Urban block outdoor microclimate monitoring system and method

Abstract

The invention relates to an outdoor microclimate monitoring system and method for urban blocks, belongs to the technical field of urban intelligent monitoring and management, and solves the problem that in the prior art, low-cost accurate monitoring cannot be carried out on wide-area coverage outdoor microclimate. The method comprises the following specific steps: respectively acquiring microclimate data of a city block to be measured through a background observation point, a plurality of key observation points and a mobile observation point, and obtaining a background point temperature sequence, a key point temperature sequence and a mobile temperature sequence in a monitoring time period; respectively taking the temperature of each sampling time point in the background point temperature sequence as a reference, and correcting and calibrating the mobile temperature sequence by using the time difference; and inputting the key point temperature sequence into microclimate software, and performing dynamic heat source correction simulation on each temperature field distribution diagram in combination with the calibrated mobile temperature sequence of the corresponding time point to obtain an outdoor environment temperature simulation result in a monitoring time period, thereby realizing accurate output of meter-scale grid environment parameters of a 1KM2 block by less than or equal to 10 fixed sensors.

Description

Technical Field

[0001] This invention relates to the field of urban smart monitoring and management technology, and in particular to an outdoor microclimate monitoring system and method for urban blocks. Background Technology

[0002] With rapid industrialization and urbanization, the impact of outdoor environmental quality on human health and ecosystems has become increasingly significant. In recent years, environmental problems such as air pollution, water quality deterioration, and soil pollution have occurred frequently, posing enormous challenges to society. To effectively address these environmental issues, timely and accurate monitoring of outdoor environmental quality has become a top priority.

[0003] Currently, outdoor environmental monitoring includes methods such as fixed monitoring stations, portable devices, and remote sensing technology. Fixed monitoring stations are typically deployed in cities or specific areas, providing long-term, stable monitoring data. Portable devices are battery-powered, small in size, and easy to carry, and can be used temporarily for fixed monitoring or measuring local pollution exposure risks, but the accuracy and stability of their data are generally not as good as those from fixed monitoring stations. Remote sensing technology uses remote sensors installed in a specific area or vehicle to wirelessly connect to the cloud, providing a high-resolution data network that enables real-time understanding of the impact of emission sources on the surrounding area.

[0004] Although existing outdoor environmental monitoring technologies meet the needs of environmental monitoring to a certain extent, they still have the following shortcomings: limitations of fixed-point monitoring, sparse distribution of meteorological stations (e.g., only a dozen or so national-level stations in provincial capital cities), making it impossible to capture microclimate differences at the street scale; distortion of mobile observations: the time delay caused by vehicle-mounted mobile observations leads to poor data comparability (e.g., the error reached 3.2℃ when not corrected in the example); simulation deviates from reality: traditional physical models (e.g., microclimate simulation software) ignore sudden anthropogenic heat sources, resulting in significant differences between the simulation and the actual situation. Summary of the Invention

[0005] Based on the above analysis, the present invention aims to provide an outdoor microclimate monitoring system and method for urban blocks, in order to solve the problem that the existing technology cannot perform low-cost and accurate monitoring of outdoor microclimates with wide coverage.

[0006] The objective of this invention is mainly achieved through the following technical solutions:

[0007] On one hand, embodiments of the present invention provide a method for monitoring outdoor microclimate in urban blocks, comprising the following steps:

[0008] Microclimate data of the urban blocks under test were collected using one background observation point, several key observation points, and a moving observation point. The microclimate data included background temperature sequences, key temperature sequences, and moving temperature sequences within the monitoring period.

[0009] Using the temperature at each sampling time point in the background temperature sequence as a reference, the moving temperature sequence is calibrated by time difference correction to obtain the calibrated moving temperature sequence at each time point.

[0010] The key point temperature sequence is input into the microclimate software to obtain the initial temperature distribution map at each time point. Combined with the calibrated moving temperature sequence at the corresponding time point, dynamic heat source correction simulation is performed on each initial temperature field distribution map to obtain the outdoor environmental temperature simulation results for the monitoring period. The outdoor environmental temperature simulation results include the corrected temperature distribution map at each time point.

[0011] Furthermore, obtaining the corrected temperature distribution map at any given time point includes:

[0012] Identify the temperature difference between the initial temperature distribution map at any given time point and the corresponding region in the calibrated moving temperature sequence at the corresponding time point, obtain the congestion index and free-flow vehicle speed of the region where the temperature difference is greater than a preset threshold, and obtain the additional heat flux of the corresponding region based on the congestion index and free-flow vehicle speed using the traffic congestion index heat flux model.

[0013] The additional heat flux is added as a volume source to the microclimate software, and the simulation is corrected by combining the temperature of the key point corresponding to any given time point until the temperature difference meets the requirements, thus obtaining the corrected temperature distribution map for any given time point.

[0014] Furthermore, obtaining the calibrated moving temperature sequence at any given time point includes:

[0015] Using the temperature at any time point in the background temperature sequence as a reference value, the temperature difference between the background temperature at each time point in the background temperature sequence and the reference value is calculated to obtain a time-temperature deviation sequence; the moving temperature sequence is compensated based on the time-temperature deviation sequence to obtain the calibrated moving temperature sequence at any time point.

[0016] Furthermore, the traffic congestion index heat flux model is obtained based on the following process:

[0017] Based on the total resistance that the vehicle needs to overcome when driving in the urban area under test, the corresponding resistance power is obtained, and based on the resistance power, the engine cooling power is obtained.

[0018] Based on the kinetic energy loss of the vehicle, a vehicle start-stop heat model is constructed to obtain the corresponding start-stop heat.

[0019] Based on the engine's heat dissipation power and start-stop heat, and combined with the relationship between the congestion index and free-flow vehicle speed, the heat flux model of the traffic congestion index is obtained.

[0020] Furthermore, the expression for the traffic congestion index heat flux model is as follows:

[0021]

[0022] Among them, Q T For additional heat flux; v f denoted as , where is the free-flow vehicle speed of the urban street block to be tested; CI is the traffic congestion index; and K1, K2, and K3 are the preset rolling resistance coefficient, start-stop coefficient, and air resistance coefficient, respectively.

[0023] Furthermore, the coordinates and corresponding measured times of areas where the temperature difference is greater than a preset threshold are obtained, and the congestion index and free-flow vehicle speed of the corresponding area and time are obtained using a traffic big data platform.

[0024] Furthermore, the microclimate data also includes wind speed and direction sequences. The additional heat flux is added as a volume source to the microclimate software, and combined with the wind speed and direction sequences collected at the corresponding time points, the outdoor environmental wind field simulation results are obtained.

[0025] Furthermore, the background observation points are set up in open areas, and the mobile observation points travel along a pre-set observation route to collect the microclimate data. The equipment at each observation point is kept highly consistent, and the sampling time is kept consistent.

[0026] On the other hand, embodiments of the present invention provide an outdoor microclimate monitoring system for urban blocks, comprising:

[0027] An environmental monitoring unit is used to collect microclimate data of the urban blocks to be monitored using one background observation point, several key observation points, and a moving observation point; the microclimate data includes background temperature sequences, key temperature sequences, and moving temperature sequences within the monitoring period.

[0028] The moving data calibration unit is used to calibrate the moving temperature sequence by using the temperature of each sampling time point in the background point temperature sequence as a reference and correcting the time difference to obtain the calibrated moving temperature sequence at each time point.

[0029] The dynamic simulation unit is used to input the key point temperature sequence into the microclimate software to obtain the initial temperature distribution map at each time point. Combined with the calibrated moving temperature sequence at the corresponding time point, the initial temperature field distribution map is dynamically heat source corrected and simulated to obtain the outdoor environmental temperature simulation results for the monitoring period. The outdoor environmental temperature simulation results include the corrected temperature distribution map at each time point.

[0030] Furthermore, the dynamic simulation unit obtains the corrected temperature distribution map at any given time point based on the following steps:

[0031] Identify the temperature difference between the initial temperature distribution map at any given time point and the corresponding region in the calibrated moving temperature sequence at the corresponding time point, obtain the congestion index and free-flow vehicle speed of the region where the temperature difference is greater than a preset threshold, and obtain the additional heat flux of the corresponding region based on the congestion index and free-flow vehicle speed using the traffic congestion index heat flux model.

[0032] The additional heat flux is added as a volume source to the microclimate software, and the simulation is corrected by combining the temperature of the key point corresponding to any given time point until the temperature difference meets the requirements, thus obtaining the corrected temperature distribution map for any given time point.

[0033] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0034] 1. This invention proposes a method for monitoring outdoor environmental microclimate by combining fixed-point monitoring with mobile observation. On the one hand, it retains the flexibility of mobile monitoring, which can be quickly deployed to different areas according to needs, greatly reducing costs compared to the traditional fixed-point monitoring scheme. On the other hand, by performing time difference correction calibration and dynamic thermal correction simulation on the mobile data, the accuracy of outdoor microclimate monitoring is improved.

[0035] 2. By combining the time difference trend of the observed temperature at the background point, the temperature of the moving observation point is corrected to obtain the temperature of different moving observation points at the same time. The error after data correction is ≤0.5℃. At the same time, by combining the traffic congestion index of the area with large temperature difference, the equivalent heat source is obtained by using the traffic congestion index heat flux model. Simulation is carried out based on the equivalent heat source and the corrected moving observation temperature to improve the fitting degree between the simulation monitoring results and the actual measurement.

[0036] 3. By integrating fixed-point and mobile observation data, more in-depth data analysis can be performed. The output data of the outdoor microclimate monitoring system of this invention can be directly used for urban ventilation corridor planning and heat island mitigation projects.

[0037] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0038] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0039] Figure 1This is a flowchart of an outdoor microclimate monitoring method according to an embodiment of the present invention;

[0040] Figure 2 This is a map showing the distribution of eight fixed-point measurements and the route of the moving observation of the land plot in an embodiment of the present invention;

[0041] Figure 3 This is an ENVI-met simulation temperature field diagram of a sample plot in an embodiment of the present invention;

[0042] Figure 4 This is an ENVI-met simulated wind field diagram of a sample plot in an embodiment of the present invention. Detailed Implementation

[0043] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0044] Example 1

[0045] One specific embodiment of the present invention discloses a method for monitoring outdoor microclimate in urban blocks, such as... Figure 1 As shown, it includes the following steps:

[0046] Step S1: Collect microclimate data of the urban blocks to be measured through one background observation point, several key observation points and moving observation points; the microclimate data includes background point temperature sequence, key point temperature sequence and moving temperature sequence within the monitoring period.

[0047] Step S2: Using the temperature at each sampling time point in the background temperature sequence as a reference, the moving temperature sequence is calibrated using time difference correction to obtain the calibrated moving temperature sequence at each time point.

[0048] Step S3: Input the key point temperature sequence into the microclimate software to obtain the initial temperature distribution map at each time point. Combine the calibrated moving temperature sequence at the corresponding time point to perform dynamic heat source correction simulation on each initial temperature field distribution map to obtain the outdoor environmental temperature simulation results for the monitoring period. The outdoor environmental temperature simulation results include the corrected temperature distribution map at each time point.

[0049] Using the above method, street microclimate data is collected in collaboration between a fixed-point measurement network and vehicle-mounted mobile observation. The temperature in the mobile data is calibrated based on the time difference correction formula. Using the fixed-point data as anchor points, the traffic congestion index heat flux model is combined with traffic flow data, and the corresponding local heat source intensity is dynamically added in the microclimate software. Through two layers of corrected data, low-cost wide-area coverage is achieved while ensuring the accuracy of outdoor environmental microclimate monitoring.

[0050] It should be noted that fixed-point measurement (i.e., fixed-location measurement) involves setting up testing instruments at suitable locations within the sample plot to collect data. When the sample plot area is small and it is necessary to collect subtle changes in the microclimate within the plot, multiple fixed-point measurement stations can be set up simultaneously at key locations within the sample plot to collect data. Data collected through fixed-point measurement is highly accurate and best reflects the actual situation of the sample plot; however, it is not suitable for large-scale measurements, and a large number of fixed-point measurement stations require excessive manpower and resources.

[0051] Mobile observation is a method of collecting data by fixing the testing instrument to a vehicle (such as a car, electric vehicle, or bicycle) and moving it at a constant speed along a predetermined observation route to measure sample plots. This method is often used when the measured area is large and it is necessary to reflect the overall microclimate of the sample plot at a specific point in time. The advantage of mobile observation is that it is suitable for large-scale measurements. The disadvantage is that the collected data needs further correction to remove the influence of the time difference factor (the time taken for the mobile observation process) on the warming trend.

[0052] To balance sampling accuracy and monitoring range, this invention employs a method that combines fixed-point measurement and mobile observation.

[0053] Specifically, in step S1, a fixed-point observation network and a vehicle-mounted mobile observation point are set up in the test area of ​​the urban block to collect microclimate data of the urban block under test at the same sampling time interval. The fixed-point observation network includes several key fixed points and one background point. By evenly deploying several key fixed-point measurement positions in the test area, the microclimate environmental data of the area can be collected comprehensively to form a fixed-point measurement network. In addition, monitoring points set up in areas of the monitoring area that are not significantly disturbed or polluted by human activities serve as background observation points to reflect the background environmental level, mainly collecting data such as temperature, humidity, solar radiation, wind speed and direction, and black sphere temperature. At the key points, data such as temperature, humidity, solar radiation, wind speed and direction, black sphere temperature, and noise level are mainly collected.

[0054] The mobile observation equipment is located at the same altitude as the fixed-point measurement site and moves at a constant speed along a pre-set observation route to measure and collect microclimate data from the test plot. The mobile observation primarily collects data such as temperature, humidity, particulate pollutant levels, GPS data, and fisheye lens photographs along the mobile observation route from the test plot.

[0055] For example, eight key points and one background point are set up within the test plot. The background point is located 1.5 meters above the ground on an open grassy area within a university campus in the test city. For mobile observation, the testing instrument is fixed above a shared bicycle, 1.5 meters above the ground. The observer pushes the shared bicycle at a constant speed of 100 meters per minute along a pre-set observation route around the sample plot to collect data. Figure 2As shown in the figure. The data acquisition time interval for both fixed-point and mobile observations was set to 30 seconds. Data were collected from three typical time periods: 8:30-10:00 AM, 12:00-1:30 PM, and 6:00-7:30 PM, respectively.

[0056] The main instruments and tools used for fixed-point measurements during the test are as follows: small automatic weather data acquisition station + tripod, black ball temperature recorder, and noise recorder. The main instruments and tools used for mobile observation are shown in the figure below: small portable automatic temperature and humidity recorder + Stevenson screen, fisheye lens camera, handheld GPS, handheld laser dust detector, shared bicycle, etc. A description of the instruments and tools used in the tests is shown in Table 1.

[0057] Table 1

[0058]

[0059]

[0060]

[0061] It is important to note that all instruments should be calibrated uniformly before data acquisition to reduce measurement errors caused by the instruments themselves. Equipment at all observation points should be highly consistent, and sampling times should be kept uniform.

[0062] Furthermore, after the data collection of fixed-point measurements and mobile observations is completed, the data needs to be screened and preprocessed, including determining the accuracy and reliability of the data collection at fixed-point measurement points, removing abnormal sampling points, and correcting the influence of human factors and instrument errors on the measured data according to the calibration of the measuring instruments.

[0063] For example, in the actual measurement process, on the one hand, according to official data from the provincial meteorological center, the test site was sunny on the day of the measurement, with temperatures ranging from 13℃ to 24℃, and a westerly wind shifting to a northeasterly wind at level 3-4, then to less than level 3. This matches the typical climate characteristics of the test city during the autumn transition season, and based on this, abnormal sampling data were screened out. On the other hand, each instrument has slight differences in sensing delay or inconsistency in instrument accuracy. All instruments were placed in one location for a unified test for a period of time, and the instrument data was read and the error values ​​of different numbered instruments were recorded. Based on the error values ​​between different instruments, the recorded measured data was corrected.

[0064] Based on the preprocessed data, background point temperature sequences, key point temperature sequences, and moving temperature sequences were obtained for different time periods. Each sequence contains multiple observed temperature values ​​at different sampling time intervals.

[0065] It should be noted that although mobile observation can obtain measured temperature data over a large area at low cost, the time points of this temperature data collection are different. If temperature (thermal field) analysis is performed at different observation points at the same time, time correction is required for the mobile observation temperatures to unify them to the same time point. That is, the correction needs to remove the influence of the heating or cooling trend caused by the time difference in mobile observations. Based on this, the present invention proposes a time difference correction for mobile observation temperatures.

[0066] Specifically, in step S2, the temperature in the mobile observation data is corrected and calibrated by combining the temperature data collected from the background points. Based on the diurnal variation pattern, it is assumed that the temperature change at the background points is the same as that at the mobile observation points. Therefore, the temperature difference at different times of the background points relative to a certain sampling time point is calculated, and then the temperature difference at each sampling temperature of the mobile observation is compensated for at the corresponding time. Finally, the corrected temperature values ​​of each sampling temperature of the mobile observation (temperature at different sampling time points and locations) are obtained (equivalent to different sampling locations at the same sampling time point).

[0067] The calibration process includes: using the background temperature at any time point in the background temperature sequence as a reference value, calculating the temperature difference between the background temperature at each time point in the background temperature sequence and the reference value to obtain a time-temperature deviation sequence; and compensating the moving temperature sequence based on the time-temperature deviation sequence to obtain the calibrated moving temperature sequence at any time point.

[0068] For example, each temperature value in the moving temperature sequence is corrected based on the following formula to obtain the corrected moving temperature value at a certain time point:

[0069]

[0070] Where, θ t ' represents the correction value of the t-th temperature in the moving temperature sequence at a certain time point; θ t This represents the t-th moving temperature data point in the moving temperature sequence. This is the t-th temperature data point in the background temperature sequence. Let i be the temperature reference value selected at a certain time point (time point i) in the background temperature sequence, where i = 1, 2, ..., N, and N is the total number of temperature samples in the time series. Using the above method, corrected data for each time point in the moving temperature sequence within the monitoring period can be obtained.

[0071] Specifically, in step S3, the key point temperature sequence (observation data of all key observation points) is input into the microclimate software to extract the initial temperature distribution map of each time point of the street to be tested.

[0072] For example, the initial temperature distribution at a certain time point obtained using CFD software is shown in the following figure. Figure 3 As shown, to verify the temperature simulation effect, data from nine fixed monitoring points set up by the simulation software along the actual observation route within the sample block were extracted and compared with the actual temperature data obtained through mobile observation and related corrections for a certain period. In most cases, the fit was very good, with an error ≤0.5℃ after mobile data correction; however, some local differences in fit were observed. To find the root cause of the data fitting discrepancies, the locations of the monitoring points with fitting differences were located, and the video recordings from the mobile camera carried by the observer during the mobile observation were reviewed and compared with the GPS route records from the handheld global positioning system. The results showed that the locations where the fit between the simulated and measured data differed were in areas with large surrounding buildings, including large commercial complexes and large wholesale markets. During the actual measurement, these areas experienced high pedestrian and vehicular traffic, resulting in varying degrees of traffic congestion. Furthermore, comparing the measured data along the video recordings also revealed similar patterns in areas where the measured air temperature distribution data showed peaks.

[0073] It is evident that the discrepancy between the simulation and measured results in a few isolated areas is primarily due to anthropogenic heat generated by numerous buildings and traffic within the street block. Furthermore, the rapid, short-term temperature increases observed in the measured data are also caused by substantial localized anthropogenic heat emissions. To address these issues, this invention introduces a dynamic heat compensation (dynamic heat source correction simulation) process. Based on the calibrated moving temperature sequence, the error in the initial temperature distribution map is analyzed, and a dynamic heat source correction simulation is performed, specifically including:

[0074] S31. Identify the temperature difference between the initial temperature distribution map at any time point and the corresponding region in the calibrated moving temperature sequence at the corresponding time point, obtain the congestion index and free-flow vehicle speed of the region where the temperature difference is greater than a preset threshold, and obtain the additional heat flux of the corresponding region based on the congestion index and free-flow vehicle speed using the traffic congestion index heat flux model.

[0075] In reality, traffic congestion generates additional heat. Traditional models assume that vehicle heat generation only comes from engine efficiency losses. However, in actual traffic congestion, frequent starts and stops lead to additional heat generation, meaning that frequent starts and stops increase kinetic energy loss. Therefore, engine heat dissipation and starting / braking heat are used as the vehicle's heat dissipation coefficient, Q. T The specific steps for constructing a traffic congestion index heat flux model include:

[0076] S311. Based on the total resistance that the vehicle needs to overcome while driving, obtain the corresponding resistance power, and based on the resistance power, obtain the engine cooling power;

[0077] For example, the total resistance that a vehicle needs to overcome when driving mainly includes rolling resistance F. r and air resistance F v Then the total resistance F t Represented as:

[0078]

[0079] Among them, C r ρ is the rolling resistance coefficient, m is the vehicle mass (kg), and g is the acceleration due to gravity (9.8 m / s²). 2 ), ρ is the air density (1.225 kg / m³). 3 ), C d Where A is the drag coefficient and A is the vehicle's frontal area (m²). 2 Based on this, the vehicle's drag power P is obtained. d , is represented as:

[0080]

[0081] When the vehicle is traveling at a constant speed, all effective power overcomes the resistance, and the effective power of the engine is expressed as: P e =P d ,

[0082] This leads to the engine's heat dissipation power (fuel combustion power minus effective power), i.e.:

[0083]

[0084] Among them, P f This refers to the engine's fuel combustion power. This refers to engine efficiency (typically 20%-30%).

[0085] Substituting the resistance power, the engine cooling power Q1 is expressed as:

[0086]

[0087] S312. Based on the vehicle's driving kinetic energy loss, construct a vehicle start-stop heat model to obtain the corresponding start-stop heat.

[0088] For example, from the kinetic energy formula It is known that the kinetic energy loss during a single start-stop cycle is Introducing the start-stop frequency λ (number of start-stops per unit distance), the vehicle start-stop thermal model is as follows:

[0089]

[0090] Where Q2 is the heat generated during vehicle start-up and shutdown; Δv is the speed change during vehicle start-up and shutdown.

[0091] S313. Based on the engine's heat dissipation power and start-stop heat, and combined with the relationship between the congestion index and free-flow vehicle speed, the traffic congestion index heat flux model is obtained.

[0092] For example, vehicle heat dissipation Q T Represented as:

[0093]

[0094] The Congestion Index (CI), which measures the degree of road congestion, is defined as follows:

[0095] Among them, v f Let v be the free-flow speed (speed when traffic is flowing smoothly, i.e., the speed limit on the road, in m / s), and v be the actual speed (m / s). According to the definition of the congestion index, ... Incorporate vehicle cooling Q T From the expression, we get:

[0096]

[0097] The simplified representation of the traffic congestion index heat flux model is as follows:

[0098]

[0099] Among them, Q T For the equivalent additional heat flux; v f Where C is the free-flow vehicle speed; CI is the traffic congestion index; K1, K2, and K3 are the preset rolling resistance coefficient, start-stop coefficient, and air resistance coefficient, respectively, and K1 = C. r ·m·g, Based on statistical data, relevant parameters such as the vehicle's frontal area, mass, and starting speed are estimated, and then K1, K2, and K3 are preset.

[0100] S32. Add the additional heat flux as a volume source to the microclimate software, and perform a correction simulation based on the key point temperature corresponding to any given time point until the temperature difference meets the requirements, thereby obtaining the corrected temperature distribution map for that given time point, and thus obtaining the outdoor environmental temperature simulation results for the monitoring period. The outdoor environmental temperature simulation results include the corrected temperature distribution maps for each time point.

[0101] For example, the simulation output is calibrated using the moving temperatures at corresponding time points as a benchmark. Areas with significant differences between simulation and actual measurements (e.g., temperature difference > 2℃) are identified. Based on the GPS coordinates and actual measurement time of these areas, the corresponding congestion index and free-flow vehicle speed are obtained from a traffic big data platform. An additional heat flux is calculated using a pre-set traffic congestion index heat flux model. Based on this additional heat flux, road vehicle congestion heat is artificially added to the CFD simulation software through custom source term adjustments. An updated temperature distribution map is obtained after simulation. The error of this distribution map is analyzed again until the requirements are met, resulting in a corrected temperature distribution map for the corresponding time point.

[0102] By introducing traffic big data in the above way, the system can achieve wide-area, near real-time monitoring of dynamic heat sources during typical periods such as morning and evening peak hours without relying on manual video collection and analysis. The technical solution is easier to replicate and promote.

[0103] Furthermore, microclimate data also includes wind speed and direction sequences, particulate pollutant (such as PM2.5) sequences, etc. After adding the corresponding time-based additional heat flux as a volume source to the microclimate software, and combining it with the wind speed and direction sequences collected at the corresponding time points, the outdoor environmental wind field simulation results are obtained, such as... Figure 4 As shown, by inputting particulate pollutant sequences into microclimate software, the diffusion and deposition processes of particulate matter in urban spaces can also be simulated.

[0104] Compared with existing technologies, this embodiment provides an outdoor microclimate monitoring method for urban blocks. It utilizes dual-source data (fixed observation and mobile observation) for collaborative correction. On the one hand, it performs temporal compensation on mobile data and spatial calibration on fixed-point data to achieve large-scale spatiotemporal synchronization. On the other hand, it introduces dynamic anthropogenic heat source compensation. Ultimately, it effectively solves the industry pain points of traditional monitoring, such as difficulty in wide-area coverage, low accuracy, and insufficient dynamic response. It provides low-cost and high-precision technical support for urban thermal environment assessment and planning management.

[0105] Example 2

[0106] Another specific embodiment of the present invention discloses an outdoor microclimate monitoring system for urban blocks, comprising:

[0107] An environmental monitoring unit is used to collect microclimate data of the urban blocks to be monitored using one background observation point, several key observation points, and a moving observation point; the microclimate data includes background temperature sequences, key temperature sequences, and moving temperature sequences within the monitoring period.

[0108] The moving data calibration unit is used to calibrate the moving temperature sequence by using the temperature of each sampling time point in the background point temperature sequence as a reference and correcting the time difference to obtain the calibrated moving temperature sequence at each time point.

[0109] The dynamic simulation unit is used to input the key point temperature sequence into the microclimate software to obtain the initial temperature distribution map at each time point. Combined with the calibrated moving temperature sequence at the corresponding time point, the initial temperature field distribution map is dynamically heat source corrected and simulated to obtain the outdoor environmental temperature simulation results for the monitoring period. The outdoor environmental temperature simulation results include the corrected temperature distribution map at each time point.

[0110] A display terminal is used to output the simulated outdoor ambient temperature results;

[0111] The server is used to receive and store the data collected by the environmental monitoring unit.

[0112] The system can perform outdoor microclimate monitoring according to any of the methods described in Embodiment 1. Related aspects can be referenced from each other, but are not repeated in this embodiment.

[0113] Compared with existing technologies, the outdoor microclimate monitoring system for urban blocks provided in this embodiment, through the interaction of environmental monitoring units, mobile data calibration units, dynamic human thermal compensation units, physical simulation units and display terminals, ultimately achieves the output of environmental parameters with meter-level grid accuracy within a 1 square kilometer block area with no more than 10 fixed-point observations and one mobile route. Compared with the traditional fixed-point monitoring scheme, it saves 60% of equipment investment. The output data can be directly used for urban ventilation corridor planning and heat island mitigation projects, providing direct and quantitative decision-making basis for refined urban management.

[0114] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0115] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for monitoring outdoor microclimate in urban blocks, characterized in that, Includes the following steps: Microclimate data of the urban blocks under test were collected using one background observation point, several key observation points, and a moving observation point. The microclimate data included background temperature sequences, key temperature sequences, and moving temperature sequences within the monitoring period. Using the temperature at each sampling time point in the background temperature sequence as a reference, the moving temperature sequence is calibrated by time difference correction to obtain the calibrated moving temperature sequence at each time point. The key point temperature sequence is input into the microclimate software to obtain the initial temperature distribution map at each time point. Combined with the calibrated moving temperature sequence at the corresponding time point, dynamic heat source correction simulation is performed on each initial temperature field distribution map to obtain the outdoor environmental temperature simulation results for the monitoring period. The outdoor environmental temperature simulation results include the corrected temperature distribution map at each time point.

2. The method according to claim 1, characterized in that, Obtaining the corrected temperature distribution map at any given time point includes: Identify the temperature difference between the initial temperature distribution map at any given time point and the corresponding region in the calibrated moving temperature sequence at the corresponding time point, obtain the congestion index and free-flow vehicle speed of the region where the temperature difference is greater than a preset threshold, and obtain the additional heat flux of the corresponding region based on the congestion index and free-flow vehicle speed using the traffic congestion index heat flux model. The additional heat flux is added as a volume source to the microclimate software, and the simulation is corrected by combining the temperature of the key point corresponding to any given time point until the temperature difference meets the requirements, thus obtaining the corrected temperature distribution map for any given time point.

3. The method according to claim 2, characterized in that, Obtaining the calibrated moving temperature sequence at any given time point includes: Using the temperature at any time point in the background temperature sequence as a reference value, the temperature difference between the background temperature at each time point in the background temperature sequence and the reference value is calculated to obtain a time-temperature deviation sequence; the moving temperature sequence is compensated based on the time-temperature deviation sequence to obtain the calibrated moving temperature sequence at any time point.

4. The method according to claim 2, characterized in that, The traffic congestion index heat flux model is obtained based on the following process: Based on the total resistance that the vehicle needs to overcome while driving, the corresponding resistance power is obtained, and based on the resistance power, the engine cooling power is obtained. Based on the kinetic energy loss of the vehicle, a vehicle start-stop heat model is constructed to obtain the corresponding start-stop heat. Based on the engine's heat dissipation power and start-stop heat, and combined with the relationship between the congestion index and free-flow vehicle speed, the heat flux model of the traffic congestion index is obtained.

5. The method according to claim 4, characterized in that, The expression for the traffic congestion index heat flux model is as follows: Among them, Q T For additional heat flux; v f denoted as , where is the free-flow vehicle speed of the urban street block to be tested; CI is the traffic congestion index; and K1, K2, and K3 are the preset rolling resistance coefficient, start-stop coefficient, and air resistance coefficient, respectively.

6. The method according to any one of claims 2-5, characterized in that, The coordinates and corresponding measured times of areas where the temperature difference is greater than a preset threshold are obtained, and the congestion index and free-flow vehicle speed of the corresponding area and time are obtained using a traffic big data platform.

7. The method according to claim 6, characterized in that, The microclimate data also includes wind speed and direction sequences. The additional heat flux is added as a volume source to the microclimate software, and combined with the wind speed and direction sequences collected at the corresponding time points, the outdoor environmental wind field simulation results are obtained.

8. The method according to claim 1, characterized in that, The background observation point is set up in an open area, and the moving observation point travels along a pre-set observation route to collect the microclimate data. The equipment at each observation point is kept highly consistent, and the sampling time is kept consistent.

9. An outdoor microclimate monitoring system for urban blocks, characterized in that, include: An environmental monitoring unit is used to collect microclimate data of the urban blocks to be monitored using one background observation point, several key observation points, and a moving observation point; the microclimate data includes background temperature sequences, key temperature sequences, and moving temperature sequences within the monitoring period. The moving data calibration unit is used to calibrate the moving temperature sequence by using the temperature of each sampling time point in the background point temperature sequence as a reference and correcting the time difference to obtain the calibrated moving temperature sequence at each time point. The dynamic simulation unit is used to input the key point temperature sequence into the microclimate software to obtain the initial temperature distribution map at each time point. Combined with the calibrated moving temperature sequence at the corresponding time point, the initial temperature field distribution map is dynamically heat source corrected and simulated to obtain the outdoor environmental temperature simulation results for the monitoring period. The outdoor environmental temperature simulation results include the corrected temperature distribution map at each time point.

10. The system according to claim 9, characterized in that, The dynamic simulation unit obtains the corrected temperature distribution map at any given time point based on the following steps: Identify the temperature difference between the initial temperature distribution map at any given time point and the corresponding region in the calibrated moving temperature sequence at the corresponding time point, obtain the congestion index and free-flow vehicle speed of the region where the temperature difference is greater than a preset threshold, and obtain the additional heat flux of the corresponding region based on the congestion index and free-flow vehicle speed using the traffic congestion index heat flux model. The additional heat flux is added as a volume source to the microclimate software, and the simulation is corrected by combining the temperature of the key point corresponding to any given time point until the temperature difference meets the requirements, thus obtaining the corrected temperature distribution map for any given time point.

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