Urban Ozone Research Articles

Deciphering decadal urban ozone trends from historical records since 1980

Abstract Ozone pollution is a major environmental threat to human health. Timely assessment of ozone trends is crucial for informing environmental policy. Here we show that for the most recent decade (2013–2022) in the Northern Hemisphere, warm-season (April-September) mean daily 8-h average maximum (MDA8) ozone increases much faster in urban regions with top ozone levels (mainly in North China Plain, 1.2 ± 1.3 ppbv year−1) than that in other low-ozone regions (0.2 ± 0.9 ppbv year−1). These trends widen the ozone differences across urban regions, and increase extreme pollution levels and health threats from a global perspective. Comparison of historical trends in different urban regions reveals that, ozone increases in China during 2013–2022 differ in magnitude and mechanisms from historical periods in other regions since 1980. This reflects a unique chemical environment characterized by exceptionally high nitrogen oxides and aerosol concentrations, where reducing ozone precursor emissions leads to substantial ozone increase. Ozone increase in China has slowed down in 2018–2022 compared to 2013–2017, driven by ongoing emission reductions but with ozone-favorable weather conditions. Historical ozone evolution in Japan and South Korea indicates that ozone increases should be suppressed with continuous emission reduction. Increasing temperature and associated wildfires have also reversed ozone decreases in the US and Europe with anthropogenic ozone control slowing down in recent decades.

Can Environmental Protection Tax Decrease Urban Ozone Pollution? A Quasi-Natural Experiment Based on Cities in China

Can Environmental Protection Tax Decrease Urban Ozone Pollution? A Quasi-Natural Experiment Based on Cities in China

The impact of multi-decadal changes in VOC speciation on urban ozone chemistry: a case study in Birmingham, United Kingdom

Abstract. Anthropogenic non-methane volatile organic compounds (VOCs) in the United Kingdom have been substantially reduced since 1990, which is, in part, attributed to controls on evaporative and vehicle tailpipe emissions. Over time, other sources with a different speciation (for example, alcohols from solvent use and industry processes) have grown in both relative importance and, in some cases, in absolute terms. The impact of this change in speciation and the resulting photochemical reactivities of VOCs are evaluated using a photochemical box model constrained by observational data during a summertime ozone event (Birmingham, UK) and apportionment of sources based on the UK National Atmospheric Emission Inventory (NAEI) data over the period 1990–2019. Despite road transport sources representing only 3.3 % of UK VOC emissions in 2019, road transport continued being the sector with the largest influence on the local O3 production rate (P(O3)). Under case study conditions, the 96 % reduction in road transport VOC emissions that has been achieved between 1990 and 2019 has likely reduced daytime P(O3) by ∼ 1.67 ppbv h−1. Further abatement of fuel fugitive emissions was modeled to have had less impact on P(O3) reduction than abatement of VOCs from industrial processes and solvent use. The long-term trend of increased emissions of ethanol and methanol has somewhat weakened the benefits of reducing road transport emissions, increasing P(O3) by ∼ 0.19 ppbv h−1 in the case study. Abatement of VOC emissions from multiple sources has been a notable technical and policy success in the UK, but some future benefits (from an ozone perspective) of the phase-out of internal combustion engine passenger cars may be offset if domestic and commercial solvent use of VOCs continue to increase.

Diagnosing ozone–NOx–VOC–aerosol sensitivity and uncovering causes of urban–nonurban discrepancies in Shandong, China, using transformer-based estimations

Abstract. Narrowing surface ozone disparities between urban and nonurban areas escalate health risks in densely populated urban zones. A comprehensive understanding of the impact of ozone photochemistry on this transition remains constrained by current knowledge of aerosol effects and the availability of surface monitoring. Here we reconstructed spatiotemporal gapless air quality concentrations using a novel transformer deep learning (DL) framework capable of perceiving spatiotemporal dynamics to analyze ozone urban–nonurban differences. Subsequently, the photochemical effect on these discrepancies was analyzed by elucidating shifts in ozone regimes inferred from an interpretable machine learning method. The evaluations of the model exhibited an average out-of-sample cross-validation coefficient of determination of 0.96, 0.92, and 0.95 for ozone, nitrogen dioxide, and fine particulate matter (PM2.5), respectively. The ozone sensitivity in nonurban areas, dominated by a nitrogen-oxide-limited (NOx-limited) regime, was observed to shift towards increased sensitivity to volatile organic compounds (VOCs) when extended to urban areas. A third “aerosol-inhibited” regime was identified in the Jiaodong Peninsula, where the uptake of hydroperoxyl radicals onto aerosols suppressed ozone production under low NOx levels during summertime. The reduction of PM2.5 could increase the sensitivity of ozone to VOCs, necessitating more stringent VOC emission abatement for urban ozone mitigation. In 2020, urban ozone levels in Shandong surpassed those in nonurban areas, primarily due to a more pronounced decrease in the latter resulting from stronger aerosol suppression effects and less reduction in PM2.5. This case study demonstrates the critical need for advanced spatially resolved models and interpretable analysis in tackling ozone pollution challenges.

Urban ozone variability using automated machine learning: inference from different feature importance schemes.

Tropospheric ozone is an air pollutant at the ground level and a greenhouse gas which significantly contributes to the global warming. Strong anthropogenic emissions in and around urban environments enhance surface ozone pollution impacting the human health and vegetation adversely. However, observations are often scarce and the factors driving ozone variability remain uncertain in the developing regions of the world. In this regard, here, we conducted machine learning (ML) simulations of ozone variability and comprehensively examined the governing factors over a major urban environment (Ahmedabad) in western India. Ozone precursors (NO2, NO, CO, C5H8 and CH2O) from the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis and meteorological parameters from the ERA5 (European Centre for Medium-Range Weather Forecast's (ECMWF) fifth-generation reanalysis) were included as features in the ML models. Automated ML (AutoML) fitted the deep learning model optimally and simulated the daily ozone with root mean square error (RMSE) of ~2 ppbv reproducing 84-88% of variability. The model performance achieved here is comparable to widely used ML models (RF-Random Forest and XGBoost-eXtreme Gradient Boosting). Explainability of the models is discussed through different schemes of feature importance, including SAGE (Shapley Additive Global importancE) and permutation importance. The leading features are found to be different from different feature importance schemes. We show that urban ozone could be simulated well (RMSE = 2.5 ppbv and R2 = 0.78) by considering first four leading features, from different schemes, which are consistent with ozone photochemistry. Our study underscores the need to conduct science-informed analysis of feature importance from multiple schemes to infer the roles of input variables in ozone variability. AutoML-based studies, exploiting potentials of long-term observations, can strongly complement the conventional chemistry-transport modelling and can also help in accurate simulation and forecast of urban ozone.

Machine learning analysis of socioeconomic drivers in urban ozone pollution in Chinese cities.

The escalation of ground-level ozone (O3) pollution presents a significant challenge to the sustainable growth of Chinese cities. This study utilizes advanced machine learning algorithms to investigate the intricate interplay between urban socioeconomic growth and O3 levels. Surpassing traditional environmental chemistry, it assesses the effectiveness of these algorithms in interpreting socioeconomic and environmental data, while elucidating urban development's environmental impacts from a novel socioeconomic perspective. Key findings indicate that factors such as urban infrastructure, industrial activities, and demographic dynamics significantly influence O3 pollution. The study highlights the particular sensitivity of urban public transportation and population density, each exerting a unique and substantial effect on O3 levels. Additionally, the research identifies nuanced interactions among these factors, indicating a complex web of influences on urban O3 pollution. These interactions suggest that the impact of individual socioeconomic elements on O3 pollution is interdependent, being either amplified or mitigated by other factors. The study emphasizes the crucial need to integrate socioeconomic variables into urban O3 pollution strategies, advocating for policies tailored to each city's distinct characteristics, informed by the detailed analysis provided by machine learning. This approach is essential for developing effective and nuanced urban pollution management strategies.

Urban 2D and 3D morphology and the pattern of ozone pollution: a 68-city study in China

ContextAir pollution significantly impacts urban sustainable development and public health. Urban ozone pollution (UOP) is currently one of the most challenging tasks for urban air pollution control, and is possibly linked to urban morphology. However, the effect of urban two-dimensional (2D) (coverage or density, etc.) and three-dimensional (3D) (density + height, etc.) morphology on the UOP concentration remains unclear.ObjectivesThe objective of this study was to explore the influence of urban morphology on UOP concentration and provide useful information to control urban air pollutants.MethodsFirst, based on building height and remotely sensed UOP data from 68 Chinese cities, the general spatial pattern of urban 3D morphology and UOP was detected across different climate zones in China. Then, this study used variance decomposition to investigate the contribution of 2D and 3D urban morphology to UOP in China.ResultsThe study showed that China's urban morphology was dominated by Medium Rise & Medium Density (MRMD). Large cities had higher UOP levels in summer, especially for the urban morphology with Low Rise & High Density (LRHD). Further, UOP concentrations were substantially higher in the southern temperate zone than in other climatic zones. Anthropogenic factors (rather than natural factors) were always the dominant factors influencing UOP across different seasons; specifically, urban 2D and 3D morphology can explain 40% of UOP variation. The effects of urban 3D and 2D morphologies on UOP concentrations varied seasonally. Urban 2D morphology dominated in spring, whereas 3D morphology dominated in winter.ConclusionsOur study elucidates the effect of urban morphology on UOP and provides insights for sustainable urban development.

Implications of the extremely hot summer of 2022 on urban ozone control in China

Frequent occurrences of extreme heat are causing severe ozone pollution over China. This study examined the driving factors of urban ozone pollution in China during the extremely hot summer of 2022 and the impact of emission control strategies using surface measurements and the GEOS-Chem model. The results show that ozone pollution was extremely severe in summer 2022, with a significant rebound by 12–15 ppbv in the North China Plain (NCP), Yangtze River Delta (YRD), and Sichuan basin (SCB), compared to 2021. Especially over the NCP, the MDA8 (maximum daily 8-hourly average) ozone exceeded 160 ppbv, and the number of ozone exceedances was over 42 days. Based on an IPR (integrated process rate) analysis, the authors found that the net chemical production was the dominant factor contributing to the strong ozone increase in summer 2022. For example, in June over the NCP, the net chemical production resulted in an increase by 3.08 Gg d−1 (∼270%) in ozone mass change. Sensitivity simulations showed that both NOx (nitrogen oxides) and VOC (volatile organic compound) reductions were important over the NCP, and NOx reductions were more important than VOCs over southern China. To keep the ozone of 2022 at the same level as 2021, a joint reduction of NOx and VOCs by at least 50%–60% would have been required. This study highlights the urgency to develop effective ozone management since extreme heat will become more frequent.摘要本文利用地面观测和数值模式研究了2022年夏季极端高温下我国城市臭氧污染的控制策略. 研究表明, 2022年夏季臭氧污染极为严重, 相较于2021年有显著的反弹, 其中华北, 长三角和四川盆地的月均臭氧上升12–15 ppbv. 模式过程分析结果表明净化学生产是高温时造成臭氧浓度升高的主导因素. 模式多组敏感性试验表明, 华北地区需要NOx和VOC协同控制, 南方城市需要侧重对NOx排放管控, 并且需要对NOx和VOC协同减排至少50%–60% 才会使2022年夏季臭氧污染水平与2021年一致. 在极端高温愈发频繁的形势下, 本研究强调未来亟需研究更为有效的臭氧调控策略.

Does Downscaling Improve the Performance of Urban Ozone Modeling?

AbstractIncreasing the model resolution is expected to be one way for improving air quality forecasts in urban areas. In this study, we evaluate the model performance in a large city at various resolutions to examine the best resolution for air pollution simulations. The comparison with measurements at a station near the traffic emissions shows the advantage of using high resolutions for capturing the extreme values. The statistical evaluation indicates that the highest model resolution (33 m) provides the best results for NOX concentration distributions near the traffic roads, while the improvement for roadside O3 with decreasing grid spacing stops at a certain point. The best model performance for the areas with a distance to the pollution sources is with the resolution of 100–300 m, at which the transport errors are equivalent to the emission biases.

Data‐ and Model‐Based Urban O3 Responses to NOx Changes in China and the United States

AbstractUrban air pollution continues to pose a significant health threat, despite regulations to control emissions. Here we present a comparative analysis of urban ozone (O3) responses to nitrogen oxide (NOx) changes in China and the United States (US) over 2015–2020 by integrating various data‐ and model‐based methods. The data‐based deep learning (DL) model exhibited good performance in simulating urban air quality: the correlation coefficients (R) of O3 daily variabilities with respect to independent O3 observations are 0.88 and 0.79 over N. China, 0.87 and 0.90 over S. China, and 0.87 and 0.49 over E. United States by the DL and GEOS‐Chem chemical transport models, respectively. Furthermore, the data‐based methods suggest volatile organic compound (VOC)‐limited regimes in urban areas over northern inland China and transitional regimes over eastern US urban areas; in contrast, GEOS‐Chem model suggests strong NOx‐limited regimes. Sensitivity analysis indicates that the inconsistent O3 responses are partially caused by the inaccurate representation of O3 precursor concentrations at the locations of urban air quality stations in the simulations, while the data‐based methods are driven by the variabilities in local O3 precursor concentrations and meteorological conditions. The O3 responses to NOx changes reported here provide a better understanding of urban O3 pollution; for example, reductions in NOx emissions are suggested to have resulted in an increase in surface O3 by approximately 7 ppb in the Sichuan Basin in 2014–2020.

The synergistic effect of high temperature and ozone on the number of deaths from circulatory system diseases in Shijiazhuang, China.

Urban ozone pollution in China is becoming increasingly serious. Climate warming, high temperatures, and ozone pollution all have significant impacts on human health. However, the synergistic effects of high temperatures and ozone pollution in summer on human health are rarely studied. China is at a critical stage of environmental pollution control. Assessing the health impact of high temperatures and ozone exposure on the number of deaths from circulatory diseases is of great significance for formulating ozone-related prevention and control policies. This study uses daily data on deaths from circulatory system diseases in Shijiazhuang from June to August during the summer of 2013-2016, as well as concurrent meteorological data and concentration of O3 and PM2.5 pollution data. The generalized additive model (GAM) with Poisson distribution, smooth curve threshold effect, and saturation effect method is used to control for confounding effects. The study evaluates the impact of short-term exposure to temperature and ozone on deaths from circulatory system diseases and the synergistic effect after controlling for confounding factors. The results show that the impact of temperature and ozone on deaths from circulatory system diseases in Shijiazhuang is nonlinear, with a temperature threshold of 27.5°C and an ozone concentration threshold of 100 μg/m3. With an increase of temperature by 1°C, the risk of deaths for total population, men and women are 6.8%, 4.6% and 9.3%, respectively. The increase in temperature and ozone concentration has a greater impact on women; in men, the increase has a lag effect of 2 to 3 days, but the lag did not affect women. In conclusion, high temperatures and high ozone concentration have synergistic enhancement effects on circulatory system diseases. Prevention and scientific management strategies of circulatory system diseases in high temperatures and high ozone environments should be strengthened.

Evaluation of key factors influencing urban ozone pollution in the Pearl River Delta and its atmospheric implications

In recent years, the concentration of ozone (O3) in typical urban agglomerations in China has generally increased. This study carried out a three-year observation in the active photochemical reaction period (August–November) in Shenzhen, a megacity in the Pearl River Delta (PRD). Principal coordinate analysis (PCoA) was first applied to identify the major factors influencing daily maximum 8-h average O3 (MDA8-O3) concentration. Then, the MDA8-O3 concentration fitting equation was established by a stepwise multiple linear regression (MLR). In result, sensitivity test based on the fitting equation showed that temperature (+35.8%), photolysis rate of j[NO2] (+11.1%), relative humidity (−10.4%) and photolysis rate of j[O1D] (−9.5%) had more effect on the concentration of MDA8-O3 with per factor perturbation (25% change), while increments of △CO (6.9%) and NO2 (2.7%) had less effect. The insignificant effect produced by NO2 is consistent with Shenzhen being in a transition area for O3-VOCs-NOx sensitivity. Moreover, it is found in this study that PM2.5 likely promotes O3 formation by scattering light to influence j[NO2] and j[O1D] differently, which provides a new explanation for the coupled formation of PM2.5 and O3 in the PRD region.

Narrowing Differences in Urban and Nonurban Surface Ozone in the Northern Hemisphere Over 1990–2020

Surface ozone air pollution is unequally distributed in space and varies over urban and surrounding nonurban areas. Traditionally, urban ozone levels tend to be lower than their nonurban counterparts, resulting from discrepancies in emissions and nonlinearity in photochemistry. However, how the differences in urban vs nonurban ozone evolve over the past decades is uncertain. Here, we construct 6361 pairs of urban and nonurban ozone measurement sites based on available surface monitoring networks to analyze the long-term changes of their ozone differences. We show that urban vs nonurban ozone differences have narrowed substantially in North America, Europe, South Korea, and Japan over the summers of 1990–2020. The hemispheric mean urban vs nonurban ozone differences have decreased by 90% from −5.0 ppbv in the 1990s to −0.5 ppbv in the 2010s. We estimate that the anthropogenic emission reduction of nitrogen oxides is the dominant driver of the narrowing trends. It has suppressed the urban ozone titration and led to closer ozone formation regimes over urban and nonurban areas.

The influence of vegetation drought stress on formaldehyde and ozone distributions over a central European city

To estimate the effect of vegetation stress and changes in biogenic volatile organic compound (BVOC) emissions on urban ozone (O3) levels we perform a systematic, observation-based analysis of the relationship between formaldehyde (HCHO) mixing ratios, meteorological parameters, measurement-based drought indicators and O3 over the central European city of Vienna, Austria. In addition, numerical models SURface EXternalisée (SURFEX), Model of Emissions of Gases and Aerosols from Nature (MEGAN) Vers.2.1 and 3 and MOdèle de Chimie A Grande Echelle (MOCAGE) are combined to estimate the soil moisture, the spatial distribution and drought response of isoprene emissions, and the resulting distribution of HCHO in the atmosphere. To analyse the effect of drought during spring and summer we contrast observations during dry and reference years. Our results show that the observed HCHO can be explained using the simulated isoprene emissions as well as observed and simulated vegetation drought responses. HCHO mixing ratios differ strongly between dry and reference seasons. Spring-time precipitation deficits facilitate reduced HCHO mixing ratios due to delayed and weakened plant growth. In consequence also O3 burdens are lowered due to reduced BVOC precursor emissions. These reductions occur despite radiation levels being higher than during the reference year, illustrating the strong potential of spring-time BVOC emissions to modulate urban O3 burdens. Conversely, during summer elevated O3 levels occur during local drought conditions. These are driven by advected isoprene originating from nearby forest areas, which are not affected by drought. Our results regarding elevated summer-time O3 burdens under vegetation heat and drought stress are in good agreement with previous work.

Gas‐phase kinetics, POCPs, and an investigation of the contributions of VOCs to urban ozone production in the UK

AbstractAmbient concentrations of 22 volatile organic compounds (VOCs) measured at London Marylebone Road (LMR), an urban traffic site, and London Eltham (LE), an urban background site, were analyzed over a period of 23 years (1997–2019) to assess the impact of pollution control strategies. A significant decrease in ambient concentration is seen for the majority of VOCs analyzed with total VOC burden decreasing by 76% and 59% for LMR and LE, respectively, across the period studied. This is likely as a result of legislative controls. This analysis was extended to consider the dominant contribution of VOCs to ozone formation at the sites utilizing photochemical ozone creation potential (POCP) values. Similarly, the overall reactivity of the VOC burden at the sites has resulted in a significant decrease of 11% and 7% per year in ozone formation potential (OFP) for LMR and LE, respectively. At LMR, the declines in OFP for VOCs associated with road traffic emissions are all in good agreement at 11%–13% decrease per year. Reasonable agreement is also seen at LE with a decrease of 6%–11% per year in OFP of the VOCs related to traffic sources. VOCs related to non‐traffic sources, namely ethane and propane from natural gas leakage, did not see a significant decline over the study period at either site. The variation and composition of the overall VOC burden was compared across three decadal time periods (1997–2000, 2001–2010, 2011–2019) and saw an increase in significance of these pollutants at both sites. At LMR, ethane and propane moved from the fifth and eleventh largest contributors to total VOC burden in 1997–2000 to the first and second largest contributors in 2011–2019. At LE, a similar trend is seen with ethane and propane becoming the first and second largest contributors in the most recent time period, up from second and eighth at the beginning of the dataset. The similarity between these sites suggests such pollutants are not sufficiently controlled under current legislation. The increase in significance of ethane and propane was mirrored in their contribution to ozone generation potential at both sites but ethene continues to dominate in contribution to OFP. At LMR, ethene dominates by a factor of 4 and 5 compared with ethane and propane, respectively, however, at LE, ethene dominates to a lesser extent over ethane and propane at factors of 1 and 3, respectively. Alkanes are typically considered to be less important in the context of OFP due to their low reactivity in comparison to other VOCs. Analysis presented herein demonstrates the negative impact of ignoring such emissions as their influence begins to grow such that alkanes now represent 3 of the 5 highest contributors to tropospheric ozone formation at both sites (in order of contribution at LMR: ethene > propene > n‐butane > ethane > propane; and LE: ethene > ethane > n‐butane > propane > propene). The importance of high‐quality gas‐phase kinetic studies to determine the impact of VOCs in ozone production is clear and the usefulness of metrics such as POCPs is demonstrated.

Weekend-weekday variations, sources, and secondary transformation potential of volatile organic compounds in urban Zhengzhou, China

Periodical changes of human activities cause weekend-weekday differences of volatile organic compounds (VOCs) and nitrogen oxides (NO + NO2 = NOx) emissions, which induce urban ozone (O3) pollution and secondary organic aerosol (SOA) in fine particulate (with aerodynamic diameters ≤2.5 μm; PM2.5). However, influences of weekend-weekday differences in primary emissions on the production of secondary pollutants remain unknown. The TROPOspheric Monitoring Instrument and surface observations are carried to simultaneously monitor VOCs, NO2, O3, and PM2.5 concentrations in urban Zhengzhou, China during the weekend and the weekday. Reductions in anthropogenic activities result in atmospheric VOCs and NO2 reductions during the weekend. The ratios of formaldehyde columns to NO2 columns during the weekend afternoon and the weekday afternoon (0.53 and 0.39, respectively) are less than 2.30, indicating the O3 formation under the VOC-limited regime. Lower total VOCs (TVOCs) mixing ratios but higher ratios of TVOCs mixing ratios to NO2 mixing ratios during the weekend afternoon perform faster photochemical O3 production. In contrast, higher TVOCs mixing ratios are responsible for higher SOA formation during the weekday. Based on the positive matrix factorization model and VOCs reactivities, solvent usage, vehicle exhaust, and industrial sources are majorly responsible for SOA (80.1%) and O3 (79.9%) formation potential. To reduce O3 concentrations during the weekend and SOA concentrations during the weekday collaboratively, solvent, vehicle, and industrial activities should be transformed from weekday to weekend.

Urban Surface Ozone Concentration in Mainland China during 2015-2020: Spatial Clustering and Temporal Dynamics.

Urban ozone (O3) pollution in the atmosphere has become increasingly prominent on a national scale in mainland China, although the atmospheric particulate matter pollution has been significantly reduced in recent years. The clustering and dynamic variation characteristics of the O3 concentrations in cities across the country, however, have not been accurately explored at relevant spatiotemporal scales. In this study, a standard deviational ellipse analysis and multiscale geographically weighted regression models were applied to explore the migration process and influencing factors of O3 pollution based on measured data from urban monitoring sites in mainland China. The results suggested that the urban O3 concentration in mainland China reached its peak in 2018, and the annual O3 concentration reached 157 ± 27 μg/m3 from 2015 to 2020. On the scale of the whole Chinese mainland, the distribution of O3 exhibited spatial dependence and aggregation. On the regional scale, the areas of high O3 concentrations were mainly concentrated in Beijing-Tianjin-Hebei, Shandong, Jiangsu, Henan, and other regions. In addition, the standard deviation ellipse of the urban O3 concentration covered the entire eastern part of mainland China. Overall, the geographic center of ozone pollution has a tendency to move to the south with the time variation. The interaction between sunshine hours and other factors (precipitation, NO2, DEM, SO2, PM2.5) significantly affected the variation of urban O3 concentration. In Southwest China, Northwest China, and Central China, the suppression effect of vegetation on local O3 was more obvious than that in other regions. Therefore, this study clarified for the first time the migration path of the gravity center of the urban O3 pollution and identified the key areas for the prevention and control of O3 pollution in mainland China.

Characteristics of Ozone Pollution and High-impact Meteorological Factors in Urban Cities: A Case of Suzhou

The problem of urban ozone (O3) pollution has become prominent in recent years. However, the meteorological factors associated with O3 pollution remain unclear. Analyzing the characteristics of O3 pollution in Suzhou, as a typical urban city, and exploring the high-impact meteorological factors with O3 pollution are crucial to the prevention and control of air pollution in this region. This study used correlation analysis and machine learning methods to analyze the variation in O3 concentration and the relationship between meteorological driving factors in Suzhou based on the O3 concentration data provided by Suzhou Environmental Monitoring Center and the contemporaneous meteorological observation data in Suzhou from April to September in 2015 to 2020. The results showed that: ① O3 pollution exceeding the standard rate was more than 20% in ozone seasons during the past six years; further, pollution days of O3 and the number of pollution days of O3 as the primary pollutant increased yearly. Evidently, the problem of O3 pollution has become increasingly prominent. ② The diurnal variations in O3 were unimodal with the valley point at 07:00 and the highest peak between 15:00 and 16:00. Similar trends were found in diurnal variations of both air temperature and solar radiation, but the daily highest peak came earlier than that of O3. The results also showed an apparent weekend effect of O3 concentration in 2017 and 2019 and a significant correlation between O3 concentration and solar irradiance during the week. In addition, the monthly variation in O3 concentration and pollution exceeding the standard rate was bimodal. ③The occurrence of ozone pollution was affected by various meteorological conditions. The maximum number of days appeared when daily sunshine hours lasted longer than 7 hours, with a daily maximum air temperature around 30℃, solar irradiance ranging from 350 to 440 kW·m-2, and relative humidity ranging from 50% to 75%, at which time the intensity of pollution was the strongest. When the wind speed of easterly wind was less than 1.5 m·s-1, or the wind speed of southwest wind was less than 3.5 m·s-1, moderate ozone pollution occurred. ④ An optimal prediction model of O3 concentration was established based on machine learning, which had good predictive ability for O3 concentration in April, May, July, and September but did not perform well when O3 concentration exceeded 200 μg·m-3. Meanwhile, it was found that solar radiation had the most obvious effect on O3 concentration, followed by relative humidity, whereas the temperature and wind were less important than the former two factors.

Influence of Wildfire on Urban Ozone: An Observationally Constrained Box Modeling Study at a Site in the Colorado Front Range.

Increasing trends in biomass burning emissions significantly impact air quality in North America. Enhanced mixing ratios of ozone (O3) in urban areas during smoke-impacted periods occur through transport of O3 produced within the smoke or through mixing of pyrogenic volatile organic compounds (PVOCs) with urban nitrogen oxides (NOx = NO + NO2) to enhance local O3 production. Here, we analyze a set of detailed chemical measurements, including carbon monoxide (CO), NOx, and speciated volatile organic compounds (VOCs), to evaluate the effects of smoke transported from relatively local and long-range fires on O3 measured at a site in Boulder, Colorado, during summer 2020. Relative to the smoke-free period, CO, background O3, OH reactivity, and total VOCs increased during both the local and long-range smoke periods, but NOx mixing ratios remained approximately constant. These observations are consistent with transport of PVOCs (comprised primarily of oxygenates) but not NOx with the smoke and with the influence of O3 produced within the smoke upwind of the urban area. Box-model calculations show that local O3 production during all three periods was in the NOx-sensitive regime. Consequently, this locally produced O3 was similar in all three periods and was relatively insensitive to the increase in PVOCs. However, calculated NOx sensitivities show that PVOCs substantially increase O3 production in the transition and NOx-saturated (VOC-sensitive) regimes. These results suggest that (1) O3 produced during smoke transport is the main driver for O3 increases in NOx-sensitive urban areas and (2) smoke may cause an additional increase in local O3 production in NOx-saturated (VOC-sensitive) urban areas. Additional detailed VOC and NOx measurements in smoke impacted urban areas are necessary to broadly quantify the effects of wildfire smoke on urban O3 and develop effective mitigation strategies.

城市植物挥发性有机化合物排放与臭氧相互作用及其机制

PDF HTML阅读 XML下载 导出引用 引用提醒 城市植物挥发性有机化合物排放与臭氧相互作用及其机制 DOI: 10.5846/stxb202202240431 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 长株潭城乡融合发展的生态环境效应与耦合机制项目（U21A2010） The interactions and mechanisms between biogenic volatile organic compounds emissions and ozone concentrations in urban areas: A review Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:近地面臭氧（O3）已成为继PM2.5后影响我国空气质量的一种重要二次污染物。随着氮氧化物浓度的持续下降和气候变暖的加剧，城市O3的形成对挥发性有机化合物的浓度更加敏感。近年来城市绿色空间显著增长，植物源挥发性有机化合物（BVOCs）排放和浓度逐年增加。针对BVOCs与近地面O3之间复杂的交互作用，从植物BVOCs的特性与作用出发，综述了不同因素尤其是O3浓度增加对树木生理状态及BVOCs排放速率的影响，定量分析了已有研究中O3对不同植物异戊二烯和单萜烯排放速率的影响，以及BVOCs对O3形成的贡献，总结了BVOCs与O3相互作用研究领域存在的不足。未来亟需加强的研究包括：（1）城市树种BVOCs排放因子的实测，建立物种的排放速率数据库，优化模型参数，提升精细尺度BVOCs排放量估算模型精度；（2）多种环境因子，比如污染物浓度、温湿度等对城市植物BVOCs排放的交互作用和综合影响的研究；（3）植物BVOCs对O3形成贡献的定量研究，及其对植物抗污染能力的影响，为城市建设中的树种选择及减轻城市O3污染提供理论依据和借鉴。 Abstract:In China, surface ozone (O3) has become a major secondary pollutant as the fine particulate pollution problem was largely addressed. As nitrogen oxide concentrations continue to decline and climate warming intensifies, urban ozone formation becomes more sensitive to VOC emissions. With the continuous increase of urban green space in recent years, the emissions of Biogenic Volatile Organic Compounds (BVOCs) have also increased, and thus played an increased role in ozone formation. This paper presented a comprehensive review of the interactions and mechanisms between BVOCs emissions and ozone concentrations in urban areas. We first reviewed the current states and trends in the response of plant physiological state and BVOCs emission rate to environmental stress, especially the elevated O3 concentration, with a particular emphasis on previous studies that focused on the effects of O3 on isoprene and monoterpene emission rates of various plans. We then summarized the role of BVOCs plays in O3 formation. Based on the review of the existing studies, we found a few knowledge gaps and identified several priorities for future research:(1) studies on quantifying the BVOCs emission rate of different urban tree species to build a more comprehensive database for BVOCs emission rate that can be used to optimize the parameters of BVOCs emissions models, and thereby to improve the precision of the fine-scale BVOCs emission estimation; (2) Exploring the interaction and comprehensive influence of various environmental factors on BVOCs emissions from urban plants, such as pollutant concentration, temperature, and humidity; (3) Quantifying the contribution of plant BVOCs to O3 formation and its effect on plant resistance to air pollution, which aims to provide a theoretical basis and reference for the selection of tree species for urban greening and the reduction of urban O3 pollution. 参考文献 相似文献 引证文献