Accurately quantifying the concentration and transport flux of atmospheric fine particu-late matter(PM_(2.5))is vital when attempting to thoroughly identify the pollution formation mechanism.In this study,the mobile l...Accurately quantifying the concentration and transport flux of atmospheric fine particu-late matter(PM_(2.5))is vital when attempting to thoroughly identify the pollution formation mechanism.In this study,the mobile lidar measurements in Beijing on heavily polluted days in December from 2015 to 2018 are presented.The lidar was mounted on a vehicle,which could perform measurements along designated routes.On the basis of mobile lidar mea-surements along closed circuits of the 6th Ring Road around Beijing,the spatial distribution and transport flux of PM_(2.5) in Beijing were determined with information of wind field.In the spatial distribution,both the concentration and transport of PM_(2.5) were revealed to be more significant in the southern section of Beijing.The regional transport layer at heights<1.3 km plays an important role in pollution formation.The maximum transport flux reached 1600μg/(m^(2)*sec)on 11 December 2016.With the aerosol boundary layer height determined from the image edge detection(IED)method,the inter-annual variations of the aerosol boundary layer height(ABLH)were also analysed.The ABLH decreased from 0.73 to 0.46 km during the same heavy pollution period from 2015 to 2018.Increasingly adverse aerosol boundary layer(ABL)meteorological factors,including lower ABLH,light winds,temperature inversions,and accumulated moisture,have become necessary for pollution formation in Beijing.展开更多
The objective of this research was development of a statistical model for estimating vehicle tailpipe emissions of carbon dioxide (CO2). Forty hours of second-by-second emissions data (144,000 data points) were collec...The objective of this research was development of a statistical model for estimating vehicle tailpipe emissions of carbon dioxide (CO2). Forty hours of second-by-second emissions data (144,000 data points) were collected using an On-Board emissions measurement System (Horiba OBS-1300) installed in a 2007 Dodge Charger car. Data were collected for two roadway types, arterial and highway, around Arlington, Texas, and two different time periods, off peak and peak (both a.m. and p.m.). Multiple linear regression and SAS software were used to build emission models from the data, using predictor variables of velocity, acceleration and an interaction term. The arterial model explained 61% of the variability in the emissions;the highway model explained 27%. The arterial model in particular represents a reasonably good compromise between accuracy and ease of use. The arterial model could be coupled with velocity and acceleration profiles obtained from a micro-scale traffic simulation model, such as CORSIM, or from field data from an instrumented vehicle, to estimate percent emission reductions associated with local changes in traffic system operation or management.展开更多
基金This work was supported by the National Key Project of MOST(Nos.2017YFC0213002,2018YFC0213101,and 2018YFC020101)the Doctoral Scientific Research Foundation of Anhui University(No.Y040418191)the open fund of the Key Laboratory of Environmental Optics and Technology,Chinese Academy of Sciences(No.K130462001)。
文摘Accurately quantifying the concentration and transport flux of atmospheric fine particu-late matter(PM_(2.5))is vital when attempting to thoroughly identify the pollution formation mechanism.In this study,the mobile lidar measurements in Beijing on heavily polluted days in December from 2015 to 2018 are presented.The lidar was mounted on a vehicle,which could perform measurements along designated routes.On the basis of mobile lidar mea-surements along closed circuits of the 6th Ring Road around Beijing,the spatial distribution and transport flux of PM_(2.5) in Beijing were determined with information of wind field.In the spatial distribution,both the concentration and transport of PM_(2.5) were revealed to be more significant in the southern section of Beijing.The regional transport layer at heights<1.3 km plays an important role in pollution formation.The maximum transport flux reached 1600μg/(m^(2)*sec)on 11 December 2016.With the aerosol boundary layer height determined from the image edge detection(IED)method,the inter-annual variations of the aerosol boundary layer height(ABLH)were also analysed.The ABLH decreased from 0.73 to 0.46 km during the same heavy pollution period from 2015 to 2018.Increasingly adverse aerosol boundary layer(ABL)meteorological factors,including lower ABLH,light winds,temperature inversions,and accumulated moisture,have become necessary for pollution formation in Beijing.
文摘The objective of this research was development of a statistical model for estimating vehicle tailpipe emissions of carbon dioxide (CO2). Forty hours of second-by-second emissions data (144,000 data points) were collected using an On-Board emissions measurement System (Horiba OBS-1300) installed in a 2007 Dodge Charger car. Data were collected for two roadway types, arterial and highway, around Arlington, Texas, and two different time periods, off peak and peak (both a.m. and p.m.). Multiple linear regression and SAS software were used to build emission models from the data, using predictor variables of velocity, acceleration and an interaction term. The arterial model explained 61% of the variability in the emissions;the highway model explained 27%. The arterial model in particular represents a reasonably good compromise between accuracy and ease of use. The arterial model could be coupled with velocity and acceleration profiles obtained from a micro-scale traffic simulation model, such as CORSIM, or from field data from an instrumented vehicle, to estimate percent emission reductions associated with local changes in traffic system operation or management.
