نبذة مختصرة : Data associated with the MAGIC (Managing Air for Greener Inner Cities) signal time study at the London Road / Garden Row junction (London, UK) in September 2019. Two different signal timings were tested, one being a 48s cycle and the other one being a 96s cycle. A PTV Vissim microsimulation traffic model together with an instantaneous NOx vehicle emissions model, called NLR model, were used to model the impact of the change in signal timings at the junction. This dataset includes the results from the NLR NOx emissions model. The outputs from the microsimulation traffic model could not be included due to commercial reasons. Furthermore, the two signal timings were tested in real life over a 2 week period in September 2019 (weekdays only from 12pm to 4pm). Sensor data for various air pollutants (NOx, NO2, black carbon, lung deposited surface area - ultrafine particles, CO2) was collected together with anemometer data giving wind speed and wind direction. Seven Raspberry Pi cameras were installed to understand the traffic conditions. This dataset contains the following files: - NLR_output_A-48s.csv (NOx emissions model outputs for 48s cycle) - NLR_output_B-96s.csv (NOx emissions model outputs for 96s cycle) - NLR_outputs_Readme.txt (giving further information about the above NLR output files) - Traffic_counts_1min.xlsx (1 minute traffic counts obtained from the video footage using the convolutional neural network YOLO v3, includes a Readme tab with further information) - Sensor_MeteorologyData_1min.xlsx (1 minute air pollution and meteorological data, includes a Readme tab with further information) - Sensor_MeteorologyData_1second.xlsx (1 second air pollution and meteorological data, includes a Readme tab with further information) ; Clemence M. A. Le Cornec was supported by Innovate UK (project ref: 103304) and by a Skempton scholarship at the Department of Civil & Environment Engineering at Imperial College London.
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