A record of the atmospheric methane sink from formaldehyde in polar ice cores

Measurements of methane from ice cores show that the atmospheric concentration of methane has more than doubled since industrialization, and was only half of the pre-industrial value during the last ice age (1–9). Natural sources of atmospheric methane are mainly biogenic, with the main sink for methane being its reaction with OH radicals. This reaction initiates a chain of reactions involving other trace gases and radicals, one of which is formaldehyde. In the remote troposphere, oxidation of methane followed by other reactions is the main source for formaldehyde. By reconstructing records of atmospheric methane and formaldehyde from ice cores, we can examine changes in sources of methane and in the oxidation capacity of the atmosphere

Lessons Learned from Crowdsourcing Complex Engineering Tasks

<div><p>Crowdsourcing</p><p>Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simulations.</p><p>Harnessing Crowdworkers for Engineering</p><p>Our investigation examined the feasibility of using crowdsourcing for complex, highly technical tasks. This was done to determine if the benefits of crowdsourcing could be harnessed to accurately and effectively contribute to solving complex real world engineering problems. Of course, untrained crowds cannot be used as a mere substitute for trained expertise. Rather, we sought to understand how crowd workers can be used as a large pool of labor for a preliminary analysis of complex data.</p><p>Virtual Wind Tunnel</p><p>We compared the skill of the anonymous crowd workers from Amazon Mechanical Turk with that of civil engineering graduate students, making a first pass at analyzing wind simulation data. For the first phase, we posted analysis questions to Amazon crowd workers and to two groups of civil engineering graduate students. A second phase of our experiment instructed crowd workers and students to create simulations on our Virtual Wind Tunnel website to solve a more complex task.</p><p>Conclusions</p><p>With a sufficiently comprehensive tutorial and compensation similar to typical crowd-sourcing wages, we were able to enlist crowd workers to effectively complete longer, more complex tasks with competence comparable to that of graduate students with more comprehensive, expert-level knowledge. Furthermore, more complex tasks require increased communication with the workers. As tasks become more complex, the employment relationship begins to become more akin to outsourcing than crowdsourcing. Through this investigation, we were able to stretch and explore the limits of crowdsourcing as a tool for solving complex problems.</p></div

A flow visualization view of a simulation containing a triangular cross-section.

<p>This figure shows a colored flow visualization of the fluid velocity. The colors vary from red through white to blue. The red represents fast air, blue represents slow air, and white represents median speed air. This graph is meant to allow the reader to see the varying wind speeds around a structure.</p

Screenshot of the Virtual Wind Tunnel Website.

<p>A screenshot of a page of the Virtual Wind Tunnel website that contains the tools for creating the simulations and was used by the crowdworkers in phase two of the experiment. This page shows various figures which are generated in each simulation. This simulation result shows a cross-section, simulation mesh, flow visualization and a velocity plot. Users can click on these images to see larger versions and get access to more results and images. There is also a summary of the simulation provided below the figures followed by a listing of the parameters used.</p