CIM-based urban built environment carbon emission assessment method, calculation device and storage medium

Abstract

The invention provides a CIM-based urban built-up environment carbon emission assessment method, a calculation device and a storage medium, and the method comprises the following steps: S1, determining the assessment boundaries of urban built-up environment carbon emission, including a building boundary, a road boundary, a public lighting boundary and a greening boundary; s2, acquiring basic data of each evaluation boundary from the CIM model, wherein the basic data comprises geographic space data information, geometric data information and semantic data information; and S3, in combination with each evaluation boundary and the corresponding basic data, calculating the carbon emission of each evaluation boundary, and summarizing the carbon emission into total carbon emission. According to the method, the carbon emission of the urban built environment can be quickly and accurately calculated, and meanwhile, the time and space distribution of the carbon emission can be obtained, so that targeted energy-saving and emission-reducing measures are implemented, and the carbon emission of the city is effectively managed.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission calculation, and in particular to a carbon emission assessment method, a calculation device and a storage medium for a built-up urban environment based on CIM. Background Art

[0002] Cities accommodate more than 50% of the population, consume 2 / 3 of the energy and emit 70% of greenhouse gases, and are the key areas that determine sustainable development. Low-carbon sustainability is the driving force of urban development in the new era and an important connotation of future cities.

[0003] The built environment is the artificial physical entity that constitutes the city, and its carbon emissions account for a large proportion of the entire urban system. Objectively and scientifically evaluating the carbon emissions of the urban built environment and taking targeted optimization measures can effectively promote the green and sustainable development of the city.

[0004] Data collection is an important part of carbon emission calculation and assessment. Carbon emission assessment of urban built environment involves huge amount of data, which puts higher requirements on the speed and accuracy of data acquisition. With the development of information technology, the application of intelligent tools provides technical support for efficient data collection. CIM (City Information Model) is a comprehensive and integrated information model that can present and store massive data of the city. Summary of the invention

[0005] In order to solve the deficiencies in the above-mentioned prior art, the present invention provides a method for evaluating carbon emissions in the built environment of an city based on CIM, which combines the quantitative evaluation of urban carbon emissions with CIM to achieve fast and efficient data collection and accurate evaluation of the carbon emission level of the built environment of an city, comprising the following steps:

[0006] S1. Determine the assessment boundaries of urban built environment carbon emissions, including building boundaries, road boundaries, public lighting boundaries and green space boundaries.

[0007] S2. Obtain basic data of each assessment boundary from the CIM model, including geographic spatial data information, geometric data information and semantic data information.

[0008] S3. Combine each assessment boundary and its corresponding basic data to calculate the carbon emissions of each assessment boundary and summarize them into total carbon emissions.

[0009] Furthermore, the carbon emissions of the building boundary are calculated using the building carbon emission model. The calculation formula is:

[0010] B CO2 (t)=∑ i E build,i (t)×F i ;

[0011] Among them, B CO2 (t) is the building carbon emission in month t, in tCO2; E build,i (t) is the energy consumption of the building in the i-th category in month t; F i is the carbon emission factor of the i-th energy type.

[0012] Furthermore, the carbon emissions at the road boundary are calculated through the road traffic carbon emission model, including the public transportation carbon emission model and the private transportation carbon emission model.

[0013] The calculation formula of the public transportation carbon emission model is:

[0014] MB CO2 (t)=∑ j (∑ k Q k (t)×D k ×E j,k )×F j ;

[0015] Among them, MB CO2 (t) is the carbon emission of public transportation in month t, in tCO2; Q k (t) is the travel frequency of the kth type of public transportation in month t; D k is the travel distance of each trip of the kth type of public transportation, in km; E j,k F is the consumption index of the j-type energy per unit mileage of the k-th type of public transportation; j is the carbon emission factor of the jth type of energy.

[0016] The calculation formula of the private transportation carbon emission model is:

[0017] MP CO2 (t)=∑ j (∑ m L m ×V m (t)×E j )×F j ;

[0018] Among them, MP CO2 (t) is the carbon emission of private transportation in month t, in tCO2; L m is the length of the mth road section, in km; V m (t) is the number of private cars traveling on the mth road section in month t; E j F is the consumption index of j type of energy per unit mileage of private transportation; j is the carbon emission factor of the jth type of energy.

[0019] Furthermore, the carbon emissions of the public lighting boundary are calculated using the public lighting carbon emission model. The calculation formula is:

[0020] L CO2 (t)=∑ n N n ×P n ×H n (t)×d(t)×F E ;

[0021] Among them, L CO2 (t) is the carbon emission of public lighting in month t, in tCO2; N n is the number of lamps n; P n is the power of lamp n, in kW; H n (t) is the daily usage time of lamp n in month t, in hours / day; d(t) is the number of days in month t, in days; F E is the carbon emission factor of electricity, with the unit of tCO2 / kWh.

[0022] Furthermore, the carbon sequestration amount of the greening boundary is calculated by the green plant carbon absorption model, and the calculation formula is:

[0023] G CO2 (t)=∑ s A s ×LA s ×C CO2s (t) × d(t);

[0024] Among them, G CO2 (t) is the carbon fixation of green plants in month t, in tCO2; A s is the planting area of ​​plant s in the green space, in m2; LA s is the leaf area index of plant s; C CO2s (t) is the carbon fixation index of plant s in month t, in kg / (m2·day); d(t) is the day of month t, in days.

[0025] Furthermore, energy types include gasoline, diesel, natural gas and electricity, and their carbon emission factors are 2.03E-03~2.93E-03tCO2 / kg, 2.40E-03~2.45E-03tCO2 / kg, 1.56E-03~2.16E-03tCO2 / m3 and 2.11E-04~7.12E-04tCO2 / kWh respectively.

[0026] Furthermore, the energy consumption index includes 2.34E-01kg / km for large and medium-sized vehicles powered by gasoline, and 6.86E-02kg / km for small and micro-sized vehicles; 1.50E+00kWh / km for large and medium-sized vehicles powered by electricity, and 1.00E+00kWh / km for small and micro-sized vehicles; 2.12E-01kg / km for large and medium-sized vehicles powered by diesel, and 8.5E-02kg / km for small and micro-sized vehicles.

[0027] Furthermore, the species of plants included Poa annua, Ophiopogon japonicus, Zoysia japonica, Cinnamomum camphora, Willow of the weeping tree, Platanus acephala, Ginkgo biloba, Ligustrum lucidum, Osmanthus fragrans, Prunus purpurogenum, Photinia fraseri, Euonymus japonicus and Loropetalum chinensis, with leaf area indices of 8.74, 5.02, 10.2, 4.07, 5.38, 3.47, 4.32, 3.21, 3.25, 3.75, 5.08, 4.19 and 4.70, respectively.

[0028] The present invention also provides a computing device, including a processor and a memory, wherein the memory stores executable codes, and when the executable codes are executed by the processor, the processor executes the method as described above.

[0029] The present invention also provides a non-transitory machine-readable storage medium having executable codes stored thereon. When the executable codes are executed by a processor of an electronic device, the processor is caused to execute the method as described above.

[0030] The present invention can quickly and accurately calculate the carbon emissions of the urban built environment, and can also obtain the temporal and spatial distribution of carbon emissions, thereby implementing targeted energy-saving and emission reduction measures and effectively managing the city's carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 is a method flow chart of the evaluation method provided by Example 1 of the present invention;

[0033] Figure 2 is a schematic diagram of the structure of the evaluation boundary provided by Embodiment 1 of the present invention;

[0034] Figure 3 It is a schematic diagram of a module for CIM model data collection provided by Embodiment 1 of the present invention;

[0035] Figure 4 This is a parameter table of the carbon fixation index in Example 1 of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] Embodiment 1:

[0038] This embodiment is used to provide a method for evaluating carbon emissions in urban built environment based on CIM. Figure 1 As shown, the following steps are included:

[0039] S1. See Figure 2 According to the source of carbon emissions, the assessment boundary of urban built environment carbon emissions is determined; the boundary includes various types of buildings, road traffic, public lighting and greening in the city, which are divided into building boundaries, road boundaries, public lighting boundaries and greening boundaries; specifically, the sources of carbon emissions mainly include four parts: building carbon emissions, traffic carbon emissions, outdoor public lighting-related carbon emissions, and greening carbon absorption.

[0040] S2, see Figure 3 , the basic data required for evaluation are obtained from the urban CIM model, including three categories: geospatial data information (such as the geographical location of a building, the area of ​​a green space, etc.), geometric data information (such as the size and relative spatial position of a component in the building, etc.) and semantic data information (such as the material type and properties of a component in the building, etc.).

[0041] CIM is an object-based digital information modeling that uses spatial objects such as points, lines, and surfaces to define elements in the city and express their properties. The geospatial data information, geometric information data, and semantic data information of physical entities can be extracted from the CIM model.

[0042] For buildings, the CIM model can provide information on the geographical location of each building, as well as the geometric dimensions, material semantic properties, relative spatial position, and other information of each component in the building. This information, combined with the building energy consumption simulation software, can be used to simulate the use of buildings and calculate energy consumption; for road traffic, the CIM model can provide information on the length, width, direction, and geographical location of each road, and assist in determining the connection path between any two buildings in the city; for public lighting, the CIM model can provide information on the number, power, and geographical location of various lamps, and support the calculation of related carbon emissions; for greening, the CIM model can provide information on plant species, planting area, and geographical location.

[0043] S3. Combined with the data information provided by CIM, use the carbon emission assessment model to calculate part of the carbon emissions and summarize them into total carbon emissions.

[0044] The carbon emission assessment model includes the calculation formulas for building carbon emissions, road traffic (public transportation and private transportation) carbon emissions, public lighting carbon emissions, green plant carbon absorption and total carbon emissions.

[0045] The formula for calculating building carbon emissions is:

[0046] B CO2 (t)=∑ i E build,i (t)×F i ; (1)

[0047] In formula 1, B CO2 (t) is the building carbon emission in month t (unit: tCO2); E build,i (t) is the energy consumption of the building in the i-th category in month t; F i is the carbon emission factor of the i-th energy type.

[0048] E build,i (t) Calculated and output by energy consumption simulation tools (such as EnergyPlus, DeST and eQUEST). The operation of building energy consumption simulation tools usually requires the input of three types of data: the first type of data is the geometric and semantic information of the simulated building, which can be directly obtained from CIM; the second type of data is external meteorological data, which can be obtained from local meteorological stations and statistical files; the third type of data is the use of the building, which can be obtained through field surveys, questionnaires, etc.

[0049] The road traffic carbon emission calculation formula, the public transportation carbon emission calculation formula is:

[0050] MB CO2 (t)=∑ j (∑ k Q k(t)×D k ×E j,k )×F j ;; (2)

[0051] In formula 2, MB CO2 (t) is the carbon emission of public transportation in month t (unit: tCO2); Q k (t) is the travel frequency of the kth type of public transportation in month t; D k is the travel distance of each k-th type of public transportation (unit: km); E j,k F is the consumption index of the j-type energy per unit mileage of the k-th type of public transportation (unit: kg / km); j is the carbon emission factor of the jth type of energy (unit: tCO2 / kg).

[0052] The road traffic carbon emission calculation formula, the private traffic carbon emission calculation formula is:

[0053] MP CO2 (t)=∑ j (∑ m L m ×V m (t)×E j )×F j ; (3)

[0054] In formula 3, MP CO2 (t) is the carbon emission of private transportation in month t (unit: tCO2); L m is the length of the mth road section (unit: km); V m (t) is the number of private cars traveling on the mth road section in month t; E j F is the consumption index of type j energy per unit mileage of private transportation (unit: kg / km); j is the carbon emission factor of the jth energy type (unit: tCO2 / kg)

[0055] The calculation formula for public lighting carbon emissions is:

[0056] L CO2 (t)=∑ n N n ×P n ×H n (t)×d(t)×F E ;; (4)

[0057] In formula 4, L CO2 (t) is the carbon emission of public lighting in month t (unit: tCO2); N n is the number of lamps n; P n is the power of lamp n (unit: kW); Hn (t) is the daily usage time of lamp n in month t (unit: hours / day); d(t) is the number of days in month t (unit: day); F E is the carbon emission factor of electricity (unit: tCO2 / kWh).

[0058] The green plant carbon absorption calculation formula is:

[0059] G CO2 (t)=∑ s A s ×LA s ×C CO2s (t)×d(t); (5)

[0060] In formula 5, G CO2 (t) is the carbon fixation of green plants in month t (unit: tCO2); A s is the planting area of ​​plant s in the green space (unit: m2); LA s is the leaf area index of plant s; C CO2s (t) is the carbon fixation index of plant s in month t (unit: kg / (m2·day)); d(t) is the day of month t (unit: day).

[0061] The calculation formula for the total carbon emissions of the city is:

[0062] C CO2 (t) = B CO2 (t)+MB CO2 (t)+MP CO2 (t)+L CO2 (t)-G CO2 (t) (6)

[0063] In formula 6, C CO2 (t) is the total carbon emissions of the assessed city in month t (unit: tCO2); CO2 (t) is the building carbon emission in month t (unit: tCO2); MB CO2 (t) is the carbon emission of public transportation in month t (unit: tCO2); MP CO2 (t) is the carbon emission of private transportation in month t (unit: tCO2); L CO2 (t) is the carbon emission of public lighting in month t (unit: tCO2); G CO2 (t) is the carbon fixation amount of green plants in month t (unit: tCO2).

[0064] In this embodiment, the energy types used include gasoline, diesel, natural gas and electricity, and their carbon emission factors are 2.03E-03~2.93E-03tCO2 / kg, 2.40E-03~2.45E-03tCO2 / kg, 1.56E-03~2.16E-03tCO2 / m3 and 2.11E-04~7.12E-04tCO2 / kWh respectively.

[0065] The energy consumption index includes 2.34E-01kg / km for large and medium-sized vehicles powered by gasoline, and 6.86E-02kg / km for small and micro-sized vehicles; 1.50E+00kWh / km for large and medium-sized vehicles powered by electricity, and 1.00E+00kWh / km for small and micro-sized vehicles; 2.12E-01kg / km for large and medium-sized vehicles powered by diesel, and 8.5E-02kg / km for small and micro-sized vehicles.

[0066] The plant species included bluegrass, ophiopogon, zoysia, camphor tree, willow, sycamore, ginkgo, privet, osmanthus, purple-leaved plum, photinia, boxwood and red-flowered loblolly, with leaf area indexes of 8.74, 5.02, 10.2, 4.07, 5.38, 3.47, 4.32, 3.21, 3.25, 3.75, 5.08, 4.19 and 4.70, respectively. The corresponding carbon fixation index can be found in Figure 4 .

[0067] The urban built environment carbon emission assessment method based on CIM provided in this embodiment first determines the assessment boundary of carbon emission according to the different sources of carbon emission, then obtains the basic data required for the assessment from the urban CIM model, calculates the carbon emission of each part using the carbon emission assessment model, and summarizes it into total carbon emission. This assessment method can quickly and accurately calculate the carbon emission of the urban built environment, and obtain the time and space distribution of carbon emission, and then implement targeted energy-saving and emission reduction measures to effectively manage the carbon emission of the city.

[0068] Embodiment 2:

[0069] This embodiment is a computing device, including a processor and a memory, wherein the memory stores codes for executing the method in the above embodiment.

[0070] The processor may be a multi-core processor or may include multiple processors. In some embodiments, the processor may include a general-purpose main processor and one or more special coprocessors, such as a graphics processing unit (GPU), a digital signal processor (DSP), etc. In some embodiments, the processor may be implemented using a customized circuit, such as an application-specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

[0071] The memory may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage. Among them, ROM can store static data or instructions required by the processor or other modules of the computer. The permanent storage device may be a readable and writable storage device. The permanent storage device may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In some other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. In addition, the memory may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (e.g., SD card, mini SD card, Micro-SD card, etc.), a magnetic floppy disk, etc. The computer-readable storage medium does not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0072] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is enabled to execute the above method.

[0073] Embodiment 3:

[0074] This embodiment provides a non-transitory machine-readable memory having executable codes stored thereon. When the executable codes are executed by a processor of an electronic device, the processor is enabled to execute the above-mentioned system.

[0075] A non-temporary machine-readable memory (or computer-readable memory, or machine-readable memory) having executable code (or computer program, or computer instruction code) stored thereon, which, when executed by a processor of an electronic device (or computing device, server, etc.), enables the processor to perform the various steps of the above-mentioned method according to the present invention.

[0076] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or a combination of both.

[0077] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A CIM-based urban built environment carbon emission assessment method, characterized in that: The following steps are involved: S1. Determine the assessment boundaries of urban built environment carbon emissions, including building boundaries, road boundaries, public lighting boundaries and green space boundaries; S2. Obtain basic data of each assessment boundary from the CIM model, including geospatial data information, geometric data information and semantic data information; S3. Combine each assessment boundary and its corresponding basic data to calculate the carbon emissions of each assessment boundary and summarize them into total carbon emissions.

2. The urban built environment carbon emission assessment method based on CIM according to claim 1 is characterized in that: The carbon emissions of the building boundary are calculated using the building carbon emission model. The calculation formula is: B CO2 (t)=∑ i E build,i (t)×F i ; Among them, B CO2 (t) is the building carbon emission in month t, in tCO2; E build,i (t) is the energy consumption of the building in the i-th category in month t; F i is the carbon emission factor of the i-th energy type.

3. The urban built environment carbon emission assessment method based on CIM according to claim 2 is characterized in that: Calculate the carbon emissions at the road boundary through the road traffic carbon emission model, including the public transportation carbon emission model and the private transportation carbon emission model; The calculation formula of the public transportation carbon emission model is: MB CO2 (t)=∑ j (∑ k Q k (t)×D k ×E j,k )×F j ; Among them, MB CO2 (t) is the carbon emission of public transportation in month t, in tCO2; Q k (t) is the travel frequency of the kth type of public transportation in month t; D k is the travel distance of each trip of the kth type of public transportation, in km; E j,k F is the consumption index of the j-type energy per unit mileage of the k-th type of public transportation; j is the carbon emission factor of the jth energy type; The calculation formula of the private transportation carbon emission model is: MP CO2 (t)=∑ j (∑ m THE m ×V m (t)×E j )×F j ; Among them, MP CO2 (t) is the carbon emission of private transportation in month t, in tCO2; L m is the length of the mth road section, in km; V m (t) is the number of private cars traveling on the mth road section in month t; E j F is the consumption index of j type of energy per unit mileage of private transportation; j is the carbon emission factor of the jth type of energy.

4. The urban built environment carbon emission assessment method based on CIM according to claim 3 is characterized in that: The carbon emissions of public lighting boundaries are calculated using the public lighting carbon emission model. The calculation formula is: L CO2 (t)=∑ n N n ×P n ×H n (t)×d(t)×F E ; Among them, L CO2 (t) is the carbon emission of public lighting in month t, in tCO2; N n is the number of lamps n; P n is the power of lamp n, in kW; H n (t) is the daily usage time of lamp n in month t, in hours / day; d(t) is the number of days in month t, in days; F E is the carbon emission factor of electricity, with the unit of tCO2 / kWh.

5. The urban built environment carbon emission assessment method based on CIM according to claim 4 is characterized in that: The carbon sequestration amount of the greening boundary is calculated by the green plant carbon absorption model. The calculation formula is: G CO2 (t)=∑ s A s ×LA s ×C CO2s (t)×d(t); Among them, G CO2 (t) is the carbon fixation of green plants in month t, in tCO2; A s is the planting area of ​​plant s in the green space, in m2; LA s is the leaf area index of plant s; C CO2s (t) is the carbon fixation index of plant s in month t, in kg / (m2·day); d(t) is the day of month t, in days.

6. The urban built environment carbon emission assessment method based on CIM according to claim 5 is characterized in that: Energy types include gasoline, diesel, natural gas and electricity, and their carbon emission factors are 2.03E-03~2.93E-03tCO2 / kg, 2.40E-03~2.45E-03tCO2 / kg, 1.56E-03~2.16E-03tCO2 / m3 and 2.11E-04~7.12E-04tCO2 / kWh respectively.

7. The urban built environment carbon emission assessment method based on CIM according to claim 5 is characterized in that: The energy consumption index includes 2.34E-01kg / km for large and medium-sized vehicles powered by gasoline, and 6.86E-02kg / km for small and micro-sized vehicles; 1.50E+00kWh / km for large and medium-sized vehicles powered by electricity, and 1.00E+00kWh / km for small and micro-sized vehicles; 2.12E-01kg / km for large and medium-sized vehicles powered by diesel, and 8.5E-02kg / km for small and micro-sized vehicles.

8. The urban built environment carbon emission assessment method based on CIM according to claim 5 is characterized in that: The plant species included Poa annua, Ophiopogon japonicus, Zoysia japonica, Cinnamomum camphora, Willow of the weeping tree, Platanus acephala, Ginkgo biloba, Ligustrum lucidum, Osmanthus fragrans, Prunus purpurogenum, Photinia fraseri, Euonymus japonicus and Loropetalum chinensis, with leaf area indices of 8.74, 5.02, 10.2, 4.07, 5.38, 3.47, 4.32, 3.21, 3.25, 3.75, 5.08, 4.19 and 4.70, respectively.

9. A computing device, characterized in that: The method comprises a processor and a memory, wherein the memory stores executable codes, and when the executable codes are executed by the processor, the processor executes the method according to any one of claims 1 to 8.

10. A non-transitory machine-readable storage medium, characterized in that: An executable code is stored thereon, and when the executable code is executed by a processor of an electronic device, the processor is caused to execute any one of the methods described in claims 1-8.

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