1. Topic

  Traffic data/sensors

2. Introduction

   

The objective of implementing most measures is to meet local air quality in urban areas.

Traffic data is one of the most important sources of information to receive when working with air quality management systems. Fundamental differences between vehicles, such as weight, engine size and fuel type, are very significant in accounting for variations in emission rates. Recent advances in technology have delivered significant reductions in vehicle emissions. However, they continue to be an important factor in both local air quality and levels of greenhouse gases. The connection between traffic and air pollution is complex and involves a wide range of factors. To discover more knowledge about the traffic speed, distribution of different vehicles, dynamic information etc we must have data…Traffic data are available in every cities (more and less). It can be quite difficult to have access to the data, and if you have access to the data, the format is probably in the wrong format and it can also be difficult to interpret. Using computer software like emission data bases and dispersion models its fundamental to have accurate information from the traffic sensors.


3. Discussion

   

When you have a fleet of vehicles in your town (or area) you must find information that is important for your Air Quality Management System like emission database and dispersion modelling software etc. To calculate emission on an annual basis you must have information about the distribution of the vehicles, traffic network and emission factors etc. When using dispersion calculation models you also must have dynamic data information concerning monthly and daily variation of the traffic (divided in the type of vehicles).

The vehicle exhaust emissions may be influenced in two principal ways: by changing the composition of the traffic or by changing the way in which the vehicles are operated. To have that kind of information you also must have traffic data in real time and historical.

To obtain real time traffic data you must have a well defined data protocol. The protocol will be used initially to exchange traffic measurement data. Traffic measurement data can be both static and dynamic. Static data, e.g. the names of locations which do not change frequently. Dynamic data, e.g. measurements from a location, which changes frequently, sometimes several times a minute. Because of this the data is made available in two ways. Static data is returned on request. Dynamic data is returned on request or subscribed to. If subscribed to, the data will be delivered to the application as soon as it is changed.

Location data consists of static information regarding measurement locations etc. This includes information on the identity of the location, the coordinates of the location, possible sampling intervals, what parameters are measured, number of lanes etc. A location is the name for a geographical point where traffic measurement is possible.

Traffic measurement data consists of information on measurement location, sampling interval, traffic flow, traffic speed etc.

On the other side, the emission results from EU tests are not always representative for emission behaviour of the modern vehicles in real world driving conditions: measurements have pointed out that new technologies can have a different emission behaviour in real traffic compared to European tests resulting in higher emissions.

In particular Heavy Duty vehicles are the major polluters (especially for NOx and PM) in cities and have a high emission reduction potential as demonstrated in the London Low Emission Zone feasibility study.

Buses of public transport companies have a special role since transport companies can perform a role model function regarding clean transport: besides new diesel fuelled vehicles (Euro 4 starting from 2005), vehicles on alternative fuels and retrofitted vehicles can contribute to a clean city.

The integration between on-board measurements and information on traffic condition should be both used for the evaluation of different situations: data provided by the measurement campaigns will be the scientific base for the evaluation of pollution volumes and will provide quantitative data input to the air quality modelling and impact monitoring.

Representative routes may be chosen in the city area and defined as a representative driving cycle.

The most representative vehicles may be evaluated based on measurements performed driving this cycle: this will make it also possible to compare different technologies in similar conditions and real traffic.

During operation emissions (CO2, CO, NOx, THC, PM), fuel consumption and engine parameters (speed, engine speed, lambda) have to be measured.


4. Recommendation / Conclusion

   
  • Develop data protocol standards for adoption to Air Quality Management Systems.
  • Making available traffic air quality monitoring data via the internet.
  • Working to have a better “understanding” between the disciplines Air Quality Specialists and Traffic Management Specialists.
  • Develop and evaluate traffic control systems which reduce vehicle emissions and effects on air pollutions levels.

5. Examples / Further Reading

   

Traffic parameters monitored in Utrecht

Which traffic parameters do we measure and use as input in our models?


6. Additional Documents / Web Links

   

Other examples in EU Projects:

· CENTAUR: Napels (I) and Barcelona (Spain).

· ENTIRE: Cologne (Germany).

· NGVeurope: Gent, Ixelles and Mechelen (Belgium), Poitiers (France), Augsburg (Germany), Dublin (Ireland), Amstelveen and Haarlem (The Netherlands), Eslov and Gothenburg (Sweden).

· SAGITTAIRE: Besancon (France), Trento (Italy) and Alicante (Spain).

Last Updated


 

25th January 2005

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