Air quality and climate change, as two crucial environmental emergencies confronting our societies, are still generally viewed as separate problems requiring different research and policy frameworks. However, they should rightfully be viewed as two sides of the same coin. What we truly need to seek, therefore, are “win-win” solutions.
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.
Products of Gaussian noises often emerge as the result of non-linear detection techniques or as parasitic effects, and their proper handling is important in many practical applications, including fluctuation-enhanced sensing, indoor air or environmental quality monitoring, etc. We use Rice’s random phase oscillator formalism to calculate the power density spectra variance for the product of two Gaussian band-limited white noises with zero-mean and the same bandwidth W. The ensuing noise spectrum is found to decrease linearly from zero frequency to 2W, and it is zero for frequencies greater than 2W. Analogous calculations performed for the square of a single Gaussian noise confirm earlier results. The spectrum at non-zero frequencies, and the variance of the square of a noise, is amplified by a factor two as a consequence of correlation effects between frequency products. Our analytic results are corroborated by computer simulations.
The influence of the CO₂ concentration in a local air zone in naturally ventilated residential houses on the residents’ behaviour was numerically investigated. A numerical two-dimensional CFD model of the indoor zone based on experiments performed by the authors was used. Different resident locations in the fluid domain and different inlet velocities imposed by wind were considered in simulations. The overall thermal comfort and IAQ indices were also calculated. The investigations results show that in contrast to the overall air quality, the local CO₂ was strongly dependent upon the resident location, fresh air inlet velocity and ventilation system type.
People spend most of their time in indoor environments and, consequently, these environments are more significant for the contribution of the daily pollutant exposure than outdoors. In case of children, a great part of their time is spent at school. Therefore, evaluations of this microenvironment are important to assess their time-weighted exposure to air pollutants. The aim of this study was to assess the children exposure to bioaerosols at schools from two different types of areas, urban and rural. A methodology based upon passive sampling was applied to evaluate fungi, bacteria and pollens, simultaneously with active sampling for fungi and bacterial assessment. Results showed very good correlations between sampling methods, especially for summer season. Passive sampling methodologies presented advantages such as no need of specific and expensive equipment, and they allow achieving important qualitative information. The study was conducted in different periods of the year to study the seasonal variation of the bioaerosols. Fungi and pollen presented higher levels during the summer time whereas bacteria did not present a seasonal variation. Indoor to outdoor ratios were determined to assess the level of outdoor contamination upon the indoor environment. Levels of fungi were higher outdoor and bacteria presented higher concentrations indoors. Indoor levels of bioaerosols were assessed in primary schools of urban and rural areas, using the active method along with a passive sampling method. Very good correlations between methods were found which allow the use of the passive sampling method to supply important and reliable qualitative information of bioaerosols concentrations in indoor environments. Seasonal variation in bioaerosols concentrations were found for fungi and pollen. Concentrations of fungi and bacteria above AMV (Acceptable Maximum Value) were found for most of the studied classrooms showing the importance of this microenvironment for the high exposure of children to bioaerosols.
The use of quantitative methods, including stochastic and exploratory techniques in environmental studies does not seem to be sufficient in practical aspects. There is no comprehensive analytical system dedicated to this issue, as well as research regarding this subject. The aim of this study is to present the Eco Data Miner system, its idea, construction and implementation possibility to the existing environmental information systems. The methodological emphasis was placed on the one-dimensional data quality assessment issue in terms of using the proposed QAAH1 method - using harmonic model and robust estimators beside the classical tests of outlier values with their iterative expansions. The results received demonstrate both the complementarity of proposed classical methods solution as well as the fact that they allow for extending the range of applications significantly. The practical usefulness is also highly significant due to the high effectiveness and numerical efficiency as well as simplicity of using this new tool.