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Author Powe, N.A; Willis, K.G.; Garrod, G.D.
Title Difficulties in Valuing Street Light Improvement: Trust, Surprise and Bound Effects Type Journal Article
Year 2006 Publication (up) Applied Economics Abbreviated Journal
Volume 38 Issue 4 Pages 371–381
Keywords Economics
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Call Number LoNNe @ kagoburian @ Serial 1055
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Author Simpson, S.N.; Hanna, B.G.
Title Willingness to pay for a clear night sky: use of the contingent valuation method Type Journal Article
Year 2010 Publication (up) Applied Economics Letters Abbreviated Journal Applied Economics Letters
Volume 17 Issue 11 Pages 1095-1103
Keywords economics; contingent valuation method; light pollution
Abstract This article applies the Contingent Valuation Method (CVM) to the issue of night sky pollution. Light pollution decreases the ability to view a clear, unobstructed night sky. We administered a survey to the students of the Rochester Institute of Technology (RIT) to obtain estimates of Willingness To Pay (WTP) to improve night sky visibility and to prevent deterioration in visibility. This is the first CVM study that attempts to distinguish between these different WTPs. We find that students are willing to pay significantly more for a larger improvement in night sky conditions. We also find significant differences in WTP to improve versus prevent deterioration in night sky conditions.
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ISSN 1350-4851 ISBN Medium
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Call Number IDA @ john @ Serial 121
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Author Hu, T.; Huang, X.
Title A novel locally adaptive method for modeling the spatiotemporal dynamics of global electric power consumption based on DMSP-OLS nighttime stable light data Type Journal Article
Year 2019 Publication (up) Applied Energy Abbreviated Journal Applied Energy
Volume 240 Issue Pages 778-792
Keywords Remote Sensing
Abstract Timely and reliable estimation of electricity power consumption (EPC) is essential to the rational deployment of electricity power resources. Nighttime stable light (NSL) data from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) have the potential to model global 1-km gridded EPC. A processing chain to estimate EPC includes: (1) NSL data correction; and (2) regression model between EPC statistics and NSL data. For the global gridded EPC estimation, the current approach is to correct the global NSL image in a uniform manner and establish the linear relationships between NSL and EPC. However, the impacts of local socioeconomic inconsistencies on the NSL correction and model establishment are not fully considered. Therefore, in this paper, we propose a novel locally adaptive method for global EPC estimation. Firstly, we set up two options (with or without the correction) for each local area considering the global NSL image is not saturated everywhere. Secondly, three directions (forward, backward, or average) are alternatives for the inter-annual correction to remove the discontinuity effect of NSL data. Thirdly, four optional models (linear, logarithmic, exponential, or second-order polynomial) are adopted for the EPC estimation of each local area with different socioeconomic dynamic. Finally, the options for each step constitute all candidate processing chains, from which the optimal one is adaptively chosen for each local area based on the coefficient of determination. The results demonstrate that our product outperforms the existing one, at global, continental, and national scales. Particularly, the proportion of countries/districts with a high accuracy (MARE (mean of the absolute relative error)  ≤ 10%) increases from 17.8% to 57.8% and the percentage of countries/districts with inaccurate results (MARE > 50%) decreases sharply from 23.0% to 3.7%. This product can enhance the detailed understanding of the spatiotemporal dynamics of global EPC.
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ISSN 0306-2619 ISBN Medium
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Notes Approved no
Call Number GFZ @ kyba @ Serial 2242
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Author Shi, K.; Chen, Y.; Yu, B.; Xu, T.; Yang, C.; Li, L.; Huang, C.; Chen, Z.; Liu, R.; Wu, J.
Title Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data Type Journal Article
Year 2016 Publication (up) Applied Energy Abbreviated Journal Applied Energy
Volume 184 Issue Pages 450-463
Keywords Remote Sensing
Abstract The rapid development of global industrialization and urbanization has resulted in a great deal of electric power consumption (EPC), which is closely related to economic growth, carbon emissions, and the long-term stability of global climate. This study attempts to detect spatiotemporal dynamics of global EPC using the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime stable light (NSL) data. The global NSL data from 1992 to 2013 were intercalibrated via a modified invariant region (MIR) method. The global EPC at 1 km resolution was then modeled using the intercalibrated NSL data to assess spatiotemporal dynamics of EPC from a global scale down to continental and national scales. The results showed that the MIR method not only reduced the saturated lighted pixels, but also improved the continuity and comparability of the NSL data. An accuracy assessment was undertaken and confined that the intercalibrated NSL data were relatively suitable and accurate for estimating EPC in the world. Spatiotemporal variations of EPC were mainly identified in Europe, North America, and Asia. Special attention should be paid to China where the high grade and high-growth type of EPC covered 0.409% and 1.041% of the total country area during the study period, respectively. The results of this study greatly enhance the understanding of spatiotemporal dynamics of global EPC at the multiple scales. They will provide a scientific evidence base for tracking spatiotemporal dynamics of global EPC.
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ISSN 0306-2619 ISBN Medium
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Notes Approved no
Call Number GFZ @ kyba @ Serial 2486
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Author Lu, H.; Liu, G.
Title Spatial effects of carbon dioxide emissions from residential energy consumption: A county-level study using enhanced nocturnal lighting Type Journal Article
Year 2014 Publication (up) Applied Energy Abbreviated Journal Applied Energy
Volume 131 Issue Pages 297-306
Keywords Remote Sensing
Abstract As the world’s largest developing country and greenhouse gas emitter, China’s residential energy consumption (REC) is now responsible for over 11% of the country’s total energy consumption. In this paper, we present a novel method that utilizes spatially distributed information from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP–OLS) and human activity index (HAI) to test the hypothesis that counties with similar carbon dioxide emissions from REC are more spatially clustered than would be expected by chance. Our results revealed a high degree of county-level clustering in the distribution of emissions per capita. However, further analysis showed that high-emission counties tended to be surrounded by counties with relatively low per capita GDP levels. Therefore, our results contrasted with other evidence that REC emissions were closely related to GDP levels. Accordingly, we stress the need for the consideration of other factors in determining emission patterns, such as residential consumption patterns (e.g., consumer choices, behavior, knowledge, and information diffusion).
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ISSN 0306-2619 ISBN Medium
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Notes Approved no
Call Number GFZ @ kyba @ Serial 2493
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