Life Cycle Carbon Emissions Research Articles

Research on the optimal use of industrial wastewater for sustainable regeneration based on big data background

Industry, as one of the most important areas of water use in China, will use 102.89 billion cubic metres of water in 2020, accounting for 17.7 per cent of the country's total water use, and industrial wastewater discharges will account for about one fifth of the country's sewage discharges. In recent years, positive progress has been made in the recycling of industrial wastewater in China, with the water reuse rate for industries above designated size increasing from 89 per cent in 2015 to 92.5 per cent in 2020, and the water consumption of 10,000 yuan of industrial added value in 2020 decreasing by 39.6 per cent compared with 2015. The current status of research on life cycle carbon emissions of different wastewater recycling technologies and processes was analysed and summarised, taking wastewater recycling products such as reclaimed water, energy, microbial proteins and guano as research targets. The analysis pointed out that wastewater reclamation and value-added utilisation have considerable carbon reduction benefits, but quantitative assessment should be carried out at the system level in conjunction with the utilisation scenarios. This paper researches and analyses industrial wastewater based on the technical foundation of big data. On the basis of analysing the industrial wastewater treatment in China in recent years and at the same time combining the background of big data and treatment technology, it pushes the development of industrial wastewater treatment into a new field and mileage.

Life cycle carbon emissions of China's passenger vehicle sector: a fleet-based study

The passenger vehicle sector has been identified as a major contributor to carbon emissions in China. Accurately estimating carbon emissions is crucial, particularly in light of China's ambitious goal to reach its carbon emissions peak by 2030. Previous life cycle assessment (LCA) studies on single-passenger vehicles rarely consider technological advancements to accurately predict future carbon emissions in the entire fleet. As such, a fleet-based life cycle approach that integrates input-output-based hybrid LCA (IOH-LCA) and system dynamics is proposed to simulate the evolution of carbon emissions in the passenger vehicle sector from 2016 to 2035. This method captures the complex changes in the sets of vehicles produced for sale, in use, and disposed of over time, as well as the multiple time-dependent technological advancements. A scenario analysis is constructed to analyze carbon emissions in alignment with the commitment to achieving the carbon emissions peak by 2030. The results indicate that, in a positive scenario with the combined advancement of multiple technologies, the passenger vehicle sector will be able to peak carbon emissions before 2030. This study could provide support for policymaking regarding carbon reduction in China's electrification of passenger vehicles.

Performance and application boundary analysis of a solar PV/T heat pump system

In this study, the applicable boundary of a solar PV/T heat pump system is determined based on system modelling and analysis, and the entire life cycle carbon emission reductions of the system are calculated.

Life-cycle analysis of lithium chemical production in the United States

The life-cycle carbon emissions of Li-chemical production from alternative clays and low Li-content brines in the United States lie between the impacts of its production from two conventional sources: Salar brines and from spodumene ores.

Research on the Application of Blockchain Technology in the Carbon Trading Market of Substations

Abstract This study examines the entire lifecycle carbon emissions from the construction of substations, emphasizing the demand response from the carbon emission trading market. We use blockchain technology to establish an intelligent contract framework to manage and control substation configurations within digital substations’ physical environments. Based on Blockchain, a regional substation intelligent control model is developed to facilitate optimal decision-making in the carbon trading market. Simulation analyses reveal that adjustments in capacity to 150MW can enhance the peak range from 041.2% to 042.0%, indicating a 0.8% improvement in efficiency. Additionally, this research assesses the carbon emission savings, correlating the volume of carbon transactions to the verification time, particularly noting a significant increase in time cost within the first 200 transactions. This paper contributes to understanding how digital technologies can optimize carbon emissions management and energy savings in substation construction.

Waste-to-energy incineration site selection framework based on heterogeneous fuzzy regret-PROMETHEE model considering life-cycle carbon emissions.

Waste incineration technology has received extensive attention for its advantages of being harmless, reducing, and recycling. However, the waste-to-energy incineration project confronts significant "not-in-my-backyard (NIMBY) concerns," and irrational location choices will have negative effects on the project's economy and sustainability; it is also a great challenge to the credibility of the government. To this end, a multi-criteria decision-making framework is constructed for the site selection of waste-to-energy incineration projects. To begin with, a site selection criteria system is established including 16 sub-criteria from four aspects, where probabilistic linguistic term sets are introduced to depict the qualitative sub-criteria and probabilistic hesitant fuzzy sets are employed to express the uncertainty of quantitative sub-criteria. An optimization model is then built to determine the weights of criteria based on the Pearson correlation coefficient and least square method. Furthermore, a regret-preference ranking organization methods for enrichment evaluations (PROMETHEE) model is presented to rank alternatives in a heterogeneous decision environment. Finally, a case study in China is conducted to validate the applicability of the proposed framework; the result of the site selection demonstrates that alternative A2 located in Miyun, Beijing, is the most optimal option. This work provides investors with scientific decision reference and also extends the methods in the decision-making field.

Calculation and utility analysis of lychee life-cycle carbon emissions considering food loss and waste

Food loss and waste become the sever problem in the modern society. This paper studies the carbon emissions related to different circulation forms of lychee，which is a typical perishable fruit in China. First, we construct a kinetic model of lychee by using the Arrhenius equation. And then, we propose a carbon emission measurement with the unit effective carbon emission and the comprehensive carbon emission utility by using life cycle assessment. With this measurement, we measure the rate of loss and life cycle carbon emissions of four lychee's circulation scenarios, including: cold chain, room temperature, cold chain broken at the beginning and cold chain broken at the end.The results show that with the traditional carbon emission measurement, the carbon emissions generated by the cold chain circulation scenario are the highest in total carbon emissions under the four scenarios. But using the unit effective carbon emissions measurement, the total carbon emissions under the cold chain circulation situation is 34.84 % less than those of the room temperature circulation. Under the cold chain circulation scenario, the unit effective carbon emission and comprehensive carbon emission utility are 0.38 kgCO2/kg and 85.33 %, respectively. Improving the rate of cold chain circulation can improve the comprehensive carbon emission utility and achieve land-saving. Comparing with the cold chain circulation rate in China in today, when it increases to 95 %, the comprehensive carbon emission utility of lychee supply chain increases to 81.65 %, and the required land is reduced by 54.84 %.

Comfort, carbon emissions, and cost of building envelope and photovoltaic arrangement optimization through a two-stage model

The design of a high-performance building necessitates tradeoffs among multiple performance objectives, and many simulation-based optimization tools have been developed for this purpose. In practice, these tools are often constrained by excessive computational load and tight project deadlines. This study aimed to develop a holistic approach to rapidly identify optimal building design schemes. A novel two-stage model was developed as a surrogate to conventional physics-based models, which were then linked to multi-objective optimization algorithms, namely, NSGA-II, NSGA-III, and C-TAEA, in search of the Pareto optimal and best design schemes. The performance of the two-stage model was further enhanced by applying the least absolute shrinkage and selection operator (LASSO) and Neural Architecture Search methods and learning from the statistical layer. The above approach was tested in the design of an apartment building for seniors in Northern China such as thermal comfort, carbon, and cost. The optimal design achieved through the compromise optimum can significantly reduce thermal discomfort, life-cycle carbon emissions, and high levels of daylighting conditions. The design scheme was visualized using a geometrical remodel module. This study contributes methodologically to complex multi-objective building optimization problems with practical implications for design.

Life Cycle Carbon Emissions and an Uncertainty Analysis of Recycled Asphalt Mixtures

The efficient recycling of road materials is an effective way to reduce carbon emissions. Approximately 400 million tons of waste asphalt pavement materials is generated annually in China, but the utilization rate is less than 50%. In this paper, a whole life cycle CO2 emission calculation model for recycled asphalt mixtures is established, and an uncertainty analysis is carried out on the basis of this model. The steps in the recycled asphalt mixture stage with the greatest impact on emissions are identified. The life cycle of asphalt mixtures is divided into raw material production, mixture preparation, material transportation and construction phases based on the carbon emission trends in the four phases. First, recycled asphalt mixtures are considered, and the carbon emissions along a two-way four-lane highway are analyzed based on the relevant carbon emission factor and other known data. The carbon dioxide emissions of each stage are also compared to identify the key links among stages. Then, the carbon emissions of hot-recycled asphalt mixtures are compared with those of ordinary asphalt mixtures and cold-recycled asphalt mixtures in each stage. Finally, an analytical uncertainty study of recycled asphalt mixtures is conducted using uncertainty modeling in different scenarios. Based on the quantitative results of the carbon emission calculations through life cycle assessment (LCA), future measures for reducing carbon emissions from recycled asphalt mixtures are proposed.

Energetic performance and life cycle carbon emission of CO2 automotive air conditioning system with an evaporative gas cooler and a dual-evaporator configuration in China

Enhanced actions on climate change have led CO2 air conditioner to take center stage in automotive field. However, its inefficient performance in hot climates limits its further application. A dual-evaporator (D-E) configuration, an evaporative gas cooler (EGC), and their combination (D-E + EGC) were first integrated with the system and experimentally studied in this paper in an attempt to alleviate this problem. Annual energy consumption and life cycle climate performance (LCCP) under four modes (baseline, D-E, EGC, and D-E + EGC) in China were estimated. Results show D-E increases evaporation pressure and EGC is able to decrease discharge pressure. D-E + EGC combines the advantages of both. Thus, improvement percentage in coefficient of performance (COP) brought by D-E + EGC is the highest, followed by those of EGC and D-E. This percentage is more significant at higher ambient temperatures, and even reaches 67.4 % at 45°C outdoor condition. In any mode, annual energy consumption and LCCP in southeast China are double or triple of those in other regions, which shows this system is of high energy consumption and high emission in southeast China. Compared with baseline mode, annual energy consumption and LCCP can be reduced by 3 ∼ 7 % for D-E, 14 ∼ 16 % for EGC, and 18 ∼ 22 % for D-E + EGC. Specifically, D-E + EGC could save up to 890 kWh of electricity and reduce carbon emission by up to 440kgCO2 per vehicle, indicating this technique is a promising way to reduce energy consumption and carbon emission for vehicles equipped with CO2 air conditioners.

Life cycle comprehensive performance assessment of the TiAlN coated tool based on surface treatment

The optimal surface treatment process can availably improve tool surface properties, and meet the requirements of low-carbon manufacturing. In this work, based on tool surface modification technology and tool life cycle carbon emission system, TiAlN coated tools are carried out micro-blasting treatment (MBT), cryogenic treatment (CT) and heat treatment (HT). The effects of surface treatment processes on the surface integrity (morphology, roughness, micro-hardness, residual stress) of the coated tool are studied. The high-speed dry finishing turning experiments of cobalt-based superalloy are carried out to investigate the tool wear morphology and wear mechanism. The carbon emissions of the tool life cycle are analyzed. Finally, the comprehensive performance of the coated tool within life cycle is evaluated. The results show that the highest level of surface integrity of coated tool is achieved by MBT, while the lowest carbon emission of environmental is impacted by HT. Compared with the untreated (UT) tool, the micro-blasted tool has the most significant improvement in surface roughness with a 28.6% reduction. The cryogenic treated tool has the greatest improvement on the surface hardness which is increased by 44.4%. The effect of HT on the surface residual stress is the most obvious. The surface stress of the heat-treated tool has increased by 59.4%. Moreover, the flank wear VB of the micro-blasted tool, cryogenic treated tool and heat-treated tool is reduced by 25.17%, 24.50% and 32.12%, respectively. The main wear mechanisms of the treated tool are adhesive wear, oxidation wear and abrasive wear. According to comprehensive performance assessment, the performance of surface treatment process during the coated tool life cycle is: HT > MBT > CT > UT.

Improving building resilience in the face of future climate uncertainty: A comprehensive framework for enhancing building life cycle performance

This research introduces an innovative resilient design framework, addressing gaps in building performance optimization by considering a holistic life cycle perspective and factoring in climate projection uncertainties from the 2020s to 2090s. The study concludes that in the case study, future climate scenarios in different Shared Socio-Economic Paths significantly impact building life cycle performance, with wall U-value, windows U-value, and wall density identified as major factors affecting building performance under future climate uncertainty. The ensemble learning model achieves high fidelity in predicting life cycle carbon emissions (LCCE), life cycle cost (LCC), and indoor discomfort hours (IDH) through input feature screening and hyperparameter optimization. Comparing optimization algorithms, Two-Archive Evolutionary Algorithm for Constrained multi-objective optimization (C-TAEA) demonstrates better convergence degree and optimization effect. Among the tested multi-criteria decision making methods, the VIKOR method selects the best building resilient design scheme from the Pareto data set, effectively reducing LCCE, LCC, and IDH, and leading to an overall improvement in building life cycle performance. Applying this framework, the finalized scheme for an office building in cold region optimizes 44.0% of LCCE, 8.2% of LCC, and 4.3% of IDH. This framework develops a new approach to improve building life cycle performance under future climate uncertainty and supports informed decision-making for resilient building design. To promote carbon neutrality in construction, it is urged that future studies incorporate additional sources of uncertainty, such as occupant behavior, into the proposed framework.

Carbon emissions from various natural gas end-use sectors for 31 Chinese provinces between 2017 and 2021

Natural gas (NG) is a low-carbon fuel that is becoming a crucial transitional energy in China for reducing carbon emissions. In this study, a life-cycle assessment was performed to correlate carbon emissions and NG consumption for different end uses in China. A bottom-up life-cycle assessment framework was combined with carbon emission coefficients to quantify NG consumption in 31 Chinese provinces between 2017 and 2021, as well as the carbon emissions (in carbon dioxide (CO2) equivalents, including CO2 and methane) released during NG production, transportation, and consumption. The carbon emission factors for different types of end-use consumption were considered. The assessment results indicate that both NG consumption and life-cycle carbon emissions from NG use have increased since 2017. Between 2017 and 2021, NG consumption in China increased from 260 to 370 billion cubic meters and life-cycle carbon emissions from NG increased by 39% (from 930 to 1292 Mt CO2). The carbon emissions released during NG production and transportation accounted for approximately 31% of NG life-cycle emissions. Considerable variations in NG life-cycle carbon emissions were identified across different provinces and sectors, highlighting the need for targeted efforts to reduce carbon emissions. The objective of this study was to provide useful insights into sustainability development of the NG industry in China for optimizing NG allocations to different end uses and maximizing the environmental and economic benefits of NG.

Mitigating carbon emissions of single-family houses: Assessing the need for a limit value

Reducing carbon emissions in the global building and construction sector is a crucial part of achieving climate targets. Laws that aim to limit the carbon emissions of new buildings have yet to be implemented on a larger scale, although some nations already have thresholds. These thresholds may not be sufficient to mitigate carbon emissions, and not all types of buildings are obliged to comply with them. In the case of Denmark, single-family houses (SFH) are not required to not comply with a limit, although they represented approximately 17% of all newly built areas from 2010 to 2022, indicating significant resource use and associated carbon emissions. This study aims to establish sufficient background data to support the need for implementing a limit value for SFHs in building regulations to ensure necessary reductions in carbon emissions. The study finds that the life cycle carbon emissions of Danish SFHs vary between 5.6 and 13.2 kg CO2e/m2/year, showing that compliance with the current limit value of larger buildings is possible and that a reduction of more than 50% in carbon emissions is possible. However, currently, there is no intentional investigation or achievement of potential carbon emissions in the construction industry. The study’s findings inform policymakers that a limit value for SFHs must be introduced no later than 2025 to initiate the necessary reduction of carbon emissions.

Stepwise renovation of buildings: what to refurbish first to minimize life-cycle carbon emissions?

To tackle the upcoming renovation wave, this work evaluates renovation strategies with a life cycle GHG emissions perspective and includes time and sequencing in the decision-making process. A case study is used to conduct a full life cycle assessment of renovation strategies in line with the Swiss normative context. Improvements in the operational energy consumption are evaluated with an energy model using the software Lesosai and considering the normative limits from the SIA 380/1. GHG emissions are calculated using the Swiss KBOB data inventory and in line with the SIA 2032 methodology. The renovation measures are then examined individually with the carbon payback time indicator and strategies with cumulative emissions over time in contrast to carbon budgets. Results show that the sequence of the refurbishment steps can increase or decrease cumulative GHG emissions of ca. 30% over the lifetime of the building. Changing a fossil-fuel based heating system is the most impactful measure and must happen as soon as possible. Switching to decarbonized heating systems reduces the carbon effectiveness of subsequent renovation measures but poses the question of energy availability. Fully renovating a building but delaying the change of heating system by only 7 years can compromise the achievement of the carbon targets.

Medium and long-term hydrogen production technology routes and hydrogen energy supply scenarios in Guangdong Province

Hydrogen is a type of clean secondary energy, and the hydrogen energy supply is vital to regional energy development. Guangdong is at the forefront of hydrogen energy deployment in China, and aims to achieve peak carbon by 2030. However, hydrogen production research is challenging due to complex technical routes, technical maturity levels, life-cycle carbon emissions, and costs. Multi-time-scale research is necessary to explore optimal production paths and their contributions to CO2 emission reduction. This study discussed key technologies and the technical maturity of five hydrogen production routes: production from industrial byproducts and coal, wind, hydro-, and photovoltaic power. Policy scenarios were designed to investigate the potential of these routes and technology deployment intensity under medium- and long-term scenarios. This paper proposes a roadmap for hydrogen development and provides a reference for hydrogen production planning in Guangdong. This methodology can be applied in other regions for hydrogen energy development research.

Decoupling economic growth from building embodied carbon emissions in China: A nighttime light data-based innovation approach

The contribution of the construction sector is indispensable for the realization of China's carbon peaking and carbon neutrality goals. However, existing studies have focused on the decoupling relationship between GDP and building life cycle carbon emissions, neglecting the utilization of Night Time Light data (NTL). The research question of this research is how to describe the decoupling relationship between Economic Growth (EG) and Building Embodied Carbon emissions (BECs) by introducing NTL. To tackle this question, the carbon emission coefficient approach is used to calculate BECs first. Then, both GDP and NTL are selected to reflect EG. The Tapio model is utilized to examine the regional and temporal evolution of China's inter-provincial decoupling performance. The main findings are as follows: 1) the number of provinces that achieved decoupling status in China is increasing, and progress has been made in BECs reduction. 2) There are significant regional differences in the decoupling of China's BECs. Particularly, most of the provinces in the south of the Hu Huanyong line show a negative decoupling for the year 2020 due to the impact of COVID-19. 3) The long-term decoupling results of GDP and NTL are consistent, while the short-term decoupling results obtained via NTL are more accurate. The study can enrich the application of NTL in the field of BECs, and provide a basis for the Government to set effective carbon reduction targets and pathways.

Building information modelling-enabled multi-objective optimization for energy consumption parametric analysis in green buildings design using hybrid machine learning algorithms

Green buildings (GB) have been widely promoted in various nations. However, the post occupancy evaluation suggests many GB cannot well fulfill the expected targets. To overcome the mismatch among GB’s multi-objectives, this paper develops an efficient and intelligent hybrid method using BIM-DesignBuilder (BIM-DB), Grey wolf optimization (GWO), random forest (RF) and non-dominated sorting genetic algorithm II (NSGA-II) to achieve the optimization of design parameters. The BIM model and DB simulation tool were used to obtain data samples of envelope and air conditioning system design parameters, and their life cycle carbon emission (LCCE), economic cost (EC) and predicted mean vote (PMV). The RF model was used to achieve high precision prediction. The GWO was used in the hyper-parameter optimization. The NSGA-II algorithm was applied to multi-objective optimization to obtain optimal design parameters. A building case shows: (1) The RF model had an excellent prediction performance for LCCE, EC and PMV. (2) BIM-DB can be used to obtain low error and high reliability building simulation data sets. (3) The RF-NSGA-II intelligent algorithm can reduce the LCCE of the building in the entire cycle by 16.6%, reduce the EC per square meter by 2.0%, and greatly improve the thermal comfort by 18.3%, representing good application value. This research provides a way of thinking for the multiobjective optimization of green buildings from the perspective of data mining and guidance for the parameter selection of the envelopes and air conditioning systems of new and existing buildings to more scientifically and effectively design green buildings.

Analysis of the Impact of Photovoltaic Curtain Walls Replacing Glass Curtain Walls on the Whole Life Cycle Carbon Emission of Public Buildings Based on BIM Modeling Study

The construction industry plays a crucial role in achieving global carbon neutrality. The purpose of this study is to explore the application of photovoltaic curtain walls in building models and analyze their impact on carbon emissions in order to find the best adaptation method that combines economy and carbon reduction. Through a carbon emissions calculation and economic analysis of replacing photovoltaic curtain walls on a large public building in Zhenjiang, China, the results showed that after replacing glass curtain walls with photovoltaic curtain walls, the carbon emissions during the construction operation stage decreased by 30.74%, but the carbon emissions during the production and transportation stage of building materials increased by 10.48%. The carbon emissions throughout the entire life cycle of the building have been reduced by 20.99%. This indicates that photovoltaic curtain wall technology has the potential to reduce building carbon emissions. Further promoting the development of production technology and sales routes for photovoltaic curtain walls and accelerating the improvement of carbon trading systems can further improve the carbon emission reduction effect of buildings. This study provides practical reference for public buildings in similar areas and guidance for reducing carbon emissions in the future.

A probabilistic life-cycle assessment of carbon emission from magnesium phosphate cementitious material with uncertainty analysis

This study aims to quantify the carbon emission intensity of magnesium phosphate cementitious materials to explore its potential in carbon emission reduction. However, comprehensive research on the lifecycle carbon emissions of these materials remains scarce, plagued by issues of data uncertainty, accessibility, and scoping discrepancies. Therefore, a probabilistic lifecycle assessment approach was adopted in this study, enabling uncertainty analysis of the carbon emission intensity of magnesium phosphate cementitious materials. The findings indicate that the 10.5th percentile of the carbon emission intensity simulations for MPC stands at 0.624 kgCO2e/kg, suggesting that nearly 90% of the values surpass those of OPC, thereby refuting the presumption of its low-carbon attributes. Notably, the consumption and carbon emission factors of magnesium oxide and soluble phosphates emerge as pivotal influences on its carbon emissions. Additionally, a multiple linear regression model was employed to forecast the correlation between the constituents of magnesium phosphate cementitious materials and the volume of carbon emissions. Through this study, we can have a more comprehensive understanding of the environmental performance of magnesium phosphate cementitious materials in terms of carbon emission reduction, which will provide an important support for the selection and design of future green building materials.