Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model versi...Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model version 6 with a machine-learning-integrated four-mode version of the Modal Aerosol Module, we quantify global BC aging responses to emission reductions for 2011–2018 and for 2050 and 2100 under carbon neutrality. During 2011–18, global trends in BC aging degree(mass ratio of coatings to BC, R_(BC)) exhibited marked regional disparities, with a significant increase in China(5.4% yr^(-1)), which contrasts with minimal changes in the USA, Europe, and India. The divergence is attributed to opposing trends in secondary organic aerosol(SOA) and sulfate coatings, driven by regional changes in the emission ratios of corresponding coating precursors to BC(volatile organic compounds-VOCs/BC and SO_(2)/BC). Projections under carbon neutrality reveal that R_(BC) will increase globally by 47%(118%) in 2050(2100), with strong convergent increases expected across major source regions. The R_(BC) increase, primarily driven by enhanced SOA coatings due to sharper BC reductions relative to VOCs, will enhance the global BC mass absorption cross-section(MAC) by 11%(17%) in 2050(2100).Consequently, although the global BC burden will decline sharply by 60%(76%), the enhanced MAC partially offsets the magnitude of the decline in the BC direct radiative effect, resulting in the moderation of global BC DRE decreases to 88%(92%) of the BC burden reductions in 2050(2100). This study highlights the globally enhanced BC aging and light absorption capacity under carbon neutrality, thereby partly offsetting the impact of BC direct emission reductions on future changes in BC radiative effects globally.展开更多
Greenhouse gas(GHG)emissions from China’s food system are a major environmental concern;however,studies quantifying their drivers and future projections remain limited.This study uses structural decomposition analysi...Greenhouse gas(GHG)emissions from China’s food system are a major environmental concern;however,studies quantifying their drivers and future projections remain limited.This study uses structural decomposition analysis and growth curve models to assess food-related GHG trends from 1961 to 2020,identify key drivers and their contributions,and project emissions for 2050 under six economic and population scenarios.It also proposes reduction pathways to help China achieve its 2060 carbon neutrality goal.Animal and plant foods are categorized into 14 groups based on the similarity of their emission coefficients.China’s total food related GHG emissions rose tenfold,from 351.7 to 3719.8 million tons CO_(2)-equivalent(CO_(2)e)/year,between 1961 and 2020.Per-capita emissions increased from 532.1 to 2584.4 kg CO_(2)e/year.Emissions from plant based foods grew from 435.0 to 824.6 kg CO_(2)e/year,while animal-based emissions surged from 97.1 to 1759.8 kg CO_(2)e/year,with animal products contributing more owing to their higher emission coefficients.Key drivers include rising food intake,increasing demand for animal-based foods(especially red meat),and population growth.Scenario analyses predict that emissions will peak at 3826.2 million tons CO_(2)e/year in 2031(low economy-low population)and 3971.0 million tons CO_(2)e/year in 2039(high economy-medium population).Compared with Australian,Indian,and Japanese diets,Chinese diets exhibit lower per-capita emissions than Australia and India but have higher emissions than in Japan.Adhering to China’s national dietary guidelines could reduce Chinese per-capita food-related GHGs by 31.5%,and optimized diets could lower them by 45.3%.This study provides valuable insights for Chinese policymakers to reduce food-related GHG emissions,refine national dietary guidelines,and raise public awareness regarding the food system’s environmental impact,thus encouraging people to follow sustainable diets.展开更多
An integral part of the effort to reduce greenhouse gas emissions is carbon footprint accounting.EPA categorizes facility carbon footprints in three scopes.Scope-2 emissions include electricity,heat or steam purchased...An integral part of the effort to reduce greenhouse gas emissions is carbon footprint accounting.EPA categorizes facility carbon footprints in three scopes.Scope-2 emissions include electricity,heat or steam purchased from a utility provider.This paper evaluates the existing calculation methods for scope-2 CO2 emissions for purchased electricity.The electricity grid in US is complex and is divided spatially into states,eGRID regions,balancing authorities(BAs),and utilities.Up to hourly temporal granularity can be obtained from available datasets.A matrix is developed that categorizes different datasets based on the complexity to calculate the carbon emission factors.Spatial and temporal variations are evaluated.There are significant spatial overlap between regions in different categories and emission factors within a region show sub-regional variation.An area analysis is done using zip-code polygons to determine whether a state or balancing authority is smaller for all the overlapping cases.Temporal variations in emission factors are significant depending on the balancing authority considered.A single method to calculate scope-2 emission factors may not be accurate and efficient in every case and a nuanced assessment of emission factors is warranted.An implementation pathway for a“smart carbon calculator”—one that gives accurate carbon footprint that is the spatially and temporally most granular is suggested.展开更多
Iron and steel industry is one of the main sources of air pollution emissions in China.The sintering process is an important link in the blast furnace ironmaking process,but it is also accompanied by a large number of...Iron and steel industry is one of the main sources of air pollution emissions in China.The sintering process is an important link in the blast furnace ironmaking process,but it is also accompanied by a large number of pollutants.Under the background of ultra-low emissions,iron and steel enterprises urgently need to upgrade their existing processes to address the existing process in practical application problems.In this study,a steel group in Gansu Province was taken as an example.By comparing and analyzing the pollutant emission characteristics before and after the ultra-low emission retrofit,the collaborative control effect of the combined process on SO_(2),NO_(x),particulate matter,and dioxins after the new retrofit was systematically evaluated.The results show that after the retrofit,the concentrations of particulate matter,SO_(2) and NO_(x) have dropped to near-zero levels,and the dioxin removal efficiency has reached 98.87%,with all indicators being better than the national ultra-low emission standards.The study confirms that the optimal combination of multi-pollutant collaborative treatment technologies is the key to achieving efficient emission reduction,among which selective catalytic reduction technology has a particularly significant synergistic removal effect on NO_(x) and dioxins.This study provides an important technical reference and practical basis for the ultra-low emission retrofit of the steel industry,and has important guiding significance for promoting the green retrofit of the industry.Its ultra-low emission retrofit is of great significance for achieving green and low-carbon development.展开更多
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
The carbon emission trading policy is a key policy for China to achieve its dual carbon goals.This paper aims to examine the emission-reduction effects,transmission mechanisms,and carbon-market efficiency of China’s ...The carbon emission trading policy is a key policy for China to achieve its dual carbon goals.This paper aims to examine the emission-reduction effects,transmission mechanisms,and carbon-market efficiency of China’s carbon-emission trading policy from 2012 to 2023.We adopt the difference-in-differences(DID)model to analyze the effects of policy on emissions,and the empirical results from the DID model confirm that the pilot carbon emission trading policy has significantly reduced carbon emission intensity in pilot areas.Then we use the mediation model to study the transmission mechanism of the pilot carbon emission trading policy,and the mediation analysis demonstrates that the pilot carbon emission trading policy achieves emission abatement through four parallel transmission channels:scientific innovation,energy conservation,clean energy substitution,and industrial structure upgrading.Data envelopment analysis evaluates the carbon market efficiency of China.The result shows that the average carbon market efficiency of pilot areas has improved steadily,particularly from 2012 to 2023,especially in Beijing,Hubei,and Guangdong.Moreover,the efficiency of the national carbon market has shown an upward trend since its 2021 launch;it remains lower than the pilot average,constrained primarily by limited sectoral coverage,which impacts scale efficiency.展开更多
Aggregation-induced emission(AIE)polymers have been extensively studied;however,the integration of AIE units into polyelectrolytes remains largely limited by the laborious multistep synthesis of pre-designed emissive ...Aggregation-induced emission(AIE)polymers have been extensively studied;however,the integration of AIE units into polyelectrolytes remains largely limited by the laborious multistep synthesis of pre-designed emissive monomers.Herein,we report a one-pot multicomponent polymerization method that directly produces main-chain charged polyelectrolytes with intrinsic AIE characteristics from non-emissive building blocks.By optimizing the monomer structures and reaction conditions,a series of soluble high-molecular-weight polymers with welldefined backbones were obtained in high yields.The resulting polyelectrolytes displayed robust AIE behavior,exhibiting fluorescence enhancement up to about 60-fold in an aqueous environment,and maintained excellent thermal stability.Owing to their cationic backbones,these polymers interact strongly with microbial surfaces and exhibit remarkable antimicrobial activities.This study establishes a synthetically efficient route to AIE polyelectrolytes and highlights their potential applications as multifunctional materials for bioimaging,antimicrobial therapy,and other applications.展开更多
Under the“dual carbon”goals,it is imperative to incorporate carbon emissions-related factors into research of power grid risk assessment to meet the green transformation needs of the power grid.Therefore,this paper ...Under the“dual carbon”goals,it is imperative to incorporate carbon emissions-related factors into research of power grid risk assessment to meet the green transformation needs of the power grid.Therefore,this paper conducts a study on the risk assessment of carbon emissions changes in regional power grids based on dynamic carbon emission factors,aiming to quantitatively analyze the impact of random disturbances such as equipment failures or fluctuations in renewable energy generation on the carbon emission intensity of regional power grids.First,carbon emission change risk indicators are constructed from three dimensions:the probability,frequency,and magnitude of carbon emission changes.Second,a dynamic carbon emission factor calculation model is proposed to reflect the spatiotemporal change of carbon emissions in the regional power grid,considering output of different types of generators and the components of inter-area power transmission.Finally,with the premise of ensuring safe and stable operation of power grid,a quantitative assessment model for carbon emission change risks is proposed under the objective of minimizing the electricity loss.The sampling convergence conditions of the model are also derived.The results from the MRTS79 case study demonstrate the proposed method can effectively quantify and analyze the risk of carbon emissions changes in regional power grids,validating the effectiveness of the proposed model.展开更多
The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide ele...The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide electricity users in carbon reduction and promote power industry low-carbon transformation.Fundamentally,calculating indirect carbon emissions involves allocating direct carbon emission data from the power source side,indicating that accurate indirect emission results rely on the precise measurement of power source emissions.However,existing research on indirect carbon emissions in large-scale power systems rarely accounts for variations in carbon emission characteristics under different operating conditions of power sources,such as rated/non-rated operating conditions and ramping up/down conditions,making it difficult to reflect source-side and load-side carbon emission information variation during providing ancillary services.Quadratic and exponential functions are proposed to characterize the energy consumption profiles of coal-fired and gas-fired power generation,respectively,to construct a refined carbon emission model for power sources.By leveraging the theory of power system carbon flow,we analyze how variable operating conditions of power sources impact indirect carbon emissions.Case studies demonstrate that changes in power source emissions under variable conditions have a significant effect on the indirect carbon emissions of power grids.展开更多
Eu^(2+)-doped phosphors show broadband absorption,tunable emission and high quantum efficiency due to the parity-allowed 5d→4f transitions,allowing them to be used in solid-state lighting.To expand their applications...Eu^(2+)-doped phosphors show broadband absorption,tunable emission and high quantum efficiency due to the parity-allowed 5d→4f transitions,allowing them to be used in solid-state lighting.To expand their applications in other fields such as detection and sensing technologies,the Eu^(2+)emission needs to be tuned into the near-infrared region,but it is a big challenge to obtain Eu^(2+)near-infrared region emitters due to the absence of host compounds with extremely large crystal-field splitting.In this work,we chose M_(4)Li(BN_(2))_(3)(M=Ca,Sr,Ba)as a host and realize the near-infrared region emission of Eu^(2+)in it.Among these phosphors,Ba4Li(BN_(2))_(3):Eu^(2+)exhibits the longest emission of 880 nm and the largest full-width at half maximum of 276 nm under 450 nm excitation,while Ca_(4)Li(BN_(2))_(3):Eu^(2+)and Sr_(4)Li(BN_(2))_(3):Eu^(2+)emit at740 and 680 nm,respectively.We observe an interesting phenomenon that the energy shift of emission is linearly related to the radius difference between the alkaline earth cation and the activator Eu^(2+)in this system.展开更多
Reducing carbon emissions is fundamental to achieving carbon neutrality.Existing studies have typically estimated emissions by predicting fossil fuel consumption across sectors under different socioeconomic scenarios;...Reducing carbon emissions is fundamental to achieving carbon neutrality.Existing studies have typically estimated emissions by predicting fossil fuel consumption across sectors under different socioeconomic scenarios;however,uncertainties in future development often lead to deviations from these assumptions.To address this limitation,this study proposes a data-driven approach for evaluating national carbon emissions using historical data.Countries with similar energy consumption patterns were selected as reference samples,and their emission pathways were analyzed to predict future emissions for countries that have not yet reached their peak.Key indicators,including peak levels,timing,plateau duration,and post-peak decline rates,were identified.The results indicate that the trends in unpeaked economies can be effectively assessed based on the emission patterns of countries with comparable energy structures.Applying this framework to China suggests a carbon peak between 2027 and 2030,in the range of 14.207 to 16.234 Gt,followed by a gradual decline from 2031 to 2036.Compared with the average results of the existing studies,the predicted minimum and maximum emissions show error margins of 10.1% and 1.41%,respectively.This study proposes a top-down methodology that provides a transparent,reproducible,and empirical framework for forecasting carbon emission pathways,thereby offering a scientific basis for assessing countries that have not yet reached their emissions peak.展开更多
Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the acc...Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the accuracy of emission prediction models,supporting more effective real-time monitoring and enabling informed operational decisions that align with environmental compliance efforts.This paper presents a data-driven approach for the accurate prediction of gas emissions,specifically nitrogen oxides(NOx)and carbon monoxide(CO),in natural gas power plants using an optimized hybrid machine learning framework.The proposed model integrates a Feedforward Neural Network(FFNN)trained using Particle Swarm Optimization to capture the nonlinear emission dynamics under varying gas turbine operating conditions.To further enhance predictive performance,the K-Nearest Neighbor(K-NN)algorithm serves as a post-processing method to enhance IPSO-FFNN predictions through adjustment and refinement,improving overall prediction accuracy,while Neighbor Component Analysis is used to identify and rank the most influential operational variables.The study makes a significant contribution through the combination of NCA feature selection with PSO global optimization,FFNN nonlinear modelling,and K-NN error correction into one unified system,which delivers precise emission predictions.The model was developed and tested using a real-world dataset collected from gas-fired turbine operations,with validated results demonstrating robust accuracy,achieving Root Mean Square Error values of 0.355 for CO and 0.368 for NOx.When benchmarked against conventional models such as standard FFNN,Support Vector Regression,and Long Short-Term Memory networks,the hybrid model achieved substantial improvements,up to 97.8%in Mean Squared Error,95%in Mean Absolute Error(MAE),and 85.19%in RMSE for CO;and 97.16%in MSE,93.4%in MAE,and 83.15%in RMSE for NOx.These results underscore the model’s potential for improving emission prediction,thereby supporting enhanced operational efficiency and adherence to environmental standards.展开更多
Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio ac...Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio active compounds) remain poorly understood,limiting their therapeutic application.This study provides the first comprehensive characterization of spatiotemporal dynamics in airborne phytoncides and their synergistic interactions with environmental factors throughout the autumn-early spring seasonal transition in a temperate forest ecosystem.We analyzed the compositional dynamics of phytoncides and terpenoid content variations using thermal desorption-gas chromatography-mass spectrometry(TD-GC-MS) from September 2024 to March 2025.This period encompassed seasonal transitions from autumn to early spring,including diurnal variations in September and snowfall events in November.The method demonstrated detection limits(LODs) ranging from 1.35 to 5.33 ng m-3 and quantification limits(LOQs) from 4.09 to 16.15 ng m-3.Our results revealed pronounced seasonal fluctuations in phytoncide composition.In September,terpenoids,esters,alcohols,and alkanes displayed a diurnal "decrease-increase" trend,whereas aldehydes and ketones peaked at midday.Notably,esters and alcohols were undetectable in November and January.By January,terpenoids reached their lowest proportion(0.17±0.02%) at noon.Five terpenoids(α-pinene,myrcene,D-limonene,camphene,p-cymene) were detected in September,four(α-pinene,D-limonene,camphene,p-cymene) in November,two(D-limonene,p-cymene) in January,and only p-cymene in March.The total concentration and emission rate of the five terpenoids peaked in September afternoons at 1961.58±106.67 ng m^(-3) and653.86±35.56 ng m^(-3) h^(-1),respectively.Nocturnal emissions(32131.95±2522.21 ng m^(-3)) significantly surpassed daytime levels(14473.04±958.49 ng m^(-3)),with emission rates escalating from 1447.30±95.85 ng m^(-3) h^(-1)(day) to 5355.33±420.37 ng m^(-3) h^(-1)(night),marking a3.7-fold increase.Snowfall dramatically elevated terpenoid concentrations(pre-snowfall:158.58±14.12 ng m^(-3);post-snowfall:1080.57±57.76 ng m^(-3)) and emission rates(pre-snowfall:52.86±4.71 ng m^(-3) h^(-1);post-snowfall:360.19±19.25 ng m^(-3) h^(-1)),reflecting a 6.8-fold surge.This study underscores the profound influence of light intensity,seasonal shifts,and climatic conditions on airborne phytoncide levels,offering a scientific foundation for optimizing forest therapy and ecotourism strategies.展开更多
Lakes are carbon dioxide(CO_(2))and methane(CH_(4))emission hotspots,whose associated flux is spatially vari-able.Many studies have investigated the impact of microorganisms and environmental factors on CO_(2) and CH_...Lakes are carbon dioxide(CO_(2))and methane(CH_(4))emission hotspots,whose associated flux is spatially vari-able.Many studies have investigated the impact of microorganisms and environmental factors on CO_(2) and CH_(4) emissions between different lakes.However,the carbon emissions and their influencing factors of different areas within a single lake remain poorly understood.Accordingly,this study investigates CO_(2) and CH_(4) emission hetero-geneity in a large floodplain lake system and distribution characteristics of associated functional microorganisms.Findings show that mean CO_(2) and CH_(4) flux values in the sub lake area were 62.03±24.21 mg/(m2·day)and 5.97±3.2μg/(m2·day),which were greater by factors of 1.78 and 2.96 compared to the water channel and the main lake area,respectively.The alpha diversity of methanogens in the sub lake area was lower than that in the main lake and water channel areas.The abundance of methanogens in bottom water layer was higher compared with the middle and surface layers.Conversely,the abundance of methane(CH_(4))-oxidizing bacteria in the surface layer was higher than that in the bottom layer.Additionally,the composition of methanogen and CH_(4)-oxidizing bacterial community,chlorophyll a(Chl-a),pH,total phosphorus(TP)and dissolved organic carbon(DOC)con-tent constituted the dominate driving factors affecting lake C emissions.Results from this study can be used to improve our understanding of lake spatial heterogeneous of CO_(2) and CH_(4) emission and the driving mechanisms within floodplain lakes under the coupling effects of functional C microorganisms and environmental factors.展开更多
In coal mines,dynamic disasters such as rock bursts seriously threaten the safety of mining activities.Exploring the dynamic behaviors and disaster characteristics in the impact failure process of coal serves as the b...In coal mines,dynamic disasters such as rock bursts seriously threaten the safety of mining activities.Exploring the dynamic behaviors and disaster characteristics in the impact failure process of coal serves as the basis and prerequisite for monitoring and warning rock bursts.In this context,impact failure tests of coal were carried out under different axial static loads and impact velocities to analyze the dynamic behaviors and acoustic emission(AE)response characteristics of coal.The results show that the dynamic behaviors of coal under combined dynamic and static loads are significantly different from those under static loads,and the stress-strain curve displays double peaks without an obvious compaction stage.As the axial static load grows,the dynamic strength and peak strain both have a quadratic function with the axial static load.When the coal damage intensifies instantaneously,the AE count and energy parameters both witness pulse-like increases and reach their peak values.The damage effect of axial static loads on coal,though limited,has an extreme point.In contrast,the impact velocity can strengthen the response of AE signals and has linear function relationships with the peak values of AE count and energy.This plays a leading role in the damage to samples and sets a critical point for coal failure and fracture.Compared with the analysis results of stress and strain,the responses of AE signals are more accurate and reliable.Based on AE response characteristics,the damage evolution process of coal under the combined dynamic and static loads can be identified more accurately to reveal the moment corresponding to coal damage and the characteristics of coal failure.The research results are conducive to the further application of AE monitoring methods to early warning of rock burst disasters in coal mining sites.展开更多
Ionic phototheranostic agents have found extensive application in preclinical and clinical practice owing to their excellent biocompatibility and synergistic diagnostic-therapeutic integration.However,they still suffe...Ionic phototheranostic agents have found extensive application in preclinical and clinical practice owing to their excellent biocompatibility and synergistic diagnostic-therapeutic integration.However,they still suffer from certain limitations,such as short absorption/emission wavelengths,poor photostability,aggregation-caused fluorescence self-quenching,and diminished phototherapeutic efficacy upon aggregation,which collectively hinder their efficacy in complex clinical scenarios.To address these challenges,a second near-infrared(NIR-II)ionic phototheranostic agent,namely DT-BT-BIn,is rationally designed and synthesized via an innovative dual-acceptor engineering strategy.DT-BT-BIn ingeniously integrates benzothiadiazole and benzo[c,d]indolium as dual-acceptor units,which successfully achieves superior aggregation-induced NIR-II emission characteristics,highly efficient Type Ⅰ/Ⅱ photodynamic activity coupled with photothermal effect,and excellent photostability.Moreover,the self-assembled DT-BT-BIn nanoprobes(NPs)can be effectively internalized by cancer cells in vitro.Under irradiation,DT-BT-BIn NPs are capable of disrupting mitochondrial membrane potential,thereby inducing apoptotic cell death.Furthermore,in vivo investigations demonstrate DT-BT-BIn NPs can effectively accumulate at tumor location,enabling NIR-II fluorescence/photothermal imaging-guided precise tumor ablation,while simultaneously maintaining favorable biosafety toward normal tissues.Collectively,this study underscores the considerable promise of the dual-acceptor strategy in constructing high-performance NIR-II ionic phototheranostic agents and provides a new avenue for clinical precision cancer phototherapy.展开更多
Lakes are emission hotpots of nitrous oxide(N_(2)O),however,this phenomenon remains poorly constrained.Eutrophication is widespread in lakes,yet its contribution to N_(2)O emissions is still not well understood.Here,w...Lakes are emission hotpots of nitrous oxide(N_(2)O),however,this phenomenon remains poorly constrained.Eutrophication is widespread in lakes,yet its contribution to N_(2)O emissions is still not well understood.Here,we investigate the spatiotemporal variations of N_(2)O concentrations,fluxes and indirect emission factors(EF5r)and their drivers in Ulansuhai lake,a shallow eutrophic lake located in a semi-arid region in northern China,during 2019–2020.The mean concentration of N_(2)O in water was 20.0±6.7 nmol/L,with a mean diffusive N_(2)O flux of 16.50±21.52μmol/(m2·day),indicating that this lake acted as a persistent source of atmospheric N_(2)O.Estimated indirect emission factors(EF5r)(mean value 0.0037±0.0060)were significantly higher than the default values(0.0026)used in Intergovernmental Panel on Climate Change(IPCC)emission inventories.The N_(2)O concentrations,fluxes and EF5r exhibited substantial seasonal variations and small spatial variations.N_(2)O concentrations and fluxes were positively correlated with the trophic status and EF5r increased with increasing nutrient concentrations in the water.These findings demonstrate the role of eutrophication in influencing the N_(2)O dynamics and confirm that eutrophication can exacerbate N_(2)O emissions.展开更多
Aggregation-induced emission luminogens(AIEgens)are typically largeπ-conjugated molecules,but their low affinity and noninvasiveness toward analytes limit practical applications.To address this,smaller,more planar AI...Aggregation-induced emission luminogens(AIEgens)are typically largeπ-conjugated molecules,but their low affinity and noninvasiveness toward analytes limit practical applications.To address this,smaller,more planar AIEgens are needed.Stilbene,though structurally suitable,lacks visible luminescence.Here,we report a minimally modified stilbene-based AIEgen-4-dipropylamino-4'-cyano-bridged stilbene(DpCBS[7])-that exhibits fluorescence solvatochromism and efficient AIE across a broad polarity range in the visible region.DpCBS[7]exhibits low quantum yields(Φ_(fl)=0.010.04)in solvents from nonpolar n-hexane to polar dimethyl sulfoxide,with large Stokes shifts,viscosity-sensitive luminescence,and highly efficient solid-state luminescence(Φ_(fl)=0.70).To elucidate its dual solvatochromic and AiE behavior,femtosecond transient absorption spectroscopy was conducted.In solution,DpCBS[7]displays transient absorption with lifetimes of 21 ps(toluene)and 56 ps(acetonitrile)at 293 K,indicating ultrafast nonradiative decay leading to low Φ_(fl).Arrhenius analysis over the temperature range of 263-313 K revealed activation energies(ΔE_(a))of 9.90kJ/mol in toluene and 12.8 kJ/mol in acetonitrile for the S_(1)→S_(0) decay of DpCBS[7].The ΔE_(a) values show no clear systematic dependence on solvent polarity.In contrast,pre-exponential factor A remains consistently high regardless of solvent polarity,indicating that the striking photophysical response is governed primarily by the pre-exponential factor rather than by modulation of the activation energy.These findings highlight the fundamental importance of tailoring the distribution function through structural modification as a robust strategy to control AiE characteristics.展开更多
Atmospheric CO_(2) concentrations are predominantly regulated by multiple emission sources,with industrial emis-sions representing a critical anthropogenic driver that significantly influences temporal and spatial het...Atmospheric CO_(2) concentrations are predominantly regulated by multiple emission sources,with industrial emis-sions representing a critical anthropogenic driver that significantly influences temporal and spatial heterogeneity in regional CO_(2) patterns.This study investigated the spatiotemporal distribution of atmospheric CO_(2) in Pucheng and Nanping industrial parks,Nanping City,by conducting field experiments using two coherent differential absorption lidars from 1 August to 31 October 2024.Results showed that the spatial distributions of CO_(2) emis-sions within a 3 km radius were mapped,and the local diffusion processes were clarified.CO_(2) patterns varied differently in two industrial parks over the three-month period:Average CO_(2) concentrations in non-emission areas were 422.4 ppm in Pucheng and 408.7 ppm in Nanping,with the former experiencing higher and more variable carbon emissions;Correlation analysis indicated that synthetic leather factories in Pucheng contributed more to SO_(2) and NO_(x) levels compared to the chemical plant in Nanping;In Pucheng,CO_(2) concentrations were transported from the north at ground-level wind speeds exceeding 4 m/s,while in Nanping,the concentrations dispersed gradually with increasing wind speeds;Forward trajectory simulations revealed that the peak-emission from Pucheng primarily affected southern Fujian,northeastern Jiangxi,and southern Anhui,while the peak-emission from Nanping influenced central and western Fujian and northeastern Jiangxi.Besides,emissions in both industrial parks were higher on weekdays and lower on weekends,reflecting changes in industrial activi-ties.The study underscores the potential of lidar technology for providing detailed insights into CO_(2) distribution and the interactions between emissions,wind patterns,and carbon transport.展开更多
United Nations(UN)encourages sovereign states to take prompt and concrete measures to accomplish net-zero emissions by year 2050,requesting carbon dioxide removal(CDR)technologies to be prepared and implemented in suc...United Nations(UN)encourages sovereign states to take prompt and concrete measures to accomplish net-zero emissions by year 2050,requesting carbon dioxide removal(CDR)technologies to be prepared and implemented in such ambitious climate action roadmap.However,whether CDR technologies should be further promoted or discontinued post net-zero emission year remains unclear.In this Earth-system modelling research,we compare UN-suggested 2050 net-zero emission scenario against other common climate mitigation scenarios outlined by shared social-economic pathways(SSPs).We also simulate continued CDR implementations after net-zero emissions,which is hypothetically achieved in year 2050 and 2070 respectively,to investigate how CDR can impact the global climate throughout the whole 21st and 22nd centuries.The modelling results find if the 2050 UN net-zero emission goal is accomplished,the global average surface air temperature(SAT)in the end of 21st century is around 1.5℃higher compared to the pre-industrial level,promising an Earth environment more habitable than other scenarios without CDR.When CDR is applied to remove equal amount of anthropogenic CO_(2)emissions since industrial revolution,it restores the global average SAT close to pre-industrial level of 13.5℃.However,CDR-induced global carbon distribution within ocean,atmosphere,and land pools is different from the pre-industrial condition,causing reduced atmospheric CO_(2)concentration by 9 to 38 ppm compared to the pre-industrial cases,and more alkalinized ocean surface with pH increase of 0.004 to 0.024.This study affirms CDR cannot be viewed as a reversed process to anthropogenic CO_(2)emissions,accordingly climate policies to overcome the uncertainties after for late 21st century still require careful trade-offs for the decarbonation and the cost-benefits of CDR measures.展开更多
基金supported by the National Natural Science Foundation of China (42505149,41925023,U2342223,42105069,and 91744208)the China Postdoctoral Science Foundation (2025M770303)+1 种基金the Fundamental Research Funds for the Central Universities (14380230)the Jiangsu Funding Program for Excellent Postdoctoral Talent,and Jiangsu Collaborative Innovation Center of Climate Change。
文摘Countries around the world have been making efforts to reduce pollutant emissions. However, the response of global black carbon(BC) aging to emission changes remains unclear. Using the Community Atmosphere Model version 6 with a machine-learning-integrated four-mode version of the Modal Aerosol Module, we quantify global BC aging responses to emission reductions for 2011–2018 and for 2050 and 2100 under carbon neutrality. During 2011–18, global trends in BC aging degree(mass ratio of coatings to BC, R_(BC)) exhibited marked regional disparities, with a significant increase in China(5.4% yr^(-1)), which contrasts with minimal changes in the USA, Europe, and India. The divergence is attributed to opposing trends in secondary organic aerosol(SOA) and sulfate coatings, driven by regional changes in the emission ratios of corresponding coating precursors to BC(volatile organic compounds-VOCs/BC and SO_(2)/BC). Projections under carbon neutrality reveal that R_(BC) will increase globally by 47%(118%) in 2050(2100), with strong convergent increases expected across major source regions. The R_(BC) increase, primarily driven by enhanced SOA coatings due to sharper BC reductions relative to VOCs, will enhance the global BC mass absorption cross-section(MAC) by 11%(17%) in 2050(2100).Consequently, although the global BC burden will decline sharply by 60%(76%), the enhanced MAC partially offsets the magnitude of the decline in the BC direct radiative effect, resulting in the moderation of global BC DRE decreases to 88%(92%) of the BC burden reductions in 2050(2100). This study highlights the globally enhanced BC aging and light absorption capacity under carbon neutrality, thereby partly offsetting the impact of BC direct emission reductions on future changes in BC radiative effects globally.
基金funded by the General Program of the National Natural Science Foundation of China[Grant No.42171300]the Strategic Research Program of the National Natural Science Foundation of China[Grant No.42542001]+1 种基金Post-funded Project of National Social Science Fund of China[Grant No.25FJYB015]Special Project of Strategic Research and Decision Support System of the Chinese Academy of Sciences[Grant No.GHJ-ZLZX-2025-48].
文摘Greenhouse gas(GHG)emissions from China’s food system are a major environmental concern;however,studies quantifying their drivers and future projections remain limited.This study uses structural decomposition analysis and growth curve models to assess food-related GHG trends from 1961 to 2020,identify key drivers and their contributions,and project emissions for 2050 under six economic and population scenarios.It also proposes reduction pathways to help China achieve its 2060 carbon neutrality goal.Animal and plant foods are categorized into 14 groups based on the similarity of their emission coefficients.China’s total food related GHG emissions rose tenfold,from 351.7 to 3719.8 million tons CO_(2)-equivalent(CO_(2)e)/year,between 1961 and 2020.Per-capita emissions increased from 532.1 to 2584.4 kg CO_(2)e/year.Emissions from plant based foods grew from 435.0 to 824.6 kg CO_(2)e/year,while animal-based emissions surged from 97.1 to 1759.8 kg CO_(2)e/year,with animal products contributing more owing to their higher emission coefficients.Key drivers include rising food intake,increasing demand for animal-based foods(especially red meat),and population growth.Scenario analyses predict that emissions will peak at 3826.2 million tons CO_(2)e/year in 2031(low economy-low population)and 3971.0 million tons CO_(2)e/year in 2039(high economy-medium population).Compared with Australian,Indian,and Japanese diets,Chinese diets exhibit lower per-capita emissions than Australia and India but have higher emissions than in Japan.Adhering to China’s national dietary guidelines could reduce Chinese per-capita food-related GHGs by 31.5%,and optimized diets could lower them by 45.3%.This study provides valuable insights for Chinese policymakers to reduce food-related GHG emissions,refine national dietary guidelines,and raise public awareness regarding the food system’s environmental impact,thus encouraging people to follow sustainable diets.
文摘An integral part of the effort to reduce greenhouse gas emissions is carbon footprint accounting.EPA categorizes facility carbon footprints in three scopes.Scope-2 emissions include electricity,heat or steam purchased from a utility provider.This paper evaluates the existing calculation methods for scope-2 CO2 emissions for purchased electricity.The electricity grid in US is complex and is divided spatially into states,eGRID regions,balancing authorities(BAs),and utilities.Up to hourly temporal granularity can be obtained from available datasets.A matrix is developed that categorizes different datasets based on the complexity to calculate the carbon emission factors.Spatial and temporal variations are evaluated.There are significant spatial overlap between regions in different categories and emission factors within a region show sub-regional variation.An area analysis is done using zip-code polygons to determine whether a state or balancing authority is smaller for all the overlapping cases.Temporal variations in emission factors are significant depending on the balancing authority considered.A single method to calculate scope-2 emission factors may not be accurate and efficient in every case and a nuanced assessment of emission factors is warranted.An implementation pathway for a“smart carbon calculator”—one that gives accurate carbon footprint that is the spatially and temporally most granular is suggested.
基金supported by the Key Research and Development Program of Gansu Province(22YF7FA070)the National Natural Science Foundation of China(22406076,22466026)the Basic Research Project of Yunnan Province(202301BE070001-017,202401CF070139,202401AS070085)。
文摘Iron and steel industry is one of the main sources of air pollution emissions in China.The sintering process is an important link in the blast furnace ironmaking process,but it is also accompanied by a large number of pollutants.Under the background of ultra-low emissions,iron and steel enterprises urgently need to upgrade their existing processes to address the existing process in practical application problems.In this study,a steel group in Gansu Province was taken as an example.By comparing and analyzing the pollutant emission characteristics before and after the ultra-low emission retrofit,the collaborative control effect of the combined process on SO_(2),NO_(x),particulate matter,and dioxins after the new retrofit was systematically evaluated.The results show that after the retrofit,the concentrations of particulate matter,SO_(2) and NO_(x) have dropped to near-zero levels,and the dioxin removal efficiency has reached 98.87%,with all indicators being better than the national ultra-low emission standards.The study confirms that the optimal combination of multi-pollutant collaborative treatment technologies is the key to achieving efficient emission reduction,among which selective catalytic reduction technology has a particularly significant synergistic removal effect on NO_(x) and dioxins.This study provides an important technical reference and practical basis for the ultra-low emission retrofit of the steel industry,and has important guiding significance for promoting the green retrofit of the industry.Its ultra-low emission retrofit is of great significance for achieving green and low-carbon development.
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 National Social Science Fund of China under Grant 25CJL064.
文摘The carbon emission trading policy is a key policy for China to achieve its dual carbon goals.This paper aims to examine the emission-reduction effects,transmission mechanisms,and carbon-market efficiency of China’s carbon-emission trading policy from 2012 to 2023.We adopt the difference-in-differences(DID)model to analyze the effects of policy on emissions,and the empirical results from the DID model confirm that the pilot carbon emission trading policy has significantly reduced carbon emission intensity in pilot areas.Then we use the mediation model to study the transmission mechanism of the pilot carbon emission trading policy,and the mediation analysis demonstrates that the pilot carbon emission trading policy achieves emission abatement through four parallel transmission channels:scientific innovation,energy conservation,clean energy substitution,and industrial structure upgrading.Data envelopment analysis evaluates the carbon market efficiency of China.The result shows that the average carbon market efficiency of pilot areas has improved steadily,particularly from 2012 to 2023,especially in Beijing,Hubei,and Guangdong.Moreover,the efficiency of the national carbon market has shown an upward trend since its 2021 launch;it remains lower than the pilot average,constrained primarily by limited sectoral coverage,which impacts scale efficiency.
基金supported by the National Natural Science Foundation of China(No.22431004)Fund of Guangdong Provincial Key Laboratory of Luminescence from Molecular Aggregates(No.2023B1212060003)。
文摘Aggregation-induced emission(AIE)polymers have been extensively studied;however,the integration of AIE units into polyelectrolytes remains largely limited by the laborious multistep synthesis of pre-designed emissive monomers.Herein,we report a one-pot multicomponent polymerization method that directly produces main-chain charged polyelectrolytes with intrinsic AIE characteristics from non-emissive building blocks.By optimizing the monomer structures and reaction conditions,a series of soluble high-molecular-weight polymers with welldefined backbones were obtained in high yields.The resulting polyelectrolytes displayed robust AIE behavior,exhibiting fluorescence enhancement up to about 60-fold in an aqueous environment,and maintained excellent thermal stability.Owing to their cationic backbones,these polymers interact strongly with microbial surfaces and exhibit remarkable antimicrobial activities.This study establishes a synthetically efficient route to AIE polyelectrolytes and highlights their potential applications as multifunctional materials for bioimaging,antimicrobial therapy,and other applications.
基金supported by the Key R&D Program of Hubei Province(2023BAB002)the Science and technology project of State Grid Hubei Electric Power Co.,Ltd.(52153223000A)。
文摘Under the“dual carbon”goals,it is imperative to incorporate carbon emissions-related factors into research of power grid risk assessment to meet the green transformation needs of the power grid.Therefore,this paper conducts a study on the risk assessment of carbon emissions changes in regional power grids based on dynamic carbon emission factors,aiming to quantitatively analyze the impact of random disturbances such as equipment failures or fluctuations in renewable energy generation on the carbon emission intensity of regional power grids.First,carbon emission change risk indicators are constructed from three dimensions:the probability,frequency,and magnitude of carbon emission changes.Second,a dynamic carbon emission factor calculation model is proposed to reflect the spatiotemporal change of carbon emissions in the regional power grid,considering output of different types of generators and the components of inter-area power transmission.Finally,with the premise of ensuring safe and stable operation of power grid,a quantitative assessment model for carbon emission change risks is proposed under the objective of minimizing the electricity loss.The sampling convergence conditions of the model are also derived.The results from the MRTS79 case study demonstrate the proposed method can effectively quantify and analyze the risk of carbon emissions changes in regional power grids,validating the effectiveness of the proposed model.
基金supported by the Science and Technology Project of China Southern Power Grid Co.,Ltd.(ZBKTM20232244)the Project of National Natural of Science Foundation of China(52477103).
文摘The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide electricity users in carbon reduction and promote power industry low-carbon transformation.Fundamentally,calculating indirect carbon emissions involves allocating direct carbon emission data from the power source side,indicating that accurate indirect emission results rely on the precise measurement of power source emissions.However,existing research on indirect carbon emissions in large-scale power systems rarely accounts for variations in carbon emission characteristics under different operating conditions of power sources,such as rated/non-rated operating conditions and ramping up/down conditions,making it difficult to reflect source-side and load-side carbon emission information variation during providing ancillary services.Quadratic and exponential functions are proposed to characterize the energy consumption profiles of coal-fired and gas-fired power generation,respectively,to construct a refined carbon emission model for power sources.By leveraging the theory of power system carbon flow,we analyze how variable operating conditions of power sources impact indirect carbon emissions.Case studies demonstrate that changes in power source emissions under variable conditions have a significant effect on the indirect carbon emissions of power grids.
基金Project supported by the National Key Research and Development Program(2022YFE0108800)。
文摘Eu^(2+)-doped phosphors show broadband absorption,tunable emission and high quantum efficiency due to the parity-allowed 5d→4f transitions,allowing them to be used in solid-state lighting.To expand their applications in other fields such as detection and sensing technologies,the Eu^(2+)emission needs to be tuned into the near-infrared region,but it is a big challenge to obtain Eu^(2+)near-infrared region emitters due to the absence of host compounds with extremely large crystal-field splitting.In this work,we chose M_(4)Li(BN_(2))_(3)(M=Ca,Sr,Ba)as a host and realize the near-infrared region emission of Eu^(2+)in it.Among these phosphors,Ba4Li(BN_(2))_(3):Eu^(2+)exhibits the longest emission of 880 nm and the largest full-width at half maximum of 276 nm under 450 nm excitation,while Ca_(4)Li(BN_(2))_(3):Eu^(2+)and Sr_(4)Li(BN_(2))_(3):Eu^(2+)emit at740 and 680 nm,respectively.We observe an interesting phenomenon that the energy shift of emission is linearly related to the radius difference between the alkaline earth cation and the activator Eu^(2+)in this system.
基金The National Natural Science Foundation of China(No.52470211)Special Foundation of Jiangsu Province Science and Technology Plan(No.BZ2024017)RECLAIM Network Plus Project(No.EP/W034034/1).
文摘Reducing carbon emissions is fundamental to achieving carbon neutrality.Existing studies have typically estimated emissions by predicting fossil fuel consumption across sectors under different socioeconomic scenarios;however,uncertainties in future development often lead to deviations from these assumptions.To address this limitation,this study proposes a data-driven approach for evaluating national carbon emissions using historical data.Countries with similar energy consumption patterns were selected as reference samples,and their emission pathways were analyzed to predict future emissions for countries that have not yet reached their peak.Key indicators,including peak levels,timing,plateau duration,and post-peak decline rates,were identified.The results indicate that the trends in unpeaked economies can be effectively assessed based on the emission patterns of countries with comparable energy structures.Applying this framework to China suggests a carbon peak between 2027 and 2030,in the range of 14.207 to 16.234 Gt,followed by a gradual decline from 2031 to 2036.Compared with the average results of the existing studies,the predicted minimum and maximum emissions show error margins of 10.1% and 1.41%,respectively.This study proposes a top-down methodology that provides a transparent,reproducible,and empirical framework for forecasting carbon emission pathways,thereby offering a scientific basis for assessing countries that have not yet reached their emissions peak.
文摘Thermal power plants are the main contributors to greenhouse gas emissions.The prediction of the emission supports the decision makers and environmental sustainability.The objective of this study is to enhance the accuracy of emission prediction models,supporting more effective real-time monitoring and enabling informed operational decisions that align with environmental compliance efforts.This paper presents a data-driven approach for the accurate prediction of gas emissions,specifically nitrogen oxides(NOx)and carbon monoxide(CO),in natural gas power plants using an optimized hybrid machine learning framework.The proposed model integrates a Feedforward Neural Network(FFNN)trained using Particle Swarm Optimization to capture the nonlinear emission dynamics under varying gas turbine operating conditions.To further enhance predictive performance,the K-Nearest Neighbor(K-NN)algorithm serves as a post-processing method to enhance IPSO-FFNN predictions through adjustment and refinement,improving overall prediction accuracy,while Neighbor Component Analysis is used to identify and rank the most influential operational variables.The study makes a significant contribution through the combination of NCA feature selection with PSO global optimization,FFNN nonlinear modelling,and K-NN error correction into one unified system,which delivers precise emission predictions.The model was developed and tested using a real-world dataset collected from gas-fired turbine operations,with validated results demonstrating robust accuracy,achieving Root Mean Square Error values of 0.355 for CO and 0.368 for NOx.When benchmarked against conventional models such as standard FFNN,Support Vector Regression,and Long Short-Term Memory networks,the hybrid model achieved substantial improvements,up to 97.8%in Mean Squared Error,95%in Mean Absolute Error(MAE),and 85.19%in RMSE for CO;and 97.16%in MSE,93.4%in MAE,and 83.15%in RMSE for NOx.These results underscore the model’s potential for improving emission prediction,thereby supporting enhanced operational efficiency and adherence to environmental standards.
基金supported by the Key Research and Development Plan Project of Heilongjiang Province (2022ZX02C13)。
文摘Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio active compounds) remain poorly understood,limiting their therapeutic application.This study provides the first comprehensive characterization of spatiotemporal dynamics in airborne phytoncides and their synergistic interactions with environmental factors throughout the autumn-early spring seasonal transition in a temperate forest ecosystem.We analyzed the compositional dynamics of phytoncides and terpenoid content variations using thermal desorption-gas chromatography-mass spectrometry(TD-GC-MS) from September 2024 to March 2025.This period encompassed seasonal transitions from autumn to early spring,including diurnal variations in September and snowfall events in November.The method demonstrated detection limits(LODs) ranging from 1.35 to 5.33 ng m-3 and quantification limits(LOQs) from 4.09 to 16.15 ng m-3.Our results revealed pronounced seasonal fluctuations in phytoncide composition.In September,terpenoids,esters,alcohols,and alkanes displayed a diurnal "decrease-increase" trend,whereas aldehydes and ketones peaked at midday.Notably,esters and alcohols were undetectable in November and January.By January,terpenoids reached their lowest proportion(0.17±0.02%) at noon.Five terpenoids(α-pinene,myrcene,D-limonene,camphene,p-cymene) were detected in September,four(α-pinene,D-limonene,camphene,p-cymene) in November,two(D-limonene,p-cymene) in January,and only p-cymene in March.The total concentration and emission rate of the five terpenoids peaked in September afternoons at 1961.58±106.67 ng m^(-3) and653.86±35.56 ng m^(-3) h^(-1),respectively.Nocturnal emissions(32131.95±2522.21 ng m^(-3)) significantly surpassed daytime levels(14473.04±958.49 ng m^(-3)),with emission rates escalating from 1447.30±95.85 ng m^(-3) h^(-1)(day) to 5355.33±420.37 ng m^(-3) h^(-1)(night),marking a3.7-fold increase.Snowfall dramatically elevated terpenoid concentrations(pre-snowfall:158.58±14.12 ng m^(-3);post-snowfall:1080.57±57.76 ng m^(-3)) and emission rates(pre-snowfall:52.86±4.71 ng m^(-3) h^(-1);post-snowfall:360.19±19.25 ng m^(-3) h^(-1)),reflecting a 6.8-fold surge.This study underscores the profound influence of light intensity,seasonal shifts,and climatic conditions on airborne phytoncide levels,offering a scientific foundation for optimizing forest therapy and ecotourism strategies.
基金supported by the National Natural Science Foundation of China(No.42225103).
文摘Lakes are carbon dioxide(CO_(2))and methane(CH_(4))emission hotspots,whose associated flux is spatially vari-able.Many studies have investigated the impact of microorganisms and environmental factors on CO_(2) and CH_(4) emissions between different lakes.However,the carbon emissions and their influencing factors of different areas within a single lake remain poorly understood.Accordingly,this study investigates CO_(2) and CH_(4) emission hetero-geneity in a large floodplain lake system and distribution characteristics of associated functional microorganisms.Findings show that mean CO_(2) and CH_(4) flux values in the sub lake area were 62.03±24.21 mg/(m2·day)and 5.97±3.2μg/(m2·day),which were greater by factors of 1.78 and 2.96 compared to the water channel and the main lake area,respectively.The alpha diversity of methanogens in the sub lake area was lower than that in the main lake and water channel areas.The abundance of methanogens in bottom water layer was higher compared with the middle and surface layers.Conversely,the abundance of methane(CH_(4))-oxidizing bacteria in the surface layer was higher than that in the bottom layer.Additionally,the composition of methanogen and CH_(4)-oxidizing bacterial community,chlorophyll a(Chl-a),pH,total phosphorus(TP)and dissolved organic carbon(DOC)con-tent constituted the dominate driving factors affecting lake C emissions.Results from this study can be used to improve our understanding of lake spatial heterogeneous of CO_(2) and CH_(4) emission and the driving mechanisms within floodplain lakes under the coupling effects of functional C microorganisms and environmental factors.
基金Open Fund of State Key Laboratory of Coal Mine Disaster Dynamics and Control,Grant/Award Number:2011DA105287-FW202306Postgraduate Research&Practice Innovation Program of Jiangsu Province,Grant/Award Number:KYCX24_2925+4 种基金Fundamental Research Program of Xuzhou,Grant/Award Number:KC23017National Natural Science Foundation of China,Grant/Award Number:52104234Fundamental Research Funds for the Central Universities,Grant/Award Number:2024-10962National Science Foundation for Young Scientists of Jiangsu Province,Grant/Award Number:BK20200657Graduate Innovation Program of China University of Mining and Technology,Grant/Award Number:2024WLKXJ152。
文摘In coal mines,dynamic disasters such as rock bursts seriously threaten the safety of mining activities.Exploring the dynamic behaviors and disaster characteristics in the impact failure process of coal serves as the basis and prerequisite for monitoring and warning rock bursts.In this context,impact failure tests of coal were carried out under different axial static loads and impact velocities to analyze the dynamic behaviors and acoustic emission(AE)response characteristics of coal.The results show that the dynamic behaviors of coal under combined dynamic and static loads are significantly different from those under static loads,and the stress-strain curve displays double peaks without an obvious compaction stage.As the axial static load grows,the dynamic strength and peak strain both have a quadratic function with the axial static load.When the coal damage intensifies instantaneously,the AE count and energy parameters both witness pulse-like increases and reach their peak values.The damage effect of axial static loads on coal,though limited,has an extreme point.In contrast,the impact velocity can strengthen the response of AE signals and has linear function relationships with the peak values of AE count and energy.This plays a leading role in the damage to samples and sets a critical point for coal failure and fracture.Compared with the analysis results of stress and strain,the responses of AE signals are more accurate and reliable.Based on AE response characteristics,the damage evolution process of coal under the combined dynamic and static loads can be identified more accurately to reveal the moment corresponding to coal damage and the characteristics of coal failure.The research results are conducive to the further application of AE monitoring methods to early warning of rock burst disasters in coal mining sites.
基金supported by the National Natural Science Foundation of China(82572410,22405063,32300048,22307080)Guangdong Basic and Applied Basic Research Foundation(2023A1515110122,2024A1515010677,2024A1515012842,2024A1515012577)+3 种基金Characteristic Innovation Project of Guangdong Province General University(2024KTSCX166,2024KTSCX168)State Key Laboratory of Pathogenesis,Prevention and Treatment of High Incidence Diseases in Central Asia Fund(SKL-HIDCA-2024-GJ3)Clinical and Basic Science&Technology Innovation Special Project of Guangdong Medical University(GDMULCJC2024161,GDMULCJC2024120)Guangdong Medical University Undergraduate Innovation and Entrepreneurship Education Base Project(JDXM2024042).
文摘Ionic phototheranostic agents have found extensive application in preclinical and clinical practice owing to their excellent biocompatibility and synergistic diagnostic-therapeutic integration.However,they still suffer from certain limitations,such as short absorption/emission wavelengths,poor photostability,aggregation-caused fluorescence self-quenching,and diminished phototherapeutic efficacy upon aggregation,which collectively hinder their efficacy in complex clinical scenarios.To address these challenges,a second near-infrared(NIR-II)ionic phototheranostic agent,namely DT-BT-BIn,is rationally designed and synthesized via an innovative dual-acceptor engineering strategy.DT-BT-BIn ingeniously integrates benzothiadiazole and benzo[c,d]indolium as dual-acceptor units,which successfully achieves superior aggregation-induced NIR-II emission characteristics,highly efficient Type Ⅰ/Ⅱ photodynamic activity coupled with photothermal effect,and excellent photostability.Moreover,the self-assembled DT-BT-BIn nanoprobes(NPs)can be effectively internalized by cancer cells in vitro.Under irradiation,DT-BT-BIn NPs are capable of disrupting mitochondrial membrane potential,thereby inducing apoptotic cell death.Furthermore,in vivo investigations demonstrate DT-BT-BIn NPs can effectively accumulate at tumor location,enabling NIR-II fluorescence/photothermal imaging-guided precise tumor ablation,while simultaneously maintaining favorable biosafety toward normal tissues.Collectively,this study underscores the considerable promise of the dual-acceptor strategy in constructing high-performance NIR-II ionic phototheranostic agents and provides a new avenue for clinical precision cancer phototherapy.
基金supported by the National Natural Science Foundation of China(No.52279067)the National Key R&D Program of China(No.2021YFC3201203)+1 种基金the Project of Key Laboratory of River and Lake in Inner Mongolia Autonomous Region(No.2022QZBZ0003)the Research Foundation for Young Scholars of Inner Mongolia University(No.10000-23112101/333).
文摘Lakes are emission hotpots of nitrous oxide(N_(2)O),however,this phenomenon remains poorly constrained.Eutrophication is widespread in lakes,yet its contribution to N_(2)O emissions is still not well understood.Here,we investigate the spatiotemporal variations of N_(2)O concentrations,fluxes and indirect emission factors(EF5r)and their drivers in Ulansuhai lake,a shallow eutrophic lake located in a semi-arid region in northern China,during 2019–2020.The mean concentration of N_(2)O in water was 20.0±6.7 nmol/L,with a mean diffusive N_(2)O flux of 16.50±21.52μmol/(m2·day),indicating that this lake acted as a persistent source of atmospheric N_(2)O.Estimated indirect emission factors(EF5r)(mean value 0.0037±0.0060)were significantly higher than the default values(0.0026)used in Intergovernmental Panel on Climate Change(IPCC)emission inventories.The N_(2)O concentrations,fluxes and EF5r exhibited substantial seasonal variations and small spatial variations.N_(2)O concentrations and fluxes were positively correlated with the trophic status and EF5r increased with increasing nutrient concentrations in the water.These findings demonstrate the role of eutrophication in influencing the N_(2)O dynamics and confirm that eutrophication can exacerbate N_(2)O emissions.
基金supported in part by MEXT/JSPS KAK-ENHI grants 23H02036(G.K.)JP23H04631,JP23K26670,JP23H03833,JP24K01471,JP24K01515(K.M.)+8 种基金JP23K01977,JP23K20039,JP25K01678(K.O.)24K08341(S.S.)Toyota Riken Scholar(K.M.)the Yoshida Aca-demic and Educational Promotion Foundation(K.M.)the Environment Research and Technology Development Fund(grant number 3RA-2502)of the Environmental Restoration and Conservation Agency provided by Ministry of the Environment of Japan(K.M.)Kyushu University Platform of Inter-/Transdisciplinary Energy Research(Q-PIT)Module-Research Program(K.M.)Kyushu University Integrated Initiative for Designing Future Society(K.M.)JST SPRING,Grant Number JPMJSP2180(T.T.)Network Joint Research Center for Materials and Devices(20253036)(K.I.)The Creative Research Encouragement Award,School of Materials and Chemical Technology,Institute of Science Tokyo(G.K.)。
文摘Aggregation-induced emission luminogens(AIEgens)are typically largeπ-conjugated molecules,but their low affinity and noninvasiveness toward analytes limit practical applications.To address this,smaller,more planar AIEgens are needed.Stilbene,though structurally suitable,lacks visible luminescence.Here,we report a minimally modified stilbene-based AIEgen-4-dipropylamino-4'-cyano-bridged stilbene(DpCBS[7])-that exhibits fluorescence solvatochromism and efficient AIE across a broad polarity range in the visible region.DpCBS[7]exhibits low quantum yields(Φ_(fl)=0.010.04)in solvents from nonpolar n-hexane to polar dimethyl sulfoxide,with large Stokes shifts,viscosity-sensitive luminescence,and highly efficient solid-state luminescence(Φ_(fl)=0.70).To elucidate its dual solvatochromic and AiE behavior,femtosecond transient absorption spectroscopy was conducted.In solution,DpCBS[7]displays transient absorption with lifetimes of 21 ps(toluene)and 56 ps(acetonitrile)at 293 K,indicating ultrafast nonradiative decay leading to low Φ_(fl).Arrhenius analysis over the temperature range of 263-313 K revealed activation energies(ΔE_(a))of 9.90kJ/mol in toluene and 12.8 kJ/mol in acetonitrile for the S_(1)→S_(0) decay of DpCBS[7].The ΔE_(a) values show no clear systematic dependence on solvent polarity.In contrast,pre-exponential factor A remains consistently high regardless of solvent polarity,indicating that the striking photophysical response is governed primarily by the pre-exponential factor rather than by modulation of the activation energy.These findings highlight the fundamental importance of tailoring the distribution function through structural modification as a robust strategy to control AiE characteristics.
基金supported by the National Natural Science Foundation of China(Nos.42305147 and 42405138)the Natural Science Foundation of Jiangsu Province(No.BK20230428).
文摘Atmospheric CO_(2) concentrations are predominantly regulated by multiple emission sources,with industrial emis-sions representing a critical anthropogenic driver that significantly influences temporal and spatial heterogeneity in regional CO_(2) patterns.This study investigated the spatiotemporal distribution of atmospheric CO_(2) in Pucheng and Nanping industrial parks,Nanping City,by conducting field experiments using two coherent differential absorption lidars from 1 August to 31 October 2024.Results showed that the spatial distributions of CO_(2) emis-sions within a 3 km radius were mapped,and the local diffusion processes were clarified.CO_(2) patterns varied differently in two industrial parks over the three-month period:Average CO_(2) concentrations in non-emission areas were 422.4 ppm in Pucheng and 408.7 ppm in Nanping,with the former experiencing higher and more variable carbon emissions;Correlation analysis indicated that synthetic leather factories in Pucheng contributed more to SO_(2) and NO_(x) levels compared to the chemical plant in Nanping;In Pucheng,CO_(2) concentrations were transported from the north at ground-level wind speeds exceeding 4 m/s,while in Nanping,the concentrations dispersed gradually with increasing wind speeds;Forward trajectory simulations revealed that the peak-emission from Pucheng primarily affected southern Fujian,northeastern Jiangxi,and southern Anhui,while the peak-emission from Nanping influenced central and western Fujian and northeastern Jiangxi.Besides,emissions in both industrial parks were higher on weekdays and lower on weekends,reflecting changes in industrial activi-ties.The study underscores the potential of lidar technology for providing detailed insights into CO_(2) distribution and the interactions between emissions,wind patterns,and carbon transport.
基金supported by the Fundamental Research Funds for the Central Universities(No.202242001)the Mount Tai Research Grant。
文摘United Nations(UN)encourages sovereign states to take prompt and concrete measures to accomplish net-zero emissions by year 2050,requesting carbon dioxide removal(CDR)technologies to be prepared and implemented in such ambitious climate action roadmap.However,whether CDR technologies should be further promoted or discontinued post net-zero emission year remains unclear.In this Earth-system modelling research,we compare UN-suggested 2050 net-zero emission scenario against other common climate mitigation scenarios outlined by shared social-economic pathways(SSPs).We also simulate continued CDR implementations after net-zero emissions,which is hypothetically achieved in year 2050 and 2070 respectively,to investigate how CDR can impact the global climate throughout the whole 21st and 22nd centuries.The modelling results find if the 2050 UN net-zero emission goal is accomplished,the global average surface air temperature(SAT)in the end of 21st century is around 1.5℃higher compared to the pre-industrial level,promising an Earth environment more habitable than other scenarios without CDR.When CDR is applied to remove equal amount of anthropogenic CO_(2)emissions since industrial revolution,it restores the global average SAT close to pre-industrial level of 13.5℃.However,CDR-induced global carbon distribution within ocean,atmosphere,and land pools is different from the pre-industrial condition,causing reduced atmospheric CO_(2)concentration by 9 to 38 ppm compared to the pre-industrial cases,and more alkalinized ocean surface with pH increase of 0.004 to 0.024.This study affirms CDR cannot be viewed as a reversed process to anthropogenic CO_(2)emissions,accordingly climate policies to overcome the uncertainties after for late 21st century still require careful trade-offs for the decarbonation and the cost-benefits of CDR measures.
