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Title: Short-term landfill methane emissions dependency on wind

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Journal Article: Publisher's Accepted Manuscript
Journal Name:
Waste Management
Additional Journal Information:
Journal Volume: 55; Journal Issue: C; Related Information: CHORUS Timestamp: 2017-10-05 22:03:11; Journal ID: ISSN 0956-053X
Country of Publication:
United States

Citation Formats

Delkash, Madjid, Zhou, Bowen, Han, Byunghyun, Chow, Fotini K., Rella, Chris W., and Imhoff, Paul T. Short-term landfill methane emissions dependency on wind. United States: N. p., 2016. Web. doi:10.1016/j.wasman.2016.02.009.
Delkash, Madjid, Zhou, Bowen, Han, Byunghyun, Chow, Fotini K., Rella, Chris W., & Imhoff, Paul T. Short-term landfill methane emissions dependency on wind. United States. doi:10.1016/j.wasman.2016.02.009.
Delkash, Madjid, Zhou, Bowen, Han, Byunghyun, Chow, Fotini K., Rella, Chris W., and Imhoff, Paul T. 2016. "Short-term landfill methane emissions dependency on wind". United States. doi:10.1016/j.wasman.2016.02.009.
title = {Short-term landfill methane emissions dependency on wind},
author = {Delkash, Madjid and Zhou, Bowen and Han, Byunghyun and Chow, Fotini K. and Rella, Chris W. and Imhoff, Paul T.},
abstractNote = {},
doi = {10.1016/j.wasman.2016.02.009},
journal = {Waste Management},
number = C,
volume = 55,
place = {United States},
year = 2016,
month = 9

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1016/j.wasman.2016.02.009

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Cited by: 1work
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  • Forecasts of available wind power are critical in key electric power systems operations planning problems, including economic dispatch and unit commitment. Such forecasts are necessarily uncertain, limiting the reliability and cost effectiveness of operations planning models based on a single deterministic or “point” forecast. A common approach to address this limitation involves the use of a number of probabilistic scenarios, each specifying a possible trajectory of wind power production, with associated probability. We present and analyze a novel method for generating probabilistic wind power scenarios, leveraging available historical information in the form of forecasted and corresponding observed wind power timemore » series. We estimate non-parametric forecast error densities, specifically using epi-spline basis functions, allowing us to capture the skewed and non-parametric nature of error densities observed in real-world data. We then describe a method to generate probabilistic scenarios from these basis functions that allows users to control for the degree to which extreme errors are captured.We compare the performance of our approach to the current state-of-the-art considering publicly available data associated with the Bonneville Power Administration, analyzing aggregate production of a number of wind farms over a large geographic region. Finally, we discuss the advantages of our approach in the context of specific power systems operations planning problems: stochastic unit commitment and economic dispatch. Here, our methodology is embodied in the joint Sandia – University of California Davis Prescient software package for assessing and analyzing stochastic operations strategies.« less
  • Estimating landfill methane emissions at national and global levels is fraught with uncertainties. The goal for the near-term is to improve national and global estimates based on improved models, which more realistically simulate a growing database of field measurements. This would assist regulators and policy makers to more accurately evaluate landfill methane emissions and guide development of national mitigation strategies. This article provides an updated perspective on landfill methane emissions by: (1) discussing recent field measurements and research results; (2) proposing research still needed; and (3) suggesting improved modeling strategies (including regulatory approaches) to assess landfill methane emissions more accurately.
  • Methane emissions were measured at nine US landfill sites using chamber and/or tracer flux techniques. These flux measurement methodologies were compared at two sites, and excellent agreement was observed. Total methane emissions ranged from 540 to 30 100 L min[sup [minus]1]. Expressed on an area basis, methane fluxes ranged from a low of 9.1 g of CH[sub 4] m[sup [minus]2] d[sup [minus]1] at a closed 20-ha site with active gas recovery to 130 g of CH[sub 4] m[sup [minus]2] d[sup [minus]1] at a 23-ha active site with no gas recovery. Methane emission factors were calculated for seven of the ninemore » sites. The two sites with no active gas recovery exhibited the highest emission factors of 4.8 and 5.1. Values were significantly lower at three sites with partial gas recovery, ranging from 1.6 to 3.7. At the two closed sites with active gas recovery, emission factors were much lower still. It is evident that even partial gas recovery at active landfill sites can significantly reduce methane emissions, and gas recovery at closed, covered sites reduces methane emissions to the atmosphere by as much as a factor of 10.« less
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