Examining the uncertainty of carbon emission changes: A systematic approach based on peak simulation and resilience assessment

Efforts to achieve carbon peak is one of the Chinese government's commitments, but the diversity of future development paths leads to the uncertainty of carbon emissions. Based on the carbon peak simulation, this study develops a framework to assess the carbon emission uncertainty, aiming to explore the potential low-carbon paths. The STIRPAT model is firstly introduced to explore the influence of population, economic and technology factors on carbon emissions, which is followed by emission peaks simulation. The resilience theory is then introduced to define the concept of low-carbon resilience (LCR), which refers to the ability to maintain a low level of carbon emissions. The uncertainty of carbon emission changes between different scenarios is identified by considering peaking time, cumulative increase and mitigation process. This study taking 10 Chinese coastal provinces as an example, and results show that all provinces can achieve the target of carbon emission peak in low-emissions scenario, the cumulative growth of carbon emissions is low and can be mitigated over a relatively short term, showing a strong LCR. In high-emissions scenario, Liaoning, Tianjin, Fujian and Guangxi may not have a peak before 2050, the uncertainty of carbon emission changes is relatively high, while Hebei, Jiangsu, Shanghai and Guangdong show relatively low uncertainty for the clear peaking time. The study also designs intermediate scenario to reduce the uncertainty of carbon emission changes to provide reference for each province's emission reduction path. These findings help to understand carbon uncertainty to reduce the risk of increasing cumulative emissions under the scenario of only focusing on peaking times, and provide a basis for future carbon resilience and sustainable emission reduction policies.     

Meat,Dairy and Climate Change: Assessing the Long-Term Mitigation Potential of Alternative Agri-Food Consumption Patterns in Canada

We use a newly developed model of the entire Canadian energy system (TIMES-Canada) to assess the climate change mitigation potential of different agri-food consumption patterns in Canada. For this, our model has been extended by disaggregating the agricultural demand sector into individual agri-food demands to allow for a more in-depth analysis. Besides a business-as-usual (baseline) scenario, we have constructed four different agri-food scenarios to assess the viability of reducing Canadian meat and dairy consumption in order to diminish Canada’s agricultural sector energy consumption and greenhouse gas (GHG) emissions. Our policy scenarios progressively restrict the consumption of different meat and dairy agricultural products until the year 2030. Our results suggest that the implementation of a meat and dairy consumption reduction policy would lead to a 10 to 40 % reduction in agricultural GHG emissions, depending on the severity of the scenario. This translates to a 1 to 3 % decrease in total Canadian GHG emissions by the year 2030. Besides these environmental benefits, health benefits associated with a reduction in meat and dairy consumption (as inferred from other studies) are presented as an additional source of motivation for implementing such a policy in Canada.     

Can buildings sector achieve the carbon mitigation ambitious goal: Case study for a low-carbon demonstration city in China?

China is committed to peaking its carbon emissions by 2030 and become a carbon-neutral society by 2060. The building sector that accounts for over one-third of the total carbon emissions is expected to face a great challenge in helping China achieve this goal. Shenzhen, as a low-carbon pilot city, whether its low-carbon work of urban buildings reaches the target is crucial. An attempt has been made in this study to assess the intensity of carbon emissions and associated reduction efficiency of urban buildings (operation stage) in Shenzhen by using the life cycle assessment method. The results show that the total carbon emissions generated from the buildings' operation stage have increased from 22 million metric tons (Mt) CO₂eq in 2005 to 42 (±13%) Mt. CO₂eq in 2019. Carbon emissions mainly result from the buildings' electricity use (79%), followed by refrigerant release emissions (12%). The energy conservation and carbon emissions reduction intensity in Shenzhen is at the middle level in China, and there is considerable space for improvement. According to scenario-based analysis, the carbon emission of the buildings sector can probably reach its peak by 2025 with the implementation of suitable policies – 5 years earlier than national target by 2030. Overall, this study makes a systemic analysis of the characteristics of urban buildings energy consumption and carbon emissions reduction, which can provide supportings for justifying the effectiveness of low-carbon activities in Shenzhen and beyond.     

The carbon footprint of a knowledge organization and emission scenarios for a post-COVID-19 world

The looming climate crisis requires an immediate response, in which organizations, as major contributors, should play a central role. However, these organizations need appropriate tools to measure and mitigate their climate impacts. One commonly applied method is carbon footprint analysis. Carbon footprint analyses have been conducted for various types of organizations, but knowledge organizations, such as universities and research institutes, have received far less attention, because their carbon footprint is often less visible and can be easily underestimated. This study is based on the carbon footprint analysis of one multinational knowledge organization. This analysis then helped identify the major sources of climate impacts in other such knowledge organizations. These are mainly indirect emissions (Scope 3) and to a large extent (79%) travel-related emissions. Based on these findings, three scenarios for a post-COVID-19 world were developed and analyzed. The results from the first two scenarios showed that despite a reduction in business travel and employees working from home, Scope 3 and travel-related emissions would remain the largest contributor. Only in the unlikely case of the third, non-recovery scenario did the share of travel-related emissions drop, turning heating into the largest contributor. In addition to measuring the carbon footprint, the study discusses potential mitigation strategies knowledge organizations could apply to reduce their carbon footprint. The focus is on how to avoid and reduce emissions, but new forms of carbon offsetting are also addressed. Based on the findings, a mitigation policy framework and recommendations for further research are proposed.     

The potential effects of climate change on the distribution and productivity of Cunninghamia lanceolata in China

Climate changes may have immediate implications for forest productivity and may produce dramatic shifts in tree species distributions in the future. Quantifying these implications is significant for both scientists and managers. Cunninghamia lanceolata is an important coniferous timber species due to its fast growth and wide distribution in China. This paper proposes a methodology aiming at enhancing the distribution and productivity of C. lanceolata against a background of climate change. First, we simulated the potential distributions and establishment probabilities of C. lanceolata based on a species distribution model. Second, a process-based model, the PnET-II model, was calibrated and its parameterization of water balance improved. Finally, the improved PnET-II model was used to simulate the net primary productivity (NPP) of C. lanceolata. The simulated NPP and potential distribution were combined to produce an integrated indicator, the estimated total NPP, which serves to comprehensively characterize the productivity of the forest under climate change. The results of the analysis showed that (1) the distribution of C. lanceolata will increase in central China, but the mean probability of establishment will decrease in the 2050s; (2) the PnET-II model was improved, calibrated, and successfully validated for the simulation of the NPP of C. lanceolata in China; and (3) all scenarios predicted a reduction in total NPP in the 2050s, with a markedly lower reduction under the a2 scenario than under the b2 scenario. The changes in NPP suggested that forest productivity will show a large decrease in southern China and a mild increase in central China. All of these findings could improve our understanding of the impact of climate change on forest ecosystem structure and function and could provide a basis for policy-makers to apply adaptive measures and overcome the unfavorable influences of climate change.     

Estimating the mitigation potential of the Chinese service sector using embodied carbon emissions accounting

It is universally recognized that direct carbon emissions based on energy consumption and industrial production lead to carbon leakage and inequality. This paper employs input–output analysis (IOA) and the hypothetical extraction method (HEM) to establish an embodied carbon analysis framework to resolve the above externalities. As a typical downstream consumption industry, the service sector has had very little work examining its embodied carbon transfer structure and related climate policies. In this paper, carbon flows of China's service sector between 1997 and 2015 are mapped and a scenario analysis is conducted that accounts for the service sector development plan and carbon emissions reduction targets. The results demonstrate that 13–19% of carbon flows in the Chinese economy are caused by the service sector's demand of other sectors. Controlling the industry scale and carbon intensity of its upstream industries effectively mitigates the dramatic growth of embodied carbon emissions in the service sector. The embodied carbon emissions accounting framework might provide new insights for the definition of emissions reduction responsibility on both a regional and sectoral scale. The further exploration of the service industry from this novel perspective will be helpful in realizing China's overall carbon emissions reduction goals.     

How to effectively guide carbon reduction behavior of building owners under emission trading scheme? An evolutionary game-based study

The building sector accounts for the largest proportion of global carbon emissions. The implementation of a market-based emission trading scheme offers a wider range of strategic choices and greater flexibility for building owners to reduce carbon emissions, but few of them are enthusiastic and actively engaged. To address the problem, this study explores how governments can effectively guide the carbon mitigation actions of building owners under an emission trading scheme (ETS) by continually adjusting and optimizing their regulation strategies. First, an extended evolutionary game model is built, considering the synergistic effect of multiple regulation policies, to theoretically depict the long-term interactive, extensive correlative, and dynamic feedback relationship between the government and building owners. Second, taking advantage of system dynamics as a policy laboratory, a scenario cultivation and simulation analysis is conducted to fully investigate the implementation effects of different regulation strategies based on the behavioral responses of building owners under different scenarios. The city of Shenzhen is a pioneer in covering the building sector in its carbon trading scheme in China, and its hotels above four stars are selected as the realistic setting for the simulation analysis. The results demonstrate that under the emission trading scheme, compared with increasing levels of carbon monitoring and non-financial incentives for building owners, intervention measures, including penalties, subsidies, and public scrutiny, are more efficient and important for the government. These findings provide important theoretical guidance and practical implications for the government to further adjust and optimize its carbon regulation strategies for the building sector.     

A dynamic analysis of the global warming potential associated with air conditioning at a city scale: an empirical study in Shenzhen,China

Heating, ventilation and air conditioning (HVAC) systems are a major source of energy consumption in buildings, directly and indirectly contributing to greenhouse gas (GHG) emissions. In the urban environment, and depending on local climatic conditions, air conditioning units attribute to these high energy demands. This study analyzes the use of residential air conditioning units and their associated global warming potential (GWP) between 2005 and 2030 for the city of Shenzhen, a fast-growing megacity located in Southern China. A life cycle assessment approach was adopted to quantify the GWP impacts which arise from both direct (refrigerant release) and indirect (energy consumption) sources, in combination with a materials flow analysis approach. The results show that the total GWP (expressed as carbon dioxide equivalents, CO₂ eq.) from residential air conditioning systems increased from 2.2 ± 0.2 to 5.1 ± 0.4 million tonnes (Mt) CO₂ eq. between 2005 and 2017, with energy consumption and refrigerant release contributing to 72.5% and 27.5% of the total demands, respectively. Immediate measures are required to restrict refrigerant release and reduce the energy consumption of air conditioning units, to help mitigate the predicted additional total emissions of 36.4 Mt. CO₂ eq. potentially released between 2018 and 2030. This amount equals to approximately New Zealand's national CO₂ emissions in 2017. The findings proposed in this study targets air conditioning units to reduce the GWP emissions in cities, and provide useful data references and insights for local authorities to incentivise measures for improving building energy efficiency management and performance.     

Decoupling and decomposition analysis of residential building carbon emissions from residential income: Evidence from the provincial level in China

Decoupling residential building carbon emissions from residential income has great significance for carbon mitigation and even global climate change. However, the nature of the decoupling relationship between them is still unclear. This study adopts the Tapio decoupling model to explore the decoupling relationship among residential building carbon emissions (TC), per capita carbon emissions (PC), residential carbon intensity (FC) and per capita income (PCI) across 30 Chinese provinces from 2000 to 2015. Then, the Logarithmic Mean Divisa Index (LMDI) model is used to decompose the decoupling of residential building carbon intensity and PCI at the provincial level to determine the main factors determining this relationship. Results show that the main decoupling trend between FC and PCI in 30 provinces transformed from weak decoupling state to strong decoupling state during the whole period, while there is still extensive room for TC and PC to decouple with PCI. PCI has the major inhibiting effect on the decoupling between FC and PCI, while residential energy intensity (EI) has the primarily promoting effect on the decoupling. These findings provide valuable references for international policymakers in formulating precisely targeted energy-saving and carbon-reducing policies to coordinate the relationship between income and carbon emissions, and the results also can be applied to other economies and, to a greater extent, other pollutants.     

Variability of building environmental assessment tools on evaluating carbon emissions

With an increasing importance of sustainability in construction, more and more clients and designers employ building environmental assessment (BEA) tools to evaluate the environmental friendliness of their building facilities, and one important aspect of evaluation in the BEA models is the assessment of carbon emissions. However, in the absence of any agreed framework for carbon auditing and benchmarking, the results generated by the BEA tools might vary significantly which could lead to confusion or misinterpretation on the carbon performance of a building. This study thus aims to unveil the properties of and the standard imposed by the current BEA models on evaluating the life cycle carbon emissions. The analyses cover the (i) weighting of energy efficiency and emission levels among various environmental performance indicators; (ii) building life cycle stages in which carbon is taken into consideration; (iii) objectiveness of assessment; (iv) baseline set for carbon assessment; (v) mechanism for benchmarking the emission level; and (v) limitations of the carbon assessment approaches. Results indicate that the current BEA schemes focus primarily on operational carbon instead of the emissions generated throughout the entire building life cycle. Besides, the baseline and benchmark for carbon evaluation vary significantly among the BEA tools based on the analytical results of a hypothetical building. The findings point to the needs for a more transparent framework for carbon auditing and benchmarking in BEA modeling.     

Integrated Assessment of Swiss GHG Mitigation Policies After 2012

The residential sector presents a great potential for greenhouse gases (GHG) mitigation. We perform an integrated assessment of different mitigation policies for Switzerland focusing on the residential sector. We analyze the case of pure incentive taxes and technical regulations. For our analysis, we have coupled a general equilibrium model with a Swiss residential energy model. We find that a progressive GHG tax of more than 200 USD2000/tCO₂ eq is necessary to reach a target of 50% reduction of GHG emissions in 2050. Finally, we also find that efficiency-based technical regulations provide limited additional abatement incentives.     

Assessing the impact of emissions trading scheme on low-carbon technological innovation: Evidence from China

A global consensus on carbon emission reductions has been reached for combating climate change. The Chinese government has clearly stated that it is necessary to make full use of market means to improve the level of environmental governance. Emissions trading scheme (ETS) is a typical market means to accelerate low-carbon economic transition. Low-carbon technological innovation is one of the key factors affecting carbon emissions. However, literature on the relationship between ETS and low-carbon technological innovation is relatively scarce at present. This study assesses the effect of pilot ETSs on low-carbon technological innovation, and a difference in differences (DID) model is adopted to analyze China's provincial panel data from 2003 to 2017. The results indicate that China's pilot ETSs can significantly promote low-carbon technological innovation, and changing the window period, PSM-DID and placebo test all verify the robustness of this finding. The dynamic effect test reveals that China's pilot ETSs will gradually increase the effect on low-carbon technological innovation over time. The heterogeneity analysis shows that the effect of China's pilot ETSs on low-carbon technological innovation is more obvious in Guangdong, Hubei, Tianjin and Chongqing. The mechanism analysis suggests that marketization degree and green consumption concept can positively moderate the impact of China's pilot ETSs on low-carbon technological innovation, and industrial structure upgrading plays a positive mediating role between China's pilot ETSs and low-carbon technological innovation. This study is conducive to assessing the policy effectiveness of China's pilot ETSs and provides an empirical evidence for promoting the development of the carbon emissions trading market.     

Influencing factors of carbon emissions in transportation industry based on CD function and LMDI decomposition model: China as an example

Globally, the transportation industry is one of the leading fields that generate the largest share of greenhouse gas emissions. While undergoing rapid development, countries worldwide aim to solve the problems involved in high energy consumption. Taking China as an example, this paper studies the main factors of carbon emissions in the transport sector and analyses the decoupling states between carbon emission and economic growth, making energy efficiency policies accordingly. In order to better demonstrate the dependence of the economy on the carbon emissions in China's transportation industry comprehensively, combined with the CD production function, this paper develops the decomposition and decoupling technology based on the LMDI approach. Additionally, it quantifies seven effects: energy emission intensity effect, energy structure effect, energy intensity effect, transportation intensity effect, technology state effect, labor input effect and capital input effect. The results show three major points: (1) From 2001 to 2018, the cumulative carbon emissions of China's transportation industry increased by 633.46 million tons, in which the capital input effect is the key factor driving carbon emissions, accounting for 157.70% of the total cumulative increased emissions, followed by energy structure effect at 10.39%. The labor input effect accounted for the smallest proportion at 2.26%. In this case, the technology state effect is the primary factor in restraining carbon emissions. During the study period, it reduced carbon emissions by 292.27 million tons, accounting for 46.14%. To a certain extent, energy intensity effect, transportation intensity effect and energy emission intensity inhibited carbon emissions, representing 16.67%, 5.32% and 2.22%, respectively. (2) During the research period, two decoupling states existed between carbon emissions and economic growth in China's transportation industry, specifically weak decoupling and expansive coupling. (3) The analysis of decomposition and decoupling state of influencing factors of carbon emissions shows that, on the one hand, factors promoting carbon emissions (capital input effect, energy structure effect and labor input effect) hinder the decoupling process. On the other hand, factors restraining carbon emissions (technology state effect, transportation intensity effect, energy intensity effect and energy emission intensity effect) accelerate the decoupling process. The research findings provide a new perspective for achieving carbon emission reduction in the transportation industry and curbing energy consumption growth.     

Assessing the impact of environmental regulation on pollution abatement and collaborative emissions reduction: Micro-evidence from Chinese industrial enterprises

Given the rapid industrialization and urbanization of China, environmental problems have gradually become major constraints that hinder its sustainable economic development. Moreover, China's pollution abatement and reduction of greenhouse gas emissions have been severely affected by pressures coming from domestic environmental appeals and international environmental diplomacy. By using integrated data from the Chinese Industrial Enterprise and the Chinese Enterprise Environmental Survey and Reporting databases, this study constructs comprehensive indicators of pollutant discharge intensity and carbon emissions index at the enterprise level and uses the panel fixed effect model, Kaya identity, and mediation effect model to assess the effects of environmental regulations on pollution abatement and collaborative emissions reduction from the micro-perspective. Results show that these regulations can abate the pollution emissions of Chinese industrial enterprises and verify the effectiveness of environmental policies. These regulations can also efficiently reduce the carbon dioxide emissions of enterprises through pollution abatement. In other words, environmental regulations facilitate a collaborative emissions reduction of pollutant and greenhouse gas emissions from enterprises. Such collaborative emissions reduction effect is also influenced by the energy structure and consumption of enterprises. This paper presents empirical evidence and policy basis for further improving China's environmental regulation policy system and achieving coordinated progress in China's economic development and environmental governance.     

“Emission game”: some applications of the theory of games to the problem of CO2 emission

If there are no doubts that we must reduce the total emission of carbon dioxide, then the problem of how much different countries should be allowed to contribute to this amount remains a serious one. We suggest this problem to be considered as a non-antagonistic game (in Germeier's sense). A game of this kind is called an “emission game”. Suppose that there are n independent actors (countries or regions), each of them releasing a certain amount of CO₂ per year (in carbon units) into the atmosphere, and that the emission would be reduced by each actor. Each actor has his own aim: to minimise the loss in the Gross Domestic Product (GDP) caused by the reduction of emissions. On the other hand, taking into account that it is impossible to estimate more or less precisely the impact of the climate change on GDP for each country today, a common strategy will be to reduce the climate change. Since one of the main leading factors in global warming is the greenhouse effect, then the common aim will be to reduce the sum of emissions. This is a typical conflict situation. How to resolve it? We can weigh the “egoistic” and “altruistic” criteria for each actor introducing the so-called “coefficients of egoism”. This coefficient is very large, if the actor uses a very egoistic strategy, and conversely, if the actor is a “super-altruist”, then the corresponding coefficient is very small. Using these coefficients we get the general solution of the game in a form of some Pareto's equilibrium. The solution is stable and efficient.     

Circular economy application for a Green Stadium construction towards sustainable FIFA world cup Qatar 2022™

The construction industry is responsible for a significant amount of raw material consumption and environmental footprints. Therefore, sustainable construction became a hot topic, which strives to reduce material consumption, limit constructional waste disposal, and decrease contribution to climate change. In line with Qatar's commitment to organizing a sustainable FIFA World Cup in 2022, this study aims to conduct an environmental life cycle assessment (LCA) for the construction of the Education City Stadium. The work presented here provides the first empirical LCA for analyzing the environmental and economic impacts of circular economy application in a World Cup stadium. In this research, the cyclopean concrete (CYC) methodology was utilized, which incorporate the site excavated boulders with the concrete mix to cast the under-raft foundation of the stadium. This approach was compared to the conventional concrete (CC) casting approach to assess the extent to which the newly developed methodology can reduce the environmental and economic burdens. The obtained results have shown a 32% reduction in greenhouse gas emissions when adapting the CYC approach. Thus, the CYC holds a strong promise to achieve the required structural behavior with a low-cost alternative material from existing waste products in Qatar and a lower environmental impact than the CC.     

The evolution of city-scale GHG emissions inventory methods: A systematic review

The capacity of cities to act on climate change mitigation is essential to fulfil the Paris Agreement target. In order to do so, cities should establish an effective climate policy which requires, as a first step, a complete greenhouse gas (GHG) emissions inventory. The accurate city-scale GHG inventory enables cities to develop, implement and track climate solution measures, mainly those related to transportation. The compilation of a city-scale GHG inventory requires a standardized method and up-to-date activity data. This systematic review critically examines 40 articles over the past 20 years to (1) identify city-scale GHG inventory methods being applied worldwide, (2) evaluate how these methods are evolving, (3) elaborate how emissions from transport sector are being estimated, and (4) determine what data types and sources of transport-related data are being used. The review was limited to articles that addressed the process of compilation of a GHG inventory. The results demonstrate that city-scale GHG inventory methods evolved from the Intergovernmental Panel on Climate Change (IPCC) Guidelines to a variety of GHG accounting methods that offer levels of complexity to estimate city-scale emissions. Although GHG inventory methods for city-scale have advanced over the years, almost one third of the articles reviewed were focused on the proposal of a GHG inventory framework, adjusting current methods to each city's reality or proposing new ones. The majority of the cities analysed lack local transport-related data to measure GHG emissions based on the bottom-up approach. Yet, more than 40% of the articles managed to deliver the bottom-up inventory using a diversity of data types and sources. This review shows that there is still a path to achieve a globally compatible method. This would require a joint effort between researchers and city authorities to make international protocols more compliant to each city's data availability along with the improvement of cities data collection.     

Agricultural trade shocks and carbon leakage: Evidence from China's trade shocks to the Belt & Road economies

Existing literature on carbon leakage mostly focused on polluting industries or at the national level. Agriculture is one of the main sources of carbon emissions, however, research on agricultural carbon leakage is still insufficient. To fill this gap, this paper investigates the impact of China's agricultural trade shocks on carbon emissions in a panel of 62 economies along the Belt and Road (B&R) over the period 1990–2017. The results show that China's supply shocks have a significant inhibitory effect on the agricultural carbon emissions of the B&R economies, and this inhibitory effect is very stable and will not be disturbed by other factors. On the contrary, China's demand shocks only have a significant inhibitory effect on the carbon emission intensity of economies with a higher proportion of agriculture, but it will significantly increase the agricultural carbon emissions share in all economies.     

Nuclear Versus Coal plus CCS: a Comparison of Two Competitive Base-Load Climate Control Options

In this paper, we analyze the relative importance and mutual behavior of two competing base-load electricity generation options that each are capable of contributing significantly to the abatement of global CO₂ emissions: nuclear energy and coal-based power production complemented with CO₂ capture and storage (CCS). We also investigate how, in scenarios developed with an integrated assessment model that simulates the economics of a climate-constrained world, the prospects for nuclear energy would change if exogenous limitations on the spread of nuclear technology were relaxed. Using the climate change economics model World Induced Technical Change Hybrid, we find that until 2050 the growth rates of nuclear electricity generation capacity would become comparable to historical rates observed during the 1980s. Given that nuclear energy continues to face serious challenges and contention, we inspect how extensive the improvements of coal-based power equipped with CCS technology would need to be if our economic optimization model is to significantly scale down the construction of new nuclear power plants.     

Dynamic global warming impact assessment integrating temporal variables: Application to a residential building in China

Climate warming is a global concern, and buildings have been recognized as a major contributor because the carbon emissions during their entire life cycles constitute a large share of the total value (almost 40% globally). Many life cycle assessments of buildings have been conducted to quantify the associated global warming impacts. However, few studies have considered the potential temporal variation over the long lifetimes of buildings. In this study, various temporal variables were combined to evaluate the dynamic life cycle global warming impact of a residential building in China. First, annual material and energy consumption data throughout the entire life cycle were acquired from questionnaire survey, statistical reports and literatures. Five dynamic variables (household size, usage behavior, replacement and improvement of components, waste treatment, and energy mix) and their effects on consumption levels were considered. Second, a dynamic inventory analysis tool (DyPLCA) was used to transform the temporal consumption data into dynamic greenhouse gas quantities. The global warming effects of these emissions were quantified using a dynamic characterization tool (DynCO₂). Finally, emission reduction targets for future decades were used to weight the severities of the impacts at different times. The dynamic instantaneous and cumulative global warming impacts of the building were calculated. Dynamic and static assessment results were compared. We also analyzed the contribution of each dynamic variable to the final results and found that the dynamic variables had very different effects (ranging from −42.00% to 45.34%). This study provided an operable dynamic assessment model and available dynamic data for the global warming impact assessment of buildings in China.