Recovery and reuse of ammonium from wastewater treatment plants : an application for agriculture

In wastewater treatment plants based on anaerobic digestion, supernatant and outflows from sludge dewatering systems contain significantly high amount of ammonium. Generally, these waters are returned to the head of wastewater treatment plant (WWTP), thereby increasing the total nitrogen load of the influent flow. Ammonium from these waters can be recovered and commercially utilised using novel ion-exchange materials. Mackinnon et al. have described an approach for removal and recovery of ammonium from side stream centrate returns obtained from anaerobic digester of a typical WWTP. Most of the ammonium from side streams can potentially be removed, which significantly reduces overall inlet demand at a WWTP. However, the extent of reduction achieved depends on the level of ammonium and flow-rate in the side stream. The exchange efficiency of the ion-exchange material, MesoLite, used in the ammonium recovery process deteriorates with long-term use due to mechanical degradation and use of regenerant. To ensure that a sustainable process is utilised a range of potential applications for this “spent” MesoLite have been evaluated. The primary focus of evaluations has been use of ammonium-loaded MesoLite as a source of nitrogen and growth medium for plants. A MesoLite fertiliser has advantage over soluble fertilisers in that N is held on an insoluble matrix and is gradually released according to exchange equilibria. Many conventional N fertilisers are water-soluble and thus, instantly release all applied N into the soil solution. Loss of nutrient commonly occurs through volatilisation and/or leaching. On average, up to half of the N delivered by a typical soluble fertiliser can be lost through these processes. In this context, use of ammonium-loaded MesoLite as a fertiliser has been evaluated using standard greenhouse and field-based experiments for low fertility soils. Rye grass, a suitable test species for greenhouse trials, was grown in 1kg pots over a period of several weeks with regular irrigation. Nitrogen was applied at a range of rates using a chemical fertiliser as a control and using two MesoLite fertilisers. All other nutrients were applied in adequate amounts. All treatments were replicated three times. Plants were harvested after four weeks, and dry plant mass and N concentrations were determined. At all nitrogen application rates, ammonium-loaded MesoLite produced higher plant mass than plants fertilised by the chemical fertiliser. The lower fertiliser effectiveness of the chemical fertliser is attributed to possible loss of some N through volatilisation. The MesoLite fertilisers did not show any adverse effect on availability of macro and trace nutrients, as shown by lack of deficiency symptoms, dry matter yield and plant analyses. Nitrogen loaded on to MesoLite in the form of exchanged ammonium is readily available to plants while remaining protected from losses via leaching and volatilisation. Spent MesoLite appears to be a suitable and effective fertiliser for a wide range of soils, particularly sandy soils with poor nutrient holding capacity.

Treatment efficacy of algae-based sewage treatment plants

Lagoons have been traditionally used in India for decentralized treatment of domestic sewage. These are cost effective as they depend mainly on natural processes without any external energy inputs. This study focuses on the treatment efficiency of algae-based sewage treatment plant (STP) of 67.65 million liters per day (MLD) capacity considering the characteristics of domestic wastewater (sewage) and functioning of the treatment plant, while attempting to understand the role of algae in the treatment. STP performance was assessed by diurnal as well as periodic investigations of key water quality parameters and algal biota. STP with a residence time of 14.3 days perform moderately, which is evident from the removal of total chemical oxygen demand (COD) (60 %), filterable COD (50 %), total biochemical oxygen demand (BOD) (82 %), and filterable BOD (70 %) as sewage travels from the inlet to the outlet. Furthermore, nitrogen content showed sharp variations with total Kjeldahl nitrogen (TKN) removal of 36 %; ammonium N (NH4-N) removal efficiency of 18 %, nitrate (NO3-N) removal efficiency of 22 %, and nitrite (NO2-N) removal efficiency of 57.8 %. The predominant algae are euglenoides (in facultative lagoons) and chlorophycean members (maturation ponds). The drastic decrease of particulates and suspended matter highlights heterotrophy of euglenoides in removing particulates.

Investigating the removal of some pharmaceutical compounds in hospital wastewater treatment plants operating in Saudi Arabia

The concentrations of 12 pharmaceutical compounds (atenolol, erythromycin, cyclophosphamide, paracetamol, bezafibrate, carbamazepine, ciprofloxacin, caffeine, clarithromycin, lidocaine, sulfamethoxazole and Nacetylsulfamethoxazol (NACS)) were investigated in the influents and effluents of two hospital wastewater treatment plants (HWWTPs) in Saudi Arabia. The majority of the target analytes were detected in the influent samples apart from bezafibrate, cyclophosphamide, and erythromycin. Caffeine and paracetamol were detected in the influent at particularly high concentrations up to 75 and 12 ug/L, respectively. High removal efficiencies of the pharmaceutical compounds were observed in both HWWTPs, with greater than 90 % removal on average. Paracetamol, sulfamethoxazole, NACS, ciprofloxacin, and caffeine were eliminated by between >95 and >99 % on average. Atenolol, carbamazepine, and clarithromycin were eliminated by >86 % on average. Of particular interest were the high removal efficiencies of carbamazepine and antibiotics that were achieved by the HWWTPs; these compounds have been reported to be relatively recalcitrant to biological treatment and are generally only partially removed. Elevated temperatures and high levels of sunlight were considered to be the main factors that enhanced the removal of these compounds.

COD and NH4-N Estimation in the Inflow of Wastewater Treatment Plants using Machine Learning Techniques

The in-line measurement of COD and NH4-N in the WWTP inflow is crucial for the timely monitoring of biological wastewater treatment processes and for the development of advanced control strategies for optimized WWTP operation. As a direct measurement of COD and NH4-N requires expensive and high maintenance in-line probes or analyzers, an approach estimating COD and NH4-N based on standard and spectroscopic in-line inflow measurement systems using Machine Learning Techniques is presented in this paper. The results show that COD estimation using Radom Forest Regression with a normalized MSE of 0.3, which is sufficiently accurate for practical applications, can be achieved using only standard in-line measurements. In the case of NH4-N, a good estimation using Partial Least Squares Regression with a normalized MSE of 0.16 is only possible based on a combination of standard and spectroscopic in-line measurements. Furthermore, the comparison of regression and classification methods shows that both methods perform equally well in most cases.

Fungal contamination in two Portuguese wastewater treatment plants

The presence of filamentous fungi was detected in wastewater and air collected at wastewater treatment plants (WWTP) from several European countries. The aim of the present study was to assess fungal contamination in two WWTP operating in Lisbon. In addition, particulate matter (PM) contamination data was analyzed. To apply conventional methods, air samples from the two plants were collected through impaction using an air sampler with a velocity air rate of 140 L/min. Surfaces samples were collected by swabbing the surfaces of the same indoor sites. All collected samples were incubated at 27°C for 5 to 7 d. After lab processing and incubation of collected samples, quantitative and qualitative results were obtained with identification of the isolated fungal species. For molecular methods, air samples of 250 L were also collected using the impinger method at 300 L/min airflow rate. Samples were collected into 10 ml sterile phosphate-buffered saline with 0.05% Triton X-100, and the collection liquid was subsequently used for DNA extraction. Molecular identification of Aspergillus fumigatus and Stachybotrys chartarum was achieved by real-time polymerase chain reaction (RT-PCR) using the Rotor-Gene 6000 qPCR Detection System (Corbett). Assessment of PM was also conducted with portable direct-reading equipment (Lighthouse, model 3016 IAQ). Particles concentration measurement was performed at five different sizes: PM0.5, PM1, PM2.5, PM5, and PM10. Sixteen different fungal species were detected in indoor air in a total of 5400 isolates in both plants. Penicillium sp. was the most frequently isolated fungal genus (58.9%), followed by Aspergillus sp. (21.2%) and Acremonium sp. (8.2%), in the total underground area. In a partially underground plant, Penicillium sp. (39.5%) was also the most frequently isolated, also followed by Aspergillus sp. (38.7%) and Acremonium sp. (9.7%). Using RT-PCR, only A. fumigatus was detected in air samples collected, and only from partial underground plant. Stachybotrys chartarum was not detected in any of the samples analyzed. The distribution of particle sizes showed the same tendency in both plants; however, the partially underground plant presented higher levels of contamination, except for PM2.5. Fungal contamination assessment is crucial to evaluating the potential health risks to exposed workers in these settings. In order to achieve an evaluation of potential health risks to exposed workers, it is essential to combine conventional and molecular methods for fungal detection. Protective measures to minimize worker exposure to fungi need to be adopted since wastewater is the predominant internal fungal source in this setting.

Influence of seasons and sampling strategy on assessment of bioaerosols in sewage treatment plants in Switzerland

An assessment of sewage workers' exposure to airborne cultivable bacteria, fungi and inhaled endotoxins was performed at 11 sewage treatment plants. We sampled the enclosed and unenclosed treatment areas in each plant and evaluated the influence of seasons (summer and winter) on bioaerosol levels. We also measured personal exposure to endotoxins of workers during special operation where a higher risk of bioaerosol inhalation was assumed. Results show that only fungi are present in significantly higher concentrations in summer than in winter (2331 +/- 858 versus 329 +/- 95 CFU m(-3)). We also found that there are significantly more bacteria in the enclosed area, near the particle grids for incoming water, than in the unenclosed area near the aeration basins (9455 +/- 2661 versus 2435 +/- 985 CFU m(-3) in summer and 11 081 +/- 2299 versus 2002 +/- 839 CFU m(-3) in winter). All bioaerosols were frequently above the recommended values of occupational exposure. Workers carrying out special tasks such as cleaning tanks were exposed to very high levels of endotoxins (up to 500 EU m(-3)) compared to routine work. The species composition and concentration of airborne Gram-negative bacteria were also studied. A broad spectrum of different species within the Pseudomonadaceae and the Enterobacteriaceae families were predominant in nearly all plants investigated. [Authors]

High occurrence of hepatitis E virus in samples from wastewater treatment plants in Switzerland and comparison with other enteric viruses.

Hepatitis E virus (HEV) is responsible for many enterically transmitted viral hepatitides around the world. It is currently one of the waterborne diseases of global concern. In industrialized countries, HEV appears to be more common than previously thought, even if it is rarely virulent. In Switzerland, seroprevalence studies revealed that HEV is endemic, but no information was available on its environmental spread. The aim of this study was to investigate -using qPCR- the occurrence and concentration of HEV and three other viruses (norovirus genogroup II, human adenovirus-40 and porcine adenovirus) in influents and effluents of 31 wastewater treatment plants (WWTPs) in Switzerland. Low concentrations of HEV were detected in 40 out of 124 WWTP influent samples, showing that HEV is commonly present in this region. The frequency of HEV occurrence was higher in summer than in winter. No HEV was detected in WWTP effluent samples, which indicates a low risk of environmental contamination. HEV occurrence and concentrations were lower than those of norovirus and adenovirus. The autochthonous HEV genotype 3 was found in all positive samples, but a strain of the non-endemic and highly pathogenic HEV genotype I was isolated in one sample, highlighting the possibility of environmental circulation of this genotype. A porcine fecal marker (porcine adenovirus) was not detected in HEV positive samples, indicating that swine are not the direct source of HEV present in wastewater. Further investigations will be necessary to determine the reservoirs and the routes of dissemination of HEV.

Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelation between variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

Application of a support system to the design of wastewater treatment plants

This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically the compliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process