Managing air and noise in the community
Cross River Partnership wanted to explore innovative solutions to monitoring delivery-related noise and air pollution and how this could be used to drive best practice for all stakeholders, from landowners, freight operators and local authorities. A key aim was also to explore the local impact that retiming of deliveries might have.
You can find out more about the project between EMSOL, Cross River Partnership, Cadogan Estates in this webinar.
Attributing noise pollution to delivery-related activity
The study was commissioned on behalf of the Central London Sub-Regional Transport Partnership (CLSRTP) with the popular Pavilion Road, managed by Cadogan Estates, in the Royal Borough of Kensington and Chelsea as the site for this trial project
24 location tags were issued to a wide range of participating business vehicles which made deliveries to Pavillion Road throughout the research period. Noise and air quality monitors were then set up in the delivery drop-off location. This allowed the EMSOL platform to attribute pollution during the day to specific vehicles – allowing for targeted and actionable insights.
Delivery re-timing is seen as a way to reduce congestion by diverting deliveries out of peak times. However, it is essential to understand the air and noise pollution impact that any retiming might have on the local community.
During the project, we found:
- – A correlation was observed between vehicle visits and noise levels on the site.
- – The project was able to show that a combination of noise monitoring and vehicle tracking technology can be used to measure the impact of delivery activity on noise levels.
- – The loudest parts of the day were typically 10am till 2pm.
- – Night time (11pm – 7am) noise levels did not drop below 50dB, which is considered as a moderate annoyance in the WHO guidelines.
- – The PM10 and PM2.5 concentrations at the site were relatively high.
Interested in managing air and noise pollution? Then get in touch and lets discuss how EMSOL can help with targeted and specific insights.
