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A feasibility study of mapping light-absorbing carbon using a taxi fleet as a mobile platform Cover

A feasibility study of mapping light-absorbing carbon using a taxi fleet as a mobile platform

Open Access
|Jan 2014

Figures & Tables

Fig. 1

Map of the roads sampled in the Stockholm metropolitan region.

Fig. 2

Frequency-of-occurrence histograms of 1-min MLAC measurements conducted on-board four taxis (individual plots a–d, composite plot e) in the period 7–17 November 2011. The normal density function is also displayed in the composite plot (black line).

Table 1. MLAC descriptive statistics for every taxi and all data together (1-min values), along with fixed site values (hourly data) in the period 7–17 November 2011

MLAC [µg m−3]Taxi 1Taxi 2Taxi 3Taxi 4All taxisHornsgatanTorkelAspvretenArithmetic mean2.32.32.53.02.43.30.90.3Median1.41.41.61.71.52.70.70.25th percentile0.30.30.30.30.30.60.30.195th percentile6.46.97.38.97.38.62.00.8Maximum103.980.248.669.0103.916.03.81.3Arithmetic SD3.73.43.04.63.62.50.60.2MAD0.70.80.81.00.81.70.30.1Skewness [–]11.57.24.86.58.11.52.01.7# samples708071167107415025 453245245243
Fig. 3

Diurnal variation of MLAC concentrations (median: solid line, interquartile range: grey area) for all mobile measurements (a), and for three fixed stations (b) in the period 7–17 November 2011. Number of 1-min mobile samples included per hour for the diurnal calculation is also displayed.

Table 2. Vehicle speed descriptive statistics using 1-min median measurements for every taxi and all data together in the period 7–17 Nov 2011

Vehicle speed [km h−1]Taxi 1Taxi 2Taxi 3Taxi 4All taxisArithmetic mean21.424.826.028.224.4Median5.912.413.717.911.75th percentile0.10.10.10.10.195th percentile90.7100.4104.3100.399.2Arithmetic SD29.231.532.432.231.2MAD5.812.313.417.711.6Skewness [–]1.61.41.41.21.4# samples610954304807241718 763
Fig. 4

Box plots of MLAC concentrations (temporally adjusted) classified by the corresponding vehicle speed in the period 7–17 November 2011. Box represents interquartile range and whiskers are lines that extend from the 5th to 95th percentile. Median is indicated by the line across the box and the cross marks the mean value. Percentages in the top line indicate the relative frequency of occurrence for each category.

Fig. 5

MLAC concentrations as a function of traffic rates: (a) daily, all vehicles, (b) daily, diesel vehicles, and (c) hourly, gasoline vehicles in the period 7–17 November 2011. Represented are 5th, 25th, 50th, 75th, and 95 percentiles, and mean (x) values.

Fig. 6

Spatial distribution of temporally adjusted MLAC concentration in the Stockholm metropolitan area for (a) daytime (06:00–18:00), and (b) night-time (18:00–06:00) in the period 7–17 November 2011.

Fig. 7

Boxplot of 1-min vehicle speed, daily (TR) and hourly (TRh) traffic rate, and 1-min MLAC concentrations classified into four categories: local roads, street canyon, main roads, and highways in the period 7–17 November 2011. Represented are 5th, 25th, 50th, 75th, and 95 percentiles, and mean (x) values.

Table 3. Descriptive statistics (1-min values) of temporally adjusted MLAC concentrations for five road types in the period 7–17 Nov 2011

MLAC (µg m−3)TunnelHighwayMain roadCanyon streetLocal roadArithmetic mean12.93.22.42.42.1Median7.52.11.71.81.35th percentile0.90.50.40.50.395th percentile40.19.76.77.06.1Arithmetic SD13.83.73.12.43.3MAD5.11.20.80.80.7# samples (%)121141054
Fig. 8

Upper panel: Diurnal variation of MLAC concentrations (median values) for four roadway groups (canyon, main roads, local roads, and highways) in the period 7–17 November 2011. Middle panel: Median (black line) and 5th to 95th percentile (grey area) MLAC concentrations for tunnels in the same period. Bottom panel: Relative frequency per hour for each roadway group.

Fig. 9

Case studies: 1-min MLAC time series measured on board taxis together with vehicle speed: (a) Long driving inside Södra Länken tunnel (grey area). (b) Short driving inside Söderledstunneln tunnel (grey area). (c) Stop-and-go driving on Sveavägen street (inner city) due to traffic lights at several intersections, x indicates canyon structure. (d) Taxi parked on a local road very close to a hamburger grill. (e) High speed driving on E20 highway. (f) High speed driving on E4 highway.

Table 4. Correlation matrix between mobile MLAC and numerical independent variables, with r>0.60 displayed in bold

r[–]TRTRdTRhRSVSMLACHMLACTMLACATRHWSPPopTRd0.92TRh0.760.76RS0.690.740.58VS0.530.620.470.72MLACH−0.05−0.030.23−0.02−0.02MLACT−0.03−0.030.09−0.02−0.020.60MLACA0.030.020.000.030.030.260.66T0.010.000.060.01−0.020.550.360.29RH0.040.04−0.120.020.04−0.50−0.140.05−0.56WS0.020.030.030.000.00−0.12−0.36−0.03−0.03−0.04P−0.05−0.02−0.03−0.030.03−0.16−0.08−0.39−0.450.48−0.48Pop−0.17−0.21−0.15−0.29−0.26−0.040.00−0.02−0.020.040.010.03MLAC0.170.160.290.120.130.270.200.010.13−0.16−0.090.02−0.02
Language: English
Page range: 23533 - 23533
Submitted on: Dec 9, 2013
Accepted on: Mar 14, 2014
Published on: Jan 1, 2014
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2014 Patricia Krecl, Christer Johansson, Johan Ström, Boel Lövenheim, Jean-Charles Gallet, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.