Abstract We examine the behavior of natural basaltic and trachytic samples during paleointensity experiments on both the original and laboratory‐acquired thermal remanences and characterize the samples using proxies for domain state including curvature (k) and the bulk domain stability parameters of Paterson (2011,https://doi.org/10.1029/2011JB008369) and Paterson et al. (2017,https://doi.org/10.1073/pnas.1714047114), respectively. A curvature value of 0.164 (suggested by Paterson, 2011,https://doi.org/10.1029/2011JB008369) as a critical threshold that separates single‐domain‐like remanences from multidomain‐like remanances on the original paleointensity data was used to separate samples into “straight” (single‐domain‐like) and “curved” (multidomain‐like) groups. Specimens from the two sample sets were given a “fresh” thermal remanent magnetization in a 70 μT field and subjected to an infield‐zerofield, zerofield‐infield (IZZI)‐type (Yu et al., 2004,https://doi.org/10.1029/2003GC000630) paleointensity experiment. The straight sample set recovered the laboratory field with high precision while the curved set had much more scattered results (70.5 ± 1.5 and 71.9 ± 5.2 μT, respectively). The average intensity of both sets for straight and curved was quite close to the laboratory field of 70 μT, however, suggesting that if experiments contain a sufficient number of specimens, there does not seem to be a large bias in the field estimate. We found that the dependence of the laboratory thermal remanent magnetization on cooling rate was significant in most samples and did not depend on domain states inferred from proxies based on hysteresis measurements and should be estimated for all samples whose cooling rates differ from that used in the laboratory.
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Multi‐Index Attribution of Extreme Winter Air Quality in Beijing, China
Abstract High‐impact poor air quality events, such as Beijing's so‐called “Airpocalypse” in January 2013, demonstrate that short‐lived poor air quality events can have significant effects on health and economic vitality. Poor air quality events result from the combination of the emission of pollutants and meteorological conditions favorable to their accumulation, which include limited scavenging, dispersion, and ventilation. The unprecedented nature of events such as the 2013 Airpocalypse, in conjunction with our nonstationary climate, motivate an assessment of whether climate change has altered the meteorological conditions conducive to poor winter air quality in Beijing. Using three indices designed to quantify the meteorological conditions that support poor air quality and drawing on the attribution methods of Diffenbaugh et al. (2017,https://doi.org/10.1073/pnas.1618082114), we assess (i) the contribution of observed trends to the magnitude of events, (ii) the contribution of observed trends to the probability of events, (iii) the return interval of events in the observational record, preindustrial model‐simulated climate and historical model‐simulated climate, (iv) the probability of the observed trend in the preindustrial and historical model‐simulated climates, and (v) the relative influences of anthropogenic forcing and natural variability on the observed trend. We find that anthropogenic influence has had a small effect on the probability of the January 2013 event in all three indices but has increased the probability of a long‐term positive trend in two out of three indices. This work provides a framework for both further understanding the role of climate change in air quality and expanding the scope of event attribution.
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- Award ID(s):
- 1848683
- PAR ID:
- 10458317
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 124
- Issue:
- 8
- ISSN:
- 2169-897X
- Page Range / eLocation ID:
- p. 4567-4583
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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