Optimal spatiotemporal scales to aggregate satellite ocean color data for nearshore reefs and tropical coastal waters: two case studies

Remotely sensed ocean color data are useful for monitoring water quality in coastal environments. However, moderate resolution (hundreds of meters to a few kilometers) satellite data are underutilized in these environments because of frequent data gaps from cloud cover and algorithm complexities in shallow waters. Aggregating satellite data over larger space and time scales is a common method to reduce data gaps and generate a more complete time series, but potentially smooths out the small-scale, episodic changes in water quality that can have ecological influences. By comparing aggregated satellite estimates of Kd(490) with related in-water measurements, we can understand the extent to which aggregation methods are viable for filling gaps while being able to characterize ecologically relevant water quality conditions. In this study, we tested a combination of six spatial and seven temporal scales for aggregating data from the VIIRS instrument at several coral reef locations in Maui, Hawai‘i and Puerto Rico and compared these with in situ measurements of Kd(490) and turbidity. In Maui, we found that the median value of a 5-pixels, 7-days spatiotemporal cube of satellite data yielded a robust result capable of differentiating observations across small space and time domains and had the best correlation among spatiotemporal cubes when compared with in situ Kd(490) across 11 nearshore sites (R2 = 0.84). We also found long-term averages (i.e., chronic condition) of VIIRS data using this aggregation method follow a similar spatial pattern to onshore turbidity measurements along the Maui coast over a three-year period. In Puerto Rico, we found that the median of a 13-pixels, 13-days spatiotemporal cube of satellite data yielded the best overall result with an R2 = 0.54 when compared with in situ Kd(490) measurements for one nearshore site with measurement dates spanning 2016–2019. As spatiotemporal cubes of different dimensions yielded optimum results in the two locations, we recommend local analysis of spatial and temporal optima when applying this technique elsewhere. The use of satellite data and in situ water quality measurements provide complementary information, each enhancing understanding of the issues affecting coastal ecosystems, including coral reefs, and the success of management efforts

Performance and Sustainability Tradeoffs of Oxidized Carbon Nanotubes as a Cathodic Material in Lithium‐Oxygen Batteries

Climate change mitigation efforts will require a portfolio of solutions, including improvements to energy storage technologies in electric vehicles and renewable energy sources, such as the high‐energy‐density lithium‐oxygen battery (LOB). However, if LOB technology will contribute to addressing climate change, improvements to LOB performance must not come at the cost of disproportionate increases in global warming potential (GWP) or cumulative energy demand (CED) over their lifecycle. Here, oxygen‐functionalized multi‐walled carbon nanotube (O‐MWCNT) cathodes were produced and assessed for their initial discharge capacities and cyclability. Contrary to previous findings, the discharge capacity of O‐MWCNT cathodes increased with the ratio of carbonyl/carboxyl moieties, outperforming pristine MWCNTs. However, increased oxygen concentrations decreased LOB cyclability, while high‐temperature annealing increased both discharge capacity and cyclability. Improved performance resulting from MWCNT post‐processing came at the cost of increased GWP and CED, which in some cases was disproportionately higher than the level of improved performance. Based on the findings presented here, there is a need to simultaneously advance research in improving LOB performance while minimizing or mitigating the environmental impacts of LOB production.Green in the (power) bank: Altering the properties, structures, and surface chemistry of multi‐walled carbon nanotubes can make them more effective Li‐air battery cathodes, but only annealing and select oxidation techniques lead to a net environmental benefit.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166425/1/cssc202002317.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/166425/2/cssc202002317_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/166425/3/cssc202002317-sup-0001-misc_information.pd

The effect of sucralose on flavor sweetness in electronic cigarettes varies between delivery devices.

The appeal of sweet electronic cigarette flavors makes it important to identify the chemical compounds that contribute to their sweetness. While volatile chemicals that produce sweet aromas have been identified in e-liquids, there are no published reports of sugars or artificial sweeteners in commercial e-liquids. However, the sweetener sucralose is marketed as an e-liquid additive to commercial flavors. The primary aims of the study were to determine if sucralose is delivered in sufficient concentration in the inhaled aerosol to enhance flavor sweetness, and whether the amount delivered depends on the e-liquid delivery system. Thirty-two adult smokers rated flavor intensity, sweetness, harshness and liking/disliking for 4 commercial flavors with and without sucralose (1%) using 2 e-cigarette delivery systems (cartridge and tank). Participants alternately vaped normally or with the nose pinched closed to block perception of volatile flavor components via olfaction. LC/MS was used to measure the concentration of sucralose in the e-liquid aerosols using a device that mimicked vaping. Sweetness and flavor intensity were perceived much more strongly when olfaction was permitted. The contribution of sucralose to sweetness was significant only for the cartridge system, and the chemical analysis showed that the concentration of sucralose in the aerosol was higher when the cartridge was used. Together these findings indicate that future regulation of sweet flavor additives should focus first on the volatile constituents of e-liquids with the recognition that artificial sweeteners may also contribute to flavor sweetness depending upon e-cigarette design

Mean ratings of liking/disliking.

<p>Mean ratings of <i>liking/disliking</i> across both e-cig devices for all e-liquids sampled alone (gray bars) and with 1% sucralose (black bars). Olfaction = nose open, No Olfaction = nose closed. The data show that liking differed significantly between olfactory conditions, as seen by higher ratings with the nose open, and across flavors. The letters on the right-y axis represent labels on the Labeled Hedonic Scale (LHS): DM = Dislike Moderately, DS = Dislike Slightly, N = Neutral, LS = Like Slightly, LM = Like Moderately. Vertical bars represent standard errors of the mean.</p

Ratings of overall flavor, sweetness and harshness intensity.

<p>Log₁₀ mean ratings of (A) Overall Flavor, (B) Sweetness and (C) Harshness/Irritation intensity for each e-liquid alone (gray bars) and with 1% sucralose added (black bars). Data from the V2 EX tanks are on the left and the V2 cartridges on the right under 2 vaping conditions: Olfaction = nose open, No Olfaction = nose closed. The data show that in the No Olfaction condition <i>overall flavor</i> and <i>sweetness</i> were significantly attenuated compared to the Olfaction condition for both E-cigarettes, and that sucralose produced significant increases in the same 2 flavor categories only when added to the V2 cartridges. The letters on the right y-axis represent semantic labels of intensity on the general Labeled Magnitude Scale (gLMS): BD = Barely Detectable; W = Weak; M = Moderate; S = Strong. Vertical bars are standard errors of the mean.</p

Mass change of the e-liquid after 20 puffs as well as amount of condensate found inside of the mouthpiece, the mass, and resulting concentration (μg/mg) of sucralose found in the trapped vapor and the mouthpiece condensate.

<p>Mass change of the e-liquid after 20 puffs as well as amount of condensate found inside of the mouthpiece, the mass, and resulting concentration (μg/mg) of sucralose found in the trapped vapor and the mouthpiece condensate.</p

Shown are the 2 e-cigarette delivery systems that were tested.

<p>The systems (cartridge/cartomizer and tank/clearomizer) are powered by the same battery (left), but differ in the way e-liquids are stored and delivered to the heating element (i.e., in a saturated, rolled cotton/ceramic pad vs. a tank containing a braided cotton/ceramic wick) and in the design and size of the mouthpiece.</p

Measured sucralose concentrations.

<p>Average sucralose concentration (μg/mg) found across all flavors in the mouthpiece (gray bars) condensate and the vapor trap (black bars). Data from V2 tanks are shown on the left and V2 cartridges shown on the right. Error bars show standard error (n = 12 for tank, n = 15 for cartridge).</p