Athenian photochemical smog: intercomparison of simulations (APSIS), background and objectives

Athens is suffering under severe photochemical air pollution levels. The spatial variation of the photosmog characteristics in the Athens basin reveals that air pollution levels in Athens are largely affected by local wind circulation systems. A complete picture of wind field pattern and air pollutant dispersion in Athens can only be achieved with suitable mathematical models. In view of its complexity and its manifold peculiarities, the situation in Athens qualifies as a test case for prognostic mesoscale models and photochemical dispersion models. As the frame of model intercomparisons and of attempts to evaluate model simulation results, the APSIS project was initiated. With the participation of more than 30 scientific teams from four continents, this project is expected to contribute to the refinement of atmospheric environmental software.     

Computer simulation of air pollution chemistry

The computer simulation of air pollution chemistry is a powerful technique for the understanding of the formation of air pollutants and the development of effective strategies for the control of air pollution. The present status of computerized mathematical modeling of air pollution chemistry is reviewed, typical examples of recent applications are presented and present areas of uncertainties are discussed. The four major areas of air pollution chemistry that are reviewed include photochemical oxidants, acid deposition, atmospheric aerosols and air toxics. The effect of atmospheric physical processes on air pollution chemistry if briefly discussed. The numerical techniques used for the simulation of atmospheric chemistry are reviewed.     

Influence of turbulence and atmospheric chemistry on grid size with respect to location in modeling and simulation of photochemical smog formation and transport

In models for photochemical smog formation and transport, mixing is assumed to be instantaneous and consequently the reactions are assumed to be kinetically controlled. In this work, the Damkohler number is calculated to check the validity of this assumption. The results show that this number is above 50, especially near pollution point sources such as the power station stacks, so that the diffusion limits the reactions for such cases. Using the irregular or adaptive grids minimized the Damkohler number and diffusion limitations which indicates that the grids should be finer near the source and coarser in remote regions. Therefore, depending upon the atmospheric conditions and emission sources, one can determine the optimum grid sizes for modeling and simulation of photochemical smog.     

Application of a parallel photochemical air quality model to the Campania region (southern Italy)

During most of the year, the concentrations of both primary and secondary air pollutants over the Campania region (southern Italy) do not comply with the Italian air quality standards. To gain insight into the chemical and meteorological processes that lead to high air pollutant concentrations over this area, the parallel package PNAM (Parallel Naples Airshed Model) has been developed, for the numerical simulation of photosmog episodes on urban and regional scale domains. PNAM has been applied to a photosmog episode which occurred on 26 July 1995. On this day, due to the stagnant conditions and the intensive solar radiation, a high ozone concentration was reported for the Naples basin. The performance of PNAM has been assessed by comparing measured air quality data with simulated data for O₃, NO, NO₂ and CO. PNAM was able to reproduce temporal and spatial characteristics of measured air quality data, although some discrepancies were evident, probably mainly due to the emission inventory, which was based only on total annual emissions.     

Measurement and modelling of pollutant emissions from Hong Kong

During November 1997 a detailed airborne investigation of air pollution in the Hong Kong region was undertaken. The airborne investigation formed part of a larger study funded by the Hong Kong Environmental Protection Department (EPD) and included the development of a state of the art numerical air quality modelling system to simulate air pollution in the Hong Kong region.The system consisted of a numerical weather prediction module, a prognostic air–chemistry/transport model, an emissions inventory system and a Graphical User Interface for display of results and preparation of simulations. The purpose of the airborne investigations was to provide data on the fluxes of selected pollutants arising from or entering the Hong Kong airshed as a check on the inventory. In addition the aircraft was to provide data on other pollutants of interest particularly with respect to the formation of photochemical smog.This paper describes the inventory data obtained from the aircraft and makes comparisons between the predictions of the model and the aircraft data for one of the days when the aircraft was able to be used to estimate the total fluxes of NMHC and NO_x from the study area.     

Emission inventory database management system using microcomputers

An emissions inventory database management system called EMIDBMS has been developed for storage, retrieval, and processing of air pollution emission data for both urban and industrial sources. It is a generalized user-friendly database system developed on a microcomputer using the query language of dBASE III Plus. Moreover, it is a relational interactive database which has been prepared and installed on an IBM PC/AT. The menu-driven option of the software allows the user easy access to the information for retrieval by simply executing the command files in a question/answer session. This could also provide air quality enforcement authorities a system for on-site use.EMIDBMS is comprised of a number of command and database files. The database files are designed to store data on all aspects of emission inventories, while the command files are designed for storage, processing, and retrieval of the various types of information stored in the database files. The emissions inventory data retrieved by EMIDBMS can either be used as input for an air pollution dispersion model installed on a microcomputer or can be transferred to an IBM mainframe for further use.     

Air quality short-term control in an industrial region under adverse weather conditions

A new short-term optimal control of air quality in an industrial region during atmospheric inversions is proposed. Its goal is to prevent violation of health standard of air quality in a few monitored zones. The control establishes restrictions on the emission rates of industrial sources and includes the identification of the industrial sources violating (exceeding) the emission rates set by the control. Both control and identification are based on using solutions to an adjoint dispersion model. Conditions that show the convergence of the emission rates, prescribed by the control, to the original emission rates of the industrial sources are given (Theorems 4 and 5). These results ensure that the new emission rates of industrial sources (established by the control) will be as close as possible to the original emission rates throughout the entire period of application of the control. This creates the minimum possible restrictions on the functioning of industrial enterprises. The highlight of the new control is the possibility of selecting special weights for each pollution source in the goal function that is minimized. These weights are mainly aimed at reducing the intensity of emissions of the main sources of pollution. An example demonstrates the ability of the new method. A similar approach can also be used to develop methods for cleaning water zones polluted by oil (the problem of bioremediation), and to prevent excessive pollution of urban areas with automobile emissions.     

The assessment of emission-source contributions to air quality by using a coupled MM5-ARPS-CMAQ modeling system: A case study in the Beijing metropolitan region,China

A coupled MM5-ARPS-CMAQ air quality modeling system was applied for investigating the contributions of various emission sources to the ambient concentrations of PM₁₀ in the Beijing metropolitan region of China. A three-level nested simulation domain was established for facilitating the modeling study, and a GIS-based atmospheric pollutant emission database was constructed to provide important emission information for the Models-3/CMAQ model. After verification, the coupled modeling system was implemented to predict the hourly contribution ratios of various PM₁₀ emission sources to Beijing's air quality during four representative months of January, April, August and October in the base year of 2002. It was found from the modeling results that three major sources (including fugitive industrial emissions, construction sites, and road dusts) presented a relatively high contribution to the PM₁₀ pollution in Beijing, with the contribution ratios of 28.67%, 42.88%, 42.46% and 35.67% for spring, summer, autumn and winter, respectively. In addition, the impacts of emissions from two major industrial zones within Beijing on its air quality were quantified. Moreover, the coupled modeling system was applied to explore possible future PM₁₀ concentration distributions in 2008 through two proposed emission sources reduction strategies. It was found that Beijing needs to take continual emission control efforts to comprehensively improve its air quality to the Class II level by 2008. The modeling results could provide sound decision making basis for developing effective air quality management strategies in the planning region.     

An operational real-time air quality modelling system for industrial plants

The advances on computer power capabilities and air quality modelling systems (AQMS) has reached to a high degree of sophistication during the last decade. Nowadays, the state-of-the-art air quality modelling systems such as MM5–CMAQ can handle the evaluation of air pollution concentrations in a very high detail in time and space. MM5 is a non-hydrostatic modelling system developed by PSU/NCAR (USA) during the last 20 years and continuously updated by the scientific community. CMAQ is a Community Multi-scale Air Quality Modelling System for simulating the transport and chemical concentrations in the air in 3D space and time developed by EPA (USA) in 2000. Both systems are complementary and allow a full simulation of the atmospheric flow to determine the amount of air pollution concentration exists in the 3D space and during a specific period of time. TEAP (a tool to evaluate the air quality impact of industrial plants) is an EUREKA project coordinated by UPM with the participation of INDRA S.A., Institute of Physics (Lithuania) and AB ‘MAZEIKIU NAFTA’ (Lithuania). This tool allows the industrial plants – and electric power plants – to have a full control in real-time and forecasting mode of the impact of the industrial emission under daily basis by using the so-called ON–OFF operational mode. The ON–OFF mode requires to run the AQMS both time in parallel by using the industrial plant emissions (ON) and excluding them (OFF). The system allows a full knowledge of the impact of industrial emissions for the next 48–72 h in full space (3D) domain, time and for every criteria pollutant (NO_x, SO₂, CO, O₃, PM). The system requires a powerful post-processing analysis module and a clustering approach to optimize the computer capabilities. The system is mounted over a PC cluster platform under Linux operating system. Results show a full and detail analysis of the amount of air pollutant concentrations due to the industrial plant emissions in time and space and under daily operational basis. The EU Air Quality Directives mark the air concentration limits to be taken into account into the TEAP system in forecasting mode to be fulfilled. The system allows to simulate also different industrial emission reduction strategies according to the optimal economical/production balance. The system can easily be adapted for emergency use.     

基于物联网的城市交通污染气体排放监控预警系统

交通污染气体排放是影响城市环境质量的主要因素之一.融合GIS、GPRS以及GPS技术,本系统通过传感器动态跟踪监测点附近的道路交通污染气体排放量,以及与之相关的影响因素,如:交通流、道路线形、天气等,利用K-近邻算法挖掘其内在联系,结合实际交通状况,构建能够准确反映交通污染气体在时空上的排放量分布预警模型,为如何降低交通污染排放提供决策支持依据.实验结果表明,本系统能准确预测交通污染气体的排放分布趋势,为交通管理部门进行道路交通管理提供依据.     

基于GIS的城市烟气在线监控系统的设计与实现

文章介绍了一个基于GIS的城市燃煤烟气在线监控系统的设计与实现。该系统融合了INTERNET、数据库和GIS等技术,实现了在环境监控中心对分散在城市不同位置的重点污染源烟气排放的远程监测、对远端监测仪器的状态监控、对监测业务数据的常规管理和对监测数据的分析可视化处理等功能。利用该系统,将为环境监测与管理部门及时把握城市重点污染源排放状况及监测仪器运行状况并采取必要的控制措施提供支持。     

Towards High-Resolution First-Best Air Pollution Tolls

In this paper, an approach is presented to calculate high-resolution first-best air pollution tolls with respect to emission cost factors provided by Maibach et al. (2008). Dynamic traffic flows of a multi-agent transport simulation are linked to detailed air pollution emission factors. The monetary equivalent of emissions is internalized in a policy which is then used as a benchmark for evaluating the effects of a regulatory measure—a speed limitation to 30 km / h in the inner city of Munich. The calculated toll, which is equal to simulated marginal costs in terms of individual vehicle attributes and time-dependent traffic states, results in average air pollution costs that are very close to values in the literature. It is found that the regulatory measure is considerably less successful in terms of total emission reduction. It reduces emissions of urban travelers too strongly while even increasing the emissions of commuters and freight, both leading to a increase in deadweight loss. That is, the regulatory measure leads to higher market inefficiencies than a “do-nothing” strategy: too high generalized prices for urban travelers, too low generalized prices for commuters and freight. Finally, long-term changes in the vehicle fleet fuel efficiency are assumed as a reaction to the Internalization policy. The results indicate, however, that the long-term effect of emission reduction is dominated by the short-term reactions and by the assumed improvement in fleet fuel efficiency; the influence of the resulting route and mode choice decisions turns out to be relatively small.     

Application of ADIFOR for air pollution model sensitivity studies

Typical computational methods of sensitivity analysis are discussed. Automatic differentiation addresses the need for computing derivatives of large codes accurately, regardless of the complexity of the model. Automatic differentiation in FORTRAN (ADIFOR) is a source transformation technique that accepts FORTRAN coded program for the computation of a function and generates portable FORTRAN code for the computation of the derivatives of that function. ADIFOR is introduced and applied to a comprehensive atmospheric chemistry/transport/radiative-transfer model to study the sensitivity of photochemical ozone production with respect to aerosol. The modeling results indicate that aerosol interaction with ozone may be as important as NO_x and non-methane hydrocarbon (NMHC) emissions in determining ozone production. The presence of scattering and/or absorbing aerosols in the atmosphere can cause significant differences in calculated ozone levels. Normalized sensitivity coefficients show that ozone and other photochemical oxidants are most sensitive to the aerosol single scattering albedo, which determines the scattering efficiency of the aerosol. ADIFOR is demonstrated to be an effective tool for sensitivity analysis in air pollution modeling.     

Neural network-based meta-modelling approach for estimating spatial distribution of air pollutant levels

Continuous measurements of the air pollutant concentrations at monitoring stations serve as a reliable basis for air quality regulations. Their availability is however limited only at locations of interest. In most situations, the spatial distribution beyond these locations still remains uncertain as it is highly influenced by other factors such as emission sources, meteorological effects, dispersion and topographical conditions. To overcome this issue, a larger number of monitoring stations could be installed, but it would involve a high investment cost. An alternative solution is via the use of a deterministic air quality model (DAQM), which is mostly adopted by regulatory authorities for prediction in the temporal and spatial domain as well as for policy scenario development. Nevertheless, the results obtained from a model are subject to some uncertainties and it requires, in general, a significant computation time. In this work, a meta-modelling approach based on neural network evaluation is proposed to improve the estimated spatial distribution of the pollutant concentrations. From a dispersion model, it is suggested that the spatially-distributed pollutant levels (i.e. ozone, in this study) across a region under consideration is a function of the grid coordinates, topographical information, solar radiation and the pollutant's precursor emission. Initially, for training the model, the input–output relationship is extracted from a photochemical dispersion model called The Air Pollution Model and Chemical Transport Model (TAPM–CTM), and some of those input–output data are correlated with the ambient measurements collected at monitoring stations. Here, improved radial basis function networks, incorporating a proposed technique for selection of the network centres, will be developed and trained by using the data obtained and the forward selection approach. The methodology is then applied to estimate the ozone concentrations in the Sydney basin, Australia. Once executed, apart from the advantage of inexpensive computation, it provides more reliable results of the estimation and offers better predictions of ozone concentrations than those obtained by using the TAPM–CTM model only, when compared to the measurement data collected at monitoring stations.     

A GIS based component-oriented integrated system for estimation, visualization and analysis of road traffic air pollution

Road traffic is a dominant source of air pollution. Therefore it is necessary to provide decision-makers with up-to-date emission information in an easily understandable form. To achieve this goal we have integrated existing emission calculation software with a graphical user interface, which includes a GIS (geographical information system) component. The paper first gives a summary of the basic road traffic emission model and then focuses on the design and implementation of the computer application with the emphasis on the used component and GIS technology. The integrated emission evaluation system offers entirely new ways of using the emission model and gives additional visualization and analysis possibilities.     

A GIS-based approach to spatial allocation of area source solvent emissions

Current area source emission inventories estimate total emissions for various industrial, commercial, and consumer activities at the county or higher levels. The lack of emission estimates at subcounty levels severely limits the modeling and planning capabilities in urban and regional air quality management. This paper extends current area source emission inventory methodology by developing a geographical information system (GIS) based approach for allocating county-level emission estimates to subcounty units. The new methodology uses GIS to develop and integrate spatial data, to analyze spatial variations in emissions, and to derive input to cell-based air pollution models. This approach incorporates statistical models to predict the spatial distribution of emission source activities based on widely available data. The paper presents an application of the proposed approach to emission inventory of the adhesives and sealants category in the Sacramento modeling region, California.     

Further evidence of the role of air pollution on solar ultraviolet radiation reaching the ground

The influence of photochemical pollution on the ultraviolet radiation reaching the ground is examined. For this purpose, a series of UV-A and UV-B measurements as well as the results of a simple parametric model are compared. It was found that the hypothesis of UV-B depletion is significant at an almost 95 per cent confidence level. It is also indicated that the effect of photochemical pollution on UV-B levels reaching the ground is roughly three times the same effect on UV-A levels.     

Detection of Fuel Adulteration Using Wave Optical with Machine Learning Algorithms

Fuel is a very important factor and has considerable influence on the air quality in the environment, which is the heart of the world. The increase of vehicles in lived-in areas results in greater emission of carbon particles in the environment. Adulterated fuel causes more contaminated particles to mix with breathing air and becomes the main source of dangerous pollution. Adulteration is the mixing of foreign substances in fuel, which damages vehicles and causes more health problems in living beings such as humans, birds, aquatic life, and even water resources by emitting high levels of hydrocarbons, nitrogen oxides, and carbon monoxide. Most frequent blending liquids are lubricants and kerosene in the petrol, and its adulteration is a considerable problem that adds to environmental pollution. This study focuses on detecting the adulteration in petrol using sensors and machine learning algorithms. A modified evanescent wave optical fiber sensor with discrete wavelet transform is proposed for classification of adulterated data from the samples. Furthermore, support vector machine classifier is used for accurate categorization. The sensor is first tested with fuel and numerical data is classified based on machine learning algorithms. Finally, the result is evaluated with less error and high accuracy of 99.9%, which is higher than all existing techniques.     

A modelling system with adjustable emission inventories for cross-boundary air quality management in Hong Kong and the Pearl River Delta,China

Air quality problems are attracting much attention in Hong Kong (HK) and the Pearl River Delta (PRD) in China. The complex and regional characteristics of air quality problems call for a comprehensive modelling system with a highly reliable simulation and effective communication tools for decision-makers and participants from multiple disciplines. In this paper, we used a modelling management method to develop a Cyberinfrastructure system that couples meteorological and air quality models with a visual analysis to improve the cognition and management of air quality problems. The database management of both the data and the modelling parameters is an innovative advantage of this system; this will be helpful not only for sharing modelling knowledge but also for improving the acknowledgement of modelling scenarios, which are usually conducted by various stakeholders. On the basis of 19 categories of emission inventories that provide detailed information about multiple pollutants in the 11 cities in the study area, this system provides an authoritative and adjustable emission inventory to draw an accurate scientific picture for decision-makers. We applied this system to a case study to investigate the effects of emission control of nitrogen dioxide from vehicles in HK and the PRD on air quality. The simulation showed that the air quality improvement from emission control was very limited and suggested that regional and super-regional co-operation involving the comprehensive emission control of multiple pollutants may be more effective in creating a better future.     

A new tool for processing atmospheric emission inventories: Technical aspects and application to the ESCOMPTE study area

Emission databases need to be processed for several purposes, e.g., policy and scientific, and so require flexible and fast handling. As a result, the creation and use of convenient interactive tools allowing easy and fast processing are of high importance. In this paper, a new software devoted to emission inventories processing is presented and applied to the actualization of the ESCOMPTE inventory. The ESCOMPTE inventory is a yearly (1999) high-resolution (1 km²) emission inventory created for use in chemical transport models to study ozone pollution. This tool includes several functions allowing the update of emission inventories at different temporal and spatial resolutions based on the reference ESCOMPTE inventory. The actualized yearly and hourly inventories are found consistent with the hypothesis involved in emission inventory creation. Due to its flexible architecture, several other applications related to air quality analysis can be performed such as the creation of emission scenarios allowing the evaluation of abatement strategies and regulation effects on anthropogenic emissions. Also, the architecture of the software allows an easy application to other emission inventories provided that they have similar or adaptable structure compared to the ESCOMPTE one.