Can We Decode the Messages of Activated Sludge Through the Respirograms?

Wastewater contains varieties of carbonaceous and nitrogenous compounds that undergo complicated biodegradation processes in wastewater treatment plants. How these different compounds are degraded by activated sludge in aerobic conditions is still a mystery. Researchers have been trying to interpret it using the oxygen uptake rate (OUR) derived from the respirograms of respective substrates. Several models have been proposed to interpret the substrate removal mechanisms using the experimental observations. Have we succeeded in understanding the messages by activated sludge correctly using these models? In this paper, the distinctive nature of the respirograms when activated sludge is fed with different substrates and the biokinetic models that have been developed to explain the substrate removal mechanisms using derived OUR profiles are reviewed. In addition, a sensitivity study was conducted on the recently evolved simultaneous storage and growth model to investigate the influence of key parameters on OUR profiles during the biodegradation process.     

Comparative distribution of the scalp hair trace metal contents in the benign tumour patients and normal donors

The scalp hair samples of benign tumour patients (n = 77) and normal donors (n = 86) were analysed for selected trace metal contents using atomic absorption spectrophotometry. In the scalp hair of benign tumour patients, highest average levels were found for Ca (1,401 microg/g), followed by Na (476.9 microg/g), Mg (441.6 microg/g), Zn (438.3 microg/g), K (119.2 microg/g) and Fe (96.38 microg/g) while in comparison, the maximum mean levels in the scalp hair of normal donors were shown by Ca (556.5 microg/g), followed by Zn (154.2 microg/g), Mg (153.4 microg/g), Na (97.45 microg/g) and Fe (81.68 microg/g). Almost all metal levels revealed higher dispersion and asymmetry in the scalp hair of benign tumour patients compared with the normal donors. The average concentrations of Ca, Cd, Co, K, Mg, Mn, Na, Ni, Pb, Sb, Sr and Zn were significantly higher in the hair of benign tumour patients compared with the normal donors. Significant gender-based differences were also observed in the scalp hair metal contents of benign tumour patients. Strong positive correlations were found between Cd-Cr (0.547) and Cd-Co (0.507) in the hair of benign tumour patients whereas Ca-Mg, Mg-Sr, Co-Cd, Cr-Cd, Li-Cr, Li-Co, Li-Cd, Na-Cd, Na-Co and Na-Li exhibited strong relationships (r > 0.50) in the hair of normal donors. Cluster analysis (CA) and principal component analysis (PCA) were used for the source identification and apportionment of scalp hair trace metals in the two donor groups. The scalp hair of benign tumour patients and normal donors revealed six and five main clusters of trace metals, respectively. PCA extracted seven principal components of trace metals in the scalp hair of benign tumour patients while six principal components were observed in the case of normal donors. The study evidenced significantly different patterns of metal distribution in the hair of benign tumour patients in comparison with normal donors.     

Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey)

In this study, landslide risk assessment for Izmir city (west Turkey) was carried out, and the environmental effects of landslides on further urban development were evaluated using geographical information systems and remote sensing techniques. For this purpose, two different data groups, namely conditioning and triggering data, were produced. With the help of conditioning data such as lithology, slope gradient, slope aspect, distance from roads, distance from faults and distance from drainage lines, a landslide susceptibility model was constructed by using logistic regression modelling approach. The accuracy assessment of the susceptibility map was carried out by the area under curvature (AUC) approach, and a 0.810 AUC value was obtained. This value shows that the map obtained is successful. Due to the fact that the study area is located in an active seismic region, earthquake data were considered as primary triggering factor contributing to landslide occurrence. In addition to this, precipitation data were also taken into account as a secondary triggering factor. Considering the susceptibility data and triggering factors, a landslide hazard index was obtained. Furthermore, using the Aster data, a land-cover map was produced with an overall kappa value of 0.94. From this map, settlement areas were extracted, and these extracted data were assessed as elements at risk in the study area. Next, a vulnerability index was created by using these data. Finally, the hazard index and the vulnerability index were combined, and a landslide risk map for Izmir city was obtained. Based on this final risk map, it was observed that especially south and north parts of the Izmir Bay, where urbanization is dense, are threatened to future landsliding. This result can be used for preliminary land use planning by local governmental authorities.     

Statistical source identification of metals in groundwater exposed to industrial contamination

Levels of selected metals Na, Ca, Mg, K, Fe, Mn, Cr, Co, Ni, Cd, Pb and Mn were estimated by flame atomic absorption spectrophotometry in groundwater samples from Kasur, a significant industrial city of Pakistan. Salient mean concentration levels were recorded for: Na (211 mg/l), Ca (187 mg/l), Mg (122 mg/l), K (87.7 mg/l), Fe (2.57 mg/l) and Cr (2.12 mg/l). Overall, the decreasing metal concentration order was: Na > Ca > Mg > K > Fe > Cr > Zn > Co > Pb > Mn > Ni > Cd. Significantly positive correlations were found between Na–Cr (r = 0.553), Na–Mn (r = 0.543), Mg–Fe (r = 0.519), Mg–Cr (r = 0.535), Pb–K (r = 0.506) and Pb–Ni (r = 0.611). Principal Component Analysis and Cluster Analysis identified tannery effluents as the main source of metal contamination of the groundwater. The present metal data showed that Cr, Pb and Fe levels were several times higher than those recommended for water quality by WHO, US-EPA, EU and Japan. The elevated levels of Cr, recorded as 21–42 fold higher compared with the recommended quality values, were believed to originate from the tanning industry of Kasur.     

Floristic composition of arid off –shore islands in Abu Dhabi,United Arab Emirates

Data on flora and vegetation of 14 off-shore islands representing different habitat types were studied for investigating floristic composition, vegetation types and correlation with their habitats and ecosystem. The results demonstrate considerable plant distribution and diversity among the islands within the limited spectrum of species; encompassing a total of 47 species, belonging to 43 genera under 24 families. The most representative families were Amaranthaceae (9 species), Fabaceae (4 species), Poaceae (4 species) and Asteraceae and Aizoaceae (3 species each). Fourteen families are represented by only one species. The mangrove species, Avicennia marina, occurs throughout the coast of Abu Dhabi in discontinuous patches and in different water salinities. The studies also seek to underline that dominant species that constitutes the flora of Abu Dhabi are salt tolerant in nature. Compared to other Arabian Peninsula ecosystems, UAE perhaps has a higher coastal: mainland area ratio, which has contributed to a natural dominance of salt tolerant species among the community. The studies show 40% similarity among islands with respect to the species diversity. The floristic composition of the off-shore islands also indicates a need to consider these sites as protected sites.     

Mapping air quality zones for coastal urban centers

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates.

Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.     

Quality of tube well water intended for irrigation and human consumption with special emphasis on arsenic contamination at the area of Punjab,Pakistan

In the present study, the tube well water quality and the associated health risks, emphasizing on arsenic contamination, were investigated in rural and urban samples from Tehsil Mailsi located in Punjab, Pakistan. Arsenic concentrations (μg/L) were ranged from 12 to 448.5 and which exceeded the WHO recommended limit (10 μg/L) in all cases. The calculated average daily dose (3.3 × 10^?0.4 to 1.2 × 10^?0.2 mg/kg day) and hazard quotient (1.1–40) reflected the potential health risk to local population due to tube well water consumption as drinking purpose. Sodium percent (Na%), sodium absorption ratio, residual sodium carbonate, Kelly’s index and magnesium absorption ratio were also determined to assess the suitability of tube well water for irrigation purpose. The resulting piper plot revealed the Na–Ca–HCO₃ type water chemistry of the area and generally alkaline environment. The spatial distribution of arsenic in the tube well waters pinpoints the significant contribution of anthropogenic activities to arsenic pollution. Nevertheless, different statistical tools, including principal component analysis, hierarchical cluster analysis and correlation matrices, revealed the contribution of both natural and anthropogenic activities and alkaline type of aquifers toward the high level of arsenic contamination.