Comparing the Number of Ozone Exceedances in Different Seasons of the Year in Mexico City

Ozone air pollution is a serious problem in several cities of the world. Hence, to analyse the behaviour of this pollutant is a very important issue. One problem of interest is to study the behaviour of the inter-occurrences times between two ozone exceedances, i.e. between two days in which the pollutant’s measurement surpasses a given threshold. Another interest resides in comparing the behaviour of ozone measurements in different seasons of the year. In this paper we use some Poisson models to analyse this problem. The time interval at which the ozone measurements were taken is split into subintervals corresponding roughly to the seasons of the year. We consider three parametric forms for the mean of the Poisson model, and consequently for the mean of the inter-occurrences times. In each model, the parameters describing its mean are estimated using Bayesian inference via Markov chain Monte Carlo methods. The models are applied to the ozone measurements provided by the Mexico City monitoring network. Theoretical results suggest that an increase has occurred in the mean inter-exceedances times and this is corroborated by the observed data. Differences between the behaviour of the pollutant during different seasons of the year are also detected as well as similarities in the same season in different years. Besides estimating the mean of the Poisson models, inference for the possible presence and location of change-points indicating change of parameters of the model is also performed.     

Minimax Statistical Models for Air Pollution Time Series. Application to Ozone Time Series Data Measured in Bordeaux

This paper deals with the application of l(infinity) (or minimax) optimization techniques to statistical modelling of high frequency air pollution data. The method was applied to ground-level ozone time-series data measured in Bordeaux over 4 years from 1998 to 2001. The aim of model building was to develop predictive models in order to provide forecasts of the maximal daily ground-level ozone concentration. Experimental results from this case study indicate that such techniques could be more appropriate than the commonly used l2 setting if only good estimation of high levels is of interest. When the free parameters are fitted by means of l(infinity) optimization techniques, the forecasting errors are more evenly distributed amongst the data points, resulting in a better estimation of high values. The paper compares the quality of forecasts produced by both a linear and a nonlinear model, using l2 and l(infinity) parameter optimization.     

Mixed Integer Linear Programming Models for Selecting Ground-Level Ozone Control Strategies

The traditional strategy for ground-level ozone control is to apply emission reductions across the board throughout certain time periods and locations. In this paper, we study various mixed integer linear programming (MILP) models that seek to select targeted control strategies for the Dallas Fort-Worth (DFW) region to reduce emissions, in order to achieve the State Implementation Plan (SIP) requirements with minimum cost. Statistics and optimization methods are used to determine a potential set of cost-effective control strategies for reducing ozone. These targeted control strategies are specified for different types of emission sources in various time periods and locations. Three MILP models, a static model, a sequential model, and a dynamic model, are studied in this research. These different MILP models allow decision makers to study how the targeted control strategies change under different circumstances. Meanwhile, two types of auxiliary variables are considered as supplemental control strategies in the optimization if the current set of control strategies is unable to reduce ozone to comply with the 8-h ozone standard. Results from the different models can provide decision makers with information concerning how the effectiveness of the control strategies varies with daily emission patterns and meteorology.     

中国和美国地面臭氧污染对比分析

利用中国和美国地面臭氧(O₃)监测数据,从国家、区域、城市、站点多个层面对两国O₃污染的时间变化特征和空间分布特征进行了分析。结果表明:从全年角度,中国O₃污染集中在4—9月,2018年延长至3—10月;美国集中在4—8月。1980年以来,美国O₃浓度呈下降趋势;中国O₃浓度在2015—2018年呈上升趋势,与同时期美国O₃平均浓度水平相当,但O₃极值处于美国20世纪80年代污染水平,且中国站点年均O₃超标天数(22～36 d)约为美国站点(2～3 d)的9.2～12.9倍。中国O₃浓度高值区主要分布在京津冀、长三角、珠三角和四川盆地等地区,美国集中在加利福尼亚州(California)。京津冀和长三角地区2017—2018年O₃平均浓度水平高于加利福尼亚州,北京、上海和广州3个城市2015—2018年O₃平均浓度水平低于同时期的圣贝纳蒂诺(San...     

佛山市近地面臭氧污染特征及相关气象因子分析

利用2014年佛山市8个国控大气自动监测点位的O_3监测数据,分析了佛山市的O_3污染特征,结果表明,2014年O_3日最大8 h平均值的第90百分位数为167μg/m~3,O_3为首要污染物的超标天数为43d,占比46.7%;ρ(O_3)区域变化不大;ρ(O_3)月变化呈现"三峰型",全年高ρ(O_3)集中在6—10月份,其中7月份出现全年最高峰值;ρ(O_3)日变化呈单峰型分布,夜间浓度较低且变化平缓,14:00—16:00左右达到峰值,并存在一定的"周末效应",但并不明显;ρ(O_3)与气温呈显著正相关,与湿度、气压、雨量呈显著负相关,与风向、风速的相关性相对较弱;总体上看,高温、低湿、微风、偏南风、低压、无雨的天气条件下高ρ(O_3)更容易出现。     

海口市臭氧污染及气象条件特征

近年来,臭氧已成为许多城市环境空气的主要污染物之一。笔者分析了2020年海口市5个不同方位代表性监测站点逐小时空气质量监测数据及对应站点的气象要素监测数据。研究结果表明:海口市2020年环境空气污染程度为三级以上的天数有11d,其首要污染物均为臭氧。臭氧浓度高值时段主要出现在10-12月。浓度最大值主要出现在每日14:00-17:00,最小值出现在每日05:00-08:00。气象要素日均值与臭氧浓度相关性大小依次为最高温度＞平均温度＞相对湿度＞降水量＞日照时数＞风速。台风外围下沉气流和东北气流的共同影响是导致海口市臭氧浓度超标的主要因素,下沉气流更有利于低层大气中臭氧的堆积,同时在东北气流影响下,上游区域污染物的传输也会导致海口市臭氧浓度增加。     

贵阳市臭氧浓度变化及与气象因子的关联性

运用2013—2016年贵阳市环境空气自动监测站臭氧(O_3)的监测数据以及气象观测资料,分析该地区近地面O_3浓度的时空变化特征及与气象因子的关联性。结果表明,近年来贵阳市近地面O_3小时浓度均值有逐年升高趋势,增速为1. 1～5. 0μg/(m~3·a)。O_3浓度昼间变化呈明显单峰形分布,08:00左右出现最低值,15:00—16:00达到最大峰值,浓度高值主要分布在12:00—18:00。日照时数每增加1 h,则近地面O_3日最大8 h平均浓度增加8μg/m~3左右,日照时数大于8 h,则近地面O_3日最大8 h平均浓度超过100μg/m~3; O_3小时浓度与温度呈正相关(r=0. 724,α=0. 01),与相对湿度呈负相关(r=-0. 531,α=0. 01)。当日照时数大于8 h、温度超过25℃、相对湿度小于60%时,贵阳市近地面O_3容易出现高浓度值。     

青藏高原典型城市拉萨市近地面臭氧污染特征

拉萨市作为青藏高原典型城市,环境空气质量相对较好,但臭氧污染近年来有所凸显。对拉萨市臭氧的现状与污染特征进行分析基础上,探讨臭氧污染的影响因素。结果表明:拉萨市臭氧污染表现出"来得早,去得快"的特征,与内地城市相比,拉萨市臭氧质量浓度在3月即可达到全年平均值(2015年为105μg/m~3),而9月以后将低于全年平均值,并在春末夏初达到峰值;由于青藏高原海拔高,紫外线强,相对内陆地区臭氧均值偏高,2015年拉萨市臭氧年均值比北京市和成都市分别高出7.7%、29.0%,其小时浓度变化呈中午高、早晚低的特征;拉萨市臭氧的浓度变化受空气湿度、日照时间和日均气温的影响;生物质燃料的跨界传输可能也对青藏高原地区臭氧的来源产生一定影响。     

长沙地区O3污染潜势广义可加模型的季节分异性

基于长沙市2016—2019年臭氧（O₃）浓度的逐时监测资料以及该时段同时次的气象观测数据,首先利用相关性分析和方差膨胀因子相结合的方法排除了相对湿度、太阳辐射、气温、风速、气压之间存在多重共线性问题,进而构建了春、夏、秋、冬四季O₃日最大8 h滑动平均质量浓度（O₃-8 h）与上述气象因子的广义可加模型（GAMs）,分析了O₃污染潜势GAMs模型的季节分异特征。结果表明：①春、夏、秋、冬四季O₃与相对湿度、太阳辐射、气温、风速、气压各变量之间多呈现出非线性关系（自由度大于1）。②春、夏、秋、冬四季多变量GAMs模型方差解释率（IRV）分别为80.7%、60.2%、83.0%、81.4%,调整判定系数R²分别为0.795、0.564、0.819、0.795,即不同季节气象因子在GAMs模型中对O₃的解释能力存在显著差异,秋季最好,冬春季次之,夏季最差。③相对湿度、太阳辐射、气温是决定春、夏、秋、冬四季O₃浓度变化最重要的气象要素,但其重要性排序随季节有所变化,对应的太阳辐射的F统计值分别为140.841、36.606、14.16、46.377,相对湿度的F统计值分别为3.291、4.158、15.82、8.105,气温的F统计值分别为7.030、2.113、15.79、3.340。该结论揭示了气象因子对O₃演化影响的复杂性,并为后续O₃污染潜势的预报奠定了基础。     

Environmental Assessment of the Impact of Ozone to the Neuston of the Sea-Surface Microlayer of the Gulf of Mexico

Substantial amounts of NOx (146 000 t/y) and total hydrocarbons (294 000 t/y) are released to the marine atmosphere by the large number of oil and gas operations over Federal waters of the Gulf of Mexico (GOM). Under appropriate meteorological conditions these emissions react to form ozone (0–54 g/m3 over-water) which can affect the marine environment. Using a dry deposition model, this work examines the amount of ozone derived from oil and gas offshore operations and deposited in the sea surface of the Gulf of Mexico, and assesses its impact on the neuston of the sea-surface microlayer. Surface integrated estimates of ozone deposited from oil and gas operations over the sea surface ranges from 400 kg to 1800 kg which results in sea surface concentrations of 15 g/m3. This estimate and the actual toxic ozone levels suggest no acute, toxic impacts to the neuston. However, indirect effects may occur through changes to the pelagic foodwebs and organic carbon pathways. Another potential pathway for ozone impacting the environment is through the production of bromate. Based on the concentrations and time scales (11–139 days) only sublethal effects appear to occur, but uncertainties associated with this assessment need to be further studied. From an ecological perspective, the environmental impacts and risks of NOx and VOC discharges from offshore platforms need to be assessed for neuston and other components of the marine ecosystem.     

Nonlinear Growth Models for Modelling Time Series of Groundwater Nitrate Concentrations

In this paper, a novel approach of modelling time series of nitrate concentrations in drinking water by nonlinear growth functions is proposed. An almost constant increase in the average values of nitrate concentrations occurred at the Vinokov??ak wellfield in the county of Vara?din, Croatia, in the period between 1998 and 2013. Our hypothesis was that the time series would be well adjusted to the nonlinear growth function with asymptotic properties after smoothing performed by the moving average method. We used a general growth model which does not have asymptotic properties and the logistic, Gompertz and Richards functions which do have asymptotic properties. Last three growth functions were modified based on the knowledge of a constant presence of basic nitrate concentrations in the drinking water before growth. The fit of growth curves to experimental data was assessed using R ² and Aikake’s information criterion. The modified growth functions gave the best fit to the smoothed time series of nitrate concentrations with R ² ranging from 0.9960 to 0.9986.     

中欧环境空气臭氧评价对比与启示

欧盟臭氧(O₃)监测与评价起步相对较早。对比中国和欧盟O₃例行评价,欧盟在O₃标准限值、保护对象、评价指标、评价时间尺度、参评点位类型的设定和选取,以及O₃浓度与前体物排放量的关联性分析等方面,均对中国O₃评价具有一定的借鉴意义。以2017—2020年石家庄市8个国控站点O₃观测数据为分析案例,采用欧盟常用的日最大8 h滑动平均浓度(MDA8)第4高值,以及O₃暴露指标SOMO35和AOT40等3项评价指标,开展了尝试性评价应用和浓度对比。对照欧盟O₃评价指标应用经验,未来可考虑从兼顾两类功能区、丰富评价指标、扩展参评点位类型、纳入暴露影响评估、关联前体物排放变化等方面,进一步完善中国环境空气O₃评价方式,以更好地发挥其对空气质量精细化管理的数据支撑作用。     

Estimation of Ozone Trend in Central Greece, Based on Meteorologically Adjusted Time Series

Data referring to an approximately 8-year period (1999–2007) are analyzed in order to estimate the trend of the daily maximum hourly value of ozone concentration at the east coast of central Greece, where the summer background ozone concentration is high. A Kolmogorov–Zurbenko filter is applied to remove the short-term component from the raw time series of ozone and meteorological variables. Regression models are developed in order to produce meteorologically adjusted ozone time series, involving the noise-free temperature, relative humidity, and wind speed as independent variables. The analysis verifies that the meteorological adjustment provides better results on estimating ozone’s trend, which is found to be increasing (α?=?0.001) with an annual rate of 1.34?±?0.07?μg/m³. This trend could mainly be attributed to policy and changes in the emissions of ozone’s precursors. Additionally, the short-term component of ozone concentration is also meteorologically adjusted and its impact on the trend is examined. The analysis shows that its contribution is of minor importance when the ozone trend is adjusted by temperature, relative humidity, and wind speed. Moreover, the sea breeze circulation system that is frequently developed in the area influences the short-term and seasonal ozone variation, and therefore, it should be taken into account when producing meteorologically adjusted time series. The study’s conclusions could be exploited by environmental and agricultural authorities in order to develop their long-term strategies towards the air quality management.     

滁州市一次持续性臭氧污染过程气象与传输特征分析

2019年6月8日至17日,安徽省滁州市发生一次持续性臭氧(O₃)污染过程,O₃浓度值超过国家二级标准浓度限值3%~45%。基于滁州市老年大学监测站点空气质量数据、滁州市气象站及全球资料同化系统(GDAS)气象数据,运用HYSPLIT后向轨迹模型、潜在源贡献因子(PSCF)和浓度权重轨迹(CWT)分析方法,研究污染发生时段的气象和区域传输特征。结果表明:①在此次O₃污染过程中,日最高温度的变化范围为25.5~34.7 ℃,风速整体小于4 m/s,风向以偏东风为主,午后的相对湿度在40%左右。在该时段内,滁州市基本处于均压场的控制之中,且受到锋面气旋外围下沉气流的影响,大气层结稳定。②O₃污染发生期间,滁州市主要受东南方向气流的影响,但来自山东省、安徽省北部和江苏省北部的气流的影响也不容忽视。6月9日夜间至10日上午的O₃浓度异常高值,与9日下午的气压异常低值及9日夜间的大气边界层高度异常高值密切相关。上述气压及大气边界层高度异常值的出现使得上风向高浓度O₃被输送至滁州。③此次污染过程的潜在贡献源区主要分布于安徽省东南部、江苏省中西部和浙江省北部等地。上述区域的加权潜在源贡献因子(WPSCF)值大于0.4,加权浓度权重轨迹(WCWT)值超过了100 μg/m³。今后,滁州市在O₃污染防控工作中应加强与上述区域的联防联控。     

沈阳环境空气臭氧浓度及累积速率时序曲线模拟研究

为了解环境空气臭氧累积规律,利用2017年沈阳市环境空气臭氧浓度数据,统计分析臭氧累积速率,并利用回归方法拟合并优化臭氧浓度及其累积速率的时间序列模型,同时结合气温、风力、臭氧前体物等时序变化情况分析臭氧浓度的影响因素。研究发现:沈阳市臭氧月均浓度年变化、日均浓度年变化以及小时浓度日变化时序曲线均呈现单峰形态;年变化中,6月的臭氧浓度最大,4月臭氧累积速率达到最大值;日变化中,14:00臭氧浓度达到最大值,09:00—11:00臭氧累积速率最大,19:00—20:00臭氧迅速消减。温度、风速同臭氧浓度之间均有较好的正相关性。臭氧前体物二氧化氮、挥发性有机物与臭氧浓度之间均呈明显的负相关性。     

Spatial and temporal variations in inhalable CuZnPb aerosols within the Mexico City pollution plume

We report on the CuPbZn content of PM10 and PM2.5 samples collected from three sites (urban T0, suburban T1 and rural T2) during the Mexico City MILAGRO campaign of March 2006. Daytime city centre concentrations of summation operator CuZnPb(PM10) were much higher (T0 > 450 ng m(-3)) than at the suburban site (T1 < 200 ng m(-3)). Rural site (T2) summation operator CuZnPb(PM10) concentrations exceeded 50 ng m(-3) when influenced by the megacity plume but dropped to 10 ng m(-3) during clean northerly winds. Nocturnal metal concentrations more than doubled at T0, as pollutants became trapped in the nightly inversion layer, but decreased at the rural site. Transient spikes in concentrations of different metals, e.g. a "copper event" at T0 (CuPM10 281 ng m(-3)) and "zinc event" at T1 (ZnPM10 1481 ng m(-3)) on the night of March 7-8, demonstrate how industrial pollution sources produce localised chemical inhomogeneities in the city atmosphere. Most metal aerosols are <2.5 microm and SEM study demonstrates the dominance of Fe, Ti, Ba, Cu, Pb and Zn (and lesser Sn, Mo, Sb, W, Ni, V, As, Bi) in metalliferous particles that have shapes including spherical condensates, efflorescent CuZnClS particles, cindery Zn, and Cu wire. Metal aerosol concentrations do not change in concert with PM10 mass, which is more influenced by wind resuspension than industrial emissions. Metalliferous particles can induce cell damage, and PM composition is probably more important than PM mass, with respect to negative health effects, so that better monitoring and control of industrial emissions would likely produce significant improvements in air quality.     

Assessment of New Vehicles Emissions Certification Standards in the Metropolitan Area of Mexico City

Light duty gasoline vehicles account for most of CO hydrocarbons and NOx emissions at the Metropolitan Area of Mexico City (MAMC). In order to ameliorate air pollution from the beginning of 2001, Tier 1 emission standards became mandatory for all new model year sold in the country. Car manufacturers in Mexico do not guarantee the performance of their exhaust emissions systems for a given mileage. The purpose of this study was to assess whether the Tier 1 vehicles will stand the certification values for at least 162000 km with the regular fuel available at the MAMC. Mileage accumulation and deterioration show that certified carbon monoxide emissions will stand for the useful life of the vehicles but in the case of non-methane hydrocarbons will be shorter by 40%, and nitrogen oxides emissions above the standard will be reached at one third of the accumulated kilometers. The effect of gasoline sulfur content, on the current in use Tier 1 vehicles of the MAMC and the impact on the emissions inventory in year 2010 showed that 31000 extra tons of NOx could be added to the inventory caused by the failure of the vehicles to control this pollutant at the useful life of vehicles.     

欧盟臭氧污染监测现状及我国开展臭氧污染监测的建议

综述了欧盟臭氧前体物排放及地面臭氧污染监测的现状,分析了欧盟重视地面臭氧污染监测的原因及存在的主要问题.根据欧盟在地面臭氧污染监测方面的经验和做法,提出了加强我国地面臭氧污染监测的必要性和具体建议.     

2016—2020年西安市近地面臭氧污染变化趋势及分布特征

利用2016—2020年陕西省环境空气质量自动站的臭氧监测数据,分析西安市大气环境中臭氧污染的时间变化趋势及空间分布特征。从时间分布来看,西安市臭氧年均质量浓度呈先上升后下降的波动变化趋势,且浓度值略高于全国平均水平;臭氧月均浓度具有明显的季节变化特征,月超标天数和月均质量浓度均在6月达到峰值;臭氧质量浓度日变化规律在全年和四季完全一致,均呈单峰型,日内小时平均质量浓度超标最多时段集中在15:00—16:00;臭氧与NO₂、CO均呈“此消彼长”的负相关关系。从空间分布来看,西安市12个国控评价点位的O₃-8 h浓度分布变化大致分为单峰型和持续递减型,浓度主要集中在40～80μg/m³;国控点和省控点的臭氧浓度时间分布趋势一致,空间分布存在区域性差异;全市20个区县(开发区)的臭氧污染呈现南北中心城区高、东西远郊区低的空间分布特征。总之,西安市臭氧污染的时空分布主要受到气象条件、污染物排放和城市布局差异的综合性影响。     

Dependence of Ozone Biomonitoring on Meteorological Conditions of Different Sites in Catalonia (N.E. Spain)

Evaluation of visual symptoms of ozone damage was conducted in the network of bioindicator rural stations of Catalonia (NE Spain) every 14 days from May to October. Damage rates of ozone (and consequently, ozone biomonitoring capacity of bioindicators) were found to vary highly in time and space depending on the local environmental and meteorological conditions. Lower ozone damage to foliage was produced when meteorological conditions favour stomata resistance. Modulatory effects of meteorological conditions need to be considered in biomonitoring and when modeling plant ozone doses and damage.