Prediction of daily ground-level ozone concentration maxima over New Delhi

The pollution levels in New Delhi from industrial, residential, and transportation sources are continuously growing. As one of the major pollutants, ground-level ozone is responsible for various adverse effects on both humans and foliage. The present study aims to predict daily ground-level ozone concentration maxima over a site situated in New Delhi through neural networks (NN) and multiple-regression (MR) analysis. Although these methodologies are case and site specific, they are being developed and used widely. Therefore, to test these methodologies for New Delhi where no such study is available for ground-level ozone, six models have been developed based on NNs and MR using the same input data set. The changes in the performance capability of the two methods are sensitive to the selection of input parameters. The results are encouraging, and remarkable improvements in the performance of the models have been observed.     

Accuracy of bottled drinking water label content

The accurate predictions of ground ozone concentrations are required for proper management, control, and making public warning strategies. Due to the difficulties in handling phenomenological models that are based on complex chemical reactions of ozone production, neural network models gained popularity in the last decade. These models also have some limitations due to problems of overfitting, local minima, and tuning of network parameters. In this study, the predictions of daily maximum ozone concentrations are attempted using support vector machines (SVMs). The comparison between the accuracy of SVM and neural network predictions is performed to evaluate their performance. For this, the daily maximum ozone concentration data observed during 2002–2004 at a site in Delhi is utilized. The models are developed using the available meteorological parameters. The results indicated the promising performance of SVM over neural networks in predicting daily maximum ozone concentrations.     

Grey Box and Component Models to Forecast Ozone Episodes: A Comparison Study

For the purpose of short-term forecasting of high ozone concentration episodes stochastic models have been suggested and developed in the literature. The present paper compares the quality of forecasts produced by a grey box and a component time-series model. The summer ozone patterns for three European urban areas (two continental and one mediterranean) are processed. By means of forecast performance indices according to EC and WHO guidelines, the following features of the models could be found: The grey box model is highly adaptive and produces forecasts with low error variance that increases with the time horizon of forecast. The component model is more 'stiff' that results in a higher forecast-error variance and poorer adaption in detail. The forecast horizon, however, could be enlarged with this model. The accuracy of predicting threshold exceedance is similar for both models. This can be understood from the assumption of a cyclical time development of ozone that was made for both models.     

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。     

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.     

Surface ozone and meteorological condition in a single year at an urban site in central–eastern China

Surface ozone and some meteorological parameters were continuously measured from June 2003 to May 2004 at urban Jinan, China. The levels and variations of surface ozone were studied and the influences of meteorological parameters on ozone were analyzed. Annual and diurnal ozone variation patterns in Jinan both show a typical pattern for polluted urban areas. Daytime ozone concentrations in summer were the highest in the four seasons. However, during nighttime from 2100 to 0600 hours ozone concentrations in spring was higher than that in summer. Daily averaged ozone showed negative correlation with pressure and relative humidity and positive correlation with temperature, total solar radiation, sunshine duration and wind speed during the study period. Further studies show that, solar radiation is a primary influence factor for the daytime variations of ozone concentrations at this site; transport of pollutants by wind could enhance the pollution at this site; precipitation has a significant influence on decreasing surface ozone. A multi-day ozone episode from 16 to 21 June 2003 was observed at this site. Surface meteorological data analysis and backward trajectory computation show that the episode is associated with the influence of typhoon Soudelor, attributing to both local photochemical processes and transport of air pollutants from southeastern coastal region, especially Yangtze River Delta region.     

When speed matters: The importance of flight speed in an avian collision risk model

Renewable energy continues to grow globally, and the number of offshore wind farms is set to increase. Whilst wind energy developments provide energy security and reduced carbon budgets, they may impact bird populations through collision mortality, habitat modification and avoidance. To date, avian collision mortality has received the most attention and collision risk models have been developed to estimate the potential mortality caused by wind turbines. The utility of these models relies not only on their underlying assumptions but also on the data available to ensure the predictions are informative. Using a stochastic collision risk model (sCRM; based on the Band collision risk model) as an example, we explore the importance of bird flight speed and consider how the assumptions of the model influence the sensitivity to flight speed. Furthermore we explore the consequences of using site-specific GPS-derived flight speed rather than a standard generic value, with Lesser Black-backed Gulls Larus fuscus as an example, and consider how this generic value is currently used. We found that the model was most sensitive to the parameters of bird density, non-avoidance rate and percentage of birds at collision risk height, as well as bird flight speed. Using site-specific flight speed data derived from GPS tags rather than a standard value reduced the predicted number of collisions. We highlight that within the model, both the estimation of the probability of collision (PColl) and the flux of birds are sensitive to the bird flight speed; this sensitivity acts in opposite directions but the two do not necessarily balance out. Therefore, when the sCRM is used as generally done, there is little difference in collision estimates if airspeeds (bird flight speed relative to air through which it is moving) are used rather than groundspeeds (bird flight speed relative to ground). Estimates of seabird collision rates in relation to offshore wind farms are impacting future offshore wind development. By using site specific flight speed estimates and, accounting for different speeds in relation to wind direction, we demonstrate that cumulative collision estimates can be affected, highlighting the need for more representative flight speed data and where possible site-specific data.     

Forecasting Daily Maximum Ozone Concentrations in the Athens Basin

In the work ozone data from the Liossion monitoring station of the Athens/PERPA network are analysed. Data cover the months May to September for the period 1987–93. Four statistical models, three multiple regression and one ARIMA (0,1,2), for the prediction of the daily maximum 1-hour ozone concentrations are developed. All models together, with a persistence forecast, are evaluated and compared with the 1993's data, not used in the models development. Validation statistics were used to assess the relative accuracy of models. Analysis, concerning the models' ability to forecast real ozone episodes, was also carried out. Two of the three regression models provide the most accurate forecasts. The ARIMA model had the worst performance, even lower than the persistence one. The forecast skill of a bivariate wind speed and persistence based regression model for ozone episode days was found to be quite satisfactory, with a detection rate of 73% and 60% for O3 >180 g m-3 and O3 >200 g m-3, respectively.     

最优化集成方法在城市臭氧数值预报中的应用研究

基于多模式(NAQPMS、CMAQ、CAMx、WRF-Chem)空气质量数值预报业务系统的滚动预报结果,结合站点观测资料,评估了最优化集成方法在城市臭氧数值预报中的可行性和预报效果。一年的评估结果表明:当训练期为15 d时,最优化集成方法能够得到相对较好的结果。总体而言,最优化集成方法对城市臭氧浓度变化趋势和浓度水平的预报效果明显优于单个模式,且在大部分城市优于多模式的最优预报,其预报值和观测的相关系数提高0.11以上,均方根误差降低约10μg/m~3;该方法对城市臭氧污染等级的预报能力也明显优于单个模式,特别是轻、中度污染。此外,在模拟偏差较大的城市,最优化集成方法对预报效果的改进更为显著;在模拟偏差较小的城市,该方法仍可进一步提升预报效果。     

Ordinal time series model for forecasting air quality index for ozone in Southern California

Air quality index (AQI) for ozone is currently divided into six states depending on the level of public health concern. Generalized linear type modeling is a convenient and effective way to handle the AQI state, which can be characterized as non-stationary ordinal-valued time series. Various link functions which include cumulative logit, cumulative probit, and complimentary log-log are considered, and the partial maximum likelihood method is used for estimation. For a comparison purpose, the identity link, which yields a multiple regression model on the cumulative probabilities, is also considered. Random time-varying covariates include past AQI states, various meteorological processes, and periodic components. For model selection and comparison, the partial likelihood ratio tests, AIC and SIC are used. The proposed models are applied to 3 years of daily AQI ozone data from a station in San Bernardino County, CA. An independent year-long data from the same station are used to evaluate the performance of day-ahead forecasts of AQI state. The results show that the logit and probit models remove the non-stationarity in residuals, and both models successfully forecast day-ahead AQI states with almost 90 % of the chance.     

A study of ground-level ozone pollution, ozone precursors and subtropical meteorological conditions in central Taiwan

Hourly concentrations of ozone (O(3)), 55 volatile organic compounds (VOCs, ozone precursors) and nitrogen oxides (NOx) were measured at an upwind urban site, a downwind suburban site, and a rural site in central Taiwan, from January 2003 to December 2006. VOC and NOx mean concentrations showed a gradient from high to low across the urban (56 ppb and 34 ppb), suburban (38 ppb and 27 ppb) and rural sites (25 ppb and 21 ppb) but a reverse gradient in ozone across these sites (24, 27, and 29 ppb, respectively). Although there was about twice the difference in VOC concentrations between the urban and rural sites, nearly 65% ozone formation potential was contributed to by the same 9 VOCs. Seasonal patterns showed peak ozone levels in autumn and minima in summer at the urban site, but minima in winter at the downwind suburban and rural sites. Ozone precursor levels, on the other hand, were lowest in summer and highest in winter. The diurnal pattern showed that ozone levels peaked one hour later at the rural site than at the urban site. The ethylbenzene to m,p-xylene ratio, an indicator of the age of the air mass, increased from 0.4 at the urban site to 0.6 at the suburban site and 0.8 at the rural site during daily peak ozone times. This finding suggests the transport of ozone and precursors from upwind to downwind producing elevated ozone levels in the suburban and rural areas. Ozone episodes occurred mostly in days with a mean midday UV index of 6.5 (1 UV index=100 J m(-2)) and wind speed at 1.3 m s(-1) at all three sites.     

湖北臭氧分布特征及其管控措施

采用地面站点观测、卫星观测以及UWCM 0-D箱子模型模拟的方法研究湖北2013—2015年臭氧时空分布特征,并探讨其管控措施。从地面站点观测看出,时间分布上,这3年臭氧年平均浓度经历先下降后上升的过程,总体呈上升趋势,而二氧化氮年平均浓度则呈现持续下降的趋势;空间分布上,湖北各区域臭氧浓度分布不均匀,呈现东高西低的递减分布趋势。从卫星观测数据看出,2015年湖北的臭氧柱浓度高于2013、2014年同期。从空间分布来看,臭氧的柱浓度是从东北到西南、从省外到省内逐渐递减,因此推测,除了本地生成,湖北的臭氧有一部分是来源于省外传输。最大臭氧生成量法显示,烯烃(乙烯和丙烯)对湖北夏天臭氧生成量的贡献远大于其他挥发性有机化合物。箱子模型模拟的结果显示,湖北应该通过控制挥发性有机化合物的排放来降低臭氧生成速率,控制氮氧化物反而使臭氧生成速率提高。     

Establishment of a structural equation model for ground-level ozone: a case study at an urban roadside site

This study established a cause–effect relationship between ground-level ozone and latent variables employing partial least-squares analysis at an urban roadside site in four distinct seasons. Two multivariate analytic methods, factor analysis, and cluster analysis were adopted to cite and identify suitable latent variables from 14 observed variables (i.e., meteorological factors, wind and primary air pollutants) in 2008–2010. Analytical results showed that the first six components explained 80.3 % of the variance, and eigenvalues of the first four components were greater than 1. The effectiveness of this model was empirically confirmed with three indicators. Except for surface pressure, factor loadings of observed variables were 0.303–0.910 and reached statistical significance at the 5 % level. Composite reliabilities for latent variables were 0.672–0.812 and average variances were 0.404–0.547, except for latent variable “primary” in spring; thus, discriminant validity and convergent validity were marginally accepted. The developed model is suitable for the assessment of urban roadside surface ozone, considering interactions among meteorological factors, wind factors, and primary air pollutants in each season.     

Seasonal variation in the acute effects of ozone on premature mortality among elderly Japanese

We conducted a multicity time-series study using monitoring data to assess seasonal patterns of short-term ozone–mortality association among elderly aged 65 years and over in Japan. Daily exposure to ambient ozone was computed using hourly measurements of photochemical oxidants available at multiple monitoring stations in each city. Effects of ozone on daily all-cause non-accidental, cardiovascular, and respiratory mortality were estimated using distributed lag linear models, controlling for confounding by temporal, day of the week, temperature, and flu epidemics. City-level effect estimates were combined using inverse variance meta-analysis. In spring and autumn, a 10-ppbv increase of daily maximum 8-h average ozone concentration in the previous 3 days was associated with 0.69 % (95 % confidence interval (CI): 0.27–1.10), 1.07 % (0.34–1.82), and 1.77 % (0.78–2.77) increases in daily all-cause, cardiovascular, and respiratory mortality, respectively. Forward displacement of respiratory mortality was large during the cold season despite lower ozone concentration. Results were generally independent of fine particulate matter and nitrogen dioxide. Findings suggest significant mortality effects of short-term ozone exposure among the elderly during the moderate season. Those with underlying respiratory diseases were susceptible, even during winter.     

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.     

广州市近地面臭氧时空变化及其与气象因子的关系

利用2012年1月至2016年2月广州市环境空气自动监测数据和气象观测数据,对广州市近地面臭氧的时空分布特征及其与气象因子的关系进行分析。结果表明:2012—2015年广州市臭氧日最大8 h滑动平均值的第90百分位数波动变化,年变化率依次为-14.3%、5.8%、-12.1%;广州市臭氧浓度呈现夏、秋季高,春、冬季低的显著季节变化特征;臭氧日最大8 h平均值的月均值和第90百分位数最高的月份一般分别出现在10月和7—8月;臭氧浓度的日变化曲线为单峰型,最大值一般出现在14:00或15:00;臭氧浓度随垂直高度的升高而增大,从低层(6 m点位或地面站)到中层(118 m和168 m点位)、中层到高层(488 m点位)臭氧日最大8 h滑动平均值的增长率分别为18.3%和39.1%;广州市中心城区臭氧浓度低于南北部城郊,夏、秋季高值区与夏、秋季主导风向相对应;臭氧浓度受降水、气温、相对湿度和风速等气象因子影响,臭氧浓度的超标是多种因素综合作用的结果。     

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.     

Evaluating a Canadian regional air quality model using ground-based observations in north-eastern Canada and United States

The simulated concentrations from a numerical 3-dimensional regional air quality model (MC2AQ) are compared to those of ground-based observations in north-eastern Canada and the United States. The model has oxidant chemistry for both inorganic and organic species and deposition routines driven online by a mesoscale compressible community meteorological model (MC2). A standard emission inventory of anthropogenic, natural and biogenic sources for the year 1990 for 21 atmospheric trace species was used in the simulation. The model was run for July 1999, because of the occurrence of a high ozone episode and the availability of the monitoring data for surface O3, SO2, NO, NO2 and NOx. The comparisons during the episode show that the model performs quite well for predicting concentrations and diurnal variations of the surface ozone. The predictions for other gaseous species show some discrepancies with observations, but they are consistent with the results from other models evaluated in the literature. The uncertainties in the emission inventory for these species might be the main causes of the discrepancies. Further studies are needed to improve the predictability of SO and NOx, especially as the model is developed to include particulate matter formation as a result of these gaseous precursors.     

The Contribution of Acadia PRIMENet Research to Science and Resource Management in the National Park Service

Acadia National Park was one of the 14 sites included in the Park Research and Intensive Monitoring of Ecosystems network (PRIMENet). For eight years the EPA monitored ultraviolet (UV) radiation at this site, with the National Park Service (NPS) sponsoring a total climate and air monitoring station. Under the auspices of PRIMENet, research projects were initiated that investigated the effects of UV on amphibians, determined watershed mass balances, and developed a model of deposition along an elevational gradient. The monitoring data and research results have been used by park management to protect vegetation and water resources from ozone and deposition. These data are now being used to develop a “vital signs” monitoring program under the NPS’ Inventory and Monitoring Program. These data sets have been used in regional, national and international programs to protect human health and resources from air pollution. Public outreach has been accomplished through web site resources and via the Schoodic Education and Research Center.     

Some Dependence Models for the Time Between Ozone Exceedances in Mexico City

In this paper, we consider several modelling approaches for the mean time between exceedances of a given environmental threshold. The interest here resides in the time between ozone exceedances (also called ozone inter-exceedances times). The proposed models assume two basic density functions for the time between surpassings: the Weibull and the generalised exponential functions. Considering those distributions, a random effect with autoregressive structure is taken into account to determine unexpected changes in the mean of the inter-exceedances density functions. Those unexpected changes could be captured either by their scale parameter or by both their scale and shape parameters. The models are applied to ozone data from the monitoring network of Mexico City. Selection of the model that best explains the data is performed using the deviance information criterion and also the sum of the absolute values of the differences between the estimated and observed means of the inter-exceedances times. An analysis to detect the possible presence of change-points is also presented.