SAGA: a decision support system for air pollution management around a coal-fired power plant

Air quality models are currently feasible approaches to prevent air pollution episodes. From one of the first source-oriented modelling approaches for air pollution forecasting (Souto et al., 1994, 1996, 1998), a new decision support system for air quality management, SAGA, was developed to provide support to As Pontes Power Plant (APPP) staff. SAGA can provide air pollution forecasts and manage meteorological and air quality measurements. Power plant decisions are supported by the results of a non-hydrostatic meteorological model (ARPS, Xue et al., 2001) to produce Meteorological Forecasts (MFs), and to be coupled to different Lagrangian dispersion models.     

Characterization of urban air quality using GIS as a management system

Keeping the air quality acceptable has become an important task for decision makers as well as for non-governmental organizations. Particulate and gaseous emissions of pollutant from industries and auto-exhausts are responsible for rising discomfort, increasing airway diseases, decreasing productivity and the deterioration of artistic and cultural patrimony in urban centers. A model to determine the air quality in urban areas using a geographical information system will be presented here. This system permits the integration, handling, analysis and simulation of spatial and temporal data of the ambient concentration of the main pollutant. It allows the users to characterize and recognize areas with a potential increase or improvement in its air pollution situation. It is also possible to compute past or present conditions by changing basic input information as traffic flow, or stack emission rates. Additionally the model may be used to test the compliance of local standard air quality, to study the environmental impact of new industries or to determine the changes in the conditions when the vehicle circulation is increased.     

New indicator approaches for effective urban air quality management

Measurements of urban air quality at monitoring stations in developed countries have frequently involved the criteria gaseous pollutants, particulates, hazardous air pollutants, perceived air quality and relevant meteorological conditions. Large numbers of indicators have therefore been established to quantify emissions, concentrations and environmental and human health impacts of each of these groups of substances. To simplify the data for management, several indicators have been grouped together to form urban air quality indices but the weightings of individual variables is contentious. In industrialising and developing countries, data may be limited and traditional air pollutant indicators cannot often be constructed. The emphasis therefore has to be placed on the development of policy-relevant indicators, such as Response Indicators that reflect different policy principles for regulating air pollutant emissions. Indices that quantify the air quality management capabilities and capacities at the city level provide further useful decision-relevant tools. Four sets of indices, namely, 1. air quality measurement capacity, 2. data assessment and availability, 3. emissions estimates, and 4. management enabling capabilities, and a composite index to evaluate air quality management capability, were constructed and applied to 80 cities. The indices revealed that management capability varied widely between the cities. In some of the cities, existing national knowledge on urban air quality could have been more effectively used for management. It was concluded that for effective urban air quality management, a greater emphasis should be given, not just to monitoring and data capture programmes, but to the development of indicators and indices that empower decision-makers to initiate management response strategies. Over-reliance on restricted, predetermined sets of traditional air quality indicators should be avoided.     

Modeling the Baltic Sea eutrophication in a decision support system

SANBALTS (Simple As Necessary Baltic Long-Term Large-Scale) is a model of the coupled nitrogen and phosphorus cycles. This model has been developed as an integral part of the decision support system Marine Research on Eutrophication's Nest with the overall aim to evaluate management options for reducing Baltic Sea eutrophication. Simulated nutrient and oxygen concentrations as well as transport flows and major biogeochemical fluxes can be analyzed in many different ways, including construction of detailed nutrient budgets and tracing the fate of nutrient inputs. The large amounts of data that exist for this sea makes it possible to validate model results with observations. Major biogeochemical properties of the Baltic Sea are discussed through an analyses of model sensitivity to external forcing and internal parameterizations. Model results emphasize two features that are especially important for ecosystem management: i) impacts of local measures would always be modified by the long-range transports from other regions and ii) the response to significant changes in loads would only be seen after several decades.     

EuroBionet: a pan-European biomonitoring network for urban air quality assessment

EuroBionet, the 'European Network for the Assessment of Air Quality by the Use of Bioindicator Plants', is an EU-funded cooperative project currently consisting of public authorities and scientific institutes from 12 cities in 8 countries. In 2000, the bioindicator plants tobacco (Nicotiana tabacum Bel W3), poplar (Populus nigra 'Brandaris'), spiderwort (Tradescantia sp. clone 4430), Italian rye grass (Lolium multiflorum italicum) and curly kale (Brassica oleracea acephala) were exposed to ambient air at 90 monitoring sites according to standardised methods. Visible injuries and growth parameters were assessed and the accumulation of toxic substances in leaves determined. The exposure of tobacco resulted in a gradient with low levels of ozone-induced foliar injury in N and NW Europe, and medium to high values in the southern and central regions. The results of heavy metal and sulphur analyses in rye grass samples generally showed low to very low sulphur and low to medium heavy metal concentrations in leaves. In some cities, however, local hot spots of heavy metal contamination were detected. Analyses of the PAH contents in curly kale leaves gave low to medium values, with locally elevated levels at traffic-exposed sites.     

Mapping air quality zones for coastal urban centers

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates.

Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.     

A decision support system for wet soil cleaning

Newly developed software can predict the essential characteristics of the sand product resulting from the ex-situ washing of contaminated soil, dredging sludge or breaker sand. The system was designed for the Dutch situation and it works on the basis of readily available information. The primary output of the system is an assessment of the reusability of the sand product, which is obtained by comparing the prediction of the residual contamination and engineering quality with accepted levels and standards for building materials. The system also provides a ranking of potential applications for the sand with respect to treatment cost, the amount of recycled material or the environmental quality of the product. The software integrates soil cleaning expertise and unit process modelling in a way that allows varying levels of refinement of input data, ranging from a simple identification of the pollution source to a detailed particle size distribution of the contaminated soil. Tests on a database containing information on 117 processed batches of soil, dredging sludge and breaker sand show an 80% success rate in predicting cleanability, even though the input contamination levels were predominantly taken from (relatively inaccurate) in-situ data.     

Dispersion modelling: a tool for local air quality management

A local air quality management system, and the use of dispersion modelling as a tool for the system, are described. The Turkish town of Gehze is used as a model.     

A nomographic technique for estimation of air quality in urban areas

Nomograms based on the ATDL model to calculate the concentration of pollutants in an urban area in a simple manner are presented. Their use for estimation of permissible emission rates in various grids of an urban region is also elucidated.     

Evaluation of air pollution trends in Istanbul

Previously, SO2 = SO₂ and PM₁₀ (particulate matter less than 10 Bm in size) concentration distributions have been investigated in order to assess air pollution in Istanbul during the winter season (November–March) in which the concentration of these pollutants had reached formidably high levels due to the consumption of low-quality fuels (mainly coal) for residential heating. In this study, the effect of the increased share of natural gas and high-quality coal consumption in residential areas on air pollution levels was investigated. Modelling employing the method of kriging by spherical interpolation was used to obtain the concentration distribution of these pollutants, and spatial distributions of concentrations were generated. The pollution map obtained by this method indicated that increased usage of natural gas and high-quality coal in residential areas significantly improved air quality.     

Recommendations on the use of satellite remote-sensing data for urban air quality

In the last 5 yr, the capabilities of earth-observing satellites and the technological tools to share and use satellite data have advanced sufficiently to consider using satellite imagery in conjunction with ground-based data for urban-scale air quality monitoring. Satellite data can add synoptic and geospatial information to ground-based air quality data and modeling. An assessment of the integrated use of ground-based and satellite data for air quality monitoring, including several short case studies, was conducted. Findings identified current U.S. satellites with potential for air quality applications, with others available internationally and several more to be launched within the next 5 yr; several of these sensors are described in this paper as illustrations. However, use of these data for air quality applications has been hindered by historical lack of collaboration between air quality and satellite scientists, difficulty accessing and understanding new data, limited resources and agency priorities to develop new techniques, ill-defined needs, and poor understanding of the potential and limitations of the data. Specialization in organizations and funding sources has limited the resources for cross-disciplinary projects. To successfully use these new data sets requires increased collaboration between organizations, streamlined access to data, and resources for project implementation.     

Polychlorinated dibenzo-p-dioxin and dibenzofuran in urban air of an Andean city

Particle-bound polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) in ambient air were monitored together with particulate matter less than 10 μm (PM₁₀) at three sampling sites of the Andean city of Manizales, Colombia; during September 2009 and July 2010. PCDD/Fs ambient air emissions ranged from 1 fg WHO-TEQ m⁻³ to 52 fg WHO-TEQ m⁻³ in particulate fraction. The PM₁₀ concentrations ranged from 23 μg m⁻³ to 54 μg m⁻³. Concentrations of PM₁₀ and PCDD/Fs in ambient air observed for Manizales - a medium sized city with a population of 380 000 - were comparable to concentrations in larger cities. The highest concentrations of PCDD/Fs and PM₁₀ found in this study were determined at the central zone of the city, characterized by public transportation density, where diesel as principal fuel is used. In addition, hypothetical gas fractions of PCDD/Fs were calculated from theoretical K_p data. Congener profiles of PCDD/Fs exhibited ratios associated with different combustion sources at the different sampling locations, ranging from steel recycling to gasoline and diesel engines. Taking into account particle and gas hypothetical fraction of PCDD/Fs, Manizales exhibited values of PCDD/Fs equivalent to rural and urban-industrial sites in the southeast and center of the city respectively. Poor correlation of PCDDs with PM₁₀ (r = −0.55 and r = 0.52) suggests ambient air PCDDs were derived from various combustion sources. Stronger correlation was observed of PCDFs with PM₁₀. Poor correlation between precipitation and reduced PM₁₀ concentration in ambient air (r = −0.45) suggested low PM₁₀ removal by rainfall.     

GIS-based multicriteria decision analysis for settlement areas: a case study in Canik

Environmental Science and Pollution Research - In addition to global population growth due to migration from rural areas to urban areas, population density is constantly increasing in certain...     

Development of risk-based air quality management strategies under impacts of climate change

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Implications: Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.     

Evaluation of air quality by passive and active sampling in an urban city in Turkey: current status and spatial analysis of air pollution exposure

Concentrations of air pollutants, nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), ozone (O(3)), particulate matter (PM(2.5) and PM(10)), trace metals, and polycyclic aromatic hydrocarbons (PAHs) were measured in 2008 and 2009 in the city of Eski?ehir, central Turkey. Spatial distributions of NO(2), SO(2), and ozone were determined by passive sampling campaigns carried out during two different seasons with fairly large spatial coverage. A basic population exposure assessment was carried out employing Geographical Information System techniques by combining population density maps with pollutant distribution maps of NO(2) and SO(2). It was found that 95 % of the population is exposed to NO(2) levels close to the World Health Organization guideline value. Regarding SO(2), a large proportion of the population (83 %) is exposed to levels above the WHO second interim target value. Concentrations of all the pollutants showed a seasonal pattern increasing in winter period, except for ozone having higher concentrations in summer season. Daily PM(10) and PM(2.5) concentrations exceeded European Union limit values almost every sampling day. Toxic fractions of the measured PAHs were calculated and approximately fourfold increase was observed in winter period. Copper, Pb, Sn, As, Cd, Zn, Sb, and Se were found to be moderately to highly enriched in PM(10) fraction, indicating anthropogenic input to those elements measured. Exposure assessment results indicate the need for action to reduce pollutant emissions especially in the city center. Passive sampling turns out to be a practical and economical tool for air quality assessment with large spatial coverage.     

利用地衣移植法对乌鲁木齐市大气质量的评价

利用地衣移植法把中国树花移植到乌鲁木齐市7个监测点,用电感耦合等离子光谱直读仪检测中国树花体内8种重金属含量.结果显示,随着移植时间的延长,不同监测点的中国树花体内重金属含量明显增长.Nemerow综合污染指数显示,红雁池(23.79)＞钢铁厂(11.87)＞开发区(8.07)＞儿童公园(6.95)＞人民公园(5.93...     

Interactive design of urban level air quality monitoring network

An interactive optimization method for designing an air quality monitoring network in an urban area is proposed. The main purpose is to determine representative areas of monitoring stations rather than their precise locations. Two topologies are introduced to define similarities among pre-divided uniform meshes. The first is derived from the differences of long-term averages of pollutant concentrations between every two meshes and used in the Ward method clustering. The second is obtained by the cross-impacts between pairs of meshes and used as a constraint in the clustering process. Participation of specialists in the optimization process is allowed in such a way that they can modify the second topology by taking account of economic and physical conditions as well as inaccuracy of simulation models. This technique is applied to the NO_x monitoring network of Kyoto, Japan.