ABSTRACT
The presence of antiretroviral drugs (ARVs) in the aquatic environment highlights the inadequacy of traditional wastewater treatment plants in their remediation. Moreover, the fate and associated human and ecotoxicological impact of those compounds are not well established. In fact, research focusing on effective alternative treatment solutions still seems lacking. However, a growing interest in remediation techniques for pharmaceutical residues, including ARVs in wastewater, has been noticed recently. The main objective of this review is to share updated information and literature on the recent advances in wastewater treatment strategies to eliminate traces of ARVs from wastewater. Research gaps and possible ways forward for further research in the development of effective alternative treatments are well narrated in the current review. Furthermore, useful information can be derived from the highlighted biodegradation mechanisms to better understand the environmental fate of these compounds. An overview of different treatment methods is given, with particular emphasis on the removal efficiencies, reaction kinetics, degradation mechanisms, and process limitations. A summary of the environmental occurrence of ARVs is provided, as well as the status of the global HIV prevalence and antiretroviral therapy.
HIGHLIGHTS
Removal strategies of antiretroviral drugs (ARVs) from wastewater are reviewed.
Research gaps and possible remedial methods are identified and discussed.
A summary of the environmental occurrence of ARVs is given.
The current status of the global HIV prevalence and antiretroviral therapy is provided.
LIST OF ABBREVIATIONS
- 3TC
lamivudine
- ABC
abacavir
- AC
activated carbon
- ACS
activated sludge
- AOP
advanced oxidation process
- ART
antiretroviral therapy
- ARV
antiretroviral drugs
- ATV
atazanavir
- AZT
zidovudine
- BTF
biological trickling filter
- DID
didanosine
- DRV
darunavir
- EFV
efavirenz
- EO
electrochemical oxidation
- EP
emerging pollutant
- FTC
emtricitabine
- GAC
granular activated carbon
- HPLC
high-performance liquid chromatography
- IDV
indinavir
- II
integrase inhibitor
- LDH
layered double hydroxide
- LPV
lopinavir
- MBR
membrane bioreactor process
- MBR-SBR
MBR with sequencing batch reactors
- MVC
maraviroc
- NFV
nelfinavir
- NNRTI
non-nucleoside reverse transcriptase inhibitor
- NRTI
nucleoside reverse transcriptase inhibitor
- NVP
nevirapine
- O3
ozonation
- PAC
powdered activated carbon
- PHAC
pharmaceutical
- PI
protease inhibitor
- PreP
pre-exposure prophylaxis
- RAL
raltegravir
- RBC
rotating biological contactor
- RTV
ritonavir
- SQV
saquinavir
- STV
stavudine
- TFV
tenofovir
- TP
transformation product
- UNAIDS
Joint United Nations Programme on HIV/AIDS
- WHO
World Health Organization
- WWTP
wastewater treatment plant
INTRODUCTION
Several authors have reported increasing concentrations of antiretroviral drugs (ARVs) in various water compartments worldwide (Nannou et al. 2020; Reddy et al. 2021; Adeola & Forbes 2022). These compounds are classified as emerging pollutants (EPs) and are not amenable to conventional wastewater treatment plants (WWTPs). Moreover, some authors have reported potential human health and environmental risks associated with non-target exposure to ARVs (Ncube et al. 2018; Ngwenya & Musee 2023). This has prompted the urgency to develop effective and sustainable alternative ARV remediation strategies. Literature shows that various treatment approaches have been explored to remove a diverse range of ARVs from water, achieving ≥90% removals in some cases. Examples include biodegradation (Silva et al. 2024), algal processes (Reddy et al. 2021), biocatalytic process (Stuurman et al. 2024), adsorption (Krasucka et al. 2022), UV light (Ngumba et al. 2020a), photocatalysis (Tabana et al. 2023), and electrochemical oxidation (EO) (Lan et al. 2022). Despite the impressive results, it remains challenging to identify the most effective and sustainable treatment for scale-up. This could be due to the inherent individual method limitations and challenges, as well as non-standardized experimental conditions. For example, different researchers employ different ARVs, methods, reaction media, reactor configuration, light source, and catalyst/adsorbent/electrodes under different experimental conditions, thus making it extremely challenging to compare results. Additionally, the fate and ecotoxicological impact of ARVs are often reported as a subsection of the broader antiviral drug class (Horn et al. 2022), which limits available data on this important aspect. On the other hand, the ultimate cure for HIV remains elusive, although much progress in preventing AIDS-related fatalities and reducing HIV transmission has been achieved through effective antiretroviral therapy (ART). The continuous emergence of new infections shows that the fight against HIV is far from over.
Numerous reviews on ARVs have been documented, each addressing different focal areas. Ncube et al. (2018) focused on the environmental fate and ecotoxicological effects of ARVs, highlighting ATRIPLA as the predominant ART regimen. The ART and HIV prevalence data were based on 2016 and 2020 statistics from Ncube et al. (2018) and Kudu et al. (2022), respectively. Some studies briefly discussed remediation methods but lacked detail on the methods, experimental conditions, removal efficiency, degradation mechanisms, and kinetics (Ncube et al. 2018; Kudu et al. 2022). Sigonya et al. (2023) recently focused on ARV removal through adsorption. The environmental occurrence of ARVs was primarily reported in Africa and Europe (Adeola et al. 2021; Kudu et al. 2022) and Sub-Saharan Africa (S-SA; Bheki et al. 2022; Ngwenya & Musee 2023).
This review gives an overview of the recent advancements in the remediation of ARVs in the aquatic environment for the first time. Removal efficiencies, kinetics, reaction mechanism, and intermediate products are given. The existing trends and prospects of ARV removal are reviewed, with emphasis on the challenges, limitations, and improvement strategies. The updated ARVs' environmental occurrence is summarized, and the associated human health and environmental impact is highlighted. The latest ART and HIV prevalence are discussed.
ART AND ITS RELATIONSHIP TO ARVs PRESENCE IN WASTEWATER
ARVs constitute a pharmacological family of medicines used to treat retroviral infections such as malignancies, neurologic disorders, and immune deficiencies. However, this work focuses on the ARVs specifically for the treatment of HIV/AIDs, considering that HIV/AIDS is a chronic pandemic and there is widespread occurrence of ARVs in the aqueous environment. ARVs have proved effective in lowering AIDS-related fatalities, decreasing HIV transmission by suppressing the virus, and extending life expectancy (NHI 2024). To that end, the development of ARVs has changed HIV infection from an almost always fatal infection into a chronic but manageable illness. There are currently six distinct classes of ARVs, composed of more than 30 ARVs on the market. Table 1 gives a summary of the ARV classes, functions, and physicochemical properties.
ARVs function and selected physicochemical properties (Drugbank, n.d.; PubChem, n.d.)
ARVs . | Molecular formula . | Function . | Excretion (%) . | Solubility (water) mg/ml . | pKa . | log Kow . | |
---|---|---|---|---|---|---|---|
Urine . | Feces . | ||||||
NRTIs | |||||||
Abacavir (ABC) | C14H18N6O | Attack the reverse transcriptase HIV protein, stopping HIV replication | 8.22 | 16 | 0.077 | 5.77 | 1.2 |
Emtricitabine (FTC) | C8H10FN3O3S | 86 | 14 | 1,120 | 2.65 | −0.43 | |
Lamivudine (3TC) | C8H11N3O3S | 70 | 7.0 | 4.4 | −1.4 | ||
Tenofovir (TFV) | C9H14N5O4P | 70–80 | 13.4 | 3.75 | 1.25 | ||
Zidovudine (AZT) | C10H13N5O4 | 29 | 45 | 2.0 | 9.96 | 0.05 | |
Stavudine (STV) | C10H12N2O4 | 83 | 9.95 | −0.72 | |||
Didanosine (DID) | C10H12N4O3 | 27.3 | 9.13 | −1.24 | |||
NNRTIs | |||||||
Efavirenz (EFV) | C14H9ClF3NO2 | Block the reverse transcription process by binding directly to the reverse transcriptase enzyme | 14–34 | 16–61 | <0.01 | 10.2 | 4.6 |
Nevirapine (NVP) | C15H14N4O | <5.0 | 0.1 | 2.8 | 3.89 | ||
Intergrase inhibitors | |||||||
Raltegravir (RAL) | C20H21FN6O5 | Prevent the virus from integrating itself into human cell | 71.0 | 7.02 | 0.4 | ||
Dolutegravir (DTG) | C20H19F2N3O5 | 64 | 32 | 0.09 | 8.2 | 2.2 | |
Entry inhibitors | |||||||
Maraviroc (MVC) | C29H41F2N5O | Prevent the HIV envelope protein from fusing with the CD4 cell | 8.2 | 86.2 | 0.00001 | 6.69 | |
Protease inhibitors | |||||||
Atazanavir (ATV) | C38H52N6O7 | Disrupt the viral life cycle by blocking the protease enzyme's activity | 79 | 13 | 4.5 | 11.11 | 4.5 |
Darunavir (DRV) | C27H37N3O7S | 79.5 | 13.9 | 15 | 11.43 | 1.89 | |
Lopinavir (LPV) | C37H48N4O5 | 10.4 | 82.6 | <0.0002 | 13.39 | 4.69 | |
Ritonavir (RTV) | C37H48N6O5S2 | 11 | 86 | 0.000011 | 2.84 | 6.27 | |
Indinavir (IDV) | C36H47N5O4 | <20 | 0.015 | 3.7 | 2.9 | ||
Nelfinavir (NFV) | C32H45N3O4S | 1–2 | 19 | 0.00019 | 6.0 | 8.98 | |
Saquinavir (SQV) | C38H50N6O5 | 1–3 | 81–88 | 2.2 | 6.0 | 2.5 |
ARVs . | Molecular formula . | Function . | Excretion (%) . | Solubility (water) mg/ml . | pKa . | log Kow . | |
---|---|---|---|---|---|---|---|
Urine . | Feces . | ||||||
NRTIs | |||||||
Abacavir (ABC) | C14H18N6O | Attack the reverse transcriptase HIV protein, stopping HIV replication | 8.22 | 16 | 0.077 | 5.77 | 1.2 |
Emtricitabine (FTC) | C8H10FN3O3S | 86 | 14 | 1,120 | 2.65 | −0.43 | |
Lamivudine (3TC) | C8H11N3O3S | 70 | 7.0 | 4.4 | −1.4 | ||
Tenofovir (TFV) | C9H14N5O4P | 70–80 | 13.4 | 3.75 | 1.25 | ||
Zidovudine (AZT) | C10H13N5O4 | 29 | 45 | 2.0 | 9.96 | 0.05 | |
Stavudine (STV) | C10H12N2O4 | 83 | 9.95 | −0.72 | |||
Didanosine (DID) | C10H12N4O3 | 27.3 | 9.13 | −1.24 | |||
NNRTIs | |||||||
Efavirenz (EFV) | C14H9ClF3NO2 | Block the reverse transcription process by binding directly to the reverse transcriptase enzyme | 14–34 | 16–61 | <0.01 | 10.2 | 4.6 |
Nevirapine (NVP) | C15H14N4O | <5.0 | 0.1 | 2.8 | 3.89 | ||
Intergrase inhibitors | |||||||
Raltegravir (RAL) | C20H21FN6O5 | Prevent the virus from integrating itself into human cell | 71.0 | 7.02 | 0.4 | ||
Dolutegravir (DTG) | C20H19F2N3O5 | 64 | 32 | 0.09 | 8.2 | 2.2 | |
Entry inhibitors | |||||||
Maraviroc (MVC) | C29H41F2N5O | Prevent the HIV envelope protein from fusing with the CD4 cell | 8.2 | 86.2 | 0.00001 | 6.69 | |
Protease inhibitors | |||||||
Atazanavir (ATV) | C38H52N6O7 | Disrupt the viral life cycle by blocking the protease enzyme's activity | 79 | 13 | 4.5 | 11.11 | 4.5 |
Darunavir (DRV) | C27H37N3O7S | 79.5 | 13.9 | 15 | 11.43 | 1.89 | |
Lopinavir (LPV) | C37H48N4O5 | 10.4 | 82.6 | <0.0002 | 13.39 | 4.69 | |
Ritonavir (RTV) | C37H48N6O5S2 | 11 | 86 | 0.000011 | 2.84 | 6.27 | |
Indinavir (IDV) | C36H47N5O4 | <20 | 0.015 | 3.7 | 2.9 | ||
Nelfinavir (NFV) | C32H45N3O4S | 1–2 | 19 | 0.00019 | 6.0 | 8.98 | |
Saquinavir (SQV) | C38H50N6O5 | 1–3 | 81–88 | 2.2 | 6.0 | 2.5 |
The ARVs target HIV in different ways, as highlighted in Table 1. However, single-drug therapy regimens have since proven inefficient. This could be attributed to the ability of the HIV to replicate, rapidly forming variants with mutations that often confer resistance to ARVs. Furthermore, single-drug dosages were found to be complex with burdensome side effects, making it challenging for people to follow the treatment consistently over time. To tackle these complexities, drug toxicity, and drug resistance, innovative drug formulations targeting precise stages in the HIV replication process and operating through distinct mechanisms were developed. Nowadays, several fixed-dose combos containing two or more ARVs from different pharmacological classes are available. Examples include single-pill regimes such as ATRIPLA (EFV, FTC, and TFV), which was introduced as a first-line treatment in 2006 (NHI 2024).
Despite its success in treating HIV, ATRIPLA was suspended at the end of 2021, presumably because of severe side effects and insufficient demand. ATRIPLA was replaced by dolutegravir (DTG)-based fixed-dose three-in-one pill regimens such as Triumeq (ABC, DTG, and 3TC) and tenofovir/lamivudine/dolutegravir (TLD) (TFV, 3TC, and DTG). These are the latest global leading ART regimens and are highly recommended by the World Health Organization (WHO). Noteworthy, DTG replaces EFV in first-line regimens. Studies indicate that DTG is superior to EFV in lowering blood HIV levels such that the virus can no longer be transmitted through sexual intercourse. Other advantages of DTG include fewer side effects, lower cost, easier to take than other regimens (one small pill per day), and less adverse interactions with other medications, such as tuberculosis drugs, which is a major risk factor for HIV infection (González 2022). However, it remains to be seen whether DTG is amenable or resistant to conventional WWTPs. To the authors' knowledge, no relevant data have been reported yet.
Since the first administration of ARVs in the 90s, their usage has skyrocketed across the globe and continues to do so at alarming rates. This may be linked to increasing HIV infections and international programs like the 95-95-95 strategy, which have significantly increased the count of patients undergoing ART worldwide. The 95-95-95 targets were compiled by the Joint United Nations Programme on HIV/AIDS (UNAIDS), which asserts that by 2030, 95% of all HIV patients should know their status, 95% of all HIV patients should be obtaining continuous ART, and 95% of all recipients of antiretroviral treatment should have viral suppression. Impressively, the number of AIDS-related infections and deaths has decreased worldwide (Wasswa 2023), which could be a direct consequence of increased access to ART.
From Figure 1, the global antiretroviral treatment coverage was ∼77% by the end of 2023. The highest coverage (∼84%) was recorded in Eastern and Southern Africa, which constitutes most of S-SA. The regions with the lowest coverage were Eastern Europe, Central Asia, the Middle East, and North Africa. The statistics probably agree with the rate of HIV prevalence (RHP) and the ease of ARVs' accessibility in these regions.
ART AND GLOBAL HIV PREVALENCE
According to the Global HIV and AIDS Statistics – Fact sheet, 2024, approximately 40 million people were living with HIV in 2023. Thirty-one million were accessing ART globally, which was up from 7.7 million recorded in 2010 (UNAIDS 2024). Furthermore, new infections are still being recorded (although at a lower rate), and it is worrying that the majority of these are among women and girls. In 2023, females of all age groups represented 44% of the new HIV infections worldwide. Overall, S-SA exhibits the highest HIV prevalence globally (UNAIDS 2024). This could be ascribed to poverty-related issues such as lack of funding, poor public healthcare system and transport infrastructure, and lack of HIV/AIDs awareness, particularly in remote areas. Table 2 presents countries with the highest HIV prevalence rate (RHP) and the corresponding number of people living with HIV (PLH).
Countries with the highest global HIV prevalence rates (2024) (Wikipedia 2024)
Country . | RHP . | PLH . |
---|---|---|
Eswatini | 28.3 | 240,000 |
Lesotho | 24.1 | 403,000 |
Botswana | 22.6 | 398,500 |
Zimbabwe | 22.1 | 1,660,000 |
South Africa | 14.1 | 9,230,000 |
Namibia | 13.2 | 219.330 |
Mozambique | 12.7 | 2,485,000 |
Zambia | 12.5 | 1,550,000 |
Malawi | 11.4 | 1,642,570 |
Equitorial Guinea | 7.7 | 74,165 |
Tanzania | 5.5 | 2,550,000 |
Uganda | 5.0 | 1,590,000 |
Country . | RHP . | PLH . |
---|---|---|
Eswatini | 28.3 | 240,000 |
Lesotho | 24.1 | 403,000 |
Botswana | 22.6 | 398,500 |
Zimbabwe | 22.1 | 1,660,000 |
South Africa | 14.1 | 9,230,000 |
Namibia | 13.2 | 219.330 |
Mozambique | 12.7 | 2,485,000 |
Zambia | 12.5 | 1,550,000 |
Malawi | 11.4 | 1,642,570 |
Equitorial Guinea | 7.7 | 74,165 |
Tanzania | 5.5 | 2,550,000 |
Uganda | 5.0 | 1,590,000 |
Table 2 shows that Southern African countries are the worst affected by HIV infections, with Eswatini, Lesotho, Botswana, Zimbabwe, and South Africa at the top 5 global list of countries with the highest RHP. In addition to the already highlighted broader poverty-related challenges faced by S-SA, it is important to consider that, even though global accessibility to ARVs has increased over the years, not all HIV patients can access them, and not all patients respond well to treatment. The latter was affirmed in a study conducted in Kenya by Masaba et al. (2023), in which virologic treatment failure (VTF) was observed in some patients. VTF refers to an ART response that is either suboptimal or not sustained. According to the authors, risk factors for VTF include poor ART adherence, suboptimal ARV regimens, treatment interruption, prolonged ARV therapy, low baseline CD4 count, opportunistic infections, and tuberculosis (TB) co-infection. Therefore, the correct identification, interpretation, and handling of the highlighted risk factors are very critical in accomplishing viral suppression, reducing HIV transmission, and making strides in the direction of epidemic management. On the brighter side, UNAIDS revealed that 86% of PLH were aware of their HIV status in 2023. Of those, 89% were receiving treatment, and of the treated, 93% achieved viral suppression. This is an impressive milestone toward the achievement of the 95-95-95 targets by 2030.
A comprehensive understanding of the ART and HIV prevalence statistics could serve as an indicator for the current global status of the pandemic, ART accessibility and progress made so far. Additionally, treatment gaps, HIV hotspots, vulnerable groups, and public awareness shortcomings could be identified and appropriate interventions rendered by policymakers, healthcare personnel, and other relevant stakeholders. Widely used and effective ART could be identified and production increased, while ART with adverse side effects could be substituted with milder formulations. On the other hand, the occurrence of antiretrovirals in the environment informs the pharmaceutical companies about their extent of bioavailability and biodegradability, which could be used to improve/develop new drug formulations with favorable characteristics.
OVERVIEW OF ARVs IN THE AQUATIC ENVIRONMENT
The concentrations of various ARV residues detected in the aqueous environment across the globe are displayed in Table 3.
ARVs prevalence in WWTPs, surface water, drinking water, and groundwater
ARV drugs . | Maximum concentration (ng/L) . | References . | ||||
---|---|---|---|---|---|---|
Influent . | Effluent . | Surface water . | Drinking water . | Groundwater . | ||
EFV | 34,000 | 34,000 | – | – | – | South Africaa |
17,400 | 7,100 | – | – | – | South Africab | |
14,000 | – | South Africab | ||||
15,400 | 9,150 | – | – | – | South Africac | |
– | – | <LOQ | – | – | South Africad | |
– | – | 303 | – | 71 | South Africae | |
– | – | 354 | – | – | South Africaf | |
– | – | 48,300 | 0.1 | 0.1 | South Africag | |
– | – | 560 | – | – | Kenyah | |
91.7 | 43.9 | 13.3 | – | – | Chinai | |
1,020 | 110 | – | – | – | Kenyah | |
EFVM | 12,400 | 8,040 | – | – | – | South Africac |
NVP | 1486.1 | <LOQ | 1,480 | – | – | South Africad |
2,100 | 320 | – | – | – | South Africab | |
92 | 473 | – | – | – | South Africab | |
2,100 | 1,900dw | – | – | – | South Africaa | |
2,800 | 1,400 | – | – | – | South Africaa | |
681 | 658 | – | – | – | South Africac | |
– | – | 410 | – | – | Zambiaa' | |
– | – | 71 | – | 13 | SouthAfricae | |
– | 0.4 | 3.5 | 5.4 | – | South Africag | |
– | – | – | – | 4.9 | South Africag | |
– | – | – | n.d | – | Francej | |
– | – | 227 | – | – | South Africak | |
– | – | 330 | – | – | Kenyal | |
– | 2,080 | 600 | – | – | Kenyah | |
1,357 | 4,859 | – | – | Kenyam | ||
– | – | n.d | – | – | Finlandn | |
– | – | 5,620 | – | 1,600 | Kenyah | |
– | – | – | – | 27.3 | USAo | |
– | – | 1.9 | – | – | Francep | |
21.8 | 32 | 17 | – | – | Germanyq | |
4.8 | 7.2 | – | – | – | Germanyq | |
1.59 | 1.86 | 1.36 | – | – | ||
NVPM | 519 | <LOQ | – | – | – | South Africac |
AZT | 100,000 | 1,500 | <LOQ | – | – | Kenyar |
20,100 | 110 | 17,410 | – | 30 | Kenyah | |
– | 510 | 7,680 | – | – | Kenyam | |
53,000 | 500 | – | – | – | South Africaa | |
11,000 | 430 | – | – | – | South Africaa | |
– | 452 | 973 | 72.7 | – | South Africad | |
– | – | 0.3 | 1.9 | – | South Africag | |
62 | 37 | – | – | – | Finlandn | |
– | – | – | n.d | – | Francej | |
– | – | 60 | – | – | Francep | |
310 | 98.2 | 170 | – | – | Germanyq | |
380 | 564 | – | – | – | Germanyq | |
– | – | 30 | – | – | Germanys | |
– | – | n.d | – | – | Chinat | |
3TC | 405,000 | 50,000 | – | – | – | Kenyar |
60,680 | 31,070 | 167,000 | – | – | Kenyah | |
31,100 | 3,985 | 5,428 | – | – | Kenyam | |
– | – | 3,150 | – | – | Kenyal | |
– | – | 2.6 | – | – | Franceu | |
– | – | 20 | <1 | 1.8 | Germanyv | |
720 | <LOQ | n.d | – | – | Germanyq | |
210 | <LOQ | – | – | – | Germanyq | |
– | – | 12 | – | – | Finlandn | |
– | – | – | – | 25.2 | USAo | |
– | – | – | 4 | – | USAw | |
2,200 | 130 | – | – | – | South Africaa | |
1,900 | <LOD | – | – | – | South Africaa | |
– | n.d | 242 | – | – | South Africad | |
– | – | 4.9 | – | – | Japanu | |
– | – | – | <LOQ | <LOQ | South Africag | |
20,900 | <LOQ | – | – | – | South Africac | |
– | – | – | n.d | – | Francej | |
79.3 | <LOD | 19.7 | – | – | Chinai | |
– | – | 6.6 | – | – | Francep | |
3TC-COOH | 25 | 220 | 230 | 84 | – | Germanys |
ABC | <LOD | <LOD | – | – | – | South Africaa |
14,000 | <LOD | – | – | – | South Africaa | |
3,500 | <LOD | – | – | – | South Africaa | |
– | – | <LOQ | – | <LOD | South Africag | |
0.5 | South Africag | |||||
6.15 | 1.11 | 0.39 | – | – | Chinai | |
– | 33 | 2.6 | – | – | Francex | |
– | – | – | n.d | – | Francej | |
21 | <LOQ | <LOQ | – | – | Germanys | |
225 | <LOQ | 1.4 | – | – | Germanyq | |
81.7 | <LOQ | – | – | – | Germanyq | |
ABC-COOH | – | 86 | <5.0 | <LOQ | 10 | Germanyv |
FTC | 172,000 | 41,700 | – | – | – | South Africac |
– | – | 13 | – | – | South Africae | |
980 | – | 280 | – | – | Germanys | |
– | <380 | 45 | <LOQ | 3.9 | Germanyv | |
FTC-COOH | – | – | 110 | <LOQ | 370 | Germanyv |
FTC-S-Oxide | – | – | 200 | <LOQ | 23 | Germanyv |
– | – | 280 | – | – | Germanys | |
STV | – | n.d | 780 | – | – | South Africad |
– | – | – | <LOD | 0.9 | South Africag | |
778 | – | – | – | – | Kenyal | |
– | – | 440 | – | – | Kenyal | |
n.d | Chinat | |||||
11.6 | <LOQ | – | – | – | Germanyq | |
22.8 | <LOQ | |||||
TFV | – | n.d | 189–243 | – | – | South Africad |
– | – | – | – | 2.4 | South Africag | |
RTV | 17,000 | 3,500 | – | – | – | South Africaa |
<LOQ | <LOQ | – | – | – | South Africac | |
– | – | – | n.d | – | Francej | |
– | – | 17 | – | – | Francep | |
– | 90.0 | – | – | – | Switzerlandy | |
– | – | 0.1 | 156.6 | – | South Africad | |
187 | 64 | 36.7 | – | – | Chinai | |
DID | – | 3.3 | – | – | 0.1 | South Africag |
– | – | 54.0 | – | – | South Africad | |
DRV | 43,000 | 17,000 | – | – | – | South Africaa |
920 | 350 | – | – | – | South Africaa | |
– | – | 72.7 | 169 | – | Polandz | |
LPV | – | 130 | 42,700 | <LOQ | <LOQ | South Africag |
– | – | 239 | <LOQ | South Africad | ||
2,500 | 3,800 | – | – | – | South Africaa | |
1,300 | 3,800 | South Africaa | ||||
– | – | <LOD | – | – | Francep | |
829 | 584 | 121 | – | – | Chinai | |
RTV | 3,200 | 1,500 | – | – | – | South Africaa |
1,600 | 910 | – | – | – | South Africaa | |
– | – | 39,400 | – | – | South Africag | |
12 | – | – | South Africad | |||
– | – | 0.5 | – | – | Francep | |
AZT | 64 | 78 | – | – | – | South Africaa |
1,400 | 740 | – | – | – | South Africaa | |
IDV | 260 | 25 | – | – | – | South Africaa |
590 | 42 | – | – | – | South Africaa | |
– | – | – | <LOQ | – | Francex | |
NFV | – | – | – | 1.1 | <LOD | South Africag |
– | – | n.d | – | – | Frances | |
– | – | – | n.d | – | Francej | |
SQV | <LOD | <LOD | – | – | <LOD | South Africaa |
180 | <LOD | – | – | – | South Africaa | |
– | – | – | 0.1 | – | South Africag | |
– | – | – | n.d | – | Francex | |
RAL | 17,000 | 3,500dw | – | – | – | South Africaa |
810 | 86 | – | – | – | South Africaa | |
1.3 | South Africag | |||||
ZCB | – | – | 71.3 | 8.4 | – | South Africad |
ARV drugs . | Maximum concentration (ng/L) . | References . | ||||
---|---|---|---|---|---|---|
Influent . | Effluent . | Surface water . | Drinking water . | Groundwater . | ||
EFV | 34,000 | 34,000 | – | – | – | South Africaa |
17,400 | 7,100 | – | – | – | South Africab | |
14,000 | – | South Africab | ||||
15,400 | 9,150 | – | – | – | South Africac | |
– | – | <LOQ | – | – | South Africad | |
– | – | 303 | – | 71 | South Africae | |
– | – | 354 | – | – | South Africaf | |
– | – | 48,300 | 0.1 | 0.1 | South Africag | |
– | – | 560 | – | – | Kenyah | |
91.7 | 43.9 | 13.3 | – | – | Chinai | |
1,020 | 110 | – | – | – | Kenyah | |
EFVM | 12,400 | 8,040 | – | – | – | South Africac |
NVP | 1486.1 | <LOQ | 1,480 | – | – | South Africad |
2,100 | 320 | – | – | – | South Africab | |
92 | 473 | – | – | – | South Africab | |
2,100 | 1,900dw | – | – | – | South Africaa | |
2,800 | 1,400 | – | – | – | South Africaa | |
681 | 658 | – | – | – | South Africac | |
– | – | 410 | – | – | Zambiaa' | |
– | – | 71 | – | 13 | SouthAfricae | |
– | 0.4 | 3.5 | 5.4 | – | South Africag | |
– | – | – | – | 4.9 | South Africag | |
– | – | – | n.d | – | Francej | |
– | – | 227 | – | – | South Africak | |
– | – | 330 | – | – | Kenyal | |
– | 2,080 | 600 | – | – | Kenyah | |
1,357 | 4,859 | – | – | Kenyam | ||
– | – | n.d | – | – | Finlandn | |
– | – | 5,620 | – | 1,600 | Kenyah | |
– | – | – | – | 27.3 | USAo | |
– | – | 1.9 | – | – | Francep | |
21.8 | 32 | 17 | – | – | Germanyq | |
4.8 | 7.2 | – | – | – | Germanyq | |
1.59 | 1.86 | 1.36 | – | – | ||
NVPM | 519 | <LOQ | – | – | – | South Africac |
AZT | 100,000 | 1,500 | <LOQ | – | – | Kenyar |
20,100 | 110 | 17,410 | – | 30 | Kenyah | |
– | 510 | 7,680 | – | – | Kenyam | |
53,000 | 500 | – | – | – | South Africaa | |
11,000 | 430 | – | – | – | South Africaa | |
– | 452 | 973 | 72.7 | – | South Africad | |
– | – | 0.3 | 1.9 | – | South Africag | |
62 | 37 | – | – | – | Finlandn | |
– | – | – | n.d | – | Francej | |
– | – | 60 | – | – | Francep | |
310 | 98.2 | 170 | – | – | Germanyq | |
380 | 564 | – | – | – | Germanyq | |
– | – | 30 | – | – | Germanys | |
– | – | n.d | – | – | Chinat | |
3TC | 405,000 | 50,000 | – | – | – | Kenyar |
60,680 | 31,070 | 167,000 | – | – | Kenyah | |
31,100 | 3,985 | 5,428 | – | – | Kenyam | |
– | – | 3,150 | – | – | Kenyal | |
– | – | 2.6 | – | – | Franceu | |
– | – | 20 | <1 | 1.8 | Germanyv | |
720 | <LOQ | n.d | – | – | Germanyq | |
210 | <LOQ | – | – | – | Germanyq | |
– | – | 12 | – | – | Finlandn | |
– | – | – | – | 25.2 | USAo | |
– | – | – | 4 | – | USAw | |
2,200 | 130 | – | – | – | South Africaa | |
1,900 | <LOD | – | – | – | South Africaa | |
– | n.d | 242 | – | – | South Africad | |
– | – | 4.9 | – | – | Japanu | |
– | – | – | <LOQ | <LOQ | South Africag | |
20,900 | <LOQ | – | – | – | South Africac | |
– | – | – | n.d | – | Francej | |
79.3 | <LOD | 19.7 | – | – | Chinai | |
– | – | 6.6 | – | – | Francep | |
3TC-COOH | 25 | 220 | 230 | 84 | – | Germanys |
ABC | <LOD | <LOD | – | – | – | South Africaa |
14,000 | <LOD | – | – | – | South Africaa | |
3,500 | <LOD | – | – | – | South Africaa | |
– | – | <LOQ | – | <LOD | South Africag | |
0.5 | South Africag | |||||
6.15 | 1.11 | 0.39 | – | – | Chinai | |
– | 33 | 2.6 | – | – | Francex | |
– | – | – | n.d | – | Francej | |
21 | <LOQ | <LOQ | – | – | Germanys | |
225 | <LOQ | 1.4 | – | – | Germanyq | |
81.7 | <LOQ | – | – | – | Germanyq | |
ABC-COOH | – | 86 | <5.0 | <LOQ | 10 | Germanyv |
FTC | 172,000 | 41,700 | – | – | – | South Africac |
– | – | 13 | – | – | South Africae | |
980 | – | 280 | – | – | Germanys | |
– | <380 | 45 | <LOQ | 3.9 | Germanyv | |
FTC-COOH | – | – | 110 | <LOQ | 370 | Germanyv |
FTC-S-Oxide | – | – | 200 | <LOQ | 23 | Germanyv |
– | – | 280 | – | – | Germanys | |
STV | – | n.d | 780 | – | – | South Africad |
– | – | – | <LOD | 0.9 | South Africag | |
778 | – | – | – | – | Kenyal | |
– | – | 440 | – | – | Kenyal | |
n.d | Chinat | |||||
11.6 | <LOQ | – | – | – | Germanyq | |
22.8 | <LOQ | |||||
TFV | – | n.d | 189–243 | – | – | South Africad |
– | – | – | – | 2.4 | South Africag | |
RTV | 17,000 | 3,500 | – | – | – | South Africaa |
<LOQ | <LOQ | – | – | – | South Africac | |
– | – | – | n.d | – | Francej | |
– | – | 17 | – | – | Francep | |
– | 90.0 | – | – | – | Switzerlandy | |
– | – | 0.1 | 156.6 | – | South Africad | |
187 | 64 | 36.7 | – | – | Chinai | |
DID | – | 3.3 | – | – | 0.1 | South Africag |
– | – | 54.0 | – | – | South Africad | |
DRV | 43,000 | 17,000 | – | – | – | South Africaa |
920 | 350 | – | – | – | South Africaa | |
– | – | 72.7 | 169 | – | Polandz | |
LPV | – | 130 | 42,700 | <LOQ | <LOQ | South Africag |
– | – | 239 | <LOQ | South Africad | ||
2,500 | 3,800 | – | – | – | South Africaa | |
1,300 | 3,800 | South Africaa | ||||
– | – | <LOD | – | – | Francep | |
829 | 584 | 121 | – | – | Chinai | |
RTV | 3,200 | 1,500 | – | – | – | South Africaa |
1,600 | 910 | – | – | – | South Africaa | |
– | – | 39,400 | – | – | South Africag | |
12 | – | – | South Africad | |||
– | – | 0.5 | – | – | Francep | |
AZT | 64 | 78 | – | – | – | South Africaa |
1,400 | 740 | – | – | – | South Africaa | |
IDV | 260 | 25 | – | – | – | South Africaa |
590 | 42 | – | – | – | South Africaa | |
– | – | – | <LOQ | – | Francex | |
NFV | – | – | – | 1.1 | <LOD | South Africag |
– | – | n.d | – | – | Frances | |
– | – | – | n.d | – | Francej | |
SQV | <LOD | <LOD | – | – | <LOD | South Africaa |
180 | <LOD | – | – | – | South Africaa | |
– | – | – | 0.1 | – | South Africag | |
– | – | – | n.d | – | Francex | |
RAL | 17,000 | 3,500dw | – | – | – | South Africaa |
810 | 86 | – | – | – | South Africaa | |
1.3 | South Africag | |||||
ZCB | – | – | 71.3 | 8.4 | – | South Africad |
Note: n.d, not detected; –, not available; <LOD, below limit of detection; <LOQ, below limit of quantification. a(Abafe et al. 2018), b(Schoeman et al. 2015), c(Mosekiemang et al. 2019), d(Wood et al. 2015), e(Rimayi et al. 2018), f(Wooding et al. 2017), g(Swanepoel 2015), h(K'oreje et al. 2016), i(Yao et al. 2021), j(Dévier et al. 2013), k(Wooding et al. 2017), l(K'oreje et al. 2012), m(Ngumba et al. 2016a), n(Ngumba et al. 2016b), o(Fisher et al. 2016), p(Aminot et al. 2015), q(Prasse et al. 2010), r(K'oreje et al. 2018), s(Funke et al. 2016), t(Peng et al. 2014), u(Azuma et al. 2016), v(Boulard et al. 2018), w(Furlong et al. 2017), x(Aminot et al. 2016), y(Margot et al. 2013), z(Giebułtowicz et al. 2018), and a'(Ngumba et al. 2020b).
Elevated levels of ARVs have been reported in South Africa and Kenya (Table 3), with the highest concentrations of AZT, 3TC, EFV, and NVP, found in WWTPs and surface water. While this suggests low removal efficiency in WWTPs, the data corresponds with the levels of prescription in the two regions. South Africa, with the highest HIV-positive population (∼9.2 million), administered the world's largest ART program, with an estimated 5.4 million people on ARV treatment by June 2022 (Voigt 2022). Kenya has the highest persistence of ARV drugs in surface water (Table 3), which may be caused by direct WWTP and industrial discharges, waste disposal sites, and informal settlements (Ngumba et al. 2016a). AZT, 3TC, EFV, and NVP constitute the first-line daily ART (Paengsai et al. 2019), which could further explain the observed elevated environmental persistence. However, EFV has since been replaced with DTG in the new DTG-based regimens, which could result in reduced EFV environmental occurrence. Table 3 shows that most of the studies were conducted in S-SA compared with only a few in the Western countries. Again, the data probably reflects higher HIV prevalence and ARVs prescription in S-SA than in the West. Nonetheless, the limited coverage of studies renders the data insufficient to give a full representative status of the environmental persistence of ARVs in Africa or Europe. Furthermore, it has been noted that only a few compounds, particularly the most persistent are being considered in the water pollution studies. As much as this makes sense, it also neglects other potentially persistent and more toxic ARVs in the entire environment. Moreover, some ARVs, particularly those with log Kow > 4 may prevail more in the soil. To get more conclusive results, environmental occurrence studies must include soil sediments and cover a wider range of countries in all the regions.
BIODEGRADATION MECHANISMS AND ENVIRONMENTAL FATE OF ARVs
From Figure 2, all the potential sources of ARV residues eventually discharge into WWTPs. Thus, the environmental fate of the ARVs is determined in the WWTPs. Depending on the wastewater treatment processes, physicochemical properties (solubility, pKa, and Kow) of ARVs and their reaction mechanism, these compounds are partly or completely degraded and released into the aquatic matrices as parent molecules, transformation products, or degradation products. This is in agreement with Russo et al. (2018). EFV and NVP residues have been detected in the WWTP effluent streams in many studies (Nannou et al. 2020). This was attributed to the parent substrates dislodging from solids in the sludge and the potential bio-deconjugation of the glucuronide conjugates and hydroxylated NVP transformation products (TPs) (Schoeman et al. 2017).
In the environment, ARVs become exposed to different processes, including photolysis, biodegradation, hydrolysis, and sorption, with a possibility of further decomposition (Ncube et al. 2018). In one study, Prasse et al. (2010) proposed that the mechanism of FTC degradation was by photo-transformation under environmental conditions, whereas Funke et al. (2016) suggested biodegradation forming oxide and carboxy metabolites. Kim et al. (2017) reported the environmental biodegradation of TFV with a half-life of 32 days. In a similar study, TFV was found to persist in the soil, with no TPs detected (Al-Rajab et al. 2010). According to Silva et al. (2019), this could be attributed to TFV's high stability and sparing solubility in the aqueous environment. On the other hand, NVP poses extended environmental prevalence presumably because of its high photostability, bioactivity, prolonged half-life, and inferior biodegradability (Prasse et al. 2010).
Literature shows that less attention is directed toward studying the environmental fate of ARVs, which is disturbing since this aspect remains unclear. This knowledge is crucial for a better understanding of the biodegradability, reaction kinetics, and degradation mechanism of ARVs under environmental conditions. The data could be used to improve/develop new ARV formulations with enhanced bioavailability and biodegradability properties. This could result in lesser excretion of non-biodegradable forms (which may be more toxic), effective ARV biodegradation in wastewater, and reduced environmental persistence.
HUMAN AND ECOTOXICOLOGICAL IMPACT OF ARVs IN THE AQUATIC ENVIRONMENT
Unintended exposure to environmental residues of ARVs can harbor significant threats to human health and the environment. Potential consequences include threats to drinking water safety, ecotoxicological effects, antiviral resistance, disruption of microbial communities, and impaired functionality of WWTPs. Additionally, these compounds can lead to decreased growth rates, reproductive impairments, developmental anomalies, behavioral alterations, and disrupted physiological functions in terrestrial and aquatic organisms. Long-term exposure can destabilize population dynamics and disrupt the ecological balance of aquatic ecosystems. Table 3 summarizes the reported ecotoxicological impact of ARVs in the aquatic environment.
Table 4 shows that most ARVs exhibit ecotoxicological effects on aquatic life, particularly fish, algae, and daphnia. Additionally, the biodegradation of TFV in a recent study, using the cyanobacteria/bacterial culture, revealed that its TP, tenofovir isoproxil monoester, was partially active and inhibitory to DNA synthesis (Silva et al. 2024). Therefore, its continued prevalence in the environment may be detrimental to the genetic make-up of the exposed organisms.
Ecotoxicological effects of non-target exposure to ARVs (Minguez et al. 2016; Russo et al. 2018; Adeola & Forbes 2022; Kudu et al. 2022; Nugnes et al. 2024)
Antiretroviral drugs . | Ecotoxicological effects . |
---|---|
Abacavir | Potential ecotoxicity on algae |
Efavirenz | Liver impairment, overall deterioration in fish health |
Zidovudine | Blood toxicity and cancer-causing effects observed in rats |
Nevirapine | Possible toxic effects on fish, algae, and daphnia |
Reduced growth rate in Oreochromis mossambicus | |
Tenofovir | Chronic toxicity to fish, daphnia, A. fischeri, C. dubia |
Lopinavir | 50% reproduction inhibition in rotifers |
Ritonavir | Impaired cell growth and viability |
Lopinavir/Ritonavir | Chronic toxicity effects on fish and daphnia |
50% reproduction inhibition in rotifers | |
Bioaccumulation potential in the environment |
Antiretroviral drugs . | Ecotoxicological effects . |
---|---|
Abacavir | Potential ecotoxicity on algae |
Efavirenz | Liver impairment, overall deterioration in fish health |
Zidovudine | Blood toxicity and cancer-causing effects observed in rats |
Nevirapine | Possible toxic effects on fish, algae, and daphnia |
Reduced growth rate in Oreochromis mossambicus | |
Tenofovir | Chronic toxicity to fish, daphnia, A. fischeri, C. dubia |
Lopinavir | 50% reproduction inhibition in rotifers |
Ritonavir | Impaired cell growth and viability |
Lopinavir/Ritonavir | Chronic toxicity effects on fish and daphnia |
50% reproduction inhibition in rotifers | |
Bioaccumulation potential in the environment |
Although a growing research interest in the environmental impact of ARVs has been noted recently, the limited ecotoxicology data may still indicate a research lag in this important field. However, some authors have resorted to environmental risk assessments to gain an insight into the potential environmental hazards of ARVs. In this approach, a risk quotient (RQ) index is utilized whereby zero risk: RQ < 0.1, low: 0.1 ≤ RQ < 1, medium: 1 ≤ RQ < 10, and high risk: RQ ≥ 10. For example, in one study, the ARVs were reported to exhibit a chronic risk on fish, daphnia, and algae in the order EFV > LPV > RTV > NVP > AZT, with EFV showing RQ > 10 (Ngwenya & Musee 2023). In the same study, 3TC, TFV, and DID showed zero to low risk. The discrepancy in the results could probably be due to drug differences in structure and physicochemical properties. In another related study, microalgae Pseudokirchneriella subcapitata showed high tolerance to elevated concentrations of ARVs (3TC, ABC, DRV, and NVP) with 0.012 < EC50 ≤ 110 mg/L after 72 h of exposure (Reddy et al. 2021). This could be taken advantage of in developing new biological treatment regimes to enhance/complement the efficiency of the traditional ACS systems in eliminating EPs such as ARVs.
On the other hand, the corresponding studies on the human effects of environmental exposure to ARVs are still lacking. Most of the reported undesirable effects of ARV exposure are based on side effects of overdose, drug abuse, prolonged use, etc. For example, Adeola & Forbes (2022) reported that ARVs can have detrimental effects on the central and peripheral nervous systems of humans, depending on the drug type, class, and combination. Furthermore, NVP was reported to cause skin rash and liver toxicity in humans (Adeola & Forbes 2022).
Combined with the environmental fate knowledge, ecotoxicity data could be used to improve/develop new ARV drug formulations as already highlighted. The data could be further used to formulate policy or legislation governing the environmental monitoring and control of these compounds, considering that there is currently no such legislation. However, more research on the environmental impact, particularly the human health effects, are recommended to gather enough data.
INADEQUACY OF TRADITIONAL WWTPs IN ARVs REMEDIATION
Conventional WWTPs employ primary treatment such as filtration and settling for the removal of solids and debris while the secondary (biological) stage uses biological methods utilizing bacteria to decompose dissolved organic matter (DOM) into simple, non-toxic molecules such as CO2, H2O, and NH3 (Yang et al. 2020). The most common biological technique is the activated sludge process (ACS). Although highly efficient in removing BOD, nutrients, and suspended particle matter, the main disadvantage of most biological processes is that they utilize high energy input and generate a lot of sludge, which makes disposal environmentally problematic (Makinia & Zaborowska 2020).
According to Moreira et al. (2016), ARV residues are eliminated predominantly at the primary and secondary phases of treatment. During primary treatment, ARVs undergo physical removal by sorption onto solid particulate matter/sludge due to their hydrophobic composition (Reddy et al. 2021). In the biological phase, the ARVs undergo biodegradation into smaller molecules and conjugates that can be hydrolyzed and released as the parent compound (Schoeman et al. 2017). While ARVs with aromatic alcohol, nitrile, and ester groups can be easily removed by biodegradation, unsaturated cyclic rings are more resistant to biodegradation and remain persistent in the effluent (Reddy et al. 2021). Furthermore, wastewater matrix components may react with the ARV residues, forming more toxic and persistent substrates (Nannou et al. 2020). Although microorganisms play a crucial role in the biotic breakdown of antiretrovirals in WWTPs (and the environments), other variables influencing the optimal performance of WWTPs are pH, temperature, total suspended solids (TSS), oxygen demand (OD), hydraulic retention time (HRT), sludge retention time (SRT), and biomass/micropollutant concentration (Adeola & Forbes 2022; Kudu et al. 2022). Efficient optimization of these parameters could possibly enhance the elimination of EPs, including ARVs, in WWTPs.
The poor efficacy of the ACS was demonstrated by Vanková (2010) in a previous study to determine the biodegradability of AZT, 3TC, and NVP. The author concluded that the compounds were non-biodegradable, poisonous, and suppressive to the ACS bacteria. Poor EFV elimination (31%) by the ACS system was observed after 35 days of treatment in another study (Malati et al. 2023), indicating resistance to biological degradation by this compound. Mailler et al. (2016) found that while biological treatment is highly effective in removing BOD, nutrients, and suspended particle matter, it is not appropriate for treating wastewater contaminated with recalcitrant organics because of biomass poisoning. This is further confirmed in Table 3 and demonstrates the requirement of tertiary stage treatment.
Tertiary treatment raises the water treatment cost and is only applied when the receiving water body is susceptible to the impact of pollution (Nannou et al. 2020). The traditional tertiary stage often includes coagulation, sedimentation, membrane filtration (reverse osmosis, ultrafiltration), activated carbon (AC), and disinfection (i.e., UV, chlorination, ozonation). However, some ARVs (EFV, FTC, and NVP) were still found persistent in the effluent/sludge of tertiary stage treatment (UV, chlorination, membrane bioreactor (MBR)) (Schoeman et al. 2017; Mosekiemang et al. 2019). This highlights the need to upgrade WWTPs to accommodate the eradication of EPs such as ARVs. Thus, further research into cost-effective and sustainable tertiary treatment is necessary. Examples include developing sustainable integrated biological-advanced oxidation process (AOP) systems.
RECENT ADVANCES IN WASTEWATER TREATMENT STRATEGIES FOR ARV ELIMINATION
It is assumed that photolysis, absorption, adsorption, biodegradation, and bioaccumulation are among the removal mechanisms for ARVs due to their intricate structures and properties (Reddy et al. 2021). Recent studies have explored different AOP strategies in single and hybrid processes, in a quest to improve existing tertiary stage or develop more effective and sustainable treatment regimes for the complete eradication of EPs, including ARVs, in wastewater.
Membrane bioreactor process
The MBR process incorporates membrane separation and aerobic biological processes in the ACS system to help increase the removal efficiency of persistent EPs in wastewater. Although MBR exhibits excellent removal efficiency, the technique has drawbacks that include fouling, restricted water flow, salt build-up, high implementation costs, durability issues, and contaminants that are not eliminated but transferred to the concentrate stream (Al-Asheh et al. 2021). A post-treatment phase and sludge disposal may be necessary for the latter, thus increasing the overall operating expenses. On the other hand, the highlighted constraints can be overcome by benefits like low energy consumption, high-quality effluent, less chemicals, modular design, minimal space requirements, and ease of use and adaptability to existing WWTPs (Muhamad Ng et al. 2021). Additionally, the MBR-SBR system, which combines MBR with sequencing batch reactors (SBRs), allows the coupling of anaerobic and aerobic processes, enhancing the elimination of organic pollutants (Melvin & Leusch 2016). The removal of PHACs from wastewater using MBR has been reported by other authors.
Algae-based technologies
Algae-based technologies have been embraced as sustainable treatment alternatives for the elimination of residual nutrients in WWTPs (Ansari et al. 2019). The technique can also be utilized to produce microalgal biomass for use in various applications, including pigments, biofertilizers, and biofuels (Abdelfattah et al. 2023). Algae can function as a biosorbent for various organic pollutants in the environment because of the chemical composition of their cell wall (chitin, glycan, alginate, and cellulose), which provide crucial sites for adsorption (Reddy et al. 2021). Furthermore, algae have shown higher tolerance to elevated concentrations of ARVs than the reported environmental concentrations (Reddy et al. 2021). Recent advances in algae treatments have demonstrated encouraging results in the total or partial removal of PHACs from wastewater through various mechanisms, including biosorption, bioaccumulation, and intra- and intercellular degradation (Mojiri et al. 2022). Biological processes have been successfully used to remove ARVs in other studies, as illustrated in Table 5.
Removal of ARVs from water using biological processes
ARV . | Treatment . | Medium/Enzyme . | Conditions . | Removal (%) . | References . |
---|---|---|---|---|---|
TFV | Biodegradation | Cyanobacteria/bacterial culture | Tenofovir disoproxil fumarate (TDF): 25 mg/L | 94 | Silva et al. (2024) |
Time: 16 days | |||||
NVP | Algal process | C. tenuitheca | NVP: 50 ng/L | 49 | Reddy et al. (2023) |
T. obliquus | Time: 8 days | 75 | |||
NVP | Biocatalytic PES/HPEI/Combi-CLEA-Lac-Tyr | Laccase and tyrosinase (Commercial enzymes) | NVP: 5 mg/L | 99 | Stuurman et al. (2024) |
pH: 7 | |||||
EFV | Combined biological and biocatalytic process | Trametes versicolor Laccase (enzyme) Ti2NTx MXene (photocatalyst) ABTS (Mediator) | EFV: 5 ppm | 65 | Malati et al. (2023) |
Laccase: 27.6% | |||||
ABTS: 0.6 mM | 88 | ||||
pH: 5 | |||||
Time: 240 min | |||||
ABC | Bioaccumulation | Beetroot | ARV: 4 ug/L | 53 (ABC) | Kunene & Mahlambi (2023) |
EFV | Bio-translocation | Spinach | Time: 3 months | 48 (ABC) | |
NVP | Bio-translocation | Tomato | 42 (EFV) | ||
3TC | Bioaccumulation/bio-translocation | ARV: 100 ug/L | 3,463–691 ng/g | Akenga et al. (2021) | |
EFV | |||||
NVP |
ARV . | Treatment . | Medium/Enzyme . | Conditions . | Removal (%) . | References . |
---|---|---|---|---|---|
TFV | Biodegradation | Cyanobacteria/bacterial culture | Tenofovir disoproxil fumarate (TDF): 25 mg/L | 94 | Silva et al. (2024) |
Time: 16 days | |||||
NVP | Algal process | C. tenuitheca | NVP: 50 ng/L | 49 | Reddy et al. (2023) |
T. obliquus | Time: 8 days | 75 | |||
NVP | Biocatalytic PES/HPEI/Combi-CLEA-Lac-Tyr | Laccase and tyrosinase (Commercial enzymes) | NVP: 5 mg/L | 99 | Stuurman et al. (2024) |
pH: 7 | |||||
EFV | Combined biological and biocatalytic process | Trametes versicolor Laccase (enzyme) Ti2NTx MXene (photocatalyst) ABTS (Mediator) | EFV: 5 ppm | 65 | Malati et al. (2023) |
Laccase: 27.6% | |||||
ABTS: 0.6 mM | 88 | ||||
pH: 5 | |||||
Time: 240 min | |||||
ABC | Bioaccumulation | Beetroot | ARV: 4 ug/L | 53 (ABC) | Kunene & Mahlambi (2023) |
EFV | Bio-translocation | Spinach | Time: 3 months | 48 (ABC) | |
NVP | Bio-translocation | Tomato | 42 (EFV) | ||
3TC | Bioaccumulation/bio-translocation | ARV: 100 ug/L | 3,463–691 ng/g | Akenga et al. (2021) | |
EFV | |||||
NVP |
Note: ABTS, azino-bis (3-ethylbenzothia-zoline-6-sulfonic acid); PES/HPEI/Combi-CLEA-Lac-Tyr, combined cross-linked laccase and tyrosinase immobilised on a polyethersulfone membrane.
From Table 5, TFV was successfully biodegraded in water using the cyanobacteria/bacterial culture. During the first 72 h, abiotic and enzymatic mechanisms linked to an extracellular medium de-esterified TFV, resulting in the tenofovir monoester intermediate. Subsequently, intracellular mechanisms extracted the monoester from the culture media (Silva et al. 2024). According to Tolboom et al. (2019), cyanobacteria species can break down chemical pollutants through mixotrophic metabolisms. When heterotrophic bacteria coexist with cyanobacteria and microalgae, it can be beneficial for lowering energy input (because of in situ O2 production), and CO2 emissions, as well as increasing the amount of available algal biomass (Silva et al. 2024). The increased biomass can be utilized to produce novel sustainable cyanobacteria/bacterial culture for application in the biodegradation of EPs.
The algal process was effective in eliminating NVP from water (Table 5) and displayed a high concentration tolerance (up to 4 μg/L) (Reddy et al. 2023). Tetradesmus obliquus showed higher NVP decomposition potential than Coelastrella tenuitheca. The results correlate with those of Escapa et al. (2017), in which T. obliquus demonstrated higher salicylic acid elimination in a batch culture than Chlorella vulgaris. Reddy et al. (2023) proposed that NVP degradation probably occurred via biosorption and bio-adsorption, which typically occur gradually during the stages of algal growth. The predominant functional groups in the microalgal cell wall give it a negative charge, which makes bio-adsorption more conducive in the presence of positively charged PHAC substrates (Ayangbenro & Babalola 2017). Therefore, the cationic NVP (due to the positively charged amino group) may bind to the microalgal surface through electrostatic interactions. As the cell surface becomes saturated, the availability of biosorption sites decreases, increasing the pollutant's potential for adsorption (Hifney et al. 2021). During the incubation of live algae, increasing biomass concentration results in enhanced pollutant adsorption (Ndlela et al. 2023). According to Reddy et al. (2023), in the presence of low hazardous pollutants, algal species can employ different decontamination strategies such as using energy reserves to boost biomass production or directly investing more, or all of their energy reserves in the decomposition of organic contaminants. Therefore, it is critical to select the right strain of algal species for the elimination of organic pollutants.
An almost complete disappearance of NVP was obtained at neutral pH by biocatalysis (Table 5) and the authors cited the synergistic effect of the combined enzymes and membrane system for the high removals. Considering that the modified membrane had a negative surface at neutral pH (PZC ∼ 1.39), while NVP was positive (pKa ∼2.8) (Stuurman et al. 2024), enhanced NVP removals could be attributed to electrostatic interactions. The results demonstrate that biocatalysis is more effective in destroying NVP in wastewater than single biological processes employed in traditional WWTPs. For example, zero or negative NVP removals have been reported in some WWTPs (Prasse et al. 2010; Mosekiemang et al. 2019). The PES/HPEI/Combi-CLEA-Lac-Tyr membrane was reported to offer potential benefits such as ease of recovery, high biocatalytic activity, and improved enzyme stability, all of which enhance pollutant removals. In addition, the neutral pH conditions make the biocatalytic system even more attractive for wastewater treatment, as it eliminates pH adjustment for environmental discharge compliance. Biocatalysis has also been embedded in metal–organic framework (MOF) membranes and shown increased catalytic potency in the elimination of organic pollutants, due to their nanoporous structure, which activates pollutant molecules near the enzyme surface (Xu et al. 2021).
In a similar study, employing ACS, only 31% of EFV was removed from wastewater after 35 days (Malati et al. 2023). Furthermore, increased EFV concentration was observed in the sludge. Due to its low solubility and high log Kow (Table 1), EFV exhibits a high potential for bioaccumulation, which could explain its accumulation in the sludge. Similar findings were reported in a WWTP by Abafe et al. (2018) and Schoeman et al. (2017), emphasizing the requirement of tertiary stage treatment for effective EFV removals. However, the removals increased by 87% after combining the biological treatment with biocatalysis in the presence of the redox mediator, ABTS (Table 5). In addition, Malati et al. (2023) stated that immobilizing the enzyme on the biocatalyst resulted in decreased charge transfer resistance and a pH-tolerant biocatalyst with enhanced activity over a wide pH range (pH 4–6.5). The results demonstrate the positive effect of the redox mediator in accelerating charge generation, as well as the high efficacy of the combined biological-biocatalytic system in the degradation of EFV. This could lead to lower EFV levels being discharged into the environment.
Nowadays, water from WWTP effluents is widely used to irrigate horticulture crops due to freshwater scarcity. However, literature shows immense contamination of wastewater by PHAC residues (Table 5) due to WWTP inefficiencies, as already discussed. Furthermore, the use of biosolids as fertilizer or soil amendment may increase the concentration of PHACs in agricultural fields (Kunene & Mahlambi 2023). Some studies have documented that both food and non-food crops can absorb PHAC residues from the soil (Akenga et al. 2021; Kunene & Mahlambi 2023). This could result in deteriorating food quality due to the potential risk of passing PHAC residues into the food chain. Therefore, it is not surprising that research interest in agro-field contamination is growing.
The potential uptake of common ARVs (ABC, EFV, and NVP) by vegetable plants (tomato, beetroot, and spinach) from contaminated soil was assessed by Kunene & Mahlambi (2023). All the investigated vegetables demonstrated notable capacity to absorb the target ARVs from contaminated soil through the roots and transfer them to the aerial portion of the plants (Table 5). The results resonate with the earlier findings of Akenga et al. (2021) in lettuce (Table 5). In addition, Akenga et al. (2021) observed potential toxicity (34%) in the exposed root/leaf biomass of the lettuce at 100 μg/L. According to Kunene & Mahlambi (2023), hydrophobicity was the major contributing factor in drug accumulation and translocation. These results are worrying since these vegetables are the most widely used in almost all households, daily. Consumption of polluted plants may result in adverse human health problems and ecotoxicological effects on animals. Moreover, unintended exposure to ARVs may lead to antiviral resistance in HIV patients, as already highlighted.
From these findings, it is important to assess the quality of biosolid-based fertilizers and irrigation wastewater before application in agricultural lands to prevent pollution of food crops. The findings contribute knowledge to the fate of ARVs in agroecosystems and highlight potential toxicity impacts. However, more studies including a wide range of edible plants are recommended to fully comprehend the bioaccumulation and mechanism of uptake. This would help lawmakers and other relevant stakeholders develop mitigatory strategies to prevent the pharmaceutical contamination of agricultural lands.
Adsorption
Adsorption is one of the preferred processes for wastewater remediation. The phenomenon primarily utilizes liquid–solid intermolecular forces of attraction between a solute (adsorbate) and the adsorbent with a surface structure that is highly porous. Numerous benefits come with the technique: it is affordable, works with a variety of adsorbents, is versatile, simple to use, sustainable, produces no harmful byproducts, and has a high efficiency (Khan et al. 2022). For decades, AC has shown remarkable success in water remediation (Streit et al. 2021). In particular, excellent pollutant adsorptions have been displayed by powdered activated carbon (PAC) and granular activated carbon (GAC) (Rodriguez-Narvaez et al. 2017). However, the efficiency of PAC deteriorates with time because of the aging adsorption bed, which hinders the regeneration of active sites. Nonetheless, adsorption with ACs is expensive and has a large carbon footprint, since a lot of energy is needed for their production, yet they are rarely regenerated. Other adsorbents with significant EP removal include metal oxide, zeolites, silica gel, and activated alumina (Rajendran et al. 2022). However, there has been a shift toward cheaper, renewable alternatives such as green agro-waste residues in recent years (Khan et al. 2022; Svensson Grape et al. 2023). This could be due to the global adverse environmental concerns regarding climate change, depletion of natural resources, and waste accumulation. In addition, recent advancements in nanotechnology for water treatment have seen a great increase in the development of nanoadsorbents for wastewater treatment (Zahmatkesh et al. 2023). This could be ascribed to the unique properties of nanomaterials such as large surface area (due to their microstructure), low-cost production, sustainability, and high removals for organic matter and pathogens (Khan et al. 2022). Several studies have explored adsorption in the environmental remediation of PHACs (Mansouri et al. 2021; Khan et al. 2022). However, research focus on the removal of ARVs has been very limited (Table 6).
Removal of ARVs from water using adsorption
ARV . | Adsorbent . | Conditions . | qe (mg/g) . | Kd (L/g) . | References . |
---|---|---|---|---|---|
NVP | Graphene wool (GW) | ARV: 5 mg/L | 48.3 | 2.54 | Adeola et al. (2021) |
EFV | GW: 10 mg/5 ml | 4.41 | 1.46 | ||
Time: 72 h | |||||
LPV | Sewage sludge | ARV: 13 mg/L | 8.64 | 3,449 | Krasucka et al. (2022) |
RTV | pH: 7 | 8.71 | 3,449 | ||
Time: 24 h | |||||
STV | Mondia whitei root | ARV: 1.25 mg/L | 320 | 0.007 | Kebede et al. (2020) |
DID | nanofibers | Dosage: 10 mg/L | 0.022 | ||
RTV | pH: 5 | 0.002 | |||
NVP | Time: 120 min | 0.008 | |||
EFV | 0.001 |
ARV . | Adsorbent . | Conditions . | qe (mg/g) . | Kd (L/g) . | References . |
---|---|---|---|---|---|
NVP | Graphene wool (GW) | ARV: 5 mg/L | 48.3 | 2.54 | Adeola et al. (2021) |
EFV | GW: 10 mg/5 ml | 4.41 | 1.46 | ||
Time: 72 h | |||||
LPV | Sewage sludge | ARV: 13 mg/L | 8.64 | 3,449 | Krasucka et al. (2022) |
RTV | pH: 7 | 8.71 | 3,449 | ||
Time: 24 h | |||||
STV | Mondia whitei root | ARV: 1.25 mg/L | 320 | 0.007 | Kebede et al. (2020) |
DID | nanofibers | Dosage: 10 mg/L | 0.022 | ||
RTV | pH: 5 | 0.002 | |||
NVP | Time: 120 min | 0.008 | |||
EFV | 0.001 |
From the adsorption capacity range, it can be inferred that the Mondia whitei root nanofibers were efficient in the elimination of ARVs from aqueous solution (Table 6). Noteworthy, the nanofibers were processed from the discarded waste fibrous root. This demonstrates the potential application of waste plant material as nanoadsorbents in wastewater treatment. Furthermore, this application contributes to reducing environmental pollution by biomass, which is another global environmental challenge. The characteristic feature of nanomaterials that make them good adsorbents for water treatment is the large surface area to volume ratio, which facilitates high-density active sites conducive for pollutant elimination and the high surface reactivity imparted by the large surface free energy (Kebede et al. 2020).
In another research, GW was found suitable for the adsorption of NVP and EFV from water, achieving 84 and 80% removals, respectively (Adeola et al. 2021). The slightly higher NVP elimination could be attributed to the stronger GW affinity for NVP, as indicated by the larger Kd value for NVP than EFV (Table 6). The suggested removal pathway for EFV was heterogeneous adsorption, whereas a limited heterogeneous and multilayer adsorption pathway was reported for NVP. Furthermore, the GW–NVP interaction was found to be spontaneous and exothermic, while EFV adsorption was an endothermic process and proceeded spontaneously (Adeola et al. 2021). The application of graphene-based nanomaterials (GBNs) for wastewater treatment has been explored by other authors, with impressive results (Reddy et al. 2019). GBNs have since emerged as highly effective next-generation adsorbents for water treatment due to their porous hydrophobic surfaces and high adsorption affinities for a broad range of organic pollutants (Samaraweera & Khan 2023).
Krasucka et al. (2022) assessed the adsorption and desorption of LPV and RTV on three different sewage sludges (SSLs) (Table 6). The authors showed that LPV and RTV could be adsorbed by SSLs, achieving ∼70% sorption efficiency for both drugs, regardless of the SSL type. The large Kd values (Table 6) indicate the high affinity of SSLs for the ARVs, probably explaining the high sorption efficiency. The main pollutant removals were driven by the SSL–ARV interactions, with lesser contributions from other SSL matrix constituents such as metal, inorganic, or organic matter (Krasucka et al. 2022). On the other hand, desorption studies showed poor drug desorption (<15%). Thus, verifying the high affinity of SSL for the ARVs and consequently, potential environmental persistence, which may pose significant environmental risks.
For RTV, these findings correlate with Aminot et al. (2018) in their earlier study to investigate the fate of PHACs discharged into estuarine water. RTV has a large log Kow (>4) (Table 1), which probably explains its high affinity for SSL. Aminot et al. (2018) observed that increasing the amounts of suspended particles greatly accelerated the degradation process. Hence, the authors concluded that the fluctuation in suspended solid concentration is the primary factor that attenuates the stability of PHACs in estuarine environments. However, further studies into the adsorption/desorption of ARVs onto sewage sludge and/or suspended solids are necessary to fully understand their fate, and adsorption mechanism. This would assist in developing effective desorption protocols to alleviate the discharge of residual ARVs with the sludge. The associated risks of such have already been demonstrated in studies involving the uptake of ARVs by plants.
In a slightly different study, Ndilimeke et al. (2021) synthesized an alginate/polyvinylpyrrolidone/activated carbon (AC@PVP@alginate) adsorbent for the determination of AZT and NVP in wastewater. The authors used the adsorbent in a dispersive micro-solid phase extraction method aided by ultrasound before high-performance liquid chromatography (HPLC) analysis. Under optimum conditions, recoveries were in the range 92–99%, confirming the suitability of the method for application in environmental water analysis. In addition, the analysis of influent samples showed the presence of AZT and NVP at maximum concentrations of ∼1.70 μg/L. Overall, the adsorbent was found ideal for the effective adsorption of AZT and NVP. This could be ascribed to its high pore density and wide surface area, as well as the numerous functional groups (Ndilimeke et al. 2021).
Advanced oxidation processes
AOPs offer a favorable approach for degrading most EPs in the aqueous environment, largely because of their higher removal efficiency. The top distinctive feature of most AOPs is their ability to produce extremely reactive free radicals in situ, such as ·OH, which serves as a primary oxidant and can start pollutant degradations (Saravanan et al. 2022). While ·OH has a high redox potential (2.80 V) that enables it to oxidize a wide range of organic pollutants, other less reactive substrates (HO2· and O2−·) can also be formed simultaneously (Ma et al. 2021). The primary goal of AOPs is total mineralization of the pollutant, albeit this goal is not always met. Heterogeneous systems, including photocatalysis, are among the most widely used strategies. Fenton/photo-Fenton, γ-radiolysis, wet air oxidation, EO, and sonolysis are examples of homogeneous processes. Heterogeneous systems are favored more than homogeneous approaches since the latter is linked to the production of large amounts of sludge, which could be difficult to dispose of (Ma et al. 2021). Furthermore, catalyst recovery is frequently impractical, suggesting that the residual catalyst may contaminate water sources. Novel techniques such as microwaves, ferrate reagent, pulsed plasma, and ionizing radiation are also being considered. Table 7 illustrates some previous studies of AOP applications in removing ARVs from water.
Removal of ARVs from water using AOPs
ARVs . | Treatment . | Conditions . | Removal (%) . | k1 (min) . | References . |
---|---|---|---|---|---|
3TC | UV/H2O2 | 3TC: 5 mg/L | 95 | Feliciano et al. (2020) | |
H2O2: 250 mg/L | |||||
Fe: 5 mg/L | |||||
Time: 60 min | |||||
AZT | Ozonation (O3) | AZT: 5 uM | 1.9 × 10−2 | Funke et al. (2021) | |
AZT/O3: 1:2 | |||||
pH: 3 | |||||
Time: 3 h | |||||
NVP, EFV | Chlorination | NVP: 100 ug/L | 48 (NVP) | 5.46 × 10−1 | Hlongwa et al. (2024) |
EFV | pH: 5.5 (NVP) | 68 (EFV) | 5.73 × 10−1 | ||
pH: 8 (EFV) | |||||
Cl−: 5 mg/L | |||||
AZT, 3TC, NVP | UV | ARV: 0.02 mg/L | 90, 48, 13.4 | 1.01 × 10−1 | Ngumba et al. (2020a) |
3TC, NVP | UV/Cl2 | H2O2: 20.4 mg/L | 77.4, 20.8 | 4.2 × 10−2 | |
3TC, NVP | UV/H2O2 | Time: 0.5 h | 72.2, 52.9 | 2.5 × 10−2 | |
AZT | UV; UV/H2O2 | pH: 4–8 | 1.79 × 106 | Russo et al. (2018) | |
STV | pH: 6–8 | 9.87 × 105 |
ARVs . | Treatment . | Conditions . | Removal (%) . | k1 (min) . | References . |
---|---|---|---|---|---|
3TC | UV/H2O2 | 3TC: 5 mg/L | 95 | Feliciano et al. (2020) | |
H2O2: 250 mg/L | |||||
Fe: 5 mg/L | |||||
Time: 60 min | |||||
AZT | Ozonation (O3) | AZT: 5 uM | 1.9 × 10−2 | Funke et al. (2021) | |
AZT/O3: 1:2 | |||||
pH: 3 | |||||
Time: 3 h | |||||
NVP, EFV | Chlorination | NVP: 100 ug/L | 48 (NVP) | 5.46 × 10−1 | Hlongwa et al. (2024) |
EFV | pH: 5.5 (NVP) | 68 (EFV) | 5.73 × 10−1 | ||
pH: 8 (EFV) | |||||
Cl−: 5 mg/L | |||||
AZT, 3TC, NVP | UV | ARV: 0.02 mg/L | 90, 48, 13.4 | 1.01 × 10−1 | Ngumba et al. (2020a) |
3TC, NVP | UV/Cl2 | H2O2: 20.4 mg/L | 77.4, 20.8 | 4.2 × 10−2 | |
3TC, NVP | UV/H2O2 | Time: 0.5 h | 72.2, 52.9 | 2.5 × 10−2 | |
AZT | UV; UV/H2O2 | pH: 4–8 | 1.79 × 106 | Russo et al. (2018) | |
STV | pH: 6–8 | 9.87 × 105 |
The ozonation process was employed to remove AZT from water (Table 7). The degradation process proceeded via O3 attack at the C–C-double bond of the pyrimidine-base (Funke et al. 2021). The major advantages of O3 include reduced sludge formation and being environmentally friendly (Lim et al. 2022). However, single O3 has slow reaction kinetics and does not achieve complete mineralization of recalcitrant organic compounds (Rekhate & Srivastava 2020). Other limitations include pH sensitivity, organic contaminants selectivity, increased turbidity, high cost associated with the energy requirement for O3 generation, and formation of disinfectant byproducts such as chlorites, bromates, and trihalomethanes, which are potential carcinogens (Guo et al. 2020; Ruziwa et al. 2023). In addition, being a hazardous gas, residual O3 requires an ozone destruction cell, which further increases the process cost. To overcome these challenges and improve process efficiency, O3 is often combined with other processes such as H2O2, UV, and photocatalyst. O3-based AOPs have shown high success in destroying various PHACs in wastewater (Prada-Vásquez et al. 2024).
In one study, different AOPs (UV/H2O2, photo-Fenton) and UV photolysis were utilized to decompose 3TC in water under ultraviolet radiation C (UVC) irradiation (Feliciano et al. 2020). Table 7 shows almost complete 3TC degradation using the UV/H2O2. The positive effect of H2O2 was probably due to enhanced ·OH generation and suppressed charge recombination, which has been reported by other authors (Hidayah et al. 2022; Ncube et al. 2023). The authors reported poor removals for photolysis, photo-Fenton, and degradations under sunlight, which could be attributed to insufficient generation of reactive substrates. The generated TPs were found to exhibit ecotoxicity effects on some test species, which agrees with other studies (Horn et al. 2022).
Table 7 shows that a similar study (UV, UV/Cl2, and UV/H2O2) was conducted to assess the post-treatment decomposition of ARVs in wastewater. AZT was easily broken down by direct photolysis, achieving 90% decomposition, whereas photolysis removals were poor for 3TC and NVP (Table 7). To explain this, the authors cited the higher quantum yield for AZT, given that the compound exhibits similar molar extinction coefficients as 3TC and NVP. The rate of degradation increased for all the compounds after the addition of H2O2 and Cl2 to the UV system, probably due to enhanced radical production. Higher k1 values were obtained in ultra pure water (UPW) than in the effluent. This was expected because of matrix effects common in natural wastewater. Lower NVP degradation was obtained with the UV/Cl2 treatment than the UV/H2O2 treatment. The lower oxidation potential of Cl (+1.4) could have caused poor radical generation in the UV/Cl2 system than the UV/H2O2 (1.8 V). It is anticipated that ·OH and chlorine reactive substrates (Cl·, , ClO·) would be the primary oxidants involved in the UV/Cl2 system, under environmentally relevant pH levels. However, in effluent streams, the efficacy of the UV/Cl2 is largely suppressed by the inherent organic content. On the other hand, the dark experiments showed rapid degradation of 3TC and NVP with Cl2 and no removal for all the compounds with UV/H2O2. Direct reactions of H2O2 are generally slow and therefore not considered to be the major mechanism for the breakdown of organic pollutants (Ngumba et al. 2020a). Literature shows that the most important application of H2O2 involves a catalyst and/or photon activation to produce extremely reactive and non-selective ·OH. Ngumba et al. (2020a) further demonstrated the energy requirements for 90% pollutant removals to be in the order UV/H2O2 < UV/Cl2 < UV processes. The pronounced synergism between UV and the stronger H2O2 oxidant possibly contributed to the least energy input in the UV/H2O2.
The degradation of AZT and STV was investigated using the UV254/H2O2 process (Table 7). AZT showed faster reaction kinetics than STV (Russo et al. 2018). This could be explained by its higher quantum yield (28 times > STV) (Russo et al. 2018), which rendered the compound more susceptible to UV irradiation. In addition, the authors observed decreased ecotoxicological effects, typical of ARVs in water, but required high UV doses (≥2,000 mJ/cm2) compared with the traditional water UV disinfection systems. The results signify the efficacy of the UV254/H2O2 in eradicating ARVs from water as well as affirm its disinfection potency.
Greater than 90% NVP and EFV eliminations were observed at higher doses of chlorine (5 mg/L), using the chlorination process (Table 7). However, trihalomethanes (THM) formation was also detected, with bromoform, chloroform, and dibromochloromethane being the most dominant (Hlongwa et al. 2024). Although being the most used disinfection treatment, chlorination may promote the development of disinfection byproducts that may be more hazardous than the parent molecule (Wood et al. 2016). In another study, Hlongwa et al. (2024) observed that the chlorination process was largely influenced by operational variables such as temperature, pH, and chlorine dose. Therefore, emphasizing temperature regulation, pH sensitivity, accurate chlorine dose, and environmental issues such as trihalomethanes (TMH) generation may guarantee efficient disinfection while limiting adverse effects on the environment and water quality.
Photocatalysis
Semiconductor-based photocatalysis has proved to be highly effective in treating EPs contaminated wastewater (Jabbar & Ebrahim 2022). The technique utilizes a photocatalyst under light exposure to destroy organic contaminants. Light supplies the required catalyst activation energy to start radical generation, whereas the photocatalyst facilitates the generation of reactive components (photoelectrons (e−), holes (h+)), and subsequently highly oxidizing substrates (HOS) such as ·OH (Alvarez-Corena et al. 2016). Even though less reactive entities (O2−·, , H2O2) can be generated as well, ·OH shows a high oxidation strength (2.80 V), which enables it to oxidize a broad range of organic contaminants effectively and non-selectively (Jabbar & Ebrahim 2022). However, the cumulative effectiveness of a photocatalytic system is dependent on specific catalyst features, such as morphology, crystal phase, structure, surface area, particle size, porosity, and particle size distribution (Gusain et al. 2020). Furthermore, the point of zero charge (PZC) of the photocatalyst and the pKa of the organic pollutants influence the compound affinities for the catalyst, and consequently, the degree of decomposition. pKa controls the extent of speciation of the compound in water, whereas PZC gives the surface charge of the catalyst. pH is another critical parameter as it directly controls PZC, pKa, pollutant hydrolysis, reaction rate and HOS, and the reaction pathway (Gusain et al. 2020). Other influential operating parameters include oxidant dosage, catalyst loading, irradiation time, and light intensity. Photocatalysis has been widely used to remove EPs, including PHACs, in wastewater (Sendão et al. 2022; Sharma et al. 2023). Table 8 depicts the degradation of ARVs in water using photocatalysis.
Elimination of ARVs in water using photocatalysis
ARV . | Treatment . | Catalyst/Light . | Conditions . | Removal (%) . | k1 (min) . | References . |
---|---|---|---|---|---|---|
3TC | UV/TiO2 | TiO2–P25 | 3TC: 22.9 mg/L | 87 | 5.42 × 10−2 | An et al. (2011) |
UV | TiO2: 1 g/L | |||||
pH: 9 | ||||||
Time: 60 min | ||||||
NVP | UV/(FL-BP@Nb2O5) | FL-BP@Nb2O5 | NVP: 5 mg/L | 68 | 1.52 × 10−2 | Bhembe et al. (2020) |
UV/Visible | Cat: 15 mg/L | |||||
pH: 3 | ||||||
Time: 3 h | ||||||
NVP | UV/TiO2/H2O2 | TiO2 | NVP: 40 μg/L | 89 | 3.96 × 10−2 | Ncube et al. (2023) |
UV/Visible | TiO2: 0.92 g/L | |||||
H2O2: 34 mg/L | ||||||
pH: 3.0 | ||||||
Time: 60 min | ||||||
NVP | Photocatalysis | Ag–AgBr–LDH | NVP: 5 mg/L | 100 | 1.0 × 10−2 mg/L | Tabana et al. (2023) |
EFV | Visible (LED) | pH: neutral | 84 | 3.0 × 10−3 mg/L | ||
Time: 8 h | ||||||
AZT | Photocatalysis | Ba–ZnO (BZO) | AZT: 2E-04 mg/L | 100 | 3.61 × 10−2 | Bhamare & Kulkarni (2019) |
UV | BZO: 0.1 g/L | |||||
pH: 9 | ||||||
AZT | Photocatalysis | Ru–TiO2 | AZT: E-5 M | 96 | – | Bhamare & Kulkarni (2020) |
(RDTDO) | RDTDO: 1 g/L | |||||
UV | pH: 4 | |||||
Time: 100 min | ||||||
ABC | Photocatalysis | GO–TiO2 | ABC: 10 mg/L | 100 | 2.61 × 10−1 | Evgenidou et al. (2023) |
Visible | Catalyst: 0.1 g/L | |||||
pH: netural | ||||||
Time: 20 min | ||||||
MVC | Photocatalysis | TiO2–PMS | MVC: 10 mg/L | 1.480 × 100 | Skibi (2022) | |
UV/Visible | TiO2: 0.1 g/L | 3.75 × 10−1 | ||||
PMS: 2.54 mg/L |
ARV . | Treatment . | Catalyst/Light . | Conditions . | Removal (%) . | k1 (min) . | References . |
---|---|---|---|---|---|---|
3TC | UV/TiO2 | TiO2–P25 | 3TC: 22.9 mg/L | 87 | 5.42 × 10−2 | An et al. (2011) |
UV | TiO2: 1 g/L | |||||
pH: 9 | ||||||
Time: 60 min | ||||||
NVP | UV/(FL-BP@Nb2O5) | FL-BP@Nb2O5 | NVP: 5 mg/L | 68 | 1.52 × 10−2 | Bhembe et al. (2020) |
UV/Visible | Cat: 15 mg/L | |||||
pH: 3 | ||||||
Time: 3 h | ||||||
NVP | UV/TiO2/H2O2 | TiO2 | NVP: 40 μg/L | 89 | 3.96 × 10−2 | Ncube et al. (2023) |
UV/Visible | TiO2: 0.92 g/L | |||||
H2O2: 34 mg/L | ||||||
pH: 3.0 | ||||||
Time: 60 min | ||||||
NVP | Photocatalysis | Ag–AgBr–LDH | NVP: 5 mg/L | 100 | 1.0 × 10−2 mg/L | Tabana et al. (2023) |
EFV | Visible (LED) | pH: neutral | 84 | 3.0 × 10−3 mg/L | ||
Time: 8 h | ||||||
AZT | Photocatalysis | Ba–ZnO (BZO) | AZT: 2E-04 mg/L | 100 | 3.61 × 10−2 | Bhamare & Kulkarni (2019) |
UV | BZO: 0.1 g/L | |||||
pH: 9 | ||||||
AZT | Photocatalysis | Ru–TiO2 | AZT: E-5 M | 96 | – | Bhamare & Kulkarni (2020) |
(RDTDO) | RDTDO: 1 g/L | |||||
UV | pH: 4 | |||||
Time: 100 min | ||||||
ABC | Photocatalysis | GO–TiO2 | ABC: 10 mg/L | 100 | 2.61 × 10−1 | Evgenidou et al. (2023) |
Visible | Catalyst: 0.1 g/L | |||||
pH: netural | ||||||
Time: 20 min | ||||||
MVC | Photocatalysis | TiO2–PMS | MVC: 10 mg/L | 1.480 × 100 | Skibi (2022) | |
UV/Visible | TiO2: 0.1 g/L | 3.75 × 10−1 | ||||
PMS: 2.54 mg/L |
Note: FL-BP@Nb2O5, few-layer black phosphorus coupled with niobium (V) oxide nanoflowers; TiO2–GO, titania–graphene oxide; PMS, peroxymonosulfate.
Table 8 shows that NVP removal from water was the most studied, with various researchers exploring different nanocomposite photocatalysts. This may be attributed to the high persistence of NVP in the aqueous environment (Table 3), as well as its exceptional resistance to traditional wastewater treatment (Mosekiemang et al. 2019). Doped (layered double hydroxides) LDH clay (Ag–AgBr–LDH) nanocomposite demonstrated high efficacy in the elimination of NVP (100%) and EFV (84%) in water (Table 8). Doped LDH clays are widely recognized for their capacity to eliminate contaminants through multiple pathways, including adsolubilization, intercalation, and surface adsorption (Tabana et al. 2023). Surface plasmon resonance and/or the development of Z-scheme heterojunction were the authors' explanations for the removal enhancement. The Ag nanoparticles in the composite catalyst can function as electron mediators in the creation of a Z-scheme heterojunction and enhance the photocatalyst's ability to harvest light through surface plasmon resonance (Tabana et al. 2023). Furthermore, AgBr and LDH could be crucial components as photo-induced e− and h+ sinks in the degradation process. The ·OH and h+ contributed most to the degradation process. The findings illustrate that Ag–AgBr–LDH is a feasible, visible light-active catalyst suitable for removing NVP and EFV.
In another study, Ncube et al. (2023) recorded higher NVP degradation and total organic carbon (TOC) removals than Bhembe et al. (2020) (Table 8). The high TOC removal (86%) indicates almost complete mineralization. Ncube et al. (2023) attributed the impressive results to the synergistic effects of the UV light, TiO2, and H2O2 in the UV/TiO2/H2O2, while Bhembe et al. (2020) cited the heterostructure nature of the catalyst which may have facilitated the rapid generation of reactive adducts leading to the NVP breakdown. In both studies, the pollutant degradations were conducive at acidic conditions (optimum pH 3), which highlights the influence of NVP dissipation in water and consequently the considerable influence of pH on the reaction kinetics.
The TiO2–graphene oxide (GO) catalyst was highly effective for the removal of ABC in water and landfill leachate (Table 8). As expected, the degradation appeared slower in the leachate, resulting in prolonged irradiation exposure (Evgenidou et al. 2023). This could have been caused by the increased leachate matrix complexity, high organic content, as well as radical scavenging by some matrix components. For 3TC, above 80% removal was obtained using the UV/TiO2 process (Table 8). The degradation was highly favorable under alkaline conditions (pH 9), which the authors ascribed to the interactions of the negatively charged TiO2 (PZC ∼ 6.3) with the neutral 3TC (pKa 4.4) at pH 9 (An et al. 2011). High AZT decomposition was recorded in related studies (Bhamare & Kulkarni 2019, 2020) (Table 8). According to the authors, doping decreased the particle size, increased surface area, minimized charge recombination, and increased surface charge transfer, resulting in higher rate of reaction.
Combining TiO2 and PMS (TiO2–PMS) accelerated the degradation rate of MVC in natural water (Table 8) ∼67,000 times faster than direct photolysis (Skibi 2022). It is possible that, in this case, the DOM present in the river water acted as a photosensitizer, absorbing, and transferring photon energy to MVC, resulting in faster degradation kinetics (Skibi 2022). On the other hand, the compound demonstrated incredible photo resistance with a half-life of more than 250 h (Skibi 2022), thus suggesting high potential for bioaccumulation in the environment. The result is very worrying since the environmental fate of MVC is not known. Further studies on the fate of MVC are highly recommended to mitigate potential health and environmental repercussions.
Electrochemical oxidation
EO has demonstrated its superiority in decomposing organic contaminants, owing to its potent oxidation capabilities, high energy efficiency, ease of use, environmental compatibility, and no requirement for secondary treatment (Zhou et al. 2019a; Lan et al. 2022). The ·OH is the principal active component during the EO of organic contaminants and it is generated at the anode, by direct electrolysis of water without additional chemicals (Wang et al. 2022), thus preventing secondary contamination. The efficacy of the EO, therefore, strongly lies with the electrode material, which must have a greater capacity to generate ·OH (Wang et al. 2019). Furthermore, the thickness of the electrode boundary layer has a direct effect on the organic pollutant/·OH rate of reaction. In a conventional parallel plate electrode, the boundary layer thickness is >100 μm, which is far more than the reaction zone thickness (∼1 μm around the anode) (Zhou et al. 2019a). This creates undesirable mass transfer limitations. Therefore, it is imperative to develop new/modify existing EO electrodes capable of enhancing ·OH production, as well as overcoming mass transfer constraints. EO has been broadly employed to eliminate EPs from water, with encouraging results (Gharibian & Hazrati 2022; Wang et al. 2022; Zhang et al. 2022). As far as the elimination of Eps, such as ARVs, from water is concerned, the application of EO is limited. The elimination of ARVs from water using EO is illustrated in Table 9.
Removal of ARVs from water using electrochemical oxidation
ARV . | Electrodes . | Conditions . | Removal (%) . | k1 (min) . | References . |
---|---|---|---|---|---|
ABC | Anode: Ti/SnO2–Sb Cathode: Stainless steel | ABC: 5 mg/L | 97 | 4.8 × 10−1 | Zhou et al. (2019a) |
pH: 5–9 | |||||
J: 0.2 mA/cm2 | |||||
Time: 10 min | |||||
Time: 5 h (5mA/cm2) | 53.3 (TOC) | ||||
3TC | Electrode: Stainless steel | 3TC: 150 mg/L | 96.0 (COD) | 1.66 × 10−2 | Fekadu et al. (2021) |
H2O2: 150 mg/L | |||||
pH: 3 | |||||
Time: 2 h | |||||
3TC | Anode: Ti/SnO2–Sb/Ce–PbO2 Cathode: Stainless steel | 3TC: 2.5 mg/L | 90 | 1.45 × 100 | Wang et al. (2019) |
CO32−: 50 mM | |||||
pH: 6.7 | |||||
J: 10 mA/cm2 | |||||
Time: 4 h | |||||
3TC | Anode: Yb–GO–PbO2 Cathode: Titanium sheets | 3TC: 100 mg/L | 99.6 | Lan et al. (2022) | |
J: 30 mA/cm2 | 65 (COD) | ||||
pH: 9 | |||||
Time: 120 min | |||||
TFV | Persulfate ions ![]() | TFV: 0.3 mM | 99 | 1.29 × 10−1 | Carelle et al. (2022) |
![]() | |||||
I: 300 mA | |||||
pH: 3 | |||||
Time: 30 min | |||||
Time: 90 min | 99.2 (COD) | 4.1 × 10−2 | |||
STV | Anode: Ti/SnO2–Sb Cathode: Stainless steel | STV: 20 ug/L | 90 | 2.4 × 10−1 | Zhou et al. (2019b) |
J: 8 mA/cm2 | |||||
pH: 3 | |||||
Time: 20 min |
ARV . | Electrodes . | Conditions . | Removal (%) . | k1 (min) . | References . |
---|---|---|---|---|---|
ABC | Anode: Ti/SnO2–Sb Cathode: Stainless steel | ABC: 5 mg/L | 97 | 4.8 × 10−1 | Zhou et al. (2019a) |
pH: 5–9 | |||||
J: 0.2 mA/cm2 | |||||
Time: 10 min | |||||
Time: 5 h (5mA/cm2) | 53.3 (TOC) | ||||
3TC | Electrode: Stainless steel | 3TC: 150 mg/L | 96.0 (COD) | 1.66 × 10−2 | Fekadu et al. (2021) |
H2O2: 150 mg/L | |||||
pH: 3 | |||||
Time: 2 h | |||||
3TC | Anode: Ti/SnO2–Sb/Ce–PbO2 Cathode: Stainless steel | 3TC: 2.5 mg/L | 90 | 1.45 × 100 | Wang et al. (2019) |
CO32−: 50 mM | |||||
pH: 6.7 | |||||
J: 10 mA/cm2 | |||||
Time: 4 h | |||||
3TC | Anode: Yb–GO–PbO2 Cathode: Titanium sheets | 3TC: 100 mg/L | 99.6 | Lan et al. (2022) | |
J: 30 mA/cm2 | 65 (COD) | ||||
pH: 9 | |||||
Time: 120 min | |||||
TFV | Persulfate ions ![]() | TFV: 0.3 mM | 99 | 1.29 × 10−1 | Carelle et al. (2022) |
![]() | |||||
I: 300 mA | |||||
pH: 3 | |||||
Time: 30 min | |||||
Time: 90 min | 99.2 (COD) | 4.1 × 10−2 | |||
STV | Anode: Ti/SnO2–Sb Cathode: Stainless steel | STV: 20 ug/L | 90 | 2.4 × 10−1 | Zhou et al. (2019b) |
J: 8 mA/cm2 | |||||
pH: 3 | |||||
Time: 20 min |



The ·OH produced at the anode surface can be quenched by Cl− reducing its concentration, which could inhibit the decomposition of STV. Despite the formation of some oxidative chlorine conjugates (Cl2, ClO−, , and HClO) at the anode surface, their oxidation potentials are lower than that of ·OH (Zhou et al. 2019b). Therefore, STV might not be vulnerable to the oxidative Cl substrates, and the electrochemical breakdown remains inhibited. TPs of STV were identified, with some being more toxic than the parent compound (Zhou et al. 2019b).



The authors further attributed low TFV degradation efficiency under basic media to the inhibitory effect of Fe2+ present in solution, above pH 7.

In comparison with the PbO2 electrode, the Yb–GO–PbO2 electrode was found to possess many desirable properties, such as smaller charge transfer resistance, larger active surface area, and increased O2 evolution potential (Lan et al. 2022). The authors explained the high COD removal at pH 9.0 as being caused by increased ·OH generation at the anode due to the large OH− concentration at alkaline pH. Furthermore, Lan et al. (2022) recorded that the current efficiency was inversely proportional to the current density. This was disturbing as it entails the use of higher voltages, leading to the promotion of side reactions, such as the electrolysis of water. The latter can form O2 at the anode, inhibiting pollutant degradation and consequently decreasing current efficiency. It is, therefore, imperative to strike a balance between current efficiency and removal efficiency when choosing the operating current density to avoid wasteful and costly energy expenditure.







After 4 h of treatment, (39.5%),
(34.3%), and
(10.7%) eliminations were achieved (Wang et al. 2019). Overall, the findings indicate that 3TC can be effectively degraded using the Ti/SnO2–Sb/Ce–PbO2 anode, in the presence of
.
Studies focusing on developing new or modifying existing nanocomposite materials (photocatalysts/electrodes) to extend their absorption range into the visible region, as well as minimize charge recombination, are currently ongoing (Lan et al. 2022; Evgenidou et al. 2023). In addition, eco-friendly energy-saving technologies using free solar radiation provide a cost-effective alternative to UV light.
Degradation mechanisms
Intermediate products can be produced during the wastewater treatment of recalcitrant organic compounds that are not completely degraded. As previously, highlighted, these can pose higher toxicity than the original compounds and persist longer in the aqueous environment. Several authors have detected and identified TPs using different treatment methods (Evgenidou et al. 2023; Malati et al. 2023; Reddy et al. 2023). Proposed degradation routes for the various treatment approaches employed are depicted in the Supplementary material. From these, valuable insights about the fate of ARV drugs in the environment can be derived and used for human health and environmental risk assessments.
RESEARCH GAPS AND FUTURE PERSPECTIVES IN ARV REMEDIATION
The major challenge of conventional WWTPs in completely destroying ARV residues is that they are not designed to treat wastewater contaminated with EPs. An upgrade of wastewater treatment systems to accommodate EPs such as ARVs is necessary. Moreover, there is a continuous emergence of new micropollutants, requiring innovative treatment solutions.
Current ACS could be improved by substituting the bacterial culture with cyanobacteria/bacterial culture. Apart from achieving high EP removal efficiencies, this culture has been shown to be sustainable and exhibits remarkable resistance to high ARV concentrations. Most importantly, optimized wastewater treatment can be achieved through leveraging advanced technologies such as the Internet of Things (IoT) sensors and data analytics. These innovations facilitate real-time monitoring, predictive maintenance, and informed decision-making, thereby enhancing efficiency and minimizing resource waste.
AOP-based technologies have been widely exploited in wastewater treatment, showing the most promising results. However, comparison of experimental results to determine the most efficient process is a major challenge, which also inhibits scale-up initiatives. Further research could explore innovative technological solutions, such as ML, for standardizing experiments or comparing experimental results. Alternatively, tailor-made integrated protocols could be developed for particular/similar WWTPs based on local data.
On the other hand, most of the AOP-based studies only end in the laboratory. Literature shows that the major limitations of AOPs, hampering scale-up applications in wastewater treatment include high operational cost (because of high energy and chemical requirements), low photon efficiency, inadequate visible light utilization, trace contaminant concentration, post-treatment residual catalyst separation, as well as the potential production of more toxic and persistent TPs. Thus, AOPs can be integrated in hybrid systems encompassing other treatment techniques, such as biological methods, to improve their pollutant removal efficiency through synergistic interactions of individual processes. To be economically viable, AOPs may be employed in the primary treatment phase to enhance the biological degradation of refractory EPs or in the post-treatment stage to eliminate poorly biodegraded organic contaminants. Furthermore, research on the development/modification of sustainable superior materials (nanoadsorbents/photocatalysts/electrode) should be intensified. Utilization of waste biomass in these materials should be increased to further reduce costs, as well as minimize biomass environmental pollution and promote the circular economy. Cost-effective technologies would be more beneficial to the developing countries that do not have or have suboptimal tertiary treatment in their WWTPs.
Even though a lot of work has been done on the environmental occurrence and detection of ARVs, studies were only concentrated in a few countries, and not all ARVs in the ART were included. To get more conclusive findings about the global status of ARV residues in the environment, further studies should include soil sediments and cover a wider range of countries in all the regions worldwide.
Further research on the environmental impact of ARVs is necessary, with more focus on the human health risks. This is important, considering that ARVs are administered worldwide and their fate in the environment is not yet clear. Thus, making environmental monitoring and control of these compounds much more challenging. Strict legislative measures for wastewater discharge should be established to minimize surface water contamination. Furthermore, it is imperative that policymakers and healthcare administrators improve public healthcare delivery and provide drug manufacturers with additional incentives to make the ARVs more affordable. This could help address the high rate of HIV prevalence, typically seen in S-SA.
CONCLUSION
The literature and data provided in this review could equip the research community with research gaps for further studies focused on developing innovative and sustainable alternative treatment solutions for the environmental remediation of EPs such as ARVs. Better comprehension of the environmental fate, environmental impact, and human health risks of non-target exposure is crucial for developing the next-generation ARVs with more desirable properties. The overall benefits could entail reduced drug dosage and minimized antiviral resistance in HIV patients, lower environmental concentrations of ARVs, less vigorous wastewater treatment protocols, lower treatment costs, and a higher quality effluent. Additionally, the prevalence rate of HIV/AIDS in a country/region, along with the administration of ART, directly influences the amount of ARVs passing into the environment. Accurate reporting of these parameters enables policymakers and other relevant stakeholders to make informed decisions about the way forward, including appropriate intervention strategies in the fight against the pandemic.
ACKNOWLEDGEMENTS
This work was supported by the University of South Africa (UNISA). Profound thanks go to the Department of Chemistry at UNISA.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.