1 Introduction
2 Defining the problem
-
These devices are associated with errors.
-
Using this device a few parameters such as instantaneous velocity can be measured with limits and it is not possible to consider factors, as well as the entire fleet of transportation.
-
Preparation and maintenance of these tools is very expensive and not applicable in this country [4].
3 Research
3.1 Intersection profile
3.2 The volume of vehicles
3.3 The average speed of the fleet
3.4 Driving cycle
3.5 Meteorological data
3.6 Variables
3.6.1 Fleet technology
3.6.2 Air conditioning systems
3.6.3 Fuel parameters
-
The overall quality of fuel: Medium
-
The amount of lead in fuel: zero (negligible)
-
The amount of sulfur in the fuel: between 50 and 300 ppm
-
The benzene in the fuel: between 5.0 and 5.1% (average)
-
The oxygen content of gasoline (fuel additive that increases the oxygen content of fuel and improves pollution): zero
4 Results
4.1 The results of modelling
Spring 2015 | Winter 2015 | ||||
---|---|---|---|---|---|
NOX (G/Km) | CO (G/Km) | Day 2015 | NOX (G/Km) | CO (G/Km) | Day 2015 |
0.63 | 7.47 | April 15 | 0.7 | 8.35 | January 1 |
0.57 | 6.76 | April 16 | 0.61 | 7.32 | January 3 |
0.57 | 6.76 | April 17 | 0.64 | 7.71 | January 5 |
0.66 | 7.89 | April 19 | 0.55 | 6.65 | January 6 |
0.54 | 6.45 | April 20 | 0.7 | 8.35 | January 10 |
0.6 | 7.61 | April 21 | 0.77 | 9.78 | January 11 |
0.57 | 6.76 | April 22 | 0.72 | 8.59 | January 12 |
0.7 | 8.35 | April 23 | 0.62 | 7.75 | January 20 |
0.79 | 9.46 | April 24 | 0.75 | 8.87 | January 21 |
0.57 | 6.77 | April 25 | 0.54 | 6.45 | January 23 |
0.83 | 12.7 | April 30 | 0.6 | 7.1 | January 24 |
0.6 | 7.1 | May 1 | 0.6 | 7.61 | January 25 |
0.7 | 8.35 | May 3 | 0.63 | 7.47 | January 26 |
0.63 | 7.47 | May 4 | 0.7 | 8.35 | January 30 |
0.6 | 7.1 | May 7 | 0.66 | 7.89 | January 31 |
0.59 | 9.06 | May 8 | 0.75 | 8.87 | February 4 |
0.69 | 10.6 | May 12 | 0.6 | 7.61 | February 6 |
0.63 | 7.47 | May 13 | 0.61 | 7.32 | February 7 |
0.54 | 8.27 | May 14 | 0.64 | 7.71 | February 8 |
0.79 | 9.46 | May 15 | 0.61 | 7.32 | February 12 |
0.66 | 7.89 | May 16 | 0.58 | 6.97 | February 13 |
0.66 | 7.89 | May 17 | 0.6 | 7.1 | February 14 |
0.63 | 7.47 | May 18 | 0.6 | 7.61 | February 16 |
0.63 | 7.47 | May 19 | 0.49 | 6.29 | February 17 |
0.54 | 6.45 | May 20 | 0.53 | 6.36 | February 18 |
0.63 | 7.47 | May 21 | 0.57 | 7.23 | February 22 |
0.6 | 7.1 | May 25 | 0.7 | 8.35 | February 24 |
– | – | – | 0.63 | 7.47 | February 25 |
– | – | – | 0.63 | 7.47 | February 26 |
– | – | – | 0.6 | 7.1 | February 27 |
– | – | – | 0.6 | 7.1 | March 2 |
– | – | – | 0.54 | 6.45 | March 3 |
4.2 The results of field measurement
Spring 2015 | Winter 2015 | ||||||
---|---|---|---|---|---|---|---|
NO [ppb] | NO2 [ppb] | CO [ppm] | Day 2015 | NO [ppb] | NO2 [ppb] | CO [ppm] | Day 2015 |
32.6 | 53.4 | 3.05 | April 15 | 72.22 | 48.42 | 3.6 | January 1 |
53.46 | 36.15 | 2.35 | April 16 | 34.74 | 41.57 | 3.22 | January 3 |
47.09 | 36.4 | 2.38 | April 17 | 31.73 | 53.5 | 3.45 | January 5 |
49.4 | 43.41 | 2.92 | April 19 | 20.78 | 59.96 | 2.89 | January 6 |
52.69 | 31.5 | 2.03 | April 20 | 31.8 | 73.82 | 4.1 | January 10 |
39.86 | 51.57 | 2.86 | April 21 | 32.2 | 79.69 | 4.3 | January 11 |
42.54 | 42.72 | 2.55 | April 22 | 55.41 | 64.61 | 3.77 | January 12 |
11.2 | 68.6 | 3.64 | April 23 | 44.9 | 63.4 | 3.63 | January 20 |
24.78 | 71.45 | 3.99 | April 24 | 51.25 | 75.5 | 4.4 | January 21 |
37.72 | 41.71 | 2.37 | April 25 | 25.81 | 38.91 | 2.87 | January 23 |
19.8 | 70.12 | 4.65 | April 30 | 38.21 | 38.3 | 3.3 | January 24 |
37.8 | 39.81 | 2.4 | May 1 | 53.07 | 34 | 3.33 | January 25 |
27.13 | 59.7 | 3.59 | May 3 | 63.9 | 46.72 | 3.1 | January 26 |
22:25 | 56.5 | 3.32 | May 4 | 42.7 | 51.1 | 3.79 | January 30 |
19.7 | 57.41 | 2.85 | May 7 | 22.3 | 65.69 | 3.49 | January 31 |
25.97 | 43.5 | 2.53 | May 8 | 54.4 | 76.85 | 3.78 | February 4 |
29.74 | 60.03 | 3.2 | May 12 | 11.6 | 57 | 3.38 | February 6 |
38.1 | 53.17 | 2.78 | May 13 | 57.81 | 33.75 | 3.39 | February 7 |
55.35 | 33.3 | 2.15 | May 14 | 16.93 | 53.4 | 3.74 | February 8 |
17.98 | 77.51 | 3.54 | May 15 | 36.69 | 51.1 | 3.57 | February 12 |
32.6 | 52.12 | 2.41 | May 16 | 28.8 | 53.1 | 2.9 | February 13 |
27.7 | 63.4 | 2.75 | May 17 | 33.2 | 57.1 | 3.05 | February 14 |
21.2 | 64.4 | 3.33 | May 18 | 34.3 | 61.1 | 3.22 | February 16 |
37.5 | 45.2 | 2.88 | May 19 | 39.1 | 35.5 | 2.81 | February 17 |
29.1 | 47.3 | 1.92 | May 20 | 37.1 | 32.1 | 2.78 | February 18 |
21.1 | 64.3 | 3.08 | May 21 | 41.1 | 51.2 | 3.51 | February 22 |
25.2 | 57.7 | 2.1 | May 25 | 58 | 66.6 | 4.01 | February 24 |
– | – | – | – | 55.3 | 42.1 | 3.7 | February 25 |
– | – | – | – | 59.1 | 38.7 | 3.61 | February 26 |
– | – | – | – | 42.2 | 35.5 | 3.2 | February 27 |
– | – | – | – | 18.9 | 49.8 | 3.5 | March 2 |
– | – | – | – | 49.1 | 32.2 | 2.67 | March 3 |
4.3 Data comparison and results evaluation
-
The difference between the concentrations of the average CO pollutants has been 1.2 and 1.6 times for winter and spring repectively.
-
According to Table 4 this difference for NOX emissions has been 1.7 and 1.9 times for winter and spring respectively.
-
The differences are for the fact that the measuring device of this study is the environmental gauge device and evaluate the pollutant after withdrawal of supply and decreased with ambient air and it cannot measure it as it comes out of the exhaust. The device used in this study was installed on the edge of the intersection and the pollutants are spreaded and decreased before reaching the sensor. It is observed that the difference in both pollutants is higher in spring, the reason of which might be the wind and increased dispersion of pollutants.
-
-
Since the objective of using this model in this research is descriptive analysis and in order to evaluate it, the model sensitivity should be analyzed and the amount of following changes by the model must be estimated. When the results of field measurements differ from different parameters, the model must follow these alterations as well. One of the best ways for this sensitivity analysis is measuring the correlation of the model results and real perceptions. The correlation coefficient is applied to specify the sensitivity of two data series versus each other in face of changes as it presents the severity of relation, correlation and proportionality of the data. As the value approaches 1 it showes higher sensitivity of the data in a direct manner. In this study the correlation between CO concentrations in both methods was 0.86 in spring and 0.88 in winter. Also correlation between NOX concentrations in both methods was 0.84 in spring and 0.85 in winter. The results of the model were connected with the results of measurement and change by converting different parameters with a harmonized, linear trend with high regression coefficient.
Winter | Spring | ||||||
---|---|---|---|---|---|---|---|
Day 2015 | Modelling | Field data | Data difference of models (equal) | Day 2015 | Modelling | Field data | Data difference of models (equal) |
CO g/l | CO g/l | CO g/l | CO g/l | ||||
January 1 | 47.11 | 33.969 | 1.39 | April 15 | 42.998 | 28.881 | 1.49 |
January 3 | 33.839 | 30.457 | 1.11 | April 16 | 32.731 | 22.354 | 1.46 |
January 5 | 42.473 | 32.585 | 1.3 | April 17 | 33.632 | 22.635 | 1.49 |
January 6 | 29.716 | 27.394 | 1.08 | April 19 | 48.539 | 27.673 | 1.75 |
January 10 | 51.747 | 38.563 | 1.34 | April 20 | 33.69 | 19:35 | 1.74 |
January 11 | 60.639 | 40.392 | 1.5 | April 21 | 43.15 | 27.115 | 1.59 |
January 12 | 50.766 | 35.534 | 1.43 | April 22 | 36.485 | 24.225 | 1.51 |
January 20 | 46.173 | 34.245 | 1.35 | April 23 | 51.19 | 34.337 | 1.49 |
January 21 | 55.785 | 41.305 | 1.35 | April 24 | 63.302 | 37.554 | 1.69 |
January 23 | 27.238 | 27.208 | 1 | April 25 | 36.698 | 22.541 | 1.63 |
January 24 | 33.116 | 31.198 | 1.06 | April 30 | 83.993 | 43.582 | 1.93 |
January 25 | 39.935 | 31.476 | 1.27 | May 1 | 38.478 | 22.822 | 1.69 |
January 26 | 39.512 | 29.345 | 1.35 | May 3 | 52.118 | 33.876 | 1.54 |
January 30 | 52.674 | 35.718 | 1.47 | May 4 | 44.492 | 31.383 | 1.42 |
January 31 | 47.488 | 32.954 | 1.44 | May 7 | 34.693 | 27.022 | 1.28 |
February 4 | 53.617 | 35.626 | 1.5 | May 8 | 43.692 | 24.038 | 1.82 |
February 6 | 38.92 | 31.938 | 1.22 | May 12 | 62.948 | 30.272 | 2.08 |
February 7 | 36.279 | 32.03 | 1.13 | May 13 | 43.496 | 26.37 | 1.65 |
February 8 | 36.137 | 35.258 | 1.02 | May 14 | 40.622 | 20.478 | 1.98 |
February 12 | 33.839 | 33.692 | 1 | May 15 | 61.409 | 33.415 | 1.84 |
February 13 | 30.821 | 27.487 | 1.12 | May 16 | 46.086 | 22.915 | 2.01 |
February 14 | 34.22 | 28.881 | 1.18 | May 17 | 47.488 | 26.091 | 1.82 |
February 16 | 34.012 | 30.457 | 1.12 | May 18 | 44.824 | 31.476 | 1.42 |
February 17 | 27.676 | 26.65 | 1.04 | May 19 | 42.168 | 27.301 | 1.54 |
February 18 | 28.995 | 26.37 | 1.1 | May 20 | 33.69 | 18.314 | 1.84 |
February 22 | 38.745 | 33.139 | 1.17 | May 21 | 43.662 | 29.16 | 1.5 |
February 24 | 52.303 | 37.738 | 1.39 | May 25 | 38.793 | 20.008 | 1.94 |
February 25 | 40.508 | 34.89 | 1.16 | – | – | – | – |
February 26 | 41.504 | 34.061 | 1.22 | – | – | – | – |
February 27 | 35.009 | 30.272 | 1.16 | – | – | – | – |
March 2 | 31.855 | 33.046 | 0.96 | – | – | – | – |
March 3 | 28.242 | 25.345 | 1.11 | – | – | – | – |
r = 0.88 |
r = 0.86 |
Winter | Spring | ||||||
---|---|---|---|---|---|---|---|
Day 2015 | Modelling | Field data | Data difference of models (equal) | Day 2015 | Modelling | Field data | Data difference of models (equal) |
NOX g/l | NOX g/l | NOX g/l | NOX g/l | ||||
January 1 | 2.461 | 1.48 | 1.66 | April 15 | 2.264 | 1.161 | 1.95 |
January 3 | 1.759 | 0.998 | 1.76 | April 16 | 1.719 | 1.109 | 1.55 |
January 5 | 2.215 | 1.151 | 1.92 | April 17 | 1.766 | 1.048 | 1.69 |
January 6 | 1.547 | 1.144 | 1.35 | April 19 | 2.553 | 1.177 | 2.17 |
January 10 | 2.704 | 1.461 | 1.85 | April 20 | 1.764 | 1.031 | 1.71 |
January 11 | 2.995 | 1.553 | 1.93 | April 21 | 2.108 | 1.208 | 1.75 |
January 12 | 2.653 | 1.559 | 1.7 | April 22 | 1.916 | 1099 | 1.74 |
January 20 | 2.291 | 1.436 | 1.6 | April 23 | 2.674 | 1176 | 2.27 |
January 21 | 2.93 | 1.679 | 1.75 | April 24 | 3.317 | 1.354 | 2.45 |
January 23 | 1.426 | 0.868 | 1.64 | April 25 | 1.924 | 1.036 | 1.86 |
January 24 | 1.736 | 0.982 | 1.77 | April 30 | 3.426 | 1.278 | 2.68 |
January 25 | 1.951 | 1.065 | 1.83 | May 1 | 2.017 | 1.007 | 2 |
January 26 | 2.08 | 1.374 | 1.51 | May 3 | 2.723 | 1199 | 2.27 |
January 30 | 2.752 | 1.222 | 2.25 | May 4 | 2.342 | 1.102 | 2.12 |
January 31 | 2.497 | 1.244 | 2.01 | May 7 | 1.818 | 1.094 | 1.66 |
February 4 | 2.817 | 1.739 | 1.62 | May 8 | 1.773 | 0.943 | 1.88 |
February 6 | 1.901 | 1.002 | 1.9 | May 12 | 2.571 | 1.234 | 2.08 |
February 7 | 1.885 | 1.109 | 1.7 | May 13 | 2.29 | 1.215 | 1.88 |
February 8 | 1.884 | 0.998 | 1.89 | May 14 | 1.659 | 1.085 | 1.53 |
February 12 | 1.759 | 1.163 | 1.51 | May 15 | 3.218 | 1.383 | 2.33 |
February 13 | 1.607 | 1.119 | 1.44 | May 16 | 2.424 | 1.146 | 2.11 |
February 14 | 1.794 | 1225 | 1.46 | May 17 | 2.497 | 1.269 | 1.97 |
February 16 | 1.661 | 1.297 | 1.28 | May 18 | 2.36 | 1.214 | 1.94 |
February 17 | 1.354 | 0.95 | 1.43 | May 19 | 2.22 | 1.084 | 2.05 |
February 18 | 1.519 | 0.877 | 1.73 | May 20 | 1.764 | 1.038 | 1.7 |
February 22 | 1.9 | 1.209 | 1.57 | May 21 | 2.299 | 1.214 | 1.89 |
February 24 | 2.733 | 1.614 | 1.69 | May 25 | 2.033 | 1.16 | 1.75 |
February 25 | 2.133 | 1.21 | 1.76 | – | – | – | – |
February 26 | 2.185 | 1.197 | 1.83 | – | – | – | – |
February 27 | 1.835 | 0.979 | 1.87 | – | – | – | – |
March 2 | 1.67 | 0.963 | 1.73 | – | – | – | – |
March 3 | 1.478 | 1.001 | 1.48 | – | – | – | – |
r = 0.85 |
r = 0.84 |