Figueiro, M. G., & Rea, M. S. (2010). The effects of red and blue lights on circadian variations in cortisol, alpha amylase, and melatonin. Int J Endocrinol, 2010, 829351.
Abstract: The primary purpose of the present study was to expand our understanding of the impact of light exposures on the endocrine and autonomic systems as measured by acute cortisol, alpha amylase, and melatonin responses. We utilized exposures from narrowband long-wavelength (red) and from narrow-band short-wavelength (blue) lights to more precisely understand the role of the suprachiasmatic nuclei (SCN) in these responses. In a within-subjects experimental design, twelve subjects periodically received one-hour corneal exposures of 40 lux from the blue or from the red lights while continuously awake for 27 hours. Results showed-that, as expected, only the blue light reduced nocturnal melatonin. In contrast, both blue and red lights affected cortisol levels and, although less clear, alpha amylase levels as well. The present data bring into question whether the nonvisual pathway mediating nocturnal melatonin suppression is the same as that mediating other responses to light exhibited by the endocrine and the autonomic nervous systems.
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Tsao, J. Y., Saunders, H. D., Creighton, J. R., Coltrin, M. E., & Simmons, J. A. (2010). Solid-state lighting: an energy-economics perspective. J. Phys. D: Appl. Phys., 43(35), 354001.
Abstract: Artificial light has long been a significant factor contributing to the quality and productivity of human life. As a consequence, we are willing to use huge amounts of energy to produce it. Solid-state lighting (SSL) is an emerging technology that promises performance features and efficiencies well beyond those of traditional artificial lighting, accompanied by potentially massive shifts in (a) the consumption of light, (b) the human productivity and energy use associated with that consumption and (c) the semiconductor chip area inventory and turnover required to support that consumption. In this paper, we provide estimates of the baseline magnitudes of these shifts using simple extrapolations of past behaviour into the future. For past behaviour, we use recent studies of historical and contemporary consumption patterns analysed within a simple energy-economics framework (a Cobb–Douglas production function and profit maximization). For extrapolations into the future, we use recent reviews of believed-achievable long-term performance targets for SSL. We also discuss ways in which the actual magnitudes could differ from the baseline magnitudes of these shifts. These include: changes in human societal demand for light; possible demand for features beyond lumens; and guidelines and regulations aimed at economizing on consumption of light and associated energy.
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Roman, M. O., Stokes, E. C., Shrestha, R., Wang, Z., Schultz, L., Carlo, E. A. S., et al. (2019). Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14(6), e0218883.
Abstract: A real-time understanding of the distribution and duration of power outages after a major disaster is a precursor to minimizing their harmful consequences. Here, we develop an approach for using daily satellite nighttime lights data to create spatially disaggregated power outage estimates, tracking electricity restoration efforts after disasters strike. In contrast to existing utility data, these estimates are independent, open, and publicly-available, consistently measured across regions that may be serviced by several different power companies, and inclusive of distributed power supply (off-grid systems). We apply the methodology in Puerto Rico following Hurricane Maria, which caused the longest blackout in US history. Within all of the island's settlements, we track outages and recovery times, and link these measures to census-based demographic characteristics of residents. Our results show an 80% decrease in lights, in total, immediately after Hurricane Maria. During the recovery, a disproportionate share of long-duration power failures (> 120 days) occurred in rural municipalities (41% of rural municipalities vs. 29% of urban municipalities), and in the northern and eastern districts. Unexpectedly, we also identify large disparities in electricity recovery between neighborhoods within the same urban area, based primarily on the density of housing. For many urban areas, poor residents, the most vulnerable to increased mortality and morbidity risks from power losses, shouldered the longest outages because they lived in less dense, detached housing where electricity restoration lagged. The approach developed in this study demonstrates the potential of satellite-based estimates of power recovery to improve the real-time monitoring of disaster impacts, globally, at a spatial resolution that is actionable for the disaster response community.
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Andrade-Pacheco, R., Savory, D. J., Midekisa, A., Gething, P. W., Sturrock, H. J. W., & Bennett, A. (2019). Household electricity access in Africa (2000-2013): Closing information gaps with model-based geostatistics. PLoS One, 14(5), e0214635.
Abstract: Household electricity access data in Africa are scarce, particularly at the subnational level. We followed a model-based Geostatistics approach to produce maps of electricity access between 2000 and 2013 at a 5 km resolution. We collated data from 69 nationally representative household surveys conducted in Africa and incorporated nighttime lights imagery as well as land use and land cover data to produce maps of electricity access between 2000 and 2013. The information produced here can be an aid for understanding of how electricity access has changed in the region during this 14 year period. The resolution and the continental scale makes it possible to combine these data with other sources in applications in the socio-economic field, both at a local or regional level.
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Lu, Y., & Coops, N. C. (2018). Bright lights, big city: Causal effects of population and GDP on urban brightness. PLoS One, 13(7), e0199545.
Abstract: Cities are arguably both the cause, and answer, to societies' current sustainability issues. Urbanization is the interplay between a city's physical growth and its socio-economic development, both of which consume a substantial amount of energy and resources. Knowledge of the underlying driver(s) of urban expansion facilitates not only academic research but, more importantly, bridges the gap between science, policy drafting, and practical urban management. An increasing number of researchers are recognizing the benefits of innovative remotely sensed datasets, such as nighttime lights data (NTL), as a proxy to map urbanization and subsequently examine the driving socio-economic variables in cities. We further these approaches, by taking a trans-pacific view, and examine how an array of socio-economic ind0icators of 25 culturally and economically important urban hubs relate to long term patterns in NTL for the past 21 years. We undertake a classic econometric approach-panel causality tests which allow analysis of the causal relationships between NTL and socio-economic development across the region. The panel causality test results show a contrasting effect of population and gross domestic product (GDP) on NTL in fast, and slowly, changing cities. Information derived from this study quantitatively chronicles urban activities in the pan-Pacific region and potentially offers data for studies that spatially track local progress of sustainable urban development goals.
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