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Author Pravettoni, M.; Strepparava, D.; Cereghetti, N.; Klett, S.; Andretta, M.; Steiger, M. url  doi
openurl 
  Title Indoor calibration of Sky Quality Meters: linearity, spectral responsivity and uncertainty analysis Type Journal Article
  Year 2016 Publication Journal of Quantitative Spectroscopy and Radiative Transfer Abbreviated Journal Journal of Quantitative Spectroscopy and Radiative Transfer  
  Volume (down) 181 Issue in press Pages 74-86  
  Keywords Instrumentation  
  Abstract The indoor calibration of brightness sensors requires extremely low values of irradiance in the most accurate and reproducible way. In this work the testing equipment of an ISO 17025 accredited laboratory for electrical testing, qualification and type approval of solar photovoltaic modules was modified in order to test the linearity of the instruments from few mW/cm2 down to fractions of nW/cm2, corresponding to levels of simulated brightness from 6 to 19 mag/arcsec2. Sixteen Sky Quality Meter (SQM) produced by Unihedron, a Canadian manufacturer, were tested, also assessing the impact of the ageing of their protective glasses on the calibration coefficients and the drift of the instruments. The instruments are in operation on measurement points and observatories at different sites and altitudes in Southern Switzerland, within the framework of OASI, the Environmental Observatory of Southern Switzerland. The authors present the results of the calibration campaign: linearity; brightness calibration, with and without protective glasses; transmittance measurement of the glasses; and spectral responsivity of the devices. A detailed uncertainty analysis is also provided, according to the ISO 17025 standard.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0022-4073 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kyba @ Serial 1399  
Permanent link to this record
 

 
Author Xiao, Q.; Gee, G.; Jones, R.R.; Jia, P.; James, P.; Hale, L. url  doi
openurl 
  Title Cross-sectional association between outdoor artificial light at night and sleep duration in middle-to-older aged adults: The NIH-AARP Diet and Health Study Type Journal Article
  Year 2019 Publication Environmental Research Abbreviated Journal Environ Res  
  Volume (down) 180 Issue Pages 108823  
  Keywords Remote Sensing; Human Health; Artificial light at night; Circadian disruption; Neighborhood; Sleep; Socioeconomic disadvantage  
  Abstract INTRODUCTION: Artificial light at night (ALAN) can disrupt circadian rhythms and cause sleep disturbances. Several previous epidemiological studies have reported an association between higher levels of outdoor ALAN and shorter sleep duration. However, it remains unclear how this association may differ by individual- and neighborhood-level socioeconomic status, and whether ALAN may also be associated with longer sleep duration. METHODS: We assessed the cross-sectional relationship between outdoor ALAN and self-reported sleep duration in 333,365 middle- to older-aged men and women in the NIH-AARP Diet and Health Study. Study participants reported baseline addresses, which were geocoded and linked with outdoor ALAN exposure measured by satellite imagery data obtained from the U.S. Defense Meteorological Satellite Program's Operational Linescan System. We used multinomial logistic regression to estimate the multinomial odds ratio (MOR) and 95% confidence intervals (CI) for the likelihood of reporting very short (<5h), short (<7h) and long (>/=9h) sleep relative to reporting 7-8h of sleep across quintiles of LAN. We also conducted subgroup analyses by individual-level education and census tract-level poverty levels. RESULTS: We found that higher levels of ALAN were associated with both very short and short sleep. When compared to the lowest quintile, the highest quintile of ALAN was associated with 16% and 25% increases in the likelihood of reporting short sleep in women (MORQ1 vs Q5, (95% CI), 1.16 (1.10, 1.22)) and men (1.25 (1.19, 1.31)), respectively. Moreover, we found that higher ALAN was associated with a decrease in the likelihood of reporting long sleep in men (0.79 (0.71, 0.89)). We also found that the associations between ALAN and short sleep were larger in neighborhoods with higher levels of poverty. CONCLUSIONS: The burden of short sleep may be higher among residents in areas with higher levels of outdoor LAN, and this association is likely stronger in poorer neighborhoods. Future studies should investigate the potential benefits of reducing light intensity in high ALAN areas in improve sleep health.  
  Address Program in Public Health, Department of Family, Population, and Preventive Medicine, Stony Brook Medicine, Stony Brook, NY, USA  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0013-9351 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:31627155 Approved no  
  Call Number GFZ @ kyba @ Serial 2702  
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Author Jasiński, T. url  doi
openurl 
  Title Modeling electricity consumption using nighttime light images and artificial neural networks Type Journal Article
  Year 2019 Publication Energy Abbreviated Journal Energy  
  Volume (down) 179 Issue Pages 831-842  
  Keywords Remote Sensing  
  Abstract The purpose of this paper is to model electricity consumption using Artificial Neural Networks (ANN). Total electricity consumption and consumption generated by households (HH) were modeled. The input variables of the ANN were based on nighttime light images from VIIRS DNB. Studies conducted thus far have covered mainly linear models. Most of case studies focused on single countries or groups of countries with only few focusing on the sub-national scale. This paper is pioneering in covering an area of Poland (Central Europe) at NUTS-2 level. The use of ANN enabled the modeling of the non-linear relations associated with the complex structure of electricity demand. Satellite data were collected for the period 2013–2016, and included images with improved quality (inter alia higher resolution), compared to the DMSP/OLS program. As images are available from April 2012 onwards, it is only recently that their number has become sufficient for ANN learning. The images were used to create models of multilayer perceptrons. The results achieved by ANN were compared with the results obtained using linear regressions. Studies have confirmed that electricity consumption can be determined with higher precision by the ANN method.  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0360-5442 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2475  
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Author Park, Y.-M.M.; White, A.J.; Jackson, C.L.; Weinberg, C.R.; Sandler, D.P. url  doi
openurl 
  Title Association of Exposure to Artificial Light at Night While Sleeping With Risk of Obesity in Women Type Journal Article
  Year 2019 Publication JAMA Internal Medicine Abbreviated Journal JAMA Intern Med  
  Volume (down) 179 Issue 8 Pages 1061-1071  
  Keywords Human Health; Obesity; Sleep  
  Abstract Importance: Short sleep has been associated with obesity, but to date the association between exposure to artificial light at night (ALAN) while sleeping and obesity is unknown. Objective: To determine whether ALAN exposure while sleeping is associated with the prevalence and risk of obesity. Design, Setting, and Participants: This baseline and prospective analysis included women aged 35 to 74 years enrolled in the Sister Study in all 50 US states and Puerto Rico from July 2003 through March 2009. Follow-up was completed on August 14, 2015. A total of 43722 women with no history of cancer or cardiovascular disease who were not shift workers, daytime sleepers, or pregnant at baseline were included in the analysis. Data were analyzed from September 1, 2017, through December 31, 2018. Exposures: Artificial light at night while sleeping reported at enrollment, categorized as no light, small nightlight in the room, light outside the room, and light or television in the room. Main Outcomes and Measures: Prevalent obesity at baseline was based on measured general obesity (body mass index [BMI] >/=30.0) and central obesity (waist circumference [WC] >/=88 cm, waist-to-hip ratio [WHR] >/=0.85, or waist-to-height ratio [WHtR]>/=0.5). To evaluate incident overweight and obesity, self-reported BMI at enrollment was compared with self-reported BMI at follow-up (mean [SD] follow-up, 5.7 [1.0] years). Generalized log-linear models with robust error variance were used to estimate multivariable-adjusted prevalence ratios (PRs) and relative risks (RRs) with 95% CIs for prevalent and incident obesity. Results: Among the population of 43 722 women (mean [SD] age, 55.4 [8.9] years), having any ALAN exposure while sleeping was positively associated with a higher prevalence of obesity at baseline, as measured using BMI (PR, 1.03; 95% CI, 1.02-1.03), WC (PR, 1.12; 95% CI, 1.09-1.16), WHR (PR, 1.04; 95% CI, 1.00-1.08), and WHtR (PR, 1.07; 95% CI, 1.04-1.09), after adjusting for confounding factors, with P < .001 for trend for each measure. Having any ALAN exposure while sleeping was also associated with incident obesity (RR, 1.19; 95% CI, 1.06-1.34). Compared with no ALAN, sleeping with a television or a light on in the room was associated with gaining 5 kg or more (RR, 1.17; 95% CI, 1.08-1.27; P < .001 for trend), a BMI increase of 10% or more (RR, 1.13; 95% CI, 1.02-1.26; P = .04 for trend), incident overweight (RR, 1.22; 95% CI,1.06-1.40; P = .03 for trend), and incident obesity (RR, 1.33; 95% CI, 1.13-1.57; P < .001 for trend). Results were supported by sensitivity analyses and additional multivariable analyses including potential mediators such as sleep duration and quality, diet, and physical activity. Conclusions and Relevance: These results suggest that exposure to ALAN while sleeping may be a risk factor for weight gain and development of overweight or obesity. Further prospective and interventional studies could help elucidate this association and clarify whether lowering exposure to ALAN while sleeping can promote obesity prevention.  
  Address Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2168-6106 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:31180469 Approved no  
  Call Number GFZ @ kyba @ Serial 2525  
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Author Fu, D.; Xia, X.; Duan, M.; Zhang, X.; Li, X.; Wang, J.; Liu, J. url  doi
openurl 
  Title Mapping nighttime PM 2.5 from VIIRS DNB using a linear mixed-effect model Type Journal Article
  Year 2018 Publication Atmospheric Environment Abbreviated Journal Atmospheric Environment  
  Volume (down) 178 Issue Pages 214-222  
  Keywords Remote Sensing  
  Abstract Estimation of particulate matter with aerodynamic diameter less than 2.5&#8239;&#956;m (PM2.5) from daytime satellite aerosol products is widely reported in the literature; however, remote sensing of nighttime surface PM2.5 from space is very limited. PM2.5 shows a distinct diurnal cycle and PM2.5 concentration at 1:00 local standard time (LST) has a linear correlation coefficient (R) of 0.80 with daily-mean PM2.5. Therefore, estimation of nighttime PM2.5 is required toward an improved understanding of temporal variation of PM2.5 and its effects on air quality. Using data from the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) and hourly PM2.5 data at 35 stations in Beijing, a mixed-effect model is developed here to estimate nighttime PM2.5 from nighttime light radiance measurements based on the assumption that the DNB-PM2.5 relationship is constant spatially but varies temporally. Cross-validation showed that the model developed using all stations predict daily PM2.5 with mean determination coefficient (R2) of 0.87 ±± 0.12, 0.83 ±0.10±0.10, 0.87 ±± 0.09, 0.83 ±± 0.10 in spring, summer, autumn and winter. Further analysis showed that the best model performance was achieved in urban stations with average cross-validation R2 of 0.92. In rural stations, DNB light signal is weak and was likely smeared by lunar illuminance that resulted in relatively poor estimation of PM2.5. The fixed and random parameters of the mixed-effect model in urban stations differed from those in suburban stations, which indicated that the assumption of the mixed-effect model should be carefully evaluated when used at a regional scale.  
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  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1352-2310 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kyba @ Serial 1814  
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