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ARTICLE IN PRESS

SCIENCE OF THE TOTAL ENVIRONMENT XX (2008) XXXXXX

3

presented in Table 1. It shows that a significant proportion of total VKT are located in the speed bins between 20 to 40 km/h in Beijing urban area.

  • 3.

    Result and discussion

    • 3.1.

      Grid-based emission inventory

When the vehicle activity and speed correlated emission factors are acquired, the grid-based emission inventory can be developed according to Eq. (1). The grid-based vehicle emis- sion inventories of HC, CO and NOx for the Beijing urban area in 2005 are shown in Figs. 35, respectively.

The figures show that the distribution of vehicle emissions in Beijing's urban area is not uniform and the emissions are greater in urban core as compared to surrounding areas. This is due to the following reasons: (1) greater traffic flow and vehicle density in the urban center; (2) a road system that is over- burdened causing vehicles to operate under difficult condi- tions of low speed and frequent acceleration, deceleration and idle, that leads to high emission rates of the pollutants. The

radial roads with heavy traffic across some grids outside the urban core area also contribute to high emission rates in these grids.

Grid-based emissions may be aggregated to calculate the total vehicular emissions. This shows that vehicular emis- sions of HC, CO and NOx are respectively 13.33 × 104,

    • 100.02

      ×104 and 7.55×104 tons for Beijing urban area in 2005.

    • 3.2.

      Impact of vehicle activity on emission estimations

For the macro-scale approach, the average network speed is used to calculate an average emission factor for the whole city in China. The VKT of various vehicle types are usually acquired through field survey (e.g. parking lot survey and questionnaire survey). Total emissions are then estimated by multiplying total VKT by the average emission factor. Lin

0.00%

0.00%

0.00%

0.00%

0.00%

0.64%

0.35%

0.29%

0.28%

0.72%

0.72%

0.55%

1.43%

1.11%

1.51%

2.66%

2.64%

2.73%

5.47%

3.89%

5.15%

8.32%

8.25%

8.85%

14.72%

11.94%

14.05%

18.47%

18.43%

20.37%

23.51%

20.38%

23.73%

27.69%

27.64%

27.62%

16.88%

15.77%

17.55%

18.64%

18.55%

17.69%

8.18%

9.54%

8.17%

7.95%

7.97%

6.14%

4.17%

4.68%

4.88%

3.72%

3.69%

4.00%

4.24%

4.46%

5.73%

3.56%

3.54%

3.17%

3.74%

4.28%

3.83%

2.00%

1.98%

2.27%

5.02%

5.94%

4.27%

1.71%

1.69%

3.19%

1.95%

2.73%

1.75%

0.68%

0.71%

0.87%

1.40%

1.99%

1.21%

1.17%

1.18%

0.71%

3.23%

4.30%

3.39%

0.93%

1.00%

0.27%

5.71%

8.73%

4.49%

1.78%

2.02%

0.93%

Please cite this article as: Wang H, et al, A bottom-up methodology to estimate vehicle emissions for the Beijing urban area, Sci Total Environ (2008), doi:10.1016/j.scitotenv.2008.11.008

Fig. 2 Variation of emission factors with speed: (a) HC, (b) CO, and (c) NOx.

[0,5) [5,10) [10,15) [15,20) [20,25) [25,30) [30,35) [35,40) [40,45) [45,50) [50,55) [55,60) [60,65) [65,70) [70,80) [80,100)

Table 1 VKT distributions of each vehicle class in various speed bins

The geographic vehicle activities were estimated by the Beijing Transportation Research Centre with TransCAD model and traffic investigations. The urban area of Beijing was divided into 2038 1 km×1 km grid cells according to the road distributions. Information provided in each grid cell includes geographic coordinates; road length; average daily traffic flow, speed and VKT for each vehicle type. The VKT distributions of each vehicle type in various speed bins are

Bus

rapidly at first then more slowly. The NOx emission factors,

which are less sensitive to speed changes, follow a parabolic path and tend to decrease to 50 km/h and then increase.

LDT

2.3.

Vehicle activity and spatial distributions

HDT

Taxi

SB

Speed bins (km/h)

PC

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