Title of Example

Example

The negative effects of air pollution on the human health on human beings are well known, from minor and temporary troubles to a number of serious respiratory illnesses. Persons with respiratory illness (asthmatics) have even more increased sensitivity to air pollution. The society has a major cost in all reporting sick and persons on disability. Calculations show the cost even will increase in the future. Nitrogen dioxide from road traffic is one of the major local air pollutants that affect the human health.

One way to decrease the emissions from the road traffic and traffic jams is to try to influence the traffic flow at certain times of the day, or to redirect it to other roads. There are different ways to rearrange the traffic, voluntary or “by force”. One voluntary way is to show the road-users the concentration of the air pollution they are exposed to at given times and locations. This could be done by a short time NO2 concentration forecast from road traffic, presently and 1-6 hours ahead. As a GIS based forecast, Internet produced, it can be used to assist drivers when they plan their journey: At what level is the air pollution right now and will it increase or decrease during the following hours? This way a driver may plan his/her journey in terms of time choice of route, to get as little exposure as possible. One alternative calculation is to estimate the shortest / fastest route, to reduce the exposure as much as possible, or perhaps a combination of the two. A forecast like this might result in road users choosing a smarter way to travel and to produce less emission to the atmosphere.

A forecast system like this needs a lot of in parameters for a trustworthy output.

Figure 1 City map of Göteborg with NOx levels in the streets.

The concentration of air pollution in urban areas depends mainly on local road emission and meteorological factors as wind velocity and wind direction. A good quality weather forecast important as an input to the dispersion model. A forecast 12 hours ahead will make it possible to plan the morning journey in the evening. Also data on the typical traffic variations during the year / month / week and weekdays or holidays for the different streets are needed as input. Data on intensity of traffic in real time, coming from traffic sensors can also be used as input to such a forecasting system. The intensity can be compared to the statistical traffic variation and a forecast of traffic intensity can be calculated. The traffic sensors also detect the speed of the vehicles, of importance since it affects the emissions from the traffic flow.

Our vision is to have a website as a useful tool where road users use this map for planning there travels in Göteborg to avoid high levels of air pollution. A first step could be to produce stationary maps for the morning and afternoon rush hour to publish at the Internet.

Last Updated

13th January 2005