Enhancement Factors in Ozone Absorption Based on the Surface Renewal Model and its Application

Based on the Danckwerts surface renewal model, a simple explicit expression of the enhancement factor in ozone absorption with a first order ozone self-decomposition and parallel second order ozonation reactions has been derived. The results are compared with our previous work based on the film theory. The 2,4-dichlorophenol destruction rate by ozonation is predicted using the enhancement factor model in this paper.

Multi-stage ensemble-learning-based model fusion for surface ozone simulations: A focus on CMIP6 models

Accurately simulating the geographical distribution and temporal variability of global surface ozone has long been one of the principal components of chemistry-climate modelling.However,the simulation outcomes have been reported to vary significantly as a result of the complex mixture of uncertain factors that control the tropospheric ozone budget.Settling the cross-model discrepancies to achieve higher accuracy predictions of surface ozone is thus a task of priority,and methods that overcome structural biases in models going beyond naïve averaging of model simulations are urgently required.Building on the Coupled Model Intercomparison Project Phase 6(CMIP6),we have transplanted a conventional ensemble learning approach,and also constructed an innovative 2-stage enhanced space-time Bayesian neural network to fuse an ensemble of 57 simulations together with a prescribed ozone dataset,both of which have realised outstanding performances(R2>0.95,RMSE<2.12 ppbv).The conventional ensemble learning approach is computationally cheaper and results in higher overall performance,but at the expense of oceanic ozone being overestimated and the learning process being uninterpretable.The Bayesian approach performs better in spatial generalisation and enables perceivable interpretability,but induces heavier computational burdens.Both of these multi-stage machine learning-based approaches provide frameworks for improving the fidelity of composition-climate model outputs for uses in future impact studies.

Simulated Sensitivity of Ozone Generation to Precursors in Beijing during a High O_(3) Episode

This study uses the WRF-Chem model combined with the empirical kinetic modeling method(EKMA curve)to study the compound pollution event in Beijing that happened in 13−23 May 2017.Sensitivity tests are conducted to analyze ozone sensitivity to its precursors,and to develop emission reduction measures.The results suggest that the model can accurately simulate the compound pollution process of photochemistry and haze.When VOCs and NOx were reduced by the same proportion,the effect of O_(3)reduction at peak time was more obvious,and the effect during daytime was more significant than at night.The degree of change in ozone was peak time>daytime average.When reducing or increasing the ratio of precursors by 25%at the same time,the effect of reducing 25%VOCs on the average ozone concentration reduction was most significant.The degree of change in ozone decreased with increasing altitude,the location of the ozone maximum change shifted westward,and its range narrowed.As the altitude increases,the VOCs-limited zone decreases,VOCs sensitivity decreases,NOx sensitivity increases.The controlled area changed from near-surface VOCs-limited to high-altitude NOx-limited.Upon examining the EKMA curve,we have found that suburban and urban are sensitive to VOCs.The sensitivity tests indicate that when VOCs in suburban are reduced about 60%,the O_(3)-1h concentration could reach the standard,and when VOCs of the urban decreased by about 50%,the O_(3)-1h concentration could reach the standard.Thus,these findings could provide references for the control of compound air pollution in Beijing.

Analysis of Tropospheric Ozone by Artificial Neural Network Approach in Beijing

Higher concentration of tropospheric ozone in atmosphere reveals its adverse effects on human health, plants, and on environment. So, there is a need for atmospheric pollutants analysis and their concentration variation, which is a key factor for air quality management in urban areas. The Beijing Olympic center site was used as area of study and five recorded meteorological parameters temperature, dew point, wind speed, pressure, and relative humidity were employed as inputs imputes. Nitrogen Dioxide (NO2) and hour of day are also considered as input parameters for modeling of tropospheric ozone concentrations. Several deterministic methods are available for local air quality forecasting and prediction. But, in this study, multilayer perceptron (MLP) and generalized regression neural model (GRNM) were considered for prediction of ozone ground level concentration. The root mean squared errors (RMSE) and mean absolute error (MAE) value for MLP model were lower, which confirms its fitness for forecasting purpose. Regression coefficient for MLP in this study was calculated 0.91 and for GRNM model provides 0.76 value. The dew point and relative humidity were the most dominant input imputes found by model, which results in higher concentration of tropospheric ozone.

Anthropogenic Source Contributions to Ozone Formation in the Greater Houston Area

The Houston-Galveston-Brazoria (HGB) area of Texas has historically experienced severe air pollution events with high concentrations of ozone (O3) during the summer season. This study evaluates the contribution of different anthropogenic sources to ozone formation in the HGB area. The Emission Processing System (EPS3) is used to process emission files in four different scenarios (Base case as including All emission sources (BC), All sources— Area sources (AMA), All sources—Point sources (AMP), and All sources— Mobile sources (AMM). These files are used as input in photochemical modeling with the Comprehensive Air Quality Model with Extensions (CAMx) to simulate ozone formation. The data is analyzed for daily maximum ozone concentrations and contribution of source categories at three air quality monitoring locations (La Porte Sylvan beach-C556, Houston Texas avenue-C411, and Texas city in Galveston-C683) for a study period of June 1-June 30, 2012. The contribution of the point sources to ozone formation is dominated at all three locations, followed by mobile sources and area sources on high ozone days. The relative contributions of point sources are 27.51% ± 3.53%, 21.45% ± 7.36%, and 30.30% ± 9.36%;and mobile sources are 18.27% ± 2.22%, 20.60% ± 6.89%, and 18.61% ± 7.43%;and area sources were 4.2% ± 1.65%, 5.21% ± 1.59%, and 3.72% ± 1.52% at C556, C411, and C683, respectively. These results demonstrate the importance of regulatory focus on controlling point and mobile source emissions for NAAQS attainment in the study region.

Enhancement of the polynomial functions response surface model for real-time analyzing ozone sensitivity

Quantification of the nonlinearities between ambient ozone(O3)and the emissions of nitrogen oxides(NOx)and volatile organic compound(VOC)is a prerequisite for an effective O3 control strategy.An Enhanced polynomial functions Response Surface Model(Epf-RSM)with the capability to analyze O3-NOx-VOC sensitivities in real time was developed by integrating the hill-climbing adaptive method into the optimized Extended Response Surface Model(ERSM)system.The Epf-RSM could single out the best suited polynomial function for each grid cell to quantify the responses of O3 concentrations to precursor emission changes.Several comparisons between Epf-RSM and pf-ERSM(polynomial functions based ERSM)were performed using out-of-sample validation,together with comparisons of the spatial distribution and the Empirical Kinetic Modeling Approach diagrams.The comparison results showed that Epf-RSM effectively addressed the drawbacks of pf-ERSM with respect to overfitting in the margin areas and high biases in the transition areas.The O3 concentrations predicted by Epf-RSM agreed well with Community Multi-scale Air Quality simulation results.The case study results in the Pearl River Delta and the north-western area of the Shandong province indicated that the O3 formations in the central areas of both the regions were more sensitive to anthropogenic VOC in January,April,and October,while more NOx-sensitive in July.

A REGIONAL MODEL STUDY OF THE VARIATIONS AND DISTRIBUTIONS OF OZONE AND ITS PRECURSORS ON EASTERN ASIA AND WEST PACIFIC OCEAN REGIONS

A simulated study of mechanism for variations and distributions of ozone and its precursors was made by using the three-dimensional regional Eulerian model.The results showed that the ozone production was controlled by NO,but there is a complicated nonlinear relation between them.The photochemical reactions controlled by solar radiation are the determinative factors affecting the variations of the surface ozone and its precursors.The relations of ozone and CO, PAN were studied.We compared the simulated and observed results during the PEM-WEST A in order to better under- stand the photochemical processes of ozone and its precursors.

Surface ozone scenario and air quality in the north-central part of India

Tropospheric pollutants including surface ozone（O3）, nitrogen dioxide（NO2）, carbon monoxide（CO） and meteorological parameters were measured at a traffic junction（78°2′ E and 27°11′ N） in Agra, India from January 2012 to December 2012. Temporal analysis of pollutants suggests that annual average mixing ratios of tropospheric pollutants were： O3— 22.97 ± 23.36 ppbV,NO2— 19.84 ± 16.71 ppb V and CO — 0.91 ± 0.86 ppm V, with seasonal variations of O3 having maximum mixing ratio during summer season（32.41 ± 19.31 ppbV）, whereas lowest was found in post-monsoon season（8.74 ± 3.8 ppbV）. O3 precursors： NO2 and CO, showed inverse relationship with O3. Seasonal variation and high O3 episodes during summer are associated with meteorological parameters such as high solar radiation, atmospheric temperature and transboundary transport. The interdependence of these variables showed a link between the daytime mixing ratios of O3 with the nighttime level of NO2. The mixing ratios of CO and NO2 showed tight correlations, which confirms the influence of vehicular emissions combined with other anthropogenic activities due to office/working hours, shallowing, and widening of boundary layer. FLEXTRA backward trajectories for the O3 episode days clearly indicate the transport from the NW and W to S/SE and SW direction at Agra in different seasons.

Ozone episodes during and after the 2018 Chinese National Day holidays in Guangzhou:Implications for the control of precursor VOCs

The impact of reducing industrial emissions of volatile organic compounds(VOCs)on ozone(O_(3))pollution is of wide concern particularly in highly industrialized megacities.In this study,O_(3),nitrogen oxides(NOx)and VOCs were measured at an urban site in the Pearl River Delta region during the 2018 Chinese National Day Holidays and two after-holiday periods(one with ozone pollution and another without).O_(3)pollution occurred throughout the 7-day holidays even industrial emissions of VOCswere passively reduced due to temporary factory shutdowns,and the toluene to benzene ratios dropped from∼10 during non-holidays to∼5 during the holidays.Box model(AtChem2-MCM)simulations with the input of observation data revealed that O_(3)formation was all VOC-limited,and alkenes had the highest relative incremental reactivity(RIR)during the holiday and non-holiday O_(3)episodes while aromatics had the highest RIR during the non-pollution period.Box model also demonstrated that even aromatics decreased proportionally to levels with near-zero contributions of industrial aromatic solvents,O_(3)concentrations would only decrease by less than 20%during the holiday and non-holiday O_(3)episodes and ozone pollution in the periods could not be eliminated.The results imply that controlling emissions of industrial aromatic solvents might be not enough to eliminate O_(3)pollution in the region,and more attention should be paid to anthropogenic reactive alkenes.Isoprene and formaldehyde were among the top 3 species by RIRs in all the three pollution and non-pollution periods,suggesting substantial contribution to O_(3)formation from biogenic VOCs.

A NUMERICAL STUDY OF THE VARIATIONS AND DISTRIBUTIONS OF TROPOSPHERIC OZONE AND ITS PRECURSORS OVER CHINA

By means of a three-dimensional meteorological model(MM5)and a chemical model,the distributions of tropospheric ozone and its precursors over China have been simulated in summer and winter time,16—18 August 1994 and 7—9 January 1995.The distribution of ozone over the Tibetan Plateau in summer time is deeply discussed.The simulated results indicate that the distributions of surface ozone and NO_x are in good agreement with observed results,and human activities and photochemical reactions are the main factors controlling the surface ozone and NO_x concentrations.In addition,higher ozone concentrations are coincided with the air convergence, and the lower concentrations are related to the air divergence.In summer,over the Tibetan Plateau the strong flow convergence results in higher ozone concentrations in the lower troposphere:and the strong flow divergence results in lower ozone concentrations in the upper troposphere.In winter time ozone concentrations show Iarge-scale characteristics controlled by westerly flow,and in the jet area they are lower than those outside the jet.

广州市2022年臭氧污染特征与成因分析

选取2022年O_(3)及其前体物观测数据、气象观测数据和ERA5再分析数据,结合基于观测的模型(OBM)和后向轨迹模型,分析了2022年广州市O_(3)污染特征,识别了O_(3)生成控制区及关键敏感型物种,并从O_(3)前体物排放、气象条件和区域传输3个方面开展了O_(3)污染成因分析.结果表明:广州市O_(3)生成以VOCs控制和NO_(x)-VOCs协同控制为主,现阶段VOCs和NO_(x)减排比例应不低于1:1;O_(3)生成对含氧VOCs最为敏感,其次是植物源VOCs(BVOCs)、烯烃、芳香烃和烷烃;2022年广州市O_(3)前体物NO_(x)和VOCs浓度同比下降14.7%和30.4%,但副高强盛、台风外围环流影响频繁叠加强辐射、高温、低湿等不利气象条件和区域传输抵消了广州市本地前体物减排的成效,造成O_(3)浓度上升,其中典型O_(3)污染过程(2022年9月16~22日)气流轨迹由西北、西南方向气团转变为东和东南方向气团,易受到来自周边城市区域传输影响.建议下一步持续推动NO_(x)减排,促进O_(3)对NO_(x)敏感性向正敏感性的转变,同时积极构建区域联防联控机制,降低区域传输贡献.

Exploring drivers of the aggravated surface O_(3) over North China Plain in summer of 2015–2019: Aerosols, precursors, and meteorology

Continuous aggravated surface O_(3) over North China Plain(NCP)has attracted widely public concern.Herein,we evaluated the effects of changes in aerosols,precursor emissions,and meteorology on O_(3) in summer(June)of 2015–2019 over NCP via 8 scenarios with WRF-Chem model.The simulated mean MDA8 O_(3) in urban areas of 13 major cities in NCP increased by 17.1%∼34.8%,which matched well with the observations(10.8%∼33.1%).Meanwhile,the model could faithfully reproduce the changes in aerosol loads,precursors,and meteorological conditions.A relatively-even O_(3) increase(+1.2%∼+3.9%for 24-h O_(3) and+1.0%∼+3.8%for MDA8 O_(3))was induced by PM_(2.5) dropping,which was consistent with the geographic distribution of regional PM_(2.5) reduction.Meanwhile,the NO_(2) reduction coupled with a nearconstant VOCs led to the elevated VOCs/NOx ratios,and then caused O_(3) rising in the areas under VOCs-limited regimes.Therein,the pronounced increases occurred in Handan,Xingtai,Shijiazhuang,Tangshan,and Langfang(+10.7%∼+13.6%for 24-h O_(3) and+10.2%∼+12.2%forMDA8 O_(3));while the increases in other citieswere 5.7%∼10.5%for 24-h O_(3) and 4.9%∼9.2%for MDA8 O_(3).Besides,the meteorological fluctuations brought about the more noticeable O_(3) increases in northern parts(+12.5%∼+13.5%for 24-h O_(3) and+11.2%∼+12.4%for MDA8 O_(3))than those in southern and central parts(+3.2%∼+9.3%for 24-h O_(3) and+3.7%∼+8.8%for MDA8 O_(3)).The sum of the impacts of the three drivers reached 16.7%∼21.9%,which were comparable to the changes of the observed O_(3).Therefore,exploring reasonable emissionsreduction strategies is essential for the ozone pollution mitigation over this region.

光化学臭氧日变化特征与其前体物关系的探讨

应用大气光化学模式研究了日最大臭氧体积分数及其出现时刻与其前体物NMHC、NOx体积分数及NMHC/NOx比值的关系。结果表明,影响日最大臭氧体积分数(φO3m ax)脊线位置(EKMA图,Empirical K inetic Modeling Approach)的关键因子是NMHC成份组成比例;日臭氧体积分数达到最大值需要的时间(τO3m ax)与NMHC/NOx比值及NMHC成份组成比例有关,与NMHC、NOx体积分数关系不大。此外,利用该结果解释了近20 a北京日最大臭氧体积分数出现时刻具有不断提前的变化趋势的原因。

北京市城近郊区光化学烟雾模拟研究

利用EKMA(Empirical Kinetic Modeling Approach)-经验动力学模拟方法及其内置的CB-IV化学反应机理对2000年夏季北京市近郊区光化学污染进行研究,得到了前体物VOC、NOx与O3之间的非线性关系,即EKMA曲线。模拟过程中对前体物VOC、NOx和CO的逐时排放进行两种假定,排放1:假定逐时排放量为全天排放的24 h平均值;排放2:假定来自流动源的排放量与机动车流量线性相关,其他源的排放仍遵循排放1的假定。同时,对混合层以上的污染物浓度进行了6种情况的敏感性检验。结果表明,混合层以上的污染物浓度变化对O3模拟值影响不大,当混合层以上污染物浓度设置为它们在300 m处初始浓度的10%以下时,O3最大小时浓度模拟值与实测值的偏差都较小,O3模拟值与实测值吻合较好的点均落在EKMA脊线的左侧或者脊线上,说明O3模拟值与前体物VOC逐时排放的变化密切相关。敏感性实验表明VOC排放量减半引起O3模拟值降低16%左右,而NOx排放量减半只引起O3模拟值下降8%,说明影响北京地区光化学烟雾产生的主要前体物是VOC。

临安秋季近地层臭氧的形成及其前体物特征

应用浙江临安1999年秋季观测数据,分析了臭氧及其前体物特征与气象条件的关系。结果表明,该地区臭氧前体物丰富,在合适的天气条件、充足的日照下可以生成高浓度的臭氧;CO、NOx*等一次污染物浓度与大尺度大气扩散稀释能力有关;观测期间临安CO浓度很高;NMHCs以芳香烃含量最高,烷烃、烯烃、炔烃次之,生物排放的烃最少。以观测为基础的光化学模式计算表明,临安光化学臭氧生成率比损失率大一个数量级,中午净臭氧生成率最大可达14.8×10-9h-1。

北京秋季地面O_3的一维模式模拟研究

用一维光化学模式，基本模拟出静稳天气条件下2001年9月9日北京几个主要大气污染物种：O3、NO、NO2、CO以及SO2的日变化特点，并解释了影响O3及NO、NO2、CO和SO2日变化的控制因子作用。初步分析认为，地面O3对非甲烷碳氢化合物（NMHC）的变化很敏感。NMHC的增加或减少，将会造成O3的明显改变。造成9月9日夜间20：00～23：00一次污染物NO、CO和SO2浓度急剧升高的原因是由于夜间大气层结稳定情况下，大气的垂直扩散减弱，污染物在底层积累造成的。由于实际大气中，影响O3生成和损耗的机制很复杂，同时大气的平流输送是影响O3及其他污染物分布的重要因素，用一维模式虽然能够揭示出影响O3变化的几个因子的作用，但要深入分析O3产生和消耗机制，还需要用三维模式。

氧气沿面放电臭氧合成机理

提出了一种氧气沿面放电过程中臭氧合成的“双区模型”,即氧分子离解区和与之分离的臭氧形成区． 臭氧的产生率由离解区氧原子的产生效率和形成区氧原子转化为臭氧的效率决定．沿面放电中臭氧的产生率低 电场时随电场升高而增大,高电场时随电场增大而减小．在氧气的击穿电场附近和低温条件下可以获得较高的臭 氧合成效率．

臭氧数值预报模型综述

光化学大气质量模型在研究臭氧(O_3)污染以及O_3预报方面具有核心作用,是O_3污染防治决策者的有力工具。文章结合目前中国及国际区域尺度光化学大气质量预报模型的研究与应用,重点论述与O_3有关的大气化学过程在数值预报模型中的数学表达和计算方法,阐述大气物理与大气化学过程在主流大气质量数值预报模型中的实现方法及其优势和缺陷,介绍用于数值预报模型的大气物理过程和湍流参数化方案的最新进展。就当前O_3数值模拟的主要输入资料进行讨论,强调那些易被忽视但又显著影响模型预报能力和效果的诸多因素以及模型效果评估的重要性。结合O_3与复合型大气污染的关系,强调区域大气质量数值预报模型的发展趋势与方向以及在大气环境管理方面的意义和作用。

夹卷对郊外大气边界层内臭氧影响的数值模拟研究

夹卷是大气边界层与自由大气进行能量和物质交换的重要途径,对边界层动力结构及边界层内温度、水汽和各种污染物浓度有重要影响。利用化学蛳地表蛳大气蛳土壤(CLASS)模式定量评估了夹卷过程对远郊地区大气边界层内臭氧(O3)浓度的影响并与大气化学反应贡献进行了对比,结合地面O3、NOx及边界层高度、位温和比湿等观测资料和再分析资料对CLASS模拟结果进行了定量评估。结果表明:CLASS模式能较为真实地模拟夹卷和大气光化学反应对远郊地区大气边界层臭氧浓度的影响,且当自由大气层内臭氧浓度达到一定值时,两者对边界层内臭氧峰值影响相当。数值试验结果进一步揭示,夹卷对控制氮氧化物(NOX)和可挥发性有机物(VOCS)排放源控制效果有重要影响,且当夹卷区内O3跳跃值增大到一定时,可完全抵消源排放减排控制的效果。本研究旨在表明,为有效控制近地层臭氧浓度,在制定人为污染源减排措施时必须考虑自由大气层臭氧的夹卷贡献。

基于梯度提升算法的近地面臭氧浓度估算比较

提出了一种基于梯度提升树优化的近地面O_(3)浓度时空分布估算模型.基于O_(3)地面观测站点数据、高分辨率大气成分卫星数据(TROPOMI、AIRS)、ERA5气象再分析资料、以及地表覆盖和地形数据,本文研究了京津冀地区近地面O_(3)与对流层O_(3)及其前体物、气象因素、以及下垫面资料之间的相关关系,对比分析了不同梯度提升树算法模型(GBDT、XGBoost、LightGBM)的估算精度.结果表明,3种模型整体上均可对近地面O_(3)进行精确估算,GBDT、XGBoost、LightGBM的决定系数R^(2)分别为0.9489、0.9547、0.9495,均方根误差RMSE分别为13.85,13.26,13.76μg/m^(3),XGBoost模型的精度相对最高;通过采用过滤法、相关性分析法以及递归特征消除法筛选特征,对XGBoost估算模型进行了优化,在保证模型精度前提下,降低了特征复杂度,优化后模型估算精度可达到R^(2)=0.9549,估算速率提升了约17%,为区域尺度O_(3)浓度时空分布建模与估算提供了一个精细而高效的方法模型.