科研成果

Greenhouse gas mitigation and utilization attract huge attentions in energy and environment domains worldwide while few technologies enable to satisfy the both concurrently. In this study, a new greenhouse gas utilization technology, foamy emulsions, is initially developed and evaluated. Foamy emulsions usually have low production gas–liquid ratio but capable to facilitate the energy recovery. However, little researches have focused on the formation mechanism and flow property of foamy emulsions under greenhouse gas injection and the use of additives, which results in the relevant mechanism remains unclear. To address this problem, the formation process of foamy emulsions and the influence of the gas type, temperature and amount of viscosity reducer on the flow of foamy emulsions in the process of unconventional fossil fluids are investigated through a series of microscopic visualization experiments. According to the experimental results, the process of foamy emulsions formation can be divided into four stages, namely, the initial, early, middle and late stages. The middle stage corresponds to the period of steady flow of the foamy oil, with the largest number of bubbles and highest velocity. Moreover, the foamy emulsions formed using CO2 as the dissolved gas is the most effective, corresponding to an energy recovery factor of 40%. The effect of N2 is the most inferior, with the corresponding oil recovery factor being only 18%. Although the velocity of the bubbles increases with the increase in the temperature and amount of viscosity reducer, the stability of the bubbles degrades. The optimal effect of the foamy emulsions occurs at 80 °C with the amount of viscosity reducer being 1–3 wt%. This study will support the foundation of more general application pertaining to greenhouse gases mitigation and utilization in energy and environmental practices.

Prior mineral scaling investigations mainly studied the effects of membrane surface properties rather than on the mineral properties and their impact on membrane permeability. In our study, mass, crystal growth orientation, and crystallinity of mineral precipitates on membranes, as well as their effects on membrane permeability have been investigated. Gypsum scaling tests on bare and bovine serum albumin (BSA)-conditioned membranes were conducted under different saturation indices. Results show that a longer scaling period was required for BSA-conditioned membranes to reach the same membrane permeate flux decline as bare membranes. Though the final reduced permeability was the same for both two membranes, the masses of the mineral precipitates on BSA-conditioned membranes were around two times more than those on bare membranes. Further mineral characterizations confirmed that different permeability decay rates of both types of the membrane were attributed to the differences in growth orientations rather than amounts of gypsum precipitates. Moreover, BSA-conditioned layers with high carboxylic density and specific molecular structure could stabilize bassanite and disrupt the oriented growth to inhibit the formation of needle-like gypsum crystals as observed on bare membranes, thus resulting in lower surface coverage with scales on membranes and alleviating the detrimental scaling effect on membrane permeability.

Ammonia (NH3) emissions, mainly from agricultural sources, generate substantial health damage due to the adverse effects on air quality. NH3 emission reduction strategies are still far from being effective. In particular, a growing trade network in this era of globalization offers untapped emission mitigation potential that has been overlooked. Here we show that about one-fourth of global agricultural NH3 emissions in 2012 are trade-related. Globally they induce 61 thousand PM2.5-related premature mortalities, with 25 thousand deaths associated with crop cultivation and 36 thousand deaths with livestock production. The trade-related health damage network is regionally integrated and can be characterized by three trading communities. Thus, effective cooperation within trade-dependent communities will achieve considerable NH3 emission reductions allowed by technological advancements and trade structure adjustments. Identification of regional communities from network analysis offers a new perspective on addressing NH3 emissions and is also applicable to agricultural greenhouse gas emissions mitigation.

System efficient electrostatic discharge (ESD) design is an effective method for simulating the ESD behaviors of a system. Based on this simulation method, this article mainly investigates the transient behaviors of a system-level ESD protection circuit with and without a 2.5 V power supply. During power-ON state, latch-up levels of a feedback power clamp protected by off-chip elements are predicted and mainly analyzed under machine model stress. During power-OFF state, the physical failure of a hybrid-triggered power clamp under surge stress is investigated. In addition to the utilization of transmission line pulsing (TLP) I-V curves, transient TLP waveforms are also used for building the component modelsin the system-level ESD protection circuit. Moreover, the relevant measurements for the power-ON state and power-OFF state areincluded in this article for verifying the simulation results. For ESD designers, this article provides a complete modeling and analysisprocess of co-design protection circuit to investigate the electrical behaviors.

The EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation and their Effects in the Yangtze River Delta (EXPLORE-YRD) campaign was carried out between May and June 2018 at a regional site in Taizhou, China. The EXPLORE-YRD campaign helped construct a detailed air quality model to understand the formation of O3 and PM2.5 further, identify the key sources of elevated air pollution events, and design efficient emission control strategies to reduce O3 and PM2.5 pollution in YRD. In this study, we predicted the air quality during the EXPLORE-YRD campaign using the Weather Research and Forecasting/Community Multiscale Air Quality modelling system (WRF/CMAQ) and evaluated model performance on O3 and PM2.5 concentrations and compositions. Air quality was predicted using two sets of reanalysis data—NCEP Final (FNL) Operational Global Analysis and ECMWF Reanalysis v5.0 (ERA5)—and three horizontal resolutions of 36, 12, and 4 km. The results showed that PM2.5 concentration was generally under-predicted using both the FNL and ERA5 data. ERA5 yielded slightly higher PM2.5 predictions during the EXPLORE-YRD campaign. Both reanalysis data sets under-predicted the high PM2.5 pollution processes on 29–30 May 2018, indicating that reanalysis data is not essential for under-predicting extreme PM2.5 pollution processes. The performance of O3 was similar in both the reanalysis data sets, because O3 is mostly sensitive to temperature predictions and FNL and ERA5 yielded similar temperature results. Although the average performance of PM2.5 and O3 predictions yielded by FNL and ERA5 was similar, large differences were observed in certain locations on specific days (e.g. in Hangzhou between 29 May and June 6, 2018 and in Hefei on 1–3 June 2018). Therefore, the choice of reanalysis data could be an important factor affecting the predictions of PM2.5 and O3, depending on locations and episodes. Comparable results were obtained using predictions with different horizontal resolutions, indicating that grid resolution was not crucial for determining the model performance of both PM2.5 and O3 during the campaign. © 2020 Elsevier Ltd

The EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation and their Effects in the Yangtze River Delta (EXPLORE-YRD) campaign was carried out between May and June 2018 at a regional site in Taizhou, China. The EXPLORE-YRD campaign helped construct a detailed air quality model to understand the formation of O3 and PM2.5 further, identify the key sources of elevated air pollution events, and design efficient emission control strategies to reduce O3 and PM2.5 pollution in YRD. In this study, we predicted the air quality during the EXPLORE-YRD campaign using the Weather Research and Forecasting/Community Multiscale Air Quality modelling system (WRF/CMAQ) and evaluated model performance on O3 and PM2.5 concentrations and compositions. Air quality was predicted using two sets of reanalysis data—NCEP Final (FNL) Operational Global Analysis and ECMWF Reanalysis v5.0 (ERA5)—and three horizontal resolutions of 36, 12, and 4 km. The results showed that PM2.5 concentration was generally under-predicted using both the FNL and ERA5 data. ERA5 yielded slightly higher PM2.5 predictions during the EXPLORE-YRD campaign. Both reanalysis data sets under-predicted the high PM2.5 pollution processes on 29–30 May 2018, indicating that reanalysis data is not essential for under-predicting extreme PM2.5 pollution processes. The performance of O3 was similar in both the reanalysis data sets, because O3 is mostly sensitive to temperature predictions and FNL and ERA5 yielded similar temperature results. Although the average performance of PM2.5 and O3 predictions yielded by FNL and ERA5 was similar, large differences were observed in certain locations on specific days (e.g. in Hangzhou between 29 May and June 6, 2018 and in Hefei on 1–3 June 2018). Therefore, the choice of reanalysis data could be an important factor affecting the predictions of PM2.5 and O3, depending on locations and episodes. Comparable results were obtained using predictions with different horizontal resolutions, indicating that grid resolution was not crucial for determining the model performance of both PM2.5 and O3 during the campaign. © 2020 Elsevier Ltd

A source-oriented Community Multiscale Air Quality model was used to quantify the contributions of different sources to ground-level fine particulate matter (PM2.5) and ozone (O3) over the Yangtze River Delta (YRD) region during the EXPLORE-YRD (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation, and their Effects in the Yangtze River Delta) campaign (17 May to June 17, 2018). O3 formation in most urban areas of YRD is attributed to volatile organic compounds (VOCs) (81.1%, 78.5%, 60.2%, and 55.1% in Shanghai, Nanjing, Hefei, and Hangzhou, respectively), but is affected more by nitrogen oxides (NOx) in suburban and rural areas. Industry and transportation are the two major sources of O3 and PM2.5. In addition to the two sources, NOx produced owing to power generation, and VOC emissions from biogenic sources are important source of O3. Industry contributes the most to the total mass of PM2.5 in the YRD during the study period (9–25 μg/m3), followed by transportation (2–7 μg/m3). Industry, residential emissions, and transportation are the major sources of primary organic carbon and elemental carbon, whereas industry, transportation, and power generation account for most of the sulphate (SO2− 4) and nitrate (NO− 3) in the YRD. Agriculture is the most dominant source of ammonium emissions (NH+ 4). In Shanghai, Nanjing, Hefei, and Taizhou, secondary organic aerosol (SOA) are mainly contributed by industrial emissions. However, in Hangzhou, biogenic emissions contribute more than 40% of SOA. During all types of pollution episodes, industry and transportation are generally the two greatest sources of O3 and PM2.5 in YRD. The contribution of industry is higher during high PM2.5 pollution episodes, whereas biogenic and open burning contributions are more important during high O3 episodes. Overall, anthropogenic sources dominate the formation of O3 and PM2.5 pollution in the YRD, whereas biogenic emissions contribute significantly to O3 attributable to VOC emissions (O3_VOCs) accounting for 9–20% in urban areas of the YRD. © 2021 Elsevier Ltd

During the COVID-19 lockdown in 2020, large-scale industrial and transportation emissions were reduced, but high PM2.5 concentration still occurred. This study investigated the variation of particle number size distribution during the lockdown, and analyzed the characteristics of new particle formation (NPF) events and its potential impact on haze formation. Through measurement conducted in urban Beijing during the first 3 months of 2020, and comparison with year-over-year data, the decrease of primary Aitken-mode particles was observed. However, frequencies, formation rates and growth rates of NPF events remained stable between 2020 and 2019 in the same period. As a result, >25 nm particles produced by NPF events, would play a more important role in serving as the haze formation “seeds” compared to those produced by primary emissions. This finding emphasizes the significance on the understanding of NPF mechanisms when making pollution mitigation policy in the future. © 2021. The Authors.

Introduction: The COVID-19 global epidemic caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a great public health emergency. Discovering antiviral drug candidates is urgent for the prevention and treatment of COVID-19. Objectives: This work aims to discover natural SARS-CoV-2 inhibitors from the traditional Chinese herbal medicine licorice. Methods: We screened 125 small molecules from Glycyrrhiza uralensis Fisch. (licorice, Gan-Cao) by virtual ligand screening targeting the receptor-binding domain (RBD) of SARS-CoV-2 spike protein. Potential hit compounds were further evaluated by ELISA, SPR, luciferase assay, antiviral assay and pharmacokinetic study. Results: The triterpenoids licorice-saponin A3 (A3) and glycyrrhetinic acid (GA) could potently inhibit SARS-CoV-2 infection, with EC50 of 75 nM and 3.17 µM, respectively. Moreover, we reveal that A3 mainly targets the nsp7 protein, and GA binds to the spike protein RBD of SARS-CoV-2. Conclusion: In this work, we found GA and A3 from licorice potently inhibit SARS-CoV-2 infection by affecting entry and replication of the virus. Our findings indicate that these triterpenoids may contribute to the clinical efficacy of licorice for COVID-19 and could be promising candidates for antiviral drug development. Keywords: COVID-19; Glycyrrhetinic acid; Licorice; Licorice-saponin A3; SARS-CoV-2.