Tracking Soiling Losses: Assessment, Uncertainty, and Challenges in Mapping

Leonardo Micheli, Greg Smestad, Joao Bessa, Matthew Muller, Eduardo Fernandez, Florencia Almonacid

Research output: Contribution to journalArticlepeer-review

10 Scopus Citations


Several models have been presented in the recent years to estimate the magnitude of soiling from environmental parameters. However, these models are often based on data from a single site, or at most a few sites, and only limited data are, as of yet, available on their uncertainty. The present work aims to present a first comparative analysis of soiling estimation models, using measured soiling data from various locations in the USA. The study also investigates the impact that the source of the input data can have on the estimation. The results show that the model selection is only one of the factors that can affect the evaluation. Indeed, the use of satellite-derived or ground-mounted particulate matter data can lead to the generation of different soiling maps, with factors greater than 2× between the modeled losses. The current challenges and the unanswered questions that can bias soiling estimation are discussed. Additionally, potential research directions to improve the quality of soiling modeling are identified.

Original languageAmerican English
Pages (from-to)114-118
Number of pages5
JournalIEEE Journal of Photovoltaics
Issue number1
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2011-2012 IEEE.

NREL Publication Number

  • NREL/JA-5K00-80310


  • Air quality
  • map
  • particulate matter (PM)
  • photovoltaic (PV)
  • soiling


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