Storm runoff quality and pollutant loading from commercial, residential, and industrial catchments in the tropic

Information on the pollution level and the influence of hydrologic regime on the stormwater pollutant loading in tropical urban areas are still scarce. More local data are still required because rainfall and runoff generation processes in tropical environment are very different from the temperate regions. This study investigated the extent of urban runoff pollution in residential, commercial, and industrial catchments in the south of Peninsular Malaysia. Stormwater samples and flow rate data were collected from 51 storm events. Samples were analyzed for total suspended solids, 5-day biochemical oxygen demand, chemical oxygen demand, oil and grease (O&G), nitrate nitrogen (NO₃-N), nitrite nitrogen, ammonia nitrogen, soluble reactive phosphorus, total phosphorus (TP), and zinc (Zn). It was found that the event mean concentrations (EMCs) of pollutants varied greatly between storm characteristics and land uses. The results revealed that site EMCs for residential catchment were lower than the published data but higher for the commercial and industrial catchments. All rainfall variables were negatively correlated with EMCs of most pollutants except for antecedent dry days (ADD). This study reinforced the earlier findings on the importance of ADD for causing greater EMC values with exceptions for O&G, NO₃-N, TP, and Zn. In contrast, the pollutant loadings are influenced primarily by rainfall depth, mean intensity, and max 5-min intensity in all the three catchments. Overall, ADD is an important variable in multiple linear regression models for predicting the EMC values in the tropical urban catchments.     

Forecasting of daily total atmospheric ozone in Isfahan

A neural network combined to an artificial neural network model is used to forecast daily total atmospheric ozone over Isfahan city in Iran. In this work, in order to forecast the total column ozone over Isfahan, we have examined several neural networks algorithms with different meteorological predictors based on the ozone-meteorological relationships with previous day's ozone value. The meteorological predictors consist of temperatures (dry and dew point) and geopotential heights at standard levels of 100, 50, 30, 20 and 10 hPa with their wind speed and direction. These data together with previous day total ozone forms the input matrix of the neural model that is based on the back propagation algorithm (BPA) structure. The output matrix is the daily total atmospheric ozone. The model was build based on daily data from 1997 to 2004 obtained from Isfahan ozonometric station data. After modeling these data we used 3 year (from 2001 to 2003) of daily total ozone for testing the accuracy of model. In this experiment, with the final neural network, the total ozone are fairly well predicted, with an Agreement Index 76%.     

Chemical characteristics of aerosols and trace gas distribution over North and Central India

A field campaign on aerosol chemical properties and trace gases measurements was carried out along the Delhi-Hyderabad-Delhi road corridor (spanning about 3,200 km) in India, during February 1-29, 2004. Aerosol particles were collected on quartz and cellulose filters using high volume (PM(10)) sampler at various locations along the route (i.e., urban, semi-urban, rural, and forest areas) and have been characterized for major cations (Na(+), Ca(2+), Mg(2+), K(+), and NH (4) (+)), anions (Cl(-), NO (3)(-), and SO (4)(2-)), and heavy metals (Cu, Cd, Fe, Zn, Mn, and Pb). Simultaneously, we measured NO(2) and SO(2) gases. These species show large spatial and temporal variations. The ambient PM(10) concentration has been observed to be the highest (55 ± 4 μg m(-3)) near semi-urban areas followed by forest areas (48 ± 2 μg m(-3)) and in rural areas (44 ± 22 μg m(-3)). The concentrations of NO( x ) (NO(2)+NO) and SO(2) ranged from 16 to 69 μg m(-3) and 4 to 11 μg m(-3), respectively. Among anions, NO(3)(-) and SO(4) (2-) are the major constituents of PM(10). The urban and semi-urban sites showed enhanced concentrations of Fe, Zn, Mn, Cd, and Pb. This study provide information about atmospheric concentrations of various species in the northern to central India, which may be important for policy makers to better understand the air quality of the region.     

An experimental method to verify soil conservation by check dams on the Loess Plateau, China

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model–prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D_a and D_b, have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.     

Fingerprinting of petroleum hydrocarbons (PHC) and other biogenic organic compounds (BOC) in oil-contaminated and background soil samples

Total petroleum hydrocarbons (TPH) or petroleum hydrocarbons (PHC) are one of the most widespread soil contaminants in Canada, the United States and many other countries worldwide. Clean-up of PHC-contaminated soils costs the Canadian economy hundreds of millions of dollars annually. In Canada, most PHC-contaminated site evaluations are based on the methods developed by the Canadian Council of the Ministers of the Environment (CCME). However, the CCME method does not differentiate PHC from BOC (the naturally occurring biogenic organic compounds), which are co-extracted with petroleum hydrocarbons in soil samples. Consequently, this could lead to overestimation of PHC levels in soil samples. In some cases, biogenic interferences can even exceed regulatory levels (300 μg g(-1) for coarse soils and 1300 μg g(-1) for fine soils for Fraction 3, C(16)-C(34) range, in the CCME Soil Quality Level). Resulting false exceedances can trigger unnecessary and costly cleanup or remediation measures. Therefore, it is critically important to develop new protocols to characterize and quantitatively differentiate PHC and BOC in contaminated soils. The ultimate objective of this PERD (Program of Energy Research and Development) project is to correct the misconception that all detectable hydrocarbons should be regulated as toxic petroleum hydrocarbons. During 2009-2010, soil and plant samples were collected from over forty oil-contaminated and paired background sites in various provinces. The silica gel column cleanup procedure was applied to effectively remove all target BOC from the oil-contaminated sample extracts. Furthermore, a reliable GC-MS method in combination with the derivatization technique, developed in this laboratory, was used for identification and characterization of various biogenic sterols and other major biogenic compounds in these oil-contaminated samples. Both PHC and BOC in these samples were quantitatively determined. This paper reports the characterization results of this set of 21 samples. In general, the presence of petroleum-characteristic alkylated PAH homologues and biomarkers can be used as unambiguous indicators of the contamination of oil and petroleum product hydrocarbons; while the absence of petroleum-characteristic alkylated PAH homologues and biomarkers and the presence of abundant BOC can be used as unambiguous indicators of the predominance of natural organic compounds in soil samples.     

Ecological risk assessment of heavy metals in surface sediments of northern littoral zone of Lake Çıldır,Ardahan, Turkey

In this paper, the heavy metal levels (Cu, Pb, Zn, Ni, Mn, Fe, As, Cd, Cr, Hg), organic carbon, and chlorophyll degradation products were studied to prove their ecological effects in Lake Ç?ld?r, where fossil fuels are used as an energy source in the studied area for most of the year, and domestic waste from settlements is discharged directly into the lake. Sediment samples were collected from six sites on the northern shore of Ç?ld?r Lake, Turkey in November 2012. Enrichment (EF) and contamination factor (CF) values were determined, and Pollution Load (PLI) and Potential Ecological Risk (PER) indices were calculated. Average concentrations of heavy metals in the sediments were, in descending order, Fe?>?Mn?>?Zn?>?Ni?>?Cr?>?Cu?>?Pb?>?As?>?Cd?>?Hg, respectively. According to mean values, the source of these elements may be considered natural due to lack of enrichment in Cu, Pb, Zn, Ni, and Cr in the sediment samples. Regarding enrichment of As, Cd, Mn, and Hg, the highest EF belongs to Hg. PLI and PER values indicate there are moderate ecological risk in the lake.     

The development of loads of cations, anions, Cd and Pb in precipitation and of atmospheric concentrations of N-components, in Switzerland from 1988 to 2003

This study presents the results of the analyses of Cd, Pb, cations and anions present in precipitation and dust at a pre-alpine and a suburban site in Switzerland in the period from 1988 to 2003. The aim of these measurements was to monitor the success of measures taken to diminish pollutant emissions. No change was found for Ca²⁺, K⁺, Na⁺ and Mg²⁺ loads – in line with expectations, as no reducing measures had been taken. Statistically significant and largely decreasing values (50–90%) were found for Cl⁻ and Cd (linked to the fitting of filters in incineration plants), Pb (unleaded petrol), (diminishing the use of mineral oil with high S content), and the proton (lower HCl and SO₂ emissions). A smaller decrease (up to 30%) or none was registered for oxidised nitrogen components (fitting cars with catalytic converters, but an increase in numbers of cars and trucks). No significant change was found for NH₃ as farming techniques had undergone no major changes. The long-term measurements show that the measures taken to reduce emissions were successful. A shorter monitoring period would have been misleading owing to data variability and temporary incidents e.g. amount of precipitation.     

Long-Term Planning of Waste Management System in the City of Regina – an Integrated Inexact Optimization Approach

In this study, an integrated solid waste management system based on inexact fuzzy-stochastic mixed integer linear programming (IFSMILP) has been applied to the long-term planning of waste management activities in the City of Regina. The model can effectively reflect dynamic, interactive, and uncertain characteristics of the solid waste management system in the city. The results have provided useful answers for the following questions: “What waste reduction goals are desired if the existing landfill's life is prolonged for 15 years?”, “What should be the waste flow allocation pattern in the city?”, “What should be done if the waste generation rate increases rapidly, while the relevant handling capacity is limited?”, and “What level of reliability will we have given the suggested waste management plan?”