Introduction

Background of global carbon reduction

Coping with climate change has become one of the core issues in the world (Liu and Lin 2019). According to statistics, more than 120 countries have proposed carbon reduction or carbon neutrality related goals. To achieve this goal, most countries have formulated carbon reduction development paths based on industrial and energy policies (Levi 2021). At the same time, considering that the source of CO2 is mainly energy consumption, mainly including the transmission loss of the energy supply part, and the terminal consumption of buildings, transportation and industry (Jewell, et al. 2018; Inderwildi, et al. 2020). Therefore, targeted research on carbon reduction in the above aspects has also been generated correspondingly (Zhao et al. 2020; Lee, et al. 2019).

As countries around the world are at different stages of development, there are differences in the needs and positioning of low-carbon economic development. At present, most of the leading countries in low-carbon construction are developed countries. The urban development of these countries is relatively mature, and the energy system is also in the stage of green transformation, so that the goal of low carbon can be achieved relatively quickly (Samargandi 2019). For developing countries, economic development represents the use of energy and the increase of carbon emissions. Therefore, how to reduce carbon dioxide emissions while maintaining economic development is the main concern of developing countries (Gui, et al. 2017). For the above countries, due to the low level of urbanization, the concept of low carbon can be included in the initial planning stage (Han, et al. 2018; Yu 2020). Therefore, at the initial stage of urban construction, that is, at the stage of urban planning, the concept of low-carbon should be included. From the perspective of top-level design, promote the low-carbon transformation of buildings, transportation and industry from top to bottom, complete the "double decoupling" of economic development, energy consumption and carbon emissions through low-carbon means on both sides of supply and demand, and accelerate the realization of the goal of carbon neutrality in the city.

Review of low carbon urban planning

Low-carbon urban design is a low-carbon balance between supply and demand (Yu et al. 2021). Among them, long-term energy demand prediction is the basis of urban carbon emission reduction planning. The energy demand can also be divided into electricity, gas, coal and fuel oil according to the terminal energy consumption. The demand of some energy types shows obvious seasonality and periodicity (Chen et al. 2023; Qian, et al. 2020). Therefore, urban energy demand is a multi-coupled problem. Some researchers predict the overall energy demand through existing or self-developed software and models (Cruz and Dias 2016). Dawit (Dawit Habtu Gebremeskel 2021) and Muhammad (Muhammad Amir Raza 2022) all proposed that leap can be used to explore different possible future, predict the long-term energy demand of developing countries, and alleviate the energy crisis. Qiu (Qiu et al. 2021) and others proposed low-carbon and energy-saving cities, which will have a great impact on the development of energy demand in East China. Another part of researchers focuses on the single energy type with strong regularity of change, such as electric power, one of the important components of urban energy (Bailera and Lisbona 2018).

On the demand side, different energy use efficiency will have a significant impact on energy demand. Mohammad (Al-Saidi 2022) pointed out that low carbon urban development and energy efficiency measures in the construction sector can make cities (Saudi Arabia) more sustainable and environmentally responsible, and can produce positive spillover effects. Inigo (Munoz 2020) and Daniel (Horak et al. 2022) have proposed a comprehensive urban energy modeling and evaluation method, from the characterization of the city's current energy performance to the development and evaluation of future scenarios, to provide decision support for the transformation of the city's energy system to a sustainable and low-carbon system.

On the supply side, renewable energy is one of the cores of carbon reduction (Best and Burke 2018). Henrik (Lund 2021) and others analyzed how to convert renewable power into other energy carriers, such as thermal energy, hydrogen, green gas and electric fuel, and how to implement energy efficiency improvement and energy conservation through energyplan. Thellufsen (Thellufsen and H. Lund a, P. Sorknæs, P.A. Østergaard, M. Chang a, D. Drysdale, S. Nielsen a, S.R. Djørup, K. Sperling 2020) and others proposed a method of designing intelligent energy cities at the national level under the background of 100% renewable energy. Zeng (Zeng et al. 2022a) and others developed three renewable energy scenarios through the energyplan tool. The results show that all renewable energy scenarios in Sichuan, China can achieve zero emissions by 2060. In addition, maximizing the potential of wind power can better meet the electrification requirements of Sichuan's transportation departments than solar power.

Contribution and content

Because the planning of urban system is a multi-specialty coupling work, most low-carbon urban planning studies tend to focus on different fields such as transportation, construction and industry (Deng et al. 2022). At the same time, in the study of low-carbon cities, researchers often hope to build universal models to adapt to the medium and long-term forecast needs of different regions and cities (Zeng et al. 2022b). In fact, each city has different development goals and strategies. This has led to the fact that the current energy demand forecasting model often needs to be adjusted again in the specific application. Under the background of China's proposal of carbon peaking and carbon neutrality, this study proposes a low-carbon urban planning method that is goal-oriented and scenario-control coupling. Taking Jiashan County, Zhejiang Province, China as an example, through the analysis of the development orientation of the target city and its own objective conditions, combined with the prediction of the energy system, the supply and demand scenario applicable to a specific type of city is obtained. Based on the applicability assessment and sensitivity analysis of low-carbon technologies, the results of comparison and selection of low-carbon planning and policy guidance recommendations for such cities are obtained.

This study is divided into six parts. The first chapter introduces the background of low-carbon urban planning. The second chapter describes the methodology of the study. The third chapter describes the current situation of the research object and makes a preliminary analysis. The fourth chapter analyzes the differences of different carbon saving paths through scenario comparison. The fifth chapter is the discussion based on the research results. The sixth chapter summarizes and prospects the research.

Methodology

Urban energy and carbon emission model

There are various types of energy conversion in the process of urban operation. In this study, urban energy consumption is measured by terminal energy:

$${E}_{city}={E}_{power}\times {\varepsilon }_{power}+{E}_{gas}\times {\varepsilon }_{gas}+{E}_{oil}\times {\varepsilon }_{oil}+{E}_{coal}\times {\varepsilon }_{coal}$$

\({E}_{city}\) is the total demand for urban energy; \({E}_{power}\), \({E}_{gas}\), \({E}_{oil}\) and \({E}_{coal}\) are the consumption of electricity, gas, fuel oil and coal. Because different types of energy are measured in different ways, they need to be converted into unified units during planning; \({\varepsilon }_{power}\), \({\varepsilon }_{gas}\), \({\varepsilon }_{oil}\), and \({\varepsilon }_{coal}\) are the consumption of electricity, gas, fuel oil and coal.

The consumption of urban electricity can be calculated and compared separately by area index method and per capita index method. The area index method is:

$${E}_{power}={Load}_{power}\times {T}_{power}$$
$${Load}_{power}=\sum ({A}_{city}^{i}\times {\mu }_{power}^{i})\times {\mu }_{together}$$

\({Load}_{power}\) is the peak of urban power consumption; \({T}_{power}\) is the equivalent utilization hours after converting the annual power consumption into peak consumption; \({A}_{city}^{i}\) and \({\mu }_{power}^{i}\) are the area of various functional areas in the city and the corresponding power consumption per unit area. Among them, \(i\) represents different types of areas such as residence, commerce, office and industry; \({\mu }_{together}\) is the simultaneous utilization coefficient. Since the power utilization rules of different types of regions are different, the peak power demand is not a simple superposition.

The per capita index method for urban power consumption prediction is:

$${E}_{power}={P}_{city}\times {e}_{power}$$

\({P}_{city}\) is the predicted population of the city; \({e}_{power}\) is the annual power consumption per capita. According to different development levels, there are obvious differences in different countries and regions.

The consumption of gas needs to be distinguished according to the three types of residence, industry and transportation, and the per capita indicator method, unit GDP and unit mileage should be used for calculation.

$${E}_{gas}={P}_{city}\times {e}_{gas}+\sum ({E}_{GDP}^{j}\times {e}_{gas}^{j})+\sum ({N}_{car}^{k}\times {D}_{car}^{k}\times {e}_{gas}^{k})$$

\({e}_{gas}\) is the urban gas consumption per capita; \({E}_{GDP}^{j}\) and \({e}_{gas}^{j}\) are the GDP of a certain type of industry in the city and the gas consumption per unit of GDP. Among them, \(j\) represents different industrial fields; \({N}_{car}^{k}\), \({D}_{car}^{k}\) and \({e}_{gas}^{k}\) are the number of vehicles of a certain type in the city, the annual average mileage and the gas consumption per 100 km. Where, \(k\) represents different vehicle types.

The calculation method of fuel oil and coal is similar to that of gas, and residential and industrial needs to be distinguished. Among them, fuel consumption also needs to be calculated in the transportation field.

$${E}_{oil}={P}_{city}\times {e}_{oil}+\sum ({E}_{GDP}^{m}\times {e}_{oil}^{m})+\sum ({N}_{car}^{n}\times {D}_{car}^{n}\times {e}_{oil}^{n})$$

\({e}_{oil}\) is the urban fuel consumption per capita; \({E}_{GDP}^{m}\) and \({e}_{oil}^{m}\) are the GDP of a certain type of industry in the city and the fuel consumption per unit of GDP. \(m\) represents different industrial fields; \({N}_{car}^{n}\), \({D}_{car}^{n}\) and \({e}_{oil}^{n}\) are the number of vehicles of a certain type in the city, the annual average mileage and the fuel consumption per 100 km. Where, \(n\) represents different vehicle types.

$${E}_{coal}={P}_{city}\times {e}_{coal}+\sum ({E}_{GDP}^{l}\times {e}_{coal}^{l})$$

\({e}_{coal}\) is the per capita urban coal consumption; \({E}_{GDP}^{l}\) and \({e}_{coal}^{l}\) are the GDP of a certain type of industry in the city and the coal consumption per unit of GDP. Where, \(l\) represents different industrial fields.

In terms of energy supply, fuel and coal rely on the urban transportation system. Gas and electricity require additional transmission networks. In particular, electricity exists not only in the interaction of the power system outside the city, but also in the power generation unit inside the city.

Therefore, electric power has become the breakthrough point of low-carbon urban energy system and the core of realizing low-carbon from the supply side:

$${Supply}_{power}=\sum ({C}_{power}^{x}\times {e}_{power}^{x})+{Supply}_{grid}$$

\({Supply}_{power}\) is the urban power supply. There is difference in transmission loss between \({Supply}_{power}\) and \({E}_{power}\); \({C}_{power}^{x}\) and \({e}_{power}^{x}\) are the capacity and equivalent utilization hours of different power generation modes in the city. \(x\) represents different power production modes; \({Supply}_{grid}\) is the power supplied to the target city by the power network outside the city.

The total carbon emissions in cities also need to be expressed by the consumption of terminal energy:

$${C}_{city}={E}_{power}\times {\delta }_{power}+{E}_{gas}\times {\delta }_{gas}+{E}_{oil}\times {\delta }_{oil}+{E}_{coal}\times {\delta }_{coal}$$

\({\delta }_{power}\), \({\delta }_{gas}\), \({\delta }_{oil}\) and \({\delta }_{coal}\) are the unit energy CO2 emission coefficient of electricity, gas, fuel oil and coal respectively. Because of the difference in the composition of electricity \({\delta }_{power}\) can be expressed as the ratio of the sum of CO2 emissions generated by different power generation methods to the total power supply:

$${\delta }_{power}=\frac{\sum ({Supply}_{power}^{x}\times {c}_{power}^{x})+{Supply}_{grid}\times {e}_{grid}}{{Supply}_{power}}$$

\({Supply}_{power}^{x}\) and \({c}_{power}^{x}\) are the power output of a certain type of power production mode and the CO2 emission coefficient per unit energy; \({Supply}_{grid}\) and \({e}_{grid}\) are the supply volume of the power grid outside the city and the CO2 emission coefficient per unit energy.

Data sources and assumptions

This study is a low carbon city planning method study taking Jiashan County, Zhejiang Province, China as an example. The data sources used are mainly divided into four ways:

  1. (1)

    National energy conversion coefficient statistics, overall development strategy and urban planning standards;

  2. (2)

    The published energy structure and overall carbon emission information of the provincial power grid where the target city is located;

  3. (3)

    The government statistical yearbook, work report and future development plan of the target city are published to the public;

  4. (4)

    Relevant statistics and research results on the efficiency and annual utilization of various energy equipment (Ren, et al. 2019; Zhang, et al. 2021).

This study needs to make the following assumptions:

  1. (1)

    In terms of energy consumption of urban transportation, the energy consumption of intercity rail transit, water transport or aviation is not considered in the calculation. Only consider the energy consumption of private cars, logistics and municipal vehicles in the city.

  2. (2)

    Based on the urban service population, the difference of energy consumption between the permanent population and the floating population is not considered;

  3. (3)

    Only the carbon emissions in the process of energy use are considered, and the carbon emissions of energy equipment in other life cycle processes such as generation and transportation are not considered (Jacobson 2020). Therefore, it is considered that the electricity generated by photovoltaic, wind power, nuclear power and other means is zero carbon (Shao et al. 2022).

Case study

Current situation analysis

According to the documents and data released by the government, the current energy consumption of Jiashan County is 2.54 million tons of standard coal, of which coal, gas, oil and electricity account for 15%, 8.5%, 10% and 66% respectively. The carbon emissions of various energy sources are calculated, and the current carbon emissions of Jiashan County are about 5.1 million tons of CO2. According to the current population of 648.16 million and the GDP of 65.577 billion yuan, the per capita annual carbon emissions are 7.89 tons of CO2 / person · year, and the GDP carbon emissions are 0.78 tons of CO2 / 10,000 yuan.

Analysis of natural resource endowment

Jiashan County is located in the northeast of Zhejiang Province. According to the building climate zoning, it belongs to the hot summer and cold winter area. There are more than 507.68 square kilometers in the region, of which water area accounts for 14.29%, and water system resources are abundant.

  1. (1)

    Solar energy resources

Jiashan County belongs to the fourth category of solar energy area. The average sunshine hours over the years are 1927.3 h, and the equivalent utilization hours of solar photovoltaic are 1260 h. The solar energy resource endowment is general, but in combination with the fishery and industry in the area, the complementary fishery and photovoltaic projects on the roof of industrial plants can be promoted on a large scale. The total installed capacity of PV projects above the current PV scale has approached 200 MW.

  1. (2)

    Wind resources

Jiashan County has an average wind speed of 3.1 m / s over the years, with poor wind resource endowment, and there are no wind power projects above designated scale in the current area.

  1. (3)

    Geothermal resources

The Yangtze River Delta belongs to the Subei basin, and the earth heat flow is relatively high, about 70mW / m2. According to the long-term plan for the development and utilization of geothermal resources in China, the Yangtze River Delta is the most promising area for the development and utilization of geothermal resources in China. According to the geological test data, the shallow geothermal heat exchange in the Yangtze River Delta is 56W / m in summer and 52w / m in winter. The cooling load of a single well in summer is 5.93kw, and the heating load in winter is 5.29kw.

At the same time, there is Dayun hot spring, a provincial-level tourist resort in Jiashan County. According to the results of well drilling and testing of geothermal resources in the area by the geological survey of Zhejiang Province, it is found that many areas have potential for the development and utilization of geothermal resources. In combination with the rich water system conditions in Jiashan County, shallow ground source heat pumps and water source heat pumps with high energy efficiency can be promoted on a large scale in the region.

  1. (4)

    Biomass resources

Jiashan County has developed agriculture, but there are few large-scale forestry enterprises. The biomass resources in the region mainly come from straw, crop husks and household garbage. It can be combined with garbage power plants in the region to convert biomass resources into electricity.

To sum up, among all kinds of renewable energy, Jiashan County has high development potential in both solar energy and geothermal energy. At the same time, combined with the climate characteristics of Jiashan County, the energy consumption of air conditioning in winter and summer accounts for a high proportion, which is very suitable for matching application in combination with geothermal resources.

Future energy consumption forecast

The administrative area of Jiashan County covers a total area of 506.97 square kilometers. By 2035, the planned construction area of Jiashan County will be 161.3 square kilometers and the planned population will be 900,000, of which the population will reach 700,000 in 2025. Based on the existing development rate, by 2025, the GDP of the region will exceed 100 billion, and the corresponding energy consumption will also reach about 4.08 million TCE, that is, nearly 60% (1.5 million TCE) of the energy consumption increment. If combined with the national "14th five year plan" period GDP energy consumption reduction requirements (13.5%), the corresponding energy consumption is 3.53 million TCE, and the energy consumption increment is 40% (1 million TCE). Subsequently, in the ten years from 2026 to 2035, due to the slowdown of the national development rate, it is predicted that the GDP growth rate will gradually decrease from 10 to 5%, and maintain the GDP energy consumption reduction rate requirements during the 14th Five Year Plan period. It is predicted that by 2035 in the long term, Jiashan County's GDP will exceed 200 billion, and the corresponding energy consumption will reach 532 TCE, with an increase of about 50% (1.785 million TCE) in ten years. Combined with the decrease of carbon emissions per kWh due to the increase of the proportion of renewable energy in the power system and the conservative promotion forecast of electric vehicles in the transportation field (10% in 25 years and 30% in 35 years). In the near future, the carbon emissions in 2025 will reach 6.6 million tons of CO2, the GDP carbon emissions will be 0.63 tons of CO2 / 10,000 yuan, and the per capita carbon emissions will be 9.4 tons of CO2 / person · year; In the long term, the carbon emissions in 2035 will reach 7.83 million tons of CO2, the GDP carbon emissions will be 0.36 tons of CO2 / 10,000 yuan, and the per capita carbon emissions will be 8.7 tons of CO2 / person · year. It can be seen that due to the large-scale economic growth, it can not meet the demand for reducing carbon emissions only if it is consistent with the national energy consumption intensity reduction requirements.

Scenario setting and result

Scenario setting

According to the latest "net zero 2050: global energy industry action guide" and "2050 energy zero carbon emission roadmap report" issued by the US Energy Agency (IEA), deep electrification + renewable energy can achieve 75% of the carbon reduction goal, and combined with various energy-saving measures, it can reduce carbon emissions by 90%. Therefore, different carbon saving scenarios are set according to the renewable energy import strategy on the supply side and the energy conservation and electrification degree of buildings, industry and transportation on the demand side, as shown in the table below.

In the setting of Table 1 above, the basic scenario represents maintaining the existing energy structure and reducing GDP energy consumption with the national demand, that is, the results of the energy consumption prediction in the previous chapter.

Table 1 scenario setting of low carbon city planning in Jiashan County (Xu et al. 2020; Yu 2022)
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The decoupling scenario describes the scenario of decoupling GDP growth from carbon emissions before 2030. Carbon emissions will peak before 2030, and the energy structure has been adjusted, but the reduction level of energy consumption has been maintained. Among them, the gas substitution ratio of coal comes from the ratio of the coal consumption of the thermal power plant in Jiashan County to the overall coal consumption, that is, the 60% gas substitution indicates that all coal-fired boilers in the area except the thermal power plant need to be replaced by gas boilers.

In the low-carbon scenario, the energy structure is further adjusted on the basis of the decoupling scenario, and the requirements for energy conservation are also raised, laying the foundation for achieving carbon neutrality ahead of time. Among them, the comprehensive energy conservation rate mainly comes from the design energy conservation of new residential, public and industrial buildings, including green buildings, green industrial buildings and ultra-low energy consumption buildings. At the same time, the use of more efficient ground source heat pumps can also reduce the air conditioning energy consumption of buildings. The comprehensive energy conservation rate of 40% represents that the average building energy consumption in the region reaches the level of green buildings. In terms of transportation, electric vehicles are divided into two stages, 20% representing the full electrification of public transport in the region, and 50% representing that in addition to public transport, about half of private cars in the region will be driven by electricity by 2035.

The carbon neutrality scenario describes the scenario that carbon neutrality will be achieved by 2035. It should be noted that carbon neutrality is different from zero carbon, which means that the output and absorption of carbon emissions reach a balance. At the same time, because carbon neutralization itself is adjusted and dispatched from the national scale, it largely depends on the level of forest carbon sinks. Therefore, for the whole country, it is estimated that the national carbon sink will be about 1.5–2 billion tons of CO2 by 2060, so the corresponding carbon emissions to achieve carbon neutrality at this time will also be 1.2–1.5 billion tons. Such a long-term GDP is difficult to estimate, but the population should be at a sustained or negative growth level. Therefore, it is considered that the important indicator of carbon neutrality is about 1–1.5 tons of CO2 / person · year per capita. Correspondingly, this carbon neutralization scenario describes a carbon reduction scenario in which the per capita carbon emissions of Jiashan County will be about 1–1.5t CO2 / person without considering carbon sink when the population reaches 900,000 by 2035. In addition to the further requirements on energy structure and energy conservation, since the carbon emissions of external power will still be at a high level by 2035, this scenario can only be realized by introducing external green power. With the promotion of domestic carbon trading and green electricity trading market, combined with the huge demand for foreign green electricity in the Yangtze River Delta ecological and green integrated development demonstration area as a whole, it is judged that this scenario also has a high possibility of realization (Xia et al. 2022).

Comparative analysis of carbon saving scenarios

After each scenario is set, its energy consumption, installed capacity of renewable energy and carbon emissions need to be calculated. According to the assessment of the demand side energy conservation level of each scenario, the energy consumption under the four scenarios of basic, decoupling, low-carbon and carbon neutrality is shown in Fig. 1 below. It can be seen that by 2035, the proportion of power consumption will be greatly increased. At the same time, in the low-carbon and carbon neutral scenarios, the total energy consumption in 2025 and 2035 is relatively close, indicating that the decoupling between economic growth and energy consumption has been realized in these two scenarios.

Fig. 1
figure 1

Comparison of energy consumption and energy structure under various scenarios

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Combined with the land planning in the area, the installed capacity and power generation of PV under different scenarios are shown in Table 2 below.

Table 2 PV installed capacity and power generation under various scenarios
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Finally, the carbon emission scenarios under each scenario can be obtained by calculating the emission coefficients of different energy sources, as shown in the Fig. 2 below. The carbon emissions in 2025 and 2035 under the decoupling scenario are basically the same, which indicates that the decoupling between economic development and carbon emissions has been achieved. The peak of carbon emissions under this scenario will occur around 2030, which is consistent with the national goal. The carbon emissions of the low-carbon scenario and the carbon neutral scenario have been declining, which indicates that the peak of carbon emissions occurs in the period from 2020 to 2025, which is earlier than the national goal. At the same time, in the carbon neutralization scenario, the carbon emissions in 2035 can be reduced to 1.33 million tons of CO2, and the per capita carbon emissions can be reduced to 1.48 tons of CO2 / person · year, reaching the carbon neutralization standard. At this time, the proportion of green power that needs to be introduced additionally accounts for 30% of external power, about 1.08 billion kwh.

Fig. 2
figure 2

Comparison of carbon emissions under various scenarios

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Sensitivity analysis of low carbon level of external power

It can be seen from the comparison results of scenarios that for cities with poor resource endowment, carbon emissions largely depend on the low-carbon level of the external power grid. Therefore, this study has carried out sensitivity analysis on carbon emission coefficient per kilowatt hour of external power grid. Because when the carbon emission coefficient per kilowatt hour in 2025 increases by more than 10%, it will reach the current level in 2020. Therefore, the fluctuation range of carbon emission coefficient in this study is—30% ~ 10%. The change of urban total carbon emissions in 2025 and 2035 after the fluctuation of carbon emission coefficient per kilowatt hour is shown in Fig. 3 below.

Fig. 3
figure 3

Changes in total urban carbon emissions affected by carbon emission coefficient per kWh

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From the perspective of year, the sensitivity change in 2035 is relatively small, which is due to the relatively small carbon emission coefficient per kilowatt hour in 2035. From the perspective of scenario comparison, low carbon and carbon neutral scenarios are less affected. This conclusion can also be obtained from the comparison of sensitivity coefficients in Table 3. The reason is that under the two scenarios of low carbon and carbon neutral, the demand for conventional external power is suppressed by the photovoltaic power in the region and the green power outside the region. Therefore, the low-carbon and carbon–neutral scenarios are less dependent on the external environment of cities and have higher anti-risk capability.

Table 3 Sensitivity coefficient of carbon emission coefficient
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Discussion on technology application and decision-making

It can be seen that only the two scenarios of low-carbon and carbon neutrality meet the leading and demonstration needs of Jiashan County in the construction of green and low-carbon cities. The comparison of key indicators of the two scenarios is shown in Table 4 below. It can be seen that since the energy-saving level of the carbon neutral scenario is higher than that of the low-carbon scenario, even at a higher level of electrification, it can maintain a lower dependence on external power. The carbon neutrality scenario can achieve carbon neutrality by 2035. However, the realization of this scenario requires the purchase of additional green power, and requires higher energy conservation on the demand side and energy structure adjustment on the supply side. For the low-carbon scenario, based on the existing rate of carbon emission reduction, carbon neutrality will be achieved by about 2055, that is, 5 years earlier than the whole country.

Table 4 key indicators of each scenario
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The selection of scenarios, or the promotion of carbon saving technologies, needs to rely on the relevant support policies of the upper region and the region. In terms of industry, on the basis of shutting down bulk coal boilers, gas-fired boilers and GDP carbon emissions can be taken as the entry conditions for investment promotion; In terms of transportation, we can give priority to the full electrification of public transport, and arrange charging facilities first. The completeness of supporting equipment is basically proportional to the difficulty of promoting electric vehicles; In terms of architecture, restrictive requirements are put forward for new buildings, and at the same time, pilot projects of ultra-low energy consumption buildings and transformation incentive policies for energy conservation of existing buildings are arranged to comprehensively promote the process of building energy conservation. Starting from the actual finance, policy, industrial development and urban construction process of Jiashan County, and drawing on the specific settings of low-carbon scenario and carbon neutral scenario, a balanced development and construction path between the two is found.

This study takes Jiashan County, Zhejiang Province, China as an example to study the impact of different urban planning scenarios on carbon emissions. From the comparative results of the study, the government can plan and construct from the perspective of demand and supply:

  1. (1)

    On the demand side, the improvement of energy efficiency is one of the core measures to alleviate the pressure of carbon reduction. Efficient and accurate itemized accounting of energy consumption is an important support for the government to control energy efficiency. Therefore, the popularization of itemized measurement and digital management is an important basis for government management.

  2. (2)

    On the supply side, for most cities with poor objective resource conditions, large-scale construction of distributed photovoltaic and heat pump systems is the core measure to adjust the energy supply and demand structure. For the government, incorporating photovoltaic and heat pump construction into the policy documents as hard indicators and maximizing the development of regional resources are the premise of low-carbon urban planning. In the future, taking the government as the main body to carry out green power and carbon sink trading will also be one of the important directions in the future.

At the same time, the demonstration of low carbon technologies such as photovoltaic building integration, virtual power plants and hydrogen energy, and the promotion of low carbon life are also important work of the government as the decision-maker of low carbon city construction.

Conclusion

Guided by the goal of "carbon peak and carbon neutralization", this study takes Jiashan County as an example to analyze its energy and carbon emission status and natural resource endowment. Through the setting of four scenarios, namely basic, decoupling, low-carbon and carbon neutralization, the effects of different carbon saving paths are compared statistically, and the adaptability of future carbon reduction technologies is prospected.

The data used in this study are all from the plans and documents published by Jiashan County and the demonstration area. Some of the data are missing due to the inability to obtain internal documents or are still in the planning and proofreading stage. The reliability of the research results is also guaranteed by comparing the national level. However, for example, biomass production, waste heat of sewage plant, waste heat of data center and detailed capacity layout of ground source heat pump need to be further implemented in combination with detailed supporting planning documents. This study only compares the effects of low-carbon technology and government policies on energy conservation and carbon reduction from the overall perspective.