Pyrene-based monomer-excimer dual response organosilicon polymer for selective detection of 2,4,6-trinitrotoluene (TNT) and 2,4,6-trinitrophenol (TNP)

The formation or destruction of pyrene excimer with strong emission change make it a versatile fluorophore to construct excimer emission-based fluorescence probes for various analytes detection. The distinct difference between...

Rapid reduction in black carbon emissions from China: evidence from 2009–2019 observations on Fukue Island, Japan

A long-term, robust observational record of atmospheric black carbon (BC) concentrations at Fukue Island for 2009–2019 was produced by unifying the data from a continuous soot monitoring system (COSMOS) and a Multi-Angle Absorption Photometer (MAAP). This record was then used to analyze emission trends from China. We identified a rapid reduction in BC concentrations of (-5.8±1.5) % yr−1 or −48 % from 2010 to 2018. We concluded that an emission change of (-5.3±0.7) % yr−1, related to changes in China of as much as −4.6 % yr−1, was the main underlying driver. This evaluation was made after correcting for the interannual meteorological variability (IAV) by using the regional atmospheric chemistry model simulations from the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models (collectively WRF/CMAQ) with the constant emissions. This resolves the current fundamental disagreements about the sign of the BC emissions trend from China over the past decade as assessed from bottom-up emission inventories. Our analysis supports inventories reflecting the governmental clean air actions after 2010 (e.g., MEIC1.3, ECLIPSE versions 5a and 6b, and the Regional Emission inventory in ASia (REAS) version 3.1) and recommends revisions to those that do not (e.g., Community Emissions Data System – CEDS). Our estimated emission trends were fairly uniform across seasons but diverse among air mass origins. Stronger BC reductions, accompanied by a reduction in carbon monoxide (CO) emissions, occurred in regions of south-central East China, while weaker BC reductions occurred in north-central East China and northeastern China. Prior to 2017, the BC and CO emissions trends were both unexpectedly positive in northeastern China during winter months, which possibly influenced the climate at higher latitudes. The pace of the estimated emissions reduction over China surpasses the Shared Socioeconomic Pathways (SSPs with reference to SSP1, specifically) scenarios for 2015–2030, which suggests highly successful emission control policies. At Fukue Island, the BC fraction of fine particulate matter (PM2.5) also steadily decreased over the last decade. This suggests that reductions in BC emissions started without significant delay when compared to other pollutants such as NOx and SO2, which are among the key precursors of scattering PM2.5.

Flexibility and Preorganization of Fluorescent Nucleobase-Pyrene Conjugates Control DNA and RNA Recognition

We synthesized a new amino acid-fluorescent nucleobase derivative (qAN1-AA) and from it two new fluorescent nucleobase–fluorophore (pyrene) conjugates, whereby only the analogue with the longer and more flexible linker (qAN1-pyr2) self-folded into intramolecularly stacked qAN1/pyrene conformation, yielding characteristic, 100 nm-red-shifted emission (λmax = 500 nm). On the contrary, the shorter and more rigid linker resulted in non-stacked conformation (qAN1-pyr1), characterized by the emission of free pyrene at λmax = 400 nm. Both fluorescent nucleobase–fluorophore (pyrene) conjugates strongly interacted with ds-DNA/RNA grooves with similar affinity but opposite fluorescence response (due to pre-organization), whereas the amino acid-fluorescent base derivative (qAN1-AA) was inactive. However, only intramolecularly self-folded qAN1-pyr2 showed strong fluorescence selectivity toward poly U (Watson–Crick complementary to qAN1 nucleobase) and poly A (reverse Hoogsteen complementary to qAN1 nucleobase), while an opposite emission change was observed for non-complementary poly G and poly C. Non-folded analogue (qAN1-pyr1) showed no ss-RNA selectivity, demonstrating the importance of nucleobase-fluorophore pre-organization.

NOx Emission Reduction and Recovery during COVID-19 in East China

Since its first confirmed case at the end of 2019, COVID-19 has become a global pandemic in three months with more than 1.4 million confirmed cases worldwide, as of early April 2020. Quantifying the changes of pollutant emissions due to COVID-19 and associated governmental control measures is crucial to understand its impacts on economy, air pollution, and society. We used the WRF-GC model and the tropospheric NO2 column observations retrieved by the TROPOMI instrument to derive the top-down NOx emission change estimation between the three periods: P1 (January 1st to January 22nd, 2020), P2 (January 23rd, Wuhan lockdown, to February 9th, 2020), and P3 (February 10th, back-to-work day, to March 12th, 2020). We found that NOx emissions in East China averaged during P2 decreased by 50% compared to those averaged during P1. The NOx emissions averaged during P3 increased by 26% compared to those during P2. Most provinces in East China gradually regained some of their NOx emissions after February 10, the official back-to-work day, but NOx emissions in most provinces have not yet to return to their previous levels in early January. NOx emissions in Wuhan, the first epicenter of COVID-19, had no sign of emission recovering by March 12. A few provinces, such as Zhejiang and Shanxi, have recovered fast, with their averaged NOx emissions during P3 almost back to pre-lockdown levels.

Fixed Anvil Temperature Feedback: Positive, Zero, or Negative?

The fixed anvil temperature (FAT) theory describes a mechanism for how tropical anvil clouds respond to global warming and has been used to argue for a robust positive longwave cloud feedback. A constant cloud anvil temperature, due to increased anvil altitude, has been argued to lead to a “zero cloud emission change” feedback, which can be considered positive relative to the negative feedback associated with cloud anvil warming when cloud altitude is unchanged. Here, partial radiative perturbation (PRP) analysis is used to quantify the radiative feedback caused by clouds that follow the FAT theory (FAT–cloud feedback) and to set this in the context of other feedback components in two atmospheric general circulation models. The FAT–cloud feedback is positive in the PRP framework due to increasing anvil altitude, but because the cloud emission does not change, this positive feedback is cancelled by an equal and opposite component of the temperature feedback due to increasing emission from the cloud. To incorporate this cancellation, the thermal radiative damping with fixed relative humidity and anvil temperature (T-FRAT) decomposition framework is proposed for longwave feedbacks, in which temperature, fixed relative humidity, and FAT–cloud feedbacks are combined. In T-FRAT, the cloud feedback under the FAT constraint is zero, while that under the proportionately higher anvil temperature (PHAT) constraint is negative. The change in the observable cloud radiative effect with FAT–cloud response is also evaluated and shown to be negative due to so-called cloud masking effects. It is shown that “cloud masking” is a misleading term in this context, and these effects are interpreted more generally as “cloud climatology effects.”

Deep neural network model to predict N2O emission change by biochar amendment in upland agricultural soils

<p>The N<sub>2</sub>O emission change by biochar addition in soils showed inconsistent trends depending on biochar types, soil properties, environmental conditions, and soil management practices. Especially in non-flooded upland agricultural soils, due to the complexity of N<sub>2</sub>O emission processes, which include nitrification, nitrifier-denitrification, and denitrification, there are still many gaps in the mechanistic understanding of biochar effects. In order to maximize climate change mitigating effect of biochar, the biochar application guidelines that consider N<sub>2</sub>O emission change need to be offered to farmers. However, the current lack of knowledge makes it challenging to create mechanistic models, and new approaches are needed. Machine learning techniques can be a solution because we can find the relationship between input and output variables without explicit mechanistic understanding and mathematical description. We aimed at developing a deep neural network (DNN) model to predict the N<sub>2</sub>O emission change from upland agricultural soils by biochar application. Among all the papers published between Jan 2007 ~ Jul 2019 collected from Web of Science Core Collection, 65 papers were chosen which report changes in N<sub>2</sub>O emissions by biochar addition in upland agricultural soils. Eleven variables, which have been reported as important factors influencing N<sub>2</sub>O emission, were selected as input parameters. These include 5 soil properties (Total carbon and nitrogen content, sand and clay content and pH), 3 biochar properties (Feedstock type, pyrolysis temperature and biochar application rate), and 3 agricultural practices (Fertilizer type, number of fertilization and N application rate). The output parameter is the ratio of the cumulative N<sub>2</sub>O emission of biochar treatment and control. Using 85% of the compiled dataset (training set), the DNN model was trained to predict the changes in N<sub>2</sub>O emission by biochar addition. The rest of the dataset (validation set) was used to validate the DNN model. As a result, the DNN model predicted the decreasing and increasing patterns of biochar driven N<sub>2</sub>O emission change in 84% of the validation data. This preliminary result could be a basis for developing practical biochar use guidelines. Further studies will be conducted to improve the prediction accuracy of the DNN model by combining principal component analysis.</p>

N2O changes during Heinrich Stadials - Isotopic source deconvolution over HS0, HS1 and HS4 and its implication for the marine and terrestrial nitrogen cycle

<p>Using high precision and centennial resolution ice core information on atmospheric nitrous oxide concentrations and its stable nitrogen and oxygen isotopic composition enables us to quantitatively reconstruct changes in the terrestrial and marine N<sub>2</sub>O emissions over the last 21,000 years as well as over Heinrich Stadial (HS) 4.</p><p>We show that over the deglaciation N<sub>2</sub>O emissions from land and ocean increased in parallel by 1.8 ± 0.3 TgN yr<sup>-1</sup> and 0.7 ± 0.3 TgN yr<sup>-1</sup>, respectively. However, close to 50% of the terrestrial increase is accomplished within less than 200 years at the end of HS1 starting essentially in parallel with the co-occurring CH<sub>4</sub> increase. A similarly rapid but smaller increase is observed at the end of HS0 and suggested at the end of HS4, showing that terrestrial N<sub>2</sub>O emissions respond strongly and rapidly to the northward shift in the Intertropical Convergence Zone connected to the resumption of the Atlantic Meridional Overturning Circulation (AMOC). However, little change in terrestrial N<sub>2</sub>O emissions is observed during the onsets of Heinrich Stadials. Assuming that N<sub>2</sub>O loss from terrestrial ecosystems is directly connected to nitrogen turnover in soils, the fast increase at the end of Heinrich Stadials suggests that terrestrial ecosystems did not become nitrogen-limited on this relatively short time scales, as also supported by model runs in our LPX-Bern dynamic vegetation/biogeochemical model. However, changes in number of moles of N<sub>2</sub>O lost to the atmosphere per mole nitrogen turned over in soils (yield factor) may also contribute to the atmospheric N<sub>2</sub>O changes.</p><p>Marine N<sub>2</sub>O emissions also respond to Heinrich events and AMOC changes, however more gradually and less strongly compared to terrestrial emissions both in our data-based reconstruction and the Bern3D coupled ocean/biogeochemistry model. In fact, reconstructed marine emissions start to slowly increase many centuries before the rapid warmings, connected to a re-equilibration of subsurface oxygen concentrations in response to previous AMOC changes. At the onset of HS1 marine emissions decreased by about 0.5 TgN yr<sup>-1</sup>, concomitantly with changes in atmospheric CO<sub>2</sub> and δ<sup>13</sup>C(CO<sub>2</sub>), and started to re-increase after about 1500 years, when also rapid CO<sub>2</sub> and CH<sub>4</sub> jumps occurred, pointing to Southern Ocean and low-latitude circulation changes. A similar decrease as at the start of HS1 is found after the onset of HS0, but little N<sub>2</sub>O emission change is suggested by N<sub>2</sub>O concentrations and their isotopic signature at 39.5 kyr before present when Heinrich Event 4 presumably occurred, as suggested by a co-occurring intermittent CH<sub>4</sub> peak and a sudden increase in CO<sub>2</sub>.</p>