Key drivers of the oxidative potential of PM2.5 in Beijing in the context of air quality improvement from 2018 to 2022.

The mass concentration of atmospheric particulate matter (PM) has been continuously decreasing in the Beijing-Tianjin-Hebei region. However, health endpoints do not exhibit a linear correlation with PM mass concentrations. Thus, it is urgent to clarify the prior toxicological components of PM to further improve air quality. In this study, we analyzed the long-term oxidative potential (OP) of water-soluble PM2.5, which is generally considered more effective in assessing hazardous exposure to PM in Beijing from 2018 to 2022 based on the dithiothreitol assay and identified the crucial drivers of the OP of PM2.5 based on online monitoring of air pollutants, receptor model, and random forest (RF) model. Our results indicate that dust, traffic, and biomass combustion are the main sources of the OP of PM2.5 in Beijing. The complex interactions of dust particles, black carbon, and gaseous pollutants (nitrogen dioxide and sulfur dioxide) are the main factors driving the OP evolution, in particular, leading to the abnormal rise of OP in Beijing in 2022. Our data shows that a higher OP is observed in winter and spring compared to summer and autumn. The diurnal variation of the OP is characterized by a declining trend from 0:00 to 14:00 and an increasing trend from 14:00 to 23:00. The spatial variation in OP of PM2.5 was observed as the OP in Beijing is lower than that in Shijiazhuang, while it is higher than that in Zhenjiang and Haikou, which is primarily influenced by the distribution of black carbon. Our results are of significance in identifying the key drivers influencing the OP of PM2.5 and provide new insights for advancing air quality improvement efforts with a focus on safeguarding human health in Beijing.

Updating vehicle VOCs emissions characteristics under clean air actions in a tropical city of China.

In the context of clean air actions in China, vehicle emission limits have been continuously tightened, which has facilitated the reduction of volatile organic compounds (VOCs) emissions. However, the characteristics of VOC emissions from vehicles with strict emission limits are poorly understood. This study investigated the VOC emission characteristics from vehicles under the latest standards based on tunnel measurements, and identified future control strategies for vehicle emissions. The results showed that the highest percentage of VOCs from vehicle consisted of alkanes (80.9 %), followed by aromatics (15.8 %) and alkenes (3.1 %). Alkanes had the most significant ozone formation potential due to their high concentrations, in contrast to the aromatics that have been dominant in previous studies. The measured fleet-average VOC emission factor was 71.3 mg·km-1, including tailpipe emissions of 39.6 mg·km-1 and evaporative emissions of 31.7 mg·km-1. The VOC emission factors of the subgroups were obtained. The emission of evaporated VOCs accounted for 44.5 % of the total vehicle VOC emissions, which have increased substantially from previous studies. In addition, the emission characteristics of vehicles that are under the latest emission threshold values have changed significantly, and the mixing ratio of toluene/benzene (T/B) has been updated to 3:1. This study updates the VOCs emission factors of vehicles under clean air actions and highlights the future mitigation policies should focus on reducing evaporative VOC emissions.

[Ozone Pollution Characteristics and Formation Mechanism in a Typical Tropical Seaside City].

To investigate the pollution characteristics and formation mechanism of ambient air ozone(O3) in a typical tropical seaside city, we conducted an observational experiment on O3 and its precursors at an urban site in Haikou, Hainan Province, from June to October 2019. The O3 pollution characteristics were analyzed comprehensively; the O3-NOx-VOCs sensitivities and key precursors were determined, and the control strategies for O3 pollution were carried out. The results were as follows:1 O3 pollution in Haikou mainly occurred in September and October, with daily maximum 8-h O3 concentrations in the range of 39-190 µg·m-3, and the daily variation in O3 was unimodal, peaking at approximately 14:00. 2 The concentrations of NO2 and VOCs were higher during O3 pollution episodes than their respective mean values in Haikou City. The increased O3 precursor concentrations were an important factor leading to O3 pollution, whereas O3 pollution was also influenced by regional transport, with pollutants mainly transported from the northeastern part of Haikou City. 3 O3-NOx-VOCs sensitivity in Haikou City was in the VOCs and NOx transitional regime, and the most sensitive precursors in various months were different. O3 formation in September was sensitive to anthropogenic VOCs the most; however, in October it was sensitive to NOx. 4 In the future, the reduction ratio of VOCs to NOx should be 1:1-4:1 to control O3 pollution effectively in Haikou.

The role of NOx in Co-occurrence of O3 and PM2.5 pollution driven by wintertime east Asian monsoon in Hainan.

Clarifying the driving forces of O3 and fine particulate matter (PM2.5) co-pollution is important to perform their synergistic control. This work investigated the co-pollution of O3 and PM2.5 in Hainan Province using an observation-based model and explainable machine learning. The O3 and PM2.5 pollution that occurs in winter is affected by the wintertime East Asian Monsoon. The O3 formation shifts from a NOx-limited regime with a low O3 production rate (PO3) in the non-pollution season to a transition regime with a high PO3 in the pollution season due to an increase in NOx concentrations. Increased O3 and atmospheric oxidation capacity promote the conversion from gas-phase precursors to aerosols. Meanwhile, the high concentration of particulate nitrate favors HONO formation via photolysis, in turn facilitating O3 production. Machine learning reveals that NOx promotes O3 and PM2.5 co-pollution during the pollution period. The PO3 shows an upward trend at the observation site from 2018 to 2022 due to the inappropriate reduction of volatile organic compounds (VOCs) and NOx in the upwind areas. Our results suggest that a deep reduction of NOx should benefit both O3 and PM2.5 pollution control in Hainan and bring new insights into improving air quality in other regions of China in the future.

Characterization, reactivity, source apportionment, and potential source areas of ambient volatile organic compounds in a typical tropical city.

Based on one-year observation, the concentration, sources, and potential source areas of volatile organic compounds (VOCs) were comprehensively analyzed to investigate the pollution characteristics of ambient VOCs in Haikou, China. The results showed that the annual average concentration of total VOCs (TVOCs) was 11.4 ppbV, and the composition was dominated by alkanes (8.2 ppbV, 71.4%) and alkenes (1.3 ppbV, 20.5%). The diurnal variation in the concentration of dominant VOC species showed a distinct bimodal distribution with peaks in the morning and evening. The greatest contribution to ozone formation potential (OFP) was made by alkenes (51.6%), followed by alkanes (27.2%). The concentrations of VOCs and nitrogen dioxide (NO2) in spring and summer were low, and it was difficult to generate high ozone (O3) concentrations through photochemical reactions. The significant increase in O3 concentrations in autumn and winter was mainly related to the transmission of pollutants from the northeast. Traffic sources (40.1%), industrial sources (19.4%), combustion sources (18.6%), solvent usage sources (15.5%) and plant sources (6.4%) were identified as major sources of VOCs through the positive matrix factorization (PMF) model. The southeastern coastal areas of China were identified as major potential source areas of VOCs through the potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models. Overall, the concentration of ambient VOCs in Haikou was strongly influenced by traffic sources and long-distance transport, and the control of VOCs emitted from vehicles should be strengthened to reduce the active species of ambient VOCs in Haikou, thereby reducing the generation of O3.

sEMG Based Gait Phase Recognition for Children with Spastic Cerebral Palsy.

The goal of this study was to examine the optimal strategies for the recognition of gait phase based on surface electromyogram (sEMG) of leg muscles while children with cerebral palsy (CP) walked on a treadmill. Ten children with CP were recruited to participate in this study. sEMG from eight leg muscles and leg position signals were recorded while subjects walked on a treadmill. The position signals of left and right legs were used to develop a five gait sub-phases classifier, i.e., mid stance, terminal stance, pre-swing, mid swing, and terminal swing. Seven feature sets of sEMG signals were tested in recognizing the five gait sub-phases of children with CP. Results from this study indicated that the recognition performance of mean absolute value and zero crossing was better than that with other feature sets when using support vector machine (average classification accuracy was 89.40%). Further, we found that the performance of gait phase recognition is relatively better in pre-swing than other sub-phases, and the performance of gait phase recognition is relatively poorer in mid-swing than other sub-phases. Results from this study may be used to develop an intention-driven robotic gait training system/paradigm for assisting walking in children with CP through robotic training.