GC094-04
Identifying Opportunities to Electrify Diesel-Powered Irrigation Pumps Using Remote Sensing Data in Ethiopia

Monday, 14 December 2020: 19:30
Virtual
June Lukuyu, University of Massachusetts Amherst, Amherst, MA, United States and Jay Taneja, University of Massachusetts Amherst, Amherst, United States
Abstract:
Despite nearly one billion primarily rural and low-income people living without access to electricity services, crucial strides have been made in developing new pathways for connecting households and businesses to electricity supplies. However, in low-income regions particularly sub-Saharan Africa, electricity consumption remains low among newly-electrified households, stifling the impetus for expansion of electricity access. Contrary to the energy efficiency zeitgeist in industrialized regions, low-income regions need to increase their electricity consumption density, mainly for income generating purposes to grow their economies and as such, for consumers to realize the full benefits of electrification. To address this, our work explores strategies that facilitate the increase in end-use of electricity, specifically by identifying and converting other energy uses, such as fossil fuel use, to electricity.

In this work, we propose a novel method to explore whether off-grid diesel-powered irrigation activity in Ethiopia can be identified using satellite observations of pollution data. The recently launched TROPOMI instrument on the Sentinel-5 Precursor satellite provides air quality and climate-related atmospheric constituents data at unprecedented spatial and temporal resolution. To achieve this, we leverage the TROPOMI NO2 and CO datasets together with other datasets on population, crop production, and atmospheric variables. Existing land use regression models are used to estimate in-situ measurements of NO2 and CO. Using machine learning techniques, we then investigate spatial and seasonal patterns of elevated NO2 and CO levels and their correlation with irrigation seasons, low population densities, and high crop yields. Follow up work involves validating this technique with diesel irrigation pump location data collected via surveys. At scale, this technique can guide electrification of diesel irrigation pumps across Ethiopia, improving environmental and financial sustainability for farmers and utilities.