Ozone distribution and variation within the Planetary Boundary Layer (PBL) present challenges for air quality management. UAV-based ozone profile measurements offer advantages in terms of high vertical resolution throughout the PBL and flexibility. However, previous studies on vertical variation in the Pearl River Delta (PRD) region have rarely focused on measuring the vertical ozone variation during ozone pollution episodes. In this study, we integrated UAV-based monitoring, ground monitoring, and numerical modeling to investigate ozone variation, driving processes, and source regions of pollution episodic period. UAV-based observations during a 2021 ozone episode at rural areas in the PRD region revealed three ozone profiles: increasing, well-mixed, and decreasing with height. Morning profiles showed multiple layers influenced by meteorology, while peak ozone hours exhibited a well-mixed pattern. By integrating the validated numerical model, we found that chemical processes (CHEM) contributed positively to ozone episodes in both rural and urban scenarios, especially at the middle and upper PBL. Horizontal advection (HADV) significantly contributes to the episode in rural cases, while urban cases were significantly affected by vertical diffusion (VDIF). Backward trajectory and source apportionment analyses categorized PRD cities into upwind/non-upwind/local categories, showing ozone pollution originating from both upwind and non-upwind cities at different vertical levels. It is because wind shear influenced diverse source regions, and the transport channel for city-level ozone pollution exhibited daily and vertical changes. Moreover, it could also be contributed by the formed regional mixing ozone layer (ROM Layer) throughout the PBL during persistent ozone episodes, triggered by enhanced CHEM and significantly contributed by the VDIF. The ROM Layer at center cities, influencing ground-level ozone downwind through horizontal transport and vertical exchange. Considering the complex three-dimensional transport of ozone and the ROM Layer phenomenon, city-level management or regional co-control based on simple transport channels may be insufficient. Emissions control measures should cover all cities or target significant emitters to address regional ozone pollution.

Basic monitoring of the marine environment is crucial for the early warning and assessment of marine hydrometeorological conditions, climate change, and ecosystem disasters. In recent years, many marine environmental monitoring platforms have been established, such as offshore platforms, ships, or sensors placed on specially designed buoys or submerged marine structures. These platforms typically use a variety of sensors to provide high-quality observations, while they are limited by low spatial resolution and high cost during data acquisition. Satellite remote sensing allows monitoring over a larger ocean area; however, it is susceptible to cloud contamination and atmospheric effects that subject the results to large uncertainties. Unmanned vehicles have become more widely used as platforms in marine science and ocean engineering in recent years due to their ease of deployment, mobility, and the low cost involved in data acquisition. Researchers can acquire data according to their schedules and convenience, offering significant improvements over those obtained by traditional platforms. This study presents the state-of-the-art research on available unmanned vehicle observation platforms, including unmanned aerial vehicles (UAVs), underwater gliders (UGs), unmanned surface vehicles (USVs), and unmanned ships (USs), for marine environmental monitoring, and compares them with satellite remote sensing. The recent applications in marine environments have focused on marine biochemical and ecosystem features, marine physical features, marine pollution, and marine aerosols monitoring, and their integration with other products are also analysed. Additionally, the prospects of future ocean observation systems combining unmanned vehicle platforms (UVPs), global and regional autonomous platform networks, and remote sensing data are discussed.

Quantifying and comparing the effectiveness of different emission control strategies can provide insights for policy design and air quality management. In our previous work, we developed a windpollution decomposition (WPD) method that provides a robust tool to quantify meteorology-driven and emission-driven impacts on changes in air quality. In this study, we applied this method to quantify emission-driven impacts on the observed air quality changes during the three largest international socioeconomic mega-events in China, namely, Shanghai World Expo in 2010, Beijing Olympic Games in 2008, and Guangzhou Asian Games in 2010. We also applied the method to the air quality variation during the lockdown period in Wuhan due to COVID-19 and compared the emission-driven impacts on air quality among these events. The results quantitatively show that the emission-driven factor generally played a much stronger role (> 86%); the meteorologydriven factor promoted pollution mitigation during Wuhan, Beijing and Guangzhou events but worsened the air quality during Shanghai event. The emission-driven pollution reduction was largest in the Wuhan COVID-19 lockdown (64% NO2, 54% PM2.5 reductions), followed by Beijing Olympics (42% PM2.5, 31% NO2 reductions), The Wuhan COVID-19 impact on air quality improvement is not as effective as expected especially for O3, which implies the difficulty of air quality attainment under normal, non-lockdown days. Comparison of these events show that shutdown or emission control measures applied to industries and power plants were generally benefit for PM2.5, SO2 and NO2 reduction, while those applied to on-road traffic control are lesseffective for reducing NO2 and not works for the mean O3 reduction. The results imply that advanced control measures for vehicle exhaust and control strategies considering the interaction between O3 and NOx/VOC/PM are necessary. In addition, the ongoing supervision of control strategies implementation is one of the key issues for future air quality management in China.

Abstract The annual assessment of emission control effects on air quality is essential for policy adjustments. However, this assessment is difficult as the inter‐annual changes in pollution are impacted by complex meteorological conditions. In this study, based on our wind‐pollution decomposition (WPD) method, which decomposes wind effects (wind‐driven) and nonwind effects, we established the meteorology‐pollution decomposition (MPD) method, which separates meteorological effects (met‐driven) and nonmeteorological effects by importing other meteorological parameters, to approximate the emission change effects (emission‐driven) by the nonmeteorological effects. The performance of the MPD method was assessed by comparing the results of the WPD and MPD methods at multiple representative stations in Hong Kong with the longest continuous data available in China from 2000 to 2018. The decomposed emission‐driven impact is also validated by using the gross domestic product growth rates data. The emission‐driven contributions determined by the WPD and MPD methods generally show agreement in trend, while the met‐driven effects are generally larger than the wind‐driven effects with the same or opposite trend. The results showed that the met‐driven effect from the MPD method is more reasonable than the wind‐driven effect from the WPD method in representing complex meteorological influences, which indicates a better representation of emission‐driven impacts by the nonmeteorological effects during the unusual meteorological years, such as El Niño‐Southern Oscillation events. The MPD method represents an independent approach, which is based only on regular observations, to quantify the long‐term trend in emission‐driven impacts as well as the integrated meteorological impacts on the atmospheric environment under the background of climate change.