Andrzej Kałuszko

Air quality modeling for Warsaw agglomeration

Abstract The paper investigates the air quality in the urban area of Warsaw, Poland. Calculations are carried out using the emissions and meteorological data from the year 2012. The modeling tool is the regional CALMET/CALPUFF system, which is used to link the emission sources with the distributions of the annual mean concentrations. Several types of polluting species that characterize the urban atmospheric environment, like PM10, PM2.5, NOx, SO2, Pb, B(a)P, are included in the analysis. The goal of the analysis is to identify the most polluted districts and polluting compounds there, to check where the concentration limits of particular pollutants are exceeded. Then, emission sources (or emission categories) which are mainly responsible for violation of air quality standards and increase the adverse health effects, are identified. The modeling results show how the major emission sources – the energy sector, industry, traffic and the municipal sector – relate to the concentrations calculated in receptor points, including the contribution of the transboundary inflow. The results allow to identify districts where the concentration limits are exceeded and action plans are needed. A quantitative source apportionment shows the emission sources which are mainly responsible for the violation of air quality standards. It is shown that the road transport and the municipal sector are the emission classes which substantially affect air quality in Warsaw. Also transboundary inflow contributes highly to concentrations of some pollutants. The results presented can be of use in analyzing emission reduction policies for the city, as a part of an integrated modeling system.

Decision support for optimal emission reduction

In this paper, a problem related to the optimal allocation of financial means for reduction of air pollutants concentration in a given region is considered. The implementation is sulfur oxides oriented. The problem is formally stated as the cost‐constrained minimization of the environmental damage function by the optimal choice of desulfurization technologies, within the predefined set of controlled (power and heating) plants. Optimization methods have been implemented and tested on the real data for the selected region. The case study relates to the set of major power plants in the region of Silesia (Poland) and the basic desulfurization technologies, which are to be allocated.

Decision support method for cost-effective emission control on a regional scale

In the paper an implementation of a decision support algorithm for selection of emission abatement strategy on a regional scale is presented. The approach refers to optimal allocation of financial means for emission reduction in a given set of power and heating plants. The implementation considered is sulfur-oriented. The problem is formally stated as cost-constrained minimization of environmental damage function by the optimal choice of desulfurization technologies, within the set of the controlled plants. The receptor-oriented objective function utilizes air pollution forecast preprocessed by a regional scale dispersion model. An heuristic algorithm is implemented to solve the optimization problem. This is the improved and more general version of the method discussed earlier in [1]. Compared with that version, the cost constraints are considered in a more realistic form; two components of the total costs – investment and operational – are considered individually for each power plant and for the selected emission abatement technology. This requires a special construction of the optimization algorithm. Computational test results are presented for the set of the major power plants in the Silesia Region.

A Decision Support System for Air Quality Control Based on Soft Computing Methods

The problem considered is related to air quality protection on a regional scale. The approach refers to optimal allocation of financial means for emission reduction in a given set of power and heating plants. The implementation considered is sulfur-oriented. The problem is formally stated as cost-constrained minimization of environmental damage function by the optimal choice of desulfurization technologies, within the predefined set of the controlled plants. The receptor-oriented objective function utilizes air pollution forecast preprocessed by a regional scale dispersion model. An integer-type optimization problem is solved by two methods. The first method utilizes a heuristic algorithm designed for solving this specific problem, which directly finds discrete solution. Another approach is based on the classical gradient optimization algorithm and gives continuous, technologically not applicable solution. Then the continuous solution is transformed to the discrete form by enumeration of some discrete cases. Both algorithms has been implemented and tested on the real data for selected region. The case study relates to the set of major power plants in Silesia Region (Poland) and the basic desulfurization technologies, which are to be allocated. The test calculations allows us to evaluate accuracy of the heuristic method as well as applicability of both approaches for supporting decisions concerning optimal strategies of emission abatement on a regional scale.

Intra-urban variability of the intake fraction from multiple emission sources

Background Ambient air pollution and associated adverse health effects are among most acute environmental problems in many cities worldwide. The intake fraction (iF) approach can be applied for evaluating the health benefits of reducing emissions, especially when rapid decisions are needed. Intake fraction is a metric that represents emission-to-intake relationship and characterizes abatement of exposure potential attributed to specific emission sources. Aim In this study, the spatial variability of iF in Warsaw agglomeration, Poland, is discussed. Methods The iF analysis is based on the earlier air quality modeling results, that include the main pollutants characterizing an urban atmospheric environment (SO2, NOx, PM10, PM2.5, CO, C6H6, B(a)P, heavy metals). The annual mean concentrations were computed by the CALPUFF modeling system (spatial resolution 0.5 × 0.5 km2) on the basis of the emission and meteorological data from year 2012. The emission field comprised 24 high (power generation) and 3880 low (industry) point sources, 7285 mobile (transport) sources, and 6962 area (housing) sources. Results The aggregated iFs values are computed for each emission class and the related polluting compounds. Intra-urban variability maps of iFs are attributed to an emission sources by emission category and pollutant. Conclusions Intake fraction is shown as a decision support tool for implementing the cost-effective emission policy and reducing the health risk of air pollution.

KARO the Computer System for Simulation of the Impact of Energy Sector Expansion on Atmosphere Pollution

One of the most important problems of the polish economy is the transformation to the ecologically sustainable economy development, in particular in the energy production and consumption sector, which now is characterized by low efficiency and big sulphur dioxides emission. The paper desribes the computer system KARO whose main functions are: (i) to evaluate the consequences of the selected expansion scenarios for the energy demand and energy supply sectors, (ii) to verify the possibility of national economy to meet the assumed expansion scenario, (iii) to suggest the optimal strategy of new investments and technologies location that minimizes the negative impact of the economy expansion on the environment.