Emission reduction planning for carbon footprint in rural residential life cycle under the low-carbon background

Abstract

In the context of global low-carbon development, reducing rural residential carbon emissions is the key to implementing emission reduction policies. In order to reduce carbon emissions from rural housing, a carbon emission classification method based on residential life cycle assessment is proposed based on the characteristics of rural housing in China. Its innovation lies in achieving precise analysis of carbon emissions from multiple stages of residential design, construction, and use. Secondly, introducing a lifecycle based emission reduction planning strategy to achieve a new pattern of low-carbon emission reduction in rural residential areas. Taking a rural residential building as a case study, in the early stage of implementing emission reduction, the mean values of the initial carbon emissions corresponding to building energy consumption, energy consumption, and resident living habits were 689, 691, and 683, with standard deviations of 81, 79, and 84. After implementing emission reduction plans, the values decreased to 686, 674, and 631, respectively, with standard deviations reduced to 28, 32, and 13. It was evident that emission reduction planning not only significantly reduced the mean carbon emissions but also substantially decreases their variability, enhancing the stability of carbon emissions. This research contributed to a deeper understanding of the carbon emissions from rural residential life cycles and provides theoretical support and data references for the formulation and implementation of more scientific and effective emission reduction planning. Simultaneously, it promoted low-carbon development in rural areas of China, achieving a harmonious coexistence of economic and social development with environmental protection and contributing to global low-carbon development.

Introduction

In the early twenty-first century, the world began to face an unprecedented environmental challenge, especially with the global increase in carbon emissions due to large-scale industrialization and urbanization processes (Kleshch et al. 2021). In this context, low-carbon development strategies have gradually become a top priority for policy formulation and scientific research in various countries (Asgharian et al. 2021). China’s rural residential areas have a large scale and a large population base, and carbon emissions cannot be ignored. At present, China's calculation of building carbon emissions is mainly based on Western international standards, but national calculation standards mainly target residential buildings and climate environments in Western regions and are not suitable for calculating carbon emissions in rural buildings in China (Blanchard et al. 1995; Verweij et al. 2023). In addition, some domestic scholars have also designed carbon emission calculation models based on the characteristics of rural residential buildings in China, but their calculations are complex and require a large amount of computation, and their adaptability is limited (Cui et al. 2022a). In this context, in order to reduce carbon emissions from rural residential areas, a new life cycle assessment method is proposed based on the characteristics of rural housing in China, achieving analysis and carbon reduction planning of rural residential carbon emissions. There are two innovations in the research. Firstly, based on the characteristics of rural housing in China, a suitable carbon emission method for the lifecycle of housing in China is proposed, ensuring the accuracy of carbon emission analysis. Secondly, we will start from a comprehensive perspective of rural housing and propose more comprehensive carbon reduction plans to ensure the effectiveness of carbon reduction. The research content will provide technical support for carbon reduction and development in rural areas.

Related work

Against the backdrop of the increasingly severe global climate change and carbon emission issues, the carbon emissions associated with the life cycle of rural residences have garnered widespread attention. Numerous scholars have actively researched carbon emissions in this context. Ding etal. proposed the intercalation strategy of N,N-dimethylformamide, adjusting the interlayer spacing from 7.90 Å to 11.84 Å in FeOCl, thereby optimizing mass transfer kinetics and catalytic pathways. Experimental results indicate good tolerance to complex water environments. The core mechanism achieving this effect is the direct electron transfer process between Fe(IV) mediated by interlayer iron sites and pollutants, effectively removing pollutants and reducing CO2 emissions (Ding et al. 2023). Cui et al. presented a data envelopment analysis model. Based on data from 2012 to 2019, the performance of 25 international benchmark airlines for the years 2021 to 2027 was predicted. Research results reveal that Air France-KLM has the highest controlled profit, while easyJet has the lowest. Route conditions influence the potential for airlines to achieve a win–win situation of carbon reduction and income growth (Cui et al. 2022b). Liu et al. proposed the use of the U.S. EPA life cycle assessment model, taking the example of the sediment treatment and recovery project in Qingxi River, Dongguan, China. The study analyzed carbon reduction, environmental impacts, and environmental benefits at different stages. Results show that optimizing the preparation process of unfired bricks can further reduce carbon emissions and enhance environmental benefits (Liu et al. 2022). Wu et al. introduced a model to define an indicator system, evaluating urban land use efficiency under low-carbon constraints and studying the relationship between urban form and land use efficiency. Research results suggest that a compact and clustered urban form is conducive to improving land use efficiency to achieve higher land use efficiency (Wu et al. 2022a). Xue Q et al. conducted a study on the lifecycle carbon emissions of existing residential buildings. In order to reduce the carbon emissions of residential buildings, a multi-objective optimization method was proposed to minimize the lifecycle cost and carbon dioxide emissions of buildings. Among them, variable optimization design is carried out for insulation layer thickness, window type, window to wall ratio, and overhang depth. The experimental results indicate that compared to the initial residential design, there is a significant reduction in carbon emissions during the lifecycle. However, this technology did not take into account the impact of environmental climate and needs to be considered in the future to improve its feasibility (Xue et al. 2022). Kiss B et al. attempted to evaluate the relationship between building lifecycle and environmental impact in order to reduce building carbon emissions. The study used dynamic energy simulation and life cycle assessment methods to optimize and improve parameters such as building insulation type, window ratio, and enclosure structure, and introduced the cumulative optimal solution. The experimental results show that in rural areas of Hungary, there is a significant reduction in carbon emissions during the lifecycle of building construction. However, this study did not conduct any relevant research on the impact of decarbonization power combination, and further exploration is needed in the future (Kiss and Szalay 2023).

Current research on residential carbon emissions includes aspects such as carbon accounting, energy emissions, and low-carbon technologies. In the context of carbon emissions and reduction planning for rural residences, many scholars actively research this area. Zhen et al. put forth a fuzzy based solution to address the energy-water relationship and carbon reduction planning issues in regional energy systems. Research results show that water resource availability and carbon emission scenarios profoundly impact the planning of ecological grid systems. Under high carbon emission scenarios, the proportion of renewable energy generation increases, promoting the development of renewable energy (Zhen et al. 2023). Jiang et al. proposed a solution to quantify the emission reduction requirements for China to meet the air quality guidelines of the World Health Organization. The research results indicate that due to high transboundary pollution of PM2.5 (Particulate Matter 2.5) and O3, China needs to significantly reduce emissions of SO2, NOx, NH3, VOCs, and primary PM2.5. It is also necessary to address transboundary air pollution issues (Jiang et al. 2023). Garcia-Hernandez et al. proposed the establishment of a multi-regional hydro-economic model, including point and non-point source total phosphorus emissions, and extended it to a pollution reduction cost function. The study results suggest that achieving the total phosphorus reduction goal in the most cost-effective way may alter cost structures, increasing indirect costs (Garcia-Hernandez et al. 2022). Xie et al. proposed the use of polyacrylonitrile-based carbon fibers as anode material to reduce energy consumption and pollution emissions in manganese electrolysis. Research results show that the anode exhibits superior electrocatalytic activity compared to lead-based anodes, with an oxygen evolution reaction current density of up to 350 A m-2, a decrease of 112 mV in overpotential, and effective control of manganese dendrite growth, demonstrating excellent electrocatalytic performance (Xie et al. 2021). Asgharian et al. proposed a coordinated expansion planning model for power generation and transmission and carbon capture and storage expansion planning for a carbon-constrained power system. The model determines the optimal sequence and timing for coordinated transformation of carbon-emitting power generation units. The study results indicate that this is the most cost-effective planning option, even for power systems with lower expansion potential for renewable energy and hydropower resources (Asgharian et al. 2021). Feng et al. conducted a study on the characteristics of typical rural areas in southern China in order to reduce carbon emissions from rural buildings, and constructed a carbon emission analysis model based on the emission factor method. And propose measures to control building scale and improve clean energy utilization efficiency based on carbon emissions. The results showed a significant reduction in residential carbon emissions in the rural area. However, this technology only studies typical residential characteristics in the southern region, and in the future, it is necessary to analyze more residential areas to improve technical feasibility (Feng et al. 2022).

In summary, the analysis and planning control of cyclic carbon emissions from residential buildings are of great significance for regional emission reduction. Research and analysis of the latest technologies related to carbon emissions from residential cycles can effectively reduce residential carbon emissions through rational optimization of rural housing goals. However, the above technologies only consider the design and construction phase, and do not fully consider the carbon emissions during the use and maintenance phase of rural buildings. Therefore, the study will delve deeper into the carbon emissions of rural housing throughout its lifecycle and strive to reduce building carbon emissions.

Graded calculation and planning of carbon emissions throughout the life cycle of rural residences

This section mainly studies the carbon emissions and emission reduction of rural residential areas. In the analysis of carbon emissions from rural residential areas, a hierarchical calculation method for lifecycle carbon emissions is proposed. At the same time, using a typical Chinese red brick cement residential building as the data source, relevant data on the entire process of residential design, construction, use, demolition, and disposal were obtained through investigation and consultation. The results of carbon emissions during the life cycle of rural residential areas were obtained through stratified calculation. Secondly, a deep analysis of rural carbon emissions is conducted, and carbon reduction plans are proposed from the perspective of building materials and other aspects. Thus providing technical references for low-carbon development in rural areas.

Graded calculation of carbon emissions throughout the life cycle of rural residences

Low carbon emissions reduction has become a key aspect of global sustainable development, and rural housing, as an important direction for low-carbon emissions reduction, has extraordinary significance in promoting global energy conservation and emission reduction (Breuck et al. 2022). Therefore, the study will analyze the carbon emissions of rural housing based on residential life cycle assessment, providing a basis for reducing emissions in rural housing (Kou et al. 2022). The carbon emission stages throughout the entire life cycle of rural housing are shown in Fig. 1.

Fig. 1

Carbon emission stages throughout the entire life cycle of buildings

The stages of carbon emissions throughout the entire life cycle of rural residences include design, construction, usage, and disposal (Yang et al. 2022). During the research process, it was divided into five main stages, corresponding to design, material preparation, equipment construction, residential maintenance and management, and residential demolition. Carbon emissions were recorded throughout the entire building lifecycle. At the same time, it is necessary to consider the impact of geographical climate and environmental changes on carbon emissions throughout the entire stage, such as increased electricity demand in high and low temperature environments, material loss during thunderstorms, and so on. The formula for calculating the carbon index for the life cycle of residential buildings is shown in Eq. (1).

$$ GWI = \sum\limits_{j = 1}^{3} {\sum\limits_{i} {W_{ij} \times GWP_{i} } } $$

(1)

In Eq. (1), $W_{ij}$ represents the mass of the $i$ th greenhouse gas generated during phase $j$ of the residential building life cycle, for example, in the material preparation stage, the total mass of carbon dioxide produced by raw materials such as cement, wood, and steel bars during the intended process. $GWP_{i}$ denotes the global warming potential of the greenhouse gas specified by code $i$, for example, the potential value of carbon dioxide for global warming is 1, which is the main gas affecting warming. The formula for calculating the total carbon emissions throughout the building's life cycle is presented in Eq. (2).

$$ C_{LC} = C_{GH} + C_{ZB} + C_{JZ} + C_{Y} + C_{C} $$

(2)

In Eq. (2), $C_{LC}$ represents the total carbon emissions over the building's entire life cycle, this involves all carbon emissions from the five stages of design, material preparation, equipment construction, residential maintenance management, and residential demolition. $C_{GH}$ stands for carbon emissions during the design phase, mainly for the use of computers and drawings during project design to reduce carbon emissions. $C_{ZB}$ represents the carbon emissions during the preparation stage of building materials, including the total carbon emissions during the production and transportation of building materials such as concrete and steel bars. $C_{JZ}$ represents the carbon emissions during the construction phase of the equipment, including the total carbon emissions of equipment, materials, manpower, etc. during the construction process. $C_{Y}$ represents the carbon emissions during the maintenance and management phase of residential buildings, including all carbon emissions from electricity usage, material replacement, heating, and other factors during residential use. $C_{C}$ represents the carbon emissions during the demolition phase of residential buildings, including the total carbon emissions from the use of equipment, fuel, electricity, etc. during this period. The hierarchical relationship of carbon emissions in the rural residential life cycle is illustrated in Fig. 2.

Fig. 2

The grading relationship of carbon emissions during the life cycle

Due to the extremely small proportion of overall carbon emissions during the design phase in Fig. 2, it is not taken into account. The carbon emissions throughout the entire residential life cycle are mainly from fuel combustion. In equipment construction, carbon emissions mainly come from electricity, which mainly refers to the carbon emissions caused by the use of electricity by equipment during construction, such as cutting machines, mixers, etc. In addition, there is also thermal carbon emissions, which mainly refer to the carbon emissions generated by fuel driven equipment, such as excavators, mixer trucks, pouring trucks, etc. This hierarchical relationship is based on practical calculation methods and emission reduction measures. The data required for life cycle carbon emission calculations are mainly categorized into three types: products, energy, and services. The carbon emission calculation boundary for the residential usage phase is depicted in Fig. 3.

Fig. 3

Boundary for calculating carbon emissions during residential use

Carbon emissions during the residential usage phase mainly include two parts: daily operations and maintenance. The calculation boundary for the emissions during this phase focuses on the energy consumption statistics of various relevant systems, including winter heating, daily lighting, cooking, and appliance energy consumption. The preparation of construction materials is divided into the production and transportation phases, with the carbon emission calculation formula presented in Eq. (3).

$$ C_{ZB} = C_{sc} + C_{ys} $$

(3)

In Eq. (3), $C_{ZB}$ represents carbon emissions during the construction material preparation phase. $C_{sc}$ signifies carbon emissions during the production phase of construction materials. $C_{ys}$ represents carbon emissions during the transportation phase of construction materials. The formula for calculating carbon emissions during the construction and assembly phase is given in Eq. (4).

$$ C_{JZ} = C_{sg} + C_{ls} $$

(4)

In Eq. (4), $C_{JZ}$ represents carbon emissions during the construction and assembly phase. $C_{sg}$ represents carbon emissions generated by mechanical operations. $C_{ls}$ represents carbon emissions caused by temporary facilities. The formula for calculating carbon emissions during the maintenance phase of residential buildings is presented in Eq. (5).

$$ C_{Y} = C_{yx} + C_{wh} $$

(5)

In Eq. (5), $C_{Y}$ represents carbon emissions during the operational and maintenance phase. $C_{yx}$ manifests those emitted during the operational phase. $C_{wh}$ is the symbol used to describe those emitted during the maintenance phase.

Carbon emission reduction planning strategies for rural residential life cycle

China, as a densely populated developing country, has an increasingly prominent demand for energy conservation and emission reduction (Sai et al. 2022). Despite numerous studies focusing on building energy consumption statistics, research on quantifying carbon emissions remains relatively limited. Therefore, through the study of carbon emissions throughout the entire process of rural residential dwellings, summarizing energy consumption and carbon emission statistical methods, this research explores a suitable analysis method for the entire life cycle carbon emitting that aligns with the statistical characteristics of China. The rural residential energy consuming pattern is illustrated in Fig. 4.

Fig. 4

Relationship diagram of rural residential energy consumption system

The carbon emissions of rural residential buildings are not only related to the energy consumption of the buildings themselves, but also closely related to the behavior, lifestyle, and social environment of residents (Wu et al. 2022b). In terms of behavior, residents will tend to lean towards low-carbon directions in terms of transportation methods, purchasing goods, etc., such as replacing gasoline powered cars with bicycles. In terms of lifestyle, more attention will be paid to energy-saving and environmentally friendly items, which will penetrate into areas such as food, clothing, housing, and transportation, such as minimizing the use of plastic and disposable items. In the social environment, including regional policies, government regulation, and resident awareness, attention will be paid to emission reduction, such as garbage classification and recycling, strengthening supervision of high energy consumption and high pollution industries, and promoting enterprise emission reduction and energy-saving innovation. Based on the above analysis, reducing carbon emissions from energy combustion will be the optimization goal, and the calculation formula for carbon emissions is shown in Eq. (6).

$$ EF_{e} = (C_{o} R_{o} \times \frac{44}{{12}} + 28C_{m} + 265C_{n} ) \cdot C_{v} \times 10^{ - 6} $$

(6)

In Eq. (6), $C_{c}$ represents the carbon content of energy consumption, $C_{v}$ represents the heating value, and $R_{o}$ represents the oxidation rate, $EF_{e}$ represents the carbon emission coefficient of energy combustion, and $C_{m} ,C_{n}$ represent the default emissions of CH4 and N2O, respectively. Carbon emission intensity is calculated by dividing the total rural emission by the total population to obtain per capita carbon emission intensity, as expressed in Eq. (7).

$$ EF = E/A(P) $$

(7)

In Eq. (7), $A,P$ represent the rural residential building area and population, respectively. $E$ represents the carbon emissions of rural buildings. ED represents the carbon emission intensity based on population and area. The principles of emission reduction optimization for rural residences are illustrated in Fig. 5.

Fig. 5

Principles for optimizing emission reduction in rural residential areas

The carbon emission issues throughout the life cycle of rural residences need to be addressed through emission reduction optimization in directions such as wall material selection, insulation technology optimization, and architectural form adjustments (Usman and Abdullah 2023). Firstly, choosing materials with low heat dissipation efficiency and good insulation performance can effectively reduce carbon emissions. Secondly, optimizing construction processes and focusing on detailed treatment of various parts of the residence are crucial. In architectural design, efforts should be made to minimize exposed walls and adopt a layout style that connects households to reduce heat loss. The optimization goals are determined by minimizing the composite Gini coefficient to characterize fairness, using an average criterion, as shown in Eq. (8).

$$ Gini_{multi} = \frac{1}{m}\sum\limits_{j = 1}^{m} {Gini_{i} } $$

(8)

In Eq. (8), $\min (Gini_{multi} )$ represents the optimization objective. Strict control over the data quality is applied to emissions reduction optimization, with the minimum value taken as the comprehensive optimization result. The formula for calculating the average value is shown in Eq. (9).

$$ S_{DQI,avg} = \frac{1}{n}\sum\limits_{i = 1}^{n} {S_{DQI,i} } $$

(9)

In Eq. (9), $S_{DQI,i}$ represents the data quality score of the indicator $i$. When uncertain indicators are not independent, the formula for calculating the overall data uncertainty is presented in Eq. (10).

$$ \sigma_{t}^{2} = \sigma_{b}^{2} + \sum\limits_{i = 1}^{5} {\sigma_{a,i}^{2} } $$

(10)

In Eq. (10), $\sigma_{t}$ represents the overall data uncertainty, $\sigma_{b}$ represents the basic data uncertainty, and $\sigma_{a,i}$ represents the additional uncertainty of the corresponding indicator $i$. The strategy for reducing carbon emissions throughout the entire life cycle of rural residential buildings is presented in Table 1.

Table 1 Table of life cycle carbon reduction strategies for rural residential buildings

The emission reduction strategies for rural residential buildings include: optimizing building design during the design phase and reducing exposed walls. Strengthen the use of environmentally friendly materials during the material preparation stage and optimize the material scheduling process. During the equipment construction phase, carry out green construction to reduce the cost of fuel equipment construction. Strengthen the utilization of thermal efficiency in residential maintenance and management, such as using energy-saving appliances and installing solar water heaters. During the residential demolition phase, optimize the demolition sequence and the reuse rate of waste materials. The relationship between the external surface area of rural residential buildings and energy consumption is positively correlated, and the calculation formula is shown in Eq. (11).

$$ S = \frac{{F_{o} }}{{V_{o} }} = \frac{2nh(a + b) + ab}{{nhab}} = 2(\frac{1}{a} + \frac{1}{b}) + \frac{1}{nh} $$

(11)

In Eq. (11), $S$ represents the building's form factor, $F_{o}$ F represents the external surface area of the building, $n$ represents the number of building floors, $h$ represents the building height, $a$ represents the width of the residence, $b$ represents the depth of the residence, and $V_{o}$ represents the volume of the residence. Finally, a comprehensive assessment of the impact of long-term emission reduction plans is needed to determine the impact of emissions reduction on sustainable development in rural areas. The ratio of the reduction in residential carbon emissions after the use of emission reduction measures to the total carbon emissions throughout the entire life cycle will be used as the evaluation standard in the study. The higher the proportion of carbon reduction, the better the regional emission reduction. The calculation formula is shown in Eq. (12).

$$ \delta_{i} = ((C_{LC} - C_{LCi} )/C_{LC} ) \times 100\% $$

(12)

In Eq. (12), $\delta_{i}$ represents the carbon emission sensitivity of the $i$ th emission reduction measure, $C_{LC}$ represents the total life cycle carbon emissions of the residence, and $\,C_{LCi}$ represents the value after the implementation of the $i$ th emission reduction measure. Finally, the biggest obstacle in rural residential emission reduction strategies lies in long-term implementation, where the government plays a decision-maker role, while rural residents, as members of the community, play the role of executors of emission reduction. Therefore, the government has introduced relevant preferential policies, such as providing appropriate subsidies for purchasing environmentally friendly building materials, reducing residential electricity consumption, and lowering electricity prices, to ensure the sustainable development of rural residential emission reduction.

Carbon emissions and reduction calculation throughout the life cycle of rural residential areas

Result analysis

To validate the effectiveness of the life cycle assessment method proposed in this study, an experimental environment was chosen for trial assessment. All experimental data in the experiment will be strictly confidential, including process data such as design and material preparation. For data involving personal information, such as lifestyle information, personal electricity information, etc., anonymization will be carried out to ensure that specific individuals cannot be traced through the data. At the same time, during the experiment, strictly abide by relevant laws, regulations, and ethical standards to ensure the legality and morality of the experiment. The experimental setting was in a typical rural area in China, and a representative rural residence was selected as the research subject. The residence was constructed using common rural building materials such as red bricks and cement, with standard living functions including living areas, kitchen, bathroom, and bedrooms. Employing the life cycle assessment method, the comprehensive energy consumption and carbon emissions throughout the entire process from design, construction, use to dismantling of rural residences were thoroughly examined. Additionally, to more accurately assess the emissions, the impact of residents' habits and behavior on energy consumption was considered. And introduce residential buildings in urban areas for comparison. The buildings in urban areas are 120 m tall and designed with steel–concrete structures. The optimization strategy refers to Table 1. The carbon reduction comparison between urban and rural residential buildings is shown in Fig. 6.

Fig. 6

Carbon emission coefficient results of energy use and household waste disposal for rural and urban residents

In Fig. 6, the use of natural gas, electricity, and rural coal in urban and rural residential areas has shown an increasing trend, mainly due to the increase in the number of household appliances and energy demand. As shown in Fig. 6a, the carbon emissions from rural residential areas increase over time, the carbon emissions of natural gas increased from 5.12 kgCO2/t to 45.26 kgCO2/t, coal emissions rose from 2.24 kgCO2/t to 34.97 kgCO2/t, and carbon emissions from electricity usage increased from 3.57 kgCO2/t to 42.96 kgCO2/t. In contrast, Fig. 6c shows the growth trend of carbon emissions from natural gas, electricity, and energy use in urban residential areas over time. Due to the predominance of natural gas and electricity in the city, electricity will reach its peak in 2022, with the highest carbon emissions reaching 55.65kgCO2/t. In Fig. 6b, after implementing emission reduction plans, the carbon emissions of rural residential buildings during their lifecycle significantly decreased. The highest carbon emissions of natural gas, coal, and electricity have decreased to 23.58kgCO2/t, 18.66kgCO2/t, and 18.69kgCO2/t, respectively. In contrast, Fig. 6d shows that after implementing emission reduction measures for urban residential buildings, their carbon emissions from electricity have decreased, reaching a maximum of 40.25kgCO2/t in 2022, while their natural gas carbon emissions have increased to 41.25kgCO2/t. Overall, both rural and urban residential areas have seen a decrease in carbon emissions after carbon reduction, but cities are limited by the fact that natural gas is a necessary energy source for daily life. The decrease in carbon emissions from electricity has led to an increase in carbon emissions from natural gas. Overall, carbon reduction strategies in rural areas are significantly better.

Figure 7 shows the carbon emission results at different stages, with carbon emissions showing a slowing trend over time. In order to better reflect the carbon emissions at different stages, mean carbon emissions are used as the evaluation benchmark, with mean carbon emissions being the average annual carbon emissions. In the building materials stage, the mean carbon emissions were 42.35 kgCO2/t, and in the construction process stage, the mean carbon emissions were 48.68 kgCO2/t. In the energy usage stage, the mean carbon emissions amounted to 37.94 kgCO2/t, indicating the energy consumption and carbon emissions during the usage of rural residences. The mean carbon emissions in the waste disposal stage were 39.88 kgCO2/t, revealing the impact of waste disposal on carbon emissions. Thus, it was evident that each stage of the carbon emissions system of rural residences exhibited varying degrees of carbon emissions, with means ranging from 37.94 kgCO2/t to 48.68 kgCO2/t. The standard deviations of life cycle carbon emissions and the comparison with building process carbon emissions are shown in Fig. 8.

Fig. 7

Emission results of rural residential carbon emission systems at different stages

Fig. 8

Comparison of life cycle carbon emission standard deviations and construction process carbon emissions of rural residential buildings

In Fig. 8a, the standard deviation in the building design phase of the rural residential carbon emission system decreases from 11.23 to 2.97. During the construction phase, the standard deviation decreases from 16.31 to 2.68, and in the building usage phase, it decreases from 13.89 to 2.76. It is observed that the volatility of carbon emissions decreases. However, in the building demolition phase, the standard deviation increases from 15.75 to 4.02. In Fig. 8b, the carbon emissions generated in the four stages of the building process in the rural residential carbon emission system are 65.37, 99.74, 91.25, and 58.53, respectively. It can be seen that as the life cycle progresses, the volatility of carbon emissions gradually decreases, and each building stage exhibits different characteristics of carbon emissions. The comparison of rural residential carbon emissions before and after emission reduction planning is shown in Fig. 9.

Fig. 9

Carbon emissions results of rural residential areas before and after emission reduction planning

In Fig. 9a, before the implementation of emission reduction planning, carbon emissions from rural residential buildings were at a higher level. The average carbon emissions from building construction were 56.21 ktCO2, and those from residents' lifestyle habits were 42.15 ktCO2. In Fig. 9b, after the implementation of the emission reduction plan, the average carbon emissions from rural residential building construction decreased to 32.61 ktCO2, the carbon reduction ratio is 25.01%, significantly lower than the pre implementation level, including the use of new environmentally friendly synthetic building materials, prefabricated panels, and environmentally friendly bamboo building materials. In addition, the average carbon emissions from residents’ lifestyle habits have decreased to 36.78 ktCO2, the carbon reduction ratio is 12.74%, indicating that emission reduction plans have a positive effect on improving lifestyle related carbon emissions. Therefore, emission reduction planning has reduced carbon emissions from both building and residents' lifestyle habits, providing practical support for achieving low-carbon and sustainable development in rural areas. The comparison of carbon emissions before and after emission reduction planning is shown in Table 2.

Table 2 Comparison of carbon emission results before and after emission reduction planning

According to Table 2, before the implementation of emission reduction planning, the sample means of life cycle carbon emissions corresponding to building energy consumption, energy consumption, and residents' lifestyle habits were 689, 691, and 683, with standard deviations of 81, 79, and 84, and coefficients of variation of 0.49, 0.52, and 0.48, respectively. It is evident that, without the implementation of emission reduction planning, the differences in carbon emissions means in various scenarios are not significant, but there is relatively large variability, especially in residents' lifestyle habits. However, after the implementation of emission reduction planning, the sample means of life cycle carbon emissions in various scenarios decrease to 686, 674, and 631, with significantly reduced standard deviations of 28, 32, and 13, and increased coefficients of variation of 0.54, 0.52, and 0.55, respectively. This indicates that the implementation of emission reduction planning not only effectively reduces the mean carbon emissions but also substantially reduces the variability of carbon emissions, enhancing the stability of carbon emissions.

Discussion

Against the backdrop of increasingly severe global climate change and environmental pollution, low-carbon emissions have become a common global goal. As the world's largest developing country, China holds a significant position in global carbon emissions. As of 2020, according to China's population census data, China's rural residential area has reached 23.3 billion m2, accounting for 42% of the national residential area, which produces huge carbon emissions. Therefore, accelerating energy conservation and emission reduction in rural residential areas is crucial. In this regard, the study takes a typical rural residential area in China as the research object, and studies the carbon emission reduction methods of rural housing through the life cycle of housing. The impact of emission reduction strategies, comparison with urban areas, challenges, and future directions are discussed from three aspects.

The impact of emission reduction strategies

Based on the analysis of carbon emissions throughout the entire lifecycle of rural residential buildings, it is beneficial to systematically analyze the carbon emissions of rural residential buildings throughout their construction, use, and phase out. Effective measures can be formulated through each link to achieve emission reduction effects. The ultimate impact of its carbon reduction strategy is reflected in four points: firstly, promoting the optimization of energy consumption structure, by improving the energy utilization efficiency of rural housing, reducing dependence on traditional high carbon energy, and accelerating the healthy development of low-carbon housing in rural areas; The second is energy conservation and emission reduction, starting from the entire life cycle of material production, construction, operation, and demolition, reducing energy, material and other resource consumption, and responding to national emission reduction development goals; The third is to stimulate the economic development of rural areas. By implementing the rural housing emission reduction plan, it will effectively stimulate the development of housing related environmental protection industries and enhance the quality of rural life.

Comparison between urban areas

Through the analysis of the entire life cycle of rural residential buildings, a certain residential building in the city was selected as the reference object, and there were significant differences in carbon emission reduction effects between rural and urban residential buildings. In recent years, the use of natural gas, electricity, and rural coal in urban and rural residential areas has been on the rise, which is related to the increase in regional energy demand and the number of electrical appliances. For example, the carbon emissions from natural gas in rural areas have increased from 5.12 kgCO2/t to 45.26 kgCO2/t, coal emissions have increased from 2.24 kgCO2/t to 34.97 kgCO2/t, and the carbon emissions from energy use have increased from 3.57 kgCO2/t to 42.96 kgCO2/t. But after implementing building carbon reduction measures, the highest carbon emissions from natural gas, coal, and electricity in rural areas decreased to 23.58kgCO2/t, 18.66kgCO2/t, and 18.69kgCO2/t, respectively. After the implementation of the emission reduction plan, there has been a significant reduction in carbon emissions from rural natural energy use, including improvements in electricity habits, adjustments to daily energy consumption, and the ability to turn off unused light bulbs and unnecessary electrical appliances. Compared to urban housing, it is different. After the implementation of carbon reduction, the carbon emissions from electricity have been reduced, but the demand for natural gas has increased, mainly because natural gas is a necessary energy source for urban residents. In addition, emission reduction technologies have been implemented in rural areas at multiple stages, including residential design, use, and demolition. After the implementation of emission reduction measures, the carbon emissions in the region gradually stabilize, with the standard deviation in the design stage decreasing from 11.23 to 2.97. In addition, a comparison was made between the carbon emissions from rural residents' living habits before and after emission reduction and the carbon emissions from building construction. The average decrease was 36.78 ktCO2 and 32.61 ktCO2, respectively. In residential construction, rural areas actively use environmentally friendly bamboo building materials, prefabricated panels, and new environmentally friendly synthetic building materials as construction materials, resulting in a significant reduction in building carbon emissions. It can be seen that implementing carbon reduction throughout the entire life cycle of residential buildings can have a significant impact on reducing carbon emissions in various aspects of housing. Compared with urban housing, rural areas have more advantages in natural use, residential design, construction, and other carbon emissions.

Challenge and future

There are three plans for the future. Firstly, we will deepen research on the lifecycle carbon emissions of rural housing, explore more accurate carbon emission calculation methods and models, which will be more conducive to the implementation of carbon reduction in rural housing; The second is to formulate practical and feasible emission reduction policies and measures, in which the government formulates corresponding policies and actively encourages public participation; The third is to strengthen community participation and public education. By raising residents' awareness and participation in low-carbon living, a good atmosphere for the whole society to jointly promote emissions reduction can be formed.

Although emission reduction plans have achieved significant results in rural areas, there are still many challenges in practical implementation, such as limited awareness and acceptance capacity in rural areas, which is not conducive to carbon reduction. Therefore, it is necessary to strengthen policy guidance and enhance carbon reduction education and publicity. Secondly, promoting clean energy to replace traditional rural areas in rural areas will be influenced by concepts and economic factors. Therefore, process optimization should be carried out before ensuring people's livelihoods to better promote rural economic development.

Conclusion

Against the backdrop of global efforts to promote low-carbon development, the issue of life cycle carbon emissions from rural residential areas has garnered considerable attention. In order to better understand this problem and identify solutions, an in-depth study on the life cycle carbon emissions of rural housing was conducted, along with the design of corresponding emission reduction plans. The study utilized comprehensive data and rigorous analytical methods, revealing that, during the building materials stage, the mean carbon emissions were 42.35 kgCO2/t, while the mean carbon emissions during the construction process stage were 48.68 kgCO2/t. In the energy usage stage, the mean carbon emissions were 37.94 kgCO2/t, and during the waste disposal stage, the mean carbon emissions were 39.88 kgCO2/t. These findings disclosed varying degrees of carbon emissions at different stages of the rural residential carbon emission system, all ranging between 37.94 kgCO2/t and 48.68 kgCO2/t. Finally, through the implementation of emission reduction plans, the average carbon emissions from rural residential building construction have decreased to 32.61 ktCO2, with a carbon reduction ratio of 25.01%. In addition, the average carbon emissions from residents' living habits have decreased to 36.78 ktCO2, with a carbon reduction ratio of 12.74%. The research provides important data support for a deeper understanding and effective reduction of carbon emissions throughout the lifecycle of rural residential buildings. Although low-carbon emission reduction in rural residential areas has achieved good application results, the emission reduction plan still faces many challenges. Therefore, strengthening the formulation and implementation of rural residential emission reduction policies will be conducive to the development of work, including promoting green building materials, providing low-carbon subsidies for residents' housing construction, and strengthening low-carbon environmental education and publicity. In the future, carbon reduction in rural residential areas needs to focus on exploring building materials, such as introducing waste crops to press bricks for building houses, strengthening the use of bamboo products for building houses, and introducing the latest green composite building materials. At the same time, optimizing the configuration of traditional bricks, cement, and other materials to reduce energy consumption and achieve energy-saving and emission reduction goals. In summary, the research on carbon reduction throughout the life cycle of rural housing is consistent with international goals such as the Paris Agreement and the United Nations Sustainable Development Goals, which is of great significance for enhancing the relevance and significance of research, promoting global climate governance and sustainable development.