CN111861797A - Method and accounting system for rapidly accounting carbon dioxide emission in urban and rural life - Google Patents
Method and accounting system for rapidly accounting carbon dioxide emission in urban and rural life Download PDFInfo
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Abstract
The invention belongs to the technical field of quick accounting of domestic carbon dioxide emission, and particularly relates to a method for quickly accounting urban and rural domestic carbon dioxide emission, which comprises the following steps: calculating the moonlight night intensity of a town and a rural moonlight night intensity of a certain area; respectively establishing a functional relation between the urban domestic electricity consumption and the urban monthly night light intensity and a functional relation between the rural domestic electricity consumption and the rural monthly night light intensity, and calculating the urban domestic electricity consumption and the rural domestic electricity consumption in the region; establishing a functional relation between the intensity of the lamplight at monthly night in cities and towns and the emission of carbon dioxide in cities and towns, and calculating the emission of the carbon dioxide in cities and towns; establishing a functional relation between the light intensity of the rural monthly night light and the rural domestic carbon dioxide emission, and calculating the rural domestic carbon dioxide emission; and the fast accounting of the urban living carbon dioxide emission and the rural living carbon dioxide emission in the area is realized.
Description
Technical Field
The invention belongs to the technical field of quick accounting of domestic carbon dioxide emission, and particularly relates to a method and an accounting system for quickly accounting urban and rural domestic carbon dioxide emission.
Background
Rapid urbanization and climate change are the most global phenomenon of interest in the 21 st century, and the link between these two processes is becoming increasingly tight, since rapid urbanization is often accompanied by lifestyle changes, increased consumption and energy use, which contribute to global climate change to a large extent. With the rapid urbanization and the drastic reform, the annual average urbanization rate reaches 2 percent at most. In recent years, a new stage of development has been experienced-more than 50% of the population living in towns. In the next 10 years, the town population will account for 70% of the general population. On one hand, the rapid development of town economy improves social productivity and improves human living conditions, but on the other hand, the contradiction between the rapid urbanization process and environmental protection is increasingly prominent. In order to cope with global climate change problems, it is committed to achieve carbon dioxide peak reaching in 2030, and it is committed to cut carbon dioxide emission per unit total production (GDP) by 40% to 45% as compared with 2005 by 2020, and incorporate it as a constraint index into long-term planning of economy and society. The first step in achieving these goals is to quickly, accurately and timely account for carbon dioxide emissions from various regions.
The traditional method for quantifying the carbon dioxide emission at the present stage mainly depends on indirect data such as energy consumption and social and economic activity indexes of different levels of countries, regions or towns to quantify the carbon dioxide emission. The existing method for accounting the carbon dioxide emission is obtained by calculation based on energy data (including coal gas, oil products, natural gas and the like). However, due to the low availability and high hysteresis of these data and information, the calculation of carbon dioxide emissions is usually delayed, i.e., the source data takes a very long time to be counted, and the delay is severe and cannot provide a timely estimate of the carbon dioxide emissions. Furthermore, the accuracy of the carbon dioxide emission amount accounting depends largely on the quality of other information, and these accounting are absolute value accounting, including little uncertainty analysis or evaluation. In short, the existing methods have the following problems:
1) the hysteresis of the energy data and the related data cannot provide timely carbon dioxide emission accounting data;
2) the unavailability of energy data and related data creates difficulties for accurate accounting of carbon dioxide emissions;
and the data of the visible light near-infrared imaging radiation (VIIRS) sensor carried by Suomi-NPP is adopted as the most widely applied night light data at present. VIIRS can effectively detect the low-intensity night light generated by night light and even small-scale residential areas, and is a good data source for measuring the activity intensity of human beings. Researches show that the night light intensity, the electricity consumption and the domestic carbon dioxide emission have a remarkable relationship. Based on the calculation, the research provides a method for calculating monthly life carbon dioxide emission of cities and towns/rural areas of each province based on the relationship between the light intensity and the electricity consumption at night, and realizes quick calculation of the emission of the carbon dioxide of the cities and the towns/rural areas of each province in China.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a method for rapidly accounting the carbon dioxide emission in cities and towns and rural life, which can rapidly and timely account the carbon dioxide emission by adopting monthly night light data without depending on energy data, wherein the monthly night light data is monthly data which can be timely downloaded by the prior art, for example, the night light data in 1-6 months in 2020 can be timely downloaded by the prior database; by the method, the monthly night light data can be utilized to quickly and timely calculate the discharge amount of carbon dioxide in urban life and the discharge amount of carbon dioxide in rural life in a certain area.
The invention provides a method for rapidly accounting carbon dioxide emission in urban and rural life, which comprises the following steps:
respectively establishing a functional relation between the monthly night light intensity of the town and the land for the town construction and a functional relation between the monthly night light intensity of the rural area and the land for the rural residential points on the basis of the night light data, the land for the town construction and the land for the rural residential points, and calculating the monthly night light intensity of the town and the monthly night light intensity of the rural area;
respectively establishing a functional relation between the urban domestic electricity consumption and the urban monthly night light intensity and a functional relation between the rural domestic electricity consumption and the rural monthly night light intensity on the basis of the acquired urban monthly night light intensity and the rural monthly night light intensity of the region, and calculating the urban domestic electricity consumption and the rural domestic electricity consumption of the region;
establishing a functional relation between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the region, combining the functional relation with the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensity, establishing a functional relation between the urban monthly night light intensity and the urban domestic carbon dioxide emission, and calculating the urban domestic carbon dioxide emission;
establishing a functional relationship between rural domestic power consumption and rural domestic carbon dioxide emission in the area, combining the functional relationship with the established functional relationship between the rural domestic power consumption and the rural monthly night light intensity, establishing a functional relationship between the rural monthly night light intensity and the rural domestic carbon dioxide emission, and calculating the rural domestic carbon dioxide emission; and the fast accounting of the urban living carbon dioxide emission and the rural living carbon dioxide emission in the area is realized.
As an improvement of the above technical solution, the method comprises the steps of respectively establishing a functional relationship between the town monthly night light intensity and the town construction land and a functional relationship between the rural monthly night light intensity and the rural residential site land based on the night light data, the town construction land and the rural residential site land, and calculating the town monthly night light intensity and the rural monthly night light intensity of a certain area; the method specifically comprises the following steps:
acquiring urban construction land and rural residential site land of the region based on the current year land utilization data of the region;
the night light data includes: k pixel value L of night light of certain construction land in urban construction landk1And the kth pixel value L of night light of a certain rural residential point in the rural residential point landk2；
Based on the night light data, the urban construction land and the rural residential site land in the area and the night light data, according to ArcGIS, a functional relation between the monthly night light intensity of the town and the urban construction land is established by using a formula (1), and the night light intensity of the urban construction land in a certain area is calculated:
NTLit_urban＝∑Lk1*Ck1(1)
wherein, NTLit_urbanThe light intensity of the town monthly night light at the time t in a certain area is shown; ck1The number of pixels corresponding to the kth pixel value;
and (3) establishing a functional relation between the lunar night light intensity of the rural areas and the residential area of the rural areas by using a formula (2), and calculating the night light intensity of the residential area of the rural areas in a certain area:
NTLit_rural＝∑Lk2*Ck2(2)
wherein, NTLit_ruralThe light intensity of the rural monthly night light in a certain area at the time t; ck2The number of the pixels corresponding to the k-th pixel value.
As an improvement of the above technical solution, the functional relationship between the urban domestic electricity consumption and the urban monthly night light intensity and the functional relationship between the rural domestic electricity consumption and the rural monthly night light intensity are respectively established based on the acquired urban monthly night light intensity and the rural monthly night light intensity of the area, and the domestic electricity consumption of the urban construction land and the rural residential site land of the area are calculated; the method specifically comprises the following steps:
establishing a functional relation between the urban living electricity consumption and the urban monthly night light intensity of the region based on the acquired urban monthly night light intensity of the region:
EPCi_urban＝α*NTLit_urban(3)
wherein, EPCi_urbanThe unit of the domestic electricity consumption of the town in the area is ten thousand kilowatt hours; alpha is the town electricity utilization coefficient;
calculating the urban domestic electricity consumption EPC of the region based on the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensityi_urban；
Based on the acquired lunar night light intensity of the town and the lunar night light intensity of the region, establishing a functional relation between the rural domestic electricity consumption and the lunar night light intensity of the region:
EPCi_rural＝β*NTLit_rural(4)
wherein, EPCi_ruralThe unit of the rural domestic electricity consumption in the region is ten thousand kilowatt hours; beta is the residential electricity utilization coefficient;
calculating the rural domestic power consumption EPC of the region based on the established functional relationship between the rural domestic power consumption and the rural monthly night light intensity of the regioni_rural。
As one improvement of the technical scheme, the functional relationship between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the region is established, and is combined with the established functional relationship between the urban domestic electricity consumption and the urban monthly night light intensity, the functional relationship between the urban monthly night light intensity and the urban domestic carbon dioxide emission is established, and the urban domestic carbon dioxide emission is calculated; the method specifically comprises the following steps:
establishing a functional relation between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the region:
EPCi_urban＝*CEi_urban(6)
wherein, EPCi_urbanIs used for the urban life in the areaElectricity in units of hundred million kilowatt-hours; CEi_urbanThe unit of the carbon dioxide emission is ten thousand tons in the urban life of the area; the carbon dioxide emission coefficient of urban life;
the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensity is as follows:
EPCi_urban＝α*NTLit_urban(3)
the equations (3) and (6) are collated:
*CEi_urban＝α*NTLi_urban(10)
rewrite equation (10) to:
CEi_urban＝α/*NTLi_urban(11)
order to
γi_urban＝α/ (12)
Then the formula (12) is substituted into (11), and the functional relation between the town monthly night light intensity and the town living carbon dioxide emission is established:
CEi_urban＝γurban*NTLi_urban(13)
wherein, CEi_urbanThe unit is ten thousand tons of carbon dioxide emission in urban life;
and (4) calculating the discharge amount of the urban domestic carbon dioxide according to the formula (13).
As an improvement of the above technical solution, the method further includes: and predicting the discharge amount of carbon dioxide in urban life in a month in the future according to the estimated monthly night light intensity of the urban in the future.
As one improvement of the technical scheme, the functional relationship between the rural domestic electricity consumption and the rural domestic carbon dioxide emission in the area is established, and is combined with the established functional relationship between the rural domestic electricity consumption and the rural monthly night light intensity, the functional relationship between the rural monthly night light intensity and the rural domestic carbon dioxide emission is established, and the rural domestic carbon dioxide emission is calculated; the method specifically comprises the following steps:
establishing a functional relation between rural domestic electricity consumption and rural domestic carbon dioxide emission in the area:
EPCi_rural＝θ*CEi_rural(7)
wherein, EPCi_ruralThe unit of the electricity consumption is hundred million kilowatt hours in rural life; CEi_ruralThe carbon dioxide emission is ten thousand tons in rural life; theta is the carbon dioxide emission coefficient of rural life;
the established functional relationship between the rural domestic electricity consumption and the rural monthly night light intensity is as follows:
EPCi_rural＝β*NTLit_rural(4)
the equations (4) and (7) are collated:
θ*CEi_rural＝β*NTLi_rural(14)
rewrite (14) to:
CEi_rural＝β/θ*NTLi_rural(15)
order to
γi_rural＝β/θ (16)
And (16) is substituted into (15), and a function relation between the rural monthly night light intensity and the rural living carbon dioxide emission is established:
CEi_rural＝γrural*NTLi_rural(17)
wherein, CEi_ruralThe unit is ten thousand tons of carbon dioxide emission in rural life;
and (4) calculating the carbon dioxide emission in rural life according to the formula (17).
As an improvement of the above technical solution, the method further includes: and predicting the rural living carbon dioxide emission in a certain month in a certain year in the future according to the estimated rural monthly night light intensity in the certain year in the future.
The invention also provides an accounting system for rapidly accounting the emission of the carbon dioxide in the urban and rural life, which comprises:
the light intensity acquisition module is used for respectively establishing a functional relation between the town monthly night light intensity and the town construction land and a functional relation between the rural monthly night light intensity and the rural residential site land based on the night light data, the town construction land and the rural residential site land, and calculating the town monthly night light intensity and the rural monthly night light intensity in a certain area;
the domestic electricity consumption acquisition module is used for respectively establishing a functional relation between the urban domestic electricity consumption and the urban monthly night light intensity and a functional relation between the rural domestic electricity consumption and the rural monthly night light intensity based on the acquired urban monthly night light intensity and the rural monthly night light intensity of the region, and calculating the urban domestic electricity consumption and the rural domestic electricity consumption of the region;
the town life carbon dioxide emission obtaining module is used for establishing a functional relation between town life electricity consumption and town life carbon dioxide emission in the region, combining the functional relation with the established functional relation between the town life electricity consumption and the town monthly night light intensity, establishing a functional relation between the town monthly night light intensity and the town life carbon dioxide emission, and calculating the town life carbon dioxide emission; and
the rural life carbon dioxide emission acquisition module is used for establishing a functional relationship between rural life electricity consumption and rural life carbon dioxide emission in the area, combining the functional relationship with the established functional relationship between the rural life electricity consumption and the rural monthly night light intensity, establishing a functional relationship between the rural monthly night light intensity and the rural life carbon dioxide emission, and calculating the rural life carbon dioxide emission; and the fast accounting of the urban living carbon dioxide emission and the rural living carbon dioxide emission in the area is realized.
Compared with the prior art, the invention has the beneficial effects that:
the method can quickly check the urban and rural living carbon dioxide emission in a certain area by only using night light data, thereby improving the working efficiency and reducing the calculation amount;
based on the existing monthly night light data, the defects that the energy data cannot be obtained in time and the energy data is obtained late or is lost are overcome;
the method is different from the prior absolute carbon dioxide accounting method, provides an uncertainty analysis result, and greatly improves the accuracy of calculation;
based on night light data, realizing rapid accounting of the discharge amount of urban living carbon dioxide and rural living carbon dioxide in any area; and a basis is provided for the formulation and management of regional emission reduction policies in a high-timeliness manner.
Drawings
FIG. 1 is a flow chart of a method of the present invention for rapid accounting of carbon dioxide emissions from urban and rural areas;
FIG. 2 is a schematic diagram of the relationship between the monthly night light intensity in cities and towns and the electricity consumption in cities and towns in the method for rapidly accounting the carbon dioxide emission in cities and towns and the uncertainty analysis;
FIG. 3 is a schematic diagram of the relationship between the lunar night light intensity in the rural area and the power consumption in the rural area and the uncertainty analysis in the method for rapidly accounting the carbon dioxide emission in the urban and rural areas of the invention;
FIG. 4 is a schematic diagram of the relationship between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the method for rapidly accounting the urban and rural domestic carbon dioxide emission;
FIG. 5 is a schematic diagram of the relationship between rural domestic electricity consumption and rural domestic carbon dioxide emission in the method for rapidly accounting for the carbon dioxide emission in cities and towns and rural domestic carbon dioxide emission of the invention.
Detailed Description
The invention will now be further described with reference to the accompanying drawings.
As shown in figure 1, the invention provides a method for rapidly accounting the carbon dioxide emission in cities and towns and rural life, which utilizes monthly night light data to rapidly account the carbon dioxide emission in cities and towns and rural life in any provinces of China; and in the emission reduction policy making and management, a quick and accurate basis is provided.
The calculation method mainly comprises the steps of calculating the relationship between the monthly night light data and the carbon dioxide emission of the urban life department and the relationship between the monthly night light data and the carbon dioxide emission of the rural life department (both the relationship are linear, and the final result is a table D and a table E) according to the historical monthly night light data, the historical power consumption data, the carbon dioxide emission of the historical urban life department and the carbon dioxide emission of the historical rural life department (the historical data calculated through energy is corresponding to the calculation method of a formula 7); wherein, the two linear relations are obtained through historical data. For example, given monthly night light data in 1 month of 2020, the amount of carbon dioxide discharged in cities and towns and the amount of carbon dioxide discharged in rural areas in a certain region in 1 month of 2020 can be quickly calculated through tables D and E.
The method comprises the following steps:
step 1) respectively establishing a function relationship between the town monthly night light intensity and the town construction land and a function relationship between the rural monthly night light intensity and the rural residential site land based on the night light data, the town construction land and the rural residential site land, and calculating the town monthly night light intensity and the rural monthly night light intensity in a certain area;
specifically, on the basis of the current year land utilization data (100 m spatial resolution) of the region, urban construction land and rural residential site land of the region are obtained;
the night light data includes: k pixel value L of night light of certain construction land in urban construction landk1And the kth pixel value L of night light of a certain rural residential point in the rural residential point landk2；
Based on the night light data, the urban construction land and the rural residential site land in the area, and the night light data, according to ArcGIS (Arc Geographic Information System or Arc Geo-Information System, Arc Geographic Information System), a functional relationship between the urban monthly night light intensity and the urban construction land is established by using a formula (1), and the night light intensity of the urban construction land in a certain area is calculated:
NTLit_urban＝∑Lk1*Ck1(1)
wherein, NTLit_urbanFor a certain area at time tThe intensity of the light at the moonlight of the town; l isk1The kth pixel value of night light of a certain construction land in the urban construction land is obtained; ck1The number of the pixels corresponding to the kth pixel value;
and (3) establishing a functional relation between the lunar night light intensity of the rural areas and the residential area of the rural areas by using a formula (2), and calculating the night light intensity of the residential area of the rural areas in a certain area:
NTLit_rural＝∑Lk2*Ck2(2)
wherein, NTLit_ruralThe light intensity of the rural monthly night light in a certain area at the time t; l isk2The kth pixel value of night light of a certain rural residential point in the rural residential point land; ck2Is the number of pixels corresponding to the k-th pixel value.
Step 2) respectively establishing a functional relation between the urban domestic electricity consumption and the urban monthly night light intensity and a functional relation between the rural domestic electricity consumption and the rural monthly night light intensity based on the acquired urban monthly night light intensity and the rural monthly night light intensity of the region, and calculating the urban domestic electricity consumption and the rural domestic electricity consumption of the region; and uncertainty analysis results;
specifically, based on the acquired monthly night light intensity of the town in the area, a functional relation between the domestic electricity consumption of the town in the area and the monthly night light intensity of the town is established:
EPCi_urban＝α*NTLit_urban(3)
wherein, EPCi_urbanThe unit of the domestic electricity consumption of the town in the area is ten thousand kilowatt hours; alpha is the town electricity utilization coefficient;
wherein, the value of α is obtained according to fig. 2 and the following table a:
TABLE A
| Month of the year | Upper limit value | Mean value of | Lower limit value | Uncertainty (standard deviation/mean) |
| 1 | 0.75 | 0.59 | 0.50 | 0.17 |
| 2 | 0.65 | 0.56 | 0.48 | 0.11 |
| 3 | 0.64 | 0.60 | 0.55 | 0.05 |
| 4 | 0.54 | 0.50 | 0.46 | 0.07 |
| 5 | 0.61 | 0.55 | 0.51 | 0.06 |
| 6 | 0.92 | 0.87 | 0.81 | 0.04 |
| 7 | 0.86 | 0.79 | 0.70 | 0.08 |
| 8 | 0.90 | 0.80 | 0.74 | 0.08 |
| 9 | 0.77 | 0.75 | 0.72 | 0.03 |
| 10 | 0.52 | 0.50 | 0.49 | 0.02 |
| 11 | 0.46 | 0.45 | 0.43 | 0.03 |
| 12 | 0.49 | 0.46 | 0.43 | 0.05 |
For example, in month 1, the upper limit value of α is 0.75, the lower limit value of α is 0.50, and the average value of α is 0.59. The uncertainty calculated according to equation (5) was 17%.
Calculating the urban domestic electricity consumption EPC of the region based on the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensityi_urban；
Based on the acquired lunar night light intensity of the town and the lunar night light intensity of the region, establishing a functional relation between the rural domestic electricity consumption and the lunar night light intensity of the region:
EPCi_rural＝β*NTLit_rural(4)
wherein, EPCi_ruralThe unit of the rural domestic electricity consumption in the region is ten thousand kilowatt hours; beta is the residential electricity utilization coefficient.
Calculating the rural domestic power consumption EPC of the region based on the established functional relationship between the rural domestic power consumption and the rural monthly night light intensity of the regioni_rural。
In addition, the uncertainty analysis result is obtained by comparing the prediction result with the historical data, and the specific method for calculating the uncertainty analysis result is as follows:
Uncertainty＝Std/mean (5)
wherein Uncertainty is an Uncertainty analysis result; std is the standard deviation of the data of the fourth phase of each month in the previous year; mean is the mean of the data of the four phases of each month in the past year; the month in each year with the same monthly night light intensity as the current month is a first month, and the fourth month refers to the same month in each year in the past four years.
According to the uncertainty analysis result obtained by calculation, the accuracy and precision of the calculated urban and rural domestic electricity consumption can be analyzed, and the accuracy rate reaches over 90 percent. The uncertainty analysis results are shown in fig. 2 and 3, and the lower histograms in fig. 2 and 3 are the uncertainty analysis results, so that it can be seen that the calculation results based on the night lights are only a few percent deviation, and it can be clearly seen that the calculation results are very accurate.
Wherein, the value of β is obtained according to fig. 3 and the following table B:
TABLE B
For example, in month 1, β has an upper limit value of 2.47, a lower limit value of 1.71, and an average value of 2.09. The uncertainty calculated according to equation (5) was 15%.
Step 3) establishing a functional relation between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the region, combining the functional relation with the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensity, establishing a functional relation between the urban monthly night light intensity and the urban domestic carbon dioxide emission, and calculating the urban domestic carbon dioxide emission;
establishing a functional relationship between rural domestic power consumption and rural domestic carbon dioxide emission in the area, combining the functional relationship with the established functional relationship between the rural domestic power consumption and the rural monthly night light intensity, establishing a functional relationship between the rural monthly night light intensity and the rural domestic carbon dioxide emission, and calculating the rural domestic carbon dioxide emission; and the fast accounting of the urban living carbon dioxide emission and the rural living carbon dioxide emission in the area is realized.
Specifically, the carbon dioxide emission amount of the historical urban life comprises the following steps: carbon dioxide emission of urban living coal, carbon dioxide emission of urban living oil and carbon dioxide emission of urban living natural gas;
calculating the discharge amount of carbon dioxide in the historical urban life according to historical data:
CEi_urban＝ρcoal*∑Coali_urban+ρoil*∑Oil_urban+ρgas*∑Gasi_urban(8)
wherein, CEi_urbanThe unit of the discharge amount of the carbon dioxide in the ith area is ten thousand tons; sigma Goali_urbanThe carbon dioxide emission of the total living coal in the ith area is ten thousand tons; sigma Oili_urbanThe carbon dioxide emission of the total domestic oil in the ith area is ten thousand tons; sigma Gasi_urbanThe carbon dioxide emission of the total domestic natural gas in the ith area is billionth cubic meter; rhocoalCarbon dioxide emission coefficient for coal; rhooilIs the carbon dioxide emission coefficient of the oil; rhogasIs the carbon dioxide emission coefficient of natural gas.
Establishing a functional relation between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the region based on the historical urban domestic carbon dioxide emission and the historical urban domestic electricity consumption:
EPCi_urban＝*CEi_urban(6)
wherein, EPCi_urbanThe unit of the domestic electricity consumption of the town in the area is hundred million kilowatt-hours; CEi_urbanThe unit of the carbon dioxide emission is ten thousand tons in the urban life of the area; the carbon dioxide emission coefficient of urban life; the result of the calculation is shown in figure 4,
the carbon dioxide emission amount of the historical rural life comprises: carbon dioxide emission of rural domestic coal, carbon dioxide emission of rural domestic oil and carbon dioxide emission of rural domestic natural gas;
according to historical data, calculating the carbon dioxide emission in the historical rural life:
CEi_rural＝ρcoal*∑Coali_rural+ρoil*∑Oili_rural+ρgas*∑Gasi_rural(9)
wherein, CEi_ruralThe carbon dioxide is discharged for rural life in the ith area (ten thousand tons); sigmaCoali_ruralThe unit is ten thousand tons of carbon dioxide emission of the total rural domestic coal in the ith area; sigma Oili_ruralThe carbon dioxide emission of the total rural domestic oil in the ith area is ten thousand tons; sigma Gasi_ruralThe carbon dioxide emission of the total rural domestic natural gas in the ith area is billionth cubic meter; rhocoalIs the carbon dioxide emission coefficient of the coal; rhooilIs the carbon dioxide emission coefficient of the oil; rhogasIs the carbon dioxide emission coefficient of natural gas. Wherein the carbon dioxide emission coefficients of the coal, oil and natural gas are shown in table C:
watch C
| Energy source | Carbon emission factor |
| Coal (coal) | 1.93 ton/ton |
| Oil | 3.145 ton/ton |
| Natural gas | 21.622 ton/ten thousand cubic meter |
Establishing a functional relation between rural domestic power consumption and rural domestic carbon dioxide emission in the region based on the historical rural domestic carbon dioxide emission and the historical rural domestic power consumption:
EPCi_rural＝θ*CEi_rural(7)
wherein, EPCi_ruralThe unit of the electricity consumption is hundred million kilowatt hours in rural life; CEi_ruralFor the rural lifeCarbon emissions, in units of ten thousand tons; theta is the carbon dioxide emission coefficient of rural life; the result of the calculation is shown in figure 5,
the above process is a specific derivation process for establishing the functional relationship between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the area and establishing the functional relationship between the rural domestic electricity consumption and the rural domestic carbon dioxide emission in the area, and based on the specific derivation process, whether the established two functional relationships are correct can be verified.
Based on the established functional relationship between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the region:
EPCi_urban＝*CEi_urban(6)
wherein, EPCi_urbanThe unit of the domestic electricity consumption of the town in the area is hundred million kilowatt-hours; CEi_urbanThe unit of the carbon dioxide emission is ten thousand tons in the urban life of the area; the carbon dioxide emission coefficient of urban life;
and the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensity is as follows:
EPCi_urban＝α*NTLit_urban(3)
the equations (3) and (6) are collated:
*CEi_urban＝α*NTLi_urban(10)
rewrite equation (10) to:
CEi_urban＝α/*NTLi_urban(11)
let gamma bei_urban＝α/ (12)
Then the formula (12) is substituted into (11), and the functional relation between the town monthly night light intensity and the town living carbon dioxide emission is established:
CEi_urban＝γurban*NTLi_urban(13)
wherein, CEi_urbanThe unit is ten thousand tons of carbon dioxide emission in urban life.
Wherein, γi_urbanThe values of (A) are as follows:
table D
| Month of the | γ | urban |
| 1 | 2.357004～3.273617 | |
| 2 | 2.249852～3.124794 | |
| 3 | 2.405832～3.341433 | |
| 4 | 2.004868～2.784539 | |
| 5 | 2.207404～3.065839 | |
| 6 | 3.46376～4.810778 | |
| 7 | 3.148344～4.3727 | |
| 8 | 3.216696～4.467633 | |
| 9 | 2.991452～4.154794 | |
| 10 | 2.003368～2.782456 | |
| 11 | 1.788392～2.483878 | |
| 12 | 1.830096～2.5418 |
Through the table D and monthly night light data, the carbon dioxide emission amount of urban life in each region can be rapidly and timely calculated.
Based on the established functional relationship between the rural domestic electricity consumption and the rural domestic carbon dioxide emission in the region:
EPCi_rural＝θ*CEi_rural(7)
wherein, EPCi_ruralThe unit of the electricity consumption is hundred million kilowatt hours in rural life; CEi_ruralThe carbon dioxide emission is ten thousand tons in rural life; theta is the carbon dioxide emission coefficient of rural life;
and the established functional relation between the rural domestic electricity consumption and the rural monthly night light intensity is as follows:
EPCi_rural＝β*NTLit_rural(4)
the equations (4) and (7) are collated:
θ*CEi_rural＝β*NTLi_rural(14)
rewrite (14) to:
CEi_rural＝β/θ*NTLi_rural(15)
let gamma bei_rural＝β/θ (16)
And (16) is substituted into (15), and a function relation between the rural monthly night light intensity and the rural living carbon dioxide emission is established:
CEi_rural＝γrural*NTLi_rural(17)
wherein, CEi_ruralThe unit is ten thousand tons of carbon dioxide emission in rural life;
wherein, γi_ruralThe values of (d) are as follows:
TABLE E
| Month of the | γ | rural |
| 1 | 5.347949～6.952333 | |
| 2 | 5.265641～6.845333 | |
| 3 | 5.995567～7.794237 | |
| 4 | 4.934133～6.414373 | |
| 5 | 5.116367～6.651277 | |
| 6 | 7.648546～9.94311 | |
| 7 | 6.399231～8.319 | |
| 8 | 6.310815～8.20406 | |
| 9 | 5.913469～7.68751 | |
| 10 | 3.88571～5.051423 | |
| 11 | 3.42631～4.454203 | |
| 12 | 3.561738～4.63026 |
Through the table E and monthly night light data, the rural life carbon dioxide emission in each region can be rapidly and timely accounted.
The method further comprises the following steps: and predicting the discharge amount of carbon dioxide in urban life in a month in the future according to the estimated monthly night light intensity of the urban in the future.
The method further comprises the following steps: and predicting the rural living carbon dioxide emission in a certain month in a certain year in the future according to the estimated rural monthly night light intensity in the certain year in the future.
The invention also provides an accounting system for rapidly accounting the emission of the carbon dioxide in the urban and rural life, which comprises:
the light intensity acquisition module is used for respectively establishing a functional relation between the town monthly night light intensity and the town construction land and a functional relation between the rural monthly night light intensity and the rural residential site land based on the night light data, the town construction land and the rural residential site land, and calculating the town monthly night light intensity and the rural monthly night light intensity in a certain area;
the domestic electricity consumption acquisition module is used for respectively establishing a functional relation between the urban domestic electricity consumption and the urban monthly night light intensity and a functional relation between the rural domestic electricity consumption and the rural monthly night light intensity based on the acquired urban monthly night light intensity and the rural monthly night light intensity of the region, and calculating the urban domestic electricity consumption and the rural domestic electricity consumption of the region;
the town life carbon dioxide emission obtaining module is used for establishing a functional relation between town life electricity consumption and town life carbon dioxide emission in the region, combining the functional relation with the established functional relation between the town life electricity consumption and the town monthly night light intensity, establishing a functional relation between the town monthly night light intensity and the town life carbon dioxide emission, and calculating the town life carbon dioxide emission; and
the rural life carbon dioxide emission acquisition module is used for establishing a functional relationship between rural life electricity consumption and rural life carbon dioxide emission in the area, combining the functional relationship with the established functional relationship between the rural life electricity consumption and the rural monthly night light intensity, establishing a functional relationship between the rural monthly night light intensity and the rural life carbon dioxide emission, and calculating the rural life carbon dioxide emission; and the fast accounting of the urban living carbon dioxide emission and the rural living carbon dioxide emission in the area is realized.
The system further comprises: and the town prediction module is used for predicting the discharge amount of carbon dioxide in town life in a month in the future according to the predicted monthly night light intensity of the town in the future.
The system further comprises: and the rural prediction module is used for predicting the rural living carbon dioxide emission in a certain month in a certain year in the future according to the predicted rural monthly night light intensity in the certain year in the future.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A method for rapidly accounting carbon dioxide emission in urban and rural life comprises the following steps:
respectively establishing a functional relation between the monthly night light intensity of the town and the land for the town construction and a functional relation between the monthly night light intensity of the rural area and the land for the rural residential points on the basis of the night light data, the land for the town construction and the land for the rural residential points, and calculating the monthly night light intensity of the town and the monthly night light intensity of the rural area;
respectively establishing a functional relation between the urban domestic electricity consumption and the urban monthly night light intensity and a functional relation between the rural domestic electricity consumption and the rural monthly night light intensity on the basis of the acquired urban monthly night light intensity and the rural monthly night light intensity of the region, and calculating the urban domestic electricity consumption and the rural domestic electricity consumption of the region;
establishing a functional relation between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the region, combining the functional relation with the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensity, establishing a functional relation between the urban monthly night light intensity and the urban domestic carbon dioxide emission, and calculating the urban domestic carbon dioxide emission;
establishing a functional relationship between rural domestic power consumption and rural domestic carbon dioxide emission in the area, combining the functional relationship with the established functional relationship between the rural domestic power consumption and the rural monthly night light intensity, establishing a functional relationship between the rural monthly night light intensity and the rural domestic carbon dioxide emission, and calculating the rural domestic carbon dioxide emission; and the fast accounting of the urban living carbon dioxide emission and the rural living carbon dioxide emission in the area is realized.
2. The method for fast accounting for carbon dioxide emissions in cities and towns and rural areas according to claim 1, wherein the town monthly night light intensity and the rural monthly night light intensity in a certain area are calculated based on the night light data, the land for town construction and the land for rural residential areas, respectively, by establishing a functional relationship between the town monthly night light intensity and the land for town construction and a functional relationship between the rural monthly night light intensity and the land for rural residential areas; the method specifically comprises the following steps:
acquiring urban construction land and rural residential site land of the region based on the current year land utilization data of the region;
the night light data includes: k pixel value L of night light of certain construction land in urban construction landk1And the kth pixel value L of night light of a certain rural residential point in the rural residential point landk2；
Based on the night light data, the urban construction land and the rural residential site land in the area and the night light data, according to ArcGIS, a functional relation between the monthly night light intensity in the town and the urban construction land is established by using a formula (1), and the night light intensity of the urban construction land in a certain area is calculated:
NTLit_urban＝∑Lk1*Ck1(1)
wherein, NTLit_urbanThe light intensity of the town monthly night light at the time t in a certain area is shown; ck1The number of pixels corresponding to the kth pixel value;
and (3) establishing a functional relation between the lunar night light intensity of the rural areas and the residential area of the rural areas by using a formula (2), and calculating the night light intensity of the residential area of the rural areas in a certain area:
NTLit_rural＝∑Lk2*Ck2(2)
wherein, NTLit_ruralThe light intensity of the rural monthly night light in a certain area at the time t; ck2The number of the pixels corresponding to the k-th pixel value.
3. The method for fast accounting for carbon dioxide emissions in cities and towns and rural areas according to claim 1, wherein the method comprises the steps of respectively establishing a functional relationship between the urban electricity consumption and the urban monthly night light intensity and a functional relationship between the rural electricity consumption and the rural monthly night light intensity based on the acquired urban monthly night light intensity and the rural monthly night light intensity of the area, and calculating the domestic electricity consumption of the urban construction land and the rural residential site land in the area; the method specifically comprises the following steps:
establishing a functional relation between the urban living electricity consumption and the urban monthly night light intensity of the region based on the acquired urban monthly night light intensity of the region:
EPCi_urban＝α*NTLit_urban(3)
wherein, EPCi_urbanThe unit of the domestic electricity consumption of the town in the area is ten thousand kilowatt hours; alpha is the town electricity utilization coefficient;
calculating the urban domestic electricity consumption EPC of the region based on the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensityi_urban；
Based on the acquired lunar night light intensity of the town and the lunar night light intensity of the region, establishing a functional relation between the rural domestic electricity consumption and the lunar night light intensity of the region:
EPCi_rural＝β*NTLit_rural(4)
wherein, EPCi_ruralThe unit of the rural domestic electricity consumption in the region is ten thousand kilowatt hours; beta is the residential electricity utilization coefficient;
calculating the rural domestic power consumption EPC of the region based on the established functional relationship between the rural domestic power consumption and the rural monthly night light intensity of the regioni_rural。
4. The method for fast accounting for carbon dioxide emissions in cities and towns and rural areas according to claim 3, wherein the functional relationship between the urban domestic electricity consumption and the urban domestic carbon dioxide emissions in the area is established, and the functional relationship between the urban monthly night light intensity and the urban domestic carbon dioxide emissions is established in combination with the established functional relationship between the urban domestic electricity consumption and the urban monthly night light intensity to calculate the urban domestic carbon dioxide emissions; the method specifically comprises the following steps:
establishing a functional relation between the urban domestic electricity consumption and the urban domestic carbon dioxide emission in the region:
EPCi_urban＝*CEi_urban(6)
wherein, EPCi_urbanThe unit of the domestic electricity consumption of the town in the area is hundred million kilowatt-hours; CEi_urbanThe urban life of the area IICarbon oxide emissions, in units of ten thousand tons; the carbon dioxide emission coefficient of urban life;
the established functional relation between the urban domestic electricity consumption and the urban monthly night light intensity is as follows:
EPCi_urban＝α*NTLit_urban(3)
the equations (3) and (6) are collated:
*CEi_urban＝α*NTLi_urban(10)
rewrite equation (10) to:
CEi_urban＝α/*NTLi_urban(11)
order to
γi_urban＝α/ (12)
Then the formula (12) is substituted into (11), and the functional relation between the town monthly night light intensity and the town living carbon dioxide emission is established:
CEi_urban＝γurban*NTLi_urban(13)
wherein, CEi_urbanThe unit is ten thousand tons of carbon dioxide emission in urban life;
and (4) calculating the discharge amount of the urban domestic carbon dioxide according to the formula (13).
5. The method for fast accounting of carbon dioxide emissions from urban and rural communities according to claim 4, characterized in that the method further comprises: and predicting the emission amount of carbon dioxide in urban life in a future year according to the estimated monthly night light intensity in the urban in the future year.
6. The method for fast accounting for carbon dioxide emissions in cities and towns and rural areas according to claim 3, wherein the functional relationship between rural area domestic electricity consumption and rural area domestic carbon dioxide emissions in the area is established and combined with the established functional relationship between rural area domestic electricity consumption and rural area monthly night light intensity to establish the functional relationship between rural area monthly night light intensity and rural area domestic carbon dioxide emissions to calculate the rural area domestic carbon dioxide emissions; the method specifically comprises the following steps:
establishing a functional relation between rural domestic electricity consumption and rural domestic carbon dioxide emission in the area:
EPCi_rural＝θ*CEi_rural(7)
wherein, EPCi_ruralThe unit of the electricity consumption is hundred million kilowatt hours in rural life; CEi_ruralThe unit is ten thousand tons of carbon dioxide emission in rural life; theta is the carbon dioxide emission coefficient of rural life;
the established functional relationship between the rural domestic electricity consumption and the rural monthly night light intensity is as follows:
EPCi_rural＝β*NTLit_rural(4)
the equations (4) and (7) are collated:
θ*CEi_rural＝β*NTLi_rural(14)
rewrite (14) to:
CEi_rural＝β/θ*NTLi_rural(15)
order to
γi_rural＝β/θ (16)
And (16) is substituted into (15), and a functional relation between the rural monthly night light intensity and the rural living carbon dioxide emission is established:
CEi_rural＝γrural*NTLi_rural(17)
wherein, CEi_ruralThe unit is ten thousand tons of carbon dioxide emission in rural life;
and (4) calculating the carbon dioxide emission in rural life according to the formula (17).
7. The method for fast accounting of carbon dioxide emissions from urban and rural communities according to claim 6, characterized in that the method further comprises: and predicting the discharge amount of carbon dioxide in rural life in a future year according to the estimated monthly night light intensity in the rural area in the future year.
8. An accounting system for rapidly accounting carbon dioxide emissions in urban and rural life, characterized in that the system comprises:
the light intensity acquisition module is used for respectively establishing a functional relation between the town monthly night light intensity and the town construction land and a functional relation between the rural monthly night light intensity and the rural residential site land based on the night light data, the town construction land and the rural residential site land, and calculating the town monthly night light intensity and the rural monthly night light intensity in a certain area;
the domestic power consumption acquisition module is used for respectively establishing a functional relation between the urban domestic power consumption and the urban monthly night light intensity and a functional relation between the rural domestic power consumption and the rural monthly night light intensity based on the acquired urban monthly night light intensity and the rural monthly night light intensity of the region, and calculating the urban domestic power consumption and the rural domestic power consumption of the region;
the system comprises a town life carbon dioxide emission amount obtaining module, a town life power consumption calculating module and a town monthly night light intensity calculating module, wherein the town life carbon dioxide emission amount obtaining module is used for establishing a functional relation between town life power consumption and town life carbon dioxide emission in the region, combining the functional relation with the established functional relation between the town life power consumption and the town monthly night light intensity, establishing a functional relation between the town monthly night light intensity and the town life carbon dioxide emission, and calculating the town life carbon dioxide emission amount; and
the rural life carbon dioxide emission acquisition module is used for establishing a functional relationship between rural life electricity consumption and rural life carbon dioxide emission in the area, combining the functional relationship with the established functional relationship between the rural life electricity consumption and the rural monthly night light intensity, establishing a functional relationship between the rural monthly night light intensity and the rural life carbon dioxide emission, and calculating the rural life carbon dioxide emission; and the fast accounting of the urban living carbon dioxide emission and the rural living carbon dioxide emission in the area is realized.
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| CN114974453B (en) * | 2022-05-30 | 2023-08-29 | 中南大学 | High-coverage reconstruction method for atmospheric carbon dioxide column concentration |
| CN117291628A (en) * | 2023-09-21 | 2023-12-26 | 南通大学 | Comprehensive energy system carbon emission amount calculation method, device and storage medium |
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