Impacts Of Pharmaceutical Drugs On Sediment Respiration Biology Essay

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The successful completion of research needs on pharmaceuticals could lead to many outcomes some spanning a wide spectrum of disciplines and aspects of society (Daughton, 2004). This study aims to quantify the effects of the most widely used pharmaceuticals in the in the UK namely Propanolol, Ibuprofen, Diclofenac, Erythromycin and Mefenamic acid as single and multiple stressors of sediment respiration. Each of these pharmaceuticals based on aquatic toxicity data from the literature were highly persistent and the PEC: PNEC ratio (Table 2.31 and 2.32) were comparatively high or exceeded 1 ngl-1 in the aquatic environment of the UK indicating their environmental risk and potential hazards. The specific objectives of this research are to;

Determine the dose-effect relationship of single pharmaceutical compounds on sediment respiration

Determine the dose-effect relationship of a mixture of pharmaceutical compounds on sediment respiration

Conclusions from this experiment would inform regulators and the scientific community in the UK on the effects of these selected pharmaceuticals on water quality and key ecological processes, assisting in the recommendation of procedures to prevent or reduce the negative impact of pharmaceuticals on the benthic and hypoheic environment. Though this experiment would be conducted under aerobic conditions, data from this experiment would provoke critical laboratory and field research needed to quantify the attenuation of pharmaceuticals under anoxic and saturated conditions.

LITERATURE REVIEW

2.1 PHARMACEUTICALS AND PERSONAL CARE PRODUCTS (PPCPs): AN EMERGING CONTAMINANT (EC)

Ferrer and Thurman (2003) defines ECs as "compounds that are not currently covered by existing regulations of water quality, that have not been previously studied, and that are thought to be a possible threat to environmental health and safety". ECs include pharmaceuticals and personal care products (PPCPs), surfactants, new pesticides and pesticide metabolites, plasticizers, flame retardants, insect repellents, disinfection byproducts, endocrine-modulating compounds, nanoparticles, industrial chemicals (new and recently recognized) and biological metabolites and toxins and pathogens (Table 1.11 and 1.12) (Hudkin, 2005; Snow et al., 2008). ECs can be classified as organic or inorganic solids, volatile or nonvolatile, biodegradable or intractable, dissolved, suspended or settleable, liquids or gas, or as one of these mixed with, absorbed onto or dissolved in another and of animal, mineral or vegetable origin (Alley, 2007).

The most abundant class of EC compounds belong to the PPCP class (Terzić et al., 2009). PPCPs comprise thousands of registered formulated end-use products which contain more than 3000 distinct bioactive chemical entities which are ubiquitous pollutants, owing their origins in the environment to their worldwide everyday usage and disposal (Daughton, 2004). Each PPCPs consists of a bioactive substance (usually in low concentration) that are mainly simple to complex organic substances, mixed with a number of auxiliary substances that are designed to be biologically active and to cause very specific effects (Palace et al., 2002). PPCPs in the environment have no geographic boundaries or climatic-use limitations, hence, are discharged wherever people live or visit, regardless of the time of year (Daughton, 2003a; 2003b).

2.2 PPCP CONSUMPTION IN THE UK

Annual production of PPCPs exceeds 1-106 million tonnes worldwide (Daughton and Ternes, 1999). There are approximately 2,000 and 3000 active substances licensed for use on European and the UK markets respectively with many of them already been detected in surface water (Jones et al., 2001; Perazzolo et al., 2010). Records of drug use in the UK in terms of number of prescription items issued kept by the Department of Health (for prescribed drugs) and the Proprietary Association of Great Britain (for over the counter medicines) indicates the most used pharmaceuticals by weight in England in 2000 (Table 1.21) (Fatta et al., 2007) to range from over 10 tons to over 100 tons per year (Paracetamol, Metformin hydrochloride and Ibuprofen) (Jones et al., 2002). However, this type of data is

Table 2.1 Classes of emerging contaminants

Source: de Alda et al. (2003)

Table 1.12. Emerging potential waterborne pathogens.

Polyoma virus

Microsporidia

Mycobacterium avium intracellulare

Adenoviruses

Parvoviruses

Coronaviruses (SARS)

Picobirnaviruses

Circoviruses

Source: Nwachcuku and Gerba, 2004

Table 2.31 The 25 most used pharmaceuticals by weight in England in 2000

Compound name

CAS number

Therapeutic use

Total

prescription

items

dispensed

(x103)

Total

prescription

items where

DDD

information

held (x103)

Coverage

(%)

Amount used per

year (kg)

Detected in UK environment

Paracetamol

103-90-2

Analgesic

10,636

10,636

100

390,954.26

Yes

Metformin hydrochloride

1115-70-4

Antihyperglycaemic

3596

3596

100

205,795.00

No

Ibuprofen

15687-27-1

Analgesic

6683

5422

81

162,209.06

Yes

Amoxycillin

26787-78-0

Antibiotic

12,849

12,849

100

71,466.83

No

Sodium valproate

1069-66-5

Anti-epileptic

1,495

1495

100

47,479.65

No

Sulphasalazine

599-79-1

Antirheumatic

622

622

100

46,430.43

No

Mesalazine (systemic)

89-57-6

Treatment of ulcerative colitis

622

622

100

40,421.72

No

Carbamazepine

298-46-4

Anti-epileptic

2256

2256

100

40,348.75

Yes

Ferrous sulphate

7782-63-0

Iron supplement

2639

2639

100

37,538.52

No

Ranitidine hydrochloride

66357-59-3

Anti-ulcer drug

3770

3770

100

36,319.24

No

Cimetidine

51481-61-9

H2 receptor antagonist

1496

1496

100

35,654.20

No

Naproxen

22204-53-1

Anti-inflammatory

1381

1335

97

35,065.98

Yes

Atenolol

29122-68-7

β-blocker

11,554

11554

100

28,976.55

No

Oxytetracycline

79-57-2

Antibiotic

1195

1195

100

27,195.11

Yes

Erythromycin

114-07-8

Antibiotic

2936

2573

88

26,483.78

Yes

Diclofenac sodium

15307-79-6

Anti-inflammatory and Analgesic

7639

7134

93

26,120.53

Yes

Flucloxacillin sodium

1847-24-1

Antibiotic

2552

2552

100

23,381.47

No

Phenoxymethylpenicillin

87-08-1

Antibiotic

2716

2716

100

22,227.59

No

Allopurinol

315-30-0

Antigout drug

2038

2038

100

22,095.64

No

Diltiazem hydrochloride

33286-22-5

Calcium antagonist

2844

2844

100

21,791.50

No

Gliclazide

21187-98-4

Antihyperglycaemic

3060

3060

100

18,783.11

No

Aspirin

50-78-2

Analgesic

16,769

1305

8

18,105.89

Yes

Quinine sulphate

804-63-7

Muscle relaxant

1633

1633

100

16,731.26

No

Mebeverine hydrochloride

2753-45-9

Antispasmodic

1323

1323

100

15,497.35

No

Mefenamic acid

61-68-7

Anti-inflammatory

544

544

100

14,522.77

No

Figures relate to the Health Authority where the prescription was dispensed not where it was prescribed.

The weight of the chemical dispensed is based on Defined Daily Dose (DDD) information. Note that the DDD data do not cover all individual drugs. The ''coverage'' column indicates for each chemical the percentage of the prescriptions dispensed where DDD data are held. For example, the weight of aspirin dispensed is based on only 8% of prescription items dispensed.

Source: Jones et al. (2002)

often of little use when trying to estimate the amount of drugs and drug metabolites that may find their way into watercourses as the actual quantity of each of the numerous commercial drugs that is ingested/disposed is unknown, contrasting sharply with pesticides in which usage is much better documented and controlled (Jones et al., 2002). Such data can be used as a tool for ranking priorities on the basis of high volume and high activity pharmaceuticals in the UK (ibid.).

Although largely unknown, there is evidence that large quantities of prescription and non-prescription drugs are never consumed and many of these are undoubtedly disposed down toilets or via domestic refuse (Greenwood, 2008). A survey conducted in UK households revealed that two-thirds (63.2%) discard PPCPs in household waste, with the remainder returning them to a pharmacist (21.8%), emptying them into the sink or toilet (11.5%) or taking them to municipal waste sites (3.5%) that sometimes have special waste facilities (Bound and Voulvoulis, 2005).

2.3 SOURCES AND OCCURRENCE OF PHARMACEUTICALS IN THE ENVIRONMENT

Pharmaceuticals may enter the environment through the disposal of unused or expired medications or partially metabolized excrement from humans or animals on a continuous basis via agricultural run-off and aquaculture effluents (commercial animal feeding operations and surface application of manure and biosolids), sanitary sewer from hospitals and residents, industrial discharges, leaching municipal landfills or after wastewater treatment processes, which are generally not designed to remove them (Daughton, 2003a; Daughton, 2003b; Ellis, 2006; Alley, 2007) (Figure 1). During wastewater treatment, the processes acting on pharmaceuticals, metabolites and their conjugates (e.g. Bromochloroacetic acids, Chloral Hydrate, Haloacetonitriles, Trihalomethanes, Cyanogen Chloride, Carboxylic acid, Aldoketoacids and Aldehydes) (Richardson, 2003; Hemminger, 2005) are not fully understood and there are conflicting reports on their biodegradability (95% to <10%) (Jones et al., 2002; Snyder, 2008; Bolong et al., 2009). The elimination efficiency of PPCPs in wastewater treatment plants is still a matter of intensive research though some have already been well-described in the literature (Ahel et al., 1994; Larsen et al., 2004; Clara et al., 2005; Hudkin, 2005; Lindqvist et al., 2005; Phillips et al., 2005; Molinari et al. 2006; Gultekin and Ince, 2007; Santos et al., 2007).

Figure 2.1. Sources and pathways of ECS in the water cycle (Ellis, 2006)

Laboratory and field experiments indicate the persistence of pharmaceuticals in aquatic environments (Lin and Reinhard, 2005). Although there has been no systematic monitoring for the presence of pharmaceuticals in the aquatic environment of the UK, the data available indicate that the concentrations in surface waters will be very low (Jones et al., 2002). A comprehensive study conducted by the U.S. Geological Survey (USGS) on 139 streams found 80% of them to contain PPCP agents in low concentrations (Kolpin et al., 2002). About 70-80 % of drugs administered in fish farms end up in the environment with drug concentrations of antibacterial activity are found in the sediment underneath fish farms (Halling-Sorensen et al., 1998).

The environmental risks of pharmaceuticals, generally identified in soils, plant and animal tissues, groundwater, surface and drinking water in concentrations of parts per billion (µg/l) to parts per trillion (ng/l) (Hemminger, 2005) have captured the attention of scientists and the public, especially in the more developed western countries of North America, the United Kingdom, and Europe (Halling-Sorensen et al., 1998; Kolpin et al., 2002; Larsen et al., 2004).

Astonishingly, little is known about the numbers and types, and trends of occurrence of pharmaceuticals in a large number of watersheds and municipalities even though medications have been in the environment for as long as long as they have been used commercially (Daughton and Ternes, 1999). However, research over these past years in the UK which is primarily focused on the environmental occurrence and effects of endocrine disrupting compounds and antibiotics have accrued evidence that the concentrations of some pharmaceuticals detected in streams and rivers are likely to pose some treat to health and aquatic health (Thiele-Bruhn, 2003). The limited amount of research on pharmaceuticals is in most part probably due to the little experience in environmental issues by human health agencies regulating pharmaceuticals whose actions are practically unknown and their control is an ongoing challenge (Jones et al., 2002). Another reason for this general lack of data is that, until recently, there have been few highly selective and sensitive analytical methods capable of detecting pharmaceutical compounds at low concentrations which might be expected in the environment (Daughton, 2003a; Derksen et al. 2004). These analytical procedures have detection limits, for instance ranging from 0.01 to 0.20 ngl-1 for ibuprofen and 17-ethinylestradiol respectively (Möder et al., 2007). Table 1.31 shows the minimum and maximum concentrations of pharmaceutical compounds detected in the aquatic environment of the United Kingdom.

Where the predicted environmental concentrations (PEC) of pharmaceuticals exceed 0.01 μgl-1 further aquatic fate and effect studies are conducted to access the risk (Jones et al., 2002). The study of Jones et al (2002) concluded that the predicted no-effect concentration (PNEC) based on aquatic toxicity data from the literature is available for a few pharmaceuticals and the PECs for the 25 most used pharmaceuticals (Table 1.32) in the aquatic environment in England exceeded 1 ngl-1 with the PEC: PNEC ratio exceeding one for Paracetamol, Amoxycillin, Oxytetracycline and Mefenamic acid. Some probable invalid assumptions such as no metabolism or breakdown of the drug within man or the sewage system, drug being evenly distributed in usage over time and space, and the non adsorbtion of pharmaceuticals to organic or inorganic colloidal material or bacterial biomass in sewage treatment works or natural water were made during the study. However, the PEC: PNEC values estimated for these pharmaceuticals in the environment is considered uncertain or conservative estimates of risk by some researchers because of the non inclusion of the above assumptions and exclusion of over the counter medicines or illegally acquired drugs. Ferrari et al (2009) study on exposure and ecotoxicity data of six human pharmaceuticals (carbamazepine, clofibric acid, diclofenac, ofloxacin, propranolol, and sulfamethoxazole) in Europe demonstrated that all environmental concentrations (predicted or measured) for each considered pharmaceutical exceeded the 10 ngl-1 cut-off value, showed relatively limited acute toxicity, and carbamazepine and propranolol were inaccurately identified as having negligible risks under the current European draft procedure. Such results lead to discussions on the need of appropriate ecotoxicity tests.

Table 2.3 PECs PNECs and bioconcentration factors for the top 25 UK pharmaceuticals

Compound Name

Amount used (kg)

PEC

(µg l-1)

Data used for PNEC

PNEC

(µg l-1)

PEC:PNEC ratio

Bioconcentraction

factor

Test organism

Test type

Paracetamol

390,954.26

11.96

Daphnia magna

Standard

136

0.09

3.162

11.96

Daphnia magna

Non-standard

9.2

1.29

11.96

Streptocephalus proboscideu

Non-standard

29

0.41

Metformin hydrochloride

205,795.00

6.30

Green alga

Ecosar

511.57

0.01

3.162

Ibuprofen

162,209.06

4.96

Daphnia magna

Standard

9.06

0.55

3.162

4.96

Trichophyton rubrum

Non-standard

5

0.99

Amoxycillin

71,466.83

2.19

Microcystis aeruginosa

Standard

0.0037

588.02

3.162

2.19

Selenastrum capricornutum

Standard

250

0.01

Sodium valproate

47,479.65

1.45

Daphnid

Ecosar

763

0.00

3.162

Sulphasalazine

46,430.43

1.42

Daphnid

Ecosar

38.99

0.04

3.162

Mesalazine (systemic)

40,421.72

1.24

Oncorhynchus tshawytscha

Standard

10000

1.23E-0.4

3.162

1.24

Green alga

Ecosar

6078.335

2.02E-04

Carbamazepine

40,348.75

1.23

Daphnid

Ecosar

6.359

0.19

15.36

Ferrous sulphate

37,538.52

1.15

Daphnia pulex

Standard

7.1

0.16

3.162

Ranitidine hydrochloride

36,319.24

1.11

No data

No data

No data

No data

No data

Cimetidine

35,654.20

1.09

No data

No data

740

1.47E-03

3.162

Naproxen

35,065.98

1.07

No data

No data

128

0.01

3.162

Atenolol

28,976.55

0.89

Green algae

Ecosar

77.7

0.01

3.162

Oxytetracycline

27,195.11

0.83

Microcystis aeruginosa

Standard

0.23

3.60

3.162

0.83

Selenastrum capricornutum

Standard

4.5

0.18

Erythromycin

26,483.78

0.81

No data

No data

74

0.01

45.31

0.81

Penaeus vannamei

Standard

22.7

0.04

Diclofenac sodium

26,120.53

0.80

Daphnid

Ecosar

138.74

0.01

3.162

Flucloxacillin sodium

23,381.47

0.72

No data

No data

No data

No data

No data

Phenoxymethylpenicillin

22,227.59

0.68

Daphnid

Ecosar

177

3.82E-03

3.162

Allopurinol

22,095.64

0.68

Daphnid

Ecosar

80.8

0.01

3.162

Diltiazem hydrochloride

21,791.50

0.67

Green algae

Ecosar

1.943

0.34

23.93

Gliclazide

18,783.11

0.57

Green algae

Ecosar

1.335

0.43

8.556

Aspirin

18,105.89

0.55

Daphnia magna

Standard

61

0.01

3.162

Quinine sulphate

16,731.26

0.51

Penaeus setiferus

Standard

20000

2.55E-05

5.623

0.51

Green algae

Ecosar

0.959

0.53

Mebeverine hydrochloride

15,497.35

0.47

Green algae

Ecosar

0.638

0.74

3.162

Mefenamic acid

14,522.77

0.44

Daphnid

Ecosar

0.428

1.03

5.623

Source: Jones et al. (2002)

2.4 FATE, EFFECTS AND RISK OF PHARMACEUTICALS ON AQUATIC ECOSYSTEMS

The environmental fates and effects of many pharmaceuticals on the environment are poorly known, although considerable persistence and bioaccumulation in organisms and environmental systems have been reported (Daughton and Ternes, 1999). Many studies and reviews have documented adverse effects of PPCPs in environments ranging from disruptions in physiological processes leading to morbidity and mortality, impaired reproductive, other ecological functions and loss of aesthetic appeal (Daughton and Ternes, 1999; Halling- Sorensen et al., 1998; Ferrari et al., 2003; Boxall, 2004; Cunningham et al., 2006). Pharmaceuticals evoke profound linear and variably toxicological effects on the environment which are typical to their active substances (Titz and Doll, 2009), even at very low concentrations which range from being discriminating to elusive (Table 2.4). Fewer studies have been conducted on organisms such as bacteria (eg. cyanobacteria), algae (e.g. Daphnia magna) macrophytes (e.g. Lemna sp. and Myriophyllum sibiricum) and invertebrates (crustaceans, mussels, and macroinvertebrates) even though they play vital roles in river ecosystem processes (Wollenberger et al., 2000; Ferrari et al., 2003; Brian et al., 2004; Pomati et al., 2004; Oetken et a!. 2005; Gagne et al., 2006).

The major concern to stakeholders is not necessarily the acute effects to non-target species since these are conformable to monitoring once they are understood, but rather, the manifestation of indiscernible effects in aquatic organisms and ecological systems that can accumulate over time to yield truly profound changes that seem to arise from nowhere and would otherwise have been attributed to "natural" change or adaptation (Daughton and Ternes, 1999). The critical question in the field of pharmaceutical research is whether these low-level, chronic exposures adversely impact on the ecological processes of river ecosystem and possibly a near extinction of some species. To date, there are insufficient research results to derive well-substantiated and complete dose-effect relationships and there is the general difficulty in determining chronic effects of pharmaceuticals on biota and ecological systems due to large number of contamination agents, their metabolites, and diversity of organisms concerned (Titz and Doll, 2009).

There has been extensive research on individual pharmaceuticals which usually have the same mode of action and effects but some questions raised by researchers are the possibility of synergistic effects of pharmaceuticals on biota and ecological processes (Jones et al., 2002). The lack of chronic toxicity data for the majority of pharmaceuticals is a major hindrance to their adequate risk appraisal to enable their sustainable management remains a major concern (Alley, 2007, Hansen, 2007).

2.5 PHARMACEUTICALS AS SINGLE AND MULTIPLE STRESSORS

Acute and chronic toxicity tests are important in consistently assessing the toxicity of a compound but the results validity from such tests must be interpreted with care as these studies (laboratory and field) have their associated problems. To date, there is insufficient ecotoxicity, physicochemical and biodegradability data on chronic and specific actions, as well as the influence of most pharmaceutical agents as single or multiple chemical stressors (simultaneously or sequentially) on ecological processes in ecosystems for performing a complete risk evaluation (Daughton, 2004; Derksen et al. 2004).

Table 2.4. Reported subtle effects of phramaceuticals on aquatic and terrestrial organisms

Source: Boxall (2004)

Single substance toxicity studies are generally laboratory-based, different to the exposure of organisms to a mixture of pharmaceuticals in the natural environment. Kolpin et al (2002) and Daughton and Ternes (1999) notes that pharmaceuticals act in concert with others since they are not isolated in the environment, producing complex and unpredictable effects. However, research into the effects of mixed pharmaceuticals has only recently come under review (Brian et al., 2004). Measurable concentrations (16 and 195 ng l-1) of pharmaceutical mixtures, including diclofenac , mefenamic acid and propranolol have been discovered after analysis of estuarine waters around the UK (Thomas and Hilton, 2004). More than 80 pharmaceutical compounds were detected by Heberer (2002) during a review of some studies on the occurrence and fate of pharmaceutical products. Experiments conducted by Monteiro and Boxall (2010) assessing the degradation behaviour of a mixture of naproxen, carbamazepine, and fluoxetine and the antibiotic sulfamethazine, fluoxetine and carbamazepine concluded that the pharmaceuticals persistence in biosolids, soils and soil-biosolid mixtures were comparable to that detected in the single compound studies. Nevertheless, the rate of degradation of naproxen in biosolids, soils and soil-biosolid mixtures was significantly slower (3.1 to 6.9 d) than in the single-compound studies. The rate of pharmaceutical degradation had no relationship with soil physicochemical properties and soil bioactivity. Cleuvers, (2004, 2005) reported the toxicity of a mixture of the anti-inflammatory drugs diclofenac, ibuprofen, naproxen, and acetylsalicylic acid, and three β-blockers on Daphnia sp as considerable, even at concentrations at which the single substances showed no, or only very slight effects and the toxicity of the mixture could be predicted accurately using the concept of concentration addition.

There are uncertainties about the possible environmental effects of pharmaceutical mixtures and the possibility of health effects from chemicals that have not yet been detected (Debroux, 2007). There are only a few studies dealing with the potential range of effects of mixtures of pharmaceuticals, thus further toxicity studies is warranted to better understand the fate and effects of pharmaceuticals on a larger range of environmental matrixes including biosolids, soils and soil-biosolid types (Fent et al., 2006; Monteiro and Boxall, 2010).

In filling the knowledge gap between acute and chronic studies, the relationship between short term and long-term exposure of an organism to concentrations of test substance many times greater than those likely to be encountered in the environment are assumed to mimic longer exposure to much lower, environmentally realistic concentrations (Crane et al., 2006). However, Montforts (2006) discovered differences in the order of magnitude between observed and predicted levels (in soils) of antibiotics used in intensive pig and poultry rearing in the Netherlands because of uncertainties added by local heterogeneities (variation in soil types, and properties between areas). Additional research is required in the evaluation of the effects of chronic exposure to low levels of compounds, and the relationship between this and acute toxicity (Jones et al., 2002).

2.6 SEDIMENT - PHARMACEUTICAL INTERACTIONS

Many of the potential ecotoxicological tests presently differ in endpoints and sensitivities; hence, there is the need for comparative studies for a range of substances to identify the most relevant, representative and sensitive test species (Crane et al., 2006; Fent et al., 2006). Though ecotoxicity data on plants, fishes, invertebrates (algae, crustaceans) is available on the majority of pharmaceuticals, there were few ecotoxicity data in the literature reviewed for the terrestrial environment and ecological processes such as sediment metabolism (respiration and photosynthesis) which are core to the function and sustenance of aquatic ecosystems.

The fate of pharmaceutical compounds in surface waters has been well studied in microcosm systems or in laboratory-based batch experiments or taking multiple samples along the path of a river but the fate of pharmaceuticals in bed sediments have been minimally studied (research focusing on estrogens and antibiotics) though it can provide clues as to their potential pharmaceutical removal processes from surface waters (Castiglioni et al., 2006; Hernando et al., 2006). Sediments compartments serve as a pharmaceutical sink in the environment (Steinman and Midholland, 1996). Sediments of varying composition and particles may be differentially contaminated or contain a suite of contaminants (Benton et al., 2009). Pharmaceuticals such as antibiotics are biotransformed in sediments, yielding metabolites of antibiotic potency which persist in the soil matrix with residual concentrations in sediments ranging from a few g up to g kg-1 corresponding to those found for pesticides (Martins et al., 2008). The recharge of groundwater with contaminated surface water may cause pharmaceutical residues to move to groundwater (Drewes and Shore, 2001).

Soption and accumulation of pharmaceuticals in sediments which might exceed their carrying capacity pose a future problem to groundwater in the UK which is perceived to be safe for drinking because of the purification properties of the soils and rocks. Pharmaceuticals and their metabolites have been found in groundwaters in several parts of the world (Khetan & Collins, 2007). Kahle and Stamm (2007) research with the beta-blockers metoprolol, propranolol and nadolol established that hydrophobicity is essential in the adsorption of these compounds to aquifer-mineral surfaces. Global sediment/water pseudo-partitioning coefficients of 305-1267, 91-402 and 20-517 L kg-1 were recorded for the antibiotics tetracyclines, macrolides and sulphonamides respectively in the sediment phase indicating the tendency for high accumulation of pharmaceuticals in sediments following entry to the aquatic environment (Kim and Carlson, 2007). Drillia et al. (2005) study of the sorption and mobility of six pharmaceuticals (carbamazepine, sulfamehtoxazole, ofloxacin, diclofenac, clofibric acid, and propanolol), concluded that leaching was around 100 % for the clofibric acid which was weakly adsorbed but no leaching was detected for the strongly adsorbed ofloxacin. Research on soil-aquifer treatment of steroidal hormones concluded that mobility of androgens and estrogens in subsurface systems were low with both estriol and testosterones not detected (< 0.6 ngl-1) in groundwater. The low concentrations and the non-detectability of some pharmaceuticals were due to adsorption to the soil matrix and the presence of bioactivity regardless of the dominating redox reaction (Aerobic vs. Anoxic) or the type of organic matrix present (Mansell and Drewes, 2004). Biodegradation data indicates Aspirin, Paracetamol, Ibuprofen, Mefenamic acid and Diclofenac are readily biodegradable with Erythromycin slowly degrading and all these compounds possesses the high potential to almost exclusively sorb to sludge and sediments and accumulate in the food chain, leaving only a small percentage of the original concentration in the effluent (Kunkel and Radke, 2008; Ramil, 2010). Food items from the contaminated benthos may be the main contributor to the transfer of bioaccumulated pharmaceuticals up the food web (Maul et al., 2006).

Though adsorption of pharmaceuticals dictates leaching rate into groundwater there are various mechanisms for the attenuation of pharmaceuticals in the aquatic system (Drewes and Shore, 2001). Research indicates that pharmaceuticals receive additional treatment (soil-aquifer treatment) as it moves through the underground formations which substantially remove pharmaceuticals (Drewes et al., 2007). However, attenuation rates vary depending on the geophysicochemical properties of the subsurface and the type of pharmaceutical.

Many field studies to examine the fate of selected pharmaceuticals (blood lipid regulators, analgesics, anti-inflammatories, blood viscosity agents, and antiepileptics) during ground water recharge, have shown significant attenuation of pharmaceuticals during subsurface transport (Drewes and Shore, 2001; Drewes et al., 2002; Snyder et al., 2004). The concentrations of caffeine, analgesic (e.g. diclofenac), anti-inflammatory drugs (e.g. ibuprofen), and blood lipid regulators (e.g. gemfibrozil) were near or below the detection limit due to intimate contact with soils, longer retention times (< six months), and aerobic and anaerobic biodegradation during ground water recharge (Drewes and Heberer, 2002; Drewes et al., 2007). Mansell et al. (2004) demonstrated that a retention time of 21 days attenuated hormones to non detectable concentrations after three meters of infiltration through desert soil. Modelling subsurface attenuation mechanisms of pharmaceuticals in laboratory studies, research have demonstrated that subsurface mechanisms such as adsorption can effectively remove hormones present in recycled water (Debroux, 2007).

Contrary to the findings above, subsurface attenuation mechanisms are less effective at removing some pharmaceuticals due to resistance to biodegradation, excessive accumulation, concentrations and loading rates, and hydrophilic nature. Experiments indicate ibuprofen (Snyder et. al., 2004) and anti-epileptics (e.g. carbamazepine and primidone) was not completely removed even under either anoxic saturated or aerobic unsaturated flow conditions during travel times of up to eight years through the subsurface (Drewes et al., 2002; Drewes et al., 2007). This leaves the most recalcitrant pharmaceuticals in the aqueous-sediment matrix.

These results are inconclusive, due to the fact that most of these experiments were conducted under field conditions were several factors were minimally controlled. Besides, the specific process that resulted in the attenuation of pharmaceuticals within the subsurface was not well defined, thus attenuation of pharmaceuticals was vaguely attributed to various geohydrological and biological processes. Therefore, there is the need for more comprehensive research on the effect and efficiency of attenuation mechanisms on the fate and occurrences of pharmaceuticals in the underground environment since less is known (Drewes and Shore, 2001; Drewes et al, 2007). Clearly, a large amount of research remains to be completed on the poorly characterised processes such as sediment metabolism and there is the need for future research that focuses more on detailed ecotoxicity testing, using a wide range of aquatic organisms as well as how these compounds are sorbed, transferred and biodegraded in STPs, WTWs and the environment (Jones et al., 2002). Moreover, the dose and persistence time related effects of pharmaceuticals in aquatic sediment metabolism is still a field of research wilderness probably due to a lack of suitable test methods (Thiele-Bruhn, 2003).

2.7 SEDIMENT RESPIRATION

The complex interactions among abiotic and biotic factors define the structure and function of ecosystems and ecological processes which when altered are manifested at many spatial and temporal scales (Stevenson, 1997). Open sediment bottom habitats in river ecosystem are productive and must be viewed as such (Cahoon and Cooke. 1992). The stability of bed sediments is an important determinant of the biologically mediated energy flow through lotic ecosystems (Uehlinger et al., 2002). Aquatic ecologists have long been aware of the significant influence of sediment metabolism on overlying water (Grimm and Fisher, 1984).

Sediment respiration mainly occurs in hyporheic and parafluvial sediments (Uehlinger et al., 2002). Sediment respiration (oxygen uptake rate) (HR) in the hyporheic zone is governed by climatic (seasonality and water temperature), biological (protein content of particulate organic matter (POM)), chemical and physical attributes (sediment diameter) (Kanneworff and Christensen, 1986; Jones, 1995). Sediment respiration is an important measure of degradation of chemicals and decomposition of organic matter (Sörensen, 1979; Hedin, 1990). There is a distinctive vertical zonation of POM content, microbial biomass, and respiration rate within the hyporheic sediments (biofilms) with bacterial abundance, biomass, and activity strongly correlated with the amount of POM which was loosely associated to sediment surfaces (Fischer et al., 1996). The mean respiration rate for sediments in contact with the upper mixed layer is positively correlated to POM concentration in the water (Algesten et al., 2005). Total POM accounts for only a minor proportion of HR variation but the temperature, oxygen concentration and temperature in the overlying water and protein content of POM loosely associated with sediments are the primary and best predictors of HR, accounting for 76% of the variance of HR (Pusch and Schwoerbel, 1994).

The differences in algae, bacteria and invertebrate species are of secondary importance to the sediment respiration process (Provini, 1975). Sediment respiration is dominated by aerobic respiration of the biomass of the dominant macroinvertebrate (Grundmanis and Murray, 1982) and microbial species (Cahoon and Cooke 1992), and mineralization processes such as nitrification (Kikuchi, 1986). Jones et al. (1995) found that benthic production fuelled more than 80% of the hyporheic respiration through leaching dissolved material. The major functional component of the total sediment community respiration are bacteria (30% to 60%) and macrofaunal respiration (5 to 26%) (Smith JR., 1973). Colonising bacteria on sediments are important as mediators of matter and energy transfers but regardless of increasing knowledge about numbers and geochemical activity of bacteria, their population dynamics, and rates of production, turnover and degradation of pharmaceuticals are poorly understood (Fallon et al., 1983). Using selective inhibition by antibiotics, attempts have been made to measure the contribution of bacteria to sediment oxygen demand with results being equivocal (Rizzo et al., 1992).

The physical structure of sediments affects the area available for microbial attachment and metabolism. According to Jones (1995), the diameter of sediment particles is inversely related to the hyporheic respiration per unit volume of sediment. However, respiration rate per unit surface area on sediments correlates positively with particle diameter. Respration rate per unit surface area is more than twice as high in water collected from the surface flow than from subsurface flow indicating that HR is influenced by the region of flow (ibid).

Jones et al. (1994) concluded that aerobic respiration is considerably greater than chemoautotrophy in oxygenated hyporheic and parafluvial zones (2400 to 4900 mgC/m super(2)/d) and anoxic bank sediments with chemoautotrophic and methane production accounting for 1.0 to 1.3% and 5% of total sediment respiration respectively. Furthermore, aerobic respiration and chemoautotrophic production occurred in parafluvial sediments (64 to 76%), whereas anoxic bank sediments were most important for anaerobic respiration (94% of total anaerobic respiration).

A few stream studies have indicated the impact of chemicals on deep sediments metabolism and stream communities with most research being done on surface sediment processes (Grimm and Fisher, 1984). Ecological processes such as photosynthesis and respiration that takes place on sediment surfaces may be altered when pharmaceuticals are adsorbed to sediment surfaces. Hence, there is the need for research that assesses and determines the long-term fate and effects of parent pharmaceuticals or metabolites on aquatic ecosystems and the threat posed to a range of species over their lifecycle, various trophic levels, and ecological processes in sensitive zones with surface water-sediment-groundwater interactions (hypoheic zone). A thorough understanding of this subject is needed to fully assess the risks posed by these pharmaceuticals to the environment.

3.0 Materials and Methods

3.1 Sampling

Twenty grab samples of sediments were taken randomly from the Fishbeck (below the Silsden reservoir) in Silsden (Figure 3.1). The bedform of the stream sampled for sediment is a mixed sand-gravel bed channel. The river is highly canopied and is less disturbed by pollution. The grab samples were sieved and separated into 2mm, 1mm, 0.5mm and 0.15mm sediment fractions (Table 3.1). Sediment size fractions were transported the laboratory and stored below 4 °C to halt any microbial activities before sediments were used.

Table 3.1 Description and millimetre ranges for different sediment grains

Sieve mesh size (mm)

Sediment size (mm)

Description

Parts in Fisbeck

2

3.000 to 2.000

Course Sand

3

1

2.000 to 0.500

Course Sand

0.6

0.5

0.050 to 0.150

Medium and Fine Sand

0.3

0.15

0.150 to 0.004

Fine sand and silt

0.3

Source: Adapted from Charlton (2009)

Fig. 3.1 Map showing location of Fishbeck (stream) in Sisden used in study (Source: Edina Digimap (2010))

3.2 Pharmaceutical compounds

Pharmaceutical compounds were selected based on their published risk assessment values indicating their potential ecotoxological effects at environmental concentrations. Pharmaceutical compounds were purchased from Sigma. The concentrations of pharmaceutical compounds used as treatments for the experiment were that of that found at maximum concentration in the aquatic environment (low treatment) and a hundred times the amount found in the aquatic environment (high treatment) which could be the realistic amounts in the aquatic environment.

Table 3.2 Concentrations of pharmaceutical compounds (treatments) for experiment

Pharmaceutical Compounds

Max UK river conc. (ng/l)

Desired conc. (ng/l)

Dilute stock needed (ml)

Dilute stock conc. (mg/l)

HT

LT

HT

LT

Erythromycin

1022

100000

1000

9.759

0.098

4.782

Diclofenac

568

60000

600

4.679

0.047

5.984

Mefenamic acid

366

40000

400

1.800

0.018

10.370

Ibuprofen

5000

500000

5000

23.102

0.231

10.100

Propranolol

215

20000

200

4.709

0.047

1.982

The dilute stock solutions were stored below 4 °C to prevent the pharmaceutical parent compounds from being transformed into their metabolised.

3.3 Sediment Respiration

Cylindrical glass flask (25 cm deep and 4.25 cm in diameter) were filled with sediments at a ratio equivalent to the sediment sizes obtained from the Fishbeck (Table 3.1). The sediment filled cylindrical glass flasks were topped with deionised water to reduce the headspace of the sediment-water column to prevent air bubbles from accumulating to upset dissolved oxygen readings. The glass cylinders were sealed at the top end with rubber stoppers through which was fitted an oxygen probe. The studies were conducted in duplicate with the following treatments: control (no drug treatment), fertilized (57 g of N and P per m2), and oiled/fertilized [25 ml (20 g) of crude oil was added to each core as carbon source (1260 g oil/m2) and 57 g of N and P per m2].

The sediment filled flasks were acclimatised in a constant temperature room (14 ± 1 °C, 12-h light and 12-h darkness period) for 48 hours before dissolved oxygen measurements were taken. Three replicate sets of flasks were treated with one of the six pharmaceutical treatments respectively (Table 3.2). Seven additional flask containing only sediment and deionised water was used as a control. Temperature was maintained close to the ambient water temperature for the Silsden stream in August. Microbial respiration was measured on the sediment-water interface for 48 hours. Oxygen probes measured dissolved oxygen concentration (Orbisphere Model 2607 (Orbisphere Laboratories, Geneva, Switzerland) dissolved oxygen analyzer or YSI 600 (YSI, yellow Springs, OH, U.S.A.) water quality monitor) which were made at 15-min intervals over a 48-h period. The DO concentration in the overlying water was measured with a DO meter (Orion Model 810). The DO uptake rate (mmol O2/m2-day) was calculated from the slope of the DO level versus time and the cross-sectional area of the core.

3.4 Sediment organic carbon (SOC) and dissolved organic carbon (DOC)

Sediment organic carbon and dissolved organic carbon were measured in each cylindrical glass microcosms to identify possible causal relationships with sediment respiration. 15ml of water from the water column above the sediment were collected for each treatment before (0 hour) and after (48 hours) dissolved oxygen measurements. The water samples were analysed for dissolve organic carbon in a DOC analyser. The changes in dissolved organic carbon concentration before and after 48 hours were recorded.

The standing crop of sediment organic matter (SOM) was measured before and after treatment with pharmaceutical compounds. Wet weights (1g) of each of the sediment aggregates (2mm, 1mm, 0.5.mm and 0.15mm) were measured with an analytical balance (0.0001 d.c) into precombusted aluminium pans and were dried (50°C for 48hrs), desiccated (24hrs) to a constant weight, weighed (A), combusted (500 °C for 0.5 to 1hr), desiccated (24hrs), reweighed, hydrated, dried (50°C for 24hrs), desiccated (24hrs), and reweighed (B) in the laboratory to determine ash-free dry mass (AFDM) per unit area sampled. The BOM was estimated for all controls and treated sediment cores by determining the difference between dry mass (50°C) (A) and hydrated dry mass (50°C) (B).

3.5 Data analysis and presentation

Tests for differences in mean DO, DOC concentrations and OC storage between treatments were performed using a one-way ANOVA. Tests for differences in mean DO, DOC concentrations and OC storage for the interactions between the treatments at both high and low levels of pharmaceutical concentrations were performed using a two-way ANOVA. All means presented represent arithmetic means. All sediment OC storage concentrations are based on dry weight. Statistical significance was determined at the p < 0.05 level. Statistical analyses were performed using Microsoft Excel 2007 and Minitab 15 Statistical Software. Microsoft Excel 2007 was used to generate graphs to demonstrate relationships among the variables. The results were presented as the Mean ± S.D (standard deviation of the mean) of the replicates.

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