In the present article we characterized the emissions at the exhaust of a Common Rail （CR） diesel engine, representative of lightduty class, equipped with a catalyzed diesel particulate filter （CDPF） in controlled...In the present article we characterized the emissions at the exhaust of a Common Rail （CR） diesel engine, representative of lightduty class, equipped with a catalyzed diesel particulate filter （CDPF） in controlled environment. The downstream exhausts were directly analyzed （for PM, CO, CO/, Oz, HCs, NOx） by infrared and electrochemical sensors, and SEM-EDS microscope; heavy metals were chemically analyzed using mosses and lichens in bags, and glass-fibre filters all exposed at the engine exhausts. The highest particle emission value was in the 7-54 nm size range; the peak concentration rose until one order of magnitude for the highest load and speed. Particle composition was mainly carbonaceous, associated to noticeable amounts of Fe and silica fibres. Moreover, the content of Cu, Fe, Na, Ni and Zn in both moss and lichen, and of A1 and Cr in moss, was significantly increased. Glass-fibre filters were significantly enriched in A1, B, Ba, Cu, Fe, Na, and Zn. The role of diesel engines as source of carbonaceous nanoparticles has been confirmed, while further investigations in controlled environment are needed to test the catalytic muffler as a possible source of silica fibres considered very hazardous for human health.展开更多
The booming development of rare earth industry and the extensive utilization of its products accompanied by urban development have led to the accelerated accumulation of rare earth elements(REEs)as emerging pollutants...The booming development of rare earth industry and the extensive utilization of its products accompanied by urban development have led to the accelerated accumulation of rare earth elements(REEs)as emerging pollutants in atmospheric environment.In this study,the variation of REEs in PM_(2.5)with urban(a non-mining city)transformation was investigated through five consecutive years of sample collection.The compositional variability and provenance contribution of REEs in PM_(2.5)were characterized,and the REEs exposure risks of children and adults via inhalation,ingestion and dermal absorption were also evaluated.The results showed an increase in the total REEs concentration from 46.46±35.16 mg/kg(2017)to 81.22±38.98 mg/kg(2021)over the five-year period,with Ce and La making the largest contribution.The actual increment of industrial and traffic emission source among the three pollution sources was 1.34 ng/m^(3).Coal combustion source displayed a downward trend.Ingestion was the main exposure pathway for REEs in PM_(2.5)for both children and adults.Ce contributed the most to the total intake of REEs in PM_(2.5)among the population,followed by La and Nd.The exposure risks of REEs in PM_(2.5)in the region were relatively low,but the trend of change was of great concern.It was strongly recommended to strengthen the concern about traffic-related non-exhaust emissions of particulate matter.展开更多
Brake wear is an important but unregulated vehicle-related source of atmospheric particulate matter(PM).The single-particle spectral fingerprints of brake wear particles(BWPs)provide essential information for understa...Brake wear is an important but unregulated vehicle-related source of atmospheric particulate matter(PM).The single-particle spectral fingerprints of brake wear particles(BWPs)provide essential information for understanding their formation mechanism and atmospheric contributions.Herein,we obtained the single-particle mass spectra of BWPs by combining a brake dynamometer with an online single particle aerosol mass spectrometer and quantified real-world BWP emissions through a tunnel observation in Tianjin,China.The pure BWPs mainly include three distinct types of particles,namely,Bacontaining particles,mineral particles,and carbon-containing particles,accounting for 44.2%,43.4%,and 10.3%of the total BWP number concentration,respectively.The diversified mass spectra indicate complex BWP formation pathways,such as mechanical,phase transition,and chemical processes.Notably,the mass spectra of Ba-containing particles are unique,which allows them to serve as an excellent indicator for estimating ambient BWP concentrations.By evaluating this indicator,we find that approximately 4.0%of the PM in the tunnel could be attributable to brake wear;the real-world fleet-average emission factor of 0.28 mg km1 veh1 is consistent with the estimation obtained using the receptor model.The results presented herein can be used to inform assessments of the environmental and health impacts of BWPs to formulate effective emissions control policies.展开更多
A single particle aerosol mass spectrometer(SPAMS)was used to accurately quantify the contribution of vehicle non-exhaust emissions to particulate matter at typical road environment.The PM_(2.5),black carbon,meteorolo...A single particle aerosol mass spectrometer(SPAMS)was used to accurately quantify the contribution of vehicle non-exhaust emissions to particulate matter at typical road environment.The PM_(2.5),black carbon,meteorological parameters and traffic flow were recorded during the test period.The daily trend for traffic flow and speed on TEDA Street showed obvious“M”and“W”characteristics.6.3 million particles were captured via the SPAMS,including 1.3 million particles with positive and negative spectral map information.Heavy Metal,High molecular Organic Carbon,Organic Carbon,Mixed Carbon,Elemental Carbon,Rich Potassium,Levo-rotation Glucose,Rich Na,SiO_(3) and other categories were analyzed.The particle number concentration measured by SPAMS showed a good linear correlation with the mass concentrations of PM_(2.5) and BC,which indicates that the particulate matter captured by the SPAMS reflects the pollution level of fine particulate matter.EC,ECOC,OC,HM and crustal dust components were found to show high values from 7:00–9:00 AM,showing that these chemical components are directly or indirectly related to vehicle emissions.Based on the PMF model,7 major factors are resolved.The relative contributions of each factor were determined:vehicle exhaust emission(44.8%),coal-fired source(14.5%),biomass combustion(12.2%),crustal dust(9.4%),ship emission(9.0%),tires wear(6.6%)and brake pads wear(3.5%).The results show that the contribution of vehicle non-exhaust to particulate matter at roadside environment is approximately 10.1%.Vehicle non-exhaust emissions are the focus of future research in the vehicle pollutant emission control field.展开更多
基于心里声学客观参量的GA-BP声品质预测模型能够准确的预测稳态排气噪声声品质。对于非稳态噪声研究,引入正则化非稳态回归技术(RNR)优化计算维格纳-威尔分布(WVD)的时频方法,建立新的声品质参量SQP-RW(Sound Quality Parameter Base o...基于心里声学客观参量的GA-BP声品质预测模型能够准确的预测稳态排气噪声声品质。对于非稳态噪声研究,引入正则化非稳态回归技术(RNR)优化计算维格纳-威尔分布(WVD)的时频方法,建立新的声品质参量SQP-RW(Sound Quality Parameter Base on RNR-WVD),用此参量替换掉与满意度相关性较小的客观参量。同时,以Morlet小波基函数作为隐含层结点的传递函数构建小波神经网络(Wavelet Neural Network,WNN),并用GA优化小波神经网络层间的权值和阈值,构造出GA-WNN并用于非稳态排气噪声声品质预测。结果表明:GA-WNN在非稳态排气噪声声品质预测上比GA-BP神经网络更加准确;引入SQP-RW参量,模型具有更高的精度,更能体现出非稳态信号特征及声品质特点。展开更多
文摘In the present article we characterized the emissions at the exhaust of a Common Rail （CR） diesel engine, representative of lightduty class, equipped with a catalyzed diesel particulate filter （CDPF） in controlled environment. The downstream exhausts were directly analyzed （for PM, CO, CO/, Oz, HCs, NOx） by infrared and electrochemical sensors, and SEM-EDS microscope; heavy metals were chemically analyzed using mosses and lichens in bags, and glass-fibre filters all exposed at the engine exhausts. The highest particle emission value was in the 7-54 nm size range; the peak concentration rose until one order of magnitude for the highest load and speed. Particle composition was mainly carbonaceous, associated to noticeable amounts of Fe and silica fibres. Moreover, the content of Cu, Fe, Na, Ni and Zn in both moss and lichen, and of A1 and Cr in moss, was significantly increased. Glass-fibre filters were significantly enriched in A1, B, Ba, Cu, Fe, Na, and Zn. The role of diesel engines as source of carbonaceous nanoparticles has been confirmed, while further investigations in controlled environment are needed to test the catalytic muffler as a possible source of silica fibres considered very hazardous for human health.
基金supported by the National Natural Science Foundation of China(No.22176056)the Fundamental Research Funds for the Central Universities(No.2017ZZD07)。
文摘The booming development of rare earth industry and the extensive utilization of its products accompanied by urban development have led to the accelerated accumulation of rare earth elements(REEs)as emerging pollutants in atmospheric environment.In this study,the variation of REEs in PM_(2.5)with urban(a non-mining city)transformation was investigated through five consecutive years of sample collection.The compositional variability and provenance contribution of REEs in PM_(2.5)were characterized,and the REEs exposure risks of children and adults via inhalation,ingestion and dermal absorption were also evaluated.The results showed an increase in the total REEs concentration from 46.46±35.16 mg/kg(2017)to 81.22±38.98 mg/kg(2021)over the five-year period,with Ce and La making the largest contribution.The actual increment of industrial and traffic emission source among the three pollution sources was 1.34 ng/m^(3).Coal combustion source displayed a downward trend.Ingestion was the main exposure pathway for REEs in PM_(2.5)for both children and adults.Ce contributed the most to the total intake of REEs in PM_(2.5)among the population,followed by La and Nd.The exposure risks of REEs in PM_(2.5)in the region were relatively low,but the trend of change was of great concern.It was strongly recommended to strengthen the concern about traffic-related non-exhaust emissions of particulate matter.
基金supported by the National key research and development program of China(2022YFE0135000)the Tianjin Science and Technology Plan Project(19YFZCSF00960)+2 种基金the National Natural Science Foundation of China(42177084,42175123,42107114,42107125)the Natural Science Foundation of Tianjin(20JCYBJC01270)the Fundamental Research Funds for the Central Universities(63221411).
文摘Brake wear is an important but unregulated vehicle-related source of atmospheric particulate matter(PM).The single-particle spectral fingerprints of brake wear particles(BWPs)provide essential information for understanding their formation mechanism and atmospheric contributions.Herein,we obtained the single-particle mass spectra of BWPs by combining a brake dynamometer with an online single particle aerosol mass spectrometer and quantified real-world BWP emissions through a tunnel observation in Tianjin,China.The pure BWPs mainly include three distinct types of particles,namely,Bacontaining particles,mineral particles,and carbon-containing particles,accounting for 44.2%,43.4%,and 10.3%of the total BWP number concentration,respectively.The diversified mass spectra indicate complex BWP formation pathways,such as mechanical,phase transition,and chemical processes.Notably,the mass spectra of Ba-containing particles are unique,which allows them to serve as an excellent indicator for estimating ambient BWP concentrations.By evaluating this indicator,we find that approximately 4.0%of the PM in the tunnel could be attributable to brake wear;the real-world fleet-average emission factor of 0.28 mg km1 veh1 is consistent with the estimation obtained using the receptor model.The results presented herein can be used to inform assessments of the environmental and health impacts of BWPs to formulate effective emissions control policies.
基金supported by the National Natural Science Foundation of China(Nos.42107114 and 42177084)the Tianjin Science and Technology Plan Project(No.20YFZCSN01000)the Fundamental Research Funds for the Central Universities(No.63221411).
文摘A single particle aerosol mass spectrometer(SPAMS)was used to accurately quantify the contribution of vehicle non-exhaust emissions to particulate matter at typical road environment.The PM_(2.5),black carbon,meteorological parameters and traffic flow were recorded during the test period.The daily trend for traffic flow and speed on TEDA Street showed obvious“M”and“W”characteristics.6.3 million particles were captured via the SPAMS,including 1.3 million particles with positive and negative spectral map information.Heavy Metal,High molecular Organic Carbon,Organic Carbon,Mixed Carbon,Elemental Carbon,Rich Potassium,Levo-rotation Glucose,Rich Na,SiO_(3) and other categories were analyzed.The particle number concentration measured by SPAMS showed a good linear correlation with the mass concentrations of PM_(2.5) and BC,which indicates that the particulate matter captured by the SPAMS reflects the pollution level of fine particulate matter.EC,ECOC,OC,HM and crustal dust components were found to show high values from 7:00–9:00 AM,showing that these chemical components are directly or indirectly related to vehicle emissions.Based on the PMF model,7 major factors are resolved.The relative contributions of each factor were determined:vehicle exhaust emission(44.8%),coal-fired source(14.5%),biomass combustion(12.2%),crustal dust(9.4%),ship emission(9.0%),tires wear(6.6%)and brake pads wear(3.5%).The results show that the contribution of vehicle non-exhaust to particulate matter at roadside environment is approximately 10.1%.Vehicle non-exhaust emissions are the focus of future research in the vehicle pollutant emission control field.
文摘基于心里声学客观参量的GA-BP声品质预测模型能够准确的预测稳态排气噪声声品质。对于非稳态噪声研究,引入正则化非稳态回归技术(RNR)优化计算维格纳-威尔分布(WVD)的时频方法,建立新的声品质参量SQP-RW(Sound Quality Parameter Base on RNR-WVD),用此参量替换掉与满意度相关性较小的客观参量。同时,以Morlet小波基函数作为隐含层结点的传递函数构建小波神经网络(Wavelet Neural Network,WNN),并用GA优化小波神经网络层间的权值和阈值,构造出GA-WNN并用于非稳态排气噪声声品质预测。结果表明:GA-WNN在非稳态排气噪声声品质预测上比GA-BP神经网络更加准确;引入SQP-RW参量,模型具有更高的精度,更能体现出非稳态信号特征及声品质特点。
