Ammonia(NH3)has been widely recognized as a key precursor of atmospheric secondary aerosol formation.Vehicle emission is a major source of urban atmospheric NH3.With the tightening of emission standards and the growin...Ammonia(NH3)has been widely recognized as a key precursor of atmospheric secondary aerosol formation.Vehicle emission is a major source of urban atmospheric NH3.With the tightening of emission standards and the growing trend of vehicle fleet electrification,it is imperative to update the emission factors for NH3 from real-world on-road fleets.In this study,a tunnel measurement was conducted in the urban area of Tianjin,China.The fleet-average NH3 emission factor(EF)was 11.2 mg/(km·veh),significantly lower than those in previous studies,showing the benefit of emission standard updating.Through a multiple linear regression analysis,the EFs of light-duty gasoline vehicles,light-duty diesel vehicles,and heavy-duty diesel vehicles(HDDVs)were estimated to be 5.7±0.6 mg/(km·veh),40.8±5.1 mg/(km·veh),and 160.2±16.6 mg/(km·veh),respectively.Based on the results from this study,we found that HDDVs,which comprise<3%of the total vehicles may contribute approximately 22%of total NH3 emissions in Tianjin.Our results highlight NH3 emissions from HDDVs,a previously potentially overlooked source of NH3 emissions in urban areas.The actual on-road NH3 emissions from HDDVs may exceed current expectations,posing a growing concern for the future.展开更多
Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research probl...Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem.Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables.In this study,we propose a machine learning algorithm for carbon emissions,a Bayesian optimized XGboost regression model,using multi-year energy carbon emission data and nighttime lights(NTL)remote sensing data from Shaanxi Province,China.Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models,with an R^(2)of 0.906 and RMSE of 5.687.We observe an annual increase in carbon emissions,with high-emission counties primarily concentrated in northern and central Shaanxi Province,displaying a shift from discrete,sporadic points to contiguous,extended spatial distribution.Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns,with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering.Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissionsmore accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment.This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.展开更多
The challenge of establishing top-down constraints for regional emissions of fossil fuel CO_(2)(FFCO_(2))arises from the difficulty in distinguishing between atmospheric CO_(2)concentrations released from fossil fuels...The challenge of establishing top-down constraints for regional emissions of fossil fuel CO_(2)(FFCO_(2))arises from the difficulty in distinguishing between atmospheric CO_(2)concentrations released from fossil fuels and background variability,particularly owing to the influence of terrestrial biospheric fluxes.This necessitates the development of a regional inversion methodology based on atmospheric CO_(2)observations to verify bottom-up estimations independently.This study presents a promising approach for estimating China's FFCO_(2)emissions by incorporating the model residual errors(MREs)of the column-averaged dry-air mole fractions of CO_(2)(XCO_(2))from FFCO_(2)emissions(MREff)retained in the analysis of natural flux optimization.China's FFCO_(2)emissions during the COVID-19 lockdown in 2020 are estimated using the GEOS-Chem adjoint model.The relationship between the MREff and FFCO_(2)is determined using the model based on a regional FFCO_(2)anomaly suggested by posterior NOx emissions from air-quality data assimilation.The MREff is typically one-tenth in magnitude,but some positively skewed outliers exceed 1 ppm because the prior emissions lack lockdown impacts,thereby exerting considerable observation forcing given the satellite retrieval uncertainties.We initialize the FFCO_(2)with posterior NOx emissions and optimize the colinear emission ratio.Synthetic data experiments demonstrate that this approach reduces the FFCO_(2)bias to less than 10%.The real-data experiments estimate 19%lower FFCO_(2)with GOSAT XCO_(2)and 26%lower with OCO-2 XCO_(2)than the bottom-up estimations.This study proves the feasibility of our regional FFCO_(2)inversion,highlighting the importance of addressing the outlier behaviors observed in satellite XCO_(2)retrievals.展开更多
To understand the smoke level and NO_(x)emission characteristics of in-use construction machinery in Beijing,we selected 905 construction machines in Beijing from August 2022 to April 2023 to monitor the emission leve...To understand the smoke level and NO_(x)emission characteristics of in-use construction machinery in Beijing,we selected 905 construction machines in Beijing from August 2022 to April 2023 to monitor the emission level of smoke and NO_(x).The exhaust smoke level and excessive emission situation of different machinery types were identified,and their NO_(x)emission levels were monitored according to the free acceleration method.We investigated the correlation of NO_(x)and smoke emission,and proposed suggestions for controlling pollution discharge from construction machinery in the future.The results show that the exhaust smoke level was 0–2.62 m^(−1),followed a log-normal distribution(μ=-1.73,δ=1.09,R^(2)=0.99),with a 5.64%exceedance rate.Differenceswere observed amongmachinery types,with low-power engine forklifts showing higher smoke levels.The NO_(x)emission range was 71–1516 ppm,followed a normal distribution(μ=565.54,δ=309.51,R^(2)=0.83).Differences among machinery types were relatively small.Engine rated net power had the most significant impact on NO_(x)emissions.Thus,NO_(x)emissions from construction machinery need further attention.Furthermore,we found a weak negative correlation(p<0.05)between the emission level of smoke and NO_(x),that is the synergic emission reduction effect is poor,emphasizing the need for NO_(x)emission limits.In the future,the oversight in Beijing should prioritize phasing out ChinaⅠand ChinaⅡmachinery,and monitor emissions from highpower engine ChinaⅢmachinery.展开更多
As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limite...As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.展开更多
This paper presents an air quality simulation model that incorporates shipping activities and weather conditions,with a case study of Hainan Island to examine the impact of ship emissions on air quality.The findings r...This paper presents an air quality simulation model that incorporates shipping activities and weather conditions,with a case study of Hainan Island to examine the impact of ship emissions on air quality.The findings reveal that the density of automatic identification system(AIS)signals is particularly high in the southern coastal regions.The results showed that the annual ship emissions recorded the highest density of 896.7 tons/0.01°,49.8 tons/0.01°,1139.7 tons/0.01°,and 122,000 tons/0.01°for sulfur oxides(SO_(x)),particulate matter(PM),nitrogen oxides(NOx),and carbon dioxide(CO_(2)),respectively.Furthermore,the partial distributions of these emissions were not significantly affected by the seasons.Ships within twelve nautical miles of Hainan coastlines emit approximately 2817.7 tons of SO_(x),14,686.4 tons of NO_(x),630.4 tons of PM_(2.5),and 416.9 tons of hydrocarbons(HC)annually.These emissions are primarily concentrated in the sea areas surrounding the ports of Haikou,Yangpu,Basuo,and Sanya.Ships manufactured between 2000 and 2010 have contributed significantly to air pollution,with SO_(x) and HC emissions accounting for approximately 51%and 56% of total emissions,respectively.However,for shipsmanufactured after 2016,these proportions have dropped to approximately 10%.In terms of air pollutants fromship emissions in Hainan Island,the spatial distribution of their contributions is significantly uneven.The impact of PM2.5 differs significantly depending on the season,with the concentrations being substantially higher during Spring.However,the proportions of O3 and other pollutants do not vary significantly,except during Spring.展开更多
Recently,the transportation sector in China has gradually become the main source of urban air pollution and primary driver of carbon emissions growth.Considering air pollutants and greenhouse gases come from the same ...Recently,the transportation sector in China has gradually become the main source of urban air pollution and primary driver of carbon emissions growth.Considering air pollutants and greenhouse gases come from the same emission sources,it is necessary to establish an updated high-resolution emission inventory for the transportation sector in Central China,themost polluted region in China.The inventory includes on-road mobile,non-roadmobile,oil storage and transportation,and covers 9 types of air pollutants and 3 types of greenhouse gases.Based on the Long-range Energy Alternatives Planning System(LEAP)model,the emissions of pollutants were predicted for the period from2020 to 2035 in different scenarios.Results showed that in 2020,emissions of SO_(2),NO_(x),CO,PM_(10),PM_(2.5),VOCs,NH_(3),BC,OC,CO_(2),CH_(4),and N_(2)O in Henan Province were 27.5,503.2,878.6,20.1,17.4,222.1,21.5,9.4,2.9,92,077.9,6.0,and 10.4 kilotons,respectively.Energy demand and pollutant emissions in Henan Province are simulated under four scenarios(Baseline Scenario(BS),Pollution Abatement Scenario(PA),Green Transportation Scenario(GT),and Reinforcing Low Carbon Scenario(RLC)).The collaborative emission reduction effect is most significant in the RLC scenario,followed by the GT scenario.By 2035,under the RLC scenario,energy consumption and emissions of SO_(2),NO_(x),CO,PM_(10),PM_(2.5),VOCs,NH_(3),CO_(2),CH_(4),and N_(2)O are projected to decrease by 72.0%,30.0%,55.6%,56.0%,38.6%,39.7%,51.5%,66.1%,65.5%,55.4%,and 52.8%,respectively.This study provides fundamental data support for subsequent numerical simulations.展开更多
With the rapid development of aviation industry and its increasing impact on the global climate change,the contributions of carbon emissions frominternational flights are attracting more and more attention worldwide.T...With the rapid development of aviation industry and its increasing impact on the global climate change,the contributions of carbon emissions frominternational flights are attracting more and more attention worldwide.This study,taking Macao as the aviation hub,established the cross-border aviation carbon emission evaluation model to explore dynamic carbon emissions and net-zero path of international flights.The aviation hubmainly covers 58 routes and five types of civil aircraft from 12 countries or regions during 2000-2022.The results show that the aviation transportation in Macao emitted about 1.44 million tons CO_(2)eq in 2019,which is high 3.6 times that of 2000.The COVID-19 has led to a rapid decline in aviation carbon emissions in a short period of time,carbon emissions in 2020 decreased by 80%compared to 2019.In terms of cumulative carbon emissions from 2000 to 2019,the A321 and A320 Airbus contribute to 80%of carbon emissions.And the Chinese mainland(37%)and Taiwan(29%)are the main sources of emissions.In 2000-2019,the proportion of carbon emissions from China(including Taiwan and Hong Kong)decrease from 91%to 53%,while the contribution from Southeast Asia(from 5% to 26%),Japan and South Korea(from 2% to 19%)keep the growth trends.In the optimal scenario(B3C3),net zero emissions of cross-border aviation in Macao can be not achieved,and there is still only by removing 0.3 million tons CO_(2)eq.Emission reduction technology and new energy usage are priorities for the aviation emission reduction.展开更多
Ship emissions contribute considerably to air pollution and are expected to decline under domestic policies and international cooperation such as green shipping corridors(GSCs).However,evaluation of the emission reduc...Ship emissions contribute considerably to air pollution and are expected to decline under domestic policies and international cooperation such as green shipping corridors(GSCs).However,evaluation of the emission reduction potential by the Domestic Emission Control Area(DECA)policy and GSC cooperation is still lacking.Here,a series of multi-year high spatiotemporal ship emission inventories around Hainan,a representative island province of China,were developed with the state-of-the-art Shipping Emission Inventory Model.The improved origin-destination identification algorithm allowed emission allocation to port level.The emission reduction potential of the DECA policy and Hainan's joining GSCwas analyzed.In 2022,ship emission intensity in waters 12 Nm from Hainan(Hainan-12Nm)were 6.4%-7.4% of that in waters 12 Nm from China.From 2019 to 2022,Hainan-12Nm emissions dropped by 66.7%-77.8% for SO_(2) and PM2.5.Ideally,with adequate ultra-low-sulfur fuel,DECA can reduce SO_(2) and PM2.5 emissions by 16.6% and 22.4% yearly compared with no-DECA scenario.However,emission reduction would drop markedly if ultra-low-sulfur fuel is short in supply.Emissions of voyages passing through 200 Nm from Hainan took up 1%-4%of international shipping emissions,implying great emission reduction potential for Hainan's establishing GSCs,especially considering the flourishing South-South trade.This study provides a thorough assessment of the current state of shipping emissions around Hainan as well as offers excellent data support for Hainan to further advance the future upgrade of ship emission management policies.展开更多
Organic afterglow materials hold significant potential for applications in information storage,anticounterfeiting,and biological imaging.However,studies on afterglow materials capable of ultra-wide range excitation an...Organic afterglow materials hold significant potential for applications in information storage,anticounterfeiting,and biological imaging.However,studies on afterglow materials capable of ultra-wide range excitation and emission simultaneously are limited.To enhance the practicality of strong emission single-component organic afterglow systems,overcoming the constraints of crystalline or other rigid environments is essential.We have developed solid-state dual-persistent thermally activated delayed fluorescence(TADF)and room temperature phosphorescence(RTP)emissions spanning yellow to red under visible light excitation,utilizing a single-molecule terminal group regulation strategy.The RTP lifetime extends from 4.19 ms to 399.70 ms.These afterglow materials exhibit an ultra-wide absorption range from 200 nm to 800 nm,rendering them capable of being excited by both sunlight simulator and nearinfrared radiation.The upconversion phosphorescence lifetime under 808 nm excitation reaches 13.72μs.The double persistent emission of these compounds is temperature-sensitive.Moreover,following grinding or heat treatment,accompanied by extensive afterglow color conversion due to planarization of excited state conformations and additional efficient kRIsc generation.In addition,the amorphous state post melt annealing facilitates the afterglow transition from yellow to green.Crucially,these compounds also maintain stable ultra-long afterglow emission in aqueous and acid-base environments.Overall,we have successfully developed a series of single-component intelligent luminescent materials that demonstrate significant benefits,including dual TADF and RTP emissions,adjustable afterglow lifetimes,a broad range of excitation and emission wavelengths,multi-modal luminescence not restricted to crystalline states,and robust afterglow performance in challenging environments,setting the stage for the practical deployment of afterglow materials in engineering applications,the upconversion afterglow emission also holds promising potential for applications in the field of biological imaging.展开更多
Soil fugitive dust(SFD)is characterized by a variety of sources and considerable spatialtemporal variability,exerting a significant impact on environmental air quality and ecological systems in cities across northern ...Soil fugitive dust(SFD)is characterized by a variety of sources and considerable spatialtemporal variability,exerting a significant impact on environmental air quality and ecological systems in cities across northern China.Multiple factors can shape SFD emission.Nevertheless,the current comprehension of its critical impact factors and quantitative methodologies remains constrained.This study utilizes interpretable machine learning techniques to identify the principal impact factors of SFD and their interactions while delineating their action thresholds.The findings reveal seasonal variations in impact factors and emphasize the substantial effect of bare soil source strength on SFD,including parameters such as bare soil area and soil moisture.Consequently,the Wind Erosion Equation model is optimized following these findings to localize its parameters and improve its capability to calculate hourly SFD emissions.The case application is validated using observational data,demonstrating the reliability and precision of the optimized methodology.This study provides insights and solutions for the local optimization of SFD parameterization schemes and further supports the formulation of precise prevention and control policies for SFD.展开更多
In the process of deep engineering excavation,the mechanical properties of rock are significantly influenced by the coupled effects of water and high stress,which greatly increase construction difficulty.To more accur...In the process of deep engineering excavation,the mechanical properties of rock are significantly influenced by the coupled effects of water and high stress,which greatly increase construction difficulty.To more accurately investigate the impact of water disturbance on the failure process of dry rock under high stress and the failure mechanisms of saturated rock in underwater environments,a water environment test chamber and a prefabricated borehole specimen through-water device were designed.A series of experiments were conducted,including uniaxial tests,water-disturbed granite cylinder tests,and through-water disturbance tests on prefabricated hole square specimens.The results showed that the acoustic emission(AE)hits and accumulated energy after the through-water disturbance at the same time were 8.77 and 12.08 times higher than before the disturbance,respectively.And water disturbance increased the proportion of tensile failure and reduced the proportion of shear failure.A key observation was that AE events were mainly generated in the permeation areas near the borehole.The main reason was that under high stress,the weakening effect of water led to the failure of the local mineral structure of the rock,promoting crack extension and triggering overall instability.Notably,failure of the saturated specimens underwater was only observed when the applied load approached the saturation strength of the prefabricated hole square specimens.The study results provide an important theoretical basis for understanding the damage mechanism of water-disturbed rocks in deep engineering,and have significant implications for the design and construction of engineering.展开更多
In cold-region environments,where complex stresses and mining disturbances occur,rock masses are frequently segmented into discontinuous bodies by fractured structural planes,leading to anisotropic physical and mechan...In cold-region environments,where complex stresses and mining disturbances occur,rock masses are frequently segmented into discontinuous bodies by fractured structural planes,leading to anisotropic physical and mechanical properties.To explore the evolution of microcracks,degradation characteristics,and failure modes of fractured rocks in cold regions under the influence of freeze-thaw cycles,integrating laboratory experiments with the damage mechanics of freeze-thaw cycles.A numerical model for freeze-thaw cycle damage in rocks with various fracture dip angles was developed.The study revealed that the freeze-thaw expansion force generated during the pore water-ice phase transition is the primary driving factor behind freeze-thaw cycle damage.The initiation and propagation of microcracks and micropores,the detachment of matrix particles,and the loosening of clay mineral structures result in the transformation of the rock from a dense to a porous state,causing significant degradation in macroscopic mechanical properties.As freeze-thaw cycles increase,both the uniaxial compressive strength and the deformation modulus of the rock decrease significantly,with the failure mode gradually shifting from brittle instability to brittle-plastic or plastic failure.The findings of this study offer a practical approach to uncovering the mechanical response mechanisms between freeze-thaw damage in fractured rocks and structural planes.展开更多
Achieving a reduction in global greenhouse gas(GHG)emissions requires collaborative efforts from the international community;however,a comprehensive understanding of the spatiotemporal characteristics(i.e.,complex emi...Achieving a reduction in global greenhouse gas(GHG)emissions requires collaborative efforts from the international community;however,a comprehensive understanding of the spatiotemporal characteristics(i.e.,complex emission networks and driver patterns)and the mutual influence of gross domestic product(GDP)and GHG emissions remains limited at a global level in the 21st century,which is not conducive to forming a consensus in global climate change negotiations and formulating relevant policies.To fill these gaps,this study comprehensively analyzes the complex network and driver pattern of GHG emissions,as well as the corresponding mutual influence with GDP for 185 countries during 2000-2021,based on social network analysis,the logarithmic Divisia decomposition approach,and panel vector autoregression model at global and regional levels.The results indicate that significant heterogeneity and inequality exist in terms of GHG emissions among regions and countries in different geographical areas and economic income levels.Additionally,GDP per capita and GHG emission intensity are the largest positive and negative drivers,respectively,affecting the increase in global GHG emissions.Furthermore,key countries,such as Germany and Canada,that could serve as coordinating bridges to strengthen collaboration in the global emission network are identified.This study highlights the need to encourage key participants in the emission network and foster international cooperation in governance,energy technology,and economic investment to address climate change.展开更多
PM_(2.5)and O_(3) are two major issues hindering air quality improvement in China.However,the response of these two pollutants to anthropogenic emission variations in the real atmosphere was not yet well understood.He...PM_(2.5)and O_(3) are two major issues hindering air quality improvement in China.However,the response of these two pollutants to anthropogenic emission variations in the real atmosphere was not yet well understood.Here,we selected the short-term epidemic lockdown in Wuhu in 2022 as a case study and evaluated the impacts of meteorology and anthropogenic emission on PM_(2.5)and O_(3) using field observations combined with machine learning algorithms.The results showed that NO_(2) observed during the lockdown was 32.2±8.1μg/m^(3),10.1%lower than before the lockdown,and that NO_(2) continued to decrease by 19.2%after the lockdown.Notably,both PM_(2.5)and O_(3) concentrations were higher during the lockdown than before and after the lockdown.Random forest model revealed that meteorological conditions during the lockdown increased PM_(2.5)and O_(3) by 8.7%and 24.2%,respectively,but decreased NO_(2) by 6.4%.Atmospheric pressure and relative humidity were the main meteorological variables influencing PM_(2.5)and O_(3) variations,respectively.Scenario simulation analysis uncovered that anthropogenic emission reduction caused by the lockdown reduced NO_(2) by 19.7%,but increased PM_(2.5)and O_(3) by 6.3%and 26.8%,respectively.This was mainly due to the weakening titration effect of nitrogen oxides and enhanced atmospheric oxidation capacity,further increasing O_(3) and secondary PM_(2.5)production.Our results revealed that NO_(2) in Wuhu decreased significantly due to short-term epidemic lockdown,but PM_(2.5)and O_(3) pollution were not effectively reduced.To continuously improve future urban air quality,joint reductions in emissions from multiple anthropogenic sources and multiple pollutants are required.展开更多
Accurate prediction of manufacturing carbon emissions is of great significance for subsequent low-carbon optimization.To improve the accuracy of carbon emission prediction with insufficient hobbing data,combining the ...Accurate prediction of manufacturing carbon emissions is of great significance for subsequent low-carbon optimization.To improve the accuracy of carbon emission prediction with insufficient hobbing data,combining the advantages of improved algorithm and supplementary data,a method of carbon emission prediction of hobbing based on cross-process data fusion was proposed.Firstly,we analyzed the similarity of machining process and manufacturing characteristics and selected milling data as the fusion material for hobbing data.Then,the adversarial learning was used to reduce the difference between data from the two processes,so as to realize the data fusion at the characteristic level.After that,based on Meta-Transfer Learning method,the carbon emission prediction model of hobbing was established.The effectiveness and superiority of the proposed method were verified by case analysis and comparison.The prediction accuracy of the proposed method is better than other methods across different data sizes.展开更多
The textile industry,while creating material wealth,also exerts a significant impact on the environment.Particularly in the textile manufacturing phase,which is the most energy-intensive phase throughout the product l...The textile industry,while creating material wealth,also exerts a significant impact on the environment.Particularly in the textile manufacturing phase,which is the most energy-intensive phase throughout the product lifecycle,the problem of high energy usage is increasingly notable.Nevertheless,current analyses of carbon emissions in textile manufacturing emphasize the dynamic temporal characteristics while failing to adequately consider critical information such as material flows and energy consumption.A carbon emission analysis method based on a holographic process model(HPM)is proposed to address these issues.First,the system boundary in the textile manufacturing is defined,and the characteristics of carbon emissions are analyzed.Next,an HPM based on the object-centric Petri net(OCPN)is constructed,and simulation experiments are conducted on three different scenarios in the textile manufacturing.Subsequently,the constructed HPM is utilized to achieve a multi-perspective analysis of carbon emissions.Finally,the feasibility of the method is verified by using the production data of pure cotton products from a certain textile manufacturing enterprise.The results indicate that this method can analyze the impact of various factors on the carbon emissions of pure cotton product production,and by applying targeted optimization strategies,carbon emissions have been reduced by nearly 20%.This contributes to propelling the textile manufacturing industry toward sustainable development.展开更多
In contrast to the predominant mono or difunctionalization of alkenes,the multi-site functionalization of alkenes involving the synergistic formation of more than two new C–C or C–X bonds is much challenging,especia...In contrast to the predominant mono or difunctionalization of alkenes,the multi-site functionalization of alkenes involving the synergistic formation of more than two new C–C or C–X bonds is much challenging,especially for developing new reaction pathway to afford the functional heterocycle compounds with aggregation-induced emission(AIE)property has been rarely reported.In present work,the multi-site functionalization of in situ generated alkenes with indoles has been developed for the synthesis of diversely functionalized carbazoles through the synergistic construction of multiple C–C bonds and C=O bond.A proposed reaction sequence involving C–H alkenylation/radical oxygen atom transfer/Diels-Alder cycloaddition/dehydrogenative aromatization was supported by experiments and density functional theory calculations.Further derivative carbazole-linked-quinoxaline skeletons represent a class of AIEgens with acceptor-donor-acceptor configuration,which generated the desired twisted intramolecular charge transfer(TICT)AIE properties and could be used as fluorescent probes for detecting the micrometer-sized phase separation of polymer blends.The protocol provides a concise route for the synthesis and application of carbazole-based AIE luminogens.展开更多
Biotite content critically influences rock mechanical behavior and threatens underground engineering stability.Uniaxial compression tests with acoustic emission(AE)monitoring were conducted on granite pegmatite sample...Biotite content critically influences rock mechanical behavior and threatens underground engineering stability.Uniaxial compression tests with acoustic emission(AE)monitoring were conducted on granite pegmatite samples having varying biotite content.Peak frequency distribution analysis,rise angleaverage frequency(RA-AF)analysis,multifractal theory,and a dynamic multifractal algorithm were applied to explore the relationship between damage evolution and AE characteristics.Results indicate that increased biotite content reduces uniaxial compressive strength and elastic modulus,enhances plastic deformation,and increases the proportion of shear cracks.The segmented evolution of the dynamic multifractal parameter Δα_(m) is biotite-dependent.Oscillations during the elastic phase signify localized shear crack initiation and propagation;their attenuation in the plastic phase reflects frictional closure along biotite cleavage planes,promoting elastic energy storage and delaying release.AE-based damage models and time-varying signals characterize rock damage progression.Stress concentrations around biotite minerals foster localized shear band formation,leading to concentrated shear failure at lower damage levels.Higher biotite content accelerates crack propagation,while smooth cleavage planes lower the fracture energy threshold,reducing strength and stiffness.These findings enhance understanding of biotite-influenced progressive rock damage and underpin stability monitoring and early-warning systems for underground engineering.展开更多
China is currently the largest emitter of carbon dioxide globally.The nation,vulnerable to the imminent challenges of climate change and greenhouse gas emissions,is determined to reduce emissions.Thus,by adopting a sy...China is currently the largest emitter of carbon dioxide globally.The nation,vulnerable to the imminent challenges of climate change and greenhouse gas emissions,is determined to reduce emissions.Thus,by adopting a systemstheory approach,this study is aimed at examining how the agricultural lands,output values,production activities,and populations,as well as the economic factors,influence carbon emissions in Sichuan Province.To offer insights into the long-term agricultural carbon emission(ACE)trajectories,a system dynamics model is used to predict the emission trends from 2023 to 2040.The findings indicate the following:①policy regulation exerts influence on the ACE in the province.As per the simulation results,regulating the gross domestic product growth of the primary industry at 2.5%,5%,and 10%will only increase the carbon emissions by 0.24%,0.25%,and 0.53%,respectively,by 2040,indicating that effective policy regulations can decouple economic growth from substantial increases in emissions,thereby underscoring their pivotal role in emission control.②Regulating the agricultural-economy growth rate and policies can effectively reduce ACEs in the province.③While single policies exert limited influence,combining multiple measures significantly boosts carbon reduction.For example,comprehensive strategies,including reduced pesticide use and marginal farmland conversion,can lower agricultural land carbon emissions by 3.48%,5.30%,and 7.47%(by 2035)and 1.67%,2.76%,and 3.65%(by 2040).Overall,these results emphasize the effectiveness of coordinated policies,alongside market control and land-use adjustments,in advancing low-carbon agricultural development.展开更多
基金supported by the National key research and development program of China(No.2022YFE0135000)the National Natural Science Foundation of China(No.42175123)the Natural Science Foundation of Tianjin(No.23JCJQJC00170).
文摘Ammonia(NH3)has been widely recognized as a key precursor of atmospheric secondary aerosol formation.Vehicle emission is a major source of urban atmospheric NH3.With the tightening of emission standards and the growing trend of vehicle fleet electrification,it is imperative to update the emission factors for NH3 from real-world on-road fleets.In this study,a tunnel measurement was conducted in the urban area of Tianjin,China.The fleet-average NH3 emission factor(EF)was 11.2 mg/(km·veh),significantly lower than those in previous studies,showing the benefit of emission standard updating.Through a multiple linear regression analysis,the EFs of light-duty gasoline vehicles,light-duty diesel vehicles,and heavy-duty diesel vehicles(HDDVs)were estimated to be 5.7±0.6 mg/(km·veh),40.8±5.1 mg/(km·veh),and 160.2±16.6 mg/(km·veh),respectively.Based on the results from this study,we found that HDDVs,which comprise<3%of the total vehicles may contribute approximately 22%of total NH3 emissions in Tianjin.Our results highlight NH3 emissions from HDDVs,a previously potentially overlooked source of NH3 emissions in urban areas.The actual on-road NH3 emissions from HDDVs may exceed current expectations,posing a growing concern for the future.
基金supported by the Key Research and Development Program in Shaanxi Province,China(No.2022ZDLSF07-05)the Fundamental Research Funds for the Central Universities,CHD(No.300102352901)。
文摘Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem.Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables.In this study,we propose a machine learning algorithm for carbon emissions,a Bayesian optimized XGboost regression model,using multi-year energy carbon emission data and nighttime lights(NTL)remote sensing data from Shaanxi Province,China.Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models,with an R^(2)of 0.906 and RMSE of 5.687.We observe an annual increase in carbon emissions,with high-emission counties primarily concentrated in northern and central Shaanxi Province,displaying a shift from discrete,sporadic points to contiguous,extended spatial distribution.Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns,with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering.Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissionsmore accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment.This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.
基金jointly supported by the National Key Research and Development Plan(Grant No.2023YFB3907405)the National Natural Science Foundation of China(Grant No.42175132)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(Grant No.YSBR-037)。
文摘The challenge of establishing top-down constraints for regional emissions of fossil fuel CO_(2)(FFCO_(2))arises from the difficulty in distinguishing between atmospheric CO_(2)concentrations released from fossil fuels and background variability,particularly owing to the influence of terrestrial biospheric fluxes.This necessitates the development of a regional inversion methodology based on atmospheric CO_(2)observations to verify bottom-up estimations independently.This study presents a promising approach for estimating China's FFCO_(2)emissions by incorporating the model residual errors(MREs)of the column-averaged dry-air mole fractions of CO_(2)(XCO_(2))from FFCO_(2)emissions(MREff)retained in the analysis of natural flux optimization.China's FFCO_(2)emissions during the COVID-19 lockdown in 2020 are estimated using the GEOS-Chem adjoint model.The relationship between the MREff and FFCO_(2)is determined using the model based on a regional FFCO_(2)anomaly suggested by posterior NOx emissions from air-quality data assimilation.The MREff is typically one-tenth in magnitude,but some positively skewed outliers exceed 1 ppm because the prior emissions lack lockdown impacts,thereby exerting considerable observation forcing given the satellite retrieval uncertainties.We initialize the FFCO_(2)with posterior NOx emissions and optimize the colinear emission ratio.Synthetic data experiments demonstrate that this approach reduces the FFCO_(2)bias to less than 10%.The real-data experiments estimate 19%lower FFCO_(2)with GOSAT XCO_(2)and 26%lower with OCO-2 XCO_(2)than the bottom-up estimations.This study proves the feasibility of our regional FFCO_(2)inversion,highlighting the importance of addressing the outlier behaviors observed in satellite XCO_(2)retrievals.
基金supported by the Energy Foundation(No.G-2203-33693).
文摘To understand the smoke level and NO_(x)emission characteristics of in-use construction machinery in Beijing,we selected 905 construction machines in Beijing from August 2022 to April 2023 to monitor the emission level of smoke and NO_(x).The exhaust smoke level and excessive emission situation of different machinery types were identified,and their NO_(x)emission levels were monitored according to the free acceleration method.We investigated the correlation of NO_(x)and smoke emission,and proposed suggestions for controlling pollution discharge from construction machinery in the future.The results show that the exhaust smoke level was 0–2.62 m^(−1),followed a log-normal distribution(μ=-1.73,δ=1.09,R^(2)=0.99),with a 5.64%exceedance rate.Differenceswere observed amongmachinery types,with low-power engine forklifts showing higher smoke levels.The NO_(x)emission range was 71–1516 ppm,followed a normal distribution(μ=565.54,δ=309.51,R^(2)=0.83).Differences among machinery types were relatively small.Engine rated net power had the most significant impact on NO_(x)emissions.Thus,NO_(x)emissions from construction machinery need further attention.Furthermore,we found a weak negative correlation(p<0.05)between the emission level of smoke and NO_(x),that is the synergic emission reduction effect is poor,emphasizing the need for NO_(x)emission limits.In the future,the oversight in Beijing should prioritize phasing out ChinaⅠand ChinaⅡmachinery,and monitor emissions from highpower engine ChinaⅢmachinery.
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037,and 42105133)the National Key Research and Development Program of China(No.2022YFC3703502)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project(No.202203a07020003)Hefei Ecological Environment Bureau Project(No.2020BFFFD01804).
文摘As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.
基金supported by the National Key Research and Development Program of China(No.2022YFC3704200)the National Natural Science Foundation of China(No.52306128)+5 种基金the Major Program of Science and Technology of Hainan Province,China(No.ZDKJ202007)the Innovation Platform for Academicians of Hainan Province(No.YSPTZX202205)the Youth Innovation Foundation of Hainan Research Academy of Environmental Sciences,China(No.QNCX2021002)the Central Guiding Local Science and Technology Development Fund Projects(No.236Z4001G)the Natural Science Basic Research Program of Shaanxi(No.2023-JC-QN-0517)the support from Energy Foundation China.
文摘This paper presents an air quality simulation model that incorporates shipping activities and weather conditions,with a case study of Hainan Island to examine the impact of ship emissions on air quality.The findings reveal that the density of automatic identification system(AIS)signals is particularly high in the southern coastal regions.The results showed that the annual ship emissions recorded the highest density of 896.7 tons/0.01°,49.8 tons/0.01°,1139.7 tons/0.01°,and 122,000 tons/0.01°for sulfur oxides(SO_(x)),particulate matter(PM),nitrogen oxides(NOx),and carbon dioxide(CO_(2)),respectively.Furthermore,the partial distributions of these emissions were not significantly affected by the seasons.Ships within twelve nautical miles of Hainan coastlines emit approximately 2817.7 tons of SO_(x),14,686.4 tons of NO_(x),630.4 tons of PM_(2.5),and 416.9 tons of hydrocarbons(HC)annually.These emissions are primarily concentrated in the sea areas surrounding the ports of Haikou,Yangpu,Basuo,and Sanya.Ships manufactured between 2000 and 2010 have contributed significantly to air pollution,with SO_(x) and HC emissions accounting for approximately 51%and 56% of total emissions,respectively.However,for shipsmanufactured after 2016,these proportions have dropped to approximately 10%.In terms of air pollutants fromship emissions in Hainan Island,the spatial distribution of their contributions is significantly uneven.The impact of PM2.5 differs significantly depending on the season,with the concentrations being substantially higher during Spring.However,the proportions of O3 and other pollutants do not vary significantly,except during Spring.
基金supported by the 2020 National Supercomputing Zhengzhou Center Innovation Ecosystem Construction Technology Project(No.201400210700)Zhengzhou PM2.5 and O3 Collaborative Control and Monitoring Project(No.20220347A).
文摘Recently,the transportation sector in China has gradually become the main source of urban air pollution and primary driver of carbon emissions growth.Considering air pollutants and greenhouse gases come from the same emission sources,it is necessary to establish an updated high-resolution emission inventory for the transportation sector in Central China,themost polluted region in China.The inventory includes on-road mobile,non-roadmobile,oil storage and transportation,and covers 9 types of air pollutants and 3 types of greenhouse gases.Based on the Long-range Energy Alternatives Planning System(LEAP)model,the emissions of pollutants were predicted for the period from2020 to 2035 in different scenarios.Results showed that in 2020,emissions of SO_(2),NO_(x),CO,PM_(10),PM_(2.5),VOCs,NH_(3),BC,OC,CO_(2),CH_(4),and N_(2)O in Henan Province were 27.5,503.2,878.6,20.1,17.4,222.1,21.5,9.4,2.9,92,077.9,6.0,and 10.4 kilotons,respectively.Energy demand and pollutant emissions in Henan Province are simulated under four scenarios(Baseline Scenario(BS),Pollution Abatement Scenario(PA),Green Transportation Scenario(GT),and Reinforcing Low Carbon Scenario(RLC)).The collaborative emission reduction effect is most significant in the RLC scenario,followed by the GT scenario.By 2035,under the RLC scenario,energy consumption and emissions of SO_(2),NO_(x),CO,PM_(10),PM_(2.5),VOCs,NH_(3),CO_(2),CH_(4),and N_(2)O are projected to decrease by 72.0%,30.0%,55.6%,56.0%,38.6%,39.7%,51.5%,66.1%,65.5%,55.4%,and 52.8%,respectively.This study provides fundamental data support for subsequent numerical simulations.
基金supported by the Science and Technology Development Fund,Macao SAR,China(Nos.0033/2022/AFJ and 0011/2023/AMJ)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515012017).
文摘With the rapid development of aviation industry and its increasing impact on the global climate change,the contributions of carbon emissions frominternational flights are attracting more and more attention worldwide.This study,taking Macao as the aviation hub,established the cross-border aviation carbon emission evaluation model to explore dynamic carbon emissions and net-zero path of international flights.The aviation hubmainly covers 58 routes and five types of civil aircraft from 12 countries or regions during 2000-2022.The results show that the aviation transportation in Macao emitted about 1.44 million tons CO_(2)eq in 2019,which is high 3.6 times that of 2000.The COVID-19 has led to a rapid decline in aviation carbon emissions in a short period of time,carbon emissions in 2020 decreased by 80%compared to 2019.In terms of cumulative carbon emissions from 2000 to 2019,the A321 and A320 Airbus contribute to 80%of carbon emissions.And the Chinese mainland(37%)and Taiwan(29%)are the main sources of emissions.In 2000-2019,the proportion of carbon emissions from China(including Taiwan and Hong Kong)decrease from 91%to 53%,while the contribution from Southeast Asia(from 5% to 26%),Japan and South Korea(from 2% to 19%)keep the growth trends.In the optimal scenario(B3C3),net zero emissions of cross-border aviation in Macao can be not achieved,and there is still only by removing 0.3 million tons CO_(2)eq.Emission reduction technology and new energy usage are priorities for the aviation emission reduction.
基金supported by the National Natural Science Foundation of China(No.42325505)the National Key R&D Program of China(No.2022YFC3704200)the Tsinghua University Initiative Scientific Research Program.
文摘Ship emissions contribute considerably to air pollution and are expected to decline under domestic policies and international cooperation such as green shipping corridors(GSCs).However,evaluation of the emission reduction potential by the Domestic Emission Control Area(DECA)policy and GSC cooperation is still lacking.Here,a series of multi-year high spatiotemporal ship emission inventories around Hainan,a representative island province of China,were developed with the state-of-the-art Shipping Emission Inventory Model.The improved origin-destination identification algorithm allowed emission allocation to port level.The emission reduction potential of the DECA policy and Hainan's joining GSCwas analyzed.In 2022,ship emission intensity in waters 12 Nm from Hainan(Hainan-12Nm)were 6.4%-7.4% of that in waters 12 Nm from China.From 2019 to 2022,Hainan-12Nm emissions dropped by 66.7%-77.8% for SO_(2) and PM2.5.Ideally,with adequate ultra-low-sulfur fuel,DECA can reduce SO_(2) and PM2.5 emissions by 16.6% and 22.4% yearly compared with no-DECA scenario.However,emission reduction would drop markedly if ultra-low-sulfur fuel is short in supply.Emissions of voyages passing through 200 Nm from Hainan took up 1%-4%of international shipping emissions,implying great emission reduction potential for Hainan's establishing GSCs,especially considering the flourishing South-South trade.This study provides a thorough assessment of the current state of shipping emissions around Hainan as well as offers excellent data support for Hainan to further advance the future upgrade of ship emission management policies.
基金financially supported by the National Natural Science Foundation of China(No.21871122)。
文摘Organic afterglow materials hold significant potential for applications in information storage,anticounterfeiting,and biological imaging.However,studies on afterglow materials capable of ultra-wide range excitation and emission simultaneously are limited.To enhance the practicality of strong emission single-component organic afterglow systems,overcoming the constraints of crystalline or other rigid environments is essential.We have developed solid-state dual-persistent thermally activated delayed fluorescence(TADF)and room temperature phosphorescence(RTP)emissions spanning yellow to red under visible light excitation,utilizing a single-molecule terminal group regulation strategy.The RTP lifetime extends from 4.19 ms to 399.70 ms.These afterglow materials exhibit an ultra-wide absorption range from 200 nm to 800 nm,rendering them capable of being excited by both sunlight simulator and nearinfrared radiation.The upconversion phosphorescence lifetime under 808 nm excitation reaches 13.72μs.The double persistent emission of these compounds is temperature-sensitive.Moreover,following grinding or heat treatment,accompanied by extensive afterglow color conversion due to planarization of excited state conformations and additional efficient kRIsc generation.In addition,the amorphous state post melt annealing facilitates the afterglow transition from yellow to green.Crucially,these compounds also maintain stable ultra-long afterglow emission in aqueous and acid-base environments.Overall,we have successfully developed a series of single-component intelligent luminescent materials that demonstrate significant benefits,including dual TADF and RTP emissions,adjustable afterglow lifetimes,a broad range of excitation and emission wavelengths,multi-modal luminescence not restricted to crystalline states,and robust afterglow performance in challenging environments,setting the stage for the practical deployment of afterglow materials in engineering applications,the upconversion afterglow emission also holds promising potential for applications in the field of biological imaging.
基金supported by the General Program of National Natural Science Foundation of China(No.42275190)。
文摘Soil fugitive dust(SFD)is characterized by a variety of sources and considerable spatialtemporal variability,exerting a significant impact on environmental air quality and ecological systems in cities across northern China.Multiple factors can shape SFD emission.Nevertheless,the current comprehension of its critical impact factors and quantitative methodologies remains constrained.This study utilizes interpretable machine learning techniques to identify the principal impact factors of SFD and their interactions while delineating their action thresholds.The findings reveal seasonal variations in impact factors and emphasize the substantial effect of bare soil source strength on SFD,including parameters such as bare soil area and soil moisture.Consequently,the Wind Erosion Equation model is optimized following these findings to localize its parameters and improve its capability to calculate hourly SFD emissions.The case application is validated using observational data,demonstrating the reliability and precision of the optimized methodology.This study provides insights and solutions for the local optimization of SFD parameterization schemes and further supports the formulation of precise prevention and control policies for SFD.
基金supported by the National Natural Science Foundation of China(Nos.52374080 and 52404201)。
文摘In the process of deep engineering excavation,the mechanical properties of rock are significantly influenced by the coupled effects of water and high stress,which greatly increase construction difficulty.To more accurately investigate the impact of water disturbance on the failure process of dry rock under high stress and the failure mechanisms of saturated rock in underwater environments,a water environment test chamber and a prefabricated borehole specimen through-water device were designed.A series of experiments were conducted,including uniaxial tests,water-disturbed granite cylinder tests,and through-water disturbance tests on prefabricated hole square specimens.The results showed that the acoustic emission(AE)hits and accumulated energy after the through-water disturbance at the same time were 8.77 and 12.08 times higher than before the disturbance,respectively.And water disturbance increased the proportion of tensile failure and reduced the proportion of shear failure.A key observation was that AE events were mainly generated in the permeation areas near the borehole.The main reason was that under high stress,the weakening effect of water led to the failure of the local mineral structure of the rock,promoting crack extension and triggering overall instability.Notably,failure of the saturated specimens underwater was only observed when the applied load approached the saturation strength of the prefabricated hole square specimens.The study results provide an important theoretical basis for understanding the damage mechanism of water-disturbed rocks in deep engineering,and have significant implications for the design and construction of engineering.
基金supported by the National Key Research and Development Program of China(No.2022YFC2903902)the National Natural Science Foundation of China(Nos.52374157 and 52174070)+1 种基金the Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001)the Key Science and Technology Project of Ministry of Emergency Management of the People’s Republic of China(No.2024EMST080802).
文摘In cold-region environments,where complex stresses and mining disturbances occur,rock masses are frequently segmented into discontinuous bodies by fractured structural planes,leading to anisotropic physical and mechanical properties.To explore the evolution of microcracks,degradation characteristics,and failure modes of fractured rocks in cold regions under the influence of freeze-thaw cycles,integrating laboratory experiments with the damage mechanics of freeze-thaw cycles.A numerical model for freeze-thaw cycle damage in rocks with various fracture dip angles was developed.The study revealed that the freeze-thaw expansion force generated during the pore water-ice phase transition is the primary driving factor behind freeze-thaw cycle damage.The initiation and propagation of microcracks and micropores,the detachment of matrix particles,and the loosening of clay mineral structures result in the transformation of the rock from a dense to a porous state,causing significant degradation in macroscopic mechanical properties.As freeze-thaw cycles increase,both the uniaxial compressive strength and the deformation modulus of the rock decrease significantly,with the failure mode gradually shifting from brittle instability to brittle-plastic or plastic failure.The findings of this study offer a practical approach to uncovering the mechanical response mechanisms between freeze-thaw damage in fractured rocks and structural planes.
基金supported by the Humanities and Social Sciences Youth Foundation,Ministry of Education of China[Grant No.24YJC630248]Sichuan Office of Philosophy and Social Science,China[Grant No.SCJJ24ND299].
文摘Achieving a reduction in global greenhouse gas(GHG)emissions requires collaborative efforts from the international community;however,a comprehensive understanding of the spatiotemporal characteristics(i.e.,complex emission networks and driver patterns)and the mutual influence of gross domestic product(GDP)and GHG emissions remains limited at a global level in the 21st century,which is not conducive to forming a consensus in global climate change negotiations and formulating relevant policies.To fill these gaps,this study comprehensively analyzes the complex network and driver pattern of GHG emissions,as well as the corresponding mutual influence with GDP for 185 countries during 2000-2021,based on social network analysis,the logarithmic Divisia decomposition approach,and panel vector autoregression model at global and regional levels.The results indicate that significant heterogeneity and inequality exist in terms of GHG emissions among regions and countries in different geographical areas and economic income levels.Additionally,GDP per capita and GHG emission intensity are the largest positive and negative drivers,respectively,affecting the increase in global GHG emissions.Furthermore,key countries,such as Germany and Canada,that could serve as coordinating bridges to strengthen collaboration in the global emission network are identified.This study highlights the need to encourage key participants in the emission network and foster international cooperation in governance,energy technology,and economic investment to address climate change.
基金supported by the National Natural Science Foundation of China(No.42207128)the Key Research Projects of Natural Science in Colleges and Universities of Anhui Province(No.KJ2021A0091)the Natural Science Foundation of Anhui Province(No.2008085MD111)。
文摘PM_(2.5)and O_(3) are two major issues hindering air quality improvement in China.However,the response of these two pollutants to anthropogenic emission variations in the real atmosphere was not yet well understood.Here,we selected the short-term epidemic lockdown in Wuhu in 2022 as a case study and evaluated the impacts of meteorology and anthropogenic emission on PM_(2.5)and O_(3) using field observations combined with machine learning algorithms.The results showed that NO_(2) observed during the lockdown was 32.2±8.1μg/m^(3),10.1%lower than before the lockdown,and that NO_(2) continued to decrease by 19.2%after the lockdown.Notably,both PM_(2.5)and O_(3) concentrations were higher during the lockdown than before and after the lockdown.Random forest model revealed that meteorological conditions during the lockdown increased PM_(2.5)and O_(3) by 8.7%and 24.2%,respectively,but decreased NO_(2) by 6.4%.Atmospheric pressure and relative humidity were the main meteorological variables influencing PM_(2.5)and O_(3) variations,respectively.Scenario simulation analysis uncovered that anthropogenic emission reduction caused by the lockdown reduced NO_(2) by 19.7%,but increased PM_(2.5)and O_(3) by 6.3%and 26.8%,respectively.This was mainly due to the weakening titration effect of nitrogen oxides and enhanced atmospheric oxidation capacity,further increasing O_(3) and secondary PM_(2.5)production.Our results revealed that NO_(2) in Wuhu decreased significantly due to short-term epidemic lockdown,but PM_(2.5)and O_(3) pollution were not effectively reduced.To continuously improve future urban air quality,joint reductions in emissions from multiple anthropogenic sources and multiple pollutants are required.
基金Supported by National Natural Science Foundation of China(Grant No.52005062)Chongqing Municipal Natural Science Foundation of China(Grant No.CSTB2023NSCQ-MSX0390)。
文摘Accurate prediction of manufacturing carbon emissions is of great significance for subsequent low-carbon optimization.To improve the accuracy of carbon emission prediction with insufficient hobbing data,combining the advantages of improved algorithm and supplementary data,a method of carbon emission prediction of hobbing based on cross-process data fusion was proposed.Firstly,we analyzed the similarity of machining process and manufacturing characteristics and selected milling data as the fusion material for hobbing data.Then,the adversarial learning was used to reduce the difference between data from the two processes,so as to realize the data fusion at the characteristic level.After that,based on Meta-Transfer Learning method,the carbon emission prediction model of hobbing was established.The effectiveness and superiority of the proposed method were verified by case analysis and comparison.The prediction accuracy of the proposed method is better than other methods across different data sizes.
基金National Key R&D Program of China(No.2019YFB1706300)。
文摘The textile industry,while creating material wealth,also exerts a significant impact on the environment.Particularly in the textile manufacturing phase,which is the most energy-intensive phase throughout the product lifecycle,the problem of high energy usage is increasingly notable.Nevertheless,current analyses of carbon emissions in textile manufacturing emphasize the dynamic temporal characteristics while failing to adequately consider critical information such as material flows and energy consumption.A carbon emission analysis method based on a holographic process model(HPM)is proposed to address these issues.First,the system boundary in the textile manufacturing is defined,and the characteristics of carbon emissions are analyzed.Next,an HPM based on the object-centric Petri net(OCPN)is constructed,and simulation experiments are conducted on three different scenarios in the textile manufacturing.Subsequently,the constructed HPM is utilized to achieve a multi-perspective analysis of carbon emissions.Finally,the feasibility of the method is verified by using the production data of pure cotton products from a certain textile manufacturing enterprise.The results indicate that this method can analyze the impact of various factors on the carbon emissions of pure cotton product production,and by applying targeted optimization strategies,carbon emissions have been reduced by nearly 20%.This contributes to propelling the textile manufacturing industry toward sustainable development.
文摘In contrast to the predominant mono or difunctionalization of alkenes,the multi-site functionalization of alkenes involving the synergistic formation of more than two new C–C or C–X bonds is much challenging,especially for developing new reaction pathway to afford the functional heterocycle compounds with aggregation-induced emission(AIE)property has been rarely reported.In present work,the multi-site functionalization of in situ generated alkenes with indoles has been developed for the synthesis of diversely functionalized carbazoles through the synergistic construction of multiple C–C bonds and C=O bond.A proposed reaction sequence involving C–H alkenylation/radical oxygen atom transfer/Diels-Alder cycloaddition/dehydrogenative aromatization was supported by experiments and density functional theory calculations.Further derivative carbazole-linked-quinoxaline skeletons represent a class of AIEgens with acceptor-donor-acceptor configuration,which generated the desired twisted intramolecular charge transfer(TICT)AIE properties and could be used as fluorescent probes for detecting the micrometer-sized phase separation of polymer blends.The protocol provides a concise route for the synthesis and application of carbazole-based AIE luminogens.
基金provided by the National Key R&D Program of China(No.2024YFC3012605)the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project(Nos.SKLGP2022Z001,SKLGP2023Z029 and SKLGP2022K027)。
文摘Biotite content critically influences rock mechanical behavior and threatens underground engineering stability.Uniaxial compression tests with acoustic emission(AE)monitoring were conducted on granite pegmatite samples having varying biotite content.Peak frequency distribution analysis,rise angleaverage frequency(RA-AF)analysis,multifractal theory,and a dynamic multifractal algorithm were applied to explore the relationship between damage evolution and AE characteristics.Results indicate that increased biotite content reduces uniaxial compressive strength and elastic modulus,enhances plastic deformation,and increases the proportion of shear cracks.The segmented evolution of the dynamic multifractal parameter Δα_(m) is biotite-dependent.Oscillations during the elastic phase signify localized shear crack initiation and propagation;their attenuation in the plastic phase reflects frictional closure along biotite cleavage planes,promoting elastic energy storage and delaying release.AE-based damage models and time-varying signals characterize rock damage progression.Stress concentrations around biotite minerals foster localized shear band formation,leading to concentrated shear failure at lower damage levels.Higher biotite content accelerates crack propagation,while smooth cleavage planes lower the fracture energy threshold,reducing strength and stiffness.These findings enhance understanding of biotite-influenced progressive rock damage and underpin stability monitoring and early-warning systems for underground engineering.
文摘China is currently the largest emitter of carbon dioxide globally.The nation,vulnerable to the imminent challenges of climate change and greenhouse gas emissions,is determined to reduce emissions.Thus,by adopting a systemstheory approach,this study is aimed at examining how the agricultural lands,output values,production activities,and populations,as well as the economic factors,influence carbon emissions in Sichuan Province.To offer insights into the long-term agricultural carbon emission(ACE)trajectories,a system dynamics model is used to predict the emission trends from 2023 to 2040.The findings indicate the following:①policy regulation exerts influence on the ACE in the province.As per the simulation results,regulating the gross domestic product growth of the primary industry at 2.5%,5%,and 10%will only increase the carbon emissions by 0.24%,0.25%,and 0.53%,respectively,by 2040,indicating that effective policy regulations can decouple economic growth from substantial increases in emissions,thereby underscoring their pivotal role in emission control.②Regulating the agricultural-economy growth rate and policies can effectively reduce ACEs in the province.③While single policies exert limited influence,combining multiple measures significantly boosts carbon reduction.For example,comprehensive strategies,including reduced pesticide use and marginal farmland conversion,can lower agricultural land carbon emissions by 3.48%,5.30%,and 7.47%(by 2035)and 1.67%,2.76%,and 3.65%(by 2040).Overall,these results emphasize the effectiveness of coordinated policies,alongside market control and land-use adjustments,in advancing low-carbon agricultural development.
