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.

Tratamento de águas residuais

In this work, it is intended to expose the state of the art relating the use of microalgae in wastewater treatment. Nitrogen and phosphorous removal with microalgae is a common process. Biosorption by microlgae is an alternative to traditional treatment processes of metal ions removal. Neste trabalho pretende-se expor, de uma forma simples, o estado da arte no que diz respeito à utilização de microalgas para tratamento de águas residuais. São abordadas, com algum detalhe, as utilizações das microalgas para remoção de nutrientes e de metais pesadas de águas residuais.

Investigation of polyhydroxyalkanoate production by an activated sludge microbial consortium treating artificial dairy wastewater

Petrochemical plastics/polymers are a common feature of day to day living as they occur in packaging, furniture, mobile phones, computers, construction equipment etc. However, these materials are produced from non-renewable materials and are resistant to microbial degradation in the environment. Considerable research has therefore been carried out into the production of sustainable, biodegradable polymers, amenable to microbial catabolism to CO2 and H2O. A key group of microbial polyesters, widely considered as optimal replacement polymers, are the Polyhydroxyalkaonates (PHAs). Primary research in this area has focused on using recombinant pure cultures to optimise PHA yields, however, despite considerable success, the high costs of pure culture fermentation have thus far hindered the commercial viability of PHAs thus produced. In more recent years work has begun to focus on mixed cultures for the optimisation of PHA production, with waste incorporations offering optimal production cost reductions. The scale of dairy processing in Ireland, and the high organic load wastewaters generated, represent an excellent potential substrate for bioconversion to PHAs in a mixed culture system. The current study sought to investigate the potential for such bioconversion in a laboratory scale biological system and to establish key operational and microbial characteristics of same. Two sequencing batch reactors were set up and operated along the lines of an enhanced biological phosphate removal (EBPR) system, which has PHA accumulation as a key step within repeated rounds of anaerobic/aerobic cycling. Influents to the reactors varied only in the carbon sources provided. Reactor 1 received artificial wastewater with acetate alone, which is known to be readily converted to PHA in the anaerobic step of EBPR. Reactor 2 wastewater influent contained acetate and skim milk to imitate a dairy processing effluent. Chemical monitoring of nutrient remediation within the reactors as continuously applied and EBPR consistent performances observed. Qualitative analysis of the sludge was carried out using fluorescence microscopy with Nile Blue A lipophillic stain and PHA production was confirmed in both reactors. Quantitative analysis via HPLC detection of crotonic acid derivatives revealed the fluorescence to be short chain length Polyhydroxybutyrate, with biomass dry weight accumulations of 11% and 13% being observed in reactors 1 and 2, respectively. Gas Chromatography-Mass Spectrometry for medium chain length methyl ester derivatives revealed the presence of hydroxyoctanoic, -decanoic and -dodecanoic acids in reactor 1. Similar analyses in reactor 2 revealed monomers of 3-hydroxydodecenoic and 3-hydroxytetradecanoic acids. Investigation of the microbial ecology of both reactors as conducted in an attempt to identify key species potentially contributing to reactor performance. Culture dependent investigations indicated that quite different communities were present in both reactors. Reactor 1 isolates demonstrated the following species distributions Pseudomonas (82%), Delftia acidovorans (3%), Acinetobacter sp. (5%) Aminobacter sp., (3%) Bacillus sp. (3%), Thauera sp., (3%) and Cytophaga sp. (3%). Relative species distributions among reactor 2 profiled isolates were more evenly distributed between Pseudoxanthomonas (32%), Thauera sp (24%), Acinetobacter (24%), Citrobacter sp (8%), Lactococcus lactis (5%), Lysinibacillus (5%) and Elizabethkingia (2%). In both reactors Gammaproteobacteria dominated the cultured isolates. Culture independent 16S rRNA gene analyses revealed differing profiles for both reactors. Reactor 1 clone distribution was as follows; Zooglea resiniphila (83%), Zooglea oryzae (2%), Pedobacter composti (5%), Neissericeae sp. (2%) Rhodobacter sp. (2%), Runella defluvii (3%) and Streptococcus sp. (3%). RFLP based species distribution among the reactor 2 clones was as follows; Runella defluvii (50%), Zoogloea oryzae (20%), Flavobacterium sp. (9%), Simplicispira sp. (6%), Uncultured Sphingobacteria sp. (6%), Arcicella (6%) and Leadbetterella bysophila (3%). Betaproteobacteria dominated the 16S rRNA gene clones identified in both reactors. FISH analysis with Nile Blue dual staining resolved these divergent findings, identifying the Betaproteobacteria as dominant PHA accumulators within the reactor sludges, although species/strain specific allocations could not be made. GC analysis of the sludge had indicated the presence of both medium chain length as well short chain length PHAs accumulating in both reactors. In addition the cultured isolates from the reactors had been identified previously as mcl and scl PHA producers, respectively. Characterisations of the PHA monomer profiles of the individual isolates were therefore performed to screen for potential novel scl-mcl PHAs. Nitrogen limitation driven PHA accumulation in E2 minimal media revealed a greater propensity among isoates for mcl-pHA production. HPLC analysis indicated that PHB production was not a major feature of the reactor isolates and this was supported by the low presence of scl phaC1 genes among PCR screened isolates. A high percentage distribution of phaC2 mcl-PHA synthase genes was recorded, with the majority sharing high percentage homology with class II synthases from Pseudomonas sp. The common presence of a phaC2 homologue was not reflected in the production of a common polymer. Considerable variation was noted in both the monomer composition and ratios following GC analysis. While co-polymer production could not be demonstrated, potentially novel synthase substrate specificities were noted which could be exploited further in the future.

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.

Organic nitrogen in PM2.5 aerosol at a forest site in the Southeast US

There is growing evidence that organo-nitrogen compounds may constitute a significant fraction of the aerosol nitrogen (N) budget. However, very little is known about the abundance and origin of this aerosol fraction. In this study, the concentration of organic nitrogen (ON) and major inorganic ions in PM2.5 aerosol were measured at the Duke Forest Research Facility near Chapel Hill, NC, during January and June of 2007. A novel on-line instrument was used, which is based on the Steam Jet Aerosol Collector (SJAC) coupled to an on-line total carbon/total nitrogen analyzer and two on-line ion chromatographs. The concentration of ON was determined by tracking the difference in concentrations of total nitrogen and of inorganic nitrogen (determined as the sum of N-ammonium and N-nitrate). The time resolution of the instrument was 30 min with a detection limit for major aerosol components of ∼0.1 mu;gm-3. Nitrogen in organic compounds contributed ∼33% on average to the total nitrogen concentration in PM2.5, illustrating the importance of this aerosol component. Absolute concentrations of ON, however, were relatively low (lt;1.0 mu;gm-3) with an average of 0.16 mu;gm-3. The absolute and relative contribution of ON to the total aerosol nitrogen budget was practically the same in January and June. In January, the concentration of ON tended to be higher during the night and early morning, while in June it tended to be higher during the late afternoon and evening. Back-trajectories and correlation with wind direction indicate that higher concentrations of ON occur in air masses originating over the continental US, while marine air masses are characterized by lower ON concentrations. The data presented in this study suggests that ON has a variety of sources, which are very difficult to quantify without information on chemical composition of this important aerosol fraction.

Radium and barium removal through blending hydraulic fracturing fluids with acid mine drainage.

Wastewaters generated during hydraulic fracturing of the Marcellus Shale typically contain high concentrations of salts, naturally occurring radioactive material (NORM), and metals, such as barium, that pose environmental and public health risks upon inadequate treatment and disposal. In addition, fresh water scarcity in dry regions or during periods of drought could limit shale gas development. This paper explores the possibility of using alternative water sources and their impact on NORM levels through blending acid mine drainage (AMD) effluent with recycled hydraulic fracturing flowback fluids (HFFFs). We conducted a series of laboratory experiments in which the chemistry and NORM of different mix proportions of AMD and HFFF were examined after reacting for 48 h. The experimental data combined with geochemical modeling and X-ray diffraction analysis suggest that several ions, including sulfate, iron, barium, strontium, and a large portion of radium (60-100%), precipitated into newly formed solids composed mainly of Sr barite within the first ∼ 10 h of mixing. The results imply that blending AMD and HFFF could be an effective management practice for both remediation of the high NORM in the Marcellus HFFF wastewater and beneficial utilization of AMD that is currently contaminating waterways in northeastern U.S.A.

Denitrification and inference of nitrogen sources in the karstic Floridan Aquifer

Aquifer denitrification is among the most poorly constrained fluxes in global and regional nitrogen budgets. The few direct measurements of denitrification in groundwaters provide limited information about its spatial and temporal variability, particularly at the scale of whole aquifers. Uncertainty in estimates of denitrification may also lead to underestimates of its effect on isotopic signatures of inorganic N, and thereby confound the inference of N source from these data. In this study, our objectives are to quantify the magnitude and variability of denitrification in the Upper Floridan Aquifer (UFA) and evaluate its effect on N isotopic signatures at the regional scale. Using dual noble gas tracers (Ne, Ar) to generate physical predictions of N2 gas concentrations for 112 observations from 61 UFA springs, we show that excess (i.e. denitrification-derived) N2 is highly variable in space and inversely correlated with dissolved oxygen (O2). Negative relationships between O2 and δ15N NO3 across a larger dataset of 113 springs, well-constrained isotopic fractionation coefficients, and strong 15N:18O covariation further support inferences of denitrification in this uniquely organic-matter-poor system. Despite relatively low average rates, denitrification accounted for 32 % of estimated aquifer N inputs across all sampled UFA springs. Back-calculations of source δ15N NO3 based on denitrification progression suggest that isotopically-enriched nitrate (NO3-) in many springs of the UFA reflects groundwater denitrification rather than urban- or animal-derived inputs. © Author(s) 2012.

Impacts of Mountaintop Removal Coal Mining on the Mud River, West Virginia: Selenium Accumulation, Trophic Transfer, and Toxicity in Fish

Selenium (Se) is a micronutrient necessary for the function of a variety of important enzymes; Se also exhibits a narrow range in concentrations between essentiality and toxicity. Oviparous vertebrates such as birds and fish are especially sensitive to Se toxicity, which causes reproductive impairment and defects in embryo development. Selenium occurs naturally in the Earth's crust, but it can be mobilized by a variety of anthropogenic activities, including agricultural practices, coal burning, and mining.

Mountaintop removal/valley fill (MTR/VF) coal mining is a form of surface mining found throughout central Appalachia in the United States that involves blasting off the tops of mountains to access underlying coal seams. Spoil rock from the mountain is placed into adjacent valleys, forming valley fills, which bury stream headwaters and negatively impact surface water quality. This research focused on the biological impacts of Se leached from MTR/VF coal mining operations located around the Mud River, West Virginia.

In order to assess the status of Se in a lotic (flowing) system such as the Mud River, surface water, insects, and fish samples including creek chub (Semotilus atromaculatus) and green sunfish (Lepomis cyanellus) were collected from a mining impacted site as well as from a reference site not impacted by mining. Analysis of samples from the mined site showed increased conductivity and Se in the surface waters compared to the reference site in addition to increased concentrations of Se in insects and fish. Histological analysis of mined site fish gills showed a lack of normal parasites, suggesting parasite populations may be disrupted due to poor water quality. X-ray absorption near edge spectroscopy techniques were used to determine the speciation of Se in insect and creek chub samples. Insects contained approximately 40-50% inorganic Se (selenate and selenite) and 50-60% organic Se (Se-methionine and Se-cystine) while fish tissues contained lower proportions of inorganic Se than insects, instead having higher proportions of organic Se in the forms of methyl-Se-cysteine, Se-cystine, and Se-methionine.

Otoliths, calcified inner ear structures, were also collected from Mud River creek chubs and green sunfish and analyzed for Se content using laser ablation inductively couple mass spectrometry (LA-ICP-MS). Significant differences were found between the two species of fish, based on the concentrations of otolith Se. Green sunfish otoliths from all sites contained background or low concentrations of otolith Se (< 1 µg/g) that were not significantly different between mined and unmined sites. In contrast creek chub otoliths from the historically mined site contained much higher (≥ 5 µg/g, up to approximately 68 µg/g) concentrations of Se than for the same species in the unmined site or for the green sunfish. Otolith Se concentrations were related to muscle Se concentrations for creek chubs (R2 = 0.54, p = 0.0002 for the last 20% of the otolith Se versus muscle Se) while no relationship was observed for green sunfish.

Additional experiments using biofilms grown in the Mud River showed increased Se in mined site biofilms compared to the reference site. When we fed fathead minnows (Pimephales promelas) on these biofilms in the laboratory they accumulated higher concentrations of Se in liver and ovary tissues compared to fathead minnows fed on reference site biofilms. No differences in Se accumulation were found in muscle from either treatment group. Biofilms were also centrifuged and separated into filamentous green algae and the remaining diatom fraction. The majority of Se was found in the diatom fraction with only about 1/3rd of total biofilm Se concentration present in the filamentous green algae fraction

Finally, zebrafish (Danio rerio) embryos were exposed to aqueous Se in the form of selenate, selenite, and L-selenomethionine in an attempt to determine if oxidative stress plays a role in selenium embryo toxicity. Selenate and selenite exposure did not induce embryo deformities (lordosis and craniofacial malformation). L-selenomethionine, however, induced significantly higher deformity rates at 100 µg/L compared to controls. Antioxidant rescue of L-selenomethionime induced deformities was attempted in embryos using N-acetylcysteine (NAC). Pretreatment with NAC significantly reduced deformities in the zebrafish embryos secondarily treated with L-selenomethionine, suggesting that oxidative stress may play a role in Se toxicity. Selenite exposure also induced a 6.6-fold increase in glutathione-S-transferase pi class 2 gene expression, which is involved in xenobiotic transformation. No changes in gene expression were observed for selenate or L-selenomethionine-exposed embryos.

The findings in this dissertation contribute to the understanding of how Se bioaccumulates in a lotic system and is transferred through a simulated foodweb in addition to further exploring oxidative stress as a potential mechanism for Se-induced embryo toxicity. Future studies should continue to pursue the role of oxidative stress and other mechanisms in Se toxicity and the biotransformation of Se in aquatic ecosystems.

Inter-annual variability of precipitation constrains the production response of boreal Pinus sylvestris to nitrogen fertilization

© 2015 Published by Elsevier B.V.Tree growth resources and the efficiency of resource-use for biomass production determine the productivity of forest ecosystems. In nutrient-limited forests, nitrogen (N)-fertilization increases foliage [N], which may increase photosynthetic rates, leaf area index (L), and thus light interception (IC). The product of such changes is a higher gross primary production and higher net primary production (NPP). However, fertilization may also alter carbohydrate partitioning from below- to aboveground, increasing aboveground NPP (ANPP). We analyzed effects of long-term N-fertilization on NPP, and that of long-term carbon storing organs (NPPS) in a Pinus sylvestris forest on sandy soil, a wide-ranging forest type in the boreal region. We based our analyses on a combination of destructive harvesting, consecutive mensuration, and optical measurements of canopy openness. After eight-year fertilization with a total of 70gNm^-2, ANPP was 27±7% higher in the fertilized (F) relative to the reference (R) stand, but although L increased relative to its pre-fertilization values, IC was not greater than in R. On the seventh year after the treatment initiation, the increase of ANPP was matched by the decrease of belowground NPP (78 vs. 92gCm^-2yr^-1; ~17% of NPP) and, given the similarity of IC, suggests that the main effect of N-fertilization was changed carbon partitioning rather than increased canopy photosynthesis. Annual NPPS increased linearly with growing season temperature (T) in both treatments, with an upward shift of 70.2gCm^-2yr^-1 by fertilization, which also caused greater amount of unexplained variation (r²=0.53 in R, 0.21 in F). Residuals of the NPPS-T relationship of F were related to growing season precipitation (P, r²=0.48), indicating that T constrains productivity at this site regardless of fertility, while P is important in determining productivity where N-limitation is alleviated. We estimated that, in a growing season average T (11.5±1.0°C; 33-year-mean), NPPS response to N-fertilization will be nullified with P 31mm less than the mean (325±85mm), and would double with P 109mm greater than the mean. These results suggest that inter-annual variation in climate, particularly in P, may help explaining the reported large variability in growth responses to fertilization of pine stands on sandy soils. Furthermore, forest management of long-rotation systems, such as those of boreal and northern temperate forests, must consider the efficiency of fertilization in terms of wood production in the context of changes in climate predicted for the region.

Interactive Effects of Plant Species and Organic Carbon on Nitrate Removal in Chesapeake Bay Treatment Wetlands

Nitrate from agricultural runoff are a significant cause of algal blooms in estuarine ecosystems such as the Chesapeake Bay. These blooms block sunlight vital to submerged aquatic vegetation, leading to hypoxic areas. Natural and constructed wetlands have been shown to reduce the amount of nitrate flowing into adjacent bodies of water. We tested three wetland plant species native to Maryland, Typha latifolia (cattail), Panicum virgatum (switchgrass), and Schoenoplectus validus (soft-stem bulrush), in wetland microcosms to determine the effect of species combination and organic amendment on nitrate removal. In the first phase of our study, we found that microcosms containing sawdust exhibited significantly greater nitrate removal than microcosms amended with glucose or hay at a low nitrate loading rate. In the second phase of our study, we confirmed that combining these plants removed nitrate, although no one combination was significantly better. Furthermore, the above-ground biomass of microcosms containing switchgrass had a significantly greater percentage of carbon than microcosms without switchgrass, which can be studied for potential biofuel use. Based on our data, future environmental groups can make a more informed decision when choosing biofuel-capable plant species for artificial wetlands native to the Chesapeake Bay Watershed.

Algae-Based Purification of Landfill Biogas Using a CO2 Removal System and Helical Photobioreactor in Series

Biogas is a mixture of methane and other gases. In its crude state, it contains carbon dioxide (CO2) that reduces its energy efficiency and hydrogen sulfide (H2S) that is toxic and highly corrosive. Because chemical methods of removal are expensive and environmentally hazardous, this project investigated an algal-based system to remove CO2 from biogas. An anaerobic digester was used to mimic landfill biogas. Iron oxide and an alkaline spray were used to remove H2S and CO2 respectively. The CO2-laden alkali solution was added to a helical photobioreactor where the algae metabolized the dissolved CO2 to generate algal biomass. Although technical issues prevented testing of the complete system for functionality, cost analysis was completed and showed that the system, in its current state, is not economically feasible. However, modifications may reduce operation costs.

Fertilization trial on soybean in Argentine Pampa : boron or nitrogen?

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Variability in water and nitrogen availability at plot scale and its effect on Maize (Zea Mays L.) production

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Fertilization trial on soybean in Argentine Pampa : boron or nitrogen?

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