Smoke aerosols dispersion and transport from the 2013 New South Wales (Australia) bushfires

Environmental monitoring and modelling, especially in the regional context, has seen significant progress with the widely usage of satellite measurement in conjunction with local meteorological and air quality monitoring to understand the atmospheric dispersion and transport of air pollutants. This paper studies the application of these data and modelling tools to understand the environment effects of a major bushfire period in the state of New South Wales (NSW), Australia, in 2013. The bushfires have caused high pollution episodes at many sites in the greater Sydney metropolitan areas. The potential long-range transport of aerosols produced by bushfires to other region and states has been seen by regulators as a major concern. Using data and images collected from satellites, in addition to the results obtained from different simulations carried out using HYSPLIT trajectory model and a regional meteorological model called Conformal Cubic Atmospheric Model (CCAM), we were able to identify at least 2 days on which the smoke aerosols from bush fires in NSW has been transported at high altitude to the northern state of Queensland and the Coral Sea. As a result, widespread high particle concentration in South East Queensland including the Brisbane area, as measured by nearly all the air quality monitoring stations in this region, occurred on the day when the smoke aerosols intruded to lower altitude as indicated by the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) Lidar measurements on the CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite. The use of meteorological or air quality modelling to connect the ground-based measurements with satellite observations as shown in this study is useful to understand the pollutant transport due to bushfires and its impact on regional air quality.     

Short-Term Forecasting of Nitrogen Dioxide (NO<Subscript>2</Subscript>) Levels Using a Hybrid Statistical and Air Mass History Modelling Approach

A novel hybrid model has been developed to support the provision of real-time air quality forecasts. Statistical techniques have been applied in parallel with air mass history modelling to provide an efficient and accurate forecasting system with the ability to identify high NO₂ events, which tend to be the episodes of most significance in Ireland. Air mass history modelling and k-means clustering are used to identify air mass types that lead to high NO₂ levels in Ireland. Trajectory matching techniques allow data associated with these air masses to be partitioned during model development. Non-parametric regression (NPR) has been applied to describe nonlinear variations in concentration levels with wind speed, direction and season and produce a set of linearized factors which, together with other meteorological variables, are employed as inputs to a multiple linear regression. The model uses an innovative integrated approach to combine the NPR with the air mass history modelling results. On validation, a correlation coefficient of 0.75 was obtained, and 91 % of daily maximum (hourly averaged) NO₂ predictions were within a factor of two of the measured value. High pollution events were well captured, as indicated by strong agreement between measured and modelled high percentile values. The model requires only simple input data, does not require an emission inventory and utilises very low computational resources. It represents an accurate and efficient means of producing real-time air quality forecasts and, when used in combination with forecaster experience, is a useful tool for identifying periods of poor air quality 24 h in advance. The hybrid approach outlined in this paper can easily be applied to produce high-quality forecasts of both NO₂ and additional pollutants at new locations/countries where historical monitoring data are available.     

An integrated air quality forecast system for a metropolitan area

Air quality forecasting is an important issue in environmental research, due to the effects that air pollutants have on population health. To deal with this topic, in this work an integrated modelling system has been developed to forecast daily maximum eight hours ozone concentrations and daily mean PM10 concentrations, up to two days in advance, over an urban area. The presented approach involves two steps. In the first step, artificial neural networks are identified and applied to get point-wise forecasting. In the second step, the forecasts obtained at the monitoring station locations are spatially interpolated all over the domain using the cokriging technique, which allows to improve the spatial interpolation in the absence of densely sampled data. The integrated modelling system has been then applied to a case study over Northern Italy, performing a validation over space and time for the year 2004 and analyzing if the limit values for the protection of human health set by the European Commission are respected. The presented approach represents a fast and reliable way to provide decision makers and the general public with air quality forecasting, and to support prevention and precautionary measures.     

Monitoring Studies of Augusta Bay Marine Waters

The monitoring of water quality today provides a great quantity of data consisting of the values of the parameters measured as a tunction of bme or as spatial function.In the marine environment, and especially in the suspended material, increasing importance is being given to the presence of particular pollution indices. With the increase in the number of sampling points, the amount of data increases and examining the results and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous chemometric techniques have been introduced in environmental chemistry, such as Principal Component Analysis (PCA).The use of the PCA in this work has been applied to the analysis of twenty three different sampling points in three seasonal sampling cruises in the same year. This led to recognition of the influence and the localisation of wastewaters in the Augusta bay after measuring the water pollution parameters.The PCA made evident the difference between some sampling sites whose data were initially thought to be similar where the presence of hot industrial water discharge or urban wastewater determines the permanent water quality.Furthermore, it has allowed a choice of more significant parameters for monitoring programs and more representative sampling site locations.     

Chromatographic techniques for pollution analyses

Pollution studies of air and water samples have been greatly enhanced by the use of chromatographic techniques. The selection of the proper detectors coupled with the various column types and substrates have broadened the capabilities of environmental analyses. Proper care in sampling protocols and sample treatment has steadily improved the sensitivity of these measurements. The recommended methods for air, wastewater, drinking water and solid waste samples all utilize some type of chromatographic analysis for the determination of organic contaminants. Three complimentary techniques: i.e., headspace sampling (dynamic and static methods), microextractions (liquid-liquid and/or liquid-solid) and solid-phase extractions have expanded the capabilities of such studies to permit the analytical chemist to perform fast in-the-field monitoring, concentrate low levels of analytes and determine solubilities of toxic substances. A discussion of other environmental areas which should be studied, along with the changes and/or modifications in analytical technology which should be investigated, will be presented.Plenary speaker.     

Measurement of environmental pollutants using passive sampling devices--a commentary on the current state of the art

Passive sampling devices have been used since the 1970s to measure time-weighted average (TWA) or equilibrium concentrations of pollutants in various environmental matrices (e.g. air, soils and sediments and water). In recent years the popularity of using such samplers has increased and the technology in now well established for the measurement of atmospheric pollutants. This sector has a long experience of using passive samplers in the short- and long-term assessment of air quality in the local environment and on a global scale (e.g. within the United Nations Stockholm Convention on the trans-boundary movement of persistent organic pollutants (POPs) where large networks of samplers on a continental scale have been established). In comparison, the use of passive samplers for monitoring the aquatic environment has been slower to take off. There has, however, been a recent research drive to develop devices for measuring the wide range of pollutants that can be found in environmental waters (e.g. ground, surface, and marine). It is now being recognised that passive samplers can play a valuable role in monitoring water quality within a legislative framework such as the European Union's Water Framework Directive (WFD). The data from these devices can be used alongside the results obtained from conventional spot or bottle sampling to improve risk assessments and to inform decisions on undertaking potentially expensive remedial actions. Such monitoring techniques may have uses within the European Registration, Evaluation, Authorisation & restriction of CHemicals (REACH) Directive and the forthcoming European Marine Strategy Directive. It is expected that the aquatic monitoring sector will follow a transition similar to that which occurred in air monitoring where data obtained from passive samplers can use used within a legal framework. There has also been increased interest in extending the role of passive samplers to both the measurement of equilibrium concentrations and investigating the movement and release of the dissolved fraction of various pollutants in the pore water of sediments and soils.     

The design of long-term air quality monitoring networks in urban areas using a spatiotemporal approach

The implementation and maintenance of an air pollution monitoring program can be expensive and time consuming, especially when the aim is for long-term monitoring over a significant area. Consequently, it is essential that sites are optimized to provide the best representative cover while minimizing costs. In the past, there has been a tendency to locate sampling stations at pollution hot-spots. While this is acceptable for determining a maximum potential exposure or identifying the extent of a risk, there are limitations to this approach when assessing the potential impact of any future abatement strategies or determining the level of exposure outside the vicinity. This paper presents an approach in which representative air quality assessments can be undertaken for an urban area using the minimum number of measurement sites. A novel methodology is described that involves site selection to capture the maximum variance in measured pollutants, while minimizing spatiotemporal autocorrelation between the selected sites. A case study is presented for Yazd, Iran. Overall, the results show that the proposed methodology can be effective and enable the long-term monitoring of air pollution to be undertaken on a cost-effective basis in urban areas. In addition, there is the potential for the methodology to be utilized for other forms of pollution (e.g., water, soil, and noise).     

广州市天地空一体化环境空气质量监测网络的建设

简述了原有广州市环境空气自动监测网络情况,通过对环境空气自动监测网络的集成优化,增设站点、扩展监测项目和引入新技术,建立了一个"金字塔形"的集天地空一体化的环境空气监测网络,弥补了原有监测网络在反映环境空气质量总体水平、污染来源解析、预报预警所需的环境质量信息、对环境空气质量的评估等方面的不足,该网络已成功应用于广州亚运会的空气质量保障。     

Measuring strategies and monitoring of the indoor environment

This paper presents key elements on which to base the design of a strategy for a particular indoor environment measurement task. Starting from a general strategy for responding to occupant complaints and conducting epidemiological and intervention studies the paper concentrates on selected key elements, with focus on air contaminants. Strategies for grouping of occupants with the purpose of exposure assessment should aim at optimising exposure contrast between groups, and grouping according to buildings may not be the proper choice. Occupant exposure can be measured by personal sampling or constructed from measured concentrations in microenvironments and activity patterns. The cause of temporal and spatial variability is discussed and guidance is given on the number of samples needed to detect a given change in true concentration level. The sick building syndrome (SBS) is defined as those situations where a high proportion of building occupants are complaining about mucous membrane or skin irritation, general symptoms. When investigating SBS, questionnaires should be used to collect structured information from occupants on perception of environmental conditions, psychosocial factors and symptoms. There is as yet no consensus on choice of length of reference period for reporting symptoms and for estimating exposure. Finally, methods for identifying and quantification of sources of air contaminants are discussed, including lab-scale or full-scale simulation, on-site measurement of source emission, air monitoring, surface sampling, and modelling.     

Assessment of regional metal levels in ambient air by statistical regression models

The assessment of the particulate matter (PM) levels and its constituents presented in the atmosphere is an important requirement of the air quality management and air pollution abatement. The heavy metal levels in PM10 are commonly evaluated by experimental measurements; nevertheless, the EC Directives also allow the Regional Governments to estimate the regulated metal levels (Pb in Directive 2008/50/EC and As, Ni and Cd in Directive 2004/107/EC) by objective estimation and modelling techniques. These techniques are proper alternatives to the experimental determination because the required analysis and/or the number of required sampling sites are reduced. The present work aims to estimate the annual levels of regulated heavy metals by means of multivariate linear regression (MLR) and principal component regression (PCR) at four sites in the Cantabria region (Northern Spain). Since the objective estimation techniques may only be applied when the regulated metal concentrations are below to the lower assessment threshold, a previous evaluation of the determined annual levels of heavy metals is conducted to test the fulfilment of the EC Directives requirements. At the four studied sites, the results show that the objective estimations are allowed alternatives to the experimental determination. The annual average metal concentrations are well estimated by the MLR technique in all the studied sites; furthermore, the EC quality requirements for the objective estimations are fulfilled by the developed statistical MLR models. Hence these estimations may be used by Regional Governments as a proper alternative to the experimental measurements for the regulated metal levels assessment.     

Relating Background NO2 Concentrations in Air to Air Mass History Using Non-Parametric Regression Methods: Application at Two Background Sites in Ireland

The concentration of nitrogen dioxide (NO₂) in background air varies temporally and spatially and is influenced by meteorological and anthropogenic factors. Background concentrations used in local air quality modelling studies have a significant effect on the accuracy of the overall result and when based on short-term monitoring data, variation in concentrations with air mass history is often unaccounted for. The current paper presents a powerful tool for the quantification and separation of local and regional air mass effects on background air quality. The origin of and the regions traversed by an air mass prior to reaching a receptor has been modelled using HYsplit-4. Trajectories (between 12 and 96?h duration) were defined based on the frequency with which they passed into 16 predefined compass quadrants and each represented as a vector. Using this vector as the predictor variable and the background concentration as the response variable, non-parametric regression using a Gaussian kernel function was carried out. A graphical output indicated the trajectory direction of maximum NO₂ concentration, while allowing distinction to be made between spurious and true peaks. In all cases, air mass history was found to have a statistically significant effect on NO₂ concentrations. Incorporating emissions data into the analysis local and regional effects were separated and quantified. It was found that emissions in the UK and Europe have a significant effect on background NO₂ concentrations in Ireland and in some instances supersede domestic emissions. The methods can be used to identify source regions, separate local and regional effects and improve predictions of background concentrations based on limited monitoring data. In particular, the results highlight the importance of considering air mass history when assessing background concentration levels for use in local air quality modelling studies.     

Selection of appropriate sampling stations in a lake through mapping

Much valuable information is obtained from water quality measurements and monitoring of lakes around the world. A powerful tool is the use of mapping techniques, as it offers potential use in water quality research. Both remote sensing techniques and traditional water quality monitoring are required to collect data at sampling stations. This study suggests another approach to determine the most appropriate distribution of sampling stations in water reservoirs that will be mapped for water quality parameters. Tests were conducted for the proposed approach for Secchi disc depth (SDD), chlorophyll-a, turbidity and suspended solids parameters in Lake Beysehir, Turkey. Results of analysis are available for a total of 30 sampling stations in August 2006. Ten sampling stations were used to model Lake Beysehir while the others were used for validation of the model. Sampling stations that offered the best representation of the lake for each parameter were determined. Then, the best representative sampling stations for all parameters in the study were determined. Moreover, in order to confirm the accuracy of these re-determined sampling stations, modelling was performed on the results of the analysis of June 2006, and it was found that the values obtained from the re-determined sampling stations were acceptable.     

The Use of Measurement Programmes and Models to Assess Concentrations Next to Major Roads in Urban Areas

This paper shows that monitoring campaigns in association withmodelling, particularly detailed roadside modelling, are auseful and cost effective method of assessing air quality. Itproposes that an approach based on detailed monitoringassociated with concurrent meteorological data can be used incombination with a roadside model to assess concentrations at other locations near a road and in other weather conditions. Plans for improving air quality can also be assessed in simpleways. The need for complex models based on detailed emissioninventories is avoided.Two examples from streets in London and Paris are presented inwhich measurements of CO, NO_x and volatile organic compoundshave been made. The measurements are interpreted usingcorrelations between pollutant concentrations and with windspeed, and by using the USEPA CALINE4 model. It is demonstratedthat air quality measurements can be used to assess the validityof road traffic emission factors.     

相似分析在空气连续监测缺测资料插补处理中的应用

空气连续自动监测中缺测资料的插补处理是环境监测与科研的一项基础性的技术工作,文章应用数理统计中的相似分析原理进行探讨,取得了较理想的结果.该方法对解决和处理因采样时间不足而造成的污染物浓度日均值缺失问题是十分有效的,对目前我国开展的城市空气质量日报工作有一定的实际意义.     

Meteorological normalisation and non-parametric smoothing for quality assessment and trend analysis of tropospheric ozone data

Despite extensive efforts to ensure that sampling and installation and maintenance of instruments are as efficient as possible when monitoring air pollution data, there is still an indisputable need for statistical post processing (quality assessment). We examined data on tropospheric ozone and found that meteorological normalisation can reveal (i) errors that have not been eliminated by established procedures for quality assurance and control of collected data, as well as (ii) inaccuracies that may have a detrimental effect on the results of statistical tests for temporal trends. Moreover, we observed that the quality assessment of collected data could be further strengthened by combining meteorological normalisation with non-parametric smoothing techniques for seasonal adjustment and detection of sudden shifts in level. Closer examination of apparent trends in tropospheric ozone records from EMEP (European Monitoring and Evaluation Programme) sites in Finland showed that, even if potential raw data errors were taken into account, there was strong evidence of upward trends during winter and early spring.     

环境空气中VOC s 的监测技术新进展

大气中的挥发性有机物(VOCs)严重威胁着人类的健康,目前对它的监测技术的研究越来越多.文章综述了近年来国内外在VOCs的采样及测试技术上的进展,重点介绍了固相微萃取、罐取样、吸附法等采样技术以及以气相色谱法为主的分析方法,并对一些非色谱法的分析技术进行了简单介绍.     

Requirements for developing a regional monitoring capacity for aerosols in Europe within EMEP

The European Monitoring and Evaluation Programme (EMEP) has been established to provide information to Parties to the Convention on Long Range Transboundary Air Pollution on deposition and concentration of air pollutants, as well as on the quantity and significance of long-range transmission of pollutants and transboundary fluxes. To achieve its objectives with the required scientific credibility and technical underpinning, a close integration of the programme's main elements is performed. These elements are emission inventories, chemical transport modelling, and the monitoring of atmospheric chemistry and deposition fluxes, which further are integrated towards abatement policy development. A critical element is the air pollution monitoring that is performed across Europe with a focus not only on health effect aspects and compliance monitoring, but also on process studies and source receptor relationships. Without a strong observational basis a predictive modelling capacity cannot be developed and validated. Thus the modelling success strongly depends on the quality and quantity of available observations. Particulate matter (PM) is a relatively recent addition to the EMEP monitoring programme, and the network for PM mass observations is still evolving. This article presents the current status of EMEP aerosol observations, followed by a critical evaluation in view of EMEP's main objectives and its model development requirements. Specific recommendations are given for improving the PM monitoring programme within EMEP.     

Classification of air quality using fuzzy synthetic multiplication

Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.