Synergistic PM2.5 and O3 control to address the emerging global PM2.5-O3 compound pollution challenges

Spatiotemporal correlations of PM2.5 and O3 variations: A street-scale perspective on synergistic regulation

PM2.5 and O3 are major pollutants affecting air quality and posing serious health risks in China. While many studies focus on their control at urban and regional scales, their co-regulation at the street level-closely tied to traffic emissions and commuting patterns-remains unexplored. This study addressed the gap by using nonlinear statistical methods to analyze the spatiotemporal evolution of PM2.5 and O3 from street-scale mobile measurements in Fuzhou, China. A random forest (RF) model was applied to elucidate factors influencing PM2.5-O3 synchronicity. Key findings revealed that street-scale variations in PM2.5 and O3 exhibited multifractality and long-term persistence. Co-directional changes between PM2.5 and O3 peaked at noon, compared to traffic peak hours and midnight. An 800 m threshold was identified for analyzing PM2.5-O3 synchronicity-below this spatial scale, local factors weaken their concordance, while beyond it, the concordance strengthened. RF models showed that PM2.5 was primarily influenced by precursor substances in winter and meteorological conditions in summer, while O3 was consistently affected by meteorological conditions across both seasons. Road traffic and construction disrupted the co-directional changes of PM2.5 and O3, whereas high humidity partially mitigated high concentrations of both pollutants but enhanced their synchronicity.

Airway microbiota dysbiosis and metabolic disorder in ozone and PM2.5 co-exposure induced lung inflammatory injury in mice

Co-exposure to ground-level ozone (O3) and fine particles (PM2.5, ≤ 2.5 µm in diameter) has become a primary scenario for air pollution exposure of urbanites in China. Recent studies have suggested a synergistic effect of PM2.5 and O3 on induction of lung inflammatory injury. However, the underlying mechanisms for respiratory toxicity induced by this co-exposure have not been adequately elucidated. In this study, a realistic exposure was based to set up the co-exposure condition of an animal model. Specifically, eighty male C57BL/6 mice (10 months old) were randomly divided into four groups: control, O3, PM2.5 and co-exposure (O3 + PM2.5). Mice in the co-exposure group breathed O3 and orally inhaled PM2.5 suspension. The scenario for O3 exposure was 0.6 ppm, 4 h/d, for 30 consecutive days while that for PM2.5 exposure was oral inhalation of PM2.5 suspension (5.6 mg/kg bw) once every other day and 4 h prior to O3 exposure. After last exposure, bronchoalveolar lavage fluids (BALF) were collected for inflammatory biomarker measurement, 16S rRNA sequencing and metabolite profiling. Lung tissues were processed for histological examination. The results demonstrated that co-exposure to O3 and PM2.5 exacerbated the pathological changes and inflammatory response induced by O3 or PM2.5. Further studies revealed that co-exposure to O3 and PM2.5 increased the abundance of Prevotella in the airways and caused more severe metabolic disorders compared to O3 or PM2.5 exposure. Spearman correlation analysis demonstrated correlations among airway microbiota dysbiosis, metabolic disorder, inflammation, and pathological alterations induced by co-exposure to O3 and PM2.5. In summary, co-exposure to O3 and PM2.5 worsens airway inflammatory injury, possibly through interrelated airway microbiota dysbiosis and metabolic disorder.

Winter-spring droughts exacerbated PM2.5-O3 compound pollution? Evidence from China

With the impact of global climate change, drought events are becoming more frequent, making it critically important to quantitatively evaluate the effects of these events on air pollution. This study uses the augmented synthetic control method and the mediation effect model to quantitatively evaluate the impact effect of the winter-spring drought of 2023 on PM2.5-O3 compound pollution and its driving factors with Chinese prefecture-level city data. This study indicates that: firstly, compared to non-drought periods, both the monthly averaged and diurnal variations pattern of PM2.5 and O3 significantly increased during drought periods. Secondly, the winter-spring drought of 2023 led to an average increase of 101.05 μg/m3(28.14 %) for PM2.5 and 153.74 μg/m3(13.32 %) for O3 in Yunnan Province, while the average increases in Guizhou Province were 25.71 μg/m3(11.59 %) and 23.95 μg/m3(4.09 %), respectively. Thirdly, the increase in temperature and the decrease in precipitation and relative humidity during the winter-spring drought were among the main driving factors for the increased risk of "double-high" PM2.5-O3 compound pollution. The article expands the research on the impact of abnormal weather events on atmospheric compound pollution, providing new insights for preventing compound pollution events in the context of abnormal weather.

Comprehensive health risk assessment of urban ambient air pollution (PM2.5, NO2 and O3) in Ghana

Urbanization and industrialization have drastically increased ambient air pollution in urban areas globally from vehicle emissions, solid fuel combustion and industrial activities leading to some of the worst air quality conditions. Air pollution in Ghana causes approximately 28,000 premature deaths and disabilities annually, ranking as a leading cause of mortality and disability-adjusted life years. This study evaluated the annual concentrations of PM2.5, NO2 and O3 in the ambient air of 57 cities in Ghana for two decades using historical and forecasted data from satellite measurements. The study assessed urban air quality and evaluated both carcinogenic and non-carcinogenic health risks associated with human exposure to ambient air pollutants. Alarmingly, our findings revealed the yearly median PM2.5 concentrations (50.79-67.97 µg m-3) to be significantly higher than the WHO recommendation of 5 µg m-3. Tropospheric ozone concentrations (72.21-92.58 µg m-3 ) also exceeded the WHO annual standard of 60 µg m-3. Furthermore, NO2 concentrations (3.65-12.15 µg m-3 ) surpassed the WHO threshold of 10 µg/m³ in multiple cities. Hazard indices indicated that PM2.5 and O3 pose significant non-carcinogenic health risks for younger age groups for a daily exposure duration of three hours and beyond. According to the Air Quality Life Index (AQLI) in our study, exposure to PM2.5 shortens life expectancy by 4.5-6.2 years. The ambient air of the majority (98 %) of the cities was unhealthy for sensitive groups. This study reveals the urgent need for comprehensive air quality policies in Ghanaian cities. It emphasizes the significance of robust real-time monitoring of air pollutants and the investigation of seasonal dust storm effects, to fill data gaps in Ghana and West Africa, facilitating evidence-based interventions that improve urban air quality and public health outcomes.

Characterization and regional linkage analysis of PM2.5 emissions driven by energy consumption in mainland China, 2007-2017

Fine particulate matter (PM2.5) pollution poses a serious threat to public health, and there has been a recent resurgence in PM2.5 pollution levels in China. Inter-provincial trade has further complicated the allocation of responsibility for PM2.5 emissions. An in-depth analysis of the Air Pollution Prevention and Control Action Plan (APPCAP), a highly effective environmental policy, offers new perspectives and avenues for reflection. Using the multi-regional input-output model and structural decomposition analysis model, this study provides insights into the interlinkages of PM2.5 emissions, and their influencing mechanisms among different regions from the perspective of source emissions by quantifying the dynamics of production-related PM2.5 emissions (PEp) associated with energy consumption and the key driving socio-economic factors in the pre-and post-APPCAP phases. The results indicate that PEp initially increased and then decreased over the study period. In the pre-policy stage, only five provinces exhibited a decrease in PEp, and this number increased to 21 provinces post-policy. Manufacturing and energy utilities consistently account for significant PEp contributions, particularly in Shanghai, Inner Mongolia, and Shanxi. This study finds that pre-policy, the industrial structure effect, the demographic effect, and the level of affluence effect primarily drove PEp increases. The post-policy decrease was influenced by industrial structure and consumption pattern effects. Although China's PEp remains higher than the consumption-based PM2.5 emissions (PEc), significant provincial variations exist. Notably, while changes in PEp do not always align with PM2.5 concentration changes, simultaneous reductions following policy implementation signal positive progress in pollution control. This underscores the necessity of continuously optimizing policy strategies to accommodate regional characteristics.

Spatial and temporal changes of air quality in Shandong Province from 2016 to 2022 and model prediction

This study investigates the spatial and temporal dynamics of air quality in Shandong Province from 2016 to 2022. The Air Quality Index (AQI) showed a seasonal pattern, with higher values in winter due to temperature inversions and heating emissions, and lower values in summer aided by favorable dispersion conditions. The AQI improved significantly, decreasing by approximately 39.4 % from 6.44 to 3.90. Coastal cities exhibited better air quality than inland areas, influenced by industrial activities and geographical features. For instance, Zibo's geography restricts pollutant dispersion, resulting in poor air quality. CO levels remained stable, while O3 increased seasonally due to photochemical reactions in summer, with correlation coefficients indicating a strong positive correlation with temperature (r = 0.65). Winter saw elevated NO2 levels linked to heating and vehicular emissions, with an observed increase in correlation with AQI (r = 0.78). PM2.5 and PM10 concentrations were higher in colder months due to heating and atmospheric dust, showing a significant decrease of 45 % and 40 %, respectively, over the study period. Predictive modeling forecasts continued air quality improvements, contingent on sustained policy enforcement and technological advancements. This approach provides a comprehensive framework for future air quality management and improvement.