The solid-phase extraction method and the thermal-optical method were combined to obtain different polar HULIS and the carbon content of HULIS (HULIS-C) in PM_2.5 with high temporal resolution during the heavy pollution event in Xi'an. The light absorption characteristics of HULIS were analyzed using a UV-Vis spectrophotometer equipped with a liquid waveguide capillary cell (LWCC), and the positive matrix factorization model (PMF) was used to analyze the sources of HULIS. At the same time, the source of HULIS is combined with the positive matrix factorization model (PMF). The results showed that the average mass concentration of neutral HULIS (HULIS-n) (6.6±2.6)µg/m³ was higher than that of acidic HULIS (HULIS-a) (3.7±3.5)µg/m³, accounting for approximately 30% and 18% of OC, respectively, indicating severe HULIS pollution during heavy pollution periods. The absorption coefficients (AAE, E₂/E₃, and MAE₃₆₅) of HULIS-n were all greater than those of HULIS-a, suggesting that HULIS-n contains more conjugated and aromatic structures and has stronger light-absorbing properties, with a more significant impact on atmospheric visibility. The source analysis revealed clear differences in the contributions of HULIS-n and HULIS-a. The primary sources of HULIS-n included secondary sources, coal combustion, motor vehicle emissions., while the contributions of secondary sources and coal combustion were higher for HULIS-a.

This study conducted sampling and testing on the waste gases generated from different processes in typical automobile manufacturing plant coating workshops located in northern and southern China. It meticulously analyzed the emission characteristics of volatile organic compounds (VOCs) and odor characteristics, and extensively explored odor characteristic prediction methods from multiple dimensions. The results revealed that OVOCs, alkanes, and aromatic hydrocarbons are the predominant components in the exhaust gases, with OVOCs constituting 73.80% to 99.03% of the odor activity value (OAV), thereby classifying them the most significant odor-contributing substance category. Acetaldehyde, n-butyl acetate, isobutyl acetate, and n-butyraldehyde all significantly contributed to the odor at both the inlet and outlet of the treatment equipment. Furthermore, electronic noses were used to classify waste gas samples, achieving 100% and 98.1% accuracy rates for inlet and outlet, respectively. Quantification of odour was achieved through regression analysis, which revealed a strong linear correlation between OVOCs substance concentration and OAV_max and OAV_sum. The electronic nose technology combined with BP neural networks was found to be an effective predictor of OAV_max and OAV_sum. Additionally, a logarithmic relationship was observed between OVOCs substance concentration, OAV_max, OAV_sum, and odor concentration.

To address the issue of biases in the representational capabilities of existing assessment methods for ozone pollution meteorological conditions, stemming from a lack of boundary layer indicators, this study utilized meteorological and environmental observation data collected from 2019 to 2023. By integrating ozone numerical simulations and incorporating source tracking along with process rate analysis techniques within the model framework, we developed a joint model and observation-based Tianjin Ozone Pollution Meteorological Condition Assessment Index (OWI). This index aims to accurately assess ozone pollution meteorological conditions in Tianjin. The research findings reveal a strong correlation between ozone concentrations and various meteorological factors. The OWI index was constructed based on parameters such as average temperature, maximum temperature, relative humidity, daily precipitation, daytime ultraviolet radiation, midday ultraviolet radiation, sunshine duration, average wind speed, and wind direction. It effectively characterizes the impact of these meteorological conditions on ozone levels. Notably, this index exhibits a correlation coefficient of 0.82 with O₃ concentration and demonstrates an ability to identify 82% of mild or more severe ozone pollution incidents. Furthermore, by analyzing the effects of daytime and nighttime boundary layer heights on precursor diffusion processes—such as near-surface nitrogen oxide titration and vertical exchange of ozone—the study addresses potential overestimations in O₃ concentrations by the OWI index under favorable vertical diffusion conditions. To optimize the OWI index further, we incorporated indicators for both daytime and nighttime boundary layer heights. Through ozone numerical simulations, the study calculated the effects of horizontal and vertical transport, convection, chemical generation, turbulent mixing, and regional transport on ozone levels. By combining simulation results with observations, the OWI index was oized under specific conditions, such as adjusting upwards when daytime vertical transport exceeds 15µg/(m³⋅h) or daytime ozone chemical generation exceeds 20µg/(m³⋅h); and considering surrounding meteorological conditions and ozone transport impacts when regional transport was too strong.

TiCeO_x bimetallic catalysts were prepared as catalyst carries. And the Ru-supported catalysts with different dispersions were synthesized by the methods of Ru³⁺ impregnation reduction (bottom to up) and Ru colloid solution thermal diffusion (top to down) methods. In the catalyst RuTiCeO_x-N prepared by Ru³⁺ immersion reduction method, Ru species exist in the form of RuO_x nanoclusters. In the catalyst RuTiCeO_x-A prepared by Ru colloid solution thermal diffusion, Ru species exist in the form of single-atom dispersion. The different dispersion states of Ru species lead to the difference of active oxygen species and acid sites involved in chlorobenzene (CB) oxidation. Chemisorbed oxygen and surface lattice oxygen could be the dominating active oxygen species for RuTiCeO_x-N and RuTiCeO_x-A, respectively. And due to the chemisorption of CB, that could be transformed into hydroxyl radical (-OH) to be involved in the catalytic reaction. Catalyst RuTiCeO_x-A performed better with the complete conversion of CB at 300℃ and 24h of durability test without deactivation. That could be attributed to the synergy between its resulted active oxygen species and multiple acid sites (strong and weak).

To investigate the spatial and temporal distribution characteristics of dust events in Inner Mongolia and their exogenous contributions, high-precision aerosol vertical distribution profiles were obtained using seven multi-band lidars deployed in Inner Mongolia. In addition, the three-dimensional dynamic evolution, atmospheric circulation and exogenous dust sources of summer dust storms in Inner Mongolia were further analyzed by combining ground station observations, atmospheric chemistry models, meteorological reanalysis data and backward trajectory models. It is found that the overall number of dust days in Inner Mongolia from 2014 to 2024 shows a fluctuating upward trend, and spring is the peak season for dust events, with the cumulative number of dust days reaching 117. In the past five years, the change of the number of dust days in spring was relatively stable, but since 2020, the number of dust days in summer began to show an increasing trend. During 20~25July 2024, a serious dust event occurred in Inner Mongolia. The dynamic evolution of the dust event from high altitude to near-surface was effectively monitored by the networked LiDAR in Inner Mongolia. on 20 July, the dust first appeared in the west-central part of Inner Mongolia and the China-Mongolia border, and then spread eastward under the combined effect of the northwesterly winds behind the low-pressure trough and the surface gales. The intensity of the dust weakened somewhat on 22 July. However, the low-pressure trough reappeared on 23 July, and the northerly flow behind the trough guided the cold air southward to form strong winds, which rapidly blew up the surface dust particles, leading to a general increase in dust uptake in west-central Inner Mongolia and transporting them downstream through the northwesterly wind behind the trough. During this dust event, the Sino-Mongolian border became the main potential source area of PM₁₀ during the dust event, contributing most significantly to the PM₁₀ mass concentration. This indicates that the Sino-Mongolian border area is gradually becoming an important source of dust in northern China.

The seasonal vertical distribution of aerosols in the southern margin of the Taklamakan Desert was analysed using aerosol LiDAR data from the Minfeng meteorological station from June 2023 to May 2024, and the HYSPLIT backward trajectory model was employed to identify the transport paths of aerosols at different altitude layers. Finally, the vertical distribution of aerosols and their transport paths at different stages of dust pollution are analysed by taking a dust pollution event as an example. The results show that: ①The dust aerosols can be lifted up to a maximum height of 3~4km (4.4~5.4km above sea level) above the ground surface, which is comparable to the average elevation of the Tibetan Plateau (>4km), and suggests the possibility of transport of dust aerosols from the study site to the outside of the Tarim Basin. ②The extinction coefficients of the four seasons show a decreasing trend with height in the vertical direction, and the maximum values are all located at the low altitude of 150m. The highest values are found in spring (0.69km^-1, 0.20), followed by winter (0.52km^-1, 0.18) and summer (0.40km^-1, 0.16), and the lowest values are found in autumn(0.25km^-1, 0.11). ③The dust aerosols are mainly affected by the east-west transport, except for the 1500 and 3000m altitude layers in winter which are affected by the westerly transport, the 500, 1500 and 3000m altitude layers in the rest of the seasons are affected by the northeasterly and westerly transport at the same time. ④The extinction coefficients carried by the northeasterly jet are significantly higher than those carried by the westerly jet at different altitudes in all seasons, making the northeasterly jet the main dust transporting jet. ⑤The study of a dust pollution event shows that the extinction coefficient of the near-surface aerosols is greater than 1km^-1, the depolarization ratio exceeds 0.3, and the vertical trend is decreasing with height during the dust pollution process. The northeastern airflow in the Tarim Basin is the main transport airflow for dust aerosols during this dust event.

Based on the ozonesonde data in Guangdong, Hong Kong, and Macao regions from 2022 to 2023, the vertical distribution characteristics of O₃ concentration were analyzed, and the applicability of Aqua satellite AIRS O₃ vertical profile product and ERA5 reanalysis O₃ vertical profile product were evaluated by using self-organizing map neural network (SOM) method. The vertical distribution of O₃ in the Greater Bay Area exhibited significant seasonal variations. In spring, summer, and winter, the ozone vertical distribution displayed a unimodal structure, with peak concentrations located near 700, 950, and 300 hPa, respectively. In contrast, the vertical distribution in autumn showed a bimodal structure, with peaks near 925 and 400hPa. The vertical differences in O₃ between stations were relatively small, with deviations between Guangdong and Hong Kong stations ranging from -3.2% to 11.0%. The quality of AIRS and ERA5 data in autumn and winter within the troposphere was better than that in spring and summer. At 850~200hPa, both AIRS and ERA5 data showed relatively good quality, with seasonal relative average deviations (Rad) ranging from 16.5% to 25.8% for AIRS and 15.1% to 25.7% for ERA5. The average correlation coefficients (r) for the seasons ranged from 0.47 to 0.75 for AIRS and 0.23 to 0.74 for ERA5. Below 850 hPa, the quality of AIRS and ERA5 data was relatively bad, with average value of r were 0.34 and -0.15. The vertical distribution of O₃ was categorized into 5 types. Among these, the data quality of AIRS and ERA5 was best under the type 1distribution structure, while it was worst under the type 2 and type 3 structures. Type 1 occurred more frequently in autumn (43%) and winter (61%), whereas type 2 and type 3 were more common in summer (66%). Type 4 and type 5 occurred more frequently in spring (85%).

In this study, the components of dissolved organic matter (DOM) during the anaerobic-anoxic-aerobic (A²O) biological wastewater treatment process was analyzed by using fluorescence emission excitation matrix combined with parallel factor analysis(3D EEMs-PARAFAC), and the generation of nitrous oxide (N₂O) in each unit was also quantified. Additionally, machine learning model was employed to further predict the response relationship between DOM components and N₂O generation. Results showed that DOM in the influent of the wastewater treatment plants (WWTP) was primarily composed of four components, including tryptophan (C1), fulvic acid (C2), humic acid (C3), and tyrosine (C4), while C1 and C4 being the dominant components. The concentration of DOM decreased progressively throughout the treatment process, while the removal efficiency of readily biodegradable DOM (such as C1and C4) were significantly higher than that of C2 and C3. N₂O emission was the major component of direct carbon emissions and showed significant spatial heterogeneity. The N₂O emission amount of each unit ranked from high to low were observed in the following order: oxic tank, secondary sedimentation tank, anoxic tank, anaerobic tank, grille, and primary sedimentation tank. Shapley Additive exPlanation (SHAP) analysis revealed that C1 and C2 would significantly affect the N₂O generation process, while the effects of C3 and C4 were negligible. Specifically, C1would enhance N₂O generation, while C2 had an adverse effect. High-throughput sequencing results indicated that Methylotenera and Terrimonas, which could utilize readily biodegradable organic matter for denitrification, were the dominant bacterial genera in the sludge of WWTP. Overall, this study revealed disparate response between N₂O generation and different DOM components during the A²O process, which would help to improve the current carbon emission accounting method of WWTPs and provide theoretical support for optimizing their low-carbon operation processes.

As a common pollutant in water, nitrate has nonnegligible harmful effects on human health and the ecological environment. Faced with an increasingly severe energy crisis, the development of green, clean and sustainable nitrate removal technologies to replace the conventional resource-intensive denitrification process is urgently needed. Photoelectrochemical nitrate reduction powered by sunlight has become a research hotspot at home and abroad. Based on the way photogenerated electrons being transferred from semiconductor to nitrate, this technology can be categorized into photocatalytic reduction, photoelectrocatalytic reduction, and microbial photoelectrotrophic reduction. In this review, the mechanisms of three photoelectrochemical nitrate reduction technologies were discussed. With a focus on improving system performance, the selection and design strategies of photocatalysts, photoelectrodes and microbial photosensitizers were also summarized. Moreover, the technical difficulties of photoelectrochemical nitrate reduction are clarified and the future directions of research are proposed, such as regulating the pathway of microbial absorption and utilization of photogenerated electrons through genetic engineering and other methods. The insights provided will serve as a reference for the development of new nitrate removal and reutilization technologies.

Varieties of non-noble metal catalysts were prepared and screened by hydrothermal deoxidation of stearic acid for the purpose of efficiently catalyzing the conversion of waste oil into green diesel. The experimental results demonstrated that the nano-Ni-Cu alloy exhibited a significant catalytic effect on stearic acid, with its catalytic performance and product distribution being the most comparable to those of the Pt/C catalyst. Furthermore, the optimization of reaction conditions, stability analysis, catalyst characterization, reaction mechanism exploration and broad-spectrum analysis were carried out for nano Ni-Cu alloy. The characterization results revealed that the structure of nano-Ni-Cu alloy remained stable, and no significant structural changes were observed after continuous cyclic use. Under the optimum reaction conditions of 330℃, 120min, with the addition of 20µL methanol,30mg catalyst and 80µL water in a 1.67ml micro reactor, stearic acid was primarily converted into heptadecane through catalytic hydrodeoxygenation and decarbonylation. Additionally, the broad-spectrum analysis indicated that the yield of C8-C18 alkanes from various fatty acids and fatty acid esters catalyzed by nano-Ni-Cu alloy could exceed 95%, conforming its excellent catalytic performance.