| Literature DB >> 27342851 |
Thomas G Bean1,2, Ed Bergstrom3, Jane Thomas-Oates3, Amy Wolff4, Peter Bartl4, Bob Eaton4, Alistair B A Boxall5.
Abstract
Increased interest over the levels of pharmaceuticals detected in the environment has led to the need for new approaches to manage their emissions. Inappropriate disposal of unused and waste medicines and release from manufacturing plants are believed to be important pathways for pharmaceuticals entering the environment. In situ treatment technologies, which can be used on-site in pharmacies, hospitals, clinics, and at manufacturing plants, might provide a solution. In this study we explored the use of Pyropure, a microscale combined pyrolysis and gasification in situ treatment system for destroying pharmaceutical wastes. This involved selecting 17 pharmaceuticals, including 14 of the most thermally stable compounds currently in use and three of high environmental concern to determine the technology's success in waste destruction. Treatment simulation studies were done on three different waste types and liquid, solid, and gaseous emissions from the process were analyzed for parent pharmaceutical and known active transformation products. Gaseous emissions were also analyzed for NOx, particulates, dioxins, furans, and metals. Results suggest that Pyropure is an effective treatment process for pharmaceutical wastes: over 99 % of each study pharmaceutical was destroyed by the system without known active transformation products being formed during the treatment process. Emissions of the other gaseous air pollutants were within acceptable levels. Future uptake of the system, or similar in situ treatment approaches, by clinics, pharmacists, and manufacturers could help to reduce the levels of pharmaceuticals in the environment and reduce the economic and environmental costs of current waste management practices.Entities:
Keywords: Antimicrobial resistance; Pharmaceutical waste; Pyrolysis–gasification; Stewardship; Take-back strategy; Thermal decomposition
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Substances:
Year: 2016 PMID: 27342851 PMCID: PMC5026718 DOI: 10.1007/s00267-016-0728-9
Source DB: PubMed Journal: Environ Manage ISSN: 0364-152X Impact factor: 3.266
Fig. 1Cumulative percentage of pharmaceuticals looked up in literature review against decomposition temperature (°C). The decomposition temperatures of the 17 pharmaceuticals run through a Pyrolysis–gasification waste treatment system (PGWTS) are marked by white circles and all pharmaceuticals (out of the 600 we looked up) for which we found a decomposition temperature are marked with black crosses. The white circles represent the maximum decomposition temperature quoted in the literature for chloramphenicol (CHL), sulfamethoxazole (SMX), gliclazide (GLZ), ketoprofen (KTPF), allopurinol (ALPL), amantadine (AMN), atenolol (ATEN), estradiol (E2), indomethacin (IND), verapamil (VPL), fluoxetine (FLX), ibuprofen (IBF), 5-fluorouracil (5-FLU), diclofenac (DCF), carbamazepine (CBZ), and ethinylestradiol (EE2). The gray box represents the typical temperature range in which the PGWTS developed by Pyropure operate. Patient usage (based on NHS prescription cost analysis and over the counter availability (National Health Service (NHS) 2013) and toxicity were also considered when selecting pharmaceuticals, meaning a pharmaceutical with higher toxicity and or usage (E2 and CBZ) was selected over pharmaceuticals with low usage or toxicity e.g., pioglitazone hydrochloride and glimepiride (two black crosses between GLZ and SMX)
The 17 pharmaceuticals selected for testing in the Pyrolysis–gasification waste treatment system (PGWTS) trials, therapeutic class, decomposition temperature, and usage (kg/yr) in Great Britain in 2012
| API | Therapeutic class or use class | Decomposition temperature range (°C) | Usage (kg/yr) | Reference decomp. temp |
|---|---|---|---|---|
| 5-Fluorouracil | Anticancer, cytotoxic | 282 | 12,648.7 | 1 |
| Allopurinol | Antigout | 379.5–386 | 38,593 | 2 |
| Amantadine | Antiviral/AntiParkinson’s | 360 | 626.6 | 3 |
| Aspirin | Analgesic | 370 | 96,644.6 | 4 |
| Atenolol | Beta-blocker | 303–335 | 26,411.5 | 5 |
| Carbamazepine | Antiepilepsy | 190–195 | 45,331.9 | 6 |
| Chloramphenicol | Antibiotic, cytostatic | 200–704 | 484.6 | 7 |
| Diclofenac | Nonsteroidal antiinflammatory drug | >260 | 16,369.7 | 8 |
| Estradiol | Hormone | 275–317 | 151.6 | 9 |
| Ethinylestradiol | Hormone | 178 | 12.9 | 10 |
| Fluoxetine | SSRI antidepressant | 200–300 | 6200.1 | 11 |
| Gliclazide | Diabetes | 271–429 | 40,781.2 | 12 |
| Ibuprofen | Nonsteroidal antiinflammatory drug | 180–300 | 151,739.9 | 13 |
| Indomethacin | Nonsteroidal antiinflammatory drug | 230–330 | 837.2 | 14 |
| Ketoprofen | Nonsteroidal antiinflammatory drug | 235–400 | 903.47 | 15 |
| Sulfamethoxazole | Antibiotic | 380–600 | 1940.2 | 16 |
| Verapamil | Calcium channel blocker | 300–320 | 6969.9 | 17 |
1: Lewis (2007), 2: Samy et al. (2010), 3: RSC (2013), 4: Ribeiro et al. (1996), 5: Pereira et al. (2007), 6: McGregor et al. (2004), 7: Macedo et al. (1999), 8: Tudja et al. (2001), 9: Martin and Wotiz (1962), 10: Cotter et al. (1978), 11: Silva et al. (2007), 12: Zayed et al. (2010), 13: Tita et al. (2011a), 14: Tita et al. (2010), 15: Tita et al. (2011b), 16: Fernandes et al. (1999), 17 Lide and Milne (1994)
Limits of detection (ng/mL) (LOD) for each of the 17 APIs in Phase 1 simulation
| API | Recovery of analytical extraction method (%) | LOD (ng/mL) |
|---|---|---|
| 5-Fluorouracil | 28.5 | 100 |
| Allopurinol | 21.4 | 10 |
| Amantadine | 52.1 | 50 |
| Aspirin | 0 | 100 |
| Atenolol | 58.3 | 100 |
| Carbamazepine | 86.8 | 10 |
| Chloramphenicol | 75.2 | 50 |
| Diclofenac | 79.4 | 10 |
| Estradiol | 79.7 | 500 |
| Ethinylestradiol | 79.8 | 100 |
| Fluoxetine | 80.6 | 50 |
| Gliclazide | 45.8 | 100 |
| Ibuprofen | 41.6 | 10 |
| Indomethacin | 13.9 | 10 |
| Ketoprofen | 68.5 | 50 |
| Sulfamethoxazole | 55.5 | 100 |
Aspirin could not be recovered from the solids
Limits of detection (LOD) and quantification (ng/mL) (LOQ) for each of the six retested APIs in Phase 2 simulation in liquid effluent, sludge, ashpot solids, and the air emission
| API | Liquid effluent | Sludge | Ashpot | Air | ||||
|---|---|---|---|---|---|---|---|---|
| LOD (ng/mL) | LOQ (ng/mL) | LOD (ng/mL) | LOQ (ng/mL) | LOD (ng/mL) | LOQ (ng/mL) | LOD (ng/mL) | LOQ (ng/mL) | |
| 5-Fluorouracil | 35.3 | 117.6 | 188.2 | 627.3 | 188.2 | 627.3 | 313.6 | 1045.5 |
| Atenolol | 2.6 | 8.6 | 1.0 | 3.4 | 0.9 | 2.9 | 1.7 | 5.7 |
| Estradiol | 12.6 | 42.1 | 7.8 | 26.1 | 15.7 | 52.2 | 18.3 | 60.9 |
| Ethinylestradiol | 63.2 | 210.5 | 35.5 | 117.6 | 70.6 | 235.3 | 84.7 | 282.4 |
| Ibuprofen | 180.0 | 600.0 | 120.0 | 400.0 | 150.0 | 500.0 | 300.0 | 1000.0 |
| Ketoprofen | 540.0 | 1800.0 | 144.0 | 480.0 | 160.0 | 533.3 | 32.0 | 106.7 |
Fig. 2Mass balance showing the fate of pharmaceuticals tested in a Pyrolysis–gasification waste treatment system (PGWTS) in Phase 1 (a) and Phase 2 (b). The percentage that was destroyed is given by white-dotted bars, the percentage found in liquid effluent is given by gray bars, in the solids (sludge and ashpot) by diagonally dashed bars and that found in the air trap is given by black bars. Note the different y-axis ranges in a 0–100 % and b 99–100 %
Active metabolites detected in Phase 1 and Phase 2, in samples of air, mains water (i.e., water straight from the tap taken at the same time as the unit was being drained and washed out with tap water), liquid effluent, the solid ashpot residue and the sludge (solid part of the effluent)
| Phase 1 | Phase 2 | |||||||
|---|---|---|---|---|---|---|---|---|
| API run 1 | API run 2 | API run 3 | ||||||
| Metabolite | Approximate parent equivalent % | Metabolite | Approximate parent equivalent % | Metabolite | Approximate parent equivalent % | Metabolite | Approximate parent equivalent % | |
| Air | F-dUMP | 25.2 | – | – | – | – | 2-me | 0.03 |
| Mains water | NA | NA | 2-hydoxyIBF | 0.028 | 2-me | 0.010 | 2-me | 0.007 |
| Liquid Effluent | F-dUMP | 60.3 | – | – | F-dUMP | 0.54 | 2-hydroxyIBF | 0.014 |
| Solid Ashpot | NA | NA | 2-me | 0.00002 | 2-me | 0.00007 | carboxyIBF | 0.0005 |
| Sludge rep 1 | 2-me | 0.0007 | 2-me | 0.007 | 2-me | 0.007 | 2-me | 0.00009 |
| Sludge rep 2 | NA | NA | Est | 0.0015 | 2-me | 0.00009 | 2-me | 0.0001 |
In Phase 1, means are presented for the three waste types (bulk, manufacturing, and sharps as only 15 samples were run in total (3 air, 3 sludge, and 9 liquid effluent). In Phase 2, a larger number of samples were analyzed and so the data are presented separately for each run. The metabolites detected were: 5-fluoro-2-deoxyuridine 5′-monophosphate (F-dUMP)), 2-methoxyestradiol (2-me), estrone (Est), 2-hyroxyibuprofen (2-hydroxyIBF), and carboxyibuprofen (carbIBF). Where an active metabolite was detected, the concentration was estimated in terms of parent equivalent and then related to the percentage of the starting mass that this was equivalent to. For control and blank runs containing only Polyethylene terephthalate (PET) and all mains water samples, no API was added and so detection must be due to background levels in the tap water. Note the F-dUMP parent equivalent is likely to be overestimated due to the low sensitivity of the MS assay for its parent compound