1. Introduction [1] Harrison, R.G. (2013) Surv. Geophys.34, 209 [2] Silva, H.G. et al. (2015) J. Aerosol Sci. 85, 42-51. [3] Hoppel, W.A. and Frick, G.M. (1986) Aerosol Sci. Technol. 5, 1-21. [4] Hoppel, W.A. (1985) J. Geophys. Res. 90(D4), 5917-5923. [5] Hõrrak, U. et al. (2008) Atmos. Chem. Phys. 8, 655-675. [6] Lomb, N.R. (1976) Astrophys. Space Scie. 39, 447-462. Experimental methods Two extended measurements were made at Manchester University where PG and PNC were recorded at 1 s intervals. The first campaign took place between 13/07/2015 and 07/08/2015, and the second between 30/10/2015 and 12/11/2015. The second campaign was chosen to incorporate November 5 th when bonfires are traditionally lit and fireworks set off at a number of events in the UK. Measurements were undertaken at a sampling station approximately 20 m above ground level. Particle number concentrations (PNC) were obtained with a Condensation Particle Counter (CPC Model 5.403, Grimm Aerosol) and size distributions with SMPS+C (Grimm Aerosol, July-August data only) and PG data was obtained using an electric field mill meter (JCI 131, Chilworth) on an outdoor balcony. PG will be distorted from a true value due to building topography, so the mean PG for each measurement period was found and the data normalised. As rain can affect PG, rainfall data was collected from Manchester Airport METARs and PG data 1 hour before and after rainfall was discarded. Time series Funding for this work was provided by Leverhulme Trust Research Project Grant RPG-2014-102 and NERC Grant No. NE/J009008/1. MP is funded by a NERC Ph.D. studentship. The authors are grateful to the late John Chubb for his useful and insightful discussions over this topic. He shall be sadly missed. Frequency analysis Discussion and Future Work Figure 2. 1 minute average of (a) Normalised PG, particle number concentration (SMPS and CPC) and attachment rate (AR) recorded from 13/07/2015 to 07/08/2015; (b) Normalised PG and PNC (CPC only) recorded from 30/10/2015 to 12/10/2016 Figure 1. Location of the balcony on the 2 nd floor of Centre for Atmospheric Science, University of Manchester (left) and the JCI 131 field mill meter in-situ (right) Small ions are created in the atmosphere by ground based radioactive decay and solar and cosmic radiation ionising the air. The ionosphere is maintained at a high potential relative to the Earth due to global thunderstorm activity, a current from the ionosphere transfers charge back to the ground through the weakly ionised atmosphere. An atmospheric electric potential gradient (PG) exists between the ionosphere and the ground [1]. PG is related to air conductivity at the Earth’s surface by: PG = J z /  Conductivity is related to the number and electrical mobility of charge carriers (air ions): ± = n ± Z ±, Relationship Between Aerosol Number Size Distribution and Atmospheric Electric Potential Gradient in an Urban Area M D Wright 1, J C Matthews 1,, A Bacak 2, H G Silva 1,3, M Priestley 2, C J Percival 2 & D E Shallcross 1 1 Atmospheric Chemistry Research Group, School of Chemistry, Cantock’s Close, Bristol, BS8 1TS, UK. 2 Centre for Atmospheric Science, School of Earth Atmospheric and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK. 3 Renewable Energies Chair and Institute of Earth Sciences, University of Évora, Portugal Tel: +44 (0)117 3317042, email: j.c.matthews@bristol.ac.uk Ion-aerosol attachment An effective aerosol attachment coefficient  eff can be found from the size distribution [4, 5]. Typical aerosol number concentration N(D) decreases above 100 nm. So peak attachment effect is typically at diameters 200-300 nm. An effective ion sink or attachment rate (AR) was derived from the aerosol number and effective attachment rate that can be used to compare to PG: The ion-aerosol attachment process is described by ion-aerosol population balance equations, e.g.: Where α is the ion recombination coefficient, n the concentration of small ions and N the concentration of aerosols and D the diameter of the aerosols.  ± are ion-aerosol attachment coefficients which modulate ion-aerosol interactions and hence aerosol influence on PG.  ± gets larger with increasing aerosol diameter [3]. Lomb-Scargle periodograms are used to assess spectral analysis of data with gaps [6]. Similar features are seen in PNC and PG spectra for the summer data. 12-h and ~24-h peaks are apparent. Evidence of a weekly cycle is also present, though larger time-series would be required to confirm this. The weekly cycle is a known signature of anthropogenic activity [2]. Acknowledgements Aerosols in the atmosphere act as a sink of air ions with an attachment rate dependent on aerosol size distribution and ion mobility. If the aerosol concentration N is high, ion loss to aerosols dominates: ion concentration decreases, mean electrical mobility of charge carriers decreases, local air conductivity decreases, and PG increases. These relationships have been used to infer high particulate, and hence pollution, levels in historic datasets of atmospheric PG and provide an easily measurable link between macrophysical quantities e.g. humidity with microphysical processes (e.g. aerosol growth) otherwise difficult to probe directly [2]. The time series show the differences in the data collected in the summer and a short campaign in the Autumn that corresponded to several bonfire events. Early comparisons show increased particle concentrations in the Autumn, and a stronger correlation. Figure 3. Averaged daily cycle of (a) Summer and (b) Autumn experiment Figure 4. Lomb Scarle periogograms for (a) normalised PG, (b) SMPS PNC and (c) CPC PNC for data recorded between 13/07/2015 and 07/08/2015. References Evidence for coupling between PG and aerosol parameters Most closely related parameter to PG is ion sink rate Continual analysis of data, including parameters such as relative humidity. Future work should extend campaign to other environments (rural, roadside) (a) (b) (c)