Urban low-carbon cooperative regulation and control method and system based on multi-source data

Abstract

The invention discloses an urban low-carbon cooperative regulation and control method and system based on multi-source data, and relates to the technical field of low-carbon cooperative regulation and control, and the main scheme is as follows: judging whether the comprehensive carbon emission of an urban region meets the standard or not according to the comprehensive carbon emission, and executing a regulation and control strategy in the energy field when the comprehensive carbon emission does not meet the standard; judging whether the annual runoff control rate of the urban area meets the standard or not according to the annual runoff control rate, and executing a regulation and control strategy of the building field if the annual runoff control rate does not meet the standard; calculating full life cycle carbon emission of different types of LID facilities according to the carbon emission data of the LID facilities; judging whether the LID facilities of the urban area meet the standard or not according to the full-life-cycle carbon emission, and executing an LID full-cycle regulation and control strategy if the LID facilities of the urban area do not meet the standard; after the corresponding regulation and control strategy is selected, effect evaluation of the regulation and control strategy is carried out regularly, and the execution effect of the regulation and control strategy is judged. The problem that a traditional method is single in data dimension is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of low-carbon collaborative regulation, and specifically to a method and system for urban low-carbon collaborative regulation based on multi-source data. Background Art

[0002] With the intensification of global climate change and the promotion of the "dual carbon" goal, cities, as the core carriers of carbon emissions, their low-carbon collaborative regulation technologies have become the strategic focus of smart city construction. Existing urban low-carbon collaborative regulation methods have shown application prospects in fields such as energy structure optimization, green building promotion, and ecological facility construction. For example, reducing industrial energy consumption through smart grids and optimizing building energy efficiency using BIM technology.

[0003] However, there is strong coupling in urban carbon emissions in links such as energy consumption, building drainage, and ecological facility operation and maintenance. It is difficult to achieve the system optimum with single-field emission reduction.

[0004] Therefore, it is urgent to construct a cross-field collaborative regulation system driven by multi-source data to break the governance dilemma of "reducing emissions while increasing emissions" of carbon emissions. Summary of the Invention

[0005] (1) Technical Problems to be Solved

[0006] Aiming at the deficiencies of the existing technology, the present invention provides a method for urban low-carbon collaborative regulation based on multi-source data, which at least solves the problems of single evaluation method and lack of comprehensive evaluation in the existing technology, resulting in poor regulation ability.

[0007] (2) Technical Solutions

[0008] To achieve the above object, the present invention is realized through the following technical solutions: A method for urban low-carbon collaborative regulation based on multi-source data, including:

[0009] Step 1: Obtain energy consumption data, analyze the comprehensive carbon emissions within the urban area based on the energy consumption data, and judge whether the comprehensive carbon emissions of the urban area meet the standard according to the comprehensive carbon emissions. When they do not meet the standard, execute the regulation strategy in the energy field;

[0010] Step 2: Obtain meteorological data, calculate the annual runoff control rate according to the meteorological data, and judge whether the annual runoff control rate of the urban area meets the standard according to the annual runoff control rate. When they do not meet the standard, execute the regulation strategy in the building field;

[0011] Step 3: Obtain the carbon emission data of LID facilities, calculate the life-cycle carbon emissions of different types of LID facilities according to the carbon emission data of LID facilities; and judge whether the LID facilities in the urban area meet the standard according to the life-cycle carbon emissions. When they do not meet the standard, execute the LID full-cycle regulation strategy;

[0012] Step 4: After selecting the corresponding regulation strategy according to the judgment results of Steps 1 to 3, regularly evaluate the effect of the regulation strategy to judge the implementation effect of the regulation strategy.

[0013] In the above preferred scheme of the urban low-carbon collaborative regulation method based on multi-source data, the formula for calculating the comprehensive carbon emissions in the urban area based on energy consumption data is as follows:

[0014]

[0015] Where: ZH represents the comprehensive carbon emissions; E i represents the total consumption of the i-th type of energy; EF i represents the carbon emission factor of the i-th type of energy; V j represents the energy consumption of the j-th type of vehicle; EC j represents the carbon emission factor of the energy consumed by the j-th type of vehicle; EQ k，i represents the consumption of the i-th type of energy by the K-th enterprise; i represents the serial number of the energy type; n is the total number of energy types; EC j represents the carbon emission factor of the energy consumed by the j-th type of vehicle; α1 represents the weight coefficient of the total energy consumption; j represents the serial number of the traffic power category, m represents the total number of traffic power categories; α2 represents the weight coefficient of the energy consumption of vehicles; α3 represents the weight coefficient of the energy consumption of enterprises.

[0016] In the above preferred scheme of the urban low-carbon collaborative regulation method based on multi-source data, the method for judging whether the comprehensive carbon emissions in the urban area meet the standard according to the comprehensive carbon emissions is: set a standard threshold for the comprehensive carbon emissions, compare the comprehensive carbon emissions with the standard threshold for the comprehensive carbon emissions. When the comprehensive carbon emissions ≥ the standard threshold for the comprehensive carbon emissions, it is determined that the comprehensive carbon emissions in the urban area do not meet the standard. When the comprehensive carbon emissions < the standard threshold for the comprehensive carbon emissions, it is determined that the comprehensive carbon emissions in the urban area meet the standard;

[0017] When the comprehensive carbon emissions do not meet the standard, implement the regulation strategy in the energy field; specifically:

[0018] Adjust the proportion of different energy structures, increase the use proportion of renewable energy, and reduce the use proportion of non-renewable energy;

[0019] Calculate the carbon emissions of different enterprises, and compile a list of enterprise carbon emissions rankings. Screen out the enterprises with the highest carbon emissions rankings, implement real-time monitoring of the energy consumption of the enterprises, achieve dynamic supervision of carbon emissions, and check the equipment that does not meet the emission standards in the enterprises.

[0020] In the preferred embodiment of the above-mentioned urban low-carbon collaborative regulation method based on multi-source data, the annual runoff control rate is calculated according to meteorological data, and the formula is as follows:

[0021]

[0022] Among them, KZ represents the annual runoff control rate; VRa y represents the rainfall of the y-th return period; VRn y represents the runoff of the y-th return period; P y represents the time period of the y-th return period; y represents the serial number of the return period, L represents the number of return periods; S represents the total area of the urban area; h y represents the rainfall intensity of the y-th return period.

[0023] In the preferred embodiment of the above-mentioned urban low-carbon collaborative regulation method based on multi-source data, the method for judging whether the annual runoff control rate of the urban area meets the standard according to the annual runoff control rate is as follows: set the standard threshold of the runoff control rate, compare the annual runoff control rate with the standard threshold of the runoff control rate. When the annual runoff control rate < the standard threshold of the runoff control rate, it is determined that the runoff control rate of the urban area does not meet the standard. When the annual runoff control rate ≥ the standard threshold of the runoff control rate, it is determined that the runoff control rate of the urban area meets the standard;

[0024] When the runoff control rate does not meet the standard, the regulation strategy in the building field is executed; specifically:

[0025] Divide the urban area into several sub-areas according to the grid division method, count the installation ratio of LID facilities, set the LID ratio threshold, and compare the installation ratio of LID facilities in each area with the LID ratio threshold respectively. If it is lower than the LID ratio threshold, add the corresponding LID facilities in this area;

[0026] Count the greening rate of each sub-area, set the greening rate threshold, and compare the greening rate of each area with the ratio with the greening rate threshold respectively. If it is lower than the greening rate threshold, increase the green area in the area.

[0027] In the preferred embodiment of the above-mentioned urban low-carbon collaborative regulation method based on multi-source data, the full-life cycle carbon emissions are calculated according to the carbon emission data of LID facilities, and the formula is as follows:

[0028]

[0029] Among them, ZQP represents the full-life cycle carbon emissions of LID facilities; cs g represents the emissions of the g-th type of LID facility in the construction stage; om gRepresents the emissions of the g-th type of LID facility during the operation and maintenance phase; ds g Represents the emissions of the g-th type of LID facility during the disassembly phase; g represents the serial number of the LID facility category, and A represents the total number of LID facility categories; ef g Represents the total carbon emissions of the z-th type of pollutant after being treated by the g-th type of LID facility; em z Represents the carbon emission factor of the z-th type of pollutant; z represents the serial number of the pollutant category, and B represents the total number of pollutant categories.

[0030] In the above preferred solution of the urban low-carbon collaborative regulation method based on multi-source data, the method for judging whether the LID facilities in the urban area meet the standards according to the life-cycle carbon emissions is as follows:

[0031] Set the life-cycle carbon emission threshold, compare the life-cycle carbon emissions with the life-cycle carbon emission threshold. When the life-cycle carbon emissions ≥ the life-cycle carbon emission threshold, it is determined that the comprehensive carbon emissions of the LID facilities in the urban area do not meet the standards. When the life-cycle carbon emissions < the life-cycle carbon emission threshold, it is determined that the carbon emissions of the LID facilities in the urban area meet the standards;

[0032] When the life-cycle carbon emissions do not meet the standards, it is necessary to implement the LID full-cycle regulation strategy, specifically:

[0033] In the construction phase, use recycled aggregates to replace traditional concrete and adopt prefabricated modular bioretention facilities;

[0034] In the operation and maintenance phase, install Internet of Things sensors to monitor the operation status of the facilities in real time and reduce the number of maintenance; equip the LID facilities with renewable energy power supply devices;

[0035] In the disassembly phase: recycle and reuse the LID facilities in the disassembly phase.

[0036] In the above preferred solution of the urban low-carbon collaborative regulation method based on multi-source data, after implementing the regulation strategy in the energy field, regularly obtain the renewable energy consumption ratio, the proportion of new energy vehicle ownership, and the traffic carbon emissions before and after implementing the policy, and calculate the comprehensive change rate one of all parameters; the formula is as follows:

[0037]

[0038] Among them, BHL represents the comprehensive change rate I before and after the regulation strategy in the energy field; NYQ represents the proportion of renewable energy before the regulation strategy; NYH represents the proportion of renewable energy after the regulation strategy; BYQ represents the proportion of the ownership of new energy vehicles before the regulation strategy, BYH represents the proportion of the ownership of new energy vehicles after the regulation strategy, JTQ represents the traffic carbon emissions before the regulation strategy, and JTH represents the traffic carbon emissions after the regulation strategy;

[0039] After implementing the regulation strategy in the building field, regularly obtain the LID facility coverage rate, pipe section overload rate, and greening coverage rate before and after implementing the policy, and calculate the comprehensive change rate II of all parameters; the formula is as follows:

[0040]

[0041] Among them, BHR represents the comprehensive change rate II before and after the regulation strategy in the building field; DFQ represents the LID facility coverage rate before the regulation strategy; DFH represents the LID facility coverage rate after the regulation strategy; GDQ represents the pipe overload rate before the regulation strategy, GDH represents the pipe overload rate after the regulation strategy, LHQ represents the greening coverage rate before the regulation strategy, and LHH represents the greening coverage rate after the regulation strategy;

[0042] After implementing the LID full-cycle regulation strategy, regularly obtain the recycled material substitution rate, renewable energy self-sufficiency rate, and waste recycling utilization rate before and after implementing the policy, and calculate the comprehensive change rate III of all parameters; the formula is as follows:

[0043]

[0044] Among them, BHR represents the comprehensive change rate III before and after the LID full-cycle regulation strategy; TDQ represents the recycled material substitution rate before the regulation strategy; TDH represents the recycled material substitution rate after the regulation strategy; ZJQ represents the renewable energy self-sufficiency rate before the regulation strategy, ZJH represents the renewable energy self-sufficiency rate after the regulation strategy, HSQ represents the waste recycling utilization rate before the regulation strategy, and HSH represents the waste recycling utilization rate after the regulation strategy.

[0045] In the above preferred scheme of the urban low-carbon collaborative regulation method based on multi-source data, the method for judging the implementation effect of the regulation strategy is:

[0046] Set the implementation evaluation threshold interval I, the implementation evaluation threshold interval II, and the implementation evaluation threshold interval III; compare the comprehensive change rate I, the comprehensive change rate II, and the comprehensive change rate III with the evaluation threshold interval I, the implementation evaluation threshold interval II, and the implementation evaluation threshold interval III respectively to judge the implementation effects of different adjustment strategies; specifically:

[0047] When the comprehensive change rate I conforms to the value range of the evaluation threshold interval I, it indicates that the regulation strategy in the energy field has good effects. When the comprehensive change rate I is lower than the lowest value of the value range of the evaluation threshold interval I, it indicates that the regulation strategy in the energy field has poor effects. When the comprehensive change rate I exceeds the highest value of the value range of the evaluation threshold interval I, it indicates that the regulation strategy in the energy field has excellent effects.

[0048] When the comprehensive change rate II conforms to the value range of the evaluation threshold interval II, it indicates that the regulation strategy in the building field has good effects. When the comprehensive change rate II is lower than the lowest value of the value range of the evaluation threshold interval II, it indicates that the regulation strategy in the building field has poor effects. When the comprehensive change rate II exceeds the highest value of the value range of the evaluation threshold interval II, it indicates that the regulation strategy in the building field has excellent effects.

[0049] When the comprehensive change rate III conforms to the value range of the evaluation threshold interval III, it indicates that the LID full-cycle regulation strategy has good effects. When the comprehensive change rate III is lower than the lowest value of the value range of the evaluation threshold interval III, it indicates that the LID full-cycle regulation strategy has poor effects. When the comprehensive change rate III exceeds the highest value of the value range of the evaluation threshold interval III, it indicates that the LID full-cycle regulation strategy has excellent effects.

[0050] (3) Beneficial effects

[0051] The present invention provides a method for urban low-carbon collaborative regulation based on multi-source data, having the following beneficial effects:

[0052] (1) By integrating multi-source heterogeneous data such as energy consumption data (industry, transportation, building, etc.), meteorological data, and LID facility full-life cycle data, a three-dimensional monitoring network of urban carbon emissions in the energy-building-ecological facility fields is constructed. This technical point solves the problem of single data dimension in traditional methods, enabling carbon emission assessment to cover direct emissions (energy consumption) and indirect emissions (facility construction and maintenance), and significantly improving the granularity and comprehensiveness of urban carbon emission monitoring.

[0053] (2) By setting a three-layer judgment standard of "comprehensive carbon emissions-runoff control rate-full-life cycle carbon emissions", a collaborative regulation mechanism triggered by multiple thresholds is established. This technical point breaks through the limitations of traditional single-field regulation and realizes the dynamic collaboration of energy optimization, building drainage system renovation, and LID facility upgrade.

[0054] (3) By constructing a carbon emission model of LID facilities covering the material production, construction, operation and maintenance, and demolition stages, the net carbon benefits of facilities such as permeable pavements and bioretention ponds are quantified; for the first time, life cycle assessment is combined with low-carbon urban regulation to solve the problem of difficult traceability of implicit carbon emissions of facilities. Description of the drawings

[0055] Figure 1 Schematic diagram of the steps of the urban low-carbon collaborative regulation method based on multi-source data of the present invention. Specific implementation manners

[0056] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] Embodiment 1

[0058] Please refer to Figure 1 , the present invention provides an urban low-carbon collaborative regulation method based on multi-source data, including:

[0059] Step 1: Obtain energy consumption data, analyze the comprehensive carbon emissions in the urban area based on the energy consumption data, and determine whether the comprehensive carbon emissions in the urban area meet the standards. When they do not meet the standards, implement the regulation strategy in the energy field.

[0060] Step 101: Obtain the total consumption of different energies during the evaluation period through the energy supply department, energy suppliers, and enterprise energy management systems. The types of different energies at least include natural gas, coal, oil, and renewable energies (such as solar energy, wind energy, etc.).

[0061] Step 102: Obtain the energy consumption of different types of transportation tools through the traffic management department, industry associations and research institutions, energy supply enterprises, and traffic operation-related enterprises. The types of different types of transportation tools at least include private cars, taxis, buses, and freight trucks with different fuel types, as well as subways, trains, etc.

[0062] Step 103: Obtain the energy consumption of different enterprises through the enterprise energy management system; among them, for the energy consumption of different enterprises, all types of energies consumed by them need to be calculated. For example, the coal, natural gas, and electricity consumed by the enterprise, etc.

[0063] It should be noted that the above data needs to be preprocessed by normalization. After eliminating the dimension, subsequent calculation steps are carried out.

[0064] In steps 101 - 103, by constructing a multi-source data acquisition network covering the energy supply department, traffic management department, and enterprise energy management system, full-dimensional coverage of energy consumption data is achieved. Using normalization preprocessing (such as uniformly converting different energy units to standard coal equivalent or carbon emission equivalent), the dimension difference is eliminated to ensure the scientificity and comparability of subsequent calculations; it can solve the problem that the unified carbon emission assessment method relies on a single data source (such as only counting industrial energy consumption), resulting in fragmented data dimensions and inconsistent dimensions. For example, gasoline consumption in the transportation field (unit: liter) and electricity consumption of enterprises (unit: kWh) cannot be directly added, causing deviation in the calculation of the total carbon emissions; in addition, the data is scattered in the energy supply department, traffic management department, and enterprise internal systems, making it difficult to achieve cross-departmental data integration and resulting in one-sided assessment results.

[0065] Step 104: Calculate the comprehensive carbon emissions within the urban area based on the consumption of different energies, the energy consumption of different types of transportation tools, and the energy consumption of different enterprises. The formula is as follows:

[0066]

[0067] Where: ZH represents the comprehensive carbon emissions; E i represents the total consumption of the i-th type of energy; EF i represents the carbon emission factor of the i-th type of energy; V j represents the energy consumption of the j-th type of transportation tool; EC j represents the carbon emission factor of the energy consumed by the j-th type of transportation tool; EQ k，i represents the consumption of the i-th type of energy by the K-th enterprise; i represents the serial number of the energy type; n is the total number of energy types, taking positive integer values; EC j represents the carbon emission factor of the energy consumed by the j-th type of transportation tool; j represents the serial number of the traffic power category, m represents the total number of traffic power categories, taking positive integer values; α1 represents the weight coefficient of the total energy consumption; α2 represents the weight coefficient of the energy consumption of transportation tools; α3 represents the weight coefficient of the energy consumption of enterprises.

[0068] In this step, a weighted calculation model based on weight coefficients is designed to dynamically adjust the contribution ratios of the total energy consumption, transportation emissions, and enterprise emissions. The weight coefficients can be configured differently according to the urban development stage (such as industry-dominated or service-dominated), solving the problem that existing carbon emission calculation models mostly use the simple addition method (such as total carbon emissions = industrial emissions + transportation emissions), ignoring the contribution differences of carbon emissions in different fields.

[0069] It should be noted that EF i and EC jIt can be obtained according to the carbon emission factor standards issued by the country or localities.

[0070] Step 105: Set the comprehensive carbon emission standard threshold, compare the comprehensive carbon emission with the comprehensive carbon emission standard threshold. When the comprehensive carbon emission ≥ the comprehensive carbon emission standard threshold, it is determined that the comprehensive carbon emission of the urban area does not meet the standard. When the comprehensive carbon emission < the comprehensive carbon emission standard threshold, it is determined that the comprehensive carbon emission of the urban area meets the standard.

[0071] It should be noted that the comprehensive carbon emission standard threshold can be adjusted in real time according to the specific regulations of the relevant urban departments, such as according to the corresponding standards for comprehensive carbon emissions in different historical time periods.

[0072] Step 106: When the comprehensive carbon emission does not meet the standard, implement the regulation strategy in the energy field; specifically:

[0073] Adjust the proportion of different energy structures, increase the proportion of renewable energy use, and reduce the proportion of non-renewable energy use;

[0074] Calculate the carbon emissions of different enterprises, and compile them into a carbon emission ranking table for enterprises. Screen out the enterprises with the top carbon emissions, such as the TOP10% high-emission enterprises, implement real-time monitoring of the energy consumption of the enterprises, achieve dynamic supervision of carbon emissions, and check the equipment that does not meet the emission standards in the enterprises.

[0075] Statistically analyze the proportion of vehicles of different fuel types, promote new energy vehicles, and increase the proportion of the ownership of new energy vehicles.

[0076] In this step, by increasing the proportion of renewable energy (such as the solar power generation proportion increasing from 10% to 25%), the baseline emissions are directly reduced; based on the carbon emission ranking table, real-time monitoring is implemented for the TOP10% high-emission enterprises (such as installing smart electricity meters and online carbon emission monitoring equipment), inefficient equipment is identified (such as replacing coal-fired boilers with waste heat recovery systems), and "one enterprise, one policy" emission reduction is achieved; by statistically analyzing the proportion of fuel vehicles, formulating new energy vehicle subsidy policies (such as increasing the charging pile coverage rate to 90%), and promoting the increase of the electrification rate of private cars; it can solve the problem of the extensive traditional energy regulation strategy.

[0077] This solution systematically solves problems such as data fragmentation, one-sided evaluation, and lagged regulation in traditional methods through multi-source data integration, dynamic weight models, elastic threshold determination, and precise strategy implementation.

[0078] Step Two: Obtain meteorological data, calculate the annual runoff control rate based on the meteorological data, and determine whether the annual runoff control rate of the urban area meets the standard according to the annual runoff control rate. When it does not meet the standard, implement the regulation strategy in the building field.

[0079] Step 201: Obtain meteorological data through the meteorological department or urban planning department, including at least the field rainfall amounts for different rainfall return periods, the runoff amounts generated for different rainfall return periods after setting up LID facilities, the rainfall intensities for different rainfall return periods, and the urban area.

[0080] It should be noted that the above data needs to be preprocessed by normalization. After eliminating the dimension, subsequent calculation steps are carried out.

[0081] Step 202: Calculate the annual runoff control rate based on the meteorological data. The calculation formula is as follows:

[0082]

[0083] Among them, KZ represents the annual runoff control rate; VRa y represents the rainfall amount for the y-th return period; VRn y represents the runoff amount for the y-th return period; P y represents the time period for the y-th return period; y represents the serial number of the return period, L represents the number of return periods, taking positive integers, and here it can also take the value of 3, corresponding to the 1-year return period, 3-year return period, and 5-year return period respectively; S represents the total area of the urban area; h y represents the rainfall intensity for the y-th return period.

[0084] By comprehensively analyzing the meteorological data and calculating the annual runoff control rate, the runoff control effect of the urban area can be evaluated more accurately. This method not only considers the rainfall amount and runoff amount, but also factors such as rainfall intensity and urban area, making the evaluation result more in line with the actual precipitation situation, improving the scientificity and accuracy of the evaluation, and solving the problem that the existing evaluation methods may not fully utilize meteorological data, resulting in inaccurate calculation of the annual runoff control rate and difficulty in accurately reflecting the runoff control effect of the urban area.

[0085] Step 203: Set the standard threshold for the runoff control rate, compare the annual runoff control rate with the standard threshold for the runoff control rate. When the annual runoff control rate < the standard threshold for the runoff control rate, it is determined that the runoff control rate of the urban area does not meet the standard. When the annual runoff control rate ≥ the standard threshold for the runoff control rate, it is determined that the runoff control rate of the urban area meets the standard.

[0086] It should be noted that the annual runoff control rate can be adjusted in real time according to the specific regulations of the urban relevant departments, such as according to the corresponding standards for the annual runoff control rate in different historical time periods.

[0087] Step 204: When the runoff control rate does not meet the standard, the regulation strategy in the construction field is executed; specifically:

[0088] Divide the urban area into several sub - areas by the grid division method, count the installation ratio of LID facilities, set the LID ratio threshold, and compare the installation ratio of LID facilities in each area with the LID ratio threshold respectively. If it is lower than the LID ratio threshold, add corresponding LID facilities in this area to improve the infiltration and retention capacity of rainwater, reduce surface runoff. For example, use permeable paving materials on urban roads and sidewalks to increase the infiltration capacity of rainwater; promote green roofs and rain gardens in newly built residential areas and commercial areas to retain and purify rainwater.

[0089] Count the greening rate of each sub - area, set the greening rate threshold, and compare the greening rate of each area with the threshold respectively. If it is lower than the greening rate threshold, increase the green area within the area, such as parks, green belts, etc. These green areas can absorb and retain rainwater and reduce runoff.

[0090] A rainwater collection system can also be implemented to collect rainwater for non - drinking purposes such as irrigation and flushing toilets. Improve the water - saving awareness of residents through education and publicity activities to reduce water waste, and formulate relevant policies and regulations to encourage and standardize the construction and maintenance of LID facilities.

[0091] By implementing regulatory strategies in the construction field, such as increasing LID facilities, raising the greening rate, and implementing a rainwater collection system, the infiltration and retention capacity of rainwater can be improved, and surface runoff can be reduced. For example, use permeable paving materials on urban roads and sidewalks to increase the infiltration capacity of rainwater; promote green roofs and rain gardens in newly built residential areas and commercial areas to retain and purify rainwater. These measures help to improve the runoff control rate in urban areas, reduce the risk of flood disasters, and solve the problem that existing regulatory strategies may lack pertinence and systematicness and are difficult to effectively improve the infiltration and retention capacity of rainwater and reduce surface runoff.

[0092] Step 3: Obtain the carbon emission data of LID facilities, calculate the life - cycle carbon emissions of different types of LID facilities based on the carbon emission data of LID facilities; and judge whether the LID facilities in the urban area meet the standards according to the life - cycle carbon emissions. When they do not meet the standards, implement the LID full - cycle regulatory strategy.

[0093] Step 301: Obtain the carbon emission data of different types of LID facilities through the environmental monitoring department, including at least: the carbon emissions of different LID facilities in the construction stage, the carbon emissions in the operation and maintenance stage, the carbon emissions in the facility disassembly stage, the carbon emissions of different pollutants after being treated by LID facilities, and the carbon emission factors of different pollutants.

[0094] It should be noted that the above data needs to be pre - processed by normalization. After eliminating the dimension, subsequent calculation steps are carried out.

[0095] Step 302: Calculate the life - cycle carbon emissions through the carbon emissions data of LID facilities. The formula is as follows:

[0096]

[0097] Among them, ZQP represents the life - cycle carbon emissions of LID facilities; cs g represents the emissions of the g - th type of LID facility in the construction stage; om g represents the emissions of the g - th type of LID facility in the operation and maintenance stage; ds g represents the emissions of the g - th type of LID facility in the disassembly stage; g represents the category serial number of LID facilities, A represents the total number of LID facility categories, and can take positive integer values; ef g represents the total carbon emissions of the z - th type of pollutant after being treated by the g - th type of LID facility; em z represents the carbon emission factor of the z - th type of pollutant; z represents the serial number of pollutant categories, B represents the total number of pollutant categories, and takes positive integer values.

[0098] It should be noted that pollutant categories include common pollutants in water, such as total suspended solids, total nitrogen, total phosphorus, and heavy metals, etc.

[0099] By comprehensively calculating the life - cycle carbon emissions of LID facilities, the environmental protection benefits of LID facilities can be evaluated more accurately, providing a scientific basis for urban planning and environmental management. This method helps to identify facilities and stages with high carbon emissions, so as to provide targeted improvement measures for carbon emission reduction. It solves the problem that the existing evaluation methods may not comprehensively consider the carbon emissions of LID facilities in different life - cycle stages, resulting in inaccurate evaluation of the environmental protection benefits of LID facilities.

[0100] Step 303: Set the life - cycle carbon emissions threshold, and compare the life - cycle carbon emissions with the life - cycle carbon emissions threshold. When the life - cycle carbon emissions ≥ the life - cycle carbon emissions threshold, it is determined that the comprehensive carbon emissions of LID facilities in the urban area do not meet the standard. When the life - cycle carbon emissions < the life - cycle carbon emissions threshold, it is determined that the carbon emissions of LID facilities in the urban area meet the standard.

[0101] By setting the life - cycle carbon emissions threshold, a clear standard can be provided for carbon emission control in the urban area, promoting the transformation of the city towards low - carbon development. This helps to improve the attention of urban planning and management departments to carbon emissions and promote the implementation of low - carbon technologies and policies.

[0102] Step 304: When the carbon emissions throughout the life cycle do not meet the standards, it is necessary to implement the LID full-cycle regulation strategy, specifically as follows:

[0103] In the construction stage, using recycled aggregates to replace traditional concrete can reduce the carbon emissions of permeable pavement; adopting prefabricated modular bioretention facilities can reduce the energy consumption of on-site construction machinery.

[0104] In the operation and maintenance stage, install Internet of Things sensors to monitor the operation status of facilities in real time, reducing the proportion of unnecessary maintenance times; equip LID facilities with renewable energy power supply devices, such as solar street lights or micro photovoltaic systems, to reduce the dependence of LID facilities on the power grid.

[0105] In the disassembly stage: Recycle and reuse the LID facilities in the disassembly stage to reduce the carbon emissions during the waste treatment process.

[0106] It should be noted that prefabricated modular bioretention facilities refer to prefabricating the functional components of bioretention facilities (such as plant planting layers, filter media layers, water storage layers, etc.) in the factory to form standardized modules, which are quickly assembled after being transported to the site.

[0107] By implementing the LID full-cycle regulation strategy in this step, the carbon emissions of LID facilities can be significantly reduced, improving their environmental protection benefits. For example, using recycled aggregates and prefabricated modular facilities can reduce carbon emissions in the construction stage; installing Internet of Things sensors and supporting renewable energy power supply devices can reduce energy consumption and carbon emissions in the operation and maintenance stage; recycling and reusing the facilities in the disassembly stage can reduce carbon emissions during the waste treatment process, solving the problem that the existing regulation strategies may lack pertinence and systematicness and are difficult to effectively reduce the carbon emissions of LID facilities.

[0108] Step Four: After selecting the corresponding regulation strategy according to the judgment results of Steps One to Three, regularly evaluate the effect of the regulation strategy to judge the implementation effect of the regulation strategy.

[0109] Step 401: After implementing the regulation strategy in the energy field, regularly obtain the proportion of renewable energy consumption, the proportion of new energy vehicle ownership, and the traffic carbon emissions before and after implementing the policy, and calculate the comprehensive change rate one of all parameters; the formula is as follows:

[0110]

[0111] Among them, BHL represents the comprehensive change rate before and after the regulatory strategy in the energy field; NYQ represents the proportion of renewable energy before the regulatory strategy; NYH represents the proportion of renewable energy after the regulatory strategy; BYQ represents the proportion of new energy vehicles before the regulatory strategy, BYH represents the proportion of new energy vehicles after the regulatory strategy, JTQ represents the transportation carbon emissions before the regulatory strategy, and JTH represents the transportation carbon emissions after the regulatory strategy.

[0112] It should be noted that the calculation method for the proportion of renewable energy is: Renewable energy consumption ratio = (Renewable energy consumption / Total energy consumption) × 100%. The consumption of renewable energy (such as solar energy, wind energy, hydropower, etc.) and total energy consumption data can be obtained from the energy statistics department; the calculation method for the proportion of new energy vehicle ownership is: New energy vehicle ownership ratio = (Number of new energy vehicles / Total number of vehicles) × 100%, which can be obtained through the annual statistical report released by the transportation management department; the calculation method for transportation carbon emissions is: Transportation carbon emissions = Σ(Fuel consumption of different types of vehicles × Corresponding carbon emission factor), which can be obtained by integrating the energy consumption statistics of the transportation department, the operation data of logistics companies, or through data acquisition methods such as on-board OBD equipment.

[0113] Integrate the proportion of renewable energy, the number of new energy vehicles and transportation carbon emissions, and quantify the synergistic effect of energy structure optimization and transportation emission reduction.

[0114] It should be noted that after obtaining the above data, the data are first normalized and preprocessed to eliminate the dimensions of different parameters before formula calculations are performed.

[0115] Step 402: After the control strategy for the building field is implemented, the LID facility coverage rate, pipe section overload rate and green coverage rate before and after the policy is implemented are regularly obtained, and the comprehensive change rate of all parameters is calculated; the formula based on which is as follows:

[0116]

[0117] Among them, BHR represents the comprehensive change rate before and after the regulation strategy in the building field; DFQ represents the LID facility coverage rate before the regulation strategy; DFH represents the LID facility coverage rate after the regulation strategy; GDQ represents the pipeline overload rate before the regulation strategy, GDH represents the pipeline overload rate after the regulation strategy, LHQ represents the green coverage rate before the regulation strategy, and LHH represents the green coverage rate after the regulation strategy.

[0118] It should be noted that the calculation method of the LID facility coverage rate is: LID facility coverage rate = (LID facility area / total urban area) × 100%, and the corresponding data can be obtained from the LID facility planning map and distribution map by the urban planning department; the calculation method of the pipeline overload rate is: pipeline overload rate = (actual flow - designed flow) / designed flow. The average value of the overload rates of all pipelines is taken as the actual pipeline overload rate, and the corresponding data can be obtained from the instantaneous flow of pipelines obtained through monitoring or model simulation during rainstorms, and the designed flow can be obtained from the drainage pipe network design specifications; the calculation method of the greening coverage rate is: greening coverage rate = (vertical projection area of vegetation / total area of the region) × 100%, and the corresponding data can be obtained by combining the green space census data of the urban gardening department.

[0119] Relate the LID facility coverage rate, the pipeline network overload rate, and the greening coverage rate to reveal the causal relationship between facility construction and drainage performance.

[0120] It should be noted that after obtaining the above data, the data are first preprocessed by normalization respectively to eliminate the dimensions of different parameters, and then the formula calculations are carried out.

[0121] Step 403: After implementing the LID full-cycle regulation strategy, regularly obtain the substitution rate of recycled materials, the self-sufficiency rate of renewable energy, and the waste recycling utilization rate before and after implementing the policy, and calculate the comprehensive change rate three of all parameters; the formula is as follows:

[0122]

[0123] Among them, BHR represents the comprehensive change rate three before and after the LID full-cycle regulation strategy; TDQ represents the substitution rate of recycled materials before the regulation strategy; TDH represents the substitution rate of recycled materials after the regulation strategy; ZJQ represents the self-sufficiency rate of renewable energy before the regulation strategy, ZJH represents the self-sufficiency rate of renewable energy after the regulation strategy, HSQ represents the waste recycling utilization rate before the regulation strategy, and HSH represents the waste recycling utilization rate after the regulation strategy.

[0124] It should be noted that: the calculation method of the substitution rate of recycled materials is: substitution rate of recycled materials = (usage amount of recycled materials / total usage amount of the same type of materials) × 100%; the procurement data of recycled materials (such as recycled aggregates, recycled plastics) can be obtained from construction and manufacturing enterprises and then statistically calculated; the calculation method of the self-sufficiency rate of renewable energy is: self-sufficiency rate of renewable energy = (number of LID facilities that can be self-sufficient / total number of LID facilities) × 100%; the corresponding data can be obtained through the LID facility planning map and by counting the energy consumption of LID facilities.

[0125] By setting the threshold of carbon emissions throughout the life cycle, a clear standard can be provided for carbon emission control in urban areas, promoting the transformation of cities towards low-carbon development. This helps to enhance the attention of urban planning and management departments to carbon emissions and facilitate the implementation of low-carbon technologies and policies. Introducing the substitution rate of recycled materials, the self-sufficiency rate of renewable energy, and the waste recovery rate, covering the entire chain of "material production - facility operation - demolition and recycling", and implementing the LID full-cycle regulation strategy can significantly reduce the carbon emissions of LID facilities and improve their environmental protection benefits. For example, using recycled aggregates and prefabricated modular facilities can reduce carbon emissions during the construction phase; installing Internet of Things sensors and supporting renewable energy power supply devices can reduce energy consumption and carbon emissions during the operation and maintenance phase; recycling and reusing facilities during the demolition phase can reduce carbon emissions during the waste treatment process.

[0126] It should be noted that after obtaining the above data, the data is first preprocessed by normalization to eliminate the dimensions of different parameters, and then the formula calculation is carried out.

[0127] Step 404: Set the first execution evaluation threshold range, the second execution evaluation threshold range, and the third execution evaluation threshold range; compare the first comprehensive change rate, the second comprehensive change rate, and the third comprehensive change rate with the first execution evaluation threshold range, the second execution evaluation threshold range, and the third execution evaluation threshold range respectively to judge the execution effects of different adjustment strategies; specifically:

[0128] When the first comprehensive change rate meets the value range of the first execution evaluation threshold range, it indicates that the regulation strategy in the energy field has good effects; when the first comprehensive change rate is lower than the lowest value of the value range of the first execution evaluation threshold range, it indicates that the regulation strategy in the energy field has poor effects; when the first comprehensive change rate exceeds the highest value of the value range of the first execution evaluation threshold range, it indicates that the regulation strategy in the energy field has excellent effects.

[0129] When the second comprehensive change rate meets the value range of the second execution evaluation threshold range, it indicates that the regulation strategy in the building field has good effects; when the second comprehensive change rate is lower than the lowest value of the value range of the second execution evaluation threshold range, it indicates that the regulation strategy in the building field has poor effects; when the second comprehensive change rate exceeds the highest value of the value range of the second execution evaluation threshold range, it indicates that the regulation strategy in the building field has excellent effects.

[0130] When the third comprehensive change rate meets the value range of the third execution evaluation threshold range, it indicates that the LID full-cycle regulation strategy has good effects; when the third comprehensive change rate is lower than the lowest value of the value range of the third execution evaluation threshold range, it indicates that the LID full-cycle regulation strategy has poor effects; when the third comprehensive change rate exceeds the highest value of the value range of the third execution evaluation threshold range, it indicates that the LID full-cycle regulation strategy has excellent effects.

[0131] It should be noted that the value ranges of the first execution evaluation threshold interval, the second execution evaluation threshold interval, and the third execution evaluation threshold interval can be adjusted according to the actual situation. For example, after calculating through historical data, calculate the natural growth rate of each indicator and the passive growth rate after implementing relevant policies in previous years, and then when setting the threshold interval, the minimum value should be higher than the natural growth rate, and the specific value can refer to the passive growth rate. For example, if the natural growth rate is 1% and the passive growth rate is 3%, then the minimum value of the threshold interval should be greater than 1%, and the maximum value is selected to be close to the passive growth rate, such as taking a value of 2%-4%, etc. Here, the first execution evaluation threshold interval is set to 5%-15%; the second execution evaluation threshold interval is set to 3%-10%; the third execution evaluation threshold interval is set to 8%-20%.

[0132] By regularly evaluating the effectiveness of the control strategy, the implementation situation of the strategy can be understood in a timely manner, and it can be judged whether the expected goal is achieved. This helps to discover problems and make adjustments in a timely manner, ensuring the effectiveness of the control strategy and improving the overall effect of urban low-carbon collaborative control. At the same time, this evaluation mechanism can also provide data support and experience reference for future policy formulation and adjustment.

[0133] The solution systematically solves the pain points of traditional methods such as one-sided indicators, rigid evaluation, and low data credibility by constructing a multi-dimensional evaluation, elastic threshold mechanism, and closed-loop feedback system. In practical applications, the misjudgment rate of the strategy effect is effectively reduced, and the cross-domain collaborative emission reduction efficiency is improved, providing a full-process technical closed-loop from "strategy implementation" to "effect iteration" for urban low-carbon governance.

[0134] The above-mentioned embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above-mentioned embodiments can be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution.

[0135] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0136] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application.

Claims

1. A method for urban low-carbon collaborative regulation based on multi-source data, characterized in that Including: Step 1: Obtain energy consumption data, analyze the comprehensive carbon emissions within the urban area based on the energy consumption data, and determine whether the comprehensive carbon emissions of the urban area meet the standards according to the comprehensive carbon emissions. When the standards are not met, implement the regulation strategy in the energy field; Step 2: Obtain meteorological data, calculate the annual runoff control rate based on the meteorological data, and determine whether the annual runoff control rate of the urban area meets the standards according to the annual runoff control rate. When the standards are not met, implement the regulation strategy in the building field; Step 3: Obtain the carbon emissions data of LID facilities, calculate the life-cycle carbon emissions of different types of LID facilities based on the carbon emissions data of LID facilities; and determine whether the LID facilities in the urban area meet the standards according to the life-cycle carbon emissions. When the standards are not met, implement the LID full-cycle regulation strategy; Step 4: After selecting the corresponding regulation strategy according to the judgment results of Steps 1 to 3, regularly evaluate the effect of the regulation strategy to judge the implementation effect of the regulation strategy.

2. The urban low-carbon collaborative regulation method based on multi-source data according to claim 1, wherein The formula for calculating the comprehensive carbon emissions within the urban area based on the energy consumption data is as follows: Among them: ZH represents the comprehensive carbon emissions; E i represents the total consumption of the i-th type of energy; EF i represents the carbon emission factor of the i-th type of energy; V j represents the energy consumption of the j-th type of vehicle; EC j represents the carbon emission factor of the energy type consumed by the j-th type of vehicle; EQ k，i represents the consumption of the i-th type of energy by the K-th enterprise; i represents the serial number of the energy type; n is the total number of energy types; EC j represents the carbon emission factor of the energy type consumed by the j-th type of vehicle; α1 represents the weight coefficient of the total energy consumption; j represents the serial number of the traffic power category, m represents the total number of traffic power categories; α2 represents the weight coefficient of the vehicle energy consumption; α3 represents the weight coefficient of the enterprise energy consumption.

3. The urban low-carbon collaborative regulation method based on multi-source data according to claim 2, characterized in that, The method for determining whether the comprehensive carbon emissions of the urban area meet the standards according to the comprehensive carbon emissions is: set a standard threshold for the comprehensive carbon emissions, compare the comprehensive carbon emissions with the standard threshold for the comprehensive carbon emissions. When the comprehensive carbon emissions ≥ the standard threshold for the comprehensive carbon emissions, it is determined that the comprehensive carbon emissions of the urban area do not meet the standards. When the comprehensive carbon emissions < the standard threshold for the comprehensive carbon emissions, it is determined that the comprehensive carbon emissions of the urban area meet the standards; When the comprehensive carbon emissions do not meet the standards, implement the regulation strategy in the energy field; specifically: Adjust the proportion of different energy structures, increase the use proportion of renewable energy, and reduce the use proportion of non-renewable energy; Calculate the carbon emissions of different enterprises, and compile a list of enterprise carbon emissions rankings. Screen out the enterprises with the highest carbon emissions rankings, implement real-time monitoring of energy consumption for the enterprises, achieve dynamic supervision of carbon emissions, and investigate the equipment that does not meet the emission standards in the enterprises.

4. The method for urban low-carbon collaborative regulation based on multi-source data according to claim 3, characterized in that The formula for calculating the annual runoff control rate based on the meteorological data is as follows: Among them, KZ represents the annual runoff control rate; VRa y represents the rainfall of the y-th return period; VRn y represents the runoff of the y-th return period; P y represents the time period of the y-th return period; y represents the serial number of the return period, L represents the number of return periods; S represents the total area of the urban area; h y represents the rainfall intensity of the y-th return period.

5. The method for urban low-carbon collaborative regulation based on multi-source data according to claim 4, wherein The method for determining whether the annual runoff control rate of the urban area meets the standards according to the annual runoff control rate is: set a standard threshold for the runoff control rate, compare the annual runoff control rate with the standard threshold for the runoff control rate. When the annual runoff control rate < the standard threshold for the runoff control rate, it is determined that the runoff control rate of the urban area does not reach the standards. When the annual runoff control rate ≥ the standard threshold for the runoff control rate, it is determined that the runoff control rate of the urban area reaches the standards; When the runoff control rate does not meet the standards, implement the regulation strategy in the building field; specifically: Divide the urban area into several sub-areas according to the grid division method, count the installation proportion of LID facilities, and set a LID proportion threshold. Compare the installation proportion of LID facilities in each area with the LID proportion threshold respectively. If it is lower than the LID proportion threshold, add corresponding LID facilities in this area; Count the greening rate of each sub-region, set the greening rate threshold, compare the greening rate and proportion of each region with the greening rate threshold respectively. If it is lower than the greening rate threshold, increase the green area within the region.

6. The urban low-carbon collaborative regulation method based on multi-source data according to claim 5, wherein, Calculate the life-cycle carbon emissions based on the carbon emission data of LID facilities. The formula is as follows: Among them, ZQP represents the total life-cycle carbon emissions of LID facilities; cs g represents the emissions of the g-th type of LID facility during the construction stage; om g represents the emissions of the g-th type of LID facility during the operation and maintenance stage; ds g represents the emissions of the g-th type of LID facility during the disassembly stage; g represents the category serial number of LID facilities, and A represents the total number of LID facility categories; ef g represents the total carbon emissions of the z-th type of pollutant after being treated by the g-th type of LID facility; em z represents the carbon emission factor of the z-th type of pollutant; z represents the serial number of pollutant categories, and B represents the total number of pollutant categories.

7. The urban low-carbon collaborative regulation method based on multi-source data according to claim 6, characterized in that The method for judging whether the LID facilities in urban areas meet the standards based on the life-cycle carbon emissions is as follows: Set the life-cycle carbon emission threshold, compare the life-cycle carbon emissions with the life-cycle carbon emission threshold. When the life-cycle carbon emissions ≥ the life-cycle carbon emission threshold, it is determined that the comprehensive carbon emissions of the LID facilities in the urban area do not meet the standards. When the life-cycle carbon emissions < the life-cycle carbon emission threshold, it is determined that the carbon emissions of the LID facilities in the urban area meet the standards; When the life-cycle carbon emissions do not meet the standards, it is necessary to implement the LID full-cycle regulation strategy, specifically as follows: In the construction stage, use recycled aggregates to replace traditional concrete and adopt prefabricated modular bioretention facilities; In the operation and maintenance stage, install Internet of Things sensors to monitor the operation status of the facilities in real time and reduce the number of maintenance; equip the LID facilities with renewable energy power supply devices; In the disassembly stage: recycle and reuse the LID facilities in the disassembly stage.

8. The urban low-carbon collaborative regulation method based on multi-source data according to claim 7, characterized in that After implementing the regulation strategy in the energy field, regularly obtain the proportion of renewable energy consumption, the proportion of new energy vehicle ownership, and the traffic carbon emissions before and after implementing the policy, and calculate the comprehensive change rate one of all parameters. The formula is as follows: Among them, BHL represents the comprehensive change rate one before and after the regulation strategy in the energy field; NYQ represents the proportion of renewable energy before the regulation strategy; NYH represents the proportion of renewable energy after the regulation strategy; BYQ represents the proportion of new energy vehicle ownership before the regulation strategy, BYH represents the proportion of new energy vehicle ownership after the regulation strategy, JTQ represents the traffic carbon emissions before the regulation strategy, and JTH represents the traffic carbon emissions after the regulation strategy; After implementing the regulation strategy in the building field, regularly obtain the LID facility coverage rate, pipe section overload rate, and greening coverage rate before and after implementing the policy, and calculate the comprehensive change rate two of all parameters. The formula is as follows: Among them, BHR represents the comprehensive change rate two before and after the regulation strategy in the building field; DFQ represents the LID facility coverage rate before the regulation strategy; DFH represents the LID facility coverage rate after the regulation strategy; GDQ represents the pipe section overload rate before the regulation strategy, GDH represents the pipe section overload rate after the regulation strategy, LHQ represents the greening coverage rate before the regulation strategy, and LHH represents the greening coverage rate after the regulation strategy; After implementing the LID full-cycle regulation strategy, regularly obtain the recycled material substitution rate, renewable energy self-sufficiency rate, and waste recycling utilization rate before and after implementing the policy, and calculate the comprehensive change rate three of all parameters. The formula is as follows: Among them, BHR represents the comprehensive change rate III before and after the LID full-cycle regulation strategy; TDQ represents the substitution rate of recycled materials before the regulation strategy; TDH represents the substitution rate of recycled materials after the regulation strategy; ZJQ represents the self-sufficiency rate of renewable energy before the regulation strategy, ZJH represents the self-sufficiency rate of renewable energy after the regulation strategy, HSQ represents the waste recycling utilization rate before the regulation strategy, and HSH represents the waste recycling utilization rate after the regulation strategy.

9. The method for urban low-carbon collaborative regulation based on multi-source data according to claim 8, characterized in that The method for judging the implementation effect of the regulation strategy is as follows: Set the execution evaluation threshold interval I, execution evaluation threshold interval II, and execution evaluation threshold interval III; compare the comprehensive change rate I, comprehensive change rate II, and comprehensive change rate III with the evaluation threshold interval I, execution evaluation threshold interval II, and execution evaluation threshold interval III respectively to judge the implementation effects of different adjustment strategies; specifically: When the comprehensive change rate I meets the value range of the evaluation threshold interval I, it indicates that the regulation strategy in the energy field has good effects; when the comprehensive change rate I is lower than the lowest value of the value range of the evaluation threshold interval I, it indicates that the regulation strategy in the energy field has poor effects; when the comprehensive change rate I exceeds the highest value of the value range of the evaluation threshold interval I, it indicates that the regulation strategy in the energy field has excellent effects; When the comprehensive change rate II meets the value range of the evaluation threshold interval II, it indicates that the regulation strategy in the building field has good effects; when the comprehensive change rate II is lower than the lowest value of the value range of the evaluation threshold interval II, it indicates that the regulation strategy in the building field has poor effects; when the comprehensive change rate II exceeds the highest value of the value range of the evaluation threshold interval II, it indicates that the regulation strategy in the building field has excellent effects; When the comprehensive change rate III meets the value range of the evaluation threshold interval III, it indicates that the LID full-cycle regulation strategy has good effects; when the comprehensive change rate III is lower than the lowest value of the value range of the evaluation threshold interval III, it indicates that the LID full-cycle regulation strategy has poor effects; when the comprehensive change rate III exceeds the highest value of the value range of the evaluation threshold interval III, it indicates that the LID full-cycle regulation strategy has excellent effects.

10. The urban low-carbon collaborative regulation system based on multi-source data is characterized in that A multi-source data-based urban low-carbon collaborative regulation method for implementing any one of the above claims 1-9.

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