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Monitoring and modeling wetland chloride concentrations in relationship to oil and gas development

Overview of attention for article published in Journal of Environmental Management, March 2015
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Title
Monitoring and modeling wetland chloride concentrations in relationship to oil and gas development
Published in
Journal of Environmental Management, March 2015
DOI 10.1016/j.jenvman.2014.10.028
Pubmed ID
Authors

Max Post van der Burg, Brian A. Tangen

Abstract

Extraction of oil and gas via unconventional methods is becoming an important aspect of energy production worldwide. Studying the effects of this development in countries where these technologies are being widely used may provide other countries, where development may be proposed, with some insight in terms of concerns associated with development. A fairly recent expansion of unconventional oil and gas development in North America provides such an opportunity. Rapid increases in energy development in North America have caught the attention of managers and scientists as a potential stressor for wildlife and their habitats. Of particular concern in the Northern Great Plains of the U.S. is the potential for chloride-rich produced water associated with unconventional oil and gas development to alter the water chemistry of wetlands. We describe a landscape scale modeling approach designed to examine the relationship between potential chloride contamination in wetlands and patterns of oil and gas development. We used a spatial Bayesian hierarchical modeling approach to assess multiple models explaining chloride concentrations in wetlands. These models included effects related to oil and gas wells (e.g. age of wells, number of wells) and surficial geology (e.g. glacial till, outwash). We found that the model containing the number of wells and the surficial geology surrounding a wetland best explained variation in chloride concentrations. Our spatial predictions showed regions of localized high chloride concentrations. Given the spatiotemporal variability of regional wetland water chemistry, we do not regard our results as predictions of contamination, but rather as a way to identify locations that may require more intensive sampling or further investigation. We suggest that an approach like the one outlined here could easily be extended to more of an adaptive monitoring approach to answer questions about chloride contamination risk that are of interest to managers.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Unknown 33 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 29%
Unspecified 5 14%
Student > Ph. D. Student 5 14%
Student > Bachelor 3 9%
Other 3 9%
Other 9 26%
Readers by discipline Count As %
Unspecified 10 29%
Environmental Science 7 20%
Agricultural and Biological Sciences 7 20%
Earth and Planetary Sciences 4 11%
Engineering 3 9%
Other 4 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 December 2014.
All research outputs
#7,373,915
of 11,839,155 outputs
Outputs from Journal of Environmental Management
#1,179
of 1,909 outputs
Outputs of similar age
#133,762
of 260,359 outputs
Outputs of similar age from Journal of Environmental Management
#23
of 37 outputs
Altmetric has tracked 11,839,155 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,909 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 260,359 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.