The effects of socioeconomic parameters on household solid-waste generation and composition in developing countries (a case study: Ahvaz,Iran)

Environment problems associated with the generation of waste are part of societal changes where households play an important role. These societal changes influence the size, structure and characteristic of given households. For the effective planning of solid-waste handling infrastructure, it is essential to know the quantity of waste generation and its composition. This paper presents the findings of a study carried out in an urban municipal area in Iran to determine the household solid-waste generation rate and waste composition based on field surveys and to determine the related socioeconomic parameters. The dependent variables were waste generation and composition, and independent variables were family size, family employment, age, number of room and education. Over 400 sample households were selected for the study using a stratified random sampling methodology and from five different socioeconomic groups. Waste collected from all groups of households were segregated and weighted. Waste generation rate was 5.4 kg/household/day. Household solid waste comprised of ten categories of wastes and with the largest component (76.9%). The generation and composition of household solid waste were correlated with family size, education level and households income. This paper adequately suggests new insights concerning the role of socioeconomic parameters in affecting the generation of household waste.     

Development of geomorphologic instantaneous unit hydrograph for a large watershed

Hill torrents cause a lot of environmental and property damage in Pakistan every year. Proper assessment of direct runoff in the form of hill torrents is essential for protection of environment, property, and human life. In this paper, direct surface runoff hydrograph (DSRH) was derived for a large catchment using the geomorphologic instantaneous unit hydrograph concept. The catchment with hill torrent flows in semi-arid region of Pakistan was selected for this study. It was divided into series of linear cascades and hydrologic parameters required for Nash's conceptual model, and were estimated using geomorphology of the basin. Geomorphologic parameters were derived from satellite images of the basin and ERDAS and ArcGIS were used for data processing. Computer program was developed to systematically estimate the dynamic velocity, its related parameters by optimization and thereby to simulate the DSRH. The data regarding rainfall-runoff and satellite images were collected from Punjab Irrigation and Power Department, Pakistan. Model calibration and validation was made for 15 rainfall-runoff events. Ten events were used for calibration and five for validation. Model efficiency was found to be more than 90% and root mean square error to be about 5%. Impact of variation in model parameters (shape parameter and storage coefficient) on DSRH was investigated. For shape parameter, the number of linear cascades varied from 1 to 3 and it was found that the shaper parameter value of 3 produced the best DSRH. Various values of storage coefficient were used and it was observed that the value determined from geomorphology and the dynamic velocity produced the best results.     

Assessment of the impact of the meteorological meso-scale circulation on air quality in arid subtropical region

In this paper, COSMO numerical weather prediction model is used to simulate land-sea breeze circulation in the north coast of Oman and to analyze the variability of the PBL depth. Typical summer day 1st August 2009 and winter day 1st January 2009 were simulated and verified by surface observations. The COSMO model was initialized using the German global model which runs as 40 km resolution and 40 vertical layers. The simulations show differences in the onset, strength, and inland penetration of the sea breeze. The high sea-land thermal contrast in the summer season induces earlier onset and progression of the sea breeze with larger horizontal and vertical extents. The summer and winter inland penetration is simulated around 150 and 65 km, respectively. The PBL depth was defined from the verticals profiles of the turbulence kinetic energy (TKE). The simulated PBL height varied at 1,600 m in summer and 700 m in the winter case. These results are in general in good agreement with the simulations of the National Centers for Environmental Prediction Global Data Assimilation System (NCEP-GDAS) model. The dispersive ability of the atmosphere was tested through the vertical mixing coefficient (VMC) generated by NCEP-GDAS simulations. The VMC during the summer simulated case is approximately four times larger than the respective one during the winter case. Consequently, during the advection of winter sea breeze, a shallow dome less than 100 m is shaped and forms an obstacle to the air-pollutant dispersion.     

The Role of Wind in Modeling of Oil Pollution Transport and Diffusion in the Persian Gulf

The Persian Gulf ecosystem is facing a variety of stresses as a result of being located within the richest oil province in the world, which hosts more than 67 % of the world oil reserve. In this paper, the distribution of oil pollution on the surface layer of the Persian Gulf is predicted for the different months after the release, based on the Coupled Hydrodynamical Ecological model for Regional Shelf seas (COHERENS). An Eulerian model for the Persian Gulf is set up using the Cartesian coordinate in the horizontal direction, and the sigma coordinate in the vertical direction. Based on this model, our analysis and simulation results indicate that the winds lead to diffusion of the contaminant concentration in the direction of the Arabian coast from the initial position of the spill. The results of this study can be used to provide appropriate solutions for preventing oil from spreading further in the region.     

Assessment of tap water quality and corrosion scales from the selected distribution systems in northern Pakistan

Corrosion deposits formed within drinking water distribution systems deteriorate drinking water quality and resultantly cause public health consequences. In the present study, an attempt was made to investigate the concurrent conditions of corrosion scales and the drinking water quality in selected water supply schemes (WSS) in districts Chitral, Peshawar, and Abbottabad, northern Pakistan. Characterization analyses of the corrosion by-products revealed the presence of α-FeOOH, γ-FeOOH, Fe₃O₄, and SiO₂ as major constituents with different proportions. The constituents of all the representative XRD peaks of Peshawar WSS were found insignificant as compared to other WSS, and the reason could be the variation of source water quality. Well-crystallized particles in SEM images indicated the formation of dense oxide layer on corrosion by-products. A wider asymmetric vibration peak of SiO₂ appeared only in Chitral and Abbottabad WSS, which demonstrated higher siltation in the water source. One-way ANOVA analysis showed significant variations in pH, turbidity, TDS, K, Mg, PO₄, Cl, and SO₄ values, which revealed that these parameters differently contributed to the source water quality. Findings from this study suggested the implementation of proper corrosion prevention measures and the establishment of international collaboration for best corrosion practices, expertise, and developing standards.     

Modeling of Cr contamination in the agricultural lands of three villages near the leather industry in Kasur,Pakistan, using statistical and GIS techniques

Kasur is one of the hubs of leather industry in the Punjab, Pakistan, where chrome tanning method of leather processing is extensively being used. Chromium (Cr) accumulation levels in the irrigation water, soil, and seasonal vegetables were studied in three villages located in the vicinity of wastewater treatment plant and solid waste dumping site operated by the Kasur Tanneries Waste Management Agency (KTWMA). The data was interpreted using analysis of variance (ANOVA), clustering analysis (CA), and principal component analysis (PCA). Interpolated surface maps for Cr were generated using the actual data obtained for the 30 sampling sites in each of the three villages for irrigation water, soil, and seasonal vegetables. The level of contamination in the three villages was directly proportional to their distance from KTWMA wastewater treatment plant and the direction of water runoff. The highest level of Cr contamination in soil (mg kg^?1) was observed at Faqeeria Wala (37.67), intermediate at Dollay Wala (30.33), and the least in Maan (25.16). A gradational variation in Cr accumulation was observed in the three villages from contaminated wastewater having the least contamination level (2.02–4.40 mg L^?1), to soil (25.16–37.67 mg kg^?1), and ultimately in the seasonal vegetable crops (156.67–248.33 mg kg^?1) cultivated in the region, having the highest level of Cr contamination above the permissible limit. The model used not only predicted the current situation of Cr contamination in the three villages but also indicated the trend of magnification of Cr contamination from irrigation water to soil and to the base of the food chain. Among the multiple causes of Cr contamination of vegetables, soil irrigation with contaminated groundwater was observed to be the dominant one.     

A New Approach to Plant Diversity Assessment Combining HPLC Data, Simplex Mixture Design and Discriminant Analysis

The quantitative assessment of plant diversity and its monitoring with time represent a key environmental issue for management and conservation of natural resources. Assessment of plant diversity could be based on chemical analyses of secondary metabolites (e.g. flavonoids, terpenoids), because of the substantial quantitative and qualitative between-individual variability in such compounds. At a geographical scale, the plant populations become widely dispersed, and their monitoring from numerous routine individual analyses could become restricting. To overcome such constraint, this study develops a multivariate calibration model giving the relative frequency of a particular taxon from a simple high-performance liquid chromatography (HPLC) analysis of a plant mixture. The model was built from a complete set of mixtures combining different taxons, according to an experimental design (Scheffé’s matrix). For each mixture, a reference HPLC pattern was simulated by averaging the individual HPLC profiles of the constitutive taxons. The calibration models, based on Bayesian discriminant analysis (BDA), gave statistical relationships between the contributions of each taxon in mixtures and reference HPLC patterns of these mixtures. Finally, these models were validated on new mixtures by using outside plants. This new biodiversity survey approach is illustrated on four chemical taxons (four chemotypes) of Astragalus caprinus (Fabaceae). The more differentiated the taxon, the better predicted its contributions (in mixtures) were by BDA calibration model. This new approach could be very useful for a global routine survey of plant diversity.