Valorization of Textile Sludge and Cattle Manure Wastes into Fuel Pellets and the Assessment of Their Combustion Characteristics.

The textile wastewater sludge (TWS) treatment and disposal are environmentally challenging due to toxic organics and metals. At the same time, cattle manure (CM), with better combustion performance, i.e., calorific value and uniform burning capability, is still underutilized in many parts of the world. This study evaluated and assessed the TWS and CM blending compatibility to convert them into fuel pellets for the direct combustion option and to stabilize toxic contaminants in TWS. After initial drying, grinding, and particle size control of the raw TWS and CM, both were blended at different ratios. The blended and nonblended TWS and CM samples were converted into pellets and analyzed for proximate and ultimate analyses, namely, moisture content, fixed carbon, CHNO, gross calorific value (GCV), bulk density, ash content, and metals, to evaluate the efficacy for energy applications. Out of three blended ratios, i.e., 75:25 (W/W%; CM/TWS), 50:50, and 25:75, the 75:25 blended pellet composition was found appropriate for fuel application. For the 75:25 blend, the obtained GCV was 12.77 MJ/kg, elemental carbon was 27.5%, volatiles were 41.7%, and residue ash was 42.8% of the total weight. Moreover, the blending ratios of 75:25 and 50:50 revealed that elemental and metal (Fe, Cu, Zn, Ni, Cr, Na, Mg, Mn) concentrations in TWS were stabilized to below threshold limits in the obtained residue ash for safe handling. The explored methods of TWS and CM waste processing, blending, and pelletization proposed a new technique for their sustainable waste valorization into energy sources.

An integrated approach for evaluating freshwater ecosystems under the influence of high salinity: a case study of Manchar Lake in Pakistan.

Manchar Lake, Pakistan's biggest lake in the arid zone, faces human-induced salinity issues. This study investigated its effects on the multifaceted ecosystem services, including serving as a source of drinking and irrigation water and aquatic health through assessing fish diversity and characteristics. Analyses of 189 water samples from 21 sites revealed spatiotemporal variations in major ions contributing to lake water salinity. The study assessed water suitability for drinking and agriculture using the water quality index (WQI), sodium adsorption ratio (SAR), magnesium hazard (MH), sodium percent (Na%), and Kelly's ratio (KR). The WQI, ranging from 141 to 408, indicated that the lake water was unfit for drinking. In some seasons, such as the pre-monsoon period, the lake water was deemed unsuitable for irrigation due to high SAR values (18 ± 4 g/L, average ± standard deviation), consistently rising MH values exceeding 66 in all seasons and elevated sodium percentages surpassing 66% in both the pre-monsoon and monsoon seasons. The KR remained acceptable (averaging 0.8 to 2.5) in all seasons. Fish health in highly saline conditions was assessed using data from interviews, focus group discussions, and fish sampling (1684 fish from 10 sites). Results depicted that high salt contamination severely impacted fish length and weight. The study found low richness (Simpson's biodiversity: 0.697 and Shannon Weaver: 1.51) and evenness (Pielou's index: 0.48) among the fish populations. Since 1998, Manchar Lake has seen a decline in fish varieties from 32 to 23, with changes in fish species' feeding habits. To improve lake water quality, the study recommends diverting saline water to the sea before and after the monsoon season while utilizing freshwater from alternative sources to fill any water deficit.

Informing water distribution line rehabilitation through quantitative microbial risk assessment.

Poor urban water quality has been linked to diminished source water quality, poorly functioning water treatment systems and infiltration into distribution lines after treatment resulting in microbiological contamination. With limited funding to rehabilitate distribution lines, developing nations need tools to identify the areas of greatest concern to human health so as to target cost effective remediation approaches. Herein, a case study of Hyderabad, Pakistan was used to demonstrate the efficacy of combining quantitative microbial risk assessment (QMRA) for multiple pathogens with spatial distribution system modeling to identify areas for pipe rehabilitation. Abundance of Escherichia coli, Enterococcus (enterococci), Salmonella spp., Shigella spp., Giardia intestinalis, Vibrio cholera, norovirus GI and adenovirus 40/41, were determined in 85 locations including the source water, treatment plant effluent and the city distribution lines. Bayesian statistics and Monte Carlo simulations were used in the QMRA to account for left-censored microbial abundance distributions. Bacterial and viral abundances in the distribution system samples decreased as follows: 9400 ± 19,800 norovirus gene copies/100 mL (average ± standard deviation, 100% of samples positive); 340 ± 2200 enterococci CFU/100 mL (94%), 71 ± 97 Shigella sp. CFU/100 mL (97%), 60 ± 360 E. coli CFU/100 mL (89%), 35 ± 79 adenovirus gene copies/100 mL (100%), and 21 ± 46 Salmonella sp. CFU/100 mL (76%). The QMRA revealed unacceptable probabilities of illness (>1 in 10,000 illness level) from the four exposure routes considered (drinking water, or only showering, tooth brushing, and rinsing vegetables consumed raw). Disease severity indices based on the QMRA combined with mapping the distribution system revealed areas for targeted rehabilitation. The combined intensive sampling, risk assessment and mapping can be used in low- and middle-income countries to target distribution system rehabilitation efforts and improve health outcomes.

Quantitative Microbial Risk Assessment of Drinking Water Quality to Predict the Risk of Waterborne Diseases in Primary-School Children.

Primary-school children in low- and middle-income countries are often deprived of microbiologically safe water and sanitation, often resulting in a high prevalence of gastrointestinal diseases and poor school performance. We used Quantitative Microbial Risk Assessment (QMRA) to predict the probability of infection in schoolchildren due to consumption of unsafe school water. A multistage random-sampling technique was used to randomly select 425 primary schools from ten districts of Sindh, Pakistan, to produce a representative sample of the province. We characterized water supplies in selected schools. Microbiological testing of water resulted in inputs for the QMRA model, to estimate the risks of infections to schoolchildren. Groundwater (62%) and surface water (38%) were identified as two major sources of drinking water in the selected schools, presenting varying degrees of health risks. Around half of the drinking-water samples were contaminated with Escherichia coli (49%), Shigella spp. (63%), Salmonella spp. (53%), and Vibrio cholerae (49%). Southern Sindh was found to have the highest risk of infection and illness from Campylobacter and Rotavirus. Central and Northern Sindh had a comparatively lower risk of waterborne diseases. Schoolchildren of Karachi were estimated to have the highest probability of illness per year, due to Campylobacter (70%) and Rotavirus (22.6%). Pearson correlation was run to assess the relationship between selected pathogens. V. cholerae was correlated with Salmonella spp., Campylobacter, Rotavirus, and Salmonella spp. Overall, the risk of illness due to the bacterial infection (E. coli, Salmonella spp., V. cholerae, Shigella, and Campylobacter) was high. There is a dire need for management plans in the schools of Sindh, to halt the progression of waterborne diseases in school-going children.

Probabilistic risk assessment of water distribution system in Hyderabad, Pakistan reveals unacceptable health hazards and areas for rehabilitation.

Poor water quality exacerbates multidimensional poverty in developing nations. Often centralized treatment facilities generate acceptable water quality, but the water is contaminated during distribution. Methods to assess sources of contamination in water distribution systems are lacking. A case study of two methods, human risk assessment linked to water distribution system sampling was conducted in Hyderabad, Pakistan to determine areas requiring infrastructure rehabilitation. Water samples from source water (i.e., the Indus River), treatment plant effluent and from taps in the water distribution system were analyzed by atomic adsorption spectroscopy for metals and metalloids (As, Cd, Cr, Hg, and Pb) and water quality parameters (dissolved and suspended solids, pH, conductivity, and total organic carbon). Source water exceeded acceptable drinking water levels for As, Cd, total Cr, and Pb, while the treatment plant effluent concentrations were acceptable. Concentrations of all metals and metalloids, except Hg, increased in the water distribution system post-treatment, exceeding safe drinking limits in at least one location, suggesting contamination of the water during distribution. A deterministic and a probabilistic risk assessment were conducted to evaluate two scenarios: (1) unrestricted use of piped water for all household purposes, including as drinking water and (2) restricted use of the water for purposes other than drinking in the household, including only dermal and inhalation exposure pathways. The water was deemed unsafe for unrestricted use as the sole source of drinking water by both risk assessment methods. Yet when an alternative source of drinking water was assumed and the piped water was used only for bathing and dish washing, the probabilistic risk assessment revealed acceptable health risks to the population, while the overly conservative deterministic risk assessment suggested unacceptable risks. The combined methods of water sampling, risk assessment and correlation analysis suggested areas for rehabilitation of the water distribution system in Hyderabad, Pakistan and these methods can be adopted in other developing nations to target limited funds for infrastructure rehabilitation.