristics and distribution information in S1 include the distribution and diffusion path of pollution sources, emission scale and activity level, impact range and sensitive areas; environmental background data include but are not limited to temperature, humidity, wind direction and wind speed; meteorological data include but are not limited to air pressure and rainfall.

3. The method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas according to claim 1 is characterized in that: The specific contents of S2 are: Based on the geographical environment, meteorological conditions, and climate characteristics surrounding the area to be tested, the transmission and diffusion paths of pollutants are determined, and the locations of monitoring points are preliminarily preset in combination with wind direction, terrain, and emission height; the locations of monitoring points are selected based on the emission volume and activity level of the pollution sources; the locations of monitoring points are ultimately determined based on environmental sensitivity assessments and the distribution of population, ecological, and water resource factors, combined with sensitive areas and key affected areas; and the monitoring time is determined based on the activity time, periodic emissions, and seasonal variation characteristics of the pollution sources, ensuring that the monitoring time covers the key periods of pollution source activity and changes in different seasons.

4. The method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas according to claim 1 is characterized in that: The bioaerosol monitoring equipment in S3 includes but is not limited to liquid impact samplers, solid impact samplers, cyclone samplers, filter samplers, centrifugal samplers and electrostatic samplers.

5. The method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas according to claim 1 is characterized in that: In S4, the sampling method and sampling process are optimized. Specifically, the grid division method is used to divide the entire area to be tested into multiple small grids, each small grid representing a small area; based on the characteristics and distribution information of the pollution sources in the area to be tested, the bioaerosol escape points in each small area are determined; and the monitoring equipment in S3 is used to collect bioaerosol samples at the points in each small grid area.

6. The method for optimizing bioaerosol monitoring and response strategies in complex pollution control areas according to claim 1, characterized in that: The bioaerosol samples collected in S4 were analyzed using Mie scattering and UV-induced fluorescence as analytical methods.

Images