Application of a Three-Layer Photochemical Box Model in an Athens Street Canyon

ABSTRACT

The aim of this paper is to show that a photochemical box model could describe the air pollution diurnal profiles within a typical street canyon in the city of Athens. As sophisticated three-dimensional dispersion models are computationally expensive and they cannot serve to simulate pollution levels in the scale of an urban street canyon, a suitably modified three-layer photochemical box model was applied. A street canyon of Athens with heavy traffic was chosen to apply the aforementioned model. The model was used to calculate pollutant concentrations during two days with meteorological conditions favoring pollutant accumulation. Road traffic emissions were calculated based on existing traffic load measurements. Meteorological data, as well as various pollutant concentrations, in order to compare with the model results, were provided by available measurements. The calculated concentrations were found to be in good agreement with measured concentration levels and show that, when traffic load and traffic composition data are available, this model can be used to predict pollution episodes. It is noteworthy that high concentrations persisted, even after additional traffic restriction measures were taken on the second day because of the high pollution levels.     

内燃机螺帽径向夹持下料模和镦挤孔模具设计

根据轴向应力对棒料剪断方式及其断口形状的影响,设计了对螺帽锻造所用热轧棒料能进行精密剪切下料的新型结构的径向支持下料模具.采取增加下六角冲头与凹模的配合长度及配合精度的导向方法,设计了在80吨非标压力机上锻带孔螺帽的成形模具.给出了两种模具的试验结果.     

Neural network model for predicting peak photochemical pollutant levels

In this paper, an attempt is made for the 24-hr prediction of photochemical pollutant levels using a neural network model. For this purpose, a model is developed that relates peak pollutant concentrations to meteorological and emission variables and indexes. The analysis is based on measurements of O3 and NO2 from the city of Athens. The meteorological variables are selected to cover atmospheric processes that determine the fate of the airborne pollutants while special care is taken to ensure the availability of the required input data from routine observations or forecasts. The comparison between model predictions and actual observations shows a good agreement. In addition, a series of sensitivity tests is performed in order to evaluate the sensitivity of the model to the uncertainty in meteorological variables. Model forecasts are generally rather insensitive to small perturbations in most of the input meteorological data, while they are relatively more sensitive in changes in wind speed and direction.     

Volatile Organic Compounds Selection for Incorporation in Photochemical Mechanisms and the Development of Secondary Pollution Reduction Strategies

In the present work a method for the evaluation of the importance of the VOCs species is presented, aiming to provide criteria for the incorporation of these species into atmospheric photochemical mechanisms and for the successful application of secondary pollution reduction strategies. According to the method presented here, the species can be divided into more important and less important ones, taking into account their mixing ratios and emission values in combination with their reactivity. For this classification three quantitative and one qualitative criteria were introduced. Overall, it is concluded that alkenes with more than a few carbon atoms in their chain appear to be more important in urban and suburban areas, while in background conditions the alkanes, having the smaller chain (ethane, propane), become more important. In the case of alkenes there is no clear species classification, except for the biogenically emitted compounds, isoprene and limonene. In general, more important alkenes appear to be those with the smaller chain (ethene, propene, butene). Most abundant aromatics are benzene, toluene, and xylene. In background conditions higher aromatics are also important, especially 1,2,3-, 1,3,5-, and 1,2,4-trimethylbenzene. The most important carbonylic compounds are formaldehyde, acetaldehyde, and acetone. Finally, taking into account the results mentioned above, a new photochemical mechanism was developed. The species and species groups used in the proposed mechanism are: ethane, higher alkanes, ethene, propene, 2- butene, 1-alkenes, 2-alkenes, higher alkenes, benzene, toluene, m-, o-, p-xylene, 1,3,5-, 1,2,3-, 1,2,4-trimethylbenzene, higher aromatics, formaldehyde, acetaldehyde, higher aldehydes, isoprene, limonene, and other biogenic VOCs.     

A Combined MOIP–MCDA Approach to Building and Screening Atmospheric Pollution Control Strategies in Urban Regions

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.     

Neural Network Model for Predicting Peak Photochemical Pollutant Levels

ABSTRACT

In this paper, an attempt is made for the 24-hr prediction of photochemical pollutant levels using a neural network model. For this purpose, a model is developed that relates peak pollutant concentrations to meteorological and emission variables and indexes. The analysis is based on measurements of O₃ and NO₂ from the city of Athens. The meteorological variables are selected to cover atmospheric processes that determine the fate of the airborne pollutants while special care is taken to ensure the availability of the required input data from routine observations or forecasts. The comparison between model predictions and actual observations shows a good agreement. In addition, a series of sensitivity tests is performed in order to evaluate the sensitivity of the model to the uncertainty in meteorological variables. Model forecasts are generally rather insensitive to small perturbations in most of the input meteorological data, while they are relatively more sensitive in changes in wind speed and direction.     

Urban emissions measured with aircraft

Detailed knowledge of the quantity and composition of urban emissions is a prerequisite for successful application of atmospheric models to predict transport and distribution of primary and secondary air pollutants in the troposphere. We investigate the prospects and limitations of aircraft measurements in the determination of emission fluxes from urban areas. Our analysis focuses on data collected in September 1994 in and around Athens, Greece. Generally, emission fluxes from cities can be quantified with aircraft and with the minimum acceptable precision (uncertainty better than a factor of 2) only under very favorable meteorological conditions, namely in a homogeneous flow field in a well-mixed boundary layer. Better accuracy can be achieved only through ensemble averaging of repeated measurements. From our measurements in the Athens area, we deduced relative emission ratios of pollutant gases. With the support of ground-based measurements in a street canyon, the emission ratios NOx/CO, SO2/CO, and volatile organic compounds/CO (34 individual VOCs) could be determined with high precision. These results are very useful in analyzing differences between various existing emission inventories. Our data for VOCs reveal that the non-traffic emissions are of the same magnitude as the emissions originating from traffic.     

Design of a system for real-time modelling of the dispersion of hazardous gas releases in industrial plants 2. Accidental releases from storage installations

This paper is the second part of a research programme concerning the modelling capabilities of accidental releases of heavier-than-air toxic gases. The existing theory, which includes the strength of the source and the subsequent development of the released cloud under representative environmental conditions, is described. Comparison of the ZZB-2 system predictions with field data from the Desert Tortoise and Lyme Bay V, ammonia and chlorine releases, shows excellent agreement at distances between ≈ 200 m and a few kilometres from the source. The correlation between observed and predicted cloud concentrations, was in all cases significant at a confidence level better than 95%.