A Data-Driven Approach for Studying the Washout Effects of Rain on Air Pollution
Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 387
 David, N., & Gao, H. O. (2016). Using Cellular Communication Networks To Detect Air Pollution. Environmental science & technology, 50(17), 9442-9451. DOI: 10.1021/acs.est.6b00681
 Koonin, S.E. and Holland, M., 2014. The value of big data for urban science. Privacy, Big Data and the Public Good.
 David, N. (2019). Harnessing Crowdsourced Data and Prevalent Technologies for Atmospheric Research. Advances in Atmospheric Sciences, 36(7), 766-769.
 Alpert, P., Messer, H., & David, N. (2016). Mobile networks aid weather monitoring. Nature, 537(7622), 617-617.
 Doumounia, A., Gosset, M., Cazenave, F., Kacou, M., & Zougmore, F. (2014). Rainfall monitoring based on microwave links from cellular telecommunication networks: First results from a West African test bed. Geophysical Research Letters, 41(16), 6016-6022. DOI: 10.1002/2014GL060724
 Gosset, M., et al. (2016). Improving rainfall measurement in gauge poor regions thanks to mobile telecommunication networks. Bulletin of the American Meteorological Society, 97(3), ES49-ES51. DOI:10.1175/BAMS-D-15-00164.1
 David, N., Gao, H. O., Kumah, K. K., Hoedjes, J. C. B., Su, Z., & Liu, Y. Microwave communication networks as a sustainable tool of rainfall monitoring for agriculture needs in Africa. 16th International Conference on Environmental Science And Technology (CEST). Rhodes, Greece, 4-7 September, 2019.
 Upton, G. J. G., Holt, A. R., Cummings, R. J., Rahimi, A. R., & Goddard, J. W. F. (2005). Microwave links: The future for urban rainfall measurement?. Atmospheric research, 77(1-4), 300-312.
 Messer, H., Zinevich, A., & Alpert, P. (2006). Environmental monitoring by wireless communication networks. Science, 312(5774), 713-713. DOI: 10.1126/science.1120034.
 Leijnse, H., Uijlenhoet, R., & Stricker, J. N. M. (2007). Rainfall measurement using radio links from cellular communication networks. Water Resources Research, 43(3). DOI: 10.1029/2006WR005631
 David, N., Sendik, O., Messer, H., & Alpert, P. (2015). Cellular network infrastructure: The future of fog monitoring?. Bulletin of the American Meteorological Society, 96(10), 1687-1698. DOI: https://doi.org/10.1175/BAMS-D-13-00292.1
 David, N., & Gao, H. O. (2018). Using Cell‐Phone Tower Signals for Detecting the Precursors of Fog. Journal of Geophysical Research: Atmospheres, 123(2), 1325-1338.
 David, N. (2018). Utilizing microwave communication data for detecting fog where satellite retrievals are challenged. Natural Hazards, 94(2), 867-882.
 David, N., Alpert, P., & Messer, H. (2009). Novel method for water vapour monitoring using wireless communication networks measurements. Atmospheric chemistry and physics, 9(7), 2413-2418. DOI: https://doi.org/10.5194/acp-9-2413-2009.
 Chwala, C., Kunstmann, H., Hipp, S., & Siart, U. (2014). A monostatic microwave transmission experiment for line integrated precipitation and humidity remote sensing. Atmospheric research, 144, 57-72.
 David, N., Sendik, O., Rubin, Y., Messer, H., Gao, H. O., Rostkier-Edelstein, D., & Alpert, P. (2019). Analyzing the ability to reconstruct the moisture field using commercial microwave network data. Atmospheric research, 219, 213-222.
 Harel, O., David, N., Alpert, P., & Messer, H. (2015). The Potential of Microwave Communication Networks to Detect Dew—Experimental Study. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(9), 4396-4404. DOI: 10.1109/JSTARS.2015.2465909
 Frey, T. L.: The effects of the atmosphere and weather on the performance of a mm- wave communication link, Appl. Microw. Wirel. Mag., 76-80, 1999.
 Shmool, J. L., Michanowicz, D. R., Cambal, L., Tunno, B., Howell, J., Gillooly, S., ... & Gorczynski, J. E. (2014). Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain. Environmental Health, 13(1), 28.
 Croft, B., et al. (2009). Aerosol size-dependent below-cloud scavenging by rain and snow in the ECHAM5-HAM. Atmospheric Chemistry and Physics, 9(14), 4653-4675.
 Duhanyan, N., & Roustan, Y. (2011). Below-cloud scavenging by rain of atmospheric gases and particulates. Atmospheric Environment, 45(39), 7201-7217.
 Yoo, J. M., Lee, Y. R., Kim, D., Jeong, M. J., Stockwell, W. R., Kundu, P. K., ... & Lee, S. J. (2014). New indices for wet scavenging of air pollutants (O3, CO, NO2, SO2, and PM10) by summertime rain. Atmospheric Environment, 82, 226-237.
 Guo, L. C., Zhang, Y., Lin, H., Zeng, W., Liu, T., Xiao, J., ... & Ma, W. (2016). The washout effects of rainfall on atmospheric particulate pollution in two Chinese cities. Environmental Pollution, 215, 195-202.
 Olsen, R. O. G. E. R. S., Rogers, D. V., & Hodge, D. (1978). The aR b relation in the calculation of rain attenuation. IEEE Transactions on antennas and propagation, 26(2), 318-329.
 Zinevich, A., Messer, H., & Alpert, P. (2010). Prediction of rainfall intensity measurement errors using commercial microwave communication links. Atmospheric Measurement Techniques, 3(5), 1385.
 Zinevich, A., Messer, H., & Alpert, P. (2009). Frontal rainfall observation by a commercial microwave communication network. Journal of Applied Meteorology and Climatology, 48(7), 1317-1334. DOI: https://doi.org/10.1175/2008JAMC2014.1
 Overeem, A., Leijnse, H., & Uijlenhoet, R. (2013). Country-wide rainfall maps from cellular communication networks. Proceedings of the National Academy of Sciences, 110(8), 2741-2745. DOI: 10.1073/pnas.1217961110
 Goldshtein, O., Messer, H., & Zinevich, A. (2009). Rain rate estimation using measurements from commercial telecommunications links. IEEE Transactions on Signal Processing, 57(4), 1616-1625. DOI: 10.1109/TSP.2009.2012554
 Shepard, D. (1968, January). A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference (pp. 517-524). ACM.
 Liberman, Y., Samuels, R., Alpert, P., & Messer, H. (2014). New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping. Atmospheric Measurement Techniques, 7(10), 3549-3563. DOI: https://doi.org/10.5194/amt-7-3549-2014
 D’Amico, M., Manzoni, A., & Solazzi, G. L. (2016). Use of operational microwave link measurements for the tomographic reconstruction of 2-D maps of accumulated rainfall. IEEE Geoscience and Remote Sensing Letters, 13(12), 1827-1831.
 Fencl, M., Rieckermann, J., Schleiss, M., Stránský, D., & Bareš, V. (2013). Assessing the potential of using telecommunication microwave links in urban drainage modelling. Water Science and Technology, 68(8), 1810-1818. DOI: 10.2166/wst.2013.429
 Hoedjes, J. C., et al. (2014). A conceptual flash flood early warning system for Africa, based on terrestrial microwave links and flash flood guidance. ISPRS International Journal of Geo-Information, 3(2), 584-598. DOI: 10.3390/ijgi3020584
 Chwala, C., Keis, F., & Kunstmann, H. (2016). Real-time data acquisition of commercial microwave link networks for hydrometeorological applications. Atmospheric Measurement Techniques, 9(3), 991-999.
 David, N., Alpert, P., & Messer, H. (2013). The potential of cellular network infrastructures for sudden rainfall monitoring in dry climate regions. Atmospheric research, 131, 13-21. DOI: https://doi.org/10.1016/j.atmosres.2013.01.004
 Seinfeld, J. H., & Pandis, S. N. (2016). Atmospheric chemistry and physics: from air pollution to climate change. John Wiley & Sons.
 Herckes, P., H. Chang, T. Lee, and J. L. Collet (2007), Air pollution processing by radiation fogs, Water Air Soil Pollut., 181,65–75.
 Edstam, J., Hansryd, J., Carpenter, S., Emanuelsson, T., Li, Y & Zirath, H. (2017). Microwave backhaul evolution – reaching beyond 100GHz, Ericsson technology review.
 Liebe, H. (1983). Atmospheric EHF window transparencies near 35, 90, 140 and 220 GHz. IEEE Transactions on Antennas and Propagation, 31(1), 127-135.
 Ericsson (2016), Ericsson microwave outlook, trends and needs in the microwave industry.