scholarly journals Integrating Point-Source Methane Emissions from Imaging Spectroscopy Data into the Multi-scale Methane Analytic Framework (M2AF) Information System

2020 ◽  
Author(s):  
E. Natasha Stavros ◽  
Riley Duren ◽  
Andrew Thorpe ◽  
Daniel Cusworth ◽  
Brian Bue ◽  
...  
2020 ◽  
Author(s):  
Daniel Cusworth ◽  
Riley Duren ◽  
Andrew Thorpe ◽  
Natasha Stavros ◽  
Brian Bue ◽  
...  

<p>Methane emissions monitoring is rapidly expanding with increasing coverage of surface, airborne, and satellite instruments. However, no single methane instrument or observing strategy can both close emission budgets and pinpoint point sources on regional to global scales. Instead, we present a multi-tiered data analytics system that synthesizes information across various instruments into a single analytic framework. We highlight an example in Los Angeles, where we combine surface measurements from the Los Angeles megacities project, mountaintop measurements from the CLARS-FTS instrument, airborne AVIRIS-NG point source emission estimates, and TROPOMI total column retrievals into a single analytic framework. Surface, mountaintop, and satellite measurements are assimilated into a methane flux inverse model to constrain basin-wide emissions and pinpoint sub-basin methane hotspots. We show an example of a large urban landfill, whose anomalous emissions were detected by the inverse system, and validated using AVIRIS-NG methane plume maps. This general approach of quantifying both methane area and point source emissions is an avenue not just for closing regional to global scale budgets, but also for understanding which emission sources dominate the budget (i.e., so called methane super-emitters). We finally show how this multi-tiered analytic framework can be improved with future satellite missions, and present examples of unexpectedly large methane emissions that were detected by a new generation of satellite imaging spectrometers.</p>


2018 ◽  
Vol 40 (3) ◽  
pp. 589-629 ◽  
Author(s):  
Jochem Verrelst ◽  
Zbyněk Malenovský ◽  
Christiaan Van der Tol ◽  
Gustau Camps-Valls ◽  
Jean-Philippe Gastellu-Etchegorry ◽  
...  

Author(s):  
Eda Ustaoglu ◽  
Arif Çagdaş Aydinoglu

Land-use change models are tools to support analyses, assessments, and policy decisions concerning the causes and consequences of land-use dynamics, by providing a framework for the analysis of land-use change processes and making projections for the future land-use/cover patterns. There is a variety of modelling approaches that were developed from different disciplinary backgrounds. Following the reviews in the literature, this chapter focuses on various modelling tools and practices that range from pattern-based methods such as machine learning and GIS (Geographic Information System)-based approaches, to process-based methods such as structural economic or agent-based models. For each of these methods, an overview is given for the advances that have been progressed by geographers, natural and economy scientists in developing these models of spatial land-use change. It is noted that further progress is needed in terms of model development, and integration of models operating at various scales that better address the multi-scale characteristics of the land-use system.


2019 ◽  
Vol 62 (6) ◽  
pp. 1455-1465
Author(s):  
Richard W. Todd ◽  
Corey Moffet ◽  
James P. S. Neel ◽  
Kenneth E. Turner ◽  
Jean L. Steiner ◽  
...  

HighlightsEnteric methane (CH4) from beef cows on pasture was measured over three seasons using three methods.Methods yielded similar results during the summer grazing season but diverged in autumn and winter seasons.Emission averaged 0.34, 0.27, and 0.29 kg CH4 cow-1 during lactation, mid-gestation, and late gestation, respectively.Annualized enteric methane emission rate for a beef cow herd grazing tallgrass prairie was 0.32 kg d-1 cow-1.Abstract. Methane (CH4) is an important greenhouse gas, and about 20% of the carbon dioxide equivalent (CO2e) greenhouse gases emitted by U.S. agriculture are attributed to enteric CH4 produced by grazing beef cattle. Grazing cattle are mobile point sources of methane and present challenges to quantifying the enteric methane emission rate (MER). In this study, we applied three methods to measure herd-scale and individual-animal MER for a herd of beef cows grazing a native tallgrass prairie: a point source method that used forward-mode dispersion analysis and open-path lasers and cow locations, an open chamber breath analysis system (GreenFeed), and an eddy covariance ratio method that used the ratio of CH4 and CO2 mass fluxes. Three campaigns were conducted during the early season (July), late season (October), and dormant season (February). The point source and GreenFeed methods yielded similar MER (±SD) values during the early season campaign: 0.38 ±0.04 and 0.34 ±0.05 kg d-1 cow-1, respectively. However, the MER values from the two methods diverged in subsequent seasons. The GreenFeed MER decreased through the late and dormant seasons to 0.23 ±0.03 and 0.19 ±0.03 kg d-1 cow-1, respectively. In contrast, the point source MER stayed the same during the late season and increased during the dormant season to 0.41 ±0.07 kg d-1 cow-1. The CH4:CO2 ratio method, which was used only during the dormant season, yielded a MER of 0.29 ±0.05 kg d-1 cow-1. The point source and GreenFeed methods measured different MER (integrated herd-scale versus a subset of individual animals) and likely sampled methane emissions at different times during the day. We conclude that the point source method tended to overestimate emissions, and the GreenFeed method tended to underestimate emissions. Enteric methane emissions from beef cows over the three grazing seasons averaged 0.39 and 0.25 kg d-1 cow-1 as measured by the point source and GreenFeed methods, respectively. An annualized enteric MER for a beef cow herd grazing tallgrass prairie was 0.32 kg d-1 cow-1. Quantifying enteric methane emissions from grazing beef cows remains a challenge because of the mobile, often dispersed behavior of grazing cattle and the dynamic interactions of forage quality, dry matter intake, and changing physiological state of cows during the year. Keywords: Beef cows, Enteric methane, Forage quality, Grazing, Tallgrass prairie.


Sensors ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 578 ◽  
Author(s):  
Kai Zhou ◽  
Xinqiang Deng ◽  
Xia Yao ◽  
Yongchao Tian ◽  
Weixing Cao ◽  
...  

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