Autonomous mobile platform for monitoring air emissions from industrial and municipal wastewater ponds

Significant amounts of volatile organic compounds and greenhouse gases are generated from wastewater lagoons and tailings ponds in Alberta, Canada. Accurate measurements of these air pollutants and greenhouse gases are needed to support management and regulatory decisions. A mobile platform was developed to measure air emissions from tailings pond in the oil sands region of Alberta. The mobile platform was tested in 2015 in a municipal wastewater treatment lagoon. With a flux chamber and a CO₂/CH₄ sensor on board, the mobile platform was able to measure CO₂ and CH₄ emissions over two days at two different locations in the pond. Flux emission rates of CO₂ and CH₄ that were measured over the study period suggest the presence of aerobic and anaerobic zones in the wastewater treatment lagoon. The study demonstrated the capabilities of the mobile platform in measuring fugitive air emissions and identified the potential for the applications in air and water quality monitoring programs.

Implications: The Mobile Platform demonstrated in this study has the ability to measure greenhouse gas (GHG) emissions from fugitive sources such as municipal wastewater lagoons. This technology can be used to measure emission fluxes from tailings ponds with better detection of spatial and temporal variations of fugitive emissions. Additional air and water sampling equipment could be added to the mobile platform for a broad range of air and water quality studies in the oil sands region of Alberta.     

Cross-Linked Chitosan-Glyoxal/Kaolin Clay Composite: Parametric Optimization for Color Removal and COD Reduction of Remazol Brilliant Blue R Dye

Journal of Polymers and the Environment - Kaolin clay (KN) was employed as an inorganic filler to modify a cross-linked chitosan-glyoxal as Schiff’s-based chitosan composite derivative...     

Performance of full-scale coagulation-flocculation/DAF as a pre-treatment technology for biodegradability enhancement of high strength wastepaper-recycling wastewater

Paper mill wastewater leads to a serious damage on the environment owing to the high content of organic matters, suspended solids, toxic substances, and lignin. Hence, exploring new treatment technologies is the passion of environmental engineers to minimize the effluent impact on the environment and cleaner production aspects. This research focused on the performance of full-scale coagulation-fluctuation/DAF system for pre-treatment of high strength wastepaper-recycling wastewater and its effect on biodegradability improvement. To optimize unit performance, optimum coagulant and flocculant doses were firstly determined by jar test without prior change and adjustment of pH in lab-scale experiments. The optimum dosages were obtained by 1500 mg L^?1 polyaluminum chloride (PACl) as coagulant coupled with 40 mg L^?1 cationic polyacrylamide (C-PAM) as flocculant. Percentage removals of 39?±?10, 6.8?±?3.6, 31.0?±?6.7, 24.0?±?3.8, and 33.0?±?20.0 were achieved for COD, sCOD, BOD₅, sBOD₅, and color, respectively. The average BOD₅ to COD ratio after pre-treatment increased from 0.44 to 0.5, whereas the ratio of sBOD₅/sCOD dropped from 0.65 to 0.53. A superior effectiveness in reduction of TSS (98.1%) and VSS (98.4%) was also achieved. The results show that the application process is able to prevent malfunction operation in the following bioreactors which is obtainable through bio-treatability enhancement of pre-treated wastewater and reducing the risks of clogging and sludge washout. Attached growth processes are suggested to be applied in the further anaerobic/aerobic processes because of high proportion of soluble fraction of COD in the effluent to avoid poor floc formation and dispersed growth problems.     

Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams,United States

Environmental Science and Pollution Research - Natural streams longitudinal dispersion coefficient (Kx) is an essential indicator for pollutants transport and its determination is very important....     

What factors drive copepod community distribution in the Gulf of Gabes,Eastern Mediterranean Sea?

The spatial and temporal variations in copepod communities were investigated during four oceanographic cruises conducted between July 2005 and March 2007 aboard the R/V Hannibal. A close relationship was observed between the temperature, salinity, hydrographic properties and water masses characterising the Gulf of Gabes. Indeed, water thermal stratification began in May–June, and a thermocline was established at a 20-m depth, but ranged from 25 m in July to more than 30 m in September. The zooplankton community is dominated by copepods representing 69 % to 83 % of total zooplankton. Spatial and temporal variation of copepods in relation to environmental factors shows their close relationship with the hydrodynamic features of the water column. Thermal stratification in the column, established in summer, supports copepod development. In fact, copepod abundance increases gradually with rising water temperature and salinity, starting from the beginning of thermal stratification (May–June 2006) and lasting until its completion (July 2005 and September 2006). When the water column is well mixed (March 2007), copepod abundance decreased. Our finding shows that temperature and salinity seem to be the most important physical factors and thus strongly influence the taxonomic diversity and distribution of the copepod population. They are characterised by the dominance of Oithona nana, representing 75–86 % of total cyclopoid abundance. The most abundant species during the stratification period were O. nana, Acartia clausi and Stephos marsalensis in July 2005 and September 2006. However, during the mixing period, Euterpina acutifrons was more abundant, representing 21 % of the total. Unlike the copepod community, which is more abundant during the period of high stratification, phytoplankton proliferates during semi-mixed conditions.     

A new insight for real-time wastewater quality prediction using hybridized kernel-based extreme learning machines with advanced optimization algorithms

Environmental Science and Pollution Research - Accurate prediction of inlet chemical oxygen demand (COD) is vital for better planning and management of wastewater treatment plants. The COD values...