Characteristics And Source Analysis Of Black Carbon Concentration In Urban Environmental With Mobile Monitoring Platform

Black Carbon（BC）,as a carbon aerosol product from the incomplete combustion of fossil fuels（mainly diesel and coal）and biomass,is an important component of fine particulate matter(PM_2.5)and is currently the second warmed component in the world after CO₂.BC has significant impacts on climate change and human health.In this study,Shanghai,a highly urbanized city,was taken as the research area.A mobile monitoring platform was built using a MA200（micro Aeth（?）MA200）portable black carbon meter and GPS positioning system installed in electric taxis to repeatedly monitor atmospheric BC concentration for 46 times in Minhang District（with sampling transect length of about 60 km）.Three sample belts（with each sampling transect length of about 40 km）were set up to extend northwest,southwest,and southeast with the People’s Square as the center of the city to conduct 9 times of atmospheric BC and CO₂concentration mobile monitoring,to obtain high spatiotemporal resolution atmospheric BC concentration data of the urban environment.We investigated the impact of data processing methods,i.e.,background concentration correction,outlier processing,spatial sampling granularity,and the number of sampling runs on the atmospheric BC concentration monitoring results.The spatiotemporal variation characteristics,potential influencing factors,and source analysis of atmospheric black carbon of the urban environment in Shanghai were carried out.The spatiotemporal correlation characteristics of atmospheric BC with brown carbon（BrC）and CO₂concentrations were analyzed.The main results of this study are as follows:（1）Background concentration correction can enhance the contrast between high and low values of BC in urban ambient air.After correction,the coefficient of variation of BC concentration can be nearly doubled.It was recommended to use a smoothing method with a 10-minute time window to characterize the background concentration.During outlier processing,the center moving average（CMA）algorithm had the highest peak BC concentration reduction,with the number of negative values reduced from 326 to 1.It can effectively remove abnormal noise while preserving the characteristics of the microenvironment,which can better reflect the true situation of BC pollution.As the spatial sampling granularity continued to increase,the accuracy of BC concentration hot spot area recognition continued to decrease.When the spatial sampling granularity was 200 m,the spatial variation feature retention effect of BC concentration was the best（the variation coefficient decreased by at least 111.82%）.In the representative evaluation of the sampling runs for mobile monitoring platforms,expanding the error threshold range or preprocessing raw data can reduce the sampling runs required to achieve convergence by more than 50%.The number of repeated sampling runs required for street canyon areas with high variability was approximately twice that of park areas.In order to obtain spatially representative data during mobile monitoring,it was necessary to appropriately increase the number of mobile sampling runs for areas with high BC concentration variability.（2）Based on the mobile monitoring platform,the average near-ground BC concentration in Minhang District,Shanghai was 3.62±2.96μg·m^-3.There was a significant seasonal variation（winter>spring>autumn>summer）,and the distribution of atmospheric BC hot spots in different seasons presented a similar pattern.The BC concentration on working days was 43.66%higher than that on non-working days.The area exhibiting high variability coincided with the region characterized by high level of BC concentration.The increase in BC concentration was related to traffic accidents in road sections,such as the passing of large diesel vehicles and traffic congestion,which can lead to the emergence of short-term BC concentration peaks.The order of BC concentration in different functional areas was industrial area>commercial area>school>village>park>residential area,with an average BC concentration difference of 3.63μg·m^-3between industrial area and residential area.When the buffer distance was between 500 and 2000 m,BC concentration decreased with the increase of vegetation coverage,indicating that dense vegetation in a large range could inhibit BC diffusion.The average value of Absorption（?）ngstr（?）m Exponent（AAE）was 1.00±0.11,which was closer to the AAE_FFindex of fossil fuel combustion emissions BC.The contributions of fossil fuel emissions,fossil fuel and biomass combustion mixed sources,and biomass combustion sources to BC sources were 43.63%,43.24%,and 13.13%,respectively,indicating that vehicle generated fossil fuel emissions were the main source of atmospheric BC concentration in Minhang District,Shanghai.（3）The atmospheric BC,BrC,and CO₂concentrations in Shanghai with mobile monitoring were 3.22±3.50μg·m^-3,0.17±0.25μg·m^-3and 441.17±31.51 ppm,respectively.The average relative contribution of BrC to mixed light absorption was about 5.17%,implying that BC was the main carbon aerosol that played a light absorption role in the atmosphere.Human commuting activities increased traffic flow on weekdays,with BC concentrations higher on weekdays than on non-weekdays.While on non-weekdays,traffic flow decreased,biomass combustion increased,and BrC concentrations were lower on weekdays than on non-weekdays.Due to the sampling route mainly passing through schools,residential areas,etc.,where the density of pedestrian flow was high on non-working days,the CO₂concentration was slightly higher on non-working days than on working days.The atmospheric BC concentration presented urban(2.61±1.51μg·m^-3)<suburban(3.19±1.17μg·m^-3),which was related to the restriction measures for heavy diesel vehicles in urban areas of Shanghai,and the spatial distribution of BrC concentration was similar to BC.The CO₂concentration was higher in urban areas（441.70±14.90 ppm）than in suburban areas（440.40±20.62 ppm）.As the distance from the city center increased,BC and BrC concentrations first increased and then decreased,while CO₂concentrations generally decreased.As the main pollution sources were road traffic and coal combustion emissions,BC and BrC had similar sources and spatial distribution characteristics,with a significant positive correlation（R²=0.49,P<0.01）.However,BC was far more sensitive to traffic than CO₂.The passing of diesel vehicles and other vehicles can cause a sudden surge in BC concentration,leading to a significant difference between BC and CO₂,resulting in a small correlation.