Showing papers by "Hong Wang published in 2023"

Unambiguous identification of N-containing oxygenated organic molecules using a chemical-ionization Orbitrap (CI-Orbitrap) in an eastern Chinese megacity

Abstract: Abstract. Oxygenated organic molecules (OOMs) are dominated by the N-containing species in polluted urban environments. As N-containing OOMs, especially those with more than one nitrogen atom, prevail in the high m/z (mass-to-charge) range (m/z> 350 Th), unambiguous identification of N-containing OOMs is highly desirable for understanding of their formation processes, precursors and influencing factors. To achieve this, we applied an ultra-high-resolution chemical-ionization Orbitrap (CI-Orbitrap) in a field campaign and found that OOMs contain one (1N-OOMs), two (2N-OOMs) and three (3N-OOMs) nitrogen atoms comprised 50 %, 26 % and 4 %, respectively, of total OOMs. More interestingly, the fraction of 2N-OOMs increased with the increase in carbon number (nC) and was dominated by the ones derived from aliphatic precursors (2N-OOMAli, 64.2 %), indicating the importance of multistep oxidation. Plausible precursors of 2N-OOMs were aliphatics (2N-OOMAli, 64.2 %), aromatics (2N-OOMAro, 16 %) and monoterpenes (2N-OOMMT, 15.4 %). The absolute concentrations of 2N-OOMs were greatly affected by the pollution level for most cases. The 2N-OOMAli was the most abundant 2N-OOM, and its fraction even increased on the polluted day with an enhanced proportion of the ones with nC >10. While 2N-OOMAli and 2N-OOMAro were dominated by daytime photochemical production, nighttime NO3-initiated oxidation played a comparable role to the daytime photochemistry in the formation of 2N-OOMMT. The 2N-OOMAro species were of the highest oxygenation level, followed by 2N-OOMMT and 2N-OOMAli, which were affected by photochemistry and NOx concentrations. These results highlight the significant formation of 2N-OOMs and the influencing factors on their formation in polluted urban environments, where various volatile organic compound (VOC) precursors and atmospheric oxidants are present.

Novel Carbazole-Based Porous Organic Polymer for Efficient Iodine Capture and Rhodamine B Adsorption.

Abstract: A new porous organic polymer (CTF-CAR), which takes carbazole as the electron-rich center unit and thiophenes as the auxiliary group, has been synthesized through catalyst-free Schiff-base polymerization. At the same time, the structure, thermal stability, morphology, and other basic properties of the polymer were analyzed by IR, NMR, TGA, and SEM. Then, CTF-CAR was applied to iodine capture and rhodamine B adsorption. Due to its strong electron donor ability and abundant heteroatom binding sites, which have a positive effect on the interaction between the polymer network and adsorbates, CTF-CAR exhibits high uptake capacities for iodine vapor and rhodamine B as 2.86 g g-1 and 199.7 mg g-1, respectively. The recyclability test also confirmed that it has good reusability. We found that this low-cost and catalyst-free synthetic porous organic polymer has great potential for the treatment of polluted water and iodine capture.

Enhanced Removal of Doxycycline by Simultaneous Potassium Ferrate(VI) and Montmorillonite: Reaction Mechanism and Synergistic Effect

Abstract: Doxycycline (DOX), a typical antibiotic, is harmful to aquatic ecosystems and human health. This study presents DOX removal by potassium ferrate (Fe(VI)) and montmorillonite and investigates the effect of Fe(VI) dosage, reaction time, initial pH value, montmorillonite dosage, adsorption pH, time and temperature on DOX removal. The results show that DOX removal increases when increasing the Fe(VI) dosage, with the optimal condition for DOX removal (~97%) by Fe(VI) observed under a molar ratio ([Fe(VI)]:[DOX]) of 30:1 at pH 7. The reaction of DOX with Fe(VI) obeyed second-order kinetics with a rate constant of 10.7 ± 0.45 M−1 s−1 at pH 7. The limited promotion (~4%) of DOX adsorption by montmorillonite was observed when the temperature increased and the pH decreased. Moreover, the synergetic effect of Fe(VI) and montmorillonite on DOX removal was obtained when comparing the various types of dosing sequences (Fe(VI) oxidation first and then adsorption; adsorption first and then Fe(VI) oxidation; simultaneous oxidation and adsorption). The best synergistic effect of DOX removal (97%) was observed under the simultaneous addition of Fe(VI) and montmorillonite, maintaining the Fe(VI) dosage (from 30:1 to 5:1). Five intermediates were detected during DOX degradation, and a plausible DOX degradation pathway was proposed.

Real-time measurement of phase partitioning of organic compounds using a proton-transfer-reaction time-of-flight mass spectrometer coupled to a CHARON inlet

Abstract: Abstract. Understanding the gas–particle partitioning of semivolatile organic compounds (SVOCs) is of crucial importance in the accurate representation of the global budget of atmospheric organic aerosols. In this study, we quantified the gas- vs. particle-phase fractions of a large number of SVOCs in real time in an urban area of East China with the use of a CHemical Analysis of aeRosols ONline (CHARON) inlet coupled to a high-resolution proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS). We demonstrated the use of the CHARON inlet for highly efficient collection of particulate SVOCs while maintaining the intact molecular structures of these compounds. The collected month-long dataset with hourly resolution allows us to examine the gas–particle partitioning of a variety of SVOCs under ambient conditions. By comparing the measurements with model predictions using instantaneous equilibrium partitioning theory, we found that the dissociation of large parent molecules during the PTR ionization process likely introduces large uncertainties to the measured gas- vs. particle-phase fractions of less oxidized SVOCs, and therefore, caution should be taken when linking the molecular composition to the particle volatility when interpreting the PTR-ToF-MS data. Our analysis suggests that understanding the fragmentation mechanism of SVOCs and accounting for the neutral losses of small moieties during the molecular feature extraction from the raw PTR mass spectra could reduce, to a large extent, the uncertainties associated with the gas–particle partitioning measurement of SVOCs in the ambient atmosphere.

Biochar Addition in Membrane Bioreactor Enables Membrane Fouling Alleviation and Nitrogen Removal Improvement for Low C/N Municipal Wastewater Treatment

Abstract: Membrane bioreactors (MBRs) are frequently used to treat municipal wastewater, but membrane fouling is still the main weakness of this technology. Additionally, the low carbon-nitrogen (C/N) ratio influent has been shown to not only increase the membrane fouling, but also introduce challenges to meet the effluent discharge standard for nitrogen removal. Herein, the authors addressed the challenges by adding cost-effective biochar. The results suggested that the biochar addition can enable membrane fouling alleviation and nitrogen removal improvement. The reduced membrane fouling can be ascribed to the biochar adsorption capacity, which facilitates to form bigger flocs with carbon skeleton in biochar as a core. As a result, the biochar addition significantly altered the mixed liquor suspension with soluble microbial product (SMP) concentration reduction of approximately 14%, lower SMP protein/polysaccharide ratio from 0.28 ± 0.02 to 0.22 ± 0.03, smaller SMP molecular weight and bigger sludge particle size from 67.68 ± 6.9 μm to 113.47 ± 4.8 μm. The nitrogen removal is also dramatically improved after biochar addition, which can be due to the initial carbon source release from biochar, and formation of aerobic–anaerobic microstructures. Microbial diversity analysis results suggested more accumulation of denitrification microbes including norank_f__JG30-KF-CM45 and Plasticicumulans. Less relative abundance of Aeromonas after biochar addition suggested less extracellular polymer substance (EPS) secretion and lower membrane fouling rate.

Cellular immunotherapy combined with platinum-based chemotherapy prolongs survival for non-small cell lung cancer patients.

Abstract: Platinum-based chemotherapy is the primary treatment option for advanced non-small cell lung cancer (NSCLC) patients without a driver gene mutation, but its efficacy is still modest. Through a potential synergistic effect, autologous cellular immunotherapy (CIT) composed of cytokine-induced killer (CIK, natural killer (NK), and T cells) might enhance it. NK cells exhibited in vitro cytotoxicity toward lung cancer cells (A549 cells) following platinum therapy. Using flow cytometry, the expression of MICA, MICB, DR4, DR5, CD112, and CD155 on lung cancer cells was assessed. In this retrospective cohort study, there were included 102 previously untreated stage IIIB/IV NSCLC patients ineligible for tyrosine kinase inhibitor (TKI) target therapy who received either chemotherapy alone (n = 75) or combination therapy (n = 27). The cytotoxicity of NK cells for A549 cells was increased obviously and a time-dependent enhancement of this effect was also observed. After platinum therapy, the levels of MICA, MICB, DR4, DR5, CD112, and CD155 on the surface of A549 cells were increased. In the combination group, the median PFS was 8.3 months, compared to 5.5 months in the control group (p = 0.042); the median overall survival was 18.00 months, compared to 13.67 months in the combined group (p = 0.003). The combination group had no obvious immune-related adverse effects. The combination of NK cells with platinum showed synergistic anticancer effects. Combining the two strategies increased survival with minor adverse effects. Incorporating CIT into conventional chemotherapy regimens may improve NSCLC treatment. However, additional evidence will require multicenter randomized controlled trials.

Measurement report: Underestimated reactive organic gases from residential combustion – insights from a near-complete speciation

Abstract: Abstract. Reactive organic gases (ROGs), as important precursors of secondary pollutants, are not well resolved as their chemical complexity has challenged their quantification in many studies. Here, a near-complete speciation of ROG emissions from residential combustion was developed by the combination of proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) with a gas chromatography system equipped with a mass spectrometer and a flame ionization detector (GC-MS/FID), including 1049 species in all. Among them, 125 identified species, ∼ 90 % of the total ROG masses, were applied to evaluate their emission characteristics through real combustion samplings in rural households of China. The study revealed that with 55 species, mainly oxygenated species, higher hydrocarbons with ≥8 carbon atoms, and nitrogen-containing species, previously un- and under-characterized, ROG emissions from residential coal and biomass combustion were underestimated by 44.3 % ± 11.8 % and 22.7 % ± 3.9 %, respectively, which further amplified the underestimation of secondary organic aerosol formation potential (SOAP) as high as 70.3 % ± 1.6 % and 89.2 % ± 1.0 %, respectively. The hydroxyl radical reactivity (OHR) of ROG emissions was also undervalued significantly. The study provided a feasible method for the near-complete speciation of ROGs in the atmosphere and highlighted the importance of acquiring completely speciated measurement of ROGs from residential emissions, as well as other processes.

An Observational Constraint of VOC Emissions for Air Quality Modeling Study in the Pearl River Delta Region

Abstract: Volatile organic compounds (VOCs) have crucial influences on atmospheric chemistry. Accurate quantification of the VOC emissions is critical for air pollution research, especially when applying to air quality models. However, current bottom‐up emission inventories have biases, making observational constraints of VOC emissions necessary. We conducted concurrent VOC measurements in the Pearl River Delta (PRD) region during the summer of 2018 and found large discrepancies in the spatiotemporal variations of VOCs between observations and model simulations when using the priori VOC emission inventory (Multi‐resolution Emission Inventory for China). The normalized biases of total VOC concentrations ranged from −55% to 85% across the PRD cities in the study period. To improve the simulations, we constrained the anthropogenic VOC emissions based on their measured concentrations. The observation‐constrained VOC emissions showed clear diurnal variations and resolved the spatially‐concentrated priori emissions by reducing the high emissions by 15%–36% in the central PRD cities while elevating the sparse emissions in other cities. After employing the observation‐constrained VOC emissions, the model better reproduced the spatiotemporal variations of VOCs in the PRD region, alleviating the biases to −13%–13%. Furthermore, simulations of peak ozone (O3) concentrations were amended to reduce the mean normalized bias by 5%–12% on high O3 days. Our work has effectively combined VOC field measurements with air quality modeling to achieve better simulations of VOCs and O3. Besides, the observational‐constrained emissions are flexible for studying short‐term emission changes and their subsequent impacts on air quality.

Precise prediction of launch speed for athletes in the aerials event of freestyle skiing based on deep transfer learning

Abstract: Abstract Automatically obtaining the launch speed are powerful guarantees for athletes in the aerials event of freestyle skiing to achieve good results. In most of the published studies describing athletes getting high scores, the assisting sliding distance depends entirely on the coach and even the athlete’s own experience, which may not be optimal. The main goal of the present paper is to use an acquisition system and develop an artificial neural network (ANN) model to automatically obtain the corresponding relationship between assisting sliding distance and speed. The influence of snow friction coefficient, wind speed, wind direction, slope, height and weight can be simulated in the Unity3D engine. The influence of temperature, humidity and tilt angle needs to be measured in real world by professional testers which is strenuous. The neural network is first trained by sufficient simulation data to obtain the encoded feature. Then, the information learned in simulation environment is transferred to another network. The second network uses the data taken from twenty professional testers. Compared with the model without transfer learning, the performance of proposed method has significant improvement. The mean squared error for the testing set is 0.692. It is observed that the speed predicted by the designed deep transfer learning (DTL) model is in good agreement with the experimental measurement results. The results indicate that the proposed transfer learning method is an efficient model to be used as a tool for predicting the assisting sliding distance and launch speed for athletes in the aerials event of freestyle skiing.

Random Multi-access Scheme Based on Group Testing Theory for Massive Machine-type Communication

Abstract: Considering emerging massive machine-type communication with very few devices simultaneously transmitting short messages, random multiple access has currently become a research hot spot since the traditional multiple access protocol struggles to work properly. Inspired by the superimposed code, a channel assignment scheme based on non-adaptive group testing theory is proposed to allow multiple users to share a single channel at the same time. A superimposed code with threshold value d, which can recover the original code through the Boolean sum of up to d codes, is constructed by studying the problem of group testing. When the number of active users with a message to be transmitted is no more than the threshold value, active users encode their messages by the superimposed code and multiple active users transmit their messages together by sharing a single channel. The receiver can decode the mixed messages by the disjunction of the superimposed code. We focus on the design of the superimposed code by group testing theory, formulate this problem as the construction of a transversal design, and use the Latin square to form a useful transversal design. Theoretical proof shows that our design works well under limited circumstances where the number of active users does not exceed the threshold value. Additionally, our design can recover the original codes by the mixture of codes, which are more easily than the algorithms based on compressive sensing. Simulation analysis presents that our design performs better than the traditional competitive access protocols in terms of successful probability, throughput, and packet loss rate.