Relations between Climatic Changes and High Pollution Levels in Bulgaria

One of the important consequences of the climatic changes is the potential danger of increasing the concentrations of some pollutants, which may cause damages to humans, animals and plants. Therefore, it is worthwhile to study carefully the impact of future climate changes on the high pollution levels. The major topic of the discussion in this paper is the increase of some ozone levels in Bulgaria, but several related topics are also discussed. The particular mathematical tool applied in this study is a large-scale air pollution model, the Unified Danish Eulerian Model (UNI- DEM), which was successfully used in several investigations related to potentially dangerous pollution levels in several European countries. This model is described by a non-linear system of partial differential equations, which is solved numerically by using (a) advanced numerical algorithms and (b) modern computer architectures. Moreover, (c) the code is parallelized and (d) the cache memories of the available computers are efficiently utilized. It is shown that in Bulgaria, as in the other European countries, the climatic changes will result in permanent increases of some quantities related to the ozone pollution. The important issue is that in our study the changes of the dangerous pollution levels are followed year by year. In this way, an attempt is made both to capture the effect of the interannual variations of the meteorological conditions on the levels of the ozone concentrations and to follow directly the influence of the climatic changes on the pollution levels. Moreover, the sensitivity of the pollution levels to variations of the human made (anthropogenic) and natural (biogenic) emissions is also discussed.

History, development and characteristics of lake ecological models

This paper provides some introductory information on the history, development, and characteristics of various lake ecosystem models. The modeling of lake ecological processes began to gain importance in the early 1960s. There are a number of models available today, with varying levels of complexity to cope with the variety of environmental problems found in lake environments, e.g. eutrophication, acidification, oxygen depletion, wetland management, heavy metal and pesticide pollution, as well as hydrodynamic problems. In particular, this paper focuses on lake eutrophication and wetland models, as well as addressing strategies appropriate for the design and development of reliable lake ecological models.

Space Observations and Global Climatic Data Reanalysis in AERMOD Modeling Package to Enhance the Industrial Air Pollution and Health Risk Assessment

We try to enhance the AERMOD industrial pollution dispersion model with remote sensing observations and climatic models based on them. In this paper, we focus on surface parameters (albedo, roughness, Bowen ratio) and land use classification on which they depend. We model maximum hourly concentrations and the resulting acute health risk and assess the effect on them produced by using remote sensing data for local areas around industrial plants instead of global standard AERMOD parameters. We consider five real multi-source plants for the effect of classification and two of them for the effect of surface parameters. The effect on the critical pollutant is measured in three ways: a) as difference between the yearly maxima of hourly concentrations of a critical pollutant (“absolute”);b) the same limited to daytime workhours and 95% quantile instead of absolute maximum (“regulatory”);c) as maximum hourly difference over a year (“instant”). The measure of effect is divided either by the reference concentration of the pollutant, which yields the impact on health risk, or by the concentration obtained with AERMOD standards, which yields relative measure of impact. For a), the impact of roughness dominates, that of albedo is small and that of the Bowen ratio is almost zero. For b), the impact of roughness is less prominent, and that of albedo and Bowen ratio is noticeable. For c), the impact is considerable for all three parameters. The effect of land use classification is considerable in all three cases a) - c). We provide the figures for different measures of remote sensing data effect and discuss the perspective of using remote sensing data in regulatory context.

Effect of Changing the Effluent Path of Omar-Bek Drain on the Damietta Branch Water Quality

The Omar-Bek drain, which represents the main source of water pollution along the Damietta branch of the Nile River, receives about 600,000 m3 (158,503,200 gallons) daily of untreated domestic, agricultural, and industrial wastes. The main purpose of this research consisted of investigating alternatives of managing water quality at the Damietta branch;a comparison was conducted between the current situation and two proposed scenarios. The first scenario involved changing the effluent path of the Omar-Bek drain to another drain is called “Main Western drain”. The second scenario centered around improving water quality at the Omar-Bek drain by constructing a WWTP with a design capacity of more than 150,000 m3/day (39,625,800 gallons) and by improving water quality at this drain by increasing the efficiency of WWTPs that discharged daily about 60,000 m3 (15,850,300 gallons) of partially treated wastewater to the drain. The current situation and the two proposed scenarios were simulated by using river pollutant (RP) modeling. It was concluded that the Omar-Bek drain has no significant effect on the Damietta branch water quality and that, instead of changing the path of the drain, improving the efficiency of the existing WWTPs discharging to the Omar-Bek drain and preventing the direct discharge of domestic wastewater to the drain will provide the most effective ways of increasing the water quality of the Damietta branch.

Viscoelastic modeling of the diffusion of polymeric pollutants injected into a pipe flow

This study focuses on the transient analysis of nonlinear dispersion of a polymeric pollutant ejected by an external source into a laminar pipe flow of a Newtonian liquid under axi-symmetric conditions.The influence of density variation with pollutant concentration is approximated according to the Boussinesq approximation and the nonlinear governing equations of momentum,pollutant concentration are obtained together with and Oldroyd-B constitutive model for the polymer stress.The problem is solved numerically using a semi-implicit finite difference method.Solutions are presented in graphical form for various parameter values and given in terms of fluid velocity,pollutant concentration,polymer stress components,skin friction and wall mass transfer rate.The model can be a useful tool in understanding the dynamics of industrial pollution situations arising from improper discharge of hydrocarbon pollutants into,say,water bodies.The model can also be quite useful for available necessary early warning methods for detecting or predicting the scale of pollution and hence help mitigate related damage downstream by earlier instituting relevant decontamination measures.

An Analytical Formulation for Pollutant Dispersion Simulation in the Atmospheric Boundary Layer

In this work we present the solution of the two-dimensional advection-diffusion equation by the GILTT method. The GILTT approach uses, in the series expansion, eigenfunctions given in terms of cosine functions. Here, a different expansion for the solution of the advection-diffusion equation will be explored. In other words, a Sturm-Liouville problem carrying more information of the original problem is considered, given by Bessel functions. Numerical simulations and comparisons with experimental data are presented.

High-precision parallel computing model of solute transport based on GPU acceleration

The scenario simulation analysis of water environmental emergencies is very important for risk prevention and control,and emergency response.To quickly and accurately simulate the transport and diffusion process of high-intensity pollutants during sudden environmental water pollution events,in this study,a high-precision pollution transport and diffusion model for unstructured grids based on Compute Unified Device Architecture(CUDA)is proposed.The finite volume method of a total variation diminishing limiter with the Kong proposed r-factor is used to reduce numerical diffusion and oscillation errors in the simulation of pollutants under sharp concentration conditions,and graphics processing unit acceleration technology is used to improve computational efficiency.The advection diffusion process of the model is verified numerically using two benchmark cases,and the efficiency of the model is evaluated using an engineering example.The results demonstrate that the model perform well in the simulation of material transport in the presence of sharp concentration.Additionally,it has high computational efficiency.The acceleration ratio is 46 times the single-thread acceleration effect of the original model.The efficiency of the accelerated model meet the requirements of an engineering application,and the rapid early warning and assessment of water pollution accidents is achieved.

Modeling agricultural non-point source pollution in a high-precipitation coastal area of China

Non-point source （NPS） pollution simulation in the high-precipitation coastal areas of China is difficult because varying annual typhoon incidence leads to highly contrasting rainfall patterns in dry years and wet years. An IMPULSE （Integrated Model of Non-point Sources Pollution Processes） based NPS model of the Changtan Reservoir watershed, which is a typical high-precipitation coastal area in China, was established based on the analysis of point and NPS pollution data, a digital elevation model, and data on land-use, soil, meteorology, economy, and agricultural management practice. Pre-processed pre-rain- fall soil moisture levels were introduced during the simulation to model the effects of typhoons on hydrology. Rainfall events were simulated sequentially through the year and the model was calibrated and verified using hydrological and water quality data. Accuracy of the simulated rainfall runoff and water quality in the Changtan watershed was found to be acceptable. The study showed that the NPS modeling system could be applied to the simulation and prediction ofNPS loadings in the Changtan Reservoir watershed.

PyLUR:Efficient software for land use regression modeling the spatial distribution of air pollutants using GDAL/OGR library in Python

Land use regression(LUR)models have been widely used in air pollution modeling.This regressionbased approach estimates the ambient pollutant concentrations at un-sampled points of interest by considering the relationship between ambient concentrations and several predictor variables selected from the surrounding environment.Although conceptually quite simple,its successful implementation requires detailed knowledge of the area,expertise in GIS,statistics,and programming skills,which makes this modeling approach relatively inaccessible to novice users.In this contribution,we present a LUR modeling and pollution-mapping software named PyLUR.It uses GDAL/OGR libraries based on the Python platform and can build a LUR model and generate pollutant concentration maps efficiently.This self-developed software comprises four modules:a potential predictor variable generation module,a regression modeling module,a model validation module,and a prediction and mapping module.The performance of the newly developed PyLUR is compared to an existing LUR modeling software called RLUR(with similar functions implemented on R language platform)in terms of model accuracy,processing efficiency and software stability.The results show that PyLUR out-performs RLUR for modeling in the Bradford and Auckland case studies examined.Furthermore,PyLUR is much more efficient in data processing and it has a capability to handle detailed GIS input data.

Development of EMC-based empirical model for estimating spatial distribution of pollutant loads and its application in rural areas of Korea

An integrated approach to easily calculate pollutant loads from agricultural watersheds is suggested and verified in this research. The basic concepts of this empirical tool were based on the assumption that variations in event mean concentrations（EMCs） of pollutants from a given agricultural watershed during rainstorms were only attributable to the rainfall pattern.Fifty one sets of EMC values were obtained from nine different watersheds located in the rural areas of Korea, and these data were used to develop predictive tools for the EMCs in rainfall runoff. The results of statistical tests of these formulas show that they are fairly good in predicting actual EMC values of some parameters, and useful in terms of calculating pollutant loads for any rainfall event time span such as daily, weekly, monthly, and yearly. This model was further checked in for its field applicability in a reservoir receiving stormwater after a cleanup of the sediments, covering 17 consecutive rainfall events from 1 July to 15 August in2007. Overall the predicted values matched the observed values, indicating the feasibility of this empirical tool as a simple and useful solution in evaluating timely distribution of nonpoint source pollution loads from small rural watersheds of Korea.

Nontarget screening using passive air and water sampling with a level Ⅱ fugacity model to identify unregulated environmental contaminants

It is thought that there are many unregulated anthropogenic chemicals in the environment.For risk assessment of chemicals, it is essential to estimate the predicted environmental concentrations. As an effort of identifying residual organic contaminants in air and water in Korea, nontarget screening using two-dimensional gas chromatography time-of-flight mass spectrometry（GC × GC-TOFMS） was conducted at 10 sites using polyurethane foam passive air sampler and at 6 sites using polydimethyl siloxane（PDMS） passive water sampler in three different seasons in 2014. More than 600 chemical peaks were identified satisfying the identification criteria in air and water samples, respectively, providing a list for further investigation. Chemical substances with reported national emission rates in2014（n = 149） were also screened for potential existence in the environment using a level Ⅱ fugacity model. Most of chemical substances classified as not detectable were not identified with detection frequency greater than 20% by nontarget screening, indicating that a simple equilibrium model has a strong potential to be used to exclude chemicals that are not likely to remain in the environment after emissions from targeted monitoring.