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
An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement syst...An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system （PEMS） under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics （speed and acceleration） of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data.展开更多
A total of 14 in-use diesel buses were selected to conduct emission measurement using a portable emissions measurement system （PEMS） in Beijing. Their instantaneous gaseous emission rates, particular matter （PM） e...A total of 14 in-use diesel buses were selected to conduct emission measurement using a portable emissions measurement system （PEMS） in Beijing. Their instantaneous gaseous emission rates, particular matter （PM） emission rates and driving parameters were obtained. The influences of speed, acceleration and vehicle specific power （VSP） on emissions were analyzed. Based on the relationships between these driving parameters and emissions, 24 driving bins defined by speed, ac- celeration and VSP were constructed with cluster analysis to group emission rates for Euro Ⅲ and IV buses, respectively. Then the emissions reductions from Euro Ⅲ to Euro Ⅳ diesel buses were ana- lyzed. Lastly, on-road hot-stabilized emission rate model for diesel buses in Beijing was developed. Through the comparison of the model simulation emission rates with the measured emission rates, the modeled emission results were in good agreement with the measured emission results. In most of the cases, the differences were less than 12 %.展开更多
The choices of the parameterizations for each component in a microwave emission model have significant effects on the quality of brightness temperature （Tb） sim- ulation. How to reduce the uncertainty in the Tb simu...The choices of the parameterizations for each component in a microwave emission model have significant effects on the quality of brightness temperature （Tb） sim- ulation. How to reduce the uncertainty in the Tb simulation is investigated by adopting a statistical post-processing procedure with the Bayesian model averaging （BMA） ensemble approach. The simulations by the community microwave emission model （CMEM） cou- pled with the community land model version 4.5 （CLM4.5） over China's Mainland are con- ducted by the 24 configurations from four vegetation opacity parameterizations （VOPs）, three soil dielectric constant parameterizations （SDCPs）, and two soil roughness param- eterizations （SRPs）. Compared with the simple arithmetical averaging （SAA） method, the BMA reconstructions have a higher spatial correlation coefficient （larger than 0.99） than the C-band satellite observations of the advanced microwave scanning radiometer on the Earth observing system （AMSR-E） at the vertical polarization. Moreover, the BMA product performs the best among the ensemble members for all vegetation classes, with a mean root-mean-square difference （RMSD） of 4 K and a temporal correlation coefficient of 0.64.展开更多
The Community Microwave Emission Model (CMEM) developed by the European Centre for Me-dium-Range Weather Forecasts (ECMWF) can provide a link between surface states and satellite observations and simulate the passive ...The Community Microwave Emission Model (CMEM) developed by the European Centre for Me-dium-Range Weather Forecasts (ECMWF) can provide a link between surface states and satellite observations and simulate the passive microwave brightness temperature of the surface at low frequencies (from 1 GHz to 20 GHz).This study evaluated the performance of the CMEM cou-pled with the Community Land Model (CLM) (CMEM-CLM) using C-band (6.9 GHz) microwave brightness temperatures from the Advanced Microwave Scanning Radiometer on Earth Observing System (AMSR-E) over East Asia.Preliminary results support the argument that the simulated brightness temperatures of CMEM-CLM from July 2005 to June 2010 are comparable to AMSR-E observational data.CMEM-CLM performed better for vertical polarization,for which the root mean square error was approximately 15 K,compared to over 30 K for horizontal polarization.An evaluation performed over seven sub-regions in China indicated that CMEM-CLM was able to capture the temporal evolution of C-band brightness temperatures well,and the best correlation with AMSR-E appeared over western Northwest China (over 0.9 for vertical polarization).However,larger biases were found over southern North China and the middle and lower reaches of the Yangtze River.展开更多
China＇s energy supply-and-demand model and two related carbon emission scenarios, including a planned peak scenario and an advanced peak scenario, are designed taking into consideration China＇s economic development,...China＇s energy supply-and-demand model and two related carbon emission scenarios, including a planned peak scenario and an advanced peak scenario, are designed taking into consideration China＇s economic development, technological progress, policies, resources, environmental capacity, and other factors. The analysis of the defined scenarios provides the following conclusions： Primary energy and power demand will continue to grow leading up to 2030, and the growth rate of power demand will be much higher than that of primary energy demand. Moreover, low carbonization will be a basic feature of energy supply-and-demand structural changes, and non-fossil energy will replace oil as the second largest energy source. Finally, energy- related carbon emissions could peak in 2025 through the application of more efficient energy consumption patterns and more low-carbon energy supply modes. The push toward decarbonization of the power industry is essential for reducing the peak value of carbon emissions.展开更多
The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the ...The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the behavior in plasma.In this paper,a glass vacuum chamber and a pair of plate electrodes were designed and fabricated,using 13.56 MHz radio frequency（RF）discharge technology to ionize the working gas of Ar.This discharge was mathematically described with equivalent circuit model.The discharge voltage and current of the plasma were measured atdifferent pressures and different powers.Based on the capacitively coupled homogeneous discharge model,the equivalent circuit and the analytical formula were established.The plasma density and temperature were calculated by using the equivalent impedance principle and energy balance equation.The experimental results show that when RF discharge power is 50–300 W and pressure is 25–250 Pa,the average electron temperature is about 1.7–2.1 e V and the average electron density is about 0.5？×10^17–3.6？×10^17m^-3.Agreement was found when the results were compared to those given by optical emission spectroscopy and COMSOL simulation.展开更多
Based on the logical causal relationship and taking Liaoning Province, China, which is the Chinese traditional industrial base and is in the stage of accelerated urbanisation, as a case study, this study builds the ＇...Based on the logical causal relationship and taking Liaoning Province, China, which is the Chinese traditional industrial base and is in the stage of accelerated urbanisation, as a case study, this study builds the ＇Urbanisation-Energy Consumption-COn Emissions System Dynamics （UEC-SD）＇ model using a system dynamics method. The UEC-SD model is applied to analyse the effect of the ar- banisation process on the regional energy structure and CO2 emissions, followed by simulation of future production and living energy consumption structure as well as the evolutionary trend of CO2 emissions of three urbanisation scenarios （low speed, intermediate speed and high speed） under the assumed boundary conditions in urban and rural areas of Liaoning Province, China. The results show that the urbanisation process can alter production and the living energy consumption structure and thereby change regional CO2 emissions. An increase in the urbanisation rate in case area will lead to regional COz emissions rising in the short term, but when the urbanisation rate approaches 80%, CO2 emissions will reach a peak value and then decrease. Comparison of different urbanisation rates showed that pro- duction and living energy consumption exhibit different directions of change and rules in urban and rural areas. The effect of urbanisa- tion on CO2 emissions and energy structure is not direct, and urbanisation can increase the differences in energy and CO2 emissions between urban and rural areas caused by the industrial structure, technical level and other factors.展开更多
A one-dimensional（1D） fluid model of capacitive RF argon glow discharges between two parallel-plate electrodes at low pressure is employed. The influence of the secondary electron emission on the plasma characterist...A one-dimensional（1D） fluid model of capacitive RF argon glow discharges between two parallel-plate electrodes at low pressure is employed. The influence of the secondary electron emission on the plasma characteristics in the discharges is investigated numerically by the model. The results show that as the secondary electron emission coefficient increases,the cycle-averaged electric field has almost no change; the cycle-averaged electron temperature in the bulk plasma almost does not change, but it increases in the two sheath regions; the cycle-averaged ionization rate, electron density, electron current density, ion current density, and total current density all increase. Also, the cycle-averaged secondary electron fluxes on the surfaces of the electrodes increase as the secondary electron emission coefficient increases. The evolutions of the electron flux, the secondary electron flux and the ion flux on the powered electrode increase as the secondary electron emission coefficient increases. The cycle-averaged electron pressure heating, electron Ohmic heating, electron heating, and ion heating in the two sheath regions increase as the secondary electron emission coefficient increases. The cycle-averaged electron energy loss increases with increasing secondary electron emission coefficient.展开更多
Recently some modes of supersonic molecular beam injection （SMBI）have been put forward. Among them there are electrostatic “double layer”-shielding, simple collective and optimized numerical models to explain the ...Recently some modes of supersonic molecular beam injection （SMBI）have been put forward. Among them there are electrostatic “double layer”-shielding, simple collective and optimized numerical models to explain the experiment phenomenon. The penetrated depth A and particle deposition were calculated theoretically. About 1/7 in- cident thermal electron flux was amputated and, A increased seven times. The previous simulation is not enough for the SMBI fueling mechanism research. Hence, further investigations, both in experiment and in theory should be developed. The phenomena of line emission due to supersonic molecular beam （SMB） are of particular importance.展开更多
In this article,a comprehensive model for the analysis of carbon dioxide(CO_(2))emissions from off-highway trucks is presented,expanding the understanding of the contributions of these vehicles to global greenhouse ga...In this article,a comprehensive model for the analysis of carbon dioxide(CO_(2))emissions from off-highway trucks is presented,expanding the understanding of the contributions of these vehicles to global greenhouse gas(GHG)emissions.Off-highway trucks are key contributors in various sectors,such as mining,construction and agriculture,but their CO_(2)emissions have often been underestimated due to their operational complexity.The proposed model combines operational data,vehicle characteristics,load profiles and specific emission factors to create an accurate and adaptable analysis tool that considers the parameters of transported load,track slope,average speed and mechanical efficiency.By integrating these elements,the model calculates CO_(2)emissions,allowing for a holistic assessment of the environmental impacts of off-highway trucks.In addition,we highlight the importance of accurate modeling of CO_(2)emissions in this context,as these analyses are crucial for formulating mitigation strategies and for adopting highly sustainable practices in the operation of these vehicles.The application of the model to specific case studies demonstrates its effectiveness in different operational scenarios,and it provides valuable insights for informed decision-making.In summary,the proposed model fills a significant gap in the analysis of GHG emissions from off-highway trucks,leading to an increasingly accurate understanding of their environmental impacts.展开更多
Direct current triboelectric nanogenerators(DC-TENGs)are a groundbreaking technology to capture micromechanical energy from the natural environment,which is crucial for directly powering sensor networks.However,the re...Direct current triboelectric nanogenerators(DC-TENGs)are a groundbreaking technology to capture micromechanical energy from the natural environment,which is crucial for directly powering sensor networks.However,the research bottleneck in enhancing the triboelectric electrification capability and charge storage capability of dielectrics has hindered the overall performance breakthroughs of the DC-TENG.Here,a field emission model-based DC-TENG(FEM-TENG)is proposed,inspired by lightning rods.The enhanced local electric field between dielectric materials and electrodes induces strong electron tunneling,which improves charge neutralization on the surface of materials and their internal charge storage space,thereby utilizing the dielectric volume effect effectively and strengthening triboelectricity.Guided by the field emission model,the FEM-TENG with a historic crest factor of 1.00375 achieves a groundbreaking record of an average power density of 16.061 W m^(-2)Hz^(-1)(1,591 W m^(-3)Hz^(-1)),which is 5.36-fold of the latest DC-TENG.In particular,the FEM-TENG with high durability(100%)truly realizes the collection of breeze energy and continuously drives 50 thermohygrometers.Four additional applications exemplify the FEM-TENG,enabling comprehensive sensing of land,water,and air.This work proposes a paradigm strategy for the in-depth utilization of dielectric films,aiming to enhance the output power of DC-TENGs.展开更多
This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, use...This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling（RSM） methodology and serves as a visualization and analysis tool（VAT） for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S.demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias 〈 2% and assisting in air quality policy making in near real time.展开更多
Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon e...Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.展开更多
With the rapid increase of the amount of vehicles in urban areas,the pollution of vehicle emissions is becoming more and more serious.Precise prediction of the spatiotemporal evolution of urban traffic emissions plays...With the rapid increase of the amount of vehicles in urban areas,the pollution of vehicle emissions is becoming more and more serious.Precise prediction of the spatiotemporal evolution of urban traffic emissions plays a great role in urban planning and policy making.Most existing methods usually focus on estimating vehicle emissions at historical or current moments which cannot well meet the demands of future planning.Recent work has started to pay attention to the evolution of vehicle emissions at future moments using multiple attributes related to emissions,however,they are not effective and efficient enough in the combination and utilization of different inputs.To address this issue,we propose a joint framework to predict the future evolution of vehicle emissions based on the GPS trajectories of taxis with a multi-channel spatiotemporal network and the motor vehicle emission simulator(MOVES)model.Specifically,we first estimate the spatial distribution matrices with GPS trajectories through map-matching algorithms.These matrices can reflect the attributes related to the traffic status of road networks such as volume,speed and acceleration.Then,our multi-channel spatiotemporal network is used to efficiently combine three key attributes(volume,speed and acceleration)through the feature sharing mechanism and generate a precise prediction of them in the future period.Finally,we adopt an MOVES model to estimate vehicle emissions by integrating several traffic factors including the predicted traffic states,road networks and the statistical information of urban vehicles.We evaluate our model on the Xi′an taxi GPS trajectories dataset.Experiments show that our proposed network can effectively predict the temporal evolution of vehicle emissions.展开更多
Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carb...Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.展开更多
The γ-ray radiation will speed up the discharge of the storedcharge in nonvolatile MNOS structure. The radiation absorptionmechanism to enhance the discharge is discussed. A direct radiationemission model from the in...The γ-ray radiation will speed up the discharge of the storedcharge in nonvolatile MNOS structure. The radiation absorptionmechanism to enhance the discharge is discussed. A direct radiationemission model from the interface traps distributing both in energylevel and in space is given. The theoretical results based on thismodel are in good agreement with experimental measurements.展开更多
The extended “STIRPAT” model and the GM(1,1) model are used to predict the factors influencing inter-provincial carbon emission intensity and carbon intensity in China respectively. In this paper, based on the colla...The extended “STIRPAT” model and the GM(1,1) model are used to predict the factors influencing inter-provincial carbon emission intensity and carbon intensity in China respectively. In this paper, based on the collation of inter-provincial carbon emission data, the extended “STIRPAT” model is formulated for carbon dioxide emissions and carbon intensity emissions, and the Hausman test is used to determine the influence form of the models. The main influencing factors of carbon intensity were identified: economic development level, energy intensity, and energy consumption structure. The paper constructs GM(1,1) model for carbon emission intensity from 2010-2019 using the gray prediction method,and calculates the carbon emission intensity of China’s inter-provincial 2022 by residual test, correlation test, variance, and small error probability test, and then predicts the carbon demand of each province and city in 2022 according to the expected average annual growth rate, and finally concludes that using carbon emission intensity as the carbon emission reduction target of each region, and it cannot fundamentally solve the problem of carbon pollution in China. Compared to the regional carbon emission reduction target, there is a greater degree of regional imbalance in carbon intensity between provinces in China, and the target of reducing carbon emission intensity somehow avoids the fact that the carbon emission reduction intensity target can be achieved without reducing the absolute amount of carbon emissions that continue to increase. The focus of achieving the “double carbon” target lies in the reduction of total carbon emissions, and the target of reducing carbon intensity will eventually be transformed into a binding target of total carbon emissions in the process of implementation, so attention should be shifted from recessiontype carbon reduction and efficiency-type carbon reduction to innovative carbon reduction. It is necessary to increase investment in renewable energy, and gradually expand the scope of application of photovoltaic, and wind power to ensure the reduction of total carbon emissions.展开更多
To reduce engine pollutant emissions,an emission modeling and optimization scheme based on a hybrid artificial intelligence scheme is proposed in this study to reduce pollutant emissions of methanol/diesel dual-fuel e...To reduce engine pollutant emissions,an emission modeling and optimization scheme based on a hybrid artificial intelligence scheme is proposed in this study to reduce pollutant emissions of methanol/diesel dual-fuel engines under low load.Firstly,a data cleaning method based on isolated forest and correlation analysis is designed to improve the stability of the system.Secondly,a hybrid emission prediction model based on improved Transformer(ITransformer)and Bidirectional Gated Recurrent Unit(BiGRU)is built to obtain an accurate mathematical model between control parameters and emissions.Finally,based on the obtained mathematical model,the 3rd Non-dominated Sorting Genetic Algorithm(NGSA-Ⅲ)is used to adjust and optimize the control parameters.Using engine bench test data to evaluate the proposed hybrid emission prediction model,the R^(2) of CO,HC,and NO_(x) prediction is 0.9969,0.9973,and 0.9982,respectively,which is higher than the accuracy of the seven existing modeling methods.Compared with the unoptimized MESR46,the CO,HC,and NO_(x) emissions of the optimized scheme are reduced by at least 45.17%,15.30%,and 17.32%respectively,which can significantly reduce the CO,HC,and NO_(x) emissions,and comparison and analysis with the most advanced optimization technologies show a competitive optimization effect.展开更多
In order to evaluate the impacts of volatile organic compounds(VOCs)emissions from building materials on the indoor air quality beyond the standard chamber test conditions and test period,mechanistic emission source m...In order to evaluate the impacts of volatile organic compounds(VOCs)emissions from building materials on the indoor air quality beyond the standard chamber test conditions and test period,mechanistic emission source models have been developed in the past.However,very limited data are available for the required model parameters including the initial concentration(C_(m0)),in-material diffusion coefficient(D_(m)),partition coefficient(Kma),and convective mass transfer coefficient(k_(m)).In this study,a procedure was developed for estimating the model parameters by using VOC emission data from standard small chamber tests.In the procedure,initial values of the model parameters were refined by multivariate regression analysis of the measured emission data.To verify the procedure and estimate its uncertainty,simulated chamber test data were generated by adding 10% experimental uncertainties on the theoretical curve from the analytical solution to a mechanistic emission model.Then the procedure was applied to the generated data to estimate the model parameters.Results indicated that estimates converged to the original parameter values used for the data generation and the error of estimated parameters D_(m1)C_(m0) and K_(ma) were within±10%,±23%,and±25%of the true values,respectively.The procedure was further demonstrated by applying it to estimate the model parameters from real chamber test data.Wide application of the procedure would result in a database of mechanistic source model parameters for assessing the impact of VOC emissions on indoor pollution load,which are essential input data for evaluating the effectiveness of various indoor air quality(IAQ)design and control strategies as well as the energy required for meeting given IAQ requirements.展开更多
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 State Environmental Protection Department of Public Welfare Projects(201409013)the National Natural Science Foundation of China(No.51576016 and No.41275133)
文摘An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system （PEMS） under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics （speed and acceleration） of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data.
基金Supported by State Key Laboratory of Engines(SKLE,200906)the National Natural Science Foundation of China(40805053)
文摘A total of 14 in-use diesel buses were selected to conduct emission measurement using a portable emissions measurement system （PEMS） in Beijing. Their instantaneous gaseous emission rates, particular matter （PM） emission rates and driving parameters were obtained. The influences of speed, acceleration and vehicle specific power （VSP） on emissions were analyzed. Based on the relationships between these driving parameters and emissions, 24 driving bins defined by speed, ac- celeration and VSP were constructed with cluster analysis to group emission rates for Euro Ⅲ and IV buses, respectively. Then the emissions reductions from Euro Ⅲ to Euro Ⅳ diesel buses were ana- lyzed. Lastly, on-road hot-stabilized emission rate model for diesel buses in Beijing was developed. Through the comparison of the model simulation emission rates with the measured emission rates, the modeled emission results were in good agreement with the measured emission results. In most of the cases, the differences were less than 12 %.
基金Project supported by the China Special Fund for Meteorological Research in the Public Interest(No.GYHY201306045)the National Natural Science Foundation of China(Nos.41305066 and41575096)
文摘The choices of the parameterizations for each component in a microwave emission model have significant effects on the quality of brightness temperature （Tb） sim- ulation. How to reduce the uncertainty in the Tb simulation is investigated by adopting a statistical post-processing procedure with the Bayesian model averaging （BMA） ensemble approach. The simulations by the community microwave emission model （CMEM） cou- pled with the community land model version 4.5 （CLM4.5） over China's Mainland are con- ducted by the 24 configurations from four vegetation opacity parameterizations （VOPs）, three soil dielectric constant parameterizations （SDCPs）, and two soil roughness param- eterizations （SRPs）. Compared with the simple arithmetical averaging （SAA） method, the BMA reconstructions have a higher spatial correlation coefficient （larger than 0.99） than the C-band satellite observations of the advanced microwave scanning radiometer on the Earth observing system （AMSR-E） at the vertical polarization. Moreover, the BMA product performs the best among the ensemble members for all vegetation classes, with a mean root-mean-square difference （RMSD） of 4 K and a temporal correlation coefficient of 0.64.
基金supported by the National Basic Research Program of China under Grants 2010CB951101 and 2010CB951001the National Natural Science Foundation of China under Grant 41075062
文摘The Community Microwave Emission Model (CMEM) developed by the European Centre for Me-dium-Range Weather Forecasts (ECMWF) can provide a link between surface states and satellite observations and simulate the passive microwave brightness temperature of the surface at low frequencies (from 1 GHz to 20 GHz).This study evaluated the performance of the CMEM cou-pled with the Community Land Model (CLM) (CMEM-CLM) using C-band (6.9 GHz) microwave brightness temperatures from the Advanced Microwave Scanning Radiometer on Earth Observing System (AMSR-E) over East Asia.Preliminary results support the argument that the simulated brightness temperatures of CMEM-CLM from July 2005 to June 2010 are comparable to AMSR-E observational data.CMEM-CLM performed better for vertical polarization,for which the root mean square error was approximately 15 K,compared to over 30 K for horizontal polarization.An evaluation performed over seven sub-regions in China indicated that CMEM-CLM was able to capture the temporal evolution of C-band brightness temperatures well,and the best correlation with AMSR-E appeared over western Northwest China (over 0.9 for vertical polarization).However,larger biases were found over southern North China and the middle and lower reaches of the Yangtze River.
文摘China＇s energy supply-and-demand model and two related carbon emission scenarios, including a planned peak scenario and an advanced peak scenario, are designed taking into consideration China＇s economic development, technological progress, policies, resources, environmental capacity, and other factors. The analysis of the defined scenarios provides the following conclusions： Primary energy and power demand will continue to grow leading up to 2030, and the growth rate of power demand will be much higher than that of primary energy demand. Moreover, low carbonization will be a basic feature of energy supply-and-demand structural changes, and non-fossil energy will replace oil as the second largest energy source. Finally, energy- related carbon emissions could peak in 2025 through the application of more efficient energy consumption patterns and more low-carbon energy supply modes. The push toward decarbonization of the power industry is essential for reducing the peak value of carbon emissions.
基金supported by National Natural Science Foundation of China(Grant No.61378037)the Fundamental Research Funds for the Central Universities(Nos.2013B33614,2017B15214)+1 种基金the Research Funds of Innovation and Entrepreneurship Education Reform for Chinese Universities(No.16CCJG01Z004)the Changzhou Science and Technology Program(No.CJ20160027)
文摘The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the behavior in plasma.In this paper,a glass vacuum chamber and a pair of plate electrodes were designed and fabricated,using 13.56 MHz radio frequency（RF）discharge technology to ionize the working gas of Ar.This discharge was mathematically described with equivalent circuit model.The discharge voltage and current of the plasma were measured atdifferent pressures and different powers.Based on the capacitively coupled homogeneous discharge model,the equivalent circuit and the analytical formula were established.The plasma density and temperature were calculated by using the equivalent impedance principle and energy balance equation.The experimental results show that when RF discharge power is 50–300 W and pressure is 25–250 Pa,the average electron temperature is about 1.7–2.1 e V and the average electron density is about 0.5？×10^17–3.6？×10^17m^-3.Agreement was found when the results were compared to those given by optical emission spectroscopy and COMSOL simulation.
基金Under the auspices of National Natural Science Foundation of China(No.41301637,41101117,41271186)Key Program of National Natural Science Foundation of China(No.71133003)
文摘Based on the logical causal relationship and taking Liaoning Province, China, which is the Chinese traditional industrial base and is in the stage of accelerated urbanisation, as a case study, this study builds the ＇Urbanisation-Energy Consumption-COn Emissions System Dynamics （UEC-SD）＇ model using a system dynamics method. The UEC-SD model is applied to analyse the effect of the ar- banisation process on the regional energy structure and CO2 emissions, followed by simulation of future production and living energy consumption structure as well as the evolutionary trend of CO2 emissions of three urbanisation scenarios （low speed, intermediate speed and high speed） under the assumed boundary conditions in urban and rural areas of Liaoning Province, China. The results show that the urbanisation process can alter production and the living energy consumption structure and thereby change regional CO2 emissions. An increase in the urbanisation rate in case area will lead to regional COz emissions rising in the short term, but when the urbanisation rate approaches 80%, CO2 emissions will reach a peak value and then decrease. Comparison of different urbanisation rates showed that pro- duction and living energy consumption exhibit different directions of change and rules in urban and rural areas. The effect of urbanisa- tion on CO2 emissions and energy structure is not direct, and urbanisation can increase the differences in energy and CO2 emissions between urban and rural areas caused by the industrial structure, technical level and other factors.
基金Project supported by the National Natural Science Foundation of China(Grant No.51172101)
文摘A one-dimensional（1D） fluid model of capacitive RF argon glow discharges between two parallel-plate electrodes at low pressure is employed. The influence of the secondary electron emission on the plasma characteristics in the discharges is investigated numerically by the model. The results show that as the secondary electron emission coefficient increases,the cycle-averaged electric field has almost no change; the cycle-averaged electron temperature in the bulk plasma almost does not change, but it increases in the two sheath regions; the cycle-averaged ionization rate, electron density, electron current density, ion current density, and total current density all increase. Also, the cycle-averaged secondary electron fluxes on the surfaces of the electrodes increase as the secondary electron emission coefficient increases. The evolutions of the electron flux, the secondary electron flux and the ion flux on the powered electrode increase as the secondary electron emission coefficient increases. The cycle-averaged electron pressure heating, electron Ohmic heating, electron heating, and ion heating in the two sheath regions increase as the secondary electron emission coefficient increases. The cycle-averaged electron energy loss increases with increasing secondary electron emission coefficient.
文摘Recently some modes of supersonic molecular beam injection （SMBI）have been put forward. Among them there are electrostatic “double layer”-shielding, simple collective and optimized numerical models to explain the experiment phenomenon. The penetrated depth A and particle deposition were calculated theoretically. About 1/7 in- cident thermal electron flux was amputated and, A increased seven times. The previous simulation is not enough for the SMBI fueling mechanism research. Hence, further investigations, both in experiment and in theory should be developed. The phenomena of line emission due to supersonic molecular beam （SMB） are of particular importance.
文摘In this article,a comprehensive model for the analysis of carbon dioxide(CO_(2))emissions from off-highway trucks is presented,expanding the understanding of the contributions of these vehicles to global greenhouse gas(GHG)emissions.Off-highway trucks are key contributors in various sectors,such as mining,construction and agriculture,but their CO_(2)emissions have often been underestimated due to their operational complexity.The proposed model combines operational data,vehicle characteristics,load profiles and specific emission factors to create an accurate and adaptable analysis tool that considers the parameters of transported load,track slope,average speed and mechanical efficiency.By integrating these elements,the model calculates CO_(2)emissions,allowing for a holistic assessment of the environmental impacts of off-highway trucks.In addition,we highlight the importance of accurate modeling of CO_(2)emissions in this context,as these analyses are crucial for formulating mitigation strategies and for adopting highly sustainable practices in the operation of these vehicles.The application of the model to specific case studies demonstrates its effectiveness in different operational scenarios,and it provides valuable insights for informed decision-making.In summary,the proposed model fills a significant gap in the analysis of GHG emissions from off-highway trucks,leading to an increasingly accurate understanding of their environmental impacts.
基金supported by the National Natural Science Foundation ofChina(NSFC)(52272191)the National Key R&D Project from Minister of Science and Technology(2021YFA1201602)the Fundamental Research Funds for the Central Universities(grantno.2021CDJQY-005,2022CCJJCLK001).
文摘Direct current triboelectric nanogenerators(DC-TENGs)are a groundbreaking technology to capture micromechanical energy from the natural environment,which is crucial for directly powering sensor networks.However,the research bottleneck in enhancing the triboelectric electrification capability and charge storage capability of dielectrics has hindered the overall performance breakthroughs of the DC-TENG.Here,a field emission model-based DC-TENG(FEM-TENG)is proposed,inspired by lightning rods.The enhanced local electric field between dielectric materials and electrodes induces strong electron tunneling,which improves charge neutralization on the surface of materials and their internal charge storage space,thereby utilizing the dielectric volume effect effectively and strengthening triboelectricity.Guided by the field emission model,the FEM-TENG with a historic crest factor of 1.00375 achieves a groundbreaking record of an average power density of 16.061 W m^(-2)Hz^(-1)(1,591 W m^(-3)Hz^(-1)),which is 5.36-fold of the latest DC-TENG.In particular,the FEM-TENG with high durability(100%)truly realizes the collection of breeze energy and continuously drives 50 thermohygrometers.Four additional applications exemplify the FEM-TENG,enabling comprehensive sensing of land,water,and air.This work proposes a paradigm strategy for the in-depth utilization of dielectric films,aiming to enhance the output power of DC-TENGs.
基金Financial and data support for this work is provided by the U.S. Environmental Protection Agency (No. GS-10F-0205T)partly supported by the funding of Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control (No. h2xj D612004 Ш )+1 种基金the funding of State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex (No. SCAPC201308)the project of Atmospheric Haze Collaboration Control Technology Design (No. XDB05030400) from Chinese Academy of Sciences
文摘This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling（RSM） methodology and serves as a visualization and analysis tool（VAT） for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S.demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias 〈 2% and assisting in air quality policy making in near real time.
基金National Natural Science Foundation of China,No.41601151Guangdong Natural Science Foundation,No.2016A030310149
文摘Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.
基金This work was supported by National Key R&D Program of China under Grant(Nos.2018AAA0100800,2018YFE0106800)National Natural Science Foundation of China(Nos.61725304,61673361 and 62033012)Major Special Science and Technology Project of Anhui,China(No.912198698036).
文摘With the rapid increase of the amount of vehicles in urban areas,the pollution of vehicle emissions is becoming more and more serious.Precise prediction of the spatiotemporal evolution of urban traffic emissions plays a great role in urban planning and policy making.Most existing methods usually focus on estimating vehicle emissions at historical or current moments which cannot well meet the demands of future planning.Recent work has started to pay attention to the evolution of vehicle emissions at future moments using multiple attributes related to emissions,however,they are not effective and efficient enough in the combination and utilization of different inputs.To address this issue,we propose a joint framework to predict the future evolution of vehicle emissions based on the GPS trajectories of taxis with a multi-channel spatiotemporal network and the motor vehicle emission simulator(MOVES)model.Specifically,we first estimate the spatial distribution matrices with GPS trajectories through map-matching algorithms.These matrices can reflect the attributes related to the traffic status of road networks such as volume,speed and acceleration.Then,our multi-channel spatiotemporal network is used to efficiently combine three key attributes(volume,speed and acceleration)through the feature sharing mechanism and generate a precise prediction of them in the future period.Finally,we adopt an MOVES model to estimate vehicle emissions by integrating several traffic factors including the predicted traffic states,road networks and the statistical information of urban vehicles.We evaluate our model on the Xi′an taxi GPS trajectories dataset.Experiments show that our proposed network can effectively predict the temporal evolution of vehicle emissions.
基金Under the auspices of National Natural Science Foundation of China(No.41301633)National Social Science Foundation of China(No.10ZD&030)+1 种基金Postdoctoral Science Foundation of China(No.2012M511243,2013T60518)Clean Development Mechanism Foundation of China(No.1214073,2012065)
文摘Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.
文摘The γ-ray radiation will speed up the discharge of the storedcharge in nonvolatile MNOS structure. The radiation absorptionmechanism to enhance the discharge is discussed. A direct radiationemission model from the interface traps distributing both in energylevel and in space is given. The theoretical results based on thismodel are in good agreement with experimental measurements.
文摘The extended “STIRPAT” model and the GM(1,1) model are used to predict the factors influencing inter-provincial carbon emission intensity and carbon intensity in China respectively. In this paper, based on the collation of inter-provincial carbon emission data, the extended “STIRPAT” model is formulated for carbon dioxide emissions and carbon intensity emissions, and the Hausman test is used to determine the influence form of the models. The main influencing factors of carbon intensity were identified: economic development level, energy intensity, and energy consumption structure. The paper constructs GM(1,1) model for carbon emission intensity from 2010-2019 using the gray prediction method,and calculates the carbon emission intensity of China’s inter-provincial 2022 by residual test, correlation test, variance, and small error probability test, and then predicts the carbon demand of each province and city in 2022 according to the expected average annual growth rate, and finally concludes that using carbon emission intensity as the carbon emission reduction target of each region, and it cannot fundamentally solve the problem of carbon pollution in China. Compared to the regional carbon emission reduction target, there is a greater degree of regional imbalance in carbon intensity between provinces in China, and the target of reducing carbon emission intensity somehow avoids the fact that the carbon emission reduction intensity target can be achieved without reducing the absolute amount of carbon emissions that continue to increase. The focus of achieving the “double carbon” target lies in the reduction of total carbon emissions, and the target of reducing carbon intensity will eventually be transformed into a binding target of total carbon emissions in the process of implementation, so attention should be shifted from recessiontype carbon reduction and efficiency-type carbon reduction to innovative carbon reduction. It is necessary to increase investment in renewable energy, and gradually expand the scope of application of photovoltaic, and wind power to ensure the reduction of total carbon emissions.
基金supported by the National Natural Science Foundation of China(52066003)the Guangxi Key R&D Program(2022GXNSFFA035029).
文摘To reduce engine pollutant emissions,an emission modeling and optimization scheme based on a hybrid artificial intelligence scheme is proposed in this study to reduce pollutant emissions of methanol/diesel dual-fuel engines under low load.Firstly,a data cleaning method based on isolated forest and correlation analysis is designed to improve the stability of the system.Secondly,a hybrid emission prediction model based on improved Transformer(ITransformer)and Bidirectional Gated Recurrent Unit(BiGRU)is built to obtain an accurate mathematical model between control parameters and emissions.Finally,based on the obtained mathematical model,the 3rd Non-dominated Sorting Genetic Algorithm(NGSA-Ⅲ)is used to adjust and optimize the control parameters.Using engine bench test data to evaluate the proposed hybrid emission prediction model,the R^(2) of CO,HC,and NO_(x) prediction is 0.9969,0.9973,and 0.9982,respectively,which is higher than the accuracy of the seven existing modeling methods.Compared with the unoptimized MESR46,the CO,HC,and NO_(x) emissions of the optimized scheme are reduced by at least 45.17%,15.30%,and 17.32%respectively,which can significantly reduce the CO,HC,and NO_(x) emissions,and comparison and analysis with the most advanced optimization technologies show a competitive optimization effect.
文摘In order to evaluate the impacts of volatile organic compounds(VOCs)emissions from building materials on the indoor air quality beyond the standard chamber test conditions and test period,mechanistic emission source models have been developed in the past.However,very limited data are available for the required model parameters including the initial concentration(C_(m0)),in-material diffusion coefficient(D_(m)),partition coefficient(Kma),and convective mass transfer coefficient(k_(m)).In this study,a procedure was developed for estimating the model parameters by using VOC emission data from standard small chamber tests.In the procedure,initial values of the model parameters were refined by multivariate regression analysis of the measured emission data.To verify the procedure and estimate its uncertainty,simulated chamber test data were generated by adding 10% experimental uncertainties on the theoretical curve from the analytical solution to a mechanistic emission model.Then the procedure was applied to the generated data to estimate the model parameters.Results indicated that estimates converged to the original parameter values used for the data generation and the error of estimated parameters D_(m1)C_(m0) and K_(ma) were within±10%,±23%,and±25%of the true values,respectively.The procedure was further demonstrated by applying it to estimate the model parameters from real chamber test data.Wide application of the procedure would result in a database of mechanistic source model parameters for assessing the impact of VOC emissions on indoor pollution load,which are essential input data for evaluating the effectiveness of various indoor air quality(IAQ)design and control strategies as well as the energy required for meeting given IAQ requirements.
