| Title |
Particle size distribution predicts particulate phosphorus removal
|
|---|---|
| Published in |
Ambio, November 2017
|
| DOI | 10.1007/s13280-017-0981-z |
| Pubmed ID | |
| Authors |
Mark River, Curtis J. Richardson |
| Abstract |
Particulate phosphorus (PP) is often the largest component of the total phosphorus (P) load in stormwater. Fine-resolution measurement of particle sizes allows us to investigate the mechanisms behind the removal of PP in stormwater wetlands, since the diameter of particles influences the settling velocity and the amount of sorbed P on a particle. In this paper, we present a novel method to estimate PP, where we measure and count individual particles in stormwater and use the total surface area as a proxy for PP. Our results show a strong relationship between total particle surface area and PP, which we use to put forth a simple mechanistic model of PP removal via gravitational settling of individual mineral particles, based on a continuous particle size distribution. This information can help improve the design of stormwater Best management practices to reduce PP loading in both urban and agricultural watersheds. |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 20% |
| Researcher | 7 | 14% |
| Student > Master | 5 | 10% |
| Lecturer | 4 | 8% |
| Student > Bachelor | 3 | 6% |
| Other | 6 | 12% |
| Unknown | 15 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 12 | 24% |
| Agricultural and Biological Sciences | 5 | 10% |
| Engineering | 3 | 6% |
| Linguistics | 1 | 2% |
| Chemical Engineering | 1 | 2% |
| Other | 5 | 10% |
| Unknown | 23 | 46% |
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 07 December 2017.
All research outputs
#15,484,498
of 23,009,818 outputs
Outputs from Ambio
#1,439
of 1,633 outputs
Outputs of similar age
#265,044
of 437,742 outputs
Outputs of similar age from Ambio
#27
of 32 outputs
Altmetric has tracked 23,009,818 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.