ArticleACS omega2021
Distribution Law of the Temperature Inversion Layer in a Deep Open-Pit Mine.
Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using the methods of field experiment, numerical simulation, and theoretical analysis, a deep concave open-pit mine (DCOM) geometric model is established. Ansys Fluent software is used to simulate the change in the temperature field at night in the DCOM over time and analyze the probability of the spatial distribution of the temperature inversion layer. The results show that the location inside the stope close to the southwest edge is more likely to present temperature inversion, and the location close to the northeast edge is the least likely to have temperature inversion, and the height range where temperature inversion is likely to occur is 100-0 m. The simulated results reveal a greater probability of temperature inversion at the closed circle (+80 m), which is consistent with that obtained by field observation. Through multiple nonlinear regression analysis, a prediction model of the spatial distribution probability of the temperature inversion layer is established, which provides a theoretical basis for the prediction and control of atmospheric pollution in the DCOMs.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.