Highest Emission Intensity Research Articles

Novel Eu3+ doped mixed alkaline-earth zinc silico-aluminate glass for white-light-emitting diode, fingerprint, and security ink application

In this work, novel calcium strontium magnesium zinc silico-aluminate (CSrMZSAEux) glasses doped with varied concentrations of Eu2O3 (0.5, 1.0, 1.5, 2, 3, 4 and 5 mol%) were synthesized by an open-air melt quenching technique. The Raman and FTIR studies revealed that Eu3+ ions connected to both AlO4 and SiO4 units through non-bridging oxygen. The decrease in thermal stability from 158 to 141 °C with the gradual inclusion of Eu2O3 ions is showing modifier role of Eu3+ ions. The intense emission spectra (5D0→7Fi = 0-4 transitions) measured under 395 nm excitation wavelength, showed no concentration quenching within the studied dopant ions concentration. The high Judd-Ofelt parameter (Ω2 = 5.06 to 6.31 × 10−20 cm2) and red-to-orange emission intensity ratio (R = 3.627–4.102) have revealed the covalent nature of Eu-ligand bond and high color richness, respectively. Among all prepared glasses, the CSrMZSAEu5.0 glass showed high color purity (98.9%), correlated color temperature (<1000K), highest emission intensity and reasonable lifetime value (1387±16 μs). Further, the temperature-dependent photoluminescence demonstrated that the CSrMZSAEu5.0 glass has good emission thermal stability (⁓ 66% at 150 °C) with a high activation energy of 0.258 eV. Hence, the CSrMZSAEu5.0 glass can be used as red component for white-light-emitting diode, and red-light applications. Furthermore, the CSrMZSAEu5.0 glass composition is observed to be suitable for latent fingerprint and security ink applications.

A Taguchi-STIRPAT input-output model for unveiling the pathways of reducing household carbon emissions under dual-carbon target-A case study of Fujian province.

This study develops a novel Taguchi-STIRPAT input-output (TSIO) model for exploring pathways to reduce carbon emission from the perspective of household consumption, through incorporating input-output model (IOM), Taguchi design (TD), and STIRPAT model. TSIO can not only identify the main factors (carbon emission intensity, consumption structure, per capita consumption, and population) and evaluate their effects on indirect household carbon emissions (IHC), but also predict IHC from a long-term perspective to achieve the dual-carbon target. TSIO is then applied to Fujian province (China), where multiple scenarios related to multiple factors with multiple levels are examined. Results reveal that (i) among all sectors, the highest contributors to IHC are residence (RES), followed by food, cigarettes, and drinks (FCD), and transport and communication (TC); it is suggested that the government can consider market mechanism to control these high-carbon emission consumption behaviors; (ii) the decline in the share of RES consumption has the largest effect on rural and urban IHC; the share of RES consumption is considered to be a key factor in predicting carbon emissions; (iii) under the optimal scenario, IHC would peak in 2025 and decrease to 10.07 × 106 ton in 2060; this scenario can effectively mitigate household carbon emissions by reducing carbon emission intensity and the share of RES consumption; at the same time, it can ensure a sustained increase in per capita consumption. The results unveil the pathways of household carbon reduction under the dual-carbon target in Fujian province and suggest the local government should adopt policies (such as taxation and financial incentives) to limit residential consumptions with high carbon emission intensity.

Considering critical building materials for embodied carbon emissions in buildings: A machine learning-based prediction model and tool

Construction activities discharge considerable carbon emissions, causing serious environmental problems and gaining increasing attention. For the large-scale construction area, high emission intensity, and significant carbon reduction potential, embodied carbon emissions of buildings worth special studying. However, previous studies are usually post-evaluation and ignore the influences of project, construction and management. This paper focuses on critical building materials and adopts machine learning methods to realize carbon prediction at design stage. The activity data, including critical building materials, water, and energy consumption, is analyzed and 30 influencing factors at the project, construction, and management levels are identified. Three algorithms (artificial neural network, support vector regression and extreme gradient boosting) are used to develop machine learning models. The proposed methodology is applied to 70 projects in the Yangtze River Delta region of China. Results show that the established models achieved high interpretability (R2 >0.7) and small average error (5.33%), well proving theirs feasibility. Furthermore, an automated tool is developed to assist practitioners to predict the critical materials consumption and embodied carbon emissions conveniently. The proposed operable model and practical tool can efficiently support effective adjustments and improvement to reduce carbon in construction.

Evaluation for the effect of low-carbon city pilot policy: evidence from industry in China.

The investigation of the implementation effect of the low-carbon city pilot (LCCP) policy in promoting industrial low-carbon development is important for economic growth and carbon reduction in China. This paper takes the industry sector as an independent investigation object, and aims to examine the effectiveness of the policy in improving industrial low-carbon development. The industrial total factor carbon emission efficiency index (ITFCEE) is constructed to measure the level of industrial low-carbon development by the global frontier directional distance function. From the perspective of the multiple participants of the policy, we analyze the mechanisms of the policy, and construct the time-varying difference-in-difference model to test how LCCP policy impacts the ITFCEE. We conclude that (1) LCCP policy improves significantly the ITFCEE. (2) Heterogeneity analysis results show that the positive influence of LCCP policy is significant in cities with high industrial carbon emission intensity, high industrial structure upgrading, and high government expenditure. (3) The result of the mechanism analysis is that LCCP policy can benefit the ITFCEE by promoting enterprise green technology innovation, public environment concern, government technology support, and administrative regulation.

Protein aggregation monitoring in cells under oxidative stress: a novel fluorescent probe based on a 7-azaindole-BODIPY derivative.

The development of new fluorescent probes as molecular sensors is a critical step for the understanding of molecular mechanisms. BODIPY-based probes offer versatility due to their high fluorescence quantum yields, photostability, and tunable absorption/emission wavelengths. Here, we report the synthesis and evaluation of a novel 7-azaindole-BODIPY derivative to probe hydrophobic proteins as well as protein misfolding and aggregation. In organic solvents, this compound shows two efficiently interconverting emissive excited states. In aqueous environments, it forms molecular aggregates with unique photophysical properties. The complex photophysics of the 7-azaindole-BODIPY derivative was explored for sensing applications. In the presence of albumin, the compound is stabilized in hydrophobic protein regions, significantly increasing its fluorescence emission intensity and lifetime. Similar effects occur in the presence of protein aggregates but not with other macromolecules like pepsin, DNA, Ficoll 40, and coconut oil. Fluorescence lifetime imaging microscopy (FLIM) and two-photon fluorescence microscopy on breast (MCF-7) and lung (A549) cancer cells incubated with this compound display longer fluorescence lifetimes and higher emission intensity under oxidative stress. Synchrotron FTIR micro spectroscopy confirmed that the photophysical changes observed were due to protein misfolding and aggregation caused by the oxidative stress. These findings demonstrate that this compound can serve as a fluorescent probe to monitor protein misfolding and aggregation triggered by oxidative stress.

Carbon and financial performance nexus of the heavily polluting companies in the context of resource management during COVID-19 period

The depletion of fossil fuels and the new EU climate policy goals to achieve a zero-emission economy after 2050 encourage highly polluting companies to increase the efficiency of energy conversion from non-renewable energy sources, develop renewable energy sources and implement resource management systems in production. Studying the relationship between environmental performance and financial performance of firms is particularly important in times of the Covid-19 pandemic, as companies' decisions to limit or continue green investments and low-emission transformation may impact access to external financing sources. The aim of this study is to identify the shape of the relationship between the carbon and financial results of heavily polluting enterprises in the context of resource management and to assess the impact of the Covid-19 pandemic on the considered relationship. For a panel sample of Polish enterprises representing highly polluting industries with manufacturing plants covered by the EU ETS in 2009–2021, a third-degree polynomial describing this relationship was estimated. A U-shaped relationship was identified between carbon emission intensity and return on sales and return on assets, which can be explained by the ‘too-little-of-a-good-thing’ effect. Increase in share of renewable energy in the production structure significantly reduces firms’ profitability, which can be explained by the relatively high costs associated with the development of renewable energy and the changing legal regulations regarding this type of investment. It has been shown that companies with high carbon emission intensity achieved lower sales profits and return on assets compared to companies with lower carbon intensity during the Covid-19 pandemic. The lower scale of allocation of free emission allowances compared to previous years, combined with the increase in emission allowance prices under the influence of shocks generated by the pandemic, had a negative impact on the profitability of heavily polluting companies. The modelling results provide important information to managers who, based on them, can make more informed decisions regarding the use of natural resources in production and the involvement of enterprises in investments aimed at the use of cleaner production technologies and the development of renewable energy.

Fluorescence mechanism and biomedical applications of graphene quantum dots

Graphene quantum dots (GQDs) are fluorescent graphene nanoparticle that have tunable emission wavelength, high emission intensity and biocompatibility. The fluorescence mechanism is still indecisive, yet explanations exist. Surface or edge defects and quantum confinement are two major explanations and they accounted for the florescence properties observed so far. GQDs quantum confinement is applied to change the emission wavelength. Surface functional groups usually improve biocompatibility and solubility. Under several cases, surface defects are also engineered to tune emission wavelength and intensity to serve specific engineering propose. GQDs have found applications in bioimaging, biosensing, and therapy. GQDs can generate high intensity emission in the NIR-II window which is ideal in in vivo bioimaging. GQDs can be generated from folic acid in a one-step procedure. The GQDs generated this way can track folate receptor and help cancer diagnostics. High intensity emission also enables GQDs to be used in photothermal or photodynamic therapy. Future applications will be promoted by a better understanding of GQDs fluorescence mechanisms.

Data mining and spatio-temporal characteristics of urban road traffic emissions: A case study in Shijiazhuang, China

Accurate estimation of traffic emissions and analysis of spatio-temporal distribution on urban roads play a crucial role in the development of low-carbon transportation system. Traditionally, a region’s emission characteristics have been studied using numerous emission models with GPS-based spatio-temporal data. Due to the heavy data processing needs of GPS-based data, emission characteristics for a large region have been studied by dividing the region into a limited number of smaller areas or units. Additionally, GPS data are based on a few vehicles in the traffic which does not fully reflect road conditions. This paper proposed an approach that can be used to study and calculate the spatio-temporal emission pattern of a region at a roadway section level by using Baidu’s online traffic data and COPERT model. The proposed method can be used to estimate road-level emission patterns while avoiding the impact of redundant data in large datasets, making the dataset more reliable, applicable, and scalable. The proposed approach has been demonstrated through a study of spatio-temporal emission patterns in the Qiaoxi district within city of Shijiazhuang, China. Online data crawling technology was used to obtain data on urban road traffic speed and driving distance. The linear reference technology was used to construct a two-layer road network model to conduct the coupling and matching of traffic data with the road network data. The COPERT model was implemented to calculate the average traffic emissions on each road in the road network, and a traffic emission intensity index was proposed to quantify the CO, VOC, NOx and CO2 emissions on urban roads in the study area. The analysis results show that the traffic emission intensity of the expressway, trunk road, secondary road, and branch road is high during the morning peak (7 AM-9 AM) and evening peak (5 PM—7 PM). The sections with higher traffic emission intensity are mainly concentrated on the main roads and secondary roads such as Jiefang South Street, Shitong Road and Xinhua Road. Nearly one-third of 2nd Ring and 3rd Ring roads also have relatively high emission intensity. The research results provide new ideas for estimating traffic emissions in urban road networks and analyzing the spatio-temporal distribution of traffic emissions. The research results can also provide a decision-making basis for traffic management departments to formulate energy-saving and emission-reduction measures and promote the development of urban green and low-carbon transportation.

Highly Efficient MAPbI3-Based Quantum Dots Exhibiting Unusual Nonblinking Single Photon Emission at Room Temperature.

Highly emissive semiconductor nanocrystals, or so-called quantum dots (QDs) possess a variety of applications from displays and biology labeling, to quantum communication and modern security. Though ensembles of QDs have already shown very high photoluminescent quantum yields (PLQYs) and have been widely utilized in current optoelectronic products, QDs that exhibit high absorption cross-section, high emission intensity, and, most important, nonblinking behavior at single-dot level have long been desired and not yet realized at room temperature. In this work, infrared-emissive MAPbI3-based halide perovskite QDs is demonstrated. These QDs not only show a ≈100% PLQY at the ensemble level but also, surprisingly, at the single-dot level, display an extra-large absorption cross-section up to 1.80 × 10-12 cm2 and non-blinking single photon emission with a high single photon purity of 95.3%, a unique property that is extremely rare among all types of quantum emitters operated at room temperature. An in-depth analysis indicates that neither trion formation nor band-edge carrier trapping is observed in MAPbI3 QDs, resulting in the suppression of intensity blinking and lifetime blinking. Fluence-dependent transient absorption measurements reveal that the coexistence of non-blinking behavior and high single photon purity in these perovskite QDs results from a significant repulsive exciton-exciton interaction, which suppresses the formation of biexciton, and thus greatly reduces photocharging. The robustness of these QDs is confirmed by their excellent stability under continuous 1 h electron irradiation in high-resolution transmission electron microscope inspection. It is believed that these results mark an important milestone in realizing nonblinking single photon emission in semiconductor QDs.

Synthesis and characterization of Eu3+-doped glass ceramics from the system CaO-GeO2-Li2O-B2O3

Three Eu3+ doped glass compositions from the system CaO-GeO2-Li2O-B2O3 were thermally treated for obtaining of the nano glass-ceramics. A series of glass ceramics were obtained under different heat treatment conditions for each glass composition. The main crystallizing phases in the three investigated compositions were Ca2GeO4, Ca5Ge3O11 or Li2CaGeO4. Research was aimed at finding the optimal thermal treatment conditions of parent glasses for preparing of glass-ceramics with optimal particle size, degree of crystallization and transparency determining high emission intensity. For this, a stepwise heat treatment was applied to obtain a series of glass-ceramic samples from the same starting glass composition. Under such treatment, the kinetics of nucleation and growth of the crystallizing phase were tracked. DTA, XRD, TEM, UV–vis analyses were used for characterization of the obtained series of glass-ceramics. Based on the results, it was concluded that the main factors determining the behavior of the crystallizing nanophase (predominant new nucleation or predominant growth of already appeared seeds) are the thermal treatment conditions and the composition and structure of the parent glass, and not so much the composition and structure of the crystallizing phase.

1,10‐Phenanthroline‐Based Octahedra Induced by Protonation of a Nitrogen Atom: Structures and Emission Properties

AbstractAlthough a few metal‐free octahedral compounds based on nitrogen‐containing ligands are known, the realization of mixed ligand compounds remains difficult. To obtain an improved understanding of this class of compounds, two new octahedral compounds, [(tmphenH)(phen)]PF6, and [(tmphenH)(tmphen)]PF6 (where tmphen=3,4,7,8‐tetramethyl‐1,10‐phenanthroline and phen=1,10‐phenanthroline), were synthesized. The relationship between the emission properties, as evaluated using experimental measurements and theoretical calculations, and structures of the protonated compounds was studied. In addition, differences between the atomic charge distributions and geometries in the ground and singlet excited states were investigated using density functional theory calculations. Both [(tmphenH)(phen)]PF6 and [(tmphenH)(tmphen)]PF6 formed hydrogen‐bonded octahedrons in acetonitrile solution, even in the excited state. However, the hydrogen bonding in [(tmphenH)(phen)]PF6 was weak and thermal vibrations decreased the emission intensity. In contrast, the additional methyl substituents in [(tmphenH)(tmphen)]PF6 suppressed thermal vibrations, resulting in a higher emission intensity.

Incorporating biochar into fuels system of iron and steel industry: carbon emission reduction potential and economic analysis

Biochar as a prospective renewable energy candidate could be incorporated into the iron and steel production system to replace part of fossil fuels and reduce high-intensity greenhouse gas emissions. However, great uncertainties still exist on biochar's emission reduction capacity and economic feasibility, depending on different biochar precursors, substitution scenarios, energy consumption of biochar production and financial cost. This study aimed to explore the optimized substitution strategies concerning the above issues. A systematic carbon accounting was performed by material flow analysis method (MFA). Two biochar incorporated iron and steel production routes, integrated production route (BF-BOF) and short production route (EAF), which took the proportion of 71.5% and 28.2% in worldwide production, were considered. CO2 Supply Curve (CSC) was conducted to carry out a quantitative economic viability analysis of biochar substitution under carbon emission trading schemes (ETS). Results showed that compared with straw-based biochar, wood-based biochar showed stronger carbon reduction capacity of 1.47 t CO2e (CO2-equivalent) /t crude steel, and the reduction potential reached 66.94% mostly. Among all the steel production processes, Blast furnace in BF-BOF route had the largest emission contribution proportion (72.06%), achieving the best GWP100 reduction potential of 73.66%. The incorporation of wood-based biochar in sintering (−0.037 yuan/t CO2e) was selected as the scenario with both reduction potential and economic viability. If the scenario was fully implemented in China, it could reduce 2.01 million tons of CO2e in 2021. This study would play a vital role in guiding iron and steel industry for biochar substituted fuels.

Illuminating the mechanism and allosteric behavior of NanoLuc luciferase

NanoLuc, a superior β-barrel fold luciferase, was engineered 10 years ago but the nature of its catalysis remains puzzling. Here experimental and computational techniques are combined, revealing that imidazopyrazinone luciferins bind to an intra-barrel catalytic site but also to an allosteric site shaped on the enzyme surface. Structurally, binding to the allosteric site prevents simultaneous binding to the catalytic site, and vice versa, through concerted conformational changes. We demonstrate that restructuration of the allosteric site can boost the luminescent reaction in the remote active site. Mechanistically, an intra-barrel arginine coordinates the imidazopyrazinone component of luciferin, which reacts with O2 via a radical charge-transfer mechanism, and then it also protonates the resulting excited amide product to form a light-emitting neutral species. Concomitantly, an aspartate, supported by two tyrosines, fine-tunes the blue color emitter to secure a high emission intensity. This information is critical to engineering the next-generation of ultrasensitive bioluminescent reporters.

Identification of Calcium and Magnesium in Medicine Using Plasma Laser Spectroscopy

The identification of magnesium (Mg) in pharmaceutical products was carried out using LIPS (Laser-Induced Plasma Spectroscopy). The lasers used in the research were Nd: YAG laser and CO2 laser. The sample used was a supplement tablet. The laser beam is directed and focused by a convex lens on the sample. The plasma beam is induced on the sample surface. The sharp and high-intensity emission spectrum detected using the Nd: YAG laser indicates the presence of Calcium (Ca) and Magnesium (Mg) in the sample. The results obtained were then compared with sample testing using a CO2 laser. The results of the Mg spectrum intensity were much higher using a CO2 laser.

Synthesis and optical properties of novel red-emitting phosphors Ba3Lu1–xEuxB9O18 (x = 0–0.85)

The novel red-emitting phosphors Ba3Lu1–xEuxB9O18 (x = 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.85) belonging to the Ba3REEB9O18 (REE – Y, Pr–Lu) family were successfully obtained by a multistep solid-phase synthesis. X-ray diffraction experiments revealed no phase transitions caused by the Eu3+ → Lu3+ isomorphic substitution in this series of solid solutions. An increase in the Eu3+ content leads to an expectable increase of hexagonal unit cell parameters and volume. Optical properties of the Ba3Lu1–xEuxB9O18 (x = 0–0.85) phosphors were investigated. The highest emission intensity was demonstrated by Ba3Lu0.6Eu0.4B9O18. The concentration quenching of luminescence was revealed for the x(Eu3+) > 0.4 samples. Concentration quenching, quantum yield and structural data were compared between three red-emitting Ba–Lu borates-phosphors (BLBO:Eu3+) containing independent crystallographic sites for the REE ions (n = 1–3) in crystal structure. It was revealed that the higher the number of nonequivalent cationic REE sites suitable for the Eu3+ → Lu3+ substitution, the higher the quantum yield taking into account practically equal amount of an optimal concentration of the activator-ion. Such an observation could be useful for a crystal chemical design of novel phosphors.

A novel CeO2-ZnO-In2O3 nanocomposite for display applications and latent fingerprint detection in forensic science

An eco friendly and facile green combustion method is employed to synthesize CeO2-ZnO-In2O3 nanocomposite using Aloevera gel extract as a reducing agent followed by calcination to increase the emission properties in the blue region. The Bragg reflections of CeO2, ZnO and In2O3 confirms the formation of the NCs. However, the reflections corresponding to ZnO was found to be dominant. The crystallite size and other structural parameters such as strain, crystallinity, dislocation density and structural factor were determined. The surface morphology consists of highly agglomerated nanoparticles due to decrease in surface energy and adherence of particles with weak force. The direct energy band gap was found to be 3.06 eV. Further, the photoluminescence emission spectra, CIE and CCT coordinates clearly confirms the high intense emission in the blue region. The technique of powder dusting is used to visualize the latent finger prints. With a clear resolution, a well resolved ridge patterns for the identification of distinct latent finger prints are observed in the synthesized CeO2-ZnO-In2O3 nanocomposite. Thus, the present synthesized nanocomposite might be potential in blue light emission, fluorescence labelling and forensic applications.

Broadband 1.53 μm Emission and McCumber Analysis of Er3+ Doped Alkali Oxyfluorophosphate Glass for Fiber Optic Communication Material

Er3+ doped alkali oxyfluorophosphate glasses were prepared by the melted quenching method and characterized their optical and photoluminescence properties. Firstly, the chemical compositions of glasses were varied by changing alkali fluoride (LiF and NaF), whereas the concentration of Er3+ was fixed at 1.00 mol%. The optical absorption pattern and intensity were resemblance. Broadband 1.53 μm emission was one prominent peak of Er3+ in glass and the highest emission intensity was obtained for NaF glass under the stimulating at 521 nm. Secondly, the NaF glass was prepared by variation of Er3+ concentration (0.1, 0.5, 1.0, 2.0, and 4.0 mol%). The emission intensity of glasses increases with an increase in Er2O3 concentration up to 2.00 mol% and decreases for higher Er2O3 concentration, because of the concentration quenching effect. Broadband emission was observed that it covers three telecommunication windows: S, C, and L bands. The absorption and emission cross-section of 2.00 mol% of Er3+ doped alkali oxyfluorophosphate were found to be 1.3895 x 10−20 cm2 and 1.7248 x 1020 cm−2 , respectively by using the McCumber theory. Both values led to the estimate of the internal gain coefficient for 4I13/2→4I15/2 emission transition. The gain coefficient is positive when P is higher than 40%. All results point out that Er3+ doped alkali oxyfluorophosphate glass could be useful for fiber optic communication material.

Emission characteristics of biogenic volatile organic compounds in a subtropical pristine forest of southern China

Emission characteristics of biogenic volatile organic compounds (BVOCs) from dominant tree species in the subtropical pristine forests of China are extremely limited. Here we conducted in situ field measurements of BVOCs emissions from representative mature evergreen trees by using dynamic branch enclosures at four altitude gradients (600–1690 m a.s.l.) in the Nanling Mountains of southern China. Composition characteristics as well as seasonal and altitudinal variations were analyzed. Standardized emission rates and canopy-scale emission factors were then calculated. Results showed that BVOCs emission intensities in the wet season were generally higher than those in the dry season. Monoterpenes were the dominant BVOCs emitted from most broad-leaved trees, accounting for over 70% of the total. Schima superba, Yushania basihirsuta and Altingia chinensis had relatively high emission intensities and secondary pollutant formation potentials. The localized emission factors of isoprene were comparable to the defaults in the Model of Emissions of Gases and Aerosols from Nature (MEGAN), while emission factors of monoterpenes and sesquiterpenes were 2 to 58 times of those in the model. Our results can be used to update the current BVOCs emission inventory in MEGAN, thereby reducing the uncertainties of BVOCs emission estimations in forested regions of southern China.

Evolution Characteristics and Main Influencing Factors of Carbon Dioxide Emissions in Chinese Cities from 2005 to 2020

Based on the carbon emission database of the China Urban Greenhouse Gas Working Group, this paper analyzed the spatiotemporal evolution characteristics and main influencing factors of urban carbon dioxide emissions in China using ArcGIS spatial analysis and SPSS statistical analysis methods, in order to provide a reference for the formulation of the national “double-carbon” strategy and the construction of low-carbon urbanization. The results showed that (1) the urban carbon dioxide emissions in China exhibit a “point-line-area” spreading spatial grid. Carbon dioxide emissions form a planar emission pattern surrounded by the Beijing–Tianjin–Hebei urban agglomeration, Yangtze River Delta urban agglomeration, and Central Plains urban agglomeration. A high per capita and high-intensity emission belt from Xinjiang to Inner Mongolia has been formed. (2) The proportion of industrial emissions continues to decrease, and the range of high industrial emissions has gradually crossed the “Hu Huan-yong Line”, spreading from eastern China to the whole country. The emissions from transportation, the service industry, and households have become new growth points, and high-value emissions from households have also shown a nationwide spreading trend. (3) The main factors influencing the spatial distribution of carbon dioxide emissions are urbanization, the economy, industry, investment, and household energy consumption.

Regional common prosperity level and its spatial relationship with carbon emission intensity in China

The characteristics of common prosperity include harmonious relationships between humans and the environment, as well as sustainable economic and social growth. The process of achieving common prosperity will necessarily have an impact on carbon emissions. In this article, panel statistics collected from 30 Chinese provinces and cities between the years 2006 and 2020 are utilized to assess the level of common prosperity and the intensity of carbon emissions in China. Then the SDM model is applied to explore the effects of the common prosperity level on the intensity of carbon emissions. The findings reveal that: (i) The common prosperity level in China has shown an increasing tendency. Between 2006 and 2020, the mean level of common prosperity increased from 0.254 to 0.486. From the regional perspective, eastern China has seen greater levels of common prosperity than central China, while central China has experienced greater levels of common prosperity than western China; regional disparities in the degree of common prosperity are substantial among Chinese provinces from 2006 to 2020; the common prosperity level is relatively high in economically developed provinces and relatively low in economically backward provinces. (ii) China's carbon emission intensity shows a continuous downward tendency. The annual average intensity of China's carbon emissions decreased from 4.458 in 2006 to 2.234 in 2020. From the regional perspective, the three main regions' carbon emission intensity likewise exhibits a decline in tendency between 2006 and 2020; still, western China continues to have the greatest carbon emission intensity, following central China, while eastern China has the smallest; however, certain provinces, notably Inner Mongolia and Shanxi, continue to have high carbon emission intensity. (iii) China's common prosperity level and carbon emission intensity both exhibit positive spatial autocorrelation at a 1% significant level under the adjacency matrix. The spatial agglomeration effect is significant, and adjacent provinces can affect each other. (iv) The SDM (Spatial Durbin Model) model test with fixed effects finds that the increase in the level of common prosperity suppresses the intensity of carbon emissions in the local area and neighboring regions. (v) The mediating effects model indicates that the process of common prosperity suppresses carbon emission intensity through high-quality economic development, narrowing the income disparity, and the development of a sharing economy.