Higher Pollution Episode Detection Using Image Classification Techniques

Image classification techniques have been applied to detect higher pollution episodes in modelled air pollution data. These techniques are widely used in video processing to find patterns in videos. An attempt for the first time has been made to apply these techniques by considering air pollution as continuous video frames as the spatio-temporal changes in the pollution are linked to its previous state of the atmosphere. The applicability of these techniques has been tested over Northern Italy to detect ozone pollution episodes in year 2004 using model simulated concentrations. The methods tested in this paper are pixel, block-based, histogram, pertinent pixel and twin-comparison method. While these techniques have some kind of merits and demerits, a modified pertinent pixel comparison algorithm has been proposed to detect pollution episodes. The proposed method has been validated to detect PM10 episodes over Milan metropolitan area during 2 months in 2008 and is able to detect PM10 episodic events as well as non-events. This method provides a single binary index that can be applied by the air quality modellers and decision makers to determine the pollution episode over a given domain.     

Experimental study and comparative analysis of modified solar paraboloidal dish–thermoelectric generator systems

Environmental Science and Pollution Research - Solar energy is one of the major sources of renewable energy which contributes for environmental protection and pollution reduction. Methods and...     

Presence of macrolide-lincosamide-streptogramin B and tetracycline antimicrobials in swine waste treatment processes and amended soil.

Little is known about the fate of antimicrobials during common agricultural waste handling procedures. To better define the potential scope of this problem, concentrations of antimicrobials throughout the waste treatment process were estimated based on known antimicrobial usage, and the resulting predictions of high antimicrobial concentrations indicated the need for further investigation. Samples from building pits, a solids settling basin, a holding pond, and soil amended with waste treatment byproducts were therefore analyzed for traditional chemical parameters and macrolide, lincosamide, and tetracycline antimicrobials. Substantial improvements in water quality were observed during the treatment process. While the macrolide tylosin was not detected, chlortetracycline, oxytetracycline, and lincomycin were found at high concentrations throughout the waste treatment process. Oxytetracycline and lincomycin were also detected in soil from a field amended with waste treatment byproducts.     

Modeling a wetland system: The case of Keoladeo National Park (KNP), India

A model for the wetland part of KNP is presented and analyzed. Two-dimensional parameter scans suggest that this minimal model possesses dynamical complexities. Per capita availability of water to “bad” biomass (W₁) is one of the most vital parameters. One can ensure good health of the park by restricting the par capita availability of water to low values. Getting the “bad” biomass removed by granting permits to villagers should go hand in hand with water management and conservation activities. The model presented in this paper may be helpful in designing the timing and nature of human interventions in the form of implementation of well worked out policies in future.     

Definition and GIS-based characterization of an integral risk index applied to a chemical/petrochemical area

A risk map of the chemical/petrochemical industrial area of Tarragona (Catalonia, Spain) was designed following a two-stage procedure. The first step was the creation of a ranking system (Hazard Index) for a number of different inorganic and organic pollutants: heavy metals, polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated biphenyls (PCBs) and polychlorinated aromatic hydrocarbons (PAHs) by applying self-organizing maps (SOM) to persistence, bioaccumulation and toxicity properties of the chemicals. PCBs seemed to be the most hazardous compounds, while the light PAHs showed the minimum values. Subsequently, an Integral Risk Index was developed taking into account the Hazard Index and the concentrations of all pollutants in soil samples collected in the assessed area of Tarragona. Finally, a risk map was elaborated by representing the spatial distribution of the Integral Risk Index with a geographic information system (GIS). The results of the present study seem to indicate that the development of an integral risk map might be useful to help in making-decision processes concerning environmental pollutants.     

Design of sampling locations for river water quality monitoring considering seasonal variation of point and diffuse pollution loads

The design of a water quality monitoring network (WQMN) is a complicated decision-making process because each sampling involves high installation, operational, and maintenance costs. Therefore, data with the highest information content should be collected. The effect of seasonal variation in point and diffuse pollution loadings on river water quality may have a significant impact on the optimal selection of sampling locations, but this possible effect has never been addressed in the evaluation and design of monitoring networks. The present study proposes a systematic approach for siting an optimal number and location of river water quality sampling stations based on seasonal or monsoonal variations in both point and diffuse pollution loadings. The proposed approach conceptualizes water quality monitoring as a two-stage process; the first stage of which is to consider all potential water quality sampling sites, selected based on the existing guidelines or frameworks, and the locations of both point and diffuse pollution sources. The monitoring at all sampling sites thus identified should be continued for an adequate period of time to account for the effect of the monsoon season. In the second stage, the monitoring network is then designed separately for monsoon and non-monsoon periods by optimizing the number and locations of sampling sites, using a modified Sanders approach. The impacts of human interventions on the design of the sampling net are quantified geospatially by estimating diffuse pollution loads and verified with land use map. To demonstrate the proposed methodology, the Kali River basin in the western Uttar Pradesh state of India was selected as a study area. The final design suggests consequential pre- and post-monsoonal changes in the location and priority of water quality monitoring stations based on the seasonal variation of point and diffuse pollution loadings.     

Bringing diverse knowledge sources together--a meta-model for supporting integrated catchment management

Integrated catchment management (ICM), as promoted by recent legislation such as the European Water Framework Directive, presents difficult challenges to planners and decision-makers. To support decision-making in the face of high complexity and uncertainty, tools are required that can integrate the evidence base required to evaluate alternative management scenarios and promote communication and social learning. In this paper we present a pragmatic approach for developing an integrated decision-support tool, where the available sources of information are very diverse and a tight model coupling is not possible. In the first instance, a loosely coupled model is developed which includes numerical sub-models and knowledge-based sub-models. However, such a model is not easy for decision-makers and stakeholders to operate without modelling skills. Therefore, we derive from it a meta-model based on a Bayesian Network approach which is a decision-support tool tailored to the needs of the decision-makers and is fast and easy to operate. The meta-model can be derived at different levels of detail and complexity according to the requirements of the decision-makers. In our case, the meta-model was designed for high-level decision-makers to explore conflicts and synergies between management actions at the catchment scale. As prediction uncertainties are propagated and explicitly represented in the model outcomes, important knowledge gaps can be identified and an evidence base for robust decision-making is provided. The framework seeks to promote the development of modelling tools that can support ICM both by providing an integrated scientific evidence base and by facilitating communication and learning processes.     

Organochlorine pesticide residues in maternal blood,cord blood,placenta, and breastmilk and their relation to birth size

There is a growing concern that persistent organic pollutants like organochlorine pesticides (OCPs) can impair fetal growth and affect birth size. However, currently available epidemiological evidence is inconclusive. In this case-control study, we examined the association between exposure to hexachlorocyclohexane (HCH) and its isomers (α-HCH, β-HCH and γ-HCH), dichlorodiphenyltrichloroethane (DDT) and dichlorodiphenyldichloroethylene (DDE) and birth size. We recruited 60 infant-mother pairs, comprising of 30 term, small for gestational age babies with their mothers (Case group), and another 30 term, appropriate for gestational age babies with their mothers (Control group). This study was conducted in a tertiary hospital in Delhi, India, between March, 2009 and February 2010. Organochlorine pesticides were estimated in maternal blood, cord blood, placenta and breastmilk samples, using gas–liquid chromatography. Transplacental and transmammary transfer of OCPs was assessed by correlating the maternal blood OCP levels with those in cord blood and breastmilk by simple linear regression. The birthweight, crown heel length, head circumference, mid-arm circumference and ponderal index of the neonates was correlated with OCP levels in the maternal blood, cord blood, placenta and breastmilk. The OCP estimates were compared between samples of the case and control group. There was a significant (P < 0.001) transplacental transfer of all OCPs, however the transmammary transfer was insignificant for most OCPs except α-HCH. The OCP levels in the case group were higher than the control group; these were significantly more for t-HCH in cord blood and breastmilk; β-HCH in maternal blood, cord blood and breastmilk; DDE in placenta and DDT in breastmilk. There was a significant negative correlation between birthweight and t-HCH levels in maternal blood (P = 0.022), cord blood (P < 0.001), placenta (P = 0.008) and breastmilk (P = 0.005); β-HCH in cord blood (P < 0.001) and placenta (P = 0.020); γ-HCH in placenta (P = 0.045); and DDT (P = 0.009). Length at birth had a significant negative correlation with t-HCH in cord blood (P = 0.014) and breastmilk (P < 0.001); β-HCH in cord blood (P = 0.016) and breastmilk (P = 0.012); DDE in placenta (P = 0.016); and DDT in breastmilk (P = 0.006). Similarly, OCP levels were also found to be negatively correlated with head circumference, ponderal index and chest circumference in neonates. We conclude that prenatal exposure to some OCPs could impair the anthropometric development of the fetus, reducing the birthweight, length, head circumference, chest circumference and ponderal index.     

Treatment of electroplating industry wastewater: a review on the various techniques

Environmental Science and Pollution Research - Water pollution by recalcitrant compounds is an increasingly important problem due to the continuous introduction of new chemicals into the...     

Applications of waste-derived visibly active Fe-TiO2 composite incorporating the hybrid process of photocatalysis and photo-Fenton for the inactivation of E. coli

Environmental Science and Pollution Research - The study reports the applications of waste-derived visibly active Fe-TiO2 composite for the inactivation of E. coli present in water. The Fe/TiO2...