A review on methodology in O3-NOx-VOC sensitivity study

Characteristics of surface ozone pollution and its correlations with meteorological factors: the case of Xiangtan

Based on ozone (O3) monitoring data for Xiangtan and meteorological observation data for 2020-2022, we examined ozone pollution characteristics and the effects of meteorological factors on daily maximum 8-h average ozone (O3-8h) concentrations in Xiangtan. Thus, we observed significant increases as well as notable seasonal variations in O3-8h concentrations in Xiangtan during the period considered. The ozone and temperature change response slope (KO3-T) indicated that local emissions had no significant effect on O3-8h generation. Further, average O3-8h concentration and maximum temperature (Tmax) values showed a polynomial distribution. Specifically, at Tmax < 27 °C, it increased almost linearly with increasing temperature, and at Tmax between 27 and 37 °C, it showed an upward curvilinear trend as temperature increased, but at a much lower rate. Then, at Tmax > 37 °C, it decreased with increasing temperature. With respect to relative humidity (RH), the average O3-8h concentration primarily exceeded the standard value when RH varied in the range of 45-65%, which is the key humidity range for O3 pollution, and the inflection point for the correlation curve between O3-8h concentration and RH appeared at ~55%. Furthermore, at wind speeds (WSs) below 1.5 m∙s-1, O3-8h concentration increased rapidly, and at WSs in the 1.5-2 m∙s-1 range, it increased at a much faster rate. However, at WSs > 2 m∙s-1, it decreased slowly with increasing WS. O3-8h concentration also showed the tendency to exceed the standard value when the dominant wind directions in Xiangtan were easterly or southeasterly.

Synergistic effects of copper and oxygen vacancies in enhancing the efficacy of partially crystalline CuMnxOy catalyst for ozone decomposition

To tackle the challenge of ground-level ozone pollution, this study proposed a potential catalytic design approach for ozone decomposition using Cu-Mn bimetallic oxide. This approach is grounded in an understanding of the intrinsic reactivity for catalyst and incorporates a novel potassium-driven low-temperature oxidation process for catalyst synthesis. The research highlights the creation of a highly reactive Cu-Mn oxide phase with extensive defect coverage, leading to significantly increased reaction rates. It also identifies the MnO2(100) facet as a crucial active phase, where oxygen vacancies simultaneously enhance O3 adsorption and decomposition, albeit with a concurrent risk of O2 poisoning due to the stabilization of adsorbed O2. Crucially, the incorporation of Cu offsets the effects of oxygen vacancies, influencing conversion rates and lessening O2 poisoning. The synergistic interplay between Cu and oxygen vacancies elevates the performance of the defect-rich Cu-Mn oxide catalyst. By combining computational and experimental methods, this study not only advances the understanding of the Cu-Mn oxide system for ozone decomposition but also contributes valuable insights into developing more efficient catalysts to mitigate ozone pollution.

Application of machine learning to analyze ozone sensitivity to influencing factors: A case study in Nanjing, China

Ground-level ozone (O3) has been an emerging concern in China. Due to its complicated formation mechanisms, understanding the effects of influencing factors is critical for making effective efforts on the pollution control. This study aims to present and demonstrate the practicality of a data-driven technique that applies a machine learning (ML) model coupled with the SHapley Additive exPlanations (SHAP) approach in O3 simulation and sensitivity analysis. Based on hourly measured concentrations of O3 and its major precursors, as well as meteorological factors in a northern area of Nanjing, China, a Light Gradient Boosting Machine (LightGBM) model was established to simulate O3 concentrations in different seasons, and the SHAP approach was applied to conduct in-depth analysis on the impacts of influencing factors on O3 formation. The results indicated a reliable performance of the ML model in simulating O3 concentrations, with the coefficient of determination (R2) between the measured and simulated larger than 0.80, and the impacts of influencing factors were reasonably evaluated by the SHAP approach on both seasonal and diurnal time scales. It was found that although volatile organic compounds (VOCs) and nitrogen oxides (NOx), as well as temperature and relative humidity, were generally the main influencing factors, their sensitivities to O3 formation varied significantly in different seasons and with time of the day. This study suggests that the data-driven ML model is a practicable technique and may act as an alternative way to perform mechanism analysis to some extent, and has immense potential to be applied in both problem research and decision-making for air pollution control.

Scaling features in high-concentrations PM2.5 evolution: the Ignored factor affecting scarlet fever incidence

As an acute respiratory disease, scarlet fever has great harm to public health. Some evidence indicates that the time distribution pattern of heavy PM2.5 pollution occurrence may have an impact on health risks. This study aims to reveal the relation between scaling features in high-concentrations PM2.5 (HC-PM2.5) evolution and scarlet fever incidence (SFI). Based on the data of Hong Kong from 2012 to 2019, fractal box-counting dimension (D) is introduced to capture the scaling features of HC-PM2.5. It has been found that index D can quantify the time distribution of HC-PM2.5, and lower D values indicate more cluster distribution of HC-PM2.5. Moreover, scale-invariance in HC-PM2.5 at different time scales has been discovered, which indicates that HC-PM2.5 occurrence is not random but follows a typical power-law distribution. Next, the exposure-response relationship between SFI and scale-invariance in HC-PM2.5 is explored by Distributed lag non-linear model, in conjunction with meteorological factors. It has been discovered that scale-invariance in HC-PM2.5 has a nonlinear effect on SFI. Low and moderate D values of HC-PM2.5 are identified as risk factors for SFI at small time-scale. Moreover, relative risk shows a decreasing trend with the increase of exposure time. These results suggest that exposure to short-term clustered HC-PM2.5 makes individual more prone to SFI than exposure to long-term uniform HC-PM2.5. This means that individuals in slightly-polluted regions may face a greater risk of SFI, once the PM2.5 concentration keeps rising. In the future, it is expected that the relative risk of scarlet fever for a specific region can be estimated based on the quantitative analysis of scaling features in high-concentrations PM2.5 evolution.

Spatiotemporal evolution and key driver analysis of ozone pollution from the perspectives of spatial spillover and path-dependence effects in China

In recent years, ozone (O3) has emerged as the primary air pollutant in China, superseding PM2.5. Previous studies have concentrated on the spatiotemporal variation of ozone pollution, the analysis of its sources and drivers, as well as its environmental impacts and health benefits. Since ozone pollution can be dynamically transferred through industrial activities and meteorological factors, it is crucial to scientifically identify the spatial spillover and path-dependent effects of ozone pollution in China. However, existing studies have not yet addressed this issue. Therefore, we investigate the spatiotemporal evolution and the spatial spillover of ozone pollution by means of the exploratory spatial data analysis (ESDA) using panel data of 30 Chinese provinces from 2013 to 2020 in this study. The dynamic spatial Durbin model (SDM) was employed to reveal the key drivers of ozone pollution from the perspectives of spatial spillover and path-dependence effects. The direct and spillover effects of each driver on ozone pollution are systematically analyzed. The results show that from 2013 to 2020 ozone concentrations followed a fluctuating upward trend at national and provincial scales. Ozone pollution presented significant spatial spillover and path dependence effects. The direct effects indicated that economic growth, technological level, industrial structure, energy structure, ventilation coefficient, relative humidity and precipitation were the key drivers of local ozone pollution. The spillover effects indicated that population density, technology level, industrial structure, environmental regulations, ventilation coefficient, sunshine hours and relative humidity had significant spatial spillover effects on ozone pollution of surrounding regions. These findings will contribute to the understanding of the spatial spillover and path-dependent effects of O3 pollution, and provide scientific guidance for regional synergy and long-term ozone control policies in China.

Comparative analysis for the impacts of VOC subgroups and atmospheric oxidation capacity on O3 based on different observation-based methods at a suburban site in the North China Plain

The persistent O3 pollution in the Beijing-Tianjin-Hebei (BTH) region remains unresolved, largely due to limited comprehension of O3-precursor relationship and photochemistry drivers. In this work, intraday O3 sensitivity evolution from VOC-limited (volatile organic compound) regime in the forenoon to transition regime in the late afternoon was inferred by relative incremental reactivity (RIR) in summer 2019 at Xianghe, a suburban site in BTH region, suggesting that VOC-focused control policy could combine with stringent afternoon NOx control. Then detailed impacts of VOC subgroups on O3 formation were further comprehensively quantified by parametric OH reactivity (KOH), O3 formation potential (OFP), as well as RIR weighted value and O3 formation path tracing (OFPT) approach based on photochemical box model. O3 episode days corresponded to stronger O3 formation, depicted by higher KOH (10.4 s-1), OFP (331.7 μg m-3), RIR weighted value (1.2), and F(O3)-OFPT (15.5 ppbv h-1). High proportions of isoprene and OVOCs (oxygenated VOCs) to the total KOH and the OFPT method were demonstrated whereas results of OFP and RIR-weighted presented extra great impacts of aromatics on O3 formation. The OFPT approach captured the process that has already happened and included final O3 response to the original VOC, thus reliable for replicating VOC impacts. The comparison results of the four methods showed similarities when utilizing KOH and OFPT methods, which reveals that the potential applicability of simple KOH for contingency VOC control and more complex OFPT method for detailed VOC- and source-oriented control during policy-making. To investigate propulsion of VOC-involved O3 photochemistry, atmospheric oxidation capacity (AOC) was quantified by two atmospheric oxidation indexes (AOI). Both AOIp_G (7.0 × 107 molec cm-3 s-1, potential AOC calculated by oxidation reaction rates) and AOIe_G (8.5 μmol m-3, estimated AOC given redox electron transfer for oxidation products) were stronger on O3 episode days, indicating that AOC promoted the radical cycling initiated from VOC oxidation and subsequent O3 production. Result-oriented AOIe_G reasonably characterized actual AOC inferred by good linear correlation between AOIe_G and O3 concentrations compared to process-oriented AOIp_G. Therefore, with continuous NOx abatement, AOIe_G should be considered to represent actual AOC, also O3-inducing ability.

Research on ozone formation sensitivity based on observational methods: Development history, methodology, and application and prospects in China

Observation-based method for O3 formation sensitivity research is an important tool to analyze the causes of ground-level O3 pollution, which has broad application potentials in determining the O3 pollution formation mechanism and developing prevention and control strategies. This paper outlined the development history of research on O3 formation sensitivity based on observational methods, described the principle and applicability of the methodology, summarized the relative application results in China and provided recommendations on the prevention and control of O3 pollution in China based on relevant study results, and finally pointed out the shortcomings and future development prospects in this field in China. The overview study showed that the O3 formation sensitivity in some urban areas in China in recent years presented a gradual shifting tendency from the VOC-limited regime to the transition regime or the NOx-limited regime due to the implementation of the O3 precursors emission reduction policies; O3 pollution control strategies and precursor control countermeasures should be formulated based on local conditions and the dynamic control capability of O3 pollution control measures should be improved. There are still some current deficiencies in the study field in China. Therefore, it is recommended that a stereoscopic monitoring network for atmospheric photochemical components should be further constructed and improved; the atmospheric chemical mechanisms should be vigorously developed, and standardized methods for determining the O3 formation sensitivity should be established in China in the near future.

A new scheme of PM2.5 and O3 control strategies with the integration of SOM, GA and WRF-CAMx

Previous air pollution control strategies didn't pay enough attention to regional collaboration and the spatial response sensitivities, resulting in limited control effects in China. This study proposed an effective PM2.5 and O3 control strategy scheme with the integration of Self-Organizing Map (SOM), Genetic Algorithm (GA) and WRF-CAMx, emphasizing regional collaborative control and the strengthening of control in sensitive areas. This scheme embodies the idea of hierarchical management and spatial-temporally differentiated management, with SOM identifying the collaborative subregions, GA providing the optimized subregion-level priority of precursor emission reductions, and WRF-CAMx providing response sensitivities for grid-level priority of precursor emission reductions. With Beijing-Tianjin-Hebei and the surrounding area (BTHSA, "2 + 26" cities) as the case study area, the optimized strategy required that regions along Taihang Mountains strengthen the emission reductions of all precursors in PM2.5-dominant seasons, and strengthen VOCs reductions but moderate NOx reductions in O3-dominant season. The spatiotemporally differentiated control strategy, without additional emission reduction burdens than the 14th Five-Year Plan proposed, reduced the average annual PM2.5 and MDA8 O3 concentrations in 28 cities by 3.2%-8.2% and 3.9%-9.7% respectively in comparison with non-differential control strategies, with the most prominent optimization effects occurring in the heavily polluted seasons (6.9%-18.0% for PM2.5 and 3.3%-14.2% for MDA8 O3, respectively). This study proposed an effective scheme for the collaborative control of PM2.5 and O3 in BTHSA, and shows important methodological implications for other regions suffering from similar air quality problems.

PM2.5 pollution modulates the response of ozone formation to VOC emitted from various sources: Insights from machine learning

Numerous studies have linked ozone (O3) production to its precursors and fine particulate matter (PM2.5), while the complex interaction effects of PM2.5 and volatile organic compounds (VOCs) on O3 remain poorly understood. A systematic approach based on an interpretable machine learning (ML) model was utilized to evaluate the primary driving factors that impact O3 and to elucidate how changes in PM2.5, VOCs from different sources, NOx, and meteorological conditions either promote or inhibit O3 formation through their individual and synergistic effects in a tropical coastal city, Haikou, from 2019 to 2020. The results suggest that under low PM2.5 levels, alongside the linear O3-PM2.5 relationship observed, O3 formation is suppressed by PM2.5 with higher proportions of traffic-derived aerosol. Vehicle VOC emissions contributed maximally to O3 formation at midday, despite the lowest concentration. VOCs from fossil fuel combustion and industry emissions, which have opposing effects on O3, act as inhibitors and promoters by inducing diverse photochemical regimes. As PM2.5 pollution escalates, the impact of these VOCs reverses, becoming more pronounced in shaping O3 variation. Sensitivity analysis reveals that the O3 formation regime is VOC-limited, and effective regional O3 mitigation requires prioritizing substantial VOC reductions to offset enhanced VOC sensitivity induced by the co-reduction in PM2.5, with a focus on industrial and vehicular emissions, and subsequently, fossil fuel combustion once PM2.5 is effectively controlled. This study underscores the potential of the SHAP-based ML approach to decode the intricate O3-NOx-VOCs-PM2.5 interplay, considering both meteorological and atmospheric compositional variations.

Comparison of the ozone formation mechanisms and VOCs apportionment in different ozone pollution episodes in urban Beijing in 2019 and 2020: Insights for ozone pollution control strategies

Ground-level ozone (O3) pollution has been a tough issue in urban areas of China in the past decade. Clarifying the formation mechanisms of O3 and the sources of its precursors is necessary for the effective prevention of O3 pollution. In this study, a comparative analysis of O3 formation mechanisms and VOCs apportionment for five O3 pollution episodes was carried out at two urban sites (CRAES and CGZ) in Beijing in 2019 and 2020 by applying an observation-based modeling approach in order to obtain insights into O3 pollution control strategies. Results indicated that O3 pollution levels were generally more severe in 2019 than in 2020 during the observation periods. O3 formation at the two sites was both VOCs-limited on O3 polluted days and non-O3 polluted days. Stronger atmospheric oxidation capacity and ROx radicals cycling processes were found on O3 polluted days which could accelerate the local production of O3, and local photochemical production dominated the observed O3 concentrations at the two sites even on non-O3 polluted days. Emission reduction of VOCs should be a priority for mitigating O3 pollution, and alkenes and biogenic VOCs was the priority species at the CRAES and CGZ sites, respectively. Additionally, the reduction of oxygenated VOCs should also be important for the ozone control. Gasoline exhaust at the CRAES site, and solvent utilization and fuel evaporation at the CGZ site were main anthropogenic sources of VOCs. Therefore, local control measures should be further strengthened and differentiated control strategies of VOCs in the aspects of area, time, sources and species should be adopted in urban Beijing in the future. Overall, the findings of this study could provide a scientific understanding of the causes of O3 pollution and significant guidelines for formulating O3 control strategies from the perspective of different ozone pollution episodes in urban Beijing.

Evolution of Ozone Formation Sensitivity during a Persistent Regional Ozone Episode in Northeastern China and Its Implication for a Control Strategy

In recent years, the magnitude and frequency of regional ozone (O3) episodes have increased in China. We combined ground-based measurements, observation-based model (OBM), and the Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model to analyze a typical persistent O3 episode that occurred across 88 cities in northeastern China during June 19-30, 2021. The meteorological conditions, particularly the wind convergence centers, played crucial roles in the evolution of O3 pollution. Daily analysis of the O3 formation sensitivity showed that O3 formation was in the volatile organic compound (VOC)-limited or transitional regime at the onset of the pollution episode in 92% of the cities. Conversely, it tended to be or eventually became a NOx-limited regime as the episode progressed in the most polluted cities. Based on the emission-reduction scenario simulations, mitigation of the regional O3 pollution was found to be most effective through a phased control strategy, namely, reduction of a high ratio of VOCs to NOx at the onset of the pollution and lower ratio during evolution of the O3 episode. This study presents a new possibility for regional O3 pollution abatement in China based on a reasonable combination of OBM and the WRF-CMAQ model.

Achievements and challenges in improving air quality in China: Analysis of the long-term trends from 2014 to 2022

Due to the implementation of air pollution control measures in China, air quality has significantly improved, although there are still additional issues to be addressed. This study used the long-term trends of air pollutants to discuss the achievements and challenges in further improving air quality in China. The Kolmogorov-Zurbenko (KZ) filter and multiple-linear regression (MLR) were used to quantify the meteorology-related and emission-related trends of air pollutants from 2014 to 2022 in China. The KZ filter analysis showed that PM2.5 decreased by 7.36 ± 2.92% yr-1, while daily maximum 8-h ozone (MDA8 O3) showed an increasing trend with 3.71 ± 2.89% yr-1 in China. The decrease in PM2.5 and increase in MDA8 O3 were primarily attributed to changes in emission, with the relative contribution of 85.8% and 86.0%, respectively. Meteorology variations, including increased ambient temperature, boundary layer height, and reduced relative humidity, also contributed to the reduction of PM2.5 and the enhancement of MDA8 O3. The emission-related trends of PM2.5 and MDA8 O3 exhibited continuous decrease and increase, respectively, from 2014 to 2022, while the variation rates slowed during 2018-2020 compared to that during 2014-2017, highlighting the challenges in further improving air quality, particularly in simultaneously reducing PM2.5 and O3. This study recommends reducing NH3 emissions from the agriculture sector in rural areas and transport emissions in urban areas to further decrease PM2.5 levels. Addressing O3 pollution requires the reduction of O3 precursor gases based on site-specific atmospheric chemistry considerations.

Source apportionment and ozone formation mechanism of VOCs considering photochemical loss in Guangzhou, China

Understanding the sources and impact of volatile organic compounds (VOCs) on ozone formation is challenging when the traditional method does not account for their photochemical loss. In this study, online monitoring of 56 VOCs was carried out in summer and autumn during high ozone pollution episodes. The photochemical age method was used to evaluate the atmospheric chemical loss of VOCs and to analyze the effects on characteristics, sources, and ozone formation of VOC components. The initial concentrations during daytime were 5.12 ppbv and 4.49 ppbv higher than the observed concentrations in the summer and autumn, respectively. The positive matrix factorization (PMF) model identified 5 major emission sources. However, the omission of the chemical loss of VOCs led to underestimating the contributions of sources associated with highly reactive VOC components, such as those produced by biogenic emissions and solvent usage. Conversely it resulted in overestimating the contributions from VOC components with lower chemical activity such as liquefied petroleum gas (LPG) usage, vehicle emissions, and gasoline evaporation. Furthermore, the estimation of ozone formation may be underestimated when the atmospheric photochemical loss is not taken into account. The ozone formation potential (OFP) method and propylene-equivalent concentration method both underestimated ozone formation by 53.24 ppbv and 47.25 ppbc, respectively, in the summer, and by 40.34 ppbv and 26.37 ppbc, respectively, in the autumn. The determination of the ozone formation regime based on VOC chemical loss was more acceptable. In the summer, the ozone formation regime changed from the VOC-limited regime to the VOC-NOx transition regime, while in the autumn, the ozone formation regime changed from the strong VOC-limited regime to the weak VOC-limited regime. To obtain more thorough and precise conclusions, further monitoring and analysis studies will be conducted in the near future on a wider variety of VOC species such as oxygenated VOCs (OVOCs).

Observation on the aerosol and ozone precursors in suburban areas of Shenzhen and analysis of potential source based on MAX-DOAS

Long-term stereoscopic observations of aerosol, NO₂, and HCHO were carried out at the Yangmeikeng (YMK) site in Shenzhen. Aerosol optical depths and NO₂ vertical column concentration (NO₂ VCD) derived from MAX-DOAS were found to be consistent with other datasets. The total NO₂ VCD values of the site remained low, varying from 2 × 10¹⁵ to 8 × 10¹⁵ mol/cm², while the HCHO VCD was higher than NO₂ VCD, varying from 7 × 10¹⁵ to 11 × 10¹⁵ mol/cm². HCHO VCD was higher from September to early November than that was from mid-late November to December and during February 2021, in contrast, NO₂ VCD did not change much during the same period. In January, NO₂ VCD and HCHO VCD were both fluctuating drastically. High temperature and HCHO level in the YMK site is not only driving the ozone production up but also may be driving up the ozone concentration as well, and the O₃ production regime in the YMK site tends to be NO_x-limited. At various altitudes, backward trajectory clustering analysis and Potential Source Contribution Function (PSCF) were utilized to identify possible NO₂ and HCHO source locations. The results suggested that the Huizhou-Shanwei border and the Daya Bay Sea area were the key potential source locations in the lower (200 m) and middle (500 m) atmosphere (WPSCF > 0.6). The WPSCF value was high at the 1000 m altitude which was closer to the YMK site than the near ground, indicating that the pollution transport capability in the upper atmosphere was limited.

Statistical significance of PM2.5 and O3 trends in China under long-term memory effects

Over the past decade, the Chinese government has implemented the "Clean Air Action" measures to enhance the atmospheric environmental quality, primarily focusing on curbing PM2.5 and O3 concentrations. The efficacy of these strategies and the underlying causes (human factors or natural variability) of any observed increases or decreases in PM2.5 and O3 concentrations are of great importance. Examining the hourly PM2.5 and O3 concentration time series from six representative regions in China between 2015 and 2021 revealed an overall downward trend in PM2.5 concentrations. However, the O3 concentration time series indicated upward trends in some regions, except for the Northeast area (NE) and Sichuan Basin (SCB). In the context of conventional significance tests, the assumption is typically that the time series' samples are independent and therefore memoryless. However, in situations where the time series exhibits strong autocorrelation and limited sample size, this assumption can lead to an overestimation of the statistical significance of the linear trend. To account for this, we utilized a long-term memory model that can reproduce the long-term persistence of pollutant records to improve the accuracy of significance tests. By comparing the P-values of real and surrogate data generated by the long-term memory model, we found that only PM2.5 concentrations in the Pearl River Delta (PRD) were slightly insignificant. For the remaining five regions, the P-values of PM2.5 concentrations were smaller than the significant level of 0.05, suggesting that the observed downward trends in PM2.5 concentrations are not due to natural variability, thereby confirming the effectiveness of the government's policies aimed at curbing atmospheric particulate matter in recent years. Our results show that O3 pollution is significantly increasing only in the Beijing-Tianjin-Hebei (BTH) region, beyond natural variability. In contrast, the trends of O3 pollution in many regions of China are markedly impacted by natural and climate variability.

Sources-oriented contributions to ozone and secondary organic aerosol formation potential based on initial VOCs in an urban area of Eastern Asia

Over the past decades, the pollution of ozone (O3) and secondary organic aerosols (SOA) in the atmosphere has become a major concern worldwide due to their adverse effects on human health, air quality and climate. Volatile organic compounds (VOCs) are crucial precursors of O3 and SOA, but identifying the primary sources of VOCs that contribute to the formation of O3 and SOA has been challenging due to the rapid consumption of VOCs by oxidants in the air. To address this issue, a study was conducted in a Taipei urban area in Taiwan, where the hourly data of 54 VOC species were collected from March 2020 to February 2021 detected by Photochemical Assessment Monitoring Stations (PAMS). The initial mixing ratios of VOCs (VOCsini) were determined by combining the observed VOCs (VOCsobs) and the consumed VOCs resulting from photochemical reactions. Additionally, the ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) were estimated based on VOCsini. The OFP derived from VOCsini (OFPini) was found to exhibit a strong correlation with O3 mixing ratios (R2 = 0.82), whereas the OFP obtained from VOCsobs did not show such a correlation. Isoprene, toluene and m,p-xylene were the top three species contributing to OFPini, while toluene and m,p-xylene were the top two contributors to SOAFPini. Positive matrix factorization analysis revealed that biogenic, consumer/household products, and industrial solvents were the major contributors to OFPini in four seasons, and SOAFPini mostly came from consumer/household products and industrial solvents. This study highlights the importance of considering photochemical loss caused by different VOCs reactivity in the atmosphere when evaluating OFP and SOAFP. Moreover, it emphasizes the need to prioritize controlling the sources emitting the dominant VOC precursors of O3 and SOA to effectively alleviate the scenarios of elevated O3 and particulate matter.

Spatiotemporal characteristics of ozone and the formation sensitivity over the Fenwei Plain

High surface ozone (O₃) levels affect human and environmental health. The Fenwei Plain (FWP), one of the critical regions for China's "Blue Sky Protection Campaign", has reported severe O₃ pollution. This study investigates the spatiotemporal properties and the causes of O₃ pollution over the FWP using high-resolution data from the TROPOspheric Monitoring Instrument (TROPOMI) from 2019 to 2021. This study characterizes spatial and temporal variations in O₃ concentration by linking O₃ columns and surface monitoring using a trained deep forest machine learning model. O₃ concentrations in summer were 2-3 times higher than those found in winter due to higher temperatures and greater solar irradiation. The spatial distributions of O₃ correlate with the solar radiation showing decreased trends from the northeastern to the southwestern FWP, with the highest O₃ values in Shanxi Province and the lowest in Shaanxi Province. For urban areas, croplands and grasslands, the O₃ photochemistry in summer is NO_x-limited or in the transitional regime, while it is VOC-limited in winter and other seasons. Reducing NO_x emissions would be effective for decreasing O₃ levels in summer, while VOC reductions are necessary for winter. The annual cycle in vegetated areas included both NO_x-limited and transitional regimes, indicating the importance of NO_x controls to protect ecosystems. The O₃ response to limiting precursors shown here is of importance for optimizing control strategies and is illustrated by emission changes during the 2020 COVID-19 outbreak.

Response of cross-correlations between high PM2.5 and O3 with increasing time scales to the COVID-19: different trends in BTH and PRD

The air pollution in China currently is characterized by high fine particulate matter (PM_2.5) and ozone (O₃) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both PM_2.5 and O₃ are above the National Ambient Air Quality Standards (NAAQS)) pose a greater threat to public health and environment. In 2020, the outbreak of COVID-19 provided a special time window to further understand the cross-correlation between PM_2.5 and O₃. Based on this background, a novel detrended cross-correlation analysis (DCCA) based on maximum time series of variable time scales (VM-DCCA) method is established in this paper to compare the cross-correlation between high PM_2.5 and O₃ in Beijing-Tianjin-Heibei (BTH) and Pearl River Delta (PRD). At first, the results show that PM_2.5 decreased while O₃ increased in most cities due to the effect of COVID-19, and the increase in O₃ is more significant in PRD than in BTH. Secondly, through DCCA, the results show that the PM_2.5-O₃ DCCA exponents α decrease by an average of 4.40% and 2.35% in BTH and PRD respectively during COVID-19 period compared with non-COVID-19 period. Further, through VM-DCCA, the results show that the PM_2.5-O₃ VM-DCCA exponents [Formula: see text] in PRD weaken rapidly with the increase of time scales, with decline range of about 23.53% and 22.90% during the non-COVID-19 period and COVID-19 period respectively at 28-h time scale. BTH is completely different. Without significant tendency, its [Formula: see text] is always higher than that in PRD at different time scales. Finally, we explain the above results with the self-organized criticality (SOC) theory. The impact of meteorological conditions and atmospheric oxidation capacity (AOC) variation during the COVID-19 period on SOC state are further discussed. The results show that the characteristics of cross-correlation between high PM_2.5 and O₃ are the manifestation of the SOC theory of atmospheric system. Relevant conclusions are important for the establishment of regionally targeted PM_2.5-O₃ DHP coordinated control strategies.

Fractal analysis of impact of PM2.5 on surface O3 sensitivity regime based on field observations

Properties of PM_2.5 that can change aerosol chemistry and photolysis rates have great impacts on O₃ sensitivity regime, further affecting the production rate of surface O₃. However, responses of O₃ sensitivity regime to changes in PM_2.5 levels are difficult to be accurately determined, due to the complexity and nonlinearity of atmospheric chemistry. Here, based on long-term time series (2016-2020) of air quality variables in north and south Taiwan, fractal analysis along with Pearson correlation analysis are used to directly reveal the impacts of PM_2.5 on O₃ sensitivity regime in real atmosphere, by capturing the nonlinear dynamic relations among air pollutants. Great regional and seasonal difference in impacts of PM_2.5 on O₃ sensitivity regime may be ascribed to meteorological factors, PM_2.5 components and levels of SO₂, NO, NO₂, etc. For north Taiwan, increased PM_2.5 level can enhance the sensitivity of O₃ formation to VOC in spring and summer, whereas the opposite effect can be observed in winter. But for south Taiwan, the influence of PM_2.5 on O₃ sensitivity regime is not statistically significant, excluding spring. Furthermore, feasibility and availability of fractal analysis is tested by simulations with Empirical Kinetics Modeling Approach (EKMA). The results demonstrate the capability of fractal analysis to identify the impacts of PM_2.5 on O₃ sensitivity regime in real atmosphere, which can provide suggestions for PM_2.5-O₃ coordinated control strategies in regions suffering combined air pollution.

The Lack of HONO Measurement May Affect the Accurate Diagnosis of Ozone Production Sensitivity

Recently, deteriorating ozone (O₃) pollution in China brought the precise diagnosis of O₃ sensitive chemistry to the forefront. As a dominant precursor of OH radicals, atmospheric nitrous acid (HONO) plays an important role in O₃ production. However, its measurement unavailability in many regions especially for second- and third-tier cities may lead to the misjudgment of the O₃ sensitivity regime derived from observation-based models. Here, we systematically assess the potential impact of HONO on diagnosing the sensitivity of O₃ production using a 0-dimension box model based on a comprehensive summer urban field campaign. The results indicated that the default mode (only the NO + OH reaction is included) in the model could underestimate ∼87% of observed HONO levels, leading to an obvious decrease (∼19%) of net O₃ production in the morning, which was in line with the previous studies. The unconstrained HONO in the model was found to significantly push O₃ production toward the VOC-sensitive regime. Additionally, it is unrealistic to change NO _x but constrain HONO in the model due to the dependence of HONO formation on NO _x . Assuming that HONO varied proportionally with NO _x , a stronger NO _x -sensitive condition could be achieved. Therefore, effective reduction of NO _x should be given more attention together with VOC emission control for O₃ mitigation.

Multiple Impacts of Aerosols on O3 Production Are Largely Compensated: A Case Study Shenzhen, China

Tropospheric ozone (O₃) is a harmful gas compound to humans and vegetation, and it also serves as a climate change forcer. O₃ is formed in the reactions of nitrogen oxides and volatile organic compounds (VOCs) with light. In this study, an O₃ pollution episode encountered in Shenzhen, South China in 2018 was investigated to illustrate the influence of aerosols on local O₃ production. We used a box model with comprehensive heterogeneous mechanisms and empirical prediction of photolysis rates to reproduce the O₃ episode. Results demonstrate that the aerosol light extinction and NO₂ heterogeneous reactions showed comparable influence but opposite signs on the O₃ production. Hence, the influence of aerosols from different processes is largely counteracted. Sensitivity tests suggest that O₃ production increases with further reduction in aerosols in this study, while the continued NO_x reduction finally shifts O₃ production to an NO_x-limited regime with respect to traditional O₃-NO_x-VOC sensitivity. Our results shed light on the role of NO_x reduction on O₃ production and highlight further mitigation in NO_x not only limiting the production of O₃ but also helping to ease particulate nitrate, as a path for cocontrol of O₃ and fine particle pollution.

The regulatory role of PDE4B in the progression of inflammatory function study

Inflammation is a response of the body to external stimuli (eg. chemical irritants, bacteria, viruses, etc.), and when the stimuli are persistent, they tend to trigger chronic inflammation. The presence of chronic inflammation is an important component of the tumor microenvironment produced by a variety of inflammatory cells (eg. macrophages, neutrophils, leukocytes, etc.). The relationship between chronic inflammation and cancer development has been widely accepted, and chronic inflammation has been associated with the development of many cancers, including chronic bronchitis and lung cancer, cystitis inducing bladder cancer. Moreover, chronic colorectitis is more likely to develop into colorectal cancer. Therefore, the specific relationship and cellular mechanisms between inflammation and cancer are a hot topic of research. Recent studies have identified phosphodiesterase 4B (PDE4B), a member of the phosphodiesterase (PDEs) protein family, as a major cyclic AMP (cAMP) metabolizing enzyme in inflammatory cells, and the therapeutic role of PDE4B as chronic inflammation, cancer. In this review, we will present the tumors associated with chronic inflammation, and PDE4B potential clinical application.

Long-term trend in surface ozone in Houston-Galveston-Brazoria: Sectoral contributions based on changes in volatile organic compounds

This study investigated the long-term variations in ambient levels of surface ozone, volatile organic compounds (VOCs), and nitrogen oxides (NO_x) within the Houston-Galveston-Brazoria (HGB) region. Analysis of ozone levels revealed an overall reduction in the maximum daily 8-h average ozone (MDA8 O₃) from 2000 to 2019 (April-October) with an average rate of ∼ -0.48 ppb/yr across HGB. With a few exceptions, the MDA8 O₃ reduction rates were more pronounced for the monitoring sites closer to the Houston Ship Channel (HSC). Meanwhile, ambient levels of NO_x and most VOC species (across the three representative sites as Houston Bayland Park, Haden Road, and Lynchburg Ferry) decreased significantly within the same investigation period, reflecting the impact of emission reductions. The positive matrix factorization (PMF) model applied to the mentioned sites identified regional background ozone, petrochemical emissions, engine combustion, natural gas/fuel evaporation, and solvent/painting/rubber industries as the major sources of MDA8 O₃. The regional background ozone was the predominant source, accounting for 59-70% of MDA8 O₃ across the three sites. Regarding the local anthropogenic emissions, natural gas/fuel evaporation was the largest contributor (19.5 ± 6.1%) to MDA8 O₃ at Houston Bayland Park, whereas petrochemical facilities (10.9 ± 4.9%) and solvent/painting/rubber industries (18.1 ± 9.5%) were the largest factor at Haden Road and Lynchburg Ferry, respectively. Notable reductions were found in the contributions of petrochemical emissions, engine combustion, and natural gas/fuel evaporation to MDA8 O₃ within 2000-2019, but an increasing trend was revealed in the role of solvent/painting/rubber industries on MDA8 O₃ most probably due to the enhanced demand for their products. Results of this study corroborated the success of emission control policies in limiting ozone precursors and provided useful details for prioritizing emission reduction policies to further reduce ozone pollution in the HGB.

Nonlinear influence of winter meteorology and precursor on PM2.5 based on mathematical and numerical models: A COVID-19 and Winter Olympics case study

Air pollution during the COVID-19 epidemic in Beijing and its surrounding regions has received substantial attention. We collected observational data, including air pollutant concentrations and meteorological parameters, during January and February from 2018 to 2021. A statistical and a numerical model were applied to identify the formation of air pollution and the impact of emission reduction on air quality. Relative humidity, wind speed, SO₂, NO₂, and O₃ had nonlinear effects on the PM_2.5 concentration in Beijing, among which the effects of relative humidity, NO₂, and O₃ were prominent. During the 2020 epidemic period, high pollution concentrations were closely related to adverse meteorological conditions, with different parameters having different effects on the three pollution processes. In general, the unexpected reduction of anthropogenic emissions reduced the PM_2.5 concentration, but led to an increase in the O₃ concentration. Multi-scenario simulation results showed that anthropogenic emission reduction could reduce the average PM_2.5 concentration after the Chinese Spring Festival, but improvement during days with heavy pollution was limited. Considering that O₃ enhances the PM_2.5 levels, to achieve the collaborative improvement of PM_2.5 and O₃ concentrations, further research should explore the collaborative emission reduction scheme with VOCs and NO_x to achieve the collaborative improvement of PM_2.5 and O₃ concentrations. The conclusions of this study provide a basis for designing a plan that guarantees improved air quality for the 2022 Winter Olympics and other international major events in Beijing.

Regional collaboration to simultaneously mitigate PM2.5 and O3 pollution in Beijing-Tianjin-Hebei and the surrounding area: Multi-model synthesis from multiple data sources

Beijing-Tianjin-Hebei and the surrounding area (BTHSA) shows the poorest air quality in China, reflected in sub-standard PM_2.5 and increasingly pronounced O₃ pollution, stressing the urgency for regional cooperation and collaborative control of PM_2.5 and O₃. With the aim to explore the cooperative regions and response mechanisms of PM_2.5 and O₃ in BTHSA, this study applied multiple mathematical models and analytical indicators to multiple data sources, including applying self-organizing map (SOM), response surface model (RSM), random forest (RF), distributed lag nonlinear models (DLNMs), and meta-analysis, on ground observations of air quality and meteorology, ozone monitoring instrument (OMI) observations, and air pollutant emission inventory. The results revealed that BTHSA exhibited clear regional characteristics of air pollution and can be divided into four clusters for enhanced intercity cooperation. Over 2015-2020, anthropogenic factors played more important roles than meteorological ones on the alleviation of PM_2.5 and the deterioration of O₃. RSM based on observations and RF based on emissions both suggested that, in the near future, strengthened abatement of SO₂, PM_2.5 and VOC can be beneficial for controlling PM_2.5 and O₃ pollution, while intensive NOx reduction in PM_2.5-dominant months and mitigatory NOx reduction in O₃-dominant months should be formulated before certifying an obvious transition of O₃-NOx-VOC sensitivity. This study, with multi-model and multi-data fusion, can be expected to provide synthesized fact- and science-based guidance for the next-stage collaborative control of PM_2.5 and O₃ in BTHSA.