Air pollution modelling in Erzurum city

Various techniques have been applied to air pollution modelling. In this study, a model was developed by applying a continuity equation to the air control volume over Erzurum city centre. Model parameters were calculated by regression analysis, using SO2 and particle concentrations taken in 1989-1990 and 1990-1991 winter seasons. Multiple correlation coefficients, R2, for all analyses were of the same order of 97%. According to this model, daily polluting concentrations are not only influenced by daily meterological parameters but also by the values of previous days. The proposed model allows estimation of daily polluting concentrations by means of meteorological data.     

Evaluation and analysis of environmental noise pollution in the city of Erzurum, Turkey

Noise pollution and its influence on the environment and life quality of human beings is a hot topic in scientific research. A study has been carried out to determine the level of noise and its sources in the city of Erzurum located in the east of Turkey. Noise measurements were taken in the morning, at noon and in the evening to determine noise pollution all over the city, particularly motorway transportation noise. In order to determine the sensitivity of the city people to noise pollution, standard survey studies were also conducted. According to the results, the noise level in Erzurum city centre exceeded allowed values at 96 of 126 measurement points. From the measured noise values, a map of noise pollution was created for Erzurum. Proposed solutions are set out.     

Interaction between air pollution and meteorological parameters in Erzurum, Turkey

In recent years, the rapid increase in population density has caused increases in the consumption of fuel, and the outdoor air quality has deteriorated in the crowded urban areas of Turkey. Erzurum, a city in the eastern part of Turkey, is influenced by air pollutants such as SO₂ and suspended particles. It is known that, in general, the air pollution concentrations have a close relationship with meteorological factors. In this study, the relationship between outdoor air quality data and meteorological factors, such as wind speed, rainfall, temperature, sunshine hours and relative humidity, is statistically analysed, using the code SPSS. According to the results obtained through multiple linear regression analysis, there are moderate levels of correlation between SO₂ and particle concentrations and meteorological factors in Erzurum.     

Composition of wet and bulk deposition in Erzurum, Turkey

Seasonal variations in the chemical characteristics of wet and bulk deposition samples collected in Erzurum were investigated for the period March 2002-January 2003. Major cations (Ca2+, K+, Mg2+) and major anions (SO4(2-),NO3-) were determined in bulk and wet deposition samples; pH was also measured in wet deposition. The average pH of the wet deposition at Erzurum was 6.6 due to extensive neutralization of the acidity. A strong relationship between pH and SO4(2-) concentrations was observed in all seasons; however, only a weak relationship was found between pH and NO3-. On a seasonal basis, the correlation between Ca2+ and SO4(2-) concentrations was stronger in winter than in summer. Seasonal variations of ions were examined in both wet and bulk deposition samples. Although maximum concentrations of anions generally occurred during winter and spring, cation concentrations peaked in summer for both wet and bulk deposition. Results indicated that Ca2+ was the dominant cation and SO4(2-) the dominant anion in all deposition samples at Erzurum. Even though correlations among the crustal ions (calcium, magnesium and potassium) were high, the relationship between anthropogenic ions (sulfate and nitrate) was less clear in bulk deposition.     

Modelling the dissipation kinetics of six commonly used pesticides in two contrasting soils of New Zealand

We used three non-linear bi-phasic models, bi-exponential (BEXP), first-order double exponential decay (FODED), and first-order two-compartment (FOTC), to fit the measured degradation data for six commonly used pesticides (atrazine, terbuthylazine, bromacil, diazinon, hexazinone and procymidone) in two New Zealand soils. Corresponding DT₅₀ and DT₉₀ values for each compound were numerically obtained and compared against those estimated by simple first-order kinetic (SFOK) model. All 3 non-linear models gave good fit of the measured data under both soil depths and were well supported by the values obtained for the respective statistical indices (RMSE, CRM and r ²). The FOTC model gave by far the best fit for most compounds, followed by the FODED and BEXP models. Overall, DT₅₀ values derived by non-linear models for the six compounds in soils from both sites were lower than the values obtained by the SFOK model. Differences in the SFOK and the three non-linear models derived DT₉₀were, however, an order of magnitude higher for some compounds, while for others differences were very small. Although all three non-linear models described most data by giving excellent fits, in a few instances > 5–10% asymptotes hindered the estimation of DT₉₀ values. This work shows that when degradation deviates from first-order kinetic, application of non-linear decay models to describe the kinetics of degradation becomes important in order to derive the true end-points for pesticides in soil.     

活性污泥系统神经网络建模与仿真研究

采用神经网络技术对松江污水厂污水处理活性污泥系统进行建模试验研究，在对实际运行数据按机理准则和范围准则剔除异常数据后，将样本数据随机分成训练样本、检验样本和测试样本。用试凑法确定合理的神经网络隐层节点数，以避免采用过大或过小的网络结构，在训练过程中用检验样本实时监控从而避免“过训练”现象的影响，较好地解决神经网络方法建模的两大难题，从而建立可靠、有效的活性污泥系统神经网络模型。并应用建立的网络模型对活性污泥系统的运行情况进行了仿真研究。建模研究表明，神经网络技术能较好地应用于活性污泥系统的建模，模型具有较好的泛化能力，有很好的实用价值。     

基于神经网络的活性污泥系统建模及其控制

针对松江污水厂污水处理活性污泥系统,采用神经网络技术进行建模试验研究,在对实际运行数据剔除异常数据后,将样本数据随机分成训练样本、检验样本和测试样本.用试凑法确定合理的神经网络隐层节点数,用检验样本实时监控训练过程从而避免"过训练"现象,用多次改变网络初始连接权值求得全局极小点,从而建立了泛化能力较好的基于神经网络的活性污泥系统数学模型.利用建立的神经网络模型,对活性污泥系统运行情况的仿真与控制进行了分析研究.示例研究表明:神经网络技术能较好地应用于活性污泥系统的建模与控制,有很好的理论与实践意义.     

改性松针对水体中铅(II)的吸附

探讨了改性松针(GXLsp)作为吸附剂对水体中铅离子的吸附性能,考察了吸附时间、溶液pH值、吸附剂用量、盐离子浓度、Pb(II)初始浓度及温度对改性松针吸附Pb(II)的影响。利用Langmuir和Freundlich等温线模型对实验数据进行非线性拟合分析,结果表明,Freundlich等温线模型能很好地描述松针对Pb(II)的吸附过程。热力学参数表明吸附是一个自发的吸热过程。改性松针对铅的吸附行为符合拟二级动力学方程,表明吸附过程是以化学吸附为主。在293K时松针对Pb(II)的饱和吸附量为318.3 mg/g,因此,GXLsp可作为一种高效低值生物质吸附剂以去除水体中重金属Pb(II)的污染。     

The aflatoxin contamination of some pepper types sold in Turkey

In the present study, 44 red-scaled pepper and 26 red powder pepper samples obtained from various spice retailers in Erzurum, and 20 isot (red pepper produced in Sanliurfa) were investigated for aflatoxin contamination using thin layer chromatography. Aflatoxin (B + G) was found in 8 red pepper samples (18.2%), and 3 red powder peppers (10.7%), and 1 isot sample (5%). The aflatoxin amount ranged from 1.1 to 97.5 ppb in all samples investigated. The highest amount of aflatoxin was found in red-scaled pepper. Species of Aspergillus, Penicillium and Rhizopus were generally contaminants of all samples.     

Linear and non-linear relationships between soil sorption and hydrophobicity: model, validation and influencing factors

The hydrophobic parameter represented by the octanol/water partition coefficient (log P) is commonly used to predict the soil sorption coefficient (K_oc). However, a simple non-linear relationship between log K_oc and log P has not been reported in the literature. In the present paper, soil sorption data for 701 compounds was investigated. The results show that log K_oc is linearly related to log P for compounds with log P in the range of 0.5-7.5 and non-linearly related to log P for the compounds in a wide range of log P. A non-linear model has been developed between log K_oc and log P for a wide range of compounds in the training set. This model was validated in terms of average error (AE), average absolute error (AAE) and root-mean squared error (RMSE) by using an external test set with 107 compounds. Nearly the same predictive capacity was observed in comparison with existing models. However, this non-linear model is simple, and uses only one parameter. The best model developed in this paper is a non-linear model with six correction factors for six specific classes of compounds. This model can well predict log K_oc for 701 diverse compounds with AAE = 0.37. The reasons for systemic deviations in these groups may be attributed to the difference of sorption mechanism for hydrophilic/polar compounds, low solubility for highly hydrophobic compounds, hydrolysis of esters in solution, volatilization for volatile compounds and highly experimental errors for compounds with extremely high or low sorption coefficients.     

Estimating uncertainties and uncertainty contributors of CMB PM2.5 source apportionment results

The chemical mass balance (CMB) model was applied for source apportionment of PM_2.5 in Atlanta in order to explore levels and causes of uncertainties in source contributions. Monte Carlo analysis with Latin hypercube sampling (MC-LHS) was performed to evaluate the source impact uncertainties and quantify how uncertainties in ambient measurement and source profile data affect results. In general, uncertainties in the source profile data contribute more to the final uncertainties in source apportionment results than do those in ambient measurement data. Uncertainty contribution estimates suggest that non-linear interactions among source profiles also affect the final uncertainties although their influence is typically less than uncertainties in source profile data.     

A multi-variate statistical model integrating passive sampler and meteorology data to predict the frequency distributions of hourly ambient ozone (O3) concentrations

A multi-variate, non-linear statistical model is described to simulate passive O3 sampler data to mimic the hourly frequency distributions of continuous measurements using climatologic O3 indicators and passive sampler measurements. The main meteorological parameters identified by the model were, air temperature, relative humidity, solar radiation and wind speed, although other parameters were also considered. Together, air temperature, relative humidity and passive sampler data by themselves could explain 62.5-67.5% (R(2)) of the corresponding variability of the continuously measured O3 data. The final correlation coefficients (r) between the predicted hourly O3 concentrations from the passive sampler data and the true, continuous measurements were 0.819-0.854, with an accuracy of 92-94% for the predictive capability. With the addition of soil moisture data, the model can lead to the first order approximation of atmospheric O3 flux and plant stomatal uptake. Additionally, if such data are coupled to multi-point plant response measurements, meaningful cause-effect relationships can be derived in the future.     

Modelling of phosphorus removal from aqueous and wastewater samples using ferric iron

Batch laboratory scale experiments were conducted to investigate the removal of phosphate from aqueous and municipal wastewater samples by addition of FeCl(3).6H(2)O. The effect of pH, Fe-dose and initial phosphate concentration were assessed. Optimum phosphate removal, 63% for 1:1 molar addition of Fe(III) was observed at pH 4.5. However, a 155% excess of Fe-dose was necessary for complete phosphorus removal. Phosphorus removal from municipal wastewater was slightly higher than that observed for the aqueous solutions. A chemical precipitation mathematical model was developed and tested with the available experimental data. The model included a total of 15 chemical reactions and 4 solid phases with the option of single-phase precipitation or two-phase co-precipitation. The resulting system of non-linear algebraic equations was solved numerically, using the Wijngaarden-Dekker-Brent method.     

Impacts of some meteorological parameters on SO2 and TSP concentrations in Erzurum, Turkey

The air pollution is the one of the most important environmental problems in Erzurum, situated in the eastern of Turkey, during winter periods. The unfavorable climate as well as the city’s topography, and inappropriate urbanization cause serious air pollution problems. The air pollutant concentrations in a city have a close relationship with its meteorological parameters. In the present study, the relationship between daily average total suspended particulate (TSP) and sulphur dioxide (SO₂) concentrations with meteorological factors, such as wind speed, temperature, relative humidity, pressure and precipitation, in 1995–2002 winter seasons was statistically analyzed using the stepwise multiple linear regression analysis. According to the results obtained through analysis, higher TSP and SO₂ concentrations are strongly related to colder temperatures, lower wind speed, higher pressure system and weakly lower precipitation and higher relative humidity. The statistical models of SO₂ and TSP including meteorological parameters gave R² of 0.74 and 0.88, respectively. Furthermore, the correlation between the previous day’s SO₂, TSP concentrations and actual concentrations of these pollutants on that day was investigated and found as 0.84 and 0.53, respectively. In order to develop this model, previous day’s SO₂ and TSP concentrations were added to the equations. The new model for SO₂ enhanced considerably (R² = 0.92), but for TSP new model was not enhanced (R² = 0.89).     

Modelling dissolution of multi-component non-aqueous phase liquids using Pareto distributions

A distributed-site non-aqueous phase liquid (NAPL) dissolution model that can capture the physical process of dissolution is presented. The model uses a Pareto distribution of effective interfacial area and a correlation for the mass transfer. Model parameters are obtained using a formal constrained non-linear optimisation technique. The model is applied on effluent data from two soil column experiments. The results of the Pareto distributed site model, with only two parameters to fit, were compared to two-site and multi-site models as well as the beta distributed site model. The Pareto distributed-site model produces equal or smaller error estimates than the other models.     

Simulation of herbicide degradation in different soils by use of Pedo-transfer functions (PTF) and non-linear kinetics

The degradation behaviour of bentazone in 14 different soils was examined at constant temperature and moisture conditions. Two soils were examined at different temperatures. On the basis of these data the influence of soil properties and temperature on degradation was assessed and modelled. Pedo-transfer functions (PTF) in combination with a linear and a non-linear model were found suitable to describe the bentazone degradation in the laboratory as related to soil properties. The linear PTF can be combined with a rate related to the temperature to account for both soil property and temperature influence at the same time.     

Modelling soot and SOF emissions from a diesel engine

Modelling of soot and SOF emissions from a typical European turbocharged diesel engine has been made. The model consists of a detailed kinetic mechanism with 472 reactions (120 chemical species) and data from the thermodynamic diagnostic procedure of the combustion process of the engine. The forward kinetic constants were obtained from literature and the background constants from a self-developed non-linear fitting routine based on the Marquardt algorithm. The dilution and mixing processes inside the engine are represented by a simple Wiebe function. The system of ordinary differential equations is solved with the Rosenbrock method for rigid systems and using the interpolating Lagrange polynomials to calculate the heat capacity of each species at the corresponding temperature. The kinetic model has been implemented in Digital Visual Fortran 6.0. The model has been executed for five different fuels and three mixtures of biodiesel and reference diesel operating under three diverse conditions from the European transient urban/extraurban Certification Cycle and the results of soot and SOF predicted are compared with experimental data.     

Modeling VOCs adsorption onto activated carbon

The activated carbon adsorption process is affected by the characteristics of adsorbent, adsorbate and environmental conditions. In this study, both adsorption and desorption processes are assumed to occur simultaneously and a numerical model was developed with a non-linear driving force in conjunction with the Langmuir model for predicting the overall adsorption process. The numerical model provides both adsorption and desorption rate constants and activation energies. The resultant equilibrium constants are of the same order of magnitude as reported by other studies. Results show that the model could well predict the adsorption isotherms and breakthrough curves under various conditions.     

A novel method dependent only on the mixture information (MIM) for evaluating the toxicity of mixture

Compound contamination and toxicity interaction necessitate the development of models that have an insight into the combined toxicity of chemicals. In this paper, a novel and simple model dependent only on the mixture information (MIM), was developed. Firstly, the concentration-response data of seven groups of binary and multi-component (pseudo-binary) mixtures with different mixture ratios to Vibrio qinghaiensis sp.-Q67 were determined using the microplate toxicity analysis. Then, a desirable non-linear function was selected to fit the data. It was found that there are good linear correlations between the location parameter (α) and mixture ratio (p) of a component and between the steepness (β) and p. Based on the correlations, a mixture toxicity model independent of pure component toxicity profiles was built. The model can be used to accurately estimate the toxicities of the seven groups of mixtures, which greatly simplified the predictive procedure of the combined toxicity.