Long-term trends and drivers of aerosol pH in eastern China

Aerosol acidity plays a key role in regulating the chemistry and toxicity of atmospheric aerosol particles. The trend of aerosol pH and its drivers is crucial in understanding the multiphase formation pathways of aerosols. Here, we reported the first trend analysis of aerosol pH from 2011 to 2019 in eastern China, calculated with the ISORROPIA model based on observed gas and aerosol compositions. The implementation of the Air Pollution Prevention and Control Action Plan led to −35.8 %, −37.6 %, −9.6 %, −81.0 % and 1.2 % changes of PM2.5, SO42-, NHx, non-volatile cations (NVCs) and NO3- in the Yangtze River Delta (YRD) region during this period. Different from the drastic changes of aerosol compositions due to the implementation of the Air Pollution Prevention and Control Action Plan, aerosol pH showed a minor change of −0.24 over the 9 years. Besides the multiphase buffer effect, the opposite effects from the changes of SO42- and non-volatile cations played key roles in determining this minor pH trend, contributing to a change of +0.38 and −0.35, respectively. Seasonal variations in aerosol pH were mainly driven by the temperature, while the diurnal variations were driven by both temperature and relative humidity. In the future, SO2, NOx and NH3 emissions are expected to be further reduced by 86.9 %, 74.9 % and 41.7 % in 2050 according to the best health effect pollution control scenario (SSP1-26-BHE). The corresponding aerosol pH in eastern China is estimated to increase by ∼0.19, resulting in 0.04 less NO3- and 0.12 less NH4+ partitioning ratios, which suggests that NH3 and NOx emission controls are effective in mitigating haze pollution in eastern China.</p

Water-Soluble Single-Benzene Chromophores: Excited State Dynamics and Fluorescence Detection

Two water-soluble single-benzene-based chromophores, 2,5-di(azetidine-1-yl)-tereph- thalic acid (DAPA) and its disodium carboxylate (DAP-Na), were conveniently obtained. Both chromophores preserved moderate quantum yields in a wide range of polar and protonic solvents. Spectroscopic studies demonstrated that DAPA exhibited red luminescence as well as large Stokes shift (>200 nm) in aqueous solutions. Femtosecond transient absorption spectra illustrated quadrupolar DAPA usually involved the formation of an intramolecular charge transfer state. Its Frank–Condon state could be rapidly relaxed to a slight symmetry-breaking state upon light excitation following the solvent relaxation, then the slight charge separation may occur and the charge localization became partially asymmetrical in polar environments. Density functional theory (DFT) calculation results were supported well with the experimental measurements. Unique pH-dependent fluorescent properties endows the two chromophores with rapid, highly selective, and sensitive responses to the amino acids in aqueous media. In detail, DAPA served as a fluorescence turn-on probe with a detection limit (DL) of 0.50 μM for Arg and with that of 0.41 μM for Lys. In contrast, DAP-Na featured bright green luminescence and showed fluorescence turn-off responses to Asp and Glu with the DLs of 0.12 μM and 0.16 μM, respectively. Meanwhile, these two simple-structure probes exhibited strong anti-interference ability towards other natural amino acids and realized visual identification of specific analytes. The present work helps to understand the photophysic–structure relationship of these kinds of compounds and render their fluorescent detection applications

High-Dimensional Uncertainty Quantification in Electrical Impedance Tomography Forward Problem Based on Deep Neural Network

In electrical impedance tomography (EIT), the uncertainty of conductivity distribution may cause the uncertainty in the forward calculation and further affect the inverse problem. In this paper, an improved univariate dimension reduction method based on deep neural network (DNN-UDR) is proposed for the high-dimensional uncertainty quantification in EIT forward problem. Firstly, DNN is studied to build a substitute model for EIT forward problem in order to solve the high-dimensional problem. Three normalized circular finite element models are established with random uniform conductivity distribution. Then UDR is used to analyze and quantify the uncertainty in the simulation with the form of probability. Compared with Monte Carlo simulation (MCS), the probability distribution of voltage is fitted, and the quantification indicators such as mean, variance, variation coefficient and covariance, are also consistent. On the other hand, with the increase of parameter dimensions, DNN-UDR accelerates the computations obviously. This indicates that DNN-UDR is effective and has high structural stability, accurate prediction results and high computational efficiency

Application of artificial intelligence in ophthalmic plastic surgery

The advancement of computers and data explosion have ushered in the third wave of artificial intelligence(AI). AI is an interdisciplinary field that encompasses new ideas, new theories, and new technologies, etc. AI has brought convenience to ophthalmology application and promoted its intelligent, precise, and minimally invasive development. At present, AI has been widely applied in various fields of ophthalmology, especially in oculoplastic surgery. AI has made rapid progress in image detection, facial recognition, etc., and its performance and accuracy have even surpassed humans in some aspects. This article reviews the relevant research and applications of AI in oculoplastic surgery, including ptosis, single eyelid, pouch, eyelid mass, and exophthalmos, and discusses the challenges and opportunities faced by AI in oculoplastic surgery, and provides prospects for its future development, aiming to provide new ideas for the development of AI in oculoplastic surgery

Orbitool : a software tool for analyzing online Orbitrap mass spectrometry data

The Orbitrap mass spectrometer has recently been proved to be a powerful instrument to accurately measure gas-phase and particle-phase organic compounds with a greater mass resolving power than other widely used online mass spectrometers in atmospheric sciences. We develop an open-source software tool (Orbitool, https://orbitrap.catalyse.cnrs.fr, last access: 4 February 2021) to facilitate the analysis of long-term online Orbitrap data. Orbitool can average long-term data while improving the mass accuracy by re-calibrating each mass spectrum, assign molecular formulae of compounds and their isotopes to measured signals, and export time series and mass defect plots. The noise reduction procedure in Orbitool can separate signal peaks from noise and reduce the computational and storage expenses. Chemical ionization Orbitrap data from laboratory experiments on ozonolysis of monoterpenes and ambient measurements in urban Shanghai were used to test Orbitool. For the test dataset, the average mass accuracy was improved from < 2 to < 0.5 ppm by mass calibrating each spectrum. The denoising procedure removed 97% of the noise peaks from a spectrum averaged for 30 min while maintaining the signal peaks, substantially helping the automatic assignment of unknown species. To illustrate the capabilities of Orbitool, we used the most challenging and complex dataset we have collected so far, which consists of ambient gas-phase measurements in urban Shanghai. These tests showed that Orbitool was able to automatically assign hundreds of molecular formulae as well as their isotopes with high accuracy.Peer reviewe

Characteristics of Black Carbon Particle-Bound Polycyclic Aromatic Hydrocarbons in Two Sites of Nanjing and Shanghai, China

Airborne polycyclic aromatic hydrocarbons (PAHs) are of great concern to human health due to their potential high toxicity. Understanding the characteristics and sources of PAHs, as well as the governing factors, is therefore critical. PAHs and refractory black carbon (rBC) are both from combustion sources. This work, for the first time, investigated exclusively the rBC-bound PAH properties by using a laser-only Aerodyne soot-particle aerosol mass spectrometer (SP-AMS). This technique offers highly time-resolved PAH results that a traditional offline measurement is unable to provide. We analyzed two datasets conducted in urban Shanghai during the fall of 2018 and in suburban Nanjing during the winter of 2017, respectively. Results show that the average concentration of PAHs in Nanjing was much higher than that in Shanghai. Nanjing PAHs contained more low molecular weight components while Shanghai PAHs contained more high molecular weight ones. PAHs in Shanghai presented two peaks in early morning and evening, while Nanjing PAHs had only one significant morning peak, but remained high throughout the nighttime. A multi-linear regression algorithm combined with positive matrix factorization (PMF) analyses on sources of PAHs reveals that the industry emissions contributed the majority of PAHs in Nanjing (~80%), while traffic emissions dominated PAHs in Shanghai (~70%). We further investigated the relationships between PAHs with various factors. PAHs in both sites tended to positively correlate with primary pollutants, including primary organic aerosol (OA) factors, and gaseous pollutants of CO, NO2 and SO2, but negatively correlated with secondary OA factors and O3. This result highlights the enhancement of rBC-bound PAHs level due to primary emissions and their oxidation loss upon atmospheric aging reactions. High concentration of PAHs seemed to frequently appear under low temperature and high relative humidity conditions, especially in Shanghai

Highly Compatible Hydroxyl-Functionalized Microporous Polyimide-ZIF‑8 Mixed Matrix Membranes for Energy Efficient Propylene/Propane Separation

Mixed-matrix membranes composed of mechanically strong, solution-processable polymers and highly selective ultramicroporous fillers (pore size < 7 Å) are superior candidate membrane materials for various energy-intensive gas separation applications because of their structural tunability to achieve enhanced gas permeability and gas–pair selectivity. However, their industrial implementation has been severely hindered because inefficient compatibility of the polymer matrices and crystalline fillers results in poorly performing membranes with low filler capacity and interfacial defects. Herein, we report for the first time a unique strategy to fabricate highly propylene/propane selective mixed-matrix membranes (MMMs) composed of a hydroxyl-functionalized microporous polyimide (PIM-6FDA-OH) and an ultramicroporous, strongly size-sieving zeolitic imidazolate framework (ZIF-8). Excellent compatibility between PIM-6FDA-OH and ZIF-8 with selective filler loading up to 65 wt % resulted from N···O–H induced hydrogen bonding as evidenced by Fourier-transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS). The newly developed MMMs demonstrated <i>unprecedented mixed-gas performance</i> for C₃H₆/C₃H₈ separation and outstanding plasticization resistance of up to at least 7 bar feed pressure. The reported fabrication concept is expected to be applicable to a wide variety of OH-functionalized polymers and alternative tailor-made imidazolate framework materials designed for MMMs to achieve optimal gas separation performance