细颗粒物和臭氧协同监测现状与建议

细颗粒物和臭氧协同控制是深入打好蓝天保卫战的重要课题.加强细颗粒物和臭氧协同监测,对精准科学制定协同控制策略具有积极意义.文章从监测网络、质量管理、数据应用等方面分析了我国细颗粒物和臭氧协同监测工作的现状;针对协同监测在满足管理需求方面的短板和不足,提出了拓展网络功能、完善技术体系、深化数据应用等建议.     

国外大气中消耗臭氧层物质及其替代物的监测概况与启示

大气中消耗臭氧层物质(ODS)及其替代物监测是科学评估履约成效的重要基础。美国等发达国家针对大气中ODS及其替代物开展了长期的网络化监测,中国相关监测起步相对较晚,基础比较薄弱。该文总结了发达国家大气中ODS及其替代物的监测经验,分析了中国的监测现状及存在的问题,提出了中国大气中ODS及其替代物监测的建议:明确监测目标,推进国家大气中ODS及其替代物监测网络建设;加快相关监测设备研发及方法研究进程,形成规范统一的监测技术体系;定期开展监测数据质量评价,加强综合分析利用。通过采取相应措施,逐步形成中国履行保护臭氧层国际环境公约的监测支撑能力。     

欧洲大气挥发性有机物大尺度监测进展及启示

开展大气臭氧前体物挥发性有机物(VOCs)的大尺度监测对于臭氧污染的联防联控有重要意义。欧洲早在20世纪90年代初就开展VOCs大尺度监测,而中国自2018年才开始建设全国性的VOCs监测网络,目前处于起步发展阶段。通过总结欧洲VOCs大尺度监测的发展历程、监测指标、质量保证及监测结果等,对中国VOCs监测提出建议:开展VOCs监测的顶层设计,对全国VOCs监测进行统一科学规划,保持VOCs监测的稳定性和持续性;通过科学方法筛选优化VOCs监测指标体系,构建统一的监测技术体系和质量管理体系,优先确保监测结果的准确性和可比性;将VOCs监测与现有的大气常规六参数常规监测网、颗粒物组分监测网等其他大气监测网有机融合,形成一个综合而丰富的大气环境监测网络,同时满足业务和科研需求。     

Photochemical pollution indicators—an analysis of 12 European monitoring stations

Indicators were devised to classify air pollution monitoring sites according to the type of expected photochemical pollution. The indicators are based on measured ozone volume fractions, the most frequently monitored component of photochemical pollution, and in particular on two contributions: one due to the ratio of daily maximum-to-minimum ozone volume fractions and the other to observed peak values. The two contributions regarded as independent are logically connected by “and” and therefore mathematically combined by multiplication. The criterion of classification is mainly described by the mentioned ratio and incidences of ozone volume fractions exceeding the limit of 80 ppb. Twelve monitoring stations within the European network (Cooperative programme for monitoring and evaluation of long-range transmission of air pollutants in Europe, EMEP) were classified according to this indicator predicting what ozone levels can be expected at the particular sites during the growth season (April through September) into three groups: clean, medium, and polluted, based on the data for the 7 years (1997 to 2003).     

Reference Point Approach for Multi-objective Assessment and Reduction of Ground-Level O<Subscript>3</Subscript> Air Quality Monitoring Network in Vojvodina Province,Serbia

A monitoring network of ground-level ozone (O₃) concentration levels in Vojvodina Province, Serbia, has been established in several phases, resulting in nine sampling sites (monitoring stations). Because maintenance of a monitoring network is financially very demanding, identifying potentially redundant ozone sites and reducing the network to a cost-effective and functional one are challenging and complex tasks. To provide an easily applicable but reliable analytical framework that will allow decision-makers and other stakeholders to identify redundant ground O₃ monitors, the reference point approach, presented by Cetinkaya and Harmancioglu (Journal of Hydrology, 2014), is adopted for a multi-objective assessment of the O₃ monitoring network. The evaluation process of the stations’ performance and their ranking is implemented in several phases. Firstly, a comprehensive set of 13 performance attributes is defined and associated with location and environmental criteria, followed by defining the set of alternatives. Next, all required attribute data are collected and stations are evaluated using the reference point approach. Finally, verification of the results is performed by aggregation of ranks obtained using the ideal point multi-criteria methods compromise programing and Technique for Order of Preference by Similarity to Ideal Solution. The aggregation process is performed using the Borda count and Kemeny social choice theory methods. Results indicate that the number of stations can be significantly reduced by 67%. Also, selection of the three best performing stations enabled identification of a core network that is expected to be functionally and financially sustainable under growing environmental and economic pressure.     

应用稳健统计方法对环境空气臭氧自动监测现场比对核查结果的分析研究

根据2015年9个城市53台现场臭氧分析仪的现场比对核查结果,比较研究了稳健统计方法和一般统计方法在评价国控网臭氧自动监测数据准确性和精密性上的应用。研究表明:稳健统计能够在不剔除异常数据的前提下降低异常值对正确评价臭氧自动监测数据质量的影响,适合评价现场比对核查结果;采用Hubers方法进行稳健统计,2015年国控网臭氧日常浓度点相对偏差的95%置信区间约为-0.1%至4.5%,95%预测区间为-14.0%~18.3%,变异系数约为9.5%,数据质量仍有提升空间。     

Monitoring Air Quality in Mountains: Designing an Effective Network

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.     

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.     

Forecasting of daily total atmospheric ozone in Isfahan

A neural network combined to an artificial neural network model is used to forecast daily total atmospheric ozone over Isfahan city in Iran. In this work, in order to forecast the total column ozone over Isfahan, we have examined several neural networks algorithms with different meteorological predictors based on the ozone-meteorological relationships with previous day's ozone value. The meteorological predictors consist of temperatures (dry and dew point) and geopotential heights at standard levels of 100, 50, 30, 20 and 10 hPa with their wind speed and direction. These data together with previous day total ozone forms the input matrix of the neural model that is based on the back propagation algorithm (BPA) structure. The output matrix is the daily total atmospheric ozone. The model was build based on daily data from 1997 to 2004 obtained from Isfahan ozonometric station data. After modeling these data we used 3 year (from 2001 to 2003) of daily total ozone for testing the accuracy of model. In this experiment, with the final neural network, the total ozone are fairly well predicted, with an Agreement Index 76%.     

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。     

Faecal contamination of water and sediment in the rivers of the Scheldt drainage network

The INSHORE system (INtegrated System for High Operational REsolution in shore monitoring) is a land-base survey system designed and developed for the specific task of monitoring the evolution in time of sandy shores. This system was developed with two main objectives: (1) to produce highly accurate 3D coordinates of surface points (in the order of 0.02 to 0.03 m); and (2) to be extremely efficient in surveying a beach stretch of several kilometres. Previous tests have demonstrated that INSHORE systems fulfil such objectives. Now, the usefulness of the INSHORE system as a survey tool for the production of Digital Elevation Models (DEMs) of sandy shores is demonstrated. For this purpose, the comparison of DEMs obtained with the INSHORE system and with other relevant survey techniques is presented. This comparison focuses on the final DEM accuracy and also on the survey efficiency and its impact on the costs associated with regular monitoring programmes. The field survey method of the INSHORE system, based on profile networks, has a productivity of about 30 to 40 ha/h, depending on the beach surface characteristics. The final DEM precision, after interpolation of the global positioning system profile network, is approximately 0.08 to 0.12 m (RMS), depending on the profile network's density. Thus, this is a useful method for 3D representation of sandy shore surfaces and can permit, after interpolation, reliable calculations of volume and other physical parameters.     

Sequential optimal monitoring network design and iterative spatial estimation of pollutant concentration for identification of unknown groundwater pollution source locations

One of the difficulties in accurate characterization of unknown groundwater pollution sources is the uncertainty regarding the number and the location of such sources. Only when the number of source locations is estimated with some degree of certainty that the characterization of the sources in terms of location, magnitude, and activity duration can be meaningful. A fairly good knowledge of source locations can substantially decrease the degree of nonuniqueness in the set of possible aquifer responses to subjected geochemical stresses. A methodology is developed to use a sequence of dedicated monitoring network design and implementation and to screen and identify the possible source locations. The proposed methodology utilizes a combination of spatial interpolation of concentration measurements and simulated annealing as optimization algorithm for optimal design of the monitoring network. These monitoring networks are to be designed and implemented sequentially. The sequential design is based on iterative pollutant concentration measurement information from the sequentially designed monitoring networks. The optimal monitoring network design utilizes concentration gradient information from the monitoring network at previous iteration to define the objective function. The capability of the feedback information based iterative methodology is shown to be effective in estimating the source locations when no such information is initially available. This unknown pollution source locations identification methodology should be very useful as a screening model for subsequent accurate estimation of the unknown pollution sources in terms of location, magnitude, and activity duration.     

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.     

珠江三角洲地区空气自动监控网络数据空间模拟适用方法

珠江三角洲地区已构建起区域性空气质量自动监测网络,由于初步建立的自动监控网络监测站点对整个区域而言极其有限,如以单离散数据形式发布则不能反映出区域空气污染的连续变化特征和全貌.对有限点位监测结果进行空间模拟研究才能满足反映区域性污染状况的需求.通过运用、比对、评价不同空间插值模型于自动监控网络离散站点的模拟应用,提出了珠江三角洲自动监控网络数据空间模拟适用方法.     

全国光化学监测网络建设面临的问题分析及策略初探

当前中国大气污染形势依然严峻,挥发性有机物作为臭氧的重要前体物之一,对环境空气质量的影响日益突出.建设全国重点区域光化学监测网络,可为全面加强挥发性有机物污染防治工作和有效监测光化学污染提供基础监测平台.笔者通过分析中国光化学监测的现状和面临的挑战,探讨了中国光化学监测网络建设的发展思路,并提出了各层级环境监测单位、科...     

Near-surface ozone levels and trends at rural stations in France over the 1995–2003 period

There is a considerable interest in quantifying near-surface ozone concentrations and associated trends, as they serve to define the impacts on ozone of the anthropogenic precursors reductions and to evaluate the effects of emission control strategies. A statistical test has been used to the ozone air concentrations measured in the French rural monitoring network stations, called MERA, in order to bring out spatio-temporal trends in air quality in France over the 1995-2003 period. The non-parametric Mann-Kendall test has been developed for detecting and estimating monotonic trends in the time series and applied in our study at annual values: mean, 98th percentile and median based on hourly averaged ozone concentrations and applied to daily maxima. In France, when averaged overall 9 stations between 1995 and 2003, a slight increasing trend of the O(3) levels (+0.6 +/- 1.3% year( - 1)) is observed, which is strongly influenced by the concentrations of the high altitude stations. In stations below 1000 m a mean rate of -0.48% year( - 1) from annual average concentrations, of -0.45% year( - 1) for medians and of +0.56% year( - 1) for P.98 over the 1995-2003 period were obtained. In stations above 1,000 m a mean rate of +1.75% year( - 1) from annual averages values, of +4.05% year( - 1) for medians and of +2.55% year( - 1) for P.98 were calculated over the 1997-2003 period. This situation is comparable to the one observed in other countries. In Europe and in France a reduction of precursor emissions is observed whereas a slight increasing trend of the O(3) levels is observed over the 1995-2003 period. One reason is the non-linearity of chemical ozone production with respect to precursor emissions. Possible explanations are an increase in near-surface ozone values caused by a reduced ozone titration by reduced NO( x ), the meteorological parameters change, an increase in bio-geogenic compound concentrations, the intercontinental transport from North America and Asia and the influence of stratospheric-tropospheric exchanges. These possible explanations must be interpreted carefully as on the short time scales considered.     

美国环境空气臭氧量值传递的经验与启示

新修订的《环境空气质量标准》对环境空气中的臭氧监测提出了明确的要求,一套有效的臭氧量值传递体系已成为保证中国环境空气臭氧监测数据质量的生命线。为加强中国环境空气臭氧量值传递体系的建设,总结了美国环境空气臭氧量值传递体系及其相关的技术规范体系,简要介绍其臭氧量值传递体系各关键环节的质量控制工作要点,并提出了对中国环境空气臭氧量值传递体系建设的建议。     

Uncertainty based optimal monitoring network design for a chlorinated hydrocarbon contaminated site

An application of a newly developed optimal monitoring network for the delineation of contaminants in groundwater is demonstrated in this study. Designing a monitoring network in an optimal manner helps to delineate the contaminant plume with a minimum number of monitoring wells at optimal locations at a contaminated site. The basic principle used in this study is that the wells are installed where the measurement uncertainties are minimum at the potential monitoring locations. The development of the optimal monitoring network is based on the utilization of contaminant concentration data from an existing initial arbitrary monitoring network. The concentrations at the locations that were not sampled in the study area are estimated using geostatistical tools. The uncertainty in estimating the contaminant concentrations at such locations is used as design criteria for the optimal monitoring network. The uncertainty in the study area was quantified by using the concentration estimation variances at all the potential monitoring locations. The objective function for the monitoring network design minimizes the spatial concentration estimation variances at all potential monitoring well locations where a monitoring well is not to be installed as per the design criteria. In the proposed methodology, the optimal monitoring network is designed for the current management period and the contaminant concentration data estimated at the potential observation locations are then used as the input to the network design model. The optimal monitoring network is designed for the consideration of two different cases by assuming different initial arbitrary existing data. Three different scenarios depending on the limit of the maximum number of monitoring wells that can be allowed at any period are considered for each case. In order to estimate the efficiency of the developed optimal monitoring networks, mass estimation errors are compared for all the three different scenarios of the two different cases. The developed methodology is useful in coming up with an optimal number of monitoring wells within the budgetary limitations. The methodology also addresses the issue of redundancy, as it refines the existing monitoring network without losing much information of the network. The concept of uncertainty-based network design model is useful in various stages of a potentially contaminated site management such as delineation of contaminant plume and long-term monitoring of the remediation process.     

支撑京津冀区域大气污染联防联控的大气监测体系构建

京津冀区域已成为全国大气污染最严重的地区之一,并且呈现出明显的区域性污染特征,加强区域间的环境合作,实施区域联防联控是解决京津冀区域大气污染问题的有效手段。对照《生态环境监测网络建设方案》的要求,目前京津冀区域大气监测体系还存在着监测网络不健全、监测项目覆盖不全面、监测新技术应用不足、质控体系不完善、信息产品供给与公众需求有差距等问题,与京津冀区域大气污染联防联控的要求不相适应。为全面提升京津冀区域大气监测体系对区域联防联控的技术支撑能力,亟需进一步完善京津冀区域的监测网络,增设传输研究、污染监控等特殊监测点位;逐步拓展监测项目,开展颗粒物化学组分和O_3前体物监测;加快遥感监测等立体监测技术在大气监测中的应用,全面分析污染物时空分布特征与传输规律;加强空气质量预报预警能力建设,为重污染天气应对提供技术支持;规范监测事权上收后的全过程质控体系,建立颗粒物标准方法比对和O_3量值传递质控机制;构建环境监测大数据平台,加强数据分析应用与信息公开。     

Monitoring of the Endangered Pinna nobilis Linné, 1758 in the Mar Grande of Taranto (Ionian Sea, Italy)

Two methods were used to calculate the meteorologically adjusted ground level ozone trends in southern Taiwan. The first method utilized is a robust linear regression method. The second approach uses a multilayer perceptron (MLP) artificial neural network (ANN) method. The observations obtained from 16 monitoring stations were analyzed and divided into six groups by hierarchical divisive clustering procedure. The daily maximum 1 and 8 h ozone concentrations for each group are then calculated. The meteorologically adjusted trends obtained by linear regression and MLP methods are smaller than the unadjusted trends for all groups and average time. It indicts that the meteorological conditions in Taiwan tend to increase ambient ozone concentrations in recent years.