To investigate impact factors and source area of secondary organic aerosols in the Yangtze River Delta (YRD) region, a world-class urban agglomeration in China, long-term measurements of organic carbon (OC) and elementary carbon (EC) in particulate matter of less than 2.5 µm (PM_2.5) with hourly time resolution were conducted at a regional site in Shanghai from 2016 to 2020. Based on the 5-year measurements, the interannual, monthly, seasonal, and diurnal variations in OC and EC, as well as OC subtypes, i.e. secondary OC (SOC) and primary OC (POC), apportioned by the novel statistical model of the minimum R² method, and the formation pathways of SOC, are presented. By examining the relationship between SOC and temperature, as well as relative humidity (RH), we show that SOC formation is greatly enhanced at high temperatures (> 30 ^∘C), whereas it correlates inversely with RH. In particular, we show that the photochemical formation of SOC is the major formation pathway even in winter, when solar radiation was supposedly less intense than in summer, which is different from that in the north China plain, where aqueous phase chemistry is found to be an important SOC formation pathway. Moreover, increased SOC concentrations are also found to be associated with high wind speed (> 5 m s⁻¹) in winter, which is increased by 29.1 % (2.62 µg m⁻³) when compared with that during lower winds, suggesting regional sources of SOC in winter. By analysing the potential source regions using the concentration-weighted trajectory (CWT), the geographic regions of SOC are found to be mainly associated with transport from outside Shanghai (SOC > 3.5 µg m⁻³) including central and southern Anhui, Zhejiang, and Fujian. The results from this study provide critical information about the long-term trend of carbonaceous aerosol, in particular, SOC, in one of the largest megacities in the world, and are helpful for developing pollution control measures from a long-term planning perspective.

The increasing presence of emerging contaminants (ECs) has attracted considerable attention due to their potential harm to human health and ecosystems. Graphitic carbon nitride (g-C₃N₄), a semiconductor devoid of metals, stands out due to its distinctive optical properties and strong resistance to chemical degradation, which holds significant promise in the photocatalytic degradation of ECs. However, the inherent limitations of g-C₃N₄, such as its reduced specific surface area and the swift recombination of photogenerated electron-hole pairs, have prompted extensive research on modification strategies to enhance its photocatalytic performance. Current research on g-C₃N₄-based materials is often constrained in scope, with most reviews focusing solely on modification strategies or its application in degrading a single category of emerging contaminants (ECs). In this review, a systematic overview of synthesis methods and advanced modification strategies for g-C₃N₄-based materials is discussed, highlighting their recent advances in the photocatalytic degradation of various ECs using g-C₃N₄-based materials, which underscores their potential for environmental remediation. Moreover, this article critically examines the current challenges and outlines future research directions, with particular emphasis on integrating artificial intelligence and machine learning to accelerate the development of g-C₃N₄-based photocatalysts and optimize degradation processes, thereby promoting their efficient application in the photocatalytic degradation of ECs.

Exposure to elemental carbon (EC) and NO_x is a public health issue that has been gaining increasing interest, with high exposure levels generally observed in traffic environments, e.g., roadsides. Shanghai, home to approximately 25 million in the Yangtze River Delta (YRD) region in eastern China, has one of the most intensive traffic activity levels in the world. However, our understanding of the trend in vehicular emissions and, in particular, in response to the strict Covid-19 lockdown is limited partly due to the lack of a long-term observation dataset and application of advanced mathematical models. In this study, NO_x and EC were continuously monitored at a sampling site near a highway in western Shanghai for 5 years (2016–2020). The long-term dataset was used to train the machine learning model, rebuilding NO_x and EC in a business-as-usual (BAU) scenario for 2020. The reduction in NO_x and EC attributable to the lockdown was found to be smaller than it appeared because the first week of the lockdown overlapped with the Lunar New Year holiday, whereas, at a later stage of the lockdown, the reduction (50 %–70 %) attributable to the lockdown was more significant, consistent with the satellite monitoring of NO₂ showing reduced traffic on a regional scale. In contrast, the impact of the lockdown on vehicular emissions cannot be represented well by simply comparing the concentration before and during the lockdown for conventional campaigns. This study demonstrates the value of continuous air pollutant monitoring at a roadside on a long-term basis. Combined with the advanced mathematical model, air quality changes due to future emission control and/or event-driven scenarios are expected to be better predicted.

In this study, a systematic review of algae biofuels, including their development and production process, is presented. Compared with traditional techniques, supercritical CO₂ extraction, known for its high efficiency and environmental sustainability, has been widely applied in extracting plant compounds, oils, and fats, demonstrating its role as a promising alternative in biofuel conversion. The principle and features of supercritical CO₂ extraction technology are introduced, and its applications in biofuel production in China are reviewed. The results indicate its broad applicability and substantial scientific value in biofuel production, underscored by its unique extraction mechanisms and operational flexibility and obstacles to its large-scale implementation. Against a future where supercritical CO₂ extraction will play a pivotal role in industrial biofuel production due to the technology’s advancement and policy support in China, this review offers comprehensive insights and references to guide future research into and practices of supercritical CO₂ extraction and biofuel development.