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Li, Ke

Publications and source records attributed to Li, Ke.

At least 19 records

Machine learning-based bias-corrected future projections of ozone concentrations from a chemistry-climate model

Reliable projection of future near-surface ozone is crucial for air quality management and health risk assessment. However, potential biases in spatial distribution, magnitude and trends in ozone concentrations simulated by global chemistry-climate models limit their applicability in regional-scale evaluations. In this study, LightGBM, a machine learning (ML) algorithm is applied to correct biases in CESM2-simulated ozone concentrations over China, the United States and Europe and calibrate future ozone projections under two diverse Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) scenarios from 2020 to 2060. The ML-based correction significantly improves the spatial distribution and reduces the model bias by 40%–60%. It also reverses the potentially incorrect trend of ozone change under SSP1-2.6 in eastern China. When applying ML-based bias correction to CESM2 future projections, warm season mean ozone concentrations decrease across China, the United States, and Europe by –13.5, –17.9, and –13.7 µg/m³, respectively, between 2020 and 2060 in SSP1-2.6, while they increase by 9.4, 2.0, and 5.2 µg/m³ in SSP5-8.5. Decomposition analysis show that changes in anthropogenic emissions dominate future ozone changes in both scenarios, while strong climate penalty from ozone changes occurs in polluted eastern China and climate benefit is found in western China, the United States and Europe under SSP5-8.5. These findings demonstrate the value of combining ML with chemistry-climate models to produce more accurate air quality projections, thereby informing more effective and region-specific environmental protection strategies.

Chemistry Model↗

Intensifying heat extremes in China attributed to rising greenhouse gases and declining aerosols since the 2010s

Rising temperatures have increased the frequency, duration, and intensity of extreme temperature events over China in recent decades. The upward trends in heat extremes in China in the warm season (May–September) and their relationships with changes in aerosols and greenhouse gases are investigated using observations, reanalysis data and model results. Significant increasing trends in China are observed in daily maximum temperatures (TXx), heatwave frequency, and heatwave mean duration during 2011–2023, with increasing rates of 0.70 °C/decade, 3.77 d/decade and 0.31 d/event/decade, respectively. This study shows that 43 ± 3% of the TXx increases in China are attributed to the rising CO2 concentrations. Aerosol optical depth in China decreased at a rate of 0.054 per decade from 2011 to 2023 due to significant air quality improvements. The weakened aerosol cooling effect due to declining aerosols contributes 27 ± 3% to the observed TXx trend. In eastern China, where aerosol reductions were most significant, aerosol reduction even accounts for 79 ± 10% of the TXx increasing trend. The intensifying heat waves attributed to GHGs and aerosols are in accordance with the increasing extreme high temperatures. The results highlight the significant impacts of rising GHGs and decreasing aerosols on heat extreme events over China in recent years, emphasizing the need of considering both GHGs and aerosols to address the issue of intensification of heat extremes in a warming future.

Zou, Aili↗

Supervisory genset control in range-extended electric vehicle

A controls system for a range-extended electric vehicle comprising an overall system control unit, an engine control module configured to control a range extender of the range-extended electric vehicle, power electronics configured to control a generator of the range-extended electric vehicle, and a supervisory control module coupled between the overall system control unit and the engine control module and the power electronics, the supervisory control module configured to receive information from the overall system control unit and provide commands to the engine control module and the power electronics.

Li, Ke↗

Experimental investigation into coal wettability changes caused by reactions with scCO 2 -H 2 O

Geological CO 2 sequestration (GCS) can help mitigate global warming and enhance methane recovery from coal beds. However, few studies have linked the effects of CO 2 to surface chemistry changes controlling wetting behavior in deep coal beds. Contact angles (CAs) of CO 2 /N 2 -high volatile bituminous coal-water systems were measured under different temperatures and pressures. The surface chemistry and physical structure of coals were characterized to investigate changes in physicochemical properties and their relations with wettability after reactions. For N 2 treatment, the time-dependence of static and dynamic CAs were insignificant, ranging within 4°. For gaseous CO 2 treatment, the static CAs and the average advancing angles increased slightly. With supercritical (sc) CO 2 , both the static and dynamic CAs increased significantly, and θ adv changed to intermediate-wet (92°). Reactions with minerals exposed to scCO 2 resulted in greater surface roughness and heterogeneity, greater contact angle hysteresis and more surface sites occupied by scCO 2 rather than H 2 O. Increases in hydrophobic functional groups and decreases in hydrophilicity were shown by FTIR spectra, reflecting the shedding of polar oxygen-containing functional groups, reduction of hydrogen bonds, and increasing percentage of hydrocarbons. XRD patterns obtained following scCO 2 -treatment showed that crystallite growth and molecular polymerization were higher toward graphite-like. The calculated structural parameters of functional groups and crystallites both showed elevated coal rank. Changes in crystallite structure, notably higher carbon content and decreased negative surface charge, are unfavorable for water-wetting. Finally, this study contributes to understanding surface chemistry changes responsible for decreased wettability during CO 2 -enhanced coal bed methane recovery and GCS in coal reservoirs.

01 COAL, LIGNITE, AND PEAT↗

Meteorological characteristics of extreme ozone pollution events in China and their future predictions

Ozone (O 3 ) has become one of the most concerning air pollutants in China in recent decades. In this study, based on surface observations, reanalysis data, global atmospheric chemistry model simulations, and multi-model future predictions, meteorological characteristics conducive to extreme O 3 pollution in various regions of China are investigated, and their historical changes and future trends are analyzed. During the most severe O 3 polluted months, the chemical production of O 3 is enhanced under the hot and dry conditions over the North China Plain (NCP) in June 2018 and the Yangtze River Delta (YRD) in July 2017, while regional transport is the main reason for the severe O3 pollution over the Sichuan Basin (SCB) in July 2015 and the Pearl River Delta (PRD) in September 2019. Over the last 4 decades, the frequencies of high-temperature and low-relative-humidity conditions increased in 2000–2019 relative to 1980–1999, indicating that O 3 pollution in both the NCP and YRD has become more frequent under historical climate change. In the SCB and PRD, the occurrence of atmospheric circulation patterns similar to those during the most polluted months increased, together with the more frequent hot and dry conditions, contributing to the increases in severe O 3 pollution in the SCB and PRD during 1980–2019. In the future (by 2100), the frequencies of months with anomalous high temperature show stronger increasing trends in the high-forcing scenario (Shared Socioeconomic Pathway (SSP5-8.5)) compared to the sustainable scenario (SSP1-2.6) in China. It suggests that high anthropogenic forcing will not only lead to slow economic growth and climate warming but also likely result in environmental pollution issues.

54 ENVIRONMENTAL SCIENCES↗

Contrasting changes in ozone during 2019–2021 between eastern and the other regions of China attributed to anthropogenic emissions and meteorological conditions

Ozone pollution is one of the most severe air quality issues in China that poses a serious threat to human health and ecosystems. During 2019–2021, the maximum daily 8-h average ozone concentrations in eastern China (110–122.5°E, 26–42°N) and the rest of China (ROC) show different decreasing patterns, with ozone concentrations in eastern China decreasing by 14.9 μg/m 3 , which is much larger than 4.8 μg/m 3 in ROC. Here, based on two independent methods, the atmospheric chemical transport model (GEOS-Chem) simulations and the machine learning (ML) model (LightGBM) predictions, the reasons for the differences in ozone changes between eastern China and ROC during the warm season (April to September) are investigated. According to the GEOS-Chem (LightGBM) results, changes in the meteorological conditions contributed to an ozone decrease by 7.3 (6.8) μg/m 3 in eastern China due to decreased chemical production and an ozone decrease by 6.8 (7.0) μg/m 3 in ROC attributed to the weakened horizontal and vertical advection. With the influence of meteorological factors excluded, the observations show that changes in anthropogenic emissions resulted in an ozone decrease by 7.6 (8.1) μg/m 3 in eastern China and an ozone increase by 2.0 (2.2) μg/m 3 in ROC, which is primarily induced by the changes in NO x emissions. The surface measurements and satellite retrievals also indicate that the reduction in NO x emissions in ROC is less efficient than that in the more developed eastern China, leading to contrasting changes in ozone concentrations between eastern China and ROC during 2019–2021. In conclusion, our results highlight the critical need to reduce ozone precursor emissions in the rest regions of China apart from eastern China.

54 ENVIRONMENTAL SCIENCES↗

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Source attribution of near-surface ozone trends in the United States during 1995–2019

Emissions of ozone (O 3 ) precursors in the United States have decreased in recent decades, and near-surface O 3 concentrations showed a significant decrease in summer but an increase in winter. In this study, an O 3 source tagging technique is utilized in a chemistry–climate model to investigate the source contributions to O 3 mixing ratios in the US from various emitting sectors and regions of nitrogen oxides (NO x ) and reactive carbon species during 1995–2019. We show that domestic emission reductions from energy and surface transportation are primarily responsible for the decrease in summertime O 3 during 1995–2019. However, in winter, the emission control also weakens the NO x titration process, resulting in considerable increases in O 3 levels from natural sources. Additionally, increases in aviation and shipping emissions and transpacific transport of O 3 from Asia largely contribute to the winter O 3 increase. We also found that changes in large-scale circulation favoring O 3 transport from the upper atmosphere and foreign transport from Asia also explain 15 % of the increase in the US near-surface O 3 levels in winter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid increase in tropospheric ozone over Southeast Asia attributed to changes in precursor emission source regions and sectors

Observations indicate that tropospheric ozone (O 3 ) concentrations over Southeast Asia have been increasing rapidly since the 1990s. Here, we quantify source contributions from geographical regions and emission sectors of the two distinct types of O 3 precursors, i.e., nitrogen oxides (NO x ) and volatile organic compounds (VOCs), to the increase in tropospheric O 3 in Southeast Asia during 1990–2019 using an O 3 source tagging technique implemented in a global chemistry-climate model. In this work, the results show that although local anthropogenic emission of NO x in Southeast Asia only contributes 18% of the annual averaged near-surface O 3 concentration, the increase in local NO x emission dominates the increasing trend of O 3 concentration in Southeast Asia, accounting for 107% of the regional averaged trend of 1.07 ppb decade -1 . Increases in NO x emissions from East Asia and South Asia explain 29% of the increasing trend, but 9% is offset by the emission reduction in North America. Ground transportation is responsible for 79% of the rapid O 3 increase, followed by 39% contribution from international shipping. Because an increase in anthropogenic NO x emissions enhances the O 3 production efficiency by VOCs, the increase in near-surface O 3 concentrations in Southeast Asia is thereby largely contributed by methane and biogenic VOCs.

54 ENVIRONMENTAL SCIENCES↗

Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multi-source data

Ozone (O 3 ) is a secondary pollutant in the atmosphere formed by photochemical reactions that endangers human health and ecosystems. O 3 has aggravated in Asia in recent decades and will vary in the future. In this study, to quantify the impacts of future climate change on O 3 pollution, near-surface O 3 concentrations over Asia in 2020–2100 are projected using a machine learning (ML) method along with multi-source data. The ML model is trained with combined O 3 data from a global atmospheric chemical transport model and real-time observations. The ML model is then used to estimate future O 3 with meteorological fields from multi-model simulations under various climate scenarios. The near-surface O 3 concentrations are projected to increase by 5 %–20 % over South China, Southeast Asia, and South India and less than 10 % over North China and the Gangetic Plains under the high-forcing scenarios in the last decade of 21st century, compared to the first decade of 2020–2100. The O 3 increases are primarily owing to the favorable meteorological conditions for O 3 photochemical formation in most Asian regions. We also find that the summertime O 3 pollution over eastern China will expand from North China to South China and extend into the cold season in a warmer future. Our results demonstrate the important role of a climate change penalty on Asian O 3 in the future, which provides implications for environmental and climate strategies of adaptation and mitigation.

54 ENVIRONMENTAL SCIENCES↗

ENSO modulation of summertime tropospheric ozone over China

Ozone (O 3 ) is one of the most critical pollutants affecting air quality in China in recent years. In this study, different impacts of the El Niño–Southern Oscillation (ENSO) warm/cold phases on summertime tropospheric O 3 over China are examined based on model simulations, ground measurements, and reanalysis data. Summertime surface O 3 concentrations in China show a positive correlation with ENSO index during years 1990–2019, with the largest increases by 20% over southern China in El Niño (warm phase) relative to La Niña (cold phase) years. The ENSO modulation extends to the middle and even upper troposphere. Our analysis indicates that O 3 flux convergence associated with weakened southerlies is the primary reason for the increase in tropospheric O 3 over southern China. In addition, the O 3 increase during El Niño years is mainly from domestic emissions in China. This study highlights the potential significance of ENSO in modulating tropospheric O 3 concentrations in China, with great implications for O 3 pollution mitigation.

54 ENVIRONMENTAL SCIENCES↗

Systems and methods for point-of-care positron emission tomography

A positron emission tomography (PET) system is provided. The system includes a first detector panel including a first array of detectors, a second detector panel including a second array of detectors, said second detector panel being moveable relative to a point between the first detector panel and the second detector panel, a tracking system configured to detect a position of said second detector panel relative to the first detector panel while imaging a subject, a computing device in communication with the first detector panel, the second detector panel, and the tracking system, the computing device configured to receive coincidence data from the first and second detector panels, receive position data from the tracking system, wherein each coincidence datum of the received coincidence data is associated with a unique position datum of the received position data, and reconstruct a plurality of images based on the received coincidence data and the received position data.

Tai, Yuan-Chuan↗

Surface Redox Pseudocapacitance of Partially Oxidized Titanium Carbide MXene in Water-in-Salt Electrolyte

Achieving pseudocapacitive intercalation in MXenes with neutral aqueous electrolytes and driving reversible redox reactions is scientifically appealing and practically useful. Here, we report that the partial oxidation of MXene intensifies pseudocapacitive Li + intercalation into Ti 3 C 2 T x MXene from neutral water-in-salt electrolytes. An in situ X-ray absorption near-edge structure analysis shows that the Ti oxidation state changes during the Li+ intercalation, indicating the presence of a surface redox reaction. The Ti oxidation/reduction is further confirmed by an in situ extended X-ray absorption fine structure analysis, which shows a reversible contraction/expansion of the Ti–C interatomic distance. The intensified Li + pseudocapacitive intercalation can be explained by the higher oxidation state of Ti at the open circuit potential. Furthermore, this work demonstrates the possibility of tuning the pseudocapacitive intercalation by adjusting the initial oxidation state of the transition metal on the MXene and offers a facile way to enhance the pseudocapacitance of various MXenes.

36 MATERIALS SCIENCE↗