Annual Carbon Emissions Research Articles

The impact of internet celebrity economy on sustainable city design: From the perspectives of economics and carbon emissions

Internet Celebrity Economy (ICE) has become a mainstream trend nowadays, and it has a great impact on the sustainable development of cities in the aspects of the new consumption and travel patterns. In this study, the concept of carbon missions per unit consumption (CEPC) is introduced, which is used to represent the combined effects of ICE on cities’ economy and carbon emissions. The influencing factors can be divided into three categories: Internet-famous stores, consumers, and cities. A regression model is constructed and used to analyze the influence mechanism of each relevant factor on CEPC by category. Results indicate that CEPC is trivially correlated with Internet-famous store factor and significantly correlated with consumer and city factors. Occupation, total consumption, carbon emissions, and travel mode within the consumer factor have correlation coefficients of 0.083, −0.230, 0.937, and, 0.693, respectively; and annual carbon emissions per capita, carbon emissions per unit of gross domestic product per capita, and urban road area per capita within the city factor have correlation coefficients of −0.042, −0.041, and −0.052, respectively. The city factor has less significant influence on CEPC than the consumer factor. Finally, suggestions for sustainable urban development in the context of ICE are presented from three perspectives: urban design, consumer behavior, and business strategy.

Study on the multi-energy complementary absorption system applied for combined cooling and heating in cold winter and hot summer areas

Under the background of carbon neutrality, efficient and low-carbon cooling and heating in rural areas away from the centralized network is a meaningful topic. In this paper, a multi-energy complementary absorption system is proposed to provide space heating in winter and cooling in summer. The system utilizes renewable energy that is abundant in rural areas, including solar and biomass, and balances the energy supply through natural gas replenishment. By adopting the cooling/heating medium circulation, multiple sets of indoor terminals are driven by a single set of absorption machine and outdoor unit. It is found that as long as the renewable energy ratio is higher than 0.2, the economic performance of the proposed system will be outstanding over the existing methods. When applied in Beijing, the annual operating cost for a typical household is reduced by 25.5–46.8% compared with traditional gas furnace/compression heat pump combined with air conditioner. Moreover, even when the proposed system is driven solely by natural gas, the carbon emission is reduced by 16–20% compared with traditional methods. When the renewable energy ratio is 0.4, the carbon reduction ratio reaches 41–44%, and the annual carbon emission for cooling and heating of a typical household reduces below 3000 kg. It is expected that by solving the problem of load and concentration variation during the year-round operation, the proposed system has great application potential in cold winter and hot summer areas away from the centralized cooling or heating network.

ASSESSING STRATEGIES FOR REDUCING THE CARBON FOOTPRINT OF TEXTILE PRODUCTS IN CHINA UNDER THE SHARED SOCIOECONOMIC PATHWAYS FRAMEWORK

To realize China’s target of carbon neutrality by 2060, the country’s domestic textile industry faces tremendous pressure to reduce emissions. We assessed the potential of socioeconomic conditions and climate policies for reducing the greenhouse gas (GHG) emissions of textile products in China up to 2050 using a life cycle assessment (LCA) approach and integrated assessment model (IAM) within the Shared Socioeconomic Pathways (SSP) framework. The results showed that a combination of socioeconomic conditions and climate policies can reduce annual carbon emissions by 89.0% and reduce accumulate emissions by 34.3% by 2050. Among the strategies examined in this study, energy decarbonization and power conservation exhibited the highest potential for reducing emissions. We also demonstrated the importance of improving industry interconnectivity, developing textile recycling frameworks, and promoting sustainable consumption.

The synergy of environmental and microbial variations caused by hydrologic management affects the carbon emission in the Three Gorges Reservoir

The synergy of environmental and microbiological changes caused by hydrologic management on carbon emissions of river reservoirs remains unknown. Here, we investigated physiochemistry parameters, compositions of dissolved organic matter (DOM), carbon fluxes (CH4 and CO2), and microbial communities in the surface waters of the Three Gorges Reservoir (TGR) within one whole hydrological year. The results showed that hydrologic management significantly changed physiochemistry and DOM composition of the TGR water, and further influenced microbial community composition and functions. DOM content during the drainage period was much lower than during the impoundment period. During the impoundment period, humification extent of DOM became decreasing, while biotransformation extent became increasing compared with the drainage period. DOM composition and water pH exhibited significant correlation with the fluxes of CH4 and CO2, respectively. Microbial community composition and function significantly differed between the drainage and impoundment periods. Most of the differential microbial taxa were affiliated with functional groups involved in carbon cycle such as methanotrophy and phototrophy, which showed significant correlation with carbon fluxes. CH4 and CO2 fluxes can be mostly explained by synergy of microbial function with DOM composition and water pH, respectively. Such synergistic effect may account for the observed temporal variations of CH4 fluxes and spatial variations of CO2, and for the relatively low annual carbon emissions in the TGR. In summary, the synergy of environmental and microbial variations caused by hydrologic management affects carbon emissions from river reservoirs.

Importance of corrosion protection on steel materials in reducing carbon emissions: Carbon emission measurement throughout the life cycle of steel pipeline as an example

<p indent="0mm">This paper studies the calculation method of carbon emissions throughout the life cycle of steel materials covering all stages of manufacturing, transportation, installation, service, and recycling. Taking steel pipelines as an example, this paper explores the impact of corrosion protection on the life cycle carbon emissions and annual average carbon emissions of steel materials. A carbon emission calculation method for all links in the life cycle of engineering steel materials in corrosive environments has been established. In addition to “carbon emissions per unit GDP (carbon emission intensity),” another intensity index is proposed as “life cycle average annual carbon emissions (carbon emissions per unit time).” This intensity index can constrain the life cycle carbon footprint in the time dimension. It is the first to quantify the important role of corrosion protection in controlling carbon emissions from steel materials at home and abroad. Through. Using appropriate anticorrosion technology, steel pipelines can reduce emissions by more than 60% in typical chemical production environments, more than 83% in oil and gas field environments, more than 50% in long-distance pipelines, and more than 28% in urban gas pipeline networks. This study is important in developing low-carbon corrosion control methods and improving corrosion protection, which controls the life cycle carbon emissions and annual average carbon emissions of steel materials, thereby providing a new perspective for the corrosion protection design and engineering implementation of steel structures. Consequently, it provides a new methodology for reducing carbon emissions of steel materials.

Roadmap to urban energy internet with wind electricity-natural gas nexus: Economic and environmental analysis

Electrolysis hydrogen generation technology is one of the feasible ways to alleviate the problem of wind electricity curtailment. One promising hydrogen value-added application is to blend hydrogen into the natural gas grid and sell it as the heat energy carrier. This paper aims to discuss the feasibility of a roadmap to urban energy internet with wind electricity-natural gas nexus. Firstly, a framework is raised to integrate wind electricity generation, electrolysis hydrogen generation, and hydrogen-natural gas blending systems. Secondly, a series of reasonable hydrogen supply profiles are provided based on annual electricity curtailment and realistic natural gas scheduling. Then, an energy optimisation model and a techno-economic model are applied to simulate the generation of electricity and hydrogen, as well as determine the most economical hydrogen supply scheme. Finally, a case study in the Beijing-Tianjin-Hebei region of China is taken to validate the benefits of the proposed roadmap. The preferred scheme is worked out with the net present value of 88.8 M$, including the economy configurations of the electricity-hydrogen hybrid generation system, as well as the hydrogen-natural gas blending plan. The results also indicate that annual electricity curtailment and annual carbon emission are decreased by 204 GWh (48.8%) and 40.2 kt (49.9%).

Investigation and evaluation of building energy flexibility with energy storage system in hot summer and cold winter zones

The dramatically increasing energy demand of building air-conditioning in hot summer and cold winter zones fluctuates greatly, especially during the period of cooling and heating in summer and winter, which exerts strict operation burden and challenge on power-grid system stability. In order to realize building energy flexibility, this paper proposes a type of energy utilization system including electricity chiller, gas-boiler, electricity heater, cold and thermal energy storage tank (case II), on the basis of electricity chiller and gas-boiler for cooling and heating demand (case I), which is commonly used as cold and heat source in hot summer and cold winter zones. The total cost of the whole life period and annual carbon emission of energy systems are served as objective function is optimized. Furthermore, the system capacity confirmation and load demand management control are analyzed and discussed, the characteristics of energy-flexibility with and without energy storage are presented, the load coefficient is introduced to evaluate the impact of case II on building energy flexibility. Compared with case I, with the deployment of cold and thermal energy storage, the cost-effectiveness of case II is 16.5% and carbon emission is reduced by 30.9% compared with case I .In case II, the load coefficient of electricity chiller and electricity heater is 83.34% and 30.65% respectively, which means that energy storage system enables to promote building energy flexibility improvement and grid-friendliness enhancement. This paper provides methods and theoretical guidance for the planning-operation of building energy system and building energy flexibility in hot summer and cold winter zones.

Optimal Configuration of a Negative Carbon Emission Energy System for Green Agriculture

Agriculture has been the second largest emission sources, contributing to 23% of total global greenhouse gas emissions. Direct air capture (DAC) technology can capture CO2 in decentralized carbon emission sources, which is suitable for the development of a negative energy system to compensate for the emissions generated from agriculture. For this reason, this paper presents a DAC-based green agriculture energy system consisting of DAC, wind power, solar power, battery energy storage system and electrical boiler to meet the negative carbon reduction energy supply requirement for agricultural area. Dry reforming methane and microalgae planting technologies are also deployed to fully utilize the captured CO2. To better coordinate the multiple energy generation, conversion, consumption and storage devices within the green agricultural energy system, a capacity configuration optimization method considering the objective of minimizing the total investment and operating costs is proposed. This paper takes a 150 hm2 agricultural area located in Nanjing, China into consideration, which has a carbon emission intensity of 2,007.5 kg/hm2. The case study showed that, the proposed energy system can obtain the most economic equipment capacities while achieving the goal of annual negative carbon emission at the expenses of $1.17 million annual initial investment and $60 thousand operation costs.

Design and simulation of global model for carbon emission reduction using IoT and artificial intelligence

Human-induced carbon emissions and the resulting increase in global warming are the major threats to the habitability of our world. Even though there are several reasons for carbon emission, the energy consumed by the residences also has a significant impact on this. The developments in technology create tools to fight global warming. Internet of Things (IoT) and Artificial Intelligence (AI) have become the primary of these tools. AI can learn, establish relationships, and make decisions for particular problems, and combining the capabilities of AI with the practical and efficient use of the IoT would accelerate the fight against carbon emissions. However, global implementation of these tools is increasingly crucial for the solution. In this study, a global model based on IoT and AI has been designed to control residences’ energy consumption. The model is trained using the Decision Tree (DT) algorithm, and unique data sequences are created for each unit of the model. The smallest units are directed with central intelligence by providing data minimization. The pre-simulation of the model shows that the model is capable of reducing and stabilizing annual carbon emissions at the targeted rate by intervening with the devices connected to the global model and providing 21% of the decrease in carbon emission. Therefore, improving, developing, and implementing the model in the medium term could be used as one of the primary practical tools to reduce carbon emissions.

Grey Correlation Analysis of Low-Carbon Governance in Yangtze River Delta Cities.

The excessive emission of carbon dioxide will bring unpredictable ecological crisis, so it is particularly urgent to study the related factors of carbon emissions. Based on the grey correlation model, 31 factors in 5 aspects are selected as the reference frame for low-carbon governance, and the grey correlation degree of urban carbon emissions is calculated by using the IPCC method to calculate the annual carbon emissions of 9 major cities in the Yangtze River Delta from 2010 to 2019. Through the calculation and analysis of panel data, the following conclusions are drawn: The allocation of urban environmental practitioners is an important factor in carbon governance, and the reasonable and scientific allocation of environmental practitioners can have a significant impact on low-carbon development; the relationship between the amount of industrial power consumption and carbon dioxide emissions is not significant. On the contrary, the power consumption of urban residents can well reflect the level of carbon emissions. High residential power consumption means that the living standard of the people in the region is high, and the corresponding resource and energy consumption is large, so the carbon emissions will increase; the size of population density is particularly important for carbon governance, which is more obvious in economically developed areas. Urban economic development will inevitably lead to the improvement of people's quality of life, a stronger demand for resources, and a significant increase in carbon emissions.

A qualitative assessment of the impact of smart homes and environmentally beneficial technologies on the UK 2050 net-zero carbon emission target

PurposeThere are 29 million homes in the UK, accounting for 14% of the UK's energy consumption. This is given that UK has one of the highest water and energy demands in Europe which needs to be addressed according to the Committee on Climate Change (CCC). Smart homes technology holds a current perception that it is principally used by “tech-savvy” users with larger budgets. However, smart home technology can be used to control water, heat and energy in the entire house. This paper investigates how smart home technology could be effectively utilised to aid the UK government in meeting climate change targets and to mitigate the environmental impact of a home in use towards reducing carbon emissions.Design/methodology/approachBoth primary and secondary data were sought to gain insight into the research problem. An epistemological approach to this research is to use interpretivism to analyse data gathered via a semi-structured survey. Two groups of participants were approached: (1) professionals who are deemed knowledgeable about smart home development and implementation and (2) users of smart home technology. A variety of open-ended questions were formulated, allowing participants to elaborate by exploring issues and providing detailed qualitative responses based on their experience in this area which were interpreted quantitatively for clearer analysis.FindingsWith fossil fuel reserves depleting, there is an urgency for renewable, low carbon energy sources to reduce the 5 tonnes annual carbon emissions from a UK household. This requires a multi-faceted and a multimethod approach, relying on the involvement of both the general public and the government in order to be effective. By advancing energy grids to make them more efficient and reliable, concomitant necessitates a drastic change in the way of life and philosophy of homeowners when contemplating a reduction of carbon emissions. If both parties are able to do so, the UK is more likely to reach its 2050 net-zero carbon goal. The presence of a smart meter within the household is equally pivotal. It has a positive effect of reducing the amount of carbon emissions and hence more need to be installed.Research limitations/implicationsFurther research is needed using a larger study sample to achieve more accurate and acceptable generalisations about any future course of action. Further investigation on the specifics of smart technology within the UK household is also needed to reduce the energy consumption in order to meet net-zero carbon 2050 targets due to failures of legislation.Practical implicationsFor smart homes manufacturers and suppliers, more emphasis should be placed to enhance compatibility and interoperability of appliances and devices using different platform and creating more user's friendly manuals supported by step-by-step visual to support homeowners in the light of the wealth of knowledge base generated over the past few years. For homeowners, more emphasis should be placed on creating online knowledge management platform easily accessible which provide virtual support and technical advice to home owners to deal with any operational and technical issues or IT glitches. Developing technical design online platform for built environment professionals on incorporating smart sensors and environmentally beneficial technology during early design and construction stages towards achieving low to zero carbon homes.Originality/valueThis paper bridges a significant gap in the body of knowledge in term of its scope, theoretical validity and practical applicability, highlighting the impact of using smart home technology on the environment. It provides an insight into how the UK government could utilise smart home technology in order to reduce its carbon emission by identifying the potential link between using smart home technology and environmental sustainability in tackling and mitigating climate change. The findings can be applied to other building types and has the potential to employ aspects of smart home technology in order to manage energy and water usage including but not limited to healthcare, commercial and industrial buildings.

Evaluating the Impact of Energy Efficiency Building Codes for Residential Buildings in the GCC

In arid climates, almost half of the urban peak load of energy demand is used to supply cooling and air-conditioning in the summertime. The pressure placed on energy resources to satisfy inhabitants’ indoor comfort requirements is mounting due to accelerated urbanisation rates in developing countries and has led countries such as those in the GCC (Gulf Cooperation Council) to establish sustainable building codes to enhance their environmental performance. Using the extensive parametric energy simulations provided by DesignBuilder, this study addresses the potential of applying different GCC energy efficiency measures to reduce annual energy consumption and carbon emissions in a typical residential dwelling in the Kingdom of Bahrain. To do so, first, a base case validation simulation model was generated, followed by four design scenarios addressing the minimum requirements for Bahrain’s Energy Conservation Code, Abu Dhabi’s ESTIDAMA 1, Saudi Arabia’s code, and Kuwait’s building code. Then, a feasibility study was conducted using the simple payback period (SPP) and lifecycle cost (LCC) analysis. Overall energy and carbon emission (CO2) reduction showed the potential for building sustainable codes to improve building environmental performance throughout the year. In terms of energy performance and CO2 reduction, Abu Dhabi’s ESTIDAMA 1 code recorded the best energy savings at a 24.4% and a 26.3% reduction in carbon emissions, followed by the Saudi code with a 14.6% annual energy savings and 12.3% less carbon emissions. Regarding the economic analysis, although the SPP indicates the Bahraini code offered payback in just under two years for subsidised energy and half a year for unsubsidised, the LCC analysis suggests that applying Abu Dhabi’s ESTIDAMA 1 code was the most feasible, followed by the Saudi building code. Consequently, the study suggests a comprehensive evaluation of the relationship between the sustainable building codes and their economic feasibility in order to enhance and promote the wide application in the GCC based on the code’s capabilities and their benefits for residential households and the overall economy.

Influencing Factors of Carbon Emissions in the Construction Industry Based on Logarithmic Mean Divisia Index: A Case Study of China

Carbon emission is further intensified as urbanization and industrialization continue to accelerate. China has maintained its rapid economic development and urbanization in the last 2 decades. The development of the construction industry has not only consumed a large number of energy sources but also resulted in significant carbon emissions, causing some environmental damage. Recognizing the major influencing factors of carbon emissions in the construction industry has become a research hotspot to alleviate environmental pollution caused by the construction industry and meet industrial demands for energy saving and emission reduction. In this study, the factors that influence annual carbon emissions of different building types in China from 2011 to 2018 were decomposed by Logarithmic Mean Divisia Index (LMDI) through a case study in Henan Province. The major influencing factors of carbon emissions have been identified. Results demonstrate that the per capita carbon emission in the construction industry in Henan Province remains high from 2011 to 2018, but it decreases year by year. Carbon emissions from the construction industry in Henan Province increase due to economic development and energy structure. Energy efficiency can inhibit carbon emissions from the construction industry in Henan Province. The obtained conclusions have a positive effect on analyzing annual variations in carbon emissions from the construction industry in a region, identifying influencing factors, and proposing specific countermeasures of energy saving and emission reduction.

Improved ELMv1-ECA simulations of zero-curtain periods and cold-season CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt; and CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emissions at Alaskan Arctic tundra sites

Abstract. Field measurements have shown that cold-season methane (CH4) and carbon dioxide (CO2) emissions contribute a substantial portion to the annual net carbon emissions in permafrost regions. However, most earth system land models do not accurately reproduce cold-season CH4 and CO2 emissions, especially over the shoulder (i.e., thawing and freezing) seasons. Here we use the Energy Exascale Earth System Model (E3SM) land model version 1 (ELMv1-ECA) to tackle this challenge and fill the knowledge gap of how cold-season CH4 and CO2 emissions contribute to the annual totals at Alaska Arctic tundra sites. Specifically, we improved the ELMv1-ECA soil water phase-change scheme, environmental controls on microbial activity, and the methane module. Results demonstrate that both soil temperature and the duration of zero-curtain periods (i.e., the fall period when soil temperatures linger around 0 ∘C) simulated by the updated ELMv1-ECA were greatly improved; e.g., the mean absolute error (MAE) in zero-curtain durations at 12 cm depth was reduced by 62 % on average. Furthermore, the MAEs of simulated cold-season carbon emissions at three tundra sites were improved by 72 % and 70 % on average for CH4 and CO2, respectively. Overall, CH4 emitted during the early cold season (September and October), which often includes most of the zero-curtain period in Arctic tundra, accounted for more than 50 % of the total emissions throughout the entire cold season (September to May) in the model, compared with around 49.4 % (43 %–58 %) in observations. From 1950 to 2017, both CO2 emissions during the zero-curtain period and during the entire cold season showed increasing trends, for example, of 0.17 and 0.36 gC m−2 yr−1 at Atqasuk. This study highlights the importance of zero-curtain periods in facilitating cold-season CH4 and CO2 emissions from tundra ecosystems.

Economic and climate benefits of vehicle-to-grid for low-carbon transitions of power systems: A case study of China's 2030 renewable energy target

More and more attention has been given to the role of electric vehicles in reducing the economic cost and carbon emissions of the power system through the vehicle-to-grid (V2G) mode, as well as helping to integrate renewable energy power. The promotion of V2G mode needs to consider the effectiveness of policy costs, so it is urgent to estimate the potential benefits of V2G. In this paper, a multi-regional power dispatch and expansion model is constructed from the perspective of power system by taking China's plan to reach 1.2 billion kW of installed wind and photovoltaic power generation capacity in 2030 as an example, combining with the development planning of electric vehicles and power systems. The results show that by 2030, the implementation of unidirectional V2G and bidirectional V2G in China can reduce the total cost of power system by 2.02% and 2.08%, reduce the annual carbon emissions of the power system by 2.27% and 2.95%, and increase the total proportion of wind and photovoltaic power generation by 1.33% and 1.28% in the power mix. An increasing proportion of electric vehicles participate in V2G increases the proportion of new-installed wind generation and decreases that of photovoltaic power. Due to the high cost of battery degradation and the current power mix dominated by coal-fired generation, additional benefits of implementing bidirectional V2G over unidirectional V2G are limited.

Environmental friendly micro cold storage for last-mile Covid-19 vaccine logistics.

Globally, vaccination plays a vital role in controlling the Covid-19 pandemic. However, the cold supply chain is essential for vaccine storage and logistics services. In a country like India, the last-mile logistics of vaccines is a challenging task. The cold chain is indispensable for the Covid-19 vaccine drive to the rural areas. The demand for cold storage increases rapidly due to the rapid Covid-19 vaccine drive. The conventional cold storage facility has a more significant threat to the grid power quality and environmental impacts. The energy demand and greenhouse gas emission of traditional cold storage lead to global warming. The micro cold storage facility has to be developed rapidly to accelerate the vaccine drive to the last mile of the county with reliable and affordable energy sources. In addition, climate change mitigation is ensured by the renewable energy utilization in the Covid-19 vaccine drive. The proposed novel micro cold storage aims to be silent, clean, mobile, without moving parts, and reliable for the last-mile vaccine logistics as a vaccine carrier to the remote rural areas. This paper deals with the novel design, development, and experimental investigation of solar photovoltaic powered thermoelectric-based micro cold storage as a Covid-19 vaccine carrier for rural areas. The design consideration of Covid-19 vaccine storage has been reported. The experimental results ensure the World Health Organization recommended vaccine storage (i.e., vaccine carrier) temperature range of +2 to +8 °C. Therefore, green energy and refrigeration system provide environmental sustainability by mitigating 700kg of annual carbon emission.

Multi-Strategy Ensemble Non-Dominated Sorting Genetic Algorithm and Application in Energy-Enviro-Economic Multi-Objective Optimization of Isopropyl Alcohol/Isopropyl Ether Separation Process

The separation of isopropyl alcohol (IPA)/isopropyl ether (IPE) is crucial for the recovery of valuable solvents from alcohol ether waste liquids, but involves high energy consumption and emissions. Therefore, the multi-objective optimization of energy, economy and environment in the IPA/IPE separation process is conducive to the sustainable development of the organic solvent industry. Considering the slow convergence and the tendency to fall into local optimum for the most commonly used multi-objective optimization method, namely non-dominant sorting genetic algorithm-II (NSGA-II), a novel multi-strategy ensemble non-dominated sorting genetic algorithm (MENSGA-II) is proposed. In this algorithm, two evolution strategies based on individual neighborhood guidance and random walk are developed, aiming at accelerating convergence speed and enhancing search ability, and a selection strategy based on double space is proposed to improve the distribution of the Pareto front obtained. The MENSGA-II is tested on the benchmark functions and the actual separation process of IPA/IPE. The results prove that the proposed MENSGA-II algorithm has superiority in robustness, convergence speed and distribution of Pareto front. Compared with the actual operating condition, the annual exergy destruction and carbon emission can be reduced by 18.49% and 15.47% when the annual gross profit increases by 3.24% via multi-objective optimization.

A novel distributed energy system combining hybrid energy storage and a multi-objective optimization method for nearly zero-energy communities and buildings

A distributed energy system (DES), which combines hybrid energy storage into fully utilized renewable energies, is feasible in creating a nearly zero-energy community. Improving the design, optimization, and operation of DESs is conducive to improving system performance. Therefore, a novel DES is proposed to combine a new solar energy utilization technology and hybrid energy storage (i.e., heat storage, ice storage, and electricity storage). In addition, a new operational strategy is put forward. Subsequently, based on nearly zero-energy community and buildings, the DES configuration is optimized in relation to its environment, economy, and net interaction. Its performance and operating characteristics are compared and analysed. Then, a new indicator is proposed to evaluate the potential of the DES to achieve zero-energy. Finally, a sensitivity analysis on the carbon tax, electricity price, and equipment price is carried out. The results show that the annual carbon emissions and net interaction of the novel DES are reduced by 51.7%–73.2% and 33.5%–63.6%, respectively, compared to the reference system. Herein, the nearly zero-energy office buildings have a better zero-energy potential at 91.1%. The novel DES and corresponding multi-objective optimization method can reference a nearly zero-energy community energy supply design.

What is the impact of COVID-19 pandemic on global carbon emissions?

The coronavirus 2019 (COVID 19, or SARS-CoV-2) pandemic that started in December 2019 has caused an unprecedented impact in most countries globally and continues to threaten human lives worldwide. The COVID-19 and strict lockdown measures have had adverse effects on human health and national economies. These lockdown measures have played a critical role in improving air quality, water quality, and the ozone layer and reducing greenhouse gas emissions. Using Soil Moisture Active Passive (SMAP) Level 4 carbon (SMAP LC4) satellite products, this study investigated the impacts of COVID-19 lockdown measures on annual carbon emissions globally, focusing on 47 greatly affected countries and their 105 cities by December 2020. It is shown that while the lockdown measures significantly reduced carbon emissions globally, several countries and cities observed this reduction as temporary because strict lockdown measures were not imposed for extended periods in 2020. Overall, the total carbon emissions of select 184 countries reduced by 438 Mt in 2020 than in 2019. Since the global economic activities are slowly expected to return to the non-COVID-19 state, the reduction in carbon emissions during the pandemic will not be sustainable in the long run. For sustainability, concerned authorities have to put significant efforts to change transportation, climate, and environmental policies globally that fuel carbon emissions. Overall, the presented results provide directions to the stakeholders and policymakers to develop and implement measures to control carbon emissions for a sustainable environment.

Research on Carbon Emissions of Electric Vehicles by Constructing Mathematical Model Based on Big Data

After the “3060” carbon peak and neutrality strategic goal was put forward, various industries actively responded to find new ways for energy conservation and emission reduction. In the field of automobile manufacturing, the transition from traditional fuel vehicles to electric vehicles is an inevitable trend. This paper builds a mathematical model that uses the three major indicators of carbon emissions per 100 kilometers, energy-saving emission reduction coefficients, and annual carbon emissions as parameters to measure carbon emissions benefits, and combines survey data to conduct empirical analysis to explore the advantages of electric vehicles in energy saving and emission reduction compared with traditional fuel vehicles under different power supply structures. At the same time, based on the existing data and conclusions, the research is extended to the analysis of carbon emissions prospects in decades, and the possible contribution of future electric vehicles in energy utilization and environmental protection is predicted, to explore its role in promoting the achievement of the double-carbon goal, and put forward corresponding recommendations based on the research results.