Markus Andrews

Sachs, J., Kroll, C., Lafortune, G., Fuller, G. & Woelm, F. Sustainable Development Report 2021. Sustainable Development Report 2021 (Cambridge University Press, 2021).Department of Health. Water Quality of Public Drinking Water Supply Systems in Tasmania: Annual Report 2018-19. https://www.health.tas.gov.au/__data/assets/pdf_file/0007/421189/Annual_drinking_water_quality_report_2018-19.pdf (2019).Hall, N. L. et al. Drinking water delivery in the outer Torres Strait Islands: A case study addressing sustainable water issues in remote Indigenous communities. Australas. J. Water Resour. 25, 80–89 (2021).
Google Scholar 
Howey, K. & Grealy, L. Drinking water security: the neglected dimension of Australian water reform. Australas. J. Water Resour 1–10 (2021).Infrastructure Australia. The Australian Infrastructure Audit 2019: An Assessment of Australia’s Future Infrastructure Needs. (2019).Productivity Commission. National Water Reform 2020. www.pc.gov.au (2021).Hall, N. L., Creamer, S., Anders, W., Slatyer, A. & Hill, P. S. Water and health interlinkages of the sustainable development goals in remote Indigenous Australia. npj Clean Water 3, 10 (2020).Article 

Google Scholar 
Maloney, M. et al. 2019 Citizens’ Inquiry into the Health of the Barka / Darling River and Menindee Lakes. https://tribunal.org.au/wp-content/uploads/2020/10/2019CitizensInquiry_BarkaDarlingMenindee-201017-02.pdf (2020).Hartwig, L. D., Jackson, S., Markham, F. & Osborne, N. Water colonialism and Indigenous water justice in south-eastern Australia. International Journal of Water Resources Development https://doi.org/10.1080/07900627.2020.1868980 (2021).The White House. The Biden-Harris Lead Pipe and Paint Action Plan. https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/16/fact-sheet-the-biden-harris-lead-pipe-and-paint-action-plan/ (2021).Office of the Parliamentary Budget Officer. Clean Water for First Nations: Is the Government Spending Enough? https://www.pbo-dpb.gc.ca/en/blog/news/RP-2122-021-M–clean-water-first-nations-is-government-spending-enough–eau-potable-premieres-nations-gouvernement-depense-t-il-assez (2021).New Zealand Government. Government to provide support for water reforms, jobs and growth. https://www.beehive.govt.nz/release/government-provide-support-water-reforms-jobs-and-growth (2021).Infrastructure Australia. Australian Infrastructure Audit 2019. (2019).Infrastructure Australia. 2021 Australian Infrastructure Plan: Reforms to meet Australia’s future infrastructure needs. (2021).Australian Labor Party. Labor’s Plan to Future-Proof Australia’s Water Resources | Policies | Australian Labor Party. https://alp.org.au/policies/labors-plan-to-future-proof-australias-water-resources (2022).Northern Land Council. Submission to the Productivity Commission Review of National Water Reform. (2021).South Australian Council of Social Service. SACOSS Submission to the Productivity Commission’s National Water Reform Draft Report. (2021).Aither/South Australian Council of Social Service. Falling through the gaps: A practical approach to improving drinking water services for regional and remote communities in South Australia. https://www.sacoss.org.au/falling-through-gaps-report, https://doi.org/10.1136/bmj.e7863 (2021).Queensland Water Directorate. National Water Reform 2020: Productivity Commission Draft Report. (2021).Local Government NSW. Draft LGNSW Submission on – Productivity Commission National Water Reform Draft Report. https://www.pc.gov.au/inquiries/completed/water-reform-2020/submissions (2021).National Health and Medical Research Council (Australia). Australian Drinking Water Guidelines 6. (2021).Queensland Health. Public Health Regulation 2018. (2021).State of Victoria. Safe Drinking Water Act 2003. (2019).Water Corporation. Drinking Water Quality: Annual Report 2018–19. https://doi.org/10.1016/0278-6915(93)90134-k.Water Quality Australia. Guidelines for water quality management. https://www.waterquality.gov.au/guidelines (2021).Australian Government. Basin Plan 2012 Compilation No. 8. 269 (2021).World Health Organisation. Guidelines for drinking-water quality: Fourth edition incorporating the first and second addenda. 4 (2022).World Health Organisation. A global overview of national regulations and standards for drinking-water quality ii A global overview of national regulations and standards for drinking-water quality. https://www.who.int/publications/i/item/9789240023642 (2018).Department of Regional Planning Manufacturing and Water. Water Quality and Reporting Guideline for a Drinking Water Service. https://www.rdmw.qld.gov.au/__data/assets/pdf_file/0008/45593/water-quality-reporting-guideline.pdf (2010).Bureau of Meterology. National performance reports. http://www.bom.gov.au/water/npr/ (2021).Australian Government. Reporting Platform on the Sustainable Development Goals Indicators. https://www.sdgdata.gov.au/goals/clean-water-and-sanitation/6.1.1 (2021).Water Corporation WA. Drinking Water Quality Annual Report 2018-19. https://www.watercorporation.com.au/-/media/WaterCorp/Documents/About-us/Our-performance/Drinking-Water-Quality/Drinking-water-quality-annual-report-2019.pdf (2019).South Australian Water Corporation. South Australian Water Corporation Annual Report 2018-19. https://www.sawater.com.au/__data/assets/pdf_file/0006/424662/2018-19-Annual-Report-with-financials-online-ISSN-HR.pdf (2019).Power and Water Corporation. Drinking Water Quality Report 2019. (2019).Urban Utilities. Drinking water quality management plan report 2018–19. (2019).TasWater. Annual Drinking Water Quality Report 2018–19. (2019).Icon Water. 2018-19 Drinking Water Quality Report. (2019).NSW Health. NSW drinking water database – Water quality. https://www.health.nsw.gov.au/environment/water/Pages/drinking-water-database.aspx.New South Wales Department of Planning Industry and Environment. LWU performance monitoring data and reports – Water in New South Wales. https://www.industry.nsw.gov.au/water/water-utilities/lwu-performance-monitoring-data (2021).Office of the Auditor General Western Australia. Delivering Essential Services to Remote Aboriginal Communities – Follow-up. https://audit.wa.gov.au/wp-content/uploads/2021/05/Report-25_Delivering-Essential-Services-to-Remote-Aboriginal-Communities-%E2%80%93-Follow-up.pdf (2021).Audit Office of New South Wales. Support for regional town water infrastructure: Performance audit. https://www.audit.nsw.gov.au/sites/default/files/documents/FINAL%20-%20Support%20for%20regional%20town%20water%20infrastructure.pdf (2020).Federal Race Discrimination Commissioner. Water: A Report on the provision of water and sanitation in remote Aboriginal and Torres Strait Islander communities. (1994).West Australian Auditor General. Delivering Essential Services to Remote Aboriginal Communities. (2015).Green, K. D. Water 2000: a perspective on Australia’s water resources to the year 2000. https://trove.nla.gov.au/work/18184199 (1984).Regional Services Reform Unit. Resilient Families, Strong Communities, Key insights from consultation with remote Aboriginal communities in Western Australia. https://www.parliament.wa.gov.au/publications/tabledpapers.nsf/displaypaper/4010887a7914b1bf3330c905482581bf000764e6/$file/887.pdf (2017).Rajapakse, J. et al. Unsafe drinking water quality in remote Western Australian Aboriginal communities. Geographical Res. 57, 178–188 (2019).Article 

Google Scholar 
Hall, N. L. Challenges of WASH in remote Australian Indigenous communities. J. Water, Sanitation Hyg. Dev. 9, 429–437 (2019).Article 

Google Scholar 
Jaravani, F. G., Massey, P. D., Judd, J., Allan, J. & Allan, N. Closing the Gap: The need to consider perceptions about drinking water in rural Aboriginal communities in NSW, Australia. Public Health Res Pract 26, e2621616 (2016).Article 

Google Scholar 
Jackson, M., Stewart, R. A. & Beal, C. D. Identifying and Overcoming Barriers to Collaborative Sustainable Water Governance in Remote Australian Indigenous Communities. Water 11, 2410 (2019).Article 

Google Scholar 
Beal, C. D., Jackson, M., Stewart, R. A., Rayment, C. & Miller, A. Identifying and understanding the drivers of high water consumption in remote Australian Aboriginal and Torres Strait Island communities. J. Clean. Prod. 172, 2425–2434 (2018).Article 

Google Scholar 
Horne, J. Australian water decision making: are politicians performing? Int. J. Water Resour. Dev. 36, 462–483 (2020).Article 

Google Scholar 
Kurmelvos, R. Company remains shtum on plans to filter Laramba’s contaminated water supply | NITV. NITV News (2021).Kurmelovs, R. & Moore, I. ‘It makes us sick’: remote NT community wants answers about uranium in its water supply | Northern Territory | The Guardian. The Guardian (2021).Archibald-Binge, E. Concerns over water quality in remote Queensland: “This wouldn’t be acceptable in the city” | NITV. NITV News (2018).Richards, S. Oodnadatta residents “suffering” from poor water quality: Aboriginal Health Council. (2020).Parke, E. WA Government urged to fix contaminated water supplies in remote Indigenous communities – ABC News. ABC News (2016).Volkofsky, A., Pezet, L. & McConnell, S. Water donations flow as reports of bad drinking water increase in Darling River communities – ABC News. ABC News (2019).O’Donnell, E., Jackson, S., Langton, M. & Godden, L. Racialized water governance: the ‘hydrological frontier’ in the Northern Territory, Australia. (2022) https://doi.org/10.1080/13241583.2022.2049053.Marshall, V. Overturning aqua nullius: Securing Aboriginal water rights | AIATSIS. (Aboriginal Studies Press, 2017).Grealy, L. & Howey, K. Securing supply: governing drinking water in the Northern Territory. Australian Geographer 341–360 (2020) https://doi.org/10.1080/00049182.2020.1786945.Taylor, K. S., Moggridge, B. J. & Poelina, A. Australian Indigenous Water Policy and the impacts of the ever-changing political cycle. Aust. J. Water Resour. 20, 132–147 (2016).
Google Scholar 
Jackson, S. Water and Indigenous rights: Mechanisms and pathways of recognition, representation, and redistribution. Wiley Interdisciplinary Reviews: Water 5, e1314 (2018).
Google Scholar 
Coalition of Aboriginal and Torres Strait Islander Peak Organisations & Australia Governments. National Agreement on Closing the Gap. https://www.closingthegap.gov.au/sites/default/files/files/national-agreement-ctg.pdf (2020).Jaravani, F. G. et al. Working with an aboriginal community to understand drinking water perceptions and acceptance in rural New South Wales. Int Indigenous Policy J 8, (2017).Beal, C. D. et al. Exploring community-based water management options for remote Australia. Final report for the Remote and Isolated Communities Essential Services Project. https://www.griffith.edu.au/__data/assets/pdf_file/0036/918918/Remote-community-water-management-Beal-et-al-2019-Final-Report-1.pdf (2019).Bailie, R. S., Carson, B. E. & McDonald, E. L. Water supply and sanitation in remote Indigenous communities – Priorities for health development. Aust. N.Z. J. Public Health 28, 409–414 (2004).Article 

Google Scholar 
Thurber, K. A., Long, J., Salmon, M., Cuevas, A. G. & Lovett, R. Sugar-sweetened beverage consumption among Indigenous Australian children aged 0–3 years and association with sociodemographic, life circumstances and health factors. Public Health Nutr. 23, 295 (2020).Article 

Google Scholar 
Dharriwaa Elders Group & Walgett Aboriginal Medical Service. Recommendations for the Review of the National Water Initiative. https://www.sciencedirect.com/science/article/pii/S0264837719319799 (2020).Natural Resouces Commission. Review of the Water Sharing Plan for the Barwon-Darling Unregulated and Alluvial Water Sources 2012. (2019).Browett, H. et al. Cost Implications of Hard Water on Health Hardware in Remote Indigenous Communities in the Central Desert Region of Australia. Int. Indigenous Policy J. 3 (2012).Australian Bureau of Statistics. 1270.0.55.005 – Australian Statistical Geography Standard (ASGS): Volume 5 – Remoteness Structure, July 2016. https://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/1270.0.55.005Main+Features1July%202016?OpenDocument (2016).RiverOfLife, M., Taylor, K. S., & Poelina, A. Living Waters, Law First: Nyikina and Mangala water governance in the Kimberley, Western Australia. Australas. J. Water Resour 25, 40–56 (2021).
Google Scholar 
Jackson, S. & Nias, D. Watering country: Aboriginal partnerships with environmental water managers of the Murray-Darling Basin, Australia. Australas. J. Water Resour. 26, 287–303 (2019).
Google Scholar 
Hemming, S., Rigney, D., Bignall, S., Berg, S. & Rigney, G. Indigenous nation building for environmental futures: Murrundi flows through Ngarrindjeri country. Australas. J. Water Resour. 26, 216–235 (2019).
Google Scholar 
Moggridge, B. J. & Thompson, R. M. Cultural value of water and western water management: an Australian Indigenous perspective. Australas. J. Water Resour. 25, 4–14 (2021).
Google Scholar 
Moggridge, B. J., Betterridge, L. & Thompson, R. M. Integrating Aboriginal cultural values into water planning: a case study from New South Wales, Australia. Australas. J. Water Resour. 26, 273–286 (2019).
Google Scholar 
Hoverman, S. & Ayre, M. Methods and approaches to support Indigenous water planning: An example from the Tiwi Islands, Northern Territory, Australia. J. Hydrol. 474, 47–56 (2012).Article 

Google Scholar 
Jackson, S., Tan, P. L., Mooney, C., Hoverman, S. & White, I. Principles and guidelines for good practice in Indigenous engagement in water planning. J. Hydrol. 474, 57–65 (2012).Article 

Google Scholar 
Jackson, M., Stewart, R. A., Fielding, K. S., Cochrane, J. & Beal, C. D. Collaborating for Sustainable Water and Energy Management: Assessment and Categorisation of Indigenous Involvement in Remote Australian Communities. Sustainability 11, 427 (2019). 2019, Vol. 11, Page 427.Article 

Google Scholar 
New South Wales Water Directorate. Submission 37 – NSW Water Directorate – National Water Reform – Public inquiry. (2021).Natural Resource Management Ministerial Council. National Water Initiative Pricing Principles. https://www.awe.gov.au/water/policy/policy/nwi/pricing-principles (2010).Kukutai, T. & Taylor, J. Indigenous Data Sovereignty. Indigenous Data Sovereignty (ANU Press, 2016). https://doi.org/10.22459/CAEPR38.11.2016.Maiam Nayri Wingara Indigenous Data Sovereignty Collective. Key Principles. https://www.maiamnayriwingara.org/key-principles (2018).Ubaldi, B. Open Government Data: Towards Empirical Analysis of Open Government Data Initiatives. https://doi.org/10.1787/5k46bj4f03s7-en (2013).Sherris, A. R. et al. Nitrate in Drinking Water during Pregnancy and Spontaneous Preterm Birth: A Retrospective Within-Mother Analysis in California. Environ. Health Perspect. 129, 57001 (2021).CAS 
Article 

Google Scholar 
Australian Government PFAS Taskforce. Per- and Polyfluoroalkyl Substances (PFAS): Australian information portal. https://www.pfas.gov.au/ (2021).Environmental Protection Agency. Safe Drinking Water Information System Federal Reports Services System. https://sdwis.epa.gov/ords/sfdw_pub/f?p=108:200 (2021).Indigenous Services Canada. Short-term drinking water advisories. https://www.sac-isc.gc.ca/eng/1562856509704/1562856530304 (2021).Indigenous Services Canada. Ending long-term drinking water advisories. https://www.sac-isc.gc.ca/eng/1506514143353/1533317130660 (2021).ESR Risk and Response Group. Drinking Water Online. https://www.drinkingwater.org.nz/ (2021).Meehan, K. et al. Exposing the myths of household water insecurity in the global north: A critical review. Wiley Interdiscip. Rev.: Water 7, e1486 (2020).
Google Scholar 
O’Gorman, M. Mental and physical health impacts of water/sanitation infrastructure in First Nations communities in Canada: An analysis of the Regional Health Survey. World Dev. 145, 105517 (2021).Article 

Google Scholar 
Baijius, W. & Patrick, R. J. “We Donat Drink the Water Here”: The Reproduction of Undrinkable Water for First Nations in Canada. Water 11, 1079 (2019).Article 

Google Scholar 
Allaire, M., Wu, H. & Lall, U. National trends in drinking water quality violations. Proc Natl Acad Sci USA 115, 2078–2083 (2018).CAS 
Article 

Google Scholar 
Meehan, K., Jurjevich, J. R., Chun, N. M. J. W. & Sherrill, J. Geographies of insecure water access and the housing–water nexus in US cities. Proc. Natl Acad. Sci. USA 117, 28700–28707 (2020).CAS 
Article 

Google Scholar 
Wu, J., Cao, M., Tong, D., Finkelstein, Z. & Hoek, E. M. V. A critical review of point-of-use drinking water treatment in the United States. https://doi.org/10.1038/s41545-021-00128-z.McFarlane, K. & Harris, L. M. Small systems, big challenges: Review of small drinking water system governance. Environ. Rev. 26, 378–395 (2018).Article 

Google Scholar 
Tortajada, C. & Biswas, A. K. Achieving universal access to clean water and sanitation in an era of water scarcity: strengthening contributions from academia. Curr. Opin. Environ. Sustainability 34, 21–25 (2018).Article 

Google Scholar 
Glade, S. & Ray, I. Safe drinking water for small low-income communities: the long road from violation to remediation. Environ. Res. Lett. 17, 044008 (2022).Article 

Google Scholar 
Daley, K., Castleden, H., Jamieson, R., Furgal, C. & Ell, L. Water systems, sanitation, and public health risks in remote communities: Inuit resident perspectives from the Canadian Arctic. Soc. Sci. Med. 135, 124–132 (2015).Article 

Google Scholar 
Dunn, G., Bakker, K. & Harris, L. Drinking Water Quality Guidelines across Canadian Provinces and Territories: Jurisdictional Variation in the Context of Decentralized Water Governance. Int. J. Environ. Res. Public Health 2014 11, 4634–4651 (2014). Vol. 11, Pages 4634-4651.CAS 

Google Scholar 
Herrera, V. Reconciling global aspirations and local realities: Challenges facing the Sustainable Development Goals for water and sanitation. World Dev. 118, 106–117 (2019).Article 

Google Scholar 
Mraz, A. L. et al. Why pathogens matter for meeting the united nations’ sustainable development goal 6 on safely managed water and sanitation. Water Res. 189, 116591 (2021).CAS 
Article 

Google Scholar 
Schiff, J. Measuring the human right to water: An assessment of compliance indicators. Wiley Interdiscip. Rev.: Water 6, e1321 (2019).
Google Scholar 
Charles, K. J., Nowicki, S. & Bartram, J. K. A framework for monitoring the safety of water services: from measurements to security. npj Clean. Water 3, 1–6 (2020).Article 

Google Scholar 
Boisvert, E. SA Water dealing with complaints from some Fleurieu Peninsula residents about change to tap water from Myponga Reservoir – ABC News. ABC News https://www.abc.net.au/news/2021-07-05/fleurieu-residents-complaints-about-water-change/100267414 (2021).Uralla Shire Council. Water Quality Analysis. https://www.uralla.nsw.gov.au/Council-Services/Water-and-Sewer-Services/Water-Quality-Analysis (2021).NSW Health. Drinking water quality and incidents – Water quality. https://www.health.nsw.gov.au/environment/water/Pages/drinking-water-quality-and-incidents.aspx (2021).Kumpel, E. et al. From data to decisions: understanding information flows within regulatory water quality monitoring programs. npj Clean. Water 3, 1–11 (2020).Article 

Google Scholar 
Organisation for Economic Cooperation and Development. OECD Principles on Water Governance. https://www.oecd.org/cfe/regionaldevelopment/OECD-Principles-on-Water-Governance-en.pdf (2015).Wyrwoll, P. R., Manero, A., Taylor, K. S., Rose, E. & Grafton, R. Q. Supporting dataset for “Measuring gaps in drinking water quality and policy in regional and remote Australia.” https://osf.io/vmxdz/?view_only=9f0608088e8143dbbbf2c350ff0e5ca1 (2022). More

The Human Cost of Disasters – An overview of the last 20 years: 2000–2019 (CRED, UNDRR, 2020); https://go.nature.com/3xNXMtqTellman, B. et al. Nature 596, 80–86 (2021).CAS 
Article 

Google Scholar 
Raju, T., Boyd, E. & Otto, F. Commun. Earth Environ. 3, 1 (2022).Article 

Google Scholar 
Parrinello, G. & Kondolf, G. M. Water Hist. 13, 1–12 (2021).Article 

Google Scholar 
Li, D. et al. Science 374, 599–603 (2021).CAS 
Article 

Google Scholar 
Syvitski, J. P. M. & Brakenridge, G. R. GSA Today 23, 4–10 (2013).Article 

Google Scholar 
Chowdhooree, I. Int. J. Disaster Risk Reduc. 40, 101259 (2019).Article 

Google Scholar 
Wilson, R. Turbulent Streams: An Environmental History of Japan’s Rivers, 1600–1930 Vol. 68 (Brill, 2021).Crawford, S. E. et al. J. Hazard. Mater. 421, 126691 (2022).CAS 
Article 

Google Scholar 
Delile, H. et al. Hydrol. Process. 36, e14511 (2022).CAS 
Article 

Google Scholar 
Lake, I. R. et al. Sci. Total Environ. 491–492, 184–191 (2014).Article 

Google Scholar 
Tibbetts, J., Krause, S., Lynch, I. & Sambrook Smith, G. H. Water 10, 1597 (2018).CAS 
Article 

Google Scholar 
Hurley, R., Woodward, J. & Rothwell, J. J. Nat. Geosci. 11, 251–257 (2018).CAS 
Article 

Google Scholar 
Fothergill, L. J., Disney, A. S. & Wilson, E. E. Public Health 198, 141–145 (2021).CAS 
Article 

Google Scholar 
Gutschow, B. et al. Curr. Probl. Pediatr. Adolesc. Health Care 51, 101028 (2021).Article 

Google Scholar 
Andrikopoulou, T., Schielen, R. M. J., Spray, C. J., Schipper, C. A. & Blom, A. Sustainability 13, 11320 (2021).Article 

Google Scholar 
Karvonen, A. Prog. Plann. 74, 153–202 (2010).Article 

Google Scholar 
Boardman, J. & Vandaele, K. Area 42, 502–513 (2010).Article 

Google Scholar 
Lane, S. N. Hydrol. Earth Syst. Sci. 18, 927–952 (2014).Article 

Google Scholar 
Matthewman, S. & Uekusa, S. Theor. Soc. 50, 965–984 (2021).Article 

Google Scholar 
Ekers, M. & Prudham, S. Environ. Plann. A 47, 2438–2445 (2015).Article 

Google Scholar 
Wesselink, A., Kooy, M. & Warner, J. WIREs Water 4, e1196 (2017).Article 

Google Scholar 
Morton, T. Hyperobjects: Philosophy and Ecology after the end of the World (Univ. Minnesota Press, 2013).Rangecroft, S. et al. Hydrol. Sci. J. 662, 214–225 (2021).Article 

Google Scholar  More

Holland, R. A. et al. Global impacts of energy demand on the freshwater resources of nations. Proc. Natl Acad. Sci. U.S.A. 112, E6707–E6716 (2015).CAS 
Article 

Google Scholar 
Gleick, P. H. & Palaniappan, M. Peak water limits to freshwater withdrawal and use. Proc. Natl Acad. Sci. U.S.A. 107, 11155–11162 (2010).CAS 
Article 

Google Scholar 
Oki, T. & Kanae, S. Global hydrological cycles and world water resources. Science. 313, 1068–1072 (2006).CAS 
Article 

Google Scholar 
Postel, S. L., Daily, G. C. & Ehrlich, P. R. Human Appropriation of Renewable Fresh Water. Science. 271, 785–788 (1996).CAS 
Article 

Google Scholar 
United Nations Children’s Fund (UNICEF) & World Health Organization (WHO). Progress on household drinking water, sanitation and hygiene 2000-2017. Special focus on inequalities. https://www.unicef.org/media/55276/file/Progress on drinking water, sanitation and hygiene 2019.pdf (2019).Prüss-Ustün, A. et al. Burden of disease from inadequate water, sanitation and hygiene for selected adverse health outcomes: An updated analysis with a focus on low- and middle-income countries. Int. J. Hyg. Environ. Health 222, 765 (2019).Caprioli, A., Morabito, S., Bruégre, H. & Oswald, E. Enterohaemorrhagic Escherichia coli: emerging issues on virulence and modes of transmission. Vet. Res. 36, 289–311 (2005).CAS 
Article 

Google Scholar 
Vital, M., Fuchslin, H. P., Hammes, F. & Egli, T. Growth of Vibrio cholerae O1 Ogawa Eltor in freshwater. Microbiology 153, 1993–2001 (2007).CAS 
Article 

Google Scholar 
Agudelo Higuita, N. I. & Huycke, M. M. Enterococcal Disease, Epidemiology, and Implications for Treatment. in Enterococci: From Commensals to Leading Causes of Drug Resistant Infection 47–72 (Massachusetts Eye and Ear Infirmary, 2014).Paton, J. C. & Paton, A. W. Pathogenesis and diagnosis of Shiga toxin-producing Escherichia coli infections. Clin. Microbiol. Rev. 11, 450–479 (1998).CAS 
Article 

Google Scholar 
Bellamy, W. D., Silverman, G. P., Hendricks, D. W. & Logsdon, G. S. Removing Giardia cysts with slow sand filtration. J. Am. Water Works Assoc. 77, 52–60 (1985).Fogel, D., Isaac-Renton, J., Guasparini, R., Moorehead, W. & Removing, O. J. giardia and cryptosporidium by slow sand filtration. JAWWA, Res. Technol. 3, 77–84 (1993).Article 

Google Scholar 
Hijnen, W. A. M., Schijven, J. F., Bonné, P., Visser, A. & Medema, G. J. Elimination of viruses, bacteria and protozoan oocysts by slow sand filtration. Water Sci. Technol. 50, 147–154 (2004).CAS 
Article 

Google Scholar 
Campos, L. C., Su, M. F. J., Graham, N. J. D. & Smith, S. R. Biomass development in slow sand filters. Water Res. 36, 4543–4551 (2002).CAS 
Article 

Google Scholar 
Basu, O. D., Dhawan, S. & Black, K. Applications of biofiltration in drinking water treatment – a review. J. Chem. Technol. Biotechnol. 91, 585–595 (2016).CAS 
Article 

Google Scholar 
Terry, L. G. & Summers, R. S. Biodegradable organic matter and rapid-rate biofilter performance: A review. Water Res. 128, 234–245 (2018).CAS 
Article 

Google Scholar 
Loh, Z. Z. et al. Shifting from conventional to organic filter media in wastewater biofiltration treatment: a review. Appl. Sci. 2021, Vol. 11, Page 8650 11, 8650 (2021).CAS 

Google Scholar 
Bennett, A. Drinking water: Pathogen removal from water – technologies and techniques. Filtr. Sep. 45, 14–16 (2008).CAS 
Article 

Google Scholar 
Di Cristo, C., Esposito, G. & Leopardi, A. Modelling trihalomethanes formation in water supply systems. Environ. Technol. 34, 61–70 (2013).Article 
CAS 

Google Scholar 
Pooi, C. K. & Ng, H. Y. Review of low-cost point-of-use water treatment systems for developing communities. npj Clean Water 2018 11 1, 11 (2018).Article 

Google Scholar 
Flemming, H.-C. et al. Biofilms: an emergent form of bacterial life. Nat. Rev. Microbiol. 14, 563–575 (2016).CAS 
Article 

Google Scholar 
Fu, J. et al. Pilot investigation of two-stage biofiltration for removal of natural organic matter in drinking water treatment. Chemosphere 166, 311–322 (2017).CAS 
Article 

Google Scholar 
Chen, F. et al. Kinetics of natural organic matter (NOM) removal during drinking water biofiltration using different NOM characterization approaches. Water Res. 104, 361–370 (2016).CAS 
Article 

Google Scholar 
McKie, M. J., Ziv-El, M. C., Taylor-Edmonds, L., Andrews, R. C. & Kirisits, M. J. Biofilter scaling procedures for organics removal: A potential alternative to piloting. Water Res. 151, 87–97 (2019).CAS 
Article 

Google Scholar 
de Vries, J. Soil filtration of wastewater effluent and the mechanism of pore clogging. J. Water Pollut. Control Fed. 44, 565–573 (1972).
Google Scholar 
Métivier, R., Bourven, I., Labanowski, J. & Guibaud, G. Interaction of erythromycin ethylsuccinate and acetaminophen with protein fraction of extracellular polymeric substances (EPS) from various bacterial aggregates. Environ. Sci. Pollut. Res. 20, 7275–7285 (2013).Article 
CAS 

Google Scholar 
Writer, J. H., Barber, L. B., Ryan, J. N. & Bradley, P. M. Biodegradation and attenuation of steroidal hormones and alkylphenols by stream biofilms and sediments. Environ. Sci. Technol. 45, 4370–4376 (2011).CAS 
Article 

Google Scholar 
Flemming, H.-C. Biofilms. in Encyclopedia of Life Sciences (John Wiley & Sons, Ltd, 2008). https://doi.org/10.1002/9780470015902.a0000342.pub2.Kragh, K. N. et al. Role of multicellular aggregates in biofilm formation. MBio 7, e00237 (2016).CAS 
Article 

Google Scholar 
Grumbein, S., Opitz, M. & Lieleg, O. Selected metal ions protect Bacillus subtilis biofilms from erosion †. Metallomics 6, 1441 (2014).CAS 
Article 

Google Scholar 
Fu, J. et al. Removal of pharmaceuticals and personal care products by two-stage biofiltration for drinking water treatment. Sci. Total Environ. 664, 240–248 (2019).CAS 
Article 

Google Scholar 
Nemani, V. A., McKie, M. J., Taylor-Edmonds, L. & Andrews, R. C. Impact of biofilter operation on microbial community structure and performance. J. Water Process Eng. 24, 35–41 (2018).Article 

Google Scholar 
Beutel, M. W. & Larson, L. Pathogen removal from urban pond outflow using rock biofilters. Ecol. Eng. 78, 72–78 (2014).Article 

Google Scholar 
Wendt, C. et al. Microbial removals by a novel biofilter water treatment system. Am. J. Trop. Med. Hyg. 92, 765–772 (2015).Article 

Google Scholar 
Granger, H. C., Stoddart, A. K. & Gagnon, G. A. Direct biofiltration for manganese removal from surface water. J. Environ. Eng. 140, 04014006 (2014).Article 
CAS 

Google Scholar 
Srivastava, N. K. & Majumder, C. B. Novel biofiltration methods for the treatment of heavy metals from industrial wastewater. J. Hazard. Mater. 151, 1–8 (2008).CAS 
Article 

Google Scholar 
Fu, J. et al. Removal of disinfection byproduct (DBP) precursors in water by two-stage biofiltration treatment. Water Res. 123, 224–235 (2017).CAS 
Article 

Google Scholar 
McKie, M. J., Andrews, S. A. & Andrews, R. C. Conventional drinking water treatment and direct biofiltration for the removal of pharmaceuticals and artificial sweeteners: A pilot-scale approach. Sci. Total Environ. 544, 10–17 (2016).CAS 
Article 

Google Scholar 
Crognale, S. et al. Biological As(III) oxidation in biofilters by using native groundwater microorganisms. Sci. Total Environ. 651, 93–102 (2019).CAS 
Article 

Google Scholar 
Klayman, B. J., Volden, P. A., Stewart, P. S. & Camper, A. K. Escherichia coli O157:H7 requires colonizing partner to adhere and persist in a capillary flow cell. Environ. Sci. Technol. 43, 2105–2111 (2009).CAS 
Article 

Google Scholar 
Bauman, W. J., Nocker, A., Jones, W. L. & Camper, A. K. Retention of a model pathogen in a porous media biofilm. Biofouling 25, 229–240 (2009).CAS 
Article 

Google Scholar 
Nocker, A., Burr, M. & Camper, A. Pathogens in water and biofilms. In Microbiology of waterborne diseases: microbiological aspects and risks: Second Edition 3–32 (Academic Press, 2013). https://doi.org/10.1016/B978-0-12-415846-7.00001-9.Li, J., McLellan, S. & Ogawa, S. Accumulation and fate of green fluorescent labeled Escherichia coli in laboratory-scale drinking water biofilters. Water Res. 40, 3023–3028 (2006).CAS 
Article 

Google Scholar 
Rendueles, O. & Ghigo, J.-M. Mechanisms of competition in biofilm communities. Microbiol. Spectr. 3, 1–14 (2015).Hibbing, M. E., Fuqua, C., Parsek, M. R. & Peterson, S. B. Bacterial competition: Surviving and thriving in the microbial jungle. Nat. Rev. Microbiol. 8, 15–25 (2010).CAS 
Article 

Google Scholar 
Aoki, S. K. et al. A widespread family of polymorphic contact-dependent toxin delivery systems in bacteria. Nature 468, 439–442 (2010).CAS 
Article 

Google Scholar 
MacIntyre, D. L., Miyata, S. T., Kitaoka, M. & Pukatzki, S. The Vibrio cholerae type VI secretion system displays antimicrobial properties. Proc. Natl Acad. Sci. U.S.A. 107, 19520–19524 (2010).CAS 
Article 

Google Scholar 
Ławniczak, Ł., Marecik, R. & Chrzanowski, Ł. Contributions of biosurfactants to natural or induced bioremediation. Appl. Microbiol. Biotechnol. 97, 2327 (2013).Article 
CAS 

Google Scholar 
Cornforth, D. M. & Foster, K. R. Competition sensing: the social side of bacterial stress responses. Nat. Rev. Microbiol. 2013 114 11, 285–293 (2013).CAS 

Google Scholar 
Legnani, P., Leoni, E., Rapuano, S., Turin, D. & Valenti, C. Survival and growth of Pseudomonas aeruginosa in natural mineral water: a 5-year study. Int. J. Food Microbiol. 53, 153–158 (1999).CAS 
Article 

Google Scholar 
Moll, D. M., Summers, R. S., Fonseca, A. C. & Matheis, W. Impact of temperature on drinking water biofilter performance and microbial community structure. Environ. Sci. Technol. 33, 2377–2382 (1999).CAS 
Article 

Google Scholar 
Hozalski, R. M., Bouwer, E. J. & Goel, S. Removal of natural organic matter (NOM) from drinking water supplies by ozone-biofiltration. Water Sci. Technol. 40, 157–163 (1999).CAS 
Article 

Google Scholar 
Schmidt, K. D., Tümmler, B. & Römling, U. Comparative genome mapping of Pseudomonas aeruginosa PAO with P. aeruginosa C, which belongs to a major clone in cystic fibrosis patients and aquatic habitats. J. Bacteriol. 178, 85 (1996).CAS 
Article 

Google Scholar 
Nigaud, Y. et al. Biofilm-induced modifications in the proteome of Pseudomonas aeruginosa planktonic cells. Biochim. Biophys. Acta – Proteins Proteom. 1804, 957–966 (2010).CAS 
Article 

Google Scholar 
Von Ohle, C. et al. Real-time microsensor measurement of local metabolic activities in ex vivo dental biofilms exposed to sucrose and treated with chlorhexidine. Appl. Environ. Microbiol. 76, 2326 (2010).Article 
CAS 

Google Scholar 
Nescerecka, A., Juhna, T. & Hammes, F. Identifying the underlying causes of biological instability in a full-scale drinking water supply system. Water Res. 135, 11–21 (2018).CAS 
Article 

Google Scholar 
Prest, E. I., Hammes, F., Kötzsch, S., Van Loosdrecht, M. C. M. & Vrouwenvelder, J. S. A systematic approach for the assessment of bacterial growth-controlling factors linked to biological stability of drinking water in distribution systems. Water Sci. Technol. Water Supply 16, 865–880 (2016).CAS 
Article 

Google Scholar 
Liang, K., Sobsey, M. & Stauber, C. E. Improving Household Drinking Water Quality: Use of Biosand Filter in Cambodia. https://scholarworks.gsu.edu/iph_facpub (2010).Fabiszewski De Aceituno, A. M., Stauber, C. E., Walters, A. R., Meza Sanchez, R. E. & Sobsey, M. D. A randomized controlled trial of the plastic-housing biosand filter and its impact on diarrheal disease in Copan, Honduras. Am. J. Trop. Med. Hyg. 86, 913–921 (2012).Article 

Google Scholar 
Miettinen, I. T., Vartiainen, T. & Martikainen, P. J. Phosphorus and bacterial growth in drinking water. Appl. Environ. Microbiol. 63, 3242–3245 (1997).CAS 
Article 

Google Scholar 
Keinänen, M. M. et al. The microbial community structure of drinking water biofilms can be affected by phosphorus availability. Appl. Environ. Microbiol. 68, 434–439 (2002).Article 
CAS 

Google Scholar 
United Nations (UN). Transforming Our World: The 2030 Agenda for Sustainable Development. in A New Era in Global Health 529–567, https://doi.org/10.1891/9780826190123.ap02 (2018).Serra, M. O. D. E. & Schnitzer, M. Extraction of humic acid by alkali and chelating resin. Can. J. Soil Sci. 52, 365–374 (1972).Article 

Google Scholar 
Smith, E. J., Davison, W. & Hamilton-Taylor, J. Methods for preparing synthetic freshwaters. Water Res. 36, 1286–1296 (2002).CAS 
Article 

Google Scholar 
Sobsey, M. D. Managing Water in the Home: Accelerated Health Gains from Improved Water Supply Water, Sanitation and Health Department of Protection of the Human Environment World Health Organization Geneva. https://apps.who.int/iris/bitstream/handle/10665/67319/WHO_SDE_WSH_02.07.pdf?sequence=1&isAllowed=y (2002).Carratalà, A. et al. Solar disinfection of viruses in polyethylene terephthalate bottles. Appl. Environ. Microbiol. 82, 279–288 (2016).Attisani, M. Can solar technology generate clean water for developing nations? Renew. Energy Focus 17, 138–139 (2016).Chaidez, C. et al. Point-of-use Unit Based on Gravity Ultrafiltration Removes Waterborne Gastrointestinal Pathogens from Untreated Water Sources in Rural Communities. Wilderness Environ. Med. 27, 379–385 (2016).Clayton, G. E., Thorn, R. M. S. & Reynolds, D. M. Development of a novel off-grid drinking water production system integrating electrochemically activated solutions and ultrafiltration membranes. J. Water Process Eng. 30, 100480 (2017).Baig, S. A., Mahmood, Q., Nawab, B., Shafqat, M. N. & Pervez, A. Improvement of drinking water quality by using plant biomass through household biosand filter – A decentralized approach. Ecol. Eng. 37, 1842–1848 (2011). More

Sociodemographic of respondentsA total of 140 households completed surveys with a response rate of 45.0%. The respondents were comprised of 48.6% males (n = 68) and 51.4% females (n = 72) in the general population aged 18 to 64 years, which were differentiated into five age groups: ≤19 (1.4%); 20–29 (22.1%); 30–50 (67.1%); 51–59 (5.0%); ≥60 (4.3%). There was a variation in terms of education levels and employment status; the majority of respondents were Bachelor-degree holders (at least 45%) and working as government servants (60.0%), as tabulated in Table 1. The accounted median monthly household income of Putrajaya is RM 7512 (~USD 1803, mean monthly household income of RM 10401, ~USD 2496), exceeding the national level (RM 4585, ~USD 1100)26. The survey covered household groups: bottom 40% (B40), middle 40% (M40), and top 20% (T20), classified into income groups ≤RM 2999, RM 3000–4999, RM 5000–6999, RM 7000–8999, RM 9000–10999, RM 11000–12999, and ≥RM 13000, where RM 1 approximately equivalent to USD 0.24 in average. On an average, respondents had lived in Putrajaya for seven years.Table 1 Descriptive statistics about risk perception of drinking water supply security with potential EDC contamination.Full size tableHuman morphology and drinking water consumption patternsThe present study involved 140 households with 257 total respondents (n = 257), consisting of infants (n = 4, aged less than 1 year; birth–5; 6–11 months), children (n = 77, aged 1 to 9 years; 1–3; 4–6; 7–9 years), adolescents (n = 37, aged 10 to 19 years; 10–14; 15–19 years), adults (n = 133, aged 20 to 59 years; 20–29; 30–50; 51–59 years) and elderly (n = 6, aged more than 60 years) (Table 2). Age groups were categorized based on previous studies27,28,29,30.Table 2 Age groups and respective mean body weight, body height, body mass index, daily water intake, and daily water intake per body weight.Full size tableThere were no significant differences between males (n = 125) and females (n = 132) in terms of body weight (t(235) = 1.671, p = 0.096), body height (t(225) = 0.804, p = 0.422), body mass index (t(246) = 1.116, p = 0.266), and daily water intake (t(255) = 0.483, p = 0.629). Surprisingly, males consumed more water than females in the United States and Australia19,31. Body weight showed a significant positive correlation to height based on Pearson product-moment correlation test (r = 0.861, p  More

Sustainable Development Goal 6: Synthesis Report 2018 on Water and Sanitation (United Nations, 2018).The Millennium Development Goals Report 2015 (United Nations, 2015).Progress on Household Drinking Water, Sanitation and Hygiene 2000–2017: Special Focus on Inequalities (UNICEF and WHO, 2019).Global Health Observatory Data Repository (WHO, accessed 9 June 2022); https://www.who.intMontgomery, M. A. & Elimelech, M. Water and sanitation in developing countries: including health in the equation. Environ. Sci. Technol. 41, 17–24 (2007).Article 

Google Scholar 
Combating Waterborne Disease at the Houshold Level (WHO, 2007).Results of Round II of the WHO International Scheme to Evaluate Household Water Treatment Technologies (WHO, 2019).Chu, C., Ryberg, E. C., Loeb, S. K., Suh, M.-J. & Kim, J.-H. Water disinfection in rural areas demands unconventional solar technologies. Acc. Chem. Res. 52, 1187–1195 (2019).CAS 
Article 

Google Scholar 
McGuigan, K. G. et al. Solar water disinfection (SODIS): a review from bench-top to roof-top. J. Hazard. Mater. 235, 29–46 (2012).Article 
CAS 

Google Scholar 
Fisher, M. B., Keenan, C. R., Nelson, K. L. & Voelker, B. M. Speeding up solar disinfection (SODIS): effects of hydrogen peroxide, temperature, pH, and copper plus ascorbate on the photoinactivation of E. coli. J. Water Health 6, 35–51 (2008).CAS 
Article 

Google Scholar 
Shannon, M. A. et al. In Nanoscience and Technology: A Collection of Reviews from Nature Journals (ed. Rodgers, P.) 337–346 (World Scientific, 2010).Loeb, S., Li, C. & Kim, J.-H. Solar photothermal disinfection using broadband-light absorbing gold nanoparticles and carbon black. Environ. Sci. Technol. 52, 205–213 (2018).CAS 
Article 

Google Scholar 
Loeb, S. K. et al. Nanoparticle enhanced interfacial solar photothermal water disinfection demonstrated in 3-D printed flow-through reactors. Environ. Sci. Technol. 53, 7621–7631 (2019).CAS 
Article 

Google Scholar 
Wigginton, K. R. & Kohn, T. Virus disinfection mechanisms: the role of virus composition, structure, and function. Curr. Opin. Virol. 2, 84–89 (2012).CAS 
Article 

Google Scholar 
Fraise, A. P., Lambert, P. A. & Maillard, J.-Y. Russell, Hugo & Ayliffe’s Principles and Practice of Disinfection, Preservation and Sterilization (Wiley & Sons, 2008).McDonnell, G. E. Antisepsis, Disinfection, and Sterilization: Types, Action, and Resistance (Wiley & Sons, 2020).Burch, J. D. & Thomas, K. E. Water disinfection for developing countries and potential for solar thermal pasteurization. Sol. Energy 64, 87–97 (1998).Article 

Google Scholar 
Sampathkumar, K., Arjunan, T., Pitchandi, P. & Senthilkumar, P. Active solar distillation—a detailed review. Renew. Sustain. Energy Rev. 14, 1503–1526 (2010).CAS 
Article 

Google Scholar 
Wang, Z. et al. Pathways and challenges for efficient solar-thermal desalination. Sci. Adv. 5.7, aax0763 (2019).Article 
CAS 

Google Scholar 
Pang, Y. et al. Solar-thermal water evaporation: a review. ACS Energy Lett. 5, 437–456 (2020).CAS 
Article 

Google Scholar 
Results of Round I of the WHO International Scheme to Evaluate Household Water Treatment Technologies (WHO, 2016).Velmurugan, V., Gopalakrishnan, M., Raghu, R. & Srithar, K. Single basin solar still with fin for enhancing productivity. Energy Convers. Manage. 49, 2602–2608 (2008).Article 

Google Scholar 
Badran, O. O. & Abu-Khader, M. M. Evaluating thermal performance of a single slope solar still. Heat Mass Transf. 43, 985–995 (2007).CAS 
Article 

Google Scholar 
Luzi, S., Tobler, M., Suter, F. & Meierhofer, R. SODIS Manual: Guidance on Solar Water Disinfection (Eawag, 2016).Loeb, S. K. et al. The technology horizon for photocatalytic water treatment: sunrise or sunset? Environ. Sci. Technol. 53, 2937–2947 (2019).CAS 
Article 

Google Scholar 
Hirayama, H., Tsukada, Y., Maeda, T. & Kamata, N. Marked enhancement in the efficiency of deep-ultraviolet AlGaN light-emitting diodes by using a multiquantum-barrier electron blocking layer. Appl. Phys. Express 3, 031002 (2010).Article 
CAS 

Google Scholar 
Shur, M. S. & Gaska, R. Deep-ultraviolet light-emitting diodes. IEEE Trans. Electron Devices 57, 12–25 (2009).Article 
CAS 

Google Scholar 
Khan, A., Balakrishnan, K. & Katona, T. Ultraviolet light-emitting diodes based on group three nitrides. Nat. Photonics 2, 77–84 (2008).CAS 
Article 

Google Scholar 
Zhang, X. et al. Global sensitivity analysis of environmental, water quality, photoreactivity, and engineering design parameters in sunlight inactivation of viruses. Environ. Sci. Technol. 54, 8401–8410 (2020).CAS 
Article 

Google Scholar 
Haag, W. R. & Yao, C. D. Rate constants for reaction of hydroxyl radicals with several drinking water contaminants. Environ. Sci. Technol. 26, 1005–1013 (1992).CAS 
Article 

Google Scholar 
Brown, J. & Clasen, T. High adherence is necessary to realize health gains from water quality interventions. PLoS ONE 7, e36735 (2012).CAS 
Article 

Google Scholar 
Trimmer, J. T. et al. Re-envisioning sanitation as a human-derived resource system. Environ. Sci. Technol. 54, 10446–10459 (2020).CAS 
Article 

Google Scholar 
UN-Water Global Analysis and Assessment of Sanitation and Drinking-Water (GLAAS) 2019 Report: National Systems to Support Drinking-Water, Sanitation and Hygiene: Global Status Report 2019 (WHO, 2019).The United Nations World Water Development Report 2019: Leaving No One Behind (United Nations Educational, Scientific and Cultural Organization, 2019).Enger, K. S., Nelson, K. L., Rose, J. B. & Eisenberg, J. N. The joint effects of efficacy and compliance: a study of household water treatment effectiveness against childhood diarrhea. Water Res. 47, 1181–1190 (2013).CAS 
Article 

Google Scholar 
Hijnen, W., Beerendonk, E. & Medema, G. J. Inactivation credit of UV radiation for viruses, bacteria and protozoan (oo)cysts in water: a review. Water Res. 40, 3–22 (2006).CAS 
Article 

Google Scholar 
Evaluating Household Water Treatment Options: Health-Based Targets and Microbiological Performance Specifications (WHO, 2011).Kohn, T. & Nelson, K. L. Sunlight-mediated inactivation of MS2 coliphage via exogenous singlet oxygen produced by sensitizers in natural waters. Environ. Sci. Technol. 41, 192–197 (2007).CAS 
Article 

Google Scholar 
Guidelines for Drinking-Water Quality 4th edn (WHO, 2011).National Primary Drinking Water Regulations: Long Term 2 Enhanced Surface Water Treatment Rule; Final Rule (US EPA, 2006).Loeb, S., Hofmann, R. & Kim, J.-H. Beyond the pipeline: assessing the efficiency limits of advanced technologies for solar water disinfection. Environ. Sci. Technol. Lett. 3, 73–80 (2016).CAS 
Article 

Google Scholar 
Liu, B., Zhao, X., Terashima, C., Fujishima, A. & Nakata, K. Thermodynamic and kinetic analysis of heterogeneous photocatalysis for semiconductor systems. Phys. Chem. Chem. Phys. 16, 8751–8760 (2014).CAS 
Article 

Google Scholar 
Malato, S., Fernández-Ibáñez, P., Maldonado, M. I., Blanco, J. & Gernjak, W. Decontamination and disinfection of water by solar photocatalysis: recent overview and trends. Catal. Today 147, 1–59 (2009).CAS 
Article 

Google Scholar 
Cho, M., Chung, H., Choi, W. & Yoon, J. Linear correlation between inactivation of E. coli and OH radical concentration in TiO2 photocatalytic disinfection. Water Res. 38, 1069–1077 (2004).CAS 
Article 

Google Scholar 
Cho, M., Cates, E. L. & Kim, J.-H. Inactivation and surface interactions of MS-2 bacteriophage in a TiO2 photoelectrocatalytic reactor. Water Res. 45, 2104–2110 (2011).CAS 
Article 

Google Scholar 
Park, G. W. et al. Fluorinated TiO2 as an ambient light-activated virucidal surface coating material for the control of human norovirus. J. Photochem. Photobiol. B 140, 315–320 (2014).CAS 
Article 

Google Scholar 
Nelson, K. L. et al. Sunlight-mediated inactivation of health-relevant microorganisms in water: a review of mechanisms and modeling approaches. Environ. Sci. Process. Impacts 20, 1089–1122 (2018).CAS 
Article 

Google Scholar 
DeRosa, M. C. & Crutchley, R. J. Photosensitized singlet oxygen and its applications. Coord. Chem. Rev. 233–234, 351–371 (2002).Article 

Google Scholar 
Dobrowsky, P. et al. Efficiency of microfiltration systems for the removal of bacterial and viral contaminants from surface and rainwater. Water Air Soil Pollut. 226, 33 (2015).Article 
CAS 

Google Scholar 
Dobrowsky, P., Carstens, M., De Villiers, J., Cloete, T. & Khan, W. Efficiency of a closed-coupled solar pasteurization system in treating roof harvested rainwater. Sci. Total Environ. 536, 206–214 (2015).CAS 
Article 

Google Scholar 
Abraham, J., Plourde, B. & Minkowycz, W. Continuous flow solar thermal pasteurization of drinking water: methods, devices, microbiology, and analysis. Renew. Energy 81, 795–803 (2015).Article 

Google Scholar 
Spinks, A. T., Dunstan, R., Harrison, T., Coombes, P. & Kuczera, G. Thermal inactivation of water-borne pathogenic and indicator bacteria at sub-boiling temperatures. Water Res. 40, 1326–1332 (2006).CAS 
Article 

Google Scholar 
Sanciolo, P. et al. Pasteurisation for Production of Class A Recycled Water: A Report of a Study Funded by the Australian Water Recycling Centre of Excellence Report No. 1922202665 (Australian Water Recycling Centre of Excellence, 2015).Parry, J. & Mortimer, P. The heat sensitivity of hepatitis A virus determined by a simple tissue culture method. J. Med. Virol. 14, 277–283 (1984).CAS 
Article 

Google Scholar 
Hewitt, J., Rivera‐Aban, M. & Greening, G. Evaluation of murine norovirus as a surrogate for human norovirus and hepatitis A virus in heat inactivation studies. J. Appl. Microbiol. 107, 65–71 (2009).CAS 
Article 

Google Scholar 
Maheshwari, G., Jannat, R., McCormick, L. & Hsu, D. Thermal inactivation of adenovirus type 5. J. Virol. Methods 118, 141–146 (2004).CAS 
Article 

Google Scholar 
Strazynski, M., Krämer, J. & Becker, B. Thermal inactivation of poliovirus type 1 in water, milk and yoghurt. Int. J. Food Microbiol. 74, 73–78 (2002).Article 

Google Scholar 
Fujino, T. et al. The effect of heating against Cryptosporidium oocysts. J. Vet. Med. Sci. 64, 199–200 (2002).Article 

Google Scholar 
Fayer, R. Effect of high temperature on infectivity of Cryptosporidium parvum oocysts in water. Appl. Environ. Microbiol. 60, 2732–2735 (1994).CAS 
Article 

Google Scholar 
Harp, J. A., Fayer, R., Pesch, B. A. & Jackson, G. J. Effect of pasteurization on infectivity of Cryptosporidium parvum oocysts in water and milk. Appl. Environ. Microbiol. 62, 2866–2868 (1996).CAS 
Article 

Google Scholar 
Jarroll, E. L., Hoff, J. C. & Meyer, E. A. in Giardia and Giardiasis (eds Erlandsen, S. L. & Meyer, E. A.) 311–328 (Springer, 1984).Ongerth, J. E., Johnson, R. L., MacDonald, S. C., Frost, F. & Stibbs, H. H. Back-country water treatment to prevent giardiasis. Am. J. Public Health 79, 1633–1637 (1989).CAS 
Article 

Google Scholar 
Schaefer, F. W., Rice, E. W. & Hoff, J. C. Factors promoting in vitro excystation of Giardia muris cysts. Trans. R. Soc. Trop. Med. Hyg. 78, 795–800 (1984).Article 

Google Scholar 
Global Solar Atlas 2.0 (World Bank Group, 2020); https://globalsolaratlas.info/R Core Team. R: A language and environment for statistical computing (R Foundation for Statistical Computing, 2021).Campolongo, F., Cariboni, J. & Saltelli, A. An effective screening design for sensitivity analysis of large models. Environ. Model. Softw. 22, 1509–1518 (2007).Article 

Google Scholar 
Saltelli, A. Sensitivity analysis for importance assessment. Risk Anal. 22, 579–590 (2002).Article 

Google Scholar 
Sobol, I. M. Sensitivity analysis for non-linear mathematical models. Math. Modell. Comput. Exp. 1, 407–414 (1993).
Google Scholar 
Saltelli, A., Tarantola, S., Campolongo, F. & Ratto, M. Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models Vol. 1 (Wiley Online Library, 2004).Zhang, T. et al. A global perspective on renewable energy resources: NASA’s prediction of worldwide energy resources (power) project. In Proc. ISES World Congress 2007 Vol. 1–Vol. 5 (eds Goswami, D. Y. & Zhao, Y.) 2636–2640 (Springer, 2009).Stackhouse, P. Jr. et al. Surface Meteorology and Solar Energy (SSE) Release 6.0 Methodology version 3.2.0 (NASA, 2016).Stackhouse, P. Jr. et al. Supporting energy-related societal applications using NASA’s satellite and modeling data. In Proc. 2006 IEEE International Symposium on Geoscience and Remote Sensing (ed. Tsang, L.) 425–428 (IEEE, 2006).World Development Indicators (World Bank, accessed 9 June 2022); https://datacatalog.worldbank.org/dataset/world-development-indicatorsHaitz, R. H., Craford, M. G. & Weissman, R. H. In Handbook of optics Vol. 2 (ed. Bass, M.) 121–129 (Optical Society of America, 1995).García-Gil, Á., Abeledo-Lameiro, M. J., Gómez-Couso, H. & Marugán, J. Kinetic modeling of the synergistic thermal and spectral actions on the inactivation of Cryptosporidium parvum in water by sunlight. Water Res. 185, 116226 (2020).Article 
CAS 

Google Scholar  More

Adjusting GEFS forecasts to local climatologyWhat amount of correction is required for GEFS forecasts to align with CHIRPS local climatology? The amount of correction varies widely across the globe and throughout the year. Figure 1a shows annual mean bias for GEFS reforecast 15-day totals. In this figure, wetter-than-CHIRPS climatology and systematic over-prediction of 15-day totals by GEFS is indicated by positive mean bias values, while the opposite is indicated by negative values. GEFS forecast mean bias was calculated for each month and then averaged across rainy season months, to focus aggregate results on the rainfall seasons, when precipitation forecasts are relevant. Monthly dry masks excluded locations with a monthly average of less than 10 mm, according to CHIRPS climatology. In general, one consistent result from Fig. 1a is a tendency to increase precipitation in many mountainous tropical and subtropical regions. By design, orographic precipitation enhancements in such regions are represented fairly well in CHIRPS, and these are carried through to CHIRPS-GEFS precipitation forecasts. The CHIRPS-GEFS bias-correction process reduces systematic errors (Fig. 1b), with the overall mean absolute bias error going from 24.1 mm for GEFS to 19.7 mm for CHIRPS-GEFS, an ~18% reduction.Fig. 1Annual mean bias and global error characteristics for GEFS reforecast data compared to CHIRPS, based on 15-day precipitation totals from Day 1, 6, 11, and 16 of each month during 2000–2019. Annual mean bias (a) shows the annual average of differences in GEFS reforecast and CHIRPS monthly means. Annual average error (b) shows the distribution of GEFS reforecast and CHIRPS-GEFS errors (product – CHIRPS). Both panels are based on in-season pixels, which are defined by monthly average CHIRPS  > 10 mm.Full size imageFigure 1a through Fig. 5 are based on GEFS reforecast, CHIRPS, and CHIRPS-GEFS data for the 5-day or 15-day periods beginning on the 1st, 6th, 11th, and 16th day of the month. All these exclude dry season months. Figure 1b shows the corresponding global distribution of annual average error for the GEFS reforecast and CHIRPS-GEFS, and is discussed later.GEFS has a large annual average positive bias of higher-than 40 mm in some areas of the globe, including in central Mexico, Central America, northern South America, the Andes and Himalayan Mountain ranges, and in southern China, Papua New Guinea, and localized areas of central Africa, the Ethiopian Highlands, and the western montane United States (Fig. 1a). GEFS has positive bias, by more than 5 mm for the annual average 15-day period, across the northern United States including in the Midwest, from Mexico’s northern mountains through most of Central America, in northern South America, the Andes range, eastern Brazil, in parts of central Europe, central and northern Asia, in the area from southern China to Myanmar and Thailand, and in northeastern and western India. GEFS has positive bias in portions of East Africa (Rwanda, Burundi, Tanzania, western Ethiopia), West Africa (Cameroon, Gabon), and Southern Africa (Zambia, central Angola, northern Zimbabwe, eastern South Africa). GEFS has negative bias, by more than 5 mm on average, in parts of central and northern Africa, Senegal, northern Australia, central South America, western India, the Yucatan peninsula, and the United States Gulf Coast.GEFS’ systematic bias changes throughout the year, as shown by the monthly mean bias in January, April, July, and October (Fig. 2). This is unsurprising, given that drivers of weather change too, but higher bias in particular months can be problematic for forecast users. In Ethiopia, for example, GEFS overestimates by large amounts during the Kirempt season (e.g., in July) and in October in the southwest. In central Brazil, the bias changes markedly by season, from a high negative bias in October to an expansive wet bias in April. In the Midwestern and northern United States, GEFS also shows a more expansive wet bias in April than in January, July, or October. In some areas, like in southern China and the Andes mountains, GEFS means are higher than CHIRPS means throughout the year.Fig. 2Monthly mean bias for GEFS reforecast data compared to CHIRPS, based on 15-day precipitation totals from Day 1, 6, 11, and 16 of each month during 2000–2019. Mean bias for January (a), April (b), July (c), and October (d) shows the difference in GEFS reforecast and CHIRPS monthly means. Shown for in-season pixels, which are defined by monthly average CHIRPS  > 10 mm.Full size imageThe CHIRPS-GEFS downscaling procedure corrects for systematic errors in GEFS forecasts that vary spatially and temporally. To assess the efficacy of the CHIRPS-GEFS approach, we began by calculating the per-pixel difference between GEFS and CHIRPS, and CHIRPS-GEFS and CHIRPS for 15-day periods. These were calculated for each month, for in-season pixels, and then averaged across the year. We then looked at the histogram of the resulting differences (Fig. 1b), to identify the distribution of annual average errors in these two products. CHIRPS-GEFS errors are shown as gray bars and GEFS errors are overlaid as hollow red bars. A desirable pattern is more small errors (higher bars close to 0 mm) and fewer large magnitude errors (lower bars at larger precipitation values). As shown in Fig. 1b, the bias-correction procedure has this effect, and results in CHIRPS-GEFS having overall lower errors for global rainy seasons compared to GEFS. GEFS 15-day errors more commonly involve over prediction of observed amounts than under prediction, as shown by the higher proportion of positive versus negative moderate to large positive errors. Part of this is due to the lower limit of under prediction being zero precipitation, while over prediction can range from marginal precipitation amounts to very high amounts. As shown in Fig. 1b, the CHIRPS-GEFS bias correction particularly reduces GEFS forecast errors for moderate-to-high rainfall amounts, and it results in a global 15-day error distribution that has a higher proportion of small errors, e.g., errors within −10 mm to 10 mm of CHIRPS values (51% for CHIRPS-GEFS and 43% for GEFS). Errors in categories ranging from 10 mm to 40 mm occur less often in CHIRPS-GEFS, globally, with probabilities in those categories reduced by around 15 and 25 percent at 10 mm to 20 mm and 20 mm to 30 mm, respectively, and by around 30 percent to 40 percent for errors that are higher than 40 mm.Next, we show performance of the 5-day and 15-day CHIRPS-GEFS precipitation forecasts by correlations and mean absolute errors for the historical record, compared to CHIRPS data for these periods. As described in Data Records, multiple outlets use forecast amounts for these periods. In the Usage Notes section, probability of detection scores for 15-day CHIRPS-GEFS in Africa are presented while describing an operational application of the CHIRPS-GEFS for seasonal monitoring. In that discussion we also examine the performance of 5-day forecasts during the 2020–2021 season in key regions of Kenya, Angola, Zambia, Zimbabwe, and Madagascar.Pearson correlation coefficients for 5-day and 15-day CHIRPS-GEFS, compared to CHIRPS (Fig. 3), indicate the ability of forecasts to predict deviations from average. It should be noted that correlations are nearly entirely driven by the information coming from the GEFS forecasts. The conversion to CHIRPS-GEFS adjusts the GEFS values to make them more “CHIRPS-like,” while also approximating the historical context of the GEFS forecast. Wet extremes forecasted by GEFS translate into wet extremes in CHIRPS-GEFS. Areas with very low correlations (R  0.7) are the United States, Western Europe, and Eastern Europe, southeastern South America, southern Central Asia, eastern China, parts of East and Southern Africa, and Australia. Globally, correlations are higher in January, April, and October than in July, which indicates generally higher forecast accuracy in those months. Exceptions are in eastern China, southern Brazil, eastern Mexico, northeastern Ethiopia, and central and southern Australia, where July correlations are not substantially lower. 15-day forecasts also have high correlations in some areas, including in the Western and Midwestern United States in January, in central and northern Australia in April, and in eastern Brazil in January and October.Fig. 3CHIRPS-GEFS 5-day and 15-day Pearson correlation coefficients, as compared to CHIRPS, for January, April, July, and October. (Validation data: CHIRPS 5-day and 15-day totals from the 1st, 6th, 11th, and 16th of the month, for 2000 to 2019. Shown for in-season pixels, which are defined by monthly average CHIRPS  > 10 mm.Full size imageIn Africa, a region where CHIRPS data is actively used by the Famine Early Warning System Network (FEWS NET) and other organizations for seasonal monitoring and drought early warning, forecast correlations indicate moderate to good 5-day and 15-day forecast performance in areas of East Africa, Southern Africa, and western North Africa during rainy season months. Some of the highest 15-day correlations in Africa are during important rainy season months, for example, in northeastern Ethiopia in July and April, in Kenya in April, in Zimbabwe and southern Mozambique in January, and in the Sudanian zone of West Africa in October. Very low correlations indicate low forecast skill in the Sahel, coastal West Africa, and in Central Africa in the DRC, Republic of the Congo, and Gabon.Mean absolute error of the bias-corrected GEFS forecasts highlight the areas where forecast amounts have historically been less reliable (Fig. 4). These indicate non-systematic errors associated with rains not materializing in the forecast location in the forecast period, which can be from GEFS model deficiencies and the inherent challenges of weather forecasting. Extreme precipitation events and warm season, deep moist convection-driven precipitation are notorious challenges for numerical weather prediction systems48,49, and CHIRPS-GEFS data are not immune to this problem. Remotely sensed data, including CHIRPS, also struggle with estimating extreme high rainfall amounts13,50, though since we are comparing CHIRPS-GEFS to CHIRPS, the main source of the large errors shown here would be the GEFS reforecast.Fig. 4CHIRPS-GEFS 5-day and 15-day mean absolute errors, as compared to CHIRPS, for January, April, July, and October. Validation data: CHIRPS 5-day and 15-day totals from the 1st, 6th, 11th, and 16th of the month, for 2000 to 2019. Shown for in-season pixels, which are defined by monthly average CHIRPS  > 10 mm.Full size imageAs shown in Fig. 4, the magnitude of errors follows climatology, with 5-day errors typically under 10 mm for drier rainy season months. In wetter months and locations errors are typically between 10 mm and 20 mm. With higher rainfall magnitude there is greater potential for larger errors. The 15-day forecast errors exhibit a similar spatial pattern to the 5-day errors, and error magnitudes correspond to the three-times larger accumulation interval as well as expected lower skill at longer lead time. Figure 4 shows especially large 15-day mean absolute errors in January near northern Mozambique and Madagascar, in July and October in parts of Central America, in April in central Kenya and southwestern Tanzania, in July in India’s Western Ghats Mountains and in the Himalayas, and in the Maritime Continent. In southeast China, while the 15-day correlations indicated decent skill at forecasting the sign of precipitation anomalies, large 15-day errors indicate the influence of poorly forecast large storms, which unbiasing cannot correct for. In the Amazon rainforest, many areas with low correlations also have high forecast errors, underscoring poor forecast performance there. More

Availability per capitaThe APC water stress indicator represents the state of physical water scarcity. The total population under a certain level of water scarcity is called the stressed population. We calculated the water-stressed population and compared it to earlier estimates for validation. We found that the total population percentage (calculated using the ensemble mean discharge) facing acute physical water stress calculated using the APC of 500 m3/capita/year will vary as to ({54.9}_{-1.7}^{+1.1} %;({47.6}_{-2.5}^{+2.1} % )), ({66.6}_{-3.3}^{+2.8} %;({59.8}_{-6.1}^{+5.6} % )), and ({55.6}_{-1.8}^{+4.2} % ;({47.0}_{-2.6}^{+5.7} %)) (+/− values show the maximum variation considering discharge using single GCM to the ensemble mean discharge) at the end of the century (i.e., the year 2099) under the SSP1–RCP2.6, SSP3–RCP7.0, and SSP5–RCP8.5 scenarios, respectively, representing different socioeconomic and climate conditions considering the MY19 (JO16) future population dataset (methods for scenarios and datasets details). By contrast, 44.5% (45.1%) of the global population faced acute physical water stress at the beginning of the century (i.e., the year 2000). The above percentages correspond to 3.5 (3.3), 7.9 (7.5), and 3.9 (3.4) billion populations for the SSP1–RCP2.6, SSP3–RCP7.0, and SSP5–RCP8.5 scenarios and 2.68 (2.75) billion for the historical scenario (i.e., beginning of the century). The historical value is consistent with the value of 2.7 billion previously reported by Hoekstra et al.13 and 2.4 billion mentioned by Oki and Kanae1.APC enhanced with GDP per capita—country-scale assessmentNext, we analysed the relationship between APC and GDP per capita. First, to revisit the findings of Oki et al.19, we conducted country-level analyses for the beginning (i.e., the year 2000) and end (i.e., the year 2099) of the century. To compare the absolute change for a longer period with the constant exchange rate, we used GDP-PPP per capita (USD 2005) due to its availability and defined water stress (physical and economic water scarcity) for both past and future scenarios using the same threshold line (see “Methods” section). The consistency in the results in terms of distribution of countries (Fig. 1 and Supplementary Fig. 1) for both historical (GPWv4 and HYDE3.2) and future (MY19 and JO16) population datasets confirm the similarity in aggregated country-level population data. We did not find any countries below the threshold line at the end of the century, whereas we found Somalia, Western Sahara, Yemen, and Niger below the threshold line at the beginning of the century (Fig. 1, Supplementary Table 1 for base scenario experimental settings, results for other combinations of climate and population dataset are provided as Supplementary Fig. 1). The comparison of per capita water availability (APC) for countries below the threshold line for this study and additional analysis considering various climate forcing data with the same socioeconomic data showed substantial differences. These arid region countries have less runoff and considerable sensitivity towards the metrological data, causing the large difference in availability per capita (APC) of freshwater (Supplementary Table 2 for comparison of values considering different climate forcing data). Additionally, the quality of socioeconomic data contains uncertainty due to political instability23,24,25,26, defying the hypothesis for these countries. We confirmed that although a few countries can contradict, the hypothesis of Oki et al.19 remains valid for various scenarios considered.Fig. 1: Country-level scatter plot for APC vs GDP-PPP per capita and density plot considering the number of countries for various socioeconomic and climate scenarios.Each circle corresponds to a country, and the circle’s size corresponds to the country’s population. CHN, ESH, IND, NER, SOM, USA, and YEM represent China, Western Sahara, India, Niger, Somalia, United States of America and Yemen, respectively. Yellow, green, red, and blue colours represent the historical, SSP1–RCP2.6, SSP3–RCP7.0, and SSP5–RCP8.5 scenarios, respectively, and the dashed line represents the threshold value for physical and economic water scarcity. The analysis was performed considering the GPWv4 dataset for the historical, i.e., the year 2000 population and MY19 for the future, i.e., the year 2099 population.Full size imageAPC enhanced with GDP per capita—grid-scale assessmentNext, we proceeded with grid-level analyses. We confirmed the existence of locations in the world facing the challenges of economic and physical water scarcity identified at 0.5° resolution (Fig. 2, results of SSP1–RCP2.6 and SSP5–RCP8.5 are shown in Supplementary Fig. 2 and Supplementary Fig. 3). The total population and spatial distribution facing challenges (i.e., grids below the threshold line defined by Eq. 1) differed in the different scenarios.Fig. 2: Grid-level scatter plots for APC vs GDP-PPP per capita and density plot considering the number of grids.(a) Historical-GPW, (b) Historical-HYDE, (c) Future370-MY19, and (d) Future370-JO16 scenarios. Grid values are represented as circles, and the dashed line represents the threshold line proposed by Oki et al.19. The density plot includes dotted coloured lines (lime and red) for the median and dark shading for the interquartile range (first and third quartiles). The white circle represents the grid size of 20 million population. e Boxplot for the total population facing physical and economic water scarcity (grids below the threshold of Eq. 1) for all considered scenarios. Legend symbols represent the analysis using the discharge considering various GCMs and the ensemble mean of discharge considering all GCMs. *analysis for Historical-GPW and Future-MY scenarios, **analysis for Historical-HYDE and Future-JO scenarios (Supplementary Table 1 for scenarios/ experiment settings, and Supplementary Table 5 for water-scarce population and uncertainty values).Full size imageIt can be observed from the density plots in Fig. 1 and Fig. 2 that there is a rightward shift in the peak and a significant increase in the mean and median values of the GDP-PPP per capita for the future scenarios compared to the historical scenario. The density plot for the APC for the future follows a trend similar to the trend of the past (i.e., a similar frequency distribution of APC at the grid scale), with an increase (decrease) in the median values observed for the future scenarios for MY19 (JO16) at the grid level (Supplementary Table 3 and Supplementary Table 4 for results of all statistical analyses considering future and historical datasets).We calculated the population facing hardship due to both physical and economic water scarcity (i.e., grids below the threshold line defined by Eq. 1). As a result, at the end of the 21st century (i.e., the year 2099), ({0.32}_{+0.00}^{+0.68}) (({234}_{-10}^{+24})) million people were estimated to face hardship under the SSP1–RCP2.6 scenario when using an urban-concentrated, i.e., MY19 (dispersed, i.e., JO16) population dataset. The estimated populations facing hardship under the SSP3–RCP7.0 and SSP5–RCP8.5 scenarios were ({327}_{+35}^{+202}) (({665}_{-67}^{+181})) and ({6.9}_{-1.1}^{+1.2},left({176}_{-3}^{+36}right)) million respectively (+/− values show the maximum variation in the global population facing water scarcity, calculated considering discharge using single GCM and the ensemble mean discharge), compared to 327 (358) million at the beginning of this century (i.e., the year 2000) (Fig. 2e, Supplementary Table 5). Analysis considering MY19 and JO16 population datasets yield three orders of difference in the stressed population at maximum. The total number of water-stressed populations would decrease in the future (except for the SSP3-RCP7.0 with JO16 population distribution i.e., Future370-JO16 experiment) due to an increase in income.Analysis considering various scenarios (Supplementary Table 1 for scenarios) shows that the uncertainty associated with the SSP–RCP scenarios (i.e., maximum, and minimum difference in the population facing scarcity considering any two scenarios among SSP1-RCP2.6, SSP3-RCP7.0, and SSP5-RCP8.5 for the ensemble mean discharge) and global climate models (GCMs) (i.e., maximum and minimum difference in the population facing scarcity considering any two GCMs for a particular SSP-RCP scenario) were in the range of 6.58–489 and 0.03–248 million, respectively (Supplementary Table 5).We found that the population distribution uncertainty (i.e., maximum and minimum difference in the population facing scarcity considering MY19 and JO16 gridded population distribution for a particular SSP-RCP scenario) for the end century (i.e., the year 2099) followed a similar trend and was in the range of 169.1–338 million (Supplementary Table 5). At the same time, the uncertainty at the beginning of the century (i.e., the year 2000) was within ~10 %, considering GPWv4 and HYDE3.2 gridded population datasets, confirming the high accuracy in estimation of historical population and their distribution. The maximum range value is brought by SSP3-RCP7.0, which is attributed to the large dispersion of population distribution in the SSP3. The grid-level analyses revealed that the future prediction includes large uncertainty due to the spatial distribution of within-country population along with the SSP–RCP paths of global sustainability (SSP1–RCP2.6), regional rivalry (SSP3–RCP7.0), and economic optimism (SSP5–RCP8.5) taken by the world (Fig. 3). The number of water-scarce grids (i.e., grids below the threshold line) in the future will increase or decrease compared to the past and depend mainly on the spatial distribution of population and GDP compared to freshwater availability.Fig. 3: Physical and economic water-scarce regions.a Historical (2000) considering the GPWv4 dataset, (b) Historical (2000) considering the HYDE3.2 population dataset, (c) Future (2099) considering the MY19 population dataset, and (d) Future (2099) considering the JO16 population dataset scenarios. The future (2099) case shows the possible combinations of scenarios with different colours; the values inside the circular legend show the number of people (in millions) facing scarcity with ranges representing the minimum and maximum values considering scenarios combination.Full size imageFactor decompositionThe spatial distribution of grids below the threshold line of various historical and future scenarios (Fig. 3) showed that there would be an emergence of new water-scarce grids in the future, i.e., new grids facing water scarcity in future scenarios but were not facing water scarcity in the historical scenarios. These grids will face water scarcity either due to the decrease in freshwater availability (climate change) or GDP-PPP (socioeconomic change) or an increase in the population (socioeconomic change) among the considered variables for the analysis. Fig. 4 presents the boxplot distributions of absolute values for freshwater (mm/year), population density (capita/km2), and GDP-PPP (USD/year) for newly identified water-scarce grids (grids facing scarcity in the future but not facing it in the past), comparing the values for the historical and future scenarios. The freshwater availability (mean and median values) does not change significantly over time for the new water-scarce grids, i.e., the difference between the future scenarios (SSP1–RCP2.6, SSP3–RCP7.0, and SSP5–RCP8.5) and the historical scenario is negligible. Compared to freshwater, there is a significant increase in population density for all considered scenarios and a less significant increase (decrease) of GDP-PPP of the grids (regions) for the MY19 (JO16) population datasets (Supplementary Table 6 for statistical analysis), suggesting that the primary reason for the water scarcity in these areas will be population growth.Fig. 4: Comparison of new water-scarce grids (i.e., grids facing physical and economic water scarcity in the future but not in the past).Box plots comparing the absolute values of (a), (d) freshwater availability (mm/year); (b), (e) population density (capita/km2); and (c), (f) GDP-PPP. The analysis for (a), (b), and (c) was performed considering the Future-MY and Historical-GPW Experiment settings, and that of (d), (e), and (f) was performed considering the Future-JO and Historical-HYDE experiment settings (Supplementary Table 1). The error bars show the 100% confidence interval (i.e., 0th and 100th percentile), the bottom and top of the box are the 25th and 75th percentiles, and the line inside the box is the median (50th percentile).Full size imageThe global water scarcity analysis considering various future scenarios (SSP1–RCP2.6, SSP3–RCP7.0, and SSP5–RCP8.5) identify various possible water stress regions (grids below the threshold line) of the world affecting the different number of populations. The common water-scarce grids recognised in all these scenarios (grids showing water scarcity for the SSP1–RCP2.6, SSP3–RCP7.0, and SSP5-RCP8.5 scenarios simultaneously) have the highest possibility (certainty) of facing water scarcity in the future. We compared the sensitivity analyses (methods for the approach adopted and Supplementary Table 7 for sensitive analysis experiment settings) results with the base scenario (Supplementary Table 1) values to know the major factor causing water stress among the considered variables for the grids with the highest possibility of water scarcity. The water-scarce population, which can be simultaneously identified in all future scenarios, will be in the range of 0.46–1.82 (156–393) million (range shows the minimum and maximum population affected considering all three future scenarios), considering the historically available freshwater for future scenarios, i.e., Historical-MY (Historical-JO) experiments. Similarly, the population affected considering the historical population for the future scenarios, i.e., Future-GPW (Future-HYDE) experiments, was determined to be 13 (10–16) million; considering the historical GDP-PPP for the future scenarios, i.e., Future-MY-TG, (Future-JO-TG) experiments, the result was 1514–2928 (1466–3132) million (Supplementary Fig. 4 and Supplementary Fig. 5, Supplementary Table 7 for experiment settings). The comparison of all sensitive analysis scenarios values with the base scenario value of 0.0 (110–269) million (Fig. 3c, d) showed that the effects of the different variables were in the order of GDP  > population > climate for the regions with the highest chances of facing water scarcity in future.Even though the overall water availability on the globe per capita are 6525.16 (6434.99) m3/capita/year for historical (i.e., the year 2000) and 6960.63 (6375.98) m3/capita/year, and 3894.64 (3671.39) m3/capita/year, 6821.34 (6459.90) m3/capita/year for future (i.e. the year 2099) considering SSP1-RCP2.6, SSP3-RCP7.0, and SSP5-RCP8.5 scenarios respectively (values in bracket consider HYDE3.2 and JO16 population datasets), more than 70% of world population faces the physical water scarcity defined using a threshold value of 1700 m3/capita/year of APC15 for all the scenarios (Supplementary Table 8, and Supplementary Note 1). Estimation of population facing severe water stress considering physical aspect only (i.e., APC of 500 m3/capita/year) is 2.7 billion for historical scenarios and 3.9–7.9 (3.3–7.5) billion for the future scenario, whereas considering both physical and economic aspects (i.e., threshold line defined by Oki et al.19) is 301 (333) million for the historical scenarios and 0.33–325 (176–665) million for the future scenarios (Supplementary Fig. 6 and Supplementary Fig. 7). These values show a substantial difference in the water-stressed population when considering only physical aspects and accounting for both physical and economic factors. It also indicates that a few rich (i.e., grids with high GDP-PPP per capita) physical water-scarce regions (water-stressed regions identified using APC) can ease water scarcity by water management and technological measures.The overall analysis revealed the possibility of underestimation (or overestimation) of the population facing scarcity in the future due to large differences associated with the population and GDP data distribution within the country for the SSP scenarios. The spatial distribution of the future population and GDP within and outside a country can be affected by many factors, such as water availability27,28, job opportunities, disaster adaptation and mitigation capability of a location, migration of people29, and different policies, which can be directly and indirectly associated with climatic29,30 and socioeconomic factors27,29. Hence, it would be preferable for the projection of population and GDP to consider the feedback from the hydrological and hydrodynamic models to increase their reliability based on various climate phenomena, such as water availability, floods, and droughts, in addition to simple approaches such as the statistical model limited to roads and other infrastructure for auxiliary variables by Murakami and Yamagata21 and the gravity-based model by Jones and O’Neill22. More

Summary Progress Update 2021: SDG 6 — Water and Sanitation for All (United Nations, 2021).Lu, L. et al. Wastewater treatment for carbon capture and utilization. Nat. Sustain. 1, 750–758 (2018).Article 

Google Scholar 
Li, W.-W., Yu, H.-Q. & Rittmann, B. E. Chemistry: reuse water pollutants. Nature 528, 29–31 (2015).Article 

Google Scholar 
McCarty, P. L., Bae, J. & Kim, J. Domestic wastewater treatment as a net energy producer — can this be achieved? Environ. Sci. Technol. 45, 7100–7106 (2011).Article 

Google Scholar 
Transforming our World: The 2030 Agenda for Sustainable Development (UN Department of Economic and Social Affairs — Sustainable Development, 2015).He, M. et al. Critical impacts of pyrolysis conditions and activation methods on application-oriented production of wood waste-derived biochar. Bioresour. Technol. 341, 125811 (2021). Evaluates the critical impact of pyrolysis temperature on physicochemical properties of pristine and activated biochar.Article 

Google Scholar 
IPCC. Strengthening and implementing the global response. Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) Ch. 4 (WMO, 2018).Lehmann, J., Gaunt, J. & Rondon, M. Bio-char sequestration in terrestrial ecosystems — a review. Mitig. Adapt. Strateg. Glob. Chang. 11, 403–427 (2006).Article 

Google Scholar 
Wiedner, K. & Glaser, B. in Biochar for Environmental Management: Science, Technology and Implementation 2nd edition (eds Lehmann, J. & Joseph, S.) 14–32 (Routledge, 2015).Wang, H. et al. Phosphorus recovery from the liquid phase of anaerobic digestate using biochar derived from iron-rich sludge: a potential phosphorus fertilizer. Water Res. 174, 115629 (2020).Article 

Google Scholar 
Chen, S. S. et al. Designing sustainable drainage systems in subtropical cities: challenges and opportunities. J. Clean. Prod. 280, 124418 (2021).Article 

Google Scholar 
Shaheen, S. M. et al. Wood-based biochar for the removal of potentially toxic elements in water and wastewater: a critical review. Int. Mater. Rev. 64, 216–247 (2019).Article 

Google Scholar 
Yang, Q. et al. Prospective contributions of biomass pyrolysis to China’s 2050 carbon reduction and renewable energy goals. Nat. Commun. 12, 1698 (2021).Article 

Google Scholar 
Lehmann, J. et al. Biochar in climate change mitigation. Nat. Geosci. 14, 883–892 (2021). Highlights that biochar is a carbon-negative material for environmental and energy applications.Article 

Google Scholar 
Euronews.green. How is the €3 billion biochar industry transforming green energy in Sweden? https://www.euronews.com/green/2021/06/14/how-is-the-3-billion-biochar-industry-transforming-green-energy-sweden (2021).Inkwoodresearch. Global biochar market forecast 2020–2028. https://www.inkwoodresearch.com/reports/global-biochar-market/# (2021).State of the Biochar Industry 2015 (International Biochar Initiative (IBI), 2015).Kumar, M. et al. Critical review on biochar-supported catalysts for pollutant degradation and sustainable biorefinery. Adv. Sustain. Syst. 4, 1900149 (2020).Article 

Google Scholar 
Godlewska, P., Ok, Y. S. & Oleszczuk, P. The dark side of black gold: ecotoxicological aspects of biochar and biochar-amended soils. J. Hazard. Mater. 403, 123833 (2021). Reviews the potential risks of biochar application, which need further investigation.Article 

Google Scholar 
Li, H. B. et al. Mechanisms of metal sorption by biochars: biochar characteristics and modifications. Chemosphere 178, 466–478 (2017).Article 

Google Scholar 
Lee, J., Kim, K. H. & Kwon, E. E. Biochar as a catalyst. Renew. Sust. Energ. Rev. 77, 70–79 (2017).Article 

Google Scholar 
Xiao, X., Chen, B. L., Chen, Z. M., Zhu, L. Z. & Schnoor, J. L. Insight into multiple and multilevel structures of biochars and their potential environmental applications: a critical review. Environ. Sci. Technol. 52, 5027–5047 (2018). Reviews how the transformation of organic and inorganic phases with increasing temperature determines the properties of biochar and its potential applications.Article 

Google Scholar 
Dai, Y. J., Zhang, N. X., Xing, C. M., Cui, Q. X. & Sun, Q. Y. The adsorption, regeneration and engineering applications of biochar for removal organic pollutants: a review. Chemosphere 223, 12–27 (2019).Article 

Google Scholar 
Wang, J. L. & Wang, S. Z. Preparation, modification and environmental application of biochar: a review. J. Clean. Prod. 227, 1002–1022 (2019).Article 

Google Scholar 
Zhao, Y., Yuan, X., Li, X., Jiang, L. & Wang, H. Burgeoning prospects of biochar and its composite in persulfate-advanced oxidation process. J. Hazard. Mater. 409, 124893 (2021).Article 

Google Scholar 
Ren, S. et al. Hydrochar-facilitated anaerobic digestion: evidence for direct interspecies electron transfer mediated through surface oxygen-containing functional groups. Environ. Sci. Technol. 54, 5755–5766 (2020).Article 

Google Scholar 
Wu, J., Lu, T., Bi, J., Yuan, H. & Chen, Y. A novel sewage sludge biochar and ferrate synergetic conditioning for enhancing sludge dewaterability. Chemosphere 237, 124339 (2019).Article 

Google Scholar 
Whitman, T. & Lehmann, J. Biochar — one way forward for soil carbon in offset mechanisms in Africa? Environ. Sci. Policy 12, 1024–1027 (2009).Article 

Google Scholar 
Woolf, D., Amonette, J. E., Street-Perrott, F. A., Lehmann, J. & Joseph, S. Sustainable biochar to mitigate global climate change. Nat. Commun. 1, 56 (2010).Article 

Google Scholar 
Chen, W., Meng, J., Han, X., Lan, Y. & Zhang, W. Past, present, and future of biochar. Biochar 1, 75–87 (2019).Article 

Google Scholar 
Kwak, J.-H. et al. Biochar properties and lead(ii) adsorption capacity depend on feedstock type, pyrolysis temperature, and steam activation. Chemosphere 231, 393–404 (2019).Article 

Google Scholar 
Dutta, S., He, M., Xiong, X. & Tsang, D. C. W. Sustainable management and recycling of food waste anaerobic digestate: a review. Bioresour. Technol. 341, 125915 (2021).Article 

Google Scholar 
Xiao, X. & Chen, B. A direct observation of the fine aromatic clusters and molecular structures of biochars. Environ. Sci. Technol. 51, 5473–5482 (2017).Article 

Google Scholar 
Li, S., Harris, S., Anandhi, A. & Chen, G. Predicting biochar properties and functions based on feedstock and pyrolysis temperature: a review and data syntheses. J. Clean. Prod. 215, 890–902 (2019).Article 

Google Scholar 
Crittenden, J. C., Trussell, R. R., Hand, D. W., Howe, K. J. & Tchobanoglous, G. MWH’s Water Treatment: Principles and Design 3rd edition (Wiley, 2012).Enaime, G., Bacaoui, A., Yaacoubi, A. & Luebken, M. Biochar for wastewater treatment — conversion technologies and applications. Appl. Sci. 10, 3492 (2020).Article 

Google Scholar 
Thompson, K. A. et al. Environmental comparison of biochar and activated carbon for tertiary wastewater treatment. Environ. Sci. Technol. 50, 11253–11262 (2016).Article 

Google Scholar 
Cheng, N. et al. Adsorption of emerging contaminants from water and wastewater by modified biochar: a review. Environ. Pollut. 273, 116448 (2021).Article 

Google Scholar 
Huggins, T. M., Haeger, A., Biffinger, J. C. & Ren, Z. J. Granular biochar compared with activated carbon for wastewater treatment and resource recovery. Water Res. 94, 225–232 (2016).Article 

Google Scholar 
Activated Carbon Market by Type (Powdered, Granular, Others (Pelletized, Bead)), Application (Liquid Phase (Water Treatment, Foods & Beverages, Pharmaceutical & Medical), Gaseous Phase (Industrial, Automotive)), Region — Global Forecast to 2021 (MarketsAndMarkets, 2017).Chen, Z., Zhang, W., Wang, D., Ma, T. & Bai, R. Enhancement of activated sludge dewatering performance by combined composite enzymatic lysis and chemical re-flocculation with inorganic coagulants: kinetics of enzymatic reaction and re-flocculation morphology. Water Res. 83, 367–376 (2015).Article 

Google Scholar 
Shewa, W. A. & Dagnew, M. Revisiting chemically enhanced primary treatment of wastewater: a review. Sustainability 12, 5928 (2020).Article 

Google Scholar 
Tao, S. et al. Enhanced sludge dewaterability with sludge-derived biochar activating hydrogen peroxide: synergism of Fe and Al elements in biochar. Water Res. 182, 115927 (2020).Article 

Google Scholar 
Yang, X. et al. Enhanced sludge dewaterability by a novel MnFe2O4-biochar activated peroxymonosulfate process combined with tannic acid. Chem. Eng. J. 429, 132280 (2022).Article 

Google Scholar 
Wu, Y. et al. Possibility of sludge conditioning and dewatering with rice husk biochar modified by ferric chloride. Bioresour. Technol. 205, 258–263 (2016).Article 

Google Scholar 
Wu, Y. et al. Combined sludge conditioning of micro-disintegration, floc reconstruction and skeleton building (KMnO4/FeCl3/biochar) for enhancement of waste activated sludge dewaterability. J. Taiwan. Inst. Chem. Eng. 74, 121–128 (2017).Article 

Google Scholar 
Hu, P. et al. The influence of hydrophobicity on sludge dewatering associated with cationic starch-based flocculants. J. Environ. Manage. 296, 113218 (2021).Article 

Google Scholar 
Useviciute, L. & Baltrenaite, E. Methods for determining lignocellulosic biochar wettability. Waste Biomass Valoriz. 11, 4457–4468 (2019).Article 

Google Scholar 
Li, H. et al. Enhanced sludge dewaterability by Fe-rich biochar activating hydrogen peroxide: co-hydrothermal red mud and reed straw. J. Environ. Manage. 296, 113239 (2021).Article 

Google Scholar 
Liang, J., Luo, L., Li, D., Wang, H. & Wong, J. W. C. Conductive materials supplement alters digestate dewaterability during anaerobic co-digestion of food waste and sewage sludge and promotes follow-up indigenous peroxides activation. Chem. Eng. J. 431, 133875 (2021).Article 

Google Scholar 
Wang, C. et al. Role of biochar in the granulation of anaerobic sludge and improvement of electron transfer characteristics. Bioresour. Technol. 268, 28–35 (2018).Article 

Google Scholar 
Zhao, Z., Li, Y., Quan, X. & Zhang, Y. Towards engineering application: potential mechanism for enhancing anaerobic digestion of complex organic waste with different types of conductive materials. Water Res. 115, 266–277 (2017).Article 

Google Scholar 
Fagbohungbe, M. O. et al. The challenges of anaerobic digestion and the role of biochar in optimizing anaerobic digestion. Waste Manage. 61, 236–249 (2017).Article 

Google Scholar 
van Dijk, E. J. H., Pronk, M. & van Loosdrecht, M. C. M. A settling model for full-scale aerobic granular sludge. Water Res. 186, 116135 (2020).Article 

Google Scholar 
de Kreuk, M. K., Kishida, N. & van Loosdrecht, M. C. M. Aerobic granular sludge — state of the art. Water Sci. Technol. 55, 75–81 (2007).Article 

Google Scholar 
Wang, X. et al. Rapid aerobic granulation using biochar for the treatment of petroleum refinery wastewater. Pet. Sci. 17, 1411–1421 (2020).Article 

Google Scholar 
Ming, J. et al. Bioreactor performance using biochar and its effect on aerobic granulation. Bioresour. Technol. 300, 122620 (2020).Article 

Google Scholar 
Sohn, W. et al. A review on membrane fouling control in anaerobic membrane bioreactors by adding performance enhancers. J. Water Process. Eng. 40, 101867 (2021).Article 

Google Scholar 
Wang, Z., Wu, Z. & Tang, S. Extracellular polymeric substances (EPS) properties and their effects on membrane fouling in a submerged membrane bioreactor. Water Res. 43, 2504–2512 (2009).Article 

Google Scholar 
Sima, X.-F. et al. Robust biochar-assisted alleviation of membrane fouling in MBRs by indirect mechanism. Sep. Purif. Technol. 184, 195–204 (2017).Article 

Google Scholar 
Shimabuku, K. K. et al. Biochar sorbents for sulfamethoxazole removal from surface water, stormwater, and wastewater effluent. Water Res. 96, 236–245 (2016).Article 

Google Scholar 
Suresh Kumar, P., Korving, L., Keesman, K. J., van Loosdrecht, M. C. M. & Witkamp, G.-J. Effect of pore size distribution and particle size of porous metal oxides on phosphate adsorption capacity and kinetics. Chem. Eng. J. 358, 160–169 (2019).Article 

Google Scholar 
Zhang, M. et al. Formation of disinfection byproducts as affected by biochar during water treatment. Chemosphere 233, 190–197 (2019).Article 

Google Scholar 
Kwarciak-Kozłowska, A. in Industrial and Municipal Sludge (eds Narasimha Vara Prasad, M. et al.) 337–360 (Butterworth-Heinemann, 2019).Gopinath, A. et al. Conversion of sewage sludge into biochar: a potential resource in water and wastewater treatment. Environ. Res. 194, 110656 (2021).Article 

Google Scholar 
Chen, Y.-d et al. Production, properties, and catalytic applications of sludge derived biochar for environmental remediation. Water Res. 187, 116390 (2020).Article 

Google Scholar 
Yu, J. et al. Magnetic nitrogen-doped sludge-derived biochar catalysts for persulfate activation: Internal electron transfer mechanism. Chem. Eng. J. 364, 146–159 (2019).Article 

Google Scholar 
Wan, Z. et al. Critical impact of nitrogen vacancies in nonradical carbocatalysis on nitrogen-doped graphitic biochar. Environ. Sci. Technol. 55, 7004–7014 (2021).Article 

Google Scholar 
Yan, L. et al. ZnCl2 modified biochar derived from aerobic granular sludge for developed microporosity and enhanced adsorption to tetracycline. Bioresour. Technol. 297, 122381 (2020).Article 

Google Scholar 
Ding, X., Chen, H., Yang, Q., Wei, J. & Wei, D. Effect of sludge property on the synthesis, characterization and sorption performance of sludge-based biochar. Bioresour. Technol. Rep. 7, 100204 (2019).Article 

Google Scholar 
Barbusiński, K., Parzentna-Gabor, A. & Kasperczyk, D. Removal of odors (mainly H2S and NH3) using biological treatment methods. Clean. Technol. 3, 138–155 (2021).Article 

Google Scholar 
Talaiekhozani, A., Bagheri, M., Goli, A. & Talaei Khoozani, M. R. An overview of principles of odor production, emission, and control methods in wastewater collection and treatment systems. J. Environ. Manage. 170, 186–206 (2016).Article 

Google Scholar 
Hwang, O. et al. Efficacy of different biochars in removing odorous volatile organic compounds (VOCs) emitted from swine manure. ACS Sustain. Chem. Eng. 6, 14239–14247 (2018).Article 

Google Scholar 
Choudhury, A. & Lansing, S. Biochar addition with Fe impregnation to reduce H2S production from anaerobic digestion. Bioresour. Technol. 306, 123121 (2020).Article 

Google Scholar 
Hao, X. et al. Environmental impacts of resource recovery from wastewater treatment plants. Water Res. 160, 268–277 (2019).Article 

Google Scholar 
Fang, L. L., Valverde-Pérez, B., Damgaard, A., Plósz, B. G. & Rygaard, M. Life cycle assessment as development and decision support tool for wastewater resource recovery technology. Water Res. 88, 538–549 (2016).Article 

Google Scholar 
Zheng, Y. et al. Reclaiming phosphorus from secondary treated municipal wastewater with engineered biochar. Chem. Eng. J. 362, 460–468 (2019).Article 

Google Scholar 
He, M. et al. A critical review on performance indicators for evaluating soil biota and soil health of biochar-amended soils. J. Hazard. Mater. 414, 125378 (2021).Article 

Google Scholar 
Yang, F. et al. Metal chloride-loaded biochar for phosphorus recovery: noteworthy roles of inherent minerals in precursor. Chemosphere 266, 128991 (2021).Article 

Google Scholar 
Zheng, M., Xie, T., Li, J., Xu, K. & Wang, C. Biochar as a carrier of struvite precipitation for nitrogen and phosphorus recovery from urine. Int. J. Environ. Eng. 144, 4018101 (2018).
Google Scholar 
Medeiros, D. C. C. d. S. et al. Pristine and engineered biochar for the removal of contaminants co-existing in several types of industrial wastewaters: a critical review. Sci. Total Environ. 809, 151120 (2021).Article 

Google Scholar 
Mohan, D., Sarswat, A., Ok, Y. S. & Pittman, C. U. Organic and inorganic contaminants removal from water with biochar, a renewable, low cost and sustainable adsorbent — a critical review. Bioresour. Technol. 160, 191–202 (2014).Article 

Google Scholar 
Ahmad, Z. et al. Removal of Cu(ii), Cd(ii) and Pb(ii) ions from aqueous solutions by biochars derived from potassium-rich biomass. J. Clean. Prod. 180, 437–449 (2018).Article 

Google Scholar 
Xu, Z., Xu, X., Zhang, Y., Yu, Y. & Cao, X. Pyrolysis-temperature depended electron donating and mediating mechanisms of biochar for Cr(vi) reduction. J. Hazard. Mater. 388, 121794 (2019).Article 

Google Scholar 
Heo, J. et al. Enhanced adsorption of bisphenol A and sulfamethoxazole by a novel magnetic CuZnFe2O4–biochar composite. Bioresour. Technol. 281, 179–187 (2019).Article 

Google Scholar 
Choudhary, M., Kumar, R. & Neogi, S. Activated biochar derived from Opuntia ficus-indica for the efficient adsorption of malachite green dye, Cu2+ and Ni2+ from water. J. Hazard. Mater. 392, 122441 (2020).Article 

Google Scholar 
Tao, Y. et al. Efficient removal of atrazine by iron-modified biochar loaded Acinetobacter lwoffii DNS32. Sci. Total. Environ. 682, 59–69 (2019).Article 

Google Scholar 
Xu, X. Y. et al. Removal of Cu, Zn, and Cd from aqueous solutions by the dairy manure-derived biochar. Environ. Sci. Pollut. Res. 20, 358–368 (2013).Article 

Google Scholar 
Xu, Z., Xu, X., Tsang, D. C. W. & Cao, X. Contrasting impacts of pre- and post-application aging of biochar on the immobilization of Cd in contaminated soils. Environ. Pollut. 242, 1362–1370 (2018).Article 

Google Scholar 
Xu, X. Y., Cao, X. D. & Zhao, L. Comparison of rice husk- and dairy manure-derived biochars for simultaneously removing heavy metals from aqueous solutions: role of mineral components in biochars. Chemosphere 92, 955–961 (2013).Article 

Google Scholar 
Pei, L. et al. Further reuse of phosphorus-laden biochar for lead sorption from aqueous solution: isotherm, kinetics, and mechanism. Sci. Total. Environ. 792, 148550 (2021).Article 

Google Scholar 
Klüpfel, L., Keiluweit, M., Kleber, M. & Sander, M. Redox properties of plant biomass-derived black carbon (biochar). Environ. Sci. Technol. 48, 5601–5611 (2014). Reveals considerable redox reactivity on biochar due to its surface functionality.Article 

Google Scholar 
Xu, Z. et al. Direct and indirect electron transfer routes of chromium(vi) reduction with different crystalline ferric oxyhydroxides in the presence of pyrogenic carbon. Environ. Sci. Technol. 56, 1724–1735 (2022).Article 

Google Scholar 
Xu, Z. et al. Electroactive Fe-biochar for redox-related remediation of arsenic and chromium: distinct redox nature with varying iron/carbon speciation. J. Hazard. Mater. 430, 128479 (2022).Article 

Google Scholar 
Zhong, D. et al. pH dependence of arsenic oxidation by rice-husk-derived biochar: roles of redox-active moieties. Environ. Sci. Technol. 53, 9034–9044 (2019).Article 

Google Scholar 
Liu, J. et al. Highly efficient removal of thallium in wastewater by MnFe2O4–biochar composite. J. Hazard. Mater. 401, 123311 (2021).Article 

Google Scholar 
Ruan, X. et al. Formation, characteristics, and applications of environmentally persistent free radicals in biochars: a review. Bioresour. Technol. 281, 457–468 (2019).Article 

Google Scholar 
Liang, J. et al. Different mechanisms between biochar and activated carbon for the persulfate catalytic degradation of sulfamethoxazole: roles of radicals in solution or solid phase. Chem. Eng. J. 375, 121908 (2019).Article 

Google Scholar 
Sun, T. et al. Rapid electron transfer by the carbon matrix in natural pyrogenic carbon. Nat. Commun. 8, 14873 (2017). Emphasizes the importance of graphitic structures for the electron transfer capacity of high-temperature biochar.Article 

Google Scholar 
Wan, Z. et al. A sustainable biochar catalyst synergized with copper heteroatoms and CO2 for singlet oxygenation and electron transfer routes. Green Chem. 21, 4800–4814 (2019).Article 

Google Scholar 
Dou, J. et al. Biochar co-doped with nitrogen and boron switching the free radical based peroxydisulfate activation into the electron-transfer dominated nonradical process. Appl. Catal. B 301, 120832 (2022).Article 

Google Scholar 
Liu, W.-J., Jiang, H. & Yu, H.-Q. Emerging applications of biochar-based materials for energy storage and conversion. Energy Environ. Sci. 12, 1751–1779 (2019).Article 

Google Scholar 
Yao, F. et al. Synergistic adsorption and electrocatalytic reduction of bromate by Pd/N-doped loofah sponge-derived biochar electrode. J. Hazard. Mater. 386, 121651 (2020).Article 

Google Scholar 
Yao, F. et al. Effective adsorption/electrocatalytic degradation of perchlorate using Pd/Pt supported on N-doped activated carbon fiber cathode. J. Hazard. Mater. 323, 602–610 (2017).Article 

Google Scholar 
Zhao, Z. et al. Enhanced removal of Cu-EDTA in a three-dimensional electrolysis system with highly graphitic activated biochar produced via acidic and K2FeO4 treatment. Chem. Eng. J. 430, 132661 (2022).Article 

Google Scholar 
Zhang, T. et al. Ti–Sn–Ce/bamboo biochar particle electrodes for enhanced electrocatalytic treatment of coking wastewater in a three-dimensional electrochemical reaction system. J. Clean. Prod. 258, 120273 (2020).Article 

Google Scholar 
Sun, C. et al. Biochar cathode: reinforcing electro-Fenton pathway against four-electron reduction by controlled carbonization and surface chemistry. Sci. Total Environ. 754, 142136 (2021).Article 

Google Scholar 
Liu, W.-J., Jiang, H. & Yu, H.-Q. Development of biochar-based functional materials: toward a sustainable platform carbon material. Chem. Rev. 115, 12251–12285 (2015). Reviews how biochar-based functional materials can be used for various sustainable applications.Article 

Google Scholar 
Ng, Y. H., Ikeda, S., Matsumura, M. & Amal, R. A perspective on fabricating carbon-based nanomaterials by photocatalysis and their applications. Energy Environ. Sci. 5, 9307–9318 (2012).Article 

Google Scholar 
Wang, Z., Murugananthan, M. & Zhang, Y. Graphitic carbon nitride based photocatalysis for redox conversion of arsenic(iii) and chromium(vi) in acid aqueous solution. Appl. Catal. B 248, 349–356 (2019).Article 

Google Scholar 
Lisowski, P. et al. Dual functionality of TiO2/biochar hybrid materials: photocatalytic phenol degradation in the liquid phase and selective oxidation of methanol in the gas phase. ACS Sustain. Chem. Eng. 5, 6274–6287 (2017).Article 

Google Scholar 
Zhai, Y. et al. Novel biochar@CoFe2O4/Ag3PO4 photocatalysts for highly efficient degradation of bisphenol a under visible-light irradiation. J. Colloid Interface Sci. 560, 111–121 (2020).Article 

Google Scholar 
Tang, R. et al. π–π stacking derived from graphene-like biochar/g-C3N4 with tunable band structure for photocatalytic antibiotics degradation via peroxymonosulfate activation. J. Hazard. Mater. 423, 126944 (2022).Article 

Google Scholar 
Mian, M. M. & Liu, G. Recent progress in biochar-supported photocatalysts: synthesis, role of biochar, and applications. RSC Adv. 8, 14237–14248 (2018).Article 

Google Scholar 
Colmenares, J. C., Varma, R. S. & Lisowski, P. Sustainable hybrid photocatalysts: titania immobilized on carbon materials derived from renewable and biodegradable resources. Green. Chem. 18, 5736–5750 (2016).Article 

Google Scholar 
Shi, J. On the synergetic catalytic effect in heterogeneous nanocomposite catalysts. Chem. Rev. 113, 2139–2181 (2013).Article 

Google Scholar 
Wang, W., Serp, P., Kalck, P. & Faria, J. L. Visible light photodegradation of phenol on MWNT–TiO2 composite catalysts prepared by a modified sol–gel method. J. Mol. Catal. A Chem. 235, 194–199 (2005).Article 

Google Scholar 
Matos, J., Hofman, M. & Pietrzak, R. Synergy effect in the photocatalytic degradation of methylene blue on a suspended mixture of TiO2 and N-containing carbons. Carbon 54, 460–471 (2013).Article 

Google Scholar 
Wan, D. et al. Photogeneration of reactive species from biochar-derived dissolved black carbon for the degradation of amine and phenolic pollutants. Environ. Sci. Technol. 55, 8866–8876 (2021).Article 

Google Scholar 
Fu, H. et al. Photochemistry of dissolved black carbon released from biochar: reactive oxygen species generation and phototransformation. Environ. Sci. Technol. 50, 1218–1226 (2016).Article 

Google Scholar 
Yang, F. et al. Effects of biochar-dissolved organic matter on the photodegradation of sulfamethoxazole and chloramphenicol in biochar solutions as revealed by oxygen reduction performances and free radicals. Sci. Total. Environ. 781, 146807 (2021).Article 

Google Scholar 
Farhadi, S., Aminzadeh, B., Torabian, A., Khatibikamal, V. & Alizadeh Fard, M. Comparison of COD removal from pharmaceutical wastewater by electrocoagulation, photoelectrocoagulation, peroxi-electrocoagulation and peroxi-photoelectrocoagulation processes. J. Hazard. Mater. 219-220, 35–42 (2012).Article 

Google Scholar 
Zaied, B. K. et al. A comprehensive review on contaminants removal from pharmaceutical wastewater by electrocoagulation process. Sci. Total. Environ. 726, 138095 (2020).Article 

Google Scholar 
An, X. et al. Integrated co-pyrolysis and coating for the synthesis of a new coated biochar-based fertilizer with enhanced slow-release performance. J. Clean. Prod. 283, 124642 (2021).Article 

Google Scholar 
Krasucka, P. et al. Engineered biochar — a sustainable solution for the removal of antibiotics from water. Chem. Eng. J. 405, 126926 (2021).Article 

Google Scholar 
Zhang, Y. et al. Regulation of biochar mediated catalytic degradation of quinolone antibiotics: Important role of environmentally persistent free radicals. Bioresour. Technol. 326, 124780 (2021).Article 

Google Scholar 
Nidheesh, P. V. et al. Potential role of biochar in advanced oxidation processes: a sustainable approach. Chem. Eng. J. 405, 126582 (2021).Article 

Google Scholar 
Hynes, N. R. J. et al. Modern enabling techniques and adsorbents based dye removal with sustainability concerns in textile industrial sector -a comprehensive review. J. Clean. Prod. 272, 122636 (2020).Article 

Google Scholar 
Yu, K. L. et al. Adsorptive removal of cationic methylene blue and anionic Congo red dyes using wet-torrefied microalgal biochar: equilibrium, kinetic and mechanism modeling. Environ. Pollut. 272, 115986 (2021).Article 

Google Scholar 
Yu, F. et al. ZnO/biochar nanocomposites via solvent free ball milling for enhanced adsorption and photocatalytic degradation of methylene blue. J. Hazard. Mater. 415, 125511 (2021).Article 

Google Scholar 
Medha, I. et al. (3-Aminopropyl)triethoxysilane and iron rice straw biochar composites for the sorption of Cr (vi) and Zn (ii) using the extract of heavy metals contaminated soil. Sci. Total. Environ. 771, 144764 (2021).Article 

Google Scholar 
Xu, Z. et al. Interaction with low molecular weight organic acids affects the electron shuttling of biochar for Cr(vi) reduction. J. Hazard. Mater. 378, 120705 (2019).Article 

Google Scholar 
Wang, T. et al. Novel Bi2WO6 loaded N-biochar composites with enhanced photocatalytic degradation of rhodamine B and Cr(vi). J. Hazard. Mater. 389, 121827 (2020).Article 

Google Scholar 
Kicińska, A. & Wikar, J. Ecological risk associated with agricultural production in soils contaminated by the activities of the metal ore mining and processing industry — example from southern Poland. Soil Tillage Res. 205, 104817 (2021).Article 

Google Scholar 
Shi, J., Huang, W., Han, H. & Xu, C. Pollution control of wastewater from the coal chemical industry in China: environmental management policy and technical standards. Renew. Sust. Energ. Rev. 143, 110883 (2021).Article 

Google Scholar 
Xu, X. et al. Indispensable role of biochar-inherent mineral constituents in its environmental applications: a review. Bioresour. Technol. 241, 887–899 (2017). Highlights the indispensable role of biochar’s inorganic phase in environmental applications, including pollutant removal, carbon sequestration, and soil quality improvement.Article 

Google Scholar 
Xu, Z. et al. Unraveling iron speciation on Fe-biochar with distinct arsenic removal mechanisms and depth distributions of As and Fe. Chem. Eng. J. 425, 131489 (2021).Article 

Google Scholar 
Xu, Z. et al. Participation of soil active components in the reduction of Cr(vi) by biochar: differing effects of iron mineral alone and its combination with organic acid. J. Hazard. Mater. 384, 121455 (2020).Article 

Google Scholar 
Nguyen, T. T. N. et al. The effects of short term, long term and reapplication of biochar on soil bacteria. Sci. Total. Environ. 636, 142–151 (2018).Article 

Google Scholar 
Lau, A. Y. T. et al. Surface-modified biochar in a bioretention system for Escherichia coli removal from stormwater. Chemosphere 169, 89–98 (2017).Article 

Google Scholar 
Sun, Y. et al. Waste-derived compost and biochar amendments for stormwater treatment in bioretention column: co-transport of metals and colloids. J. Hazard. Mater. 383, 121243–121243 (2020). Shows the promising potential of biochar for stormwater harvesting in sustainable drainage systems.Article 

Google Scholar 
Lehmann, J. et al. Biochar effects on soil biota — a review. Soil. Biol. Biochem. 43, 1812–1836 (2011).Article 

Google Scholar 
Zhang, S., Lin, Z., Zhang, S. & Ge, D. Stormwater retention and detention performance of green roofs with different substrates: observational data and hydrological simulations. J. Environ. Manage 291, 112682 (2021).Article 

Google Scholar 
Tirpak, R. A. et al. Conventional and amended bioretention soil media for targeted pollutant treatment: a critical review to guide the state of the practice. Water Res. 189, 116648 (2021).Article 

Google Scholar 
Tian, J. et al. A pilot-scale, bi-layer bioretention system with biochar and zero-valent iron for enhanced nitrate removal from stormwater. Water Res. 148, 378–387 (2019).Article 

Google Scholar 
Marcińczyk, M. & Oleszczuk, P. Biochar and engineered biochar as slow- and controlled-release fertilizers. J. Clean. Prod. 339, 130685 (2022).Article 

Google Scholar 
Danish, A. et al. Reusing biochar as a filler or cement replacement material in cementitious composites: a review. Constr. Build. Mater. 300, 124295 (2021).Article 

Google Scholar 
Llovet, A. et al. Fresh biochar application provokes a reduction of nitrate which is unexplained by conventional mechanisms. Sci. Total. Environ. 755, 142430 (2021).Article 

Google Scholar 
Mohanty, S. K., Cantrell, K. B., Nelson, K. L. & Boehm, A. B. Efficacy of biochar to remove Escherichia coli from stormwater under steady and intermittent flow. Water Res. 61, 288–296 (2014).Article 

Google Scholar 
Valenca, R. et al. Biochar selection for Escherichia coli removal in stormwater biofilters. Int. J. Environ. Eng. 147, 1843 (2021).
Google Scholar 
Xu, Z., He, M., Xu, X., Cao, X. & Tsang, D. C. W. Impacts of different activation processes on the carbon stability of biochar for oxidation resistance. Bioresour. Technol. 338, 125555 (2021). Reveals how aggressive modification of biochar might lead to a decrease in carbon stability, which needs further consideration.Article 

Google Scholar 
Ulrich, B. A., Loehnert, M. & Higgins, C. P. Improved contaminant removal in vegetated stormwater biofilters amended with biochar. Environ. Sci. Water Res. Technol. 3, 726–734 (2017).Article 

Google Scholar 
Ashoori, N. et al. Evaluation of pilot-scale biochar-amended woodchip bioreactors to remove nitrate, metals, and trace organic contaminants from urban stormwater runoff. Water Res. 154, 1–11 (2019).Article 

Google Scholar 
Spokas, K. A. et al. Physical disintegration of biochar: an overlooked process. Environ. Sci. Technol. Lett. 1, 326–332 (2014).Article 

Google Scholar 
Wang, L. et al. Biochar aging: mechanisms, physicochemical changes, assessment, and implications for field applications. Environ. Sci. Technol. 54, 14797–14814 (2020). Highlights how ageing processes might have a strong impact on the long-term performance of biochar.Article 

Google Scholar 
Yang, X., Pan, H., Shaheen, S. M., Wang, H. & Rinklebe, J. Immobilization of cadmium and lead using phosphorus-rich animal-derived and iron-modified plant-derived biochars under dynamic redox conditions in a paddy soil. Environ. Int. 156, 106628 (2021).Article 

Google Scholar 
Beiyuan, J. et al. (Im)mobilization and speciation of lead under dynamic redox conditions in a contaminated soil amended with pine sawdust biochar. Environ. Int. 135, 105376 (2020).Article 

Google Scholar 
Beckers, F. et al. Impact of biochar on mobilization, methylation, and ethylation of mercury under dynamic redox conditions in a contaminated floodplain soil. Environ. Int. 127, 276–290 (2019).Article 

Google Scholar 
Tong, M., He, L., Rong, H., Li, M. & Kim, H. Transport behaviors of plastic particles in saturated quartz sand without and with biochar/Fe3O4-biochar amendment. Water Res. 169, 115284 (2020).Article 

Google Scholar 
Chen, M. et al. Facilitated transport of cadmium by biochar–Fe3O4 nanocomposites in water-saturated natural soils. Sci. Total. Environ. 684, 265–275 (2019).Article 

Google Scholar 
Song, B., Chen, M., Zhao, L., Qiu, H. & Cao, X. Physicochemical property and colloidal stability of micron- and nano-particle biochar derived from a variety of feedstock sources. Sci. Total Environ. 661, 685–695 (2019).Article 

Google Scholar 
Gui, X. et al. Soil colloids affect the aggregation and stability of biochar colloids. Sci. Total Environ. 771, 145414 (2021).Article 

Google Scholar 
Negative Emission Technologies: What Role in Meeting Paris Agreement Targets? (European Academies’ Science Advisory Council, 2018).Hu, Q. et al. Biochar industry to circular economy. Sci. Total. Environ. 757, 143820 (2021).Article 

Google Scholar 
Maroušek, J. Significant breakthrough in biochar cost reduction. Clean. Technol. Environ. Policy 16, 1821–1825 (2014).Article 

Google Scholar 
Pourhashem, G., Hung, S. Y., Medlock, K. B. & Masiello, C. A. Policy support for biochar: review and recommendations. Glob. Change Biol. Bioenergy 11, 364–380 (2019).Article 

Google Scholar 
State and Trends of Carbon Pricing 2020 (World Bank Group, 2020).Standardized Product Definition and Product Testing Guidelines for Biochar that is used in Soil Version 2.1 (International Biochar Initiative (IBI), 2015).European Biochar Certificate — Guidelines for a Sustainable Production of Biochar Version 9.3E of 11 April 2021. (European Biochar Foundation, 2012).Shackley, S., Ibarrola Esteinou, R., Hopkins, D. & Hammond, J. Biochar Quality Mandate (BQM) Version 1.0 (British Biochar Foundation, 2014).Meyer, S. et al. Biochar standardization and legislation harmonization. Int. J. Environ. Eng. Landsc. Manage 25, 175–191 (2017).Article 

Google Scholar 
Azzi, E. S., Karltun, E. & Sundberg, C. Prospective life cycle assessment of large-scale biochar production and use for negative emissions in Stockholm. Environ. Sci. Technol. 53, 8466–8476 (2019).Article 

Google Scholar 
ESG Investing: Environmental Pillar Scoring and Reporting (OECD, 2020).Maroušek, J., Strunecký, O. & Stehel, V. Biochar farming: defining economically perspective applications. Clean. Technol. Environ. Policy 21, 1389–1395 (2019).Article 

Google Scholar 
Maroušek, J., Hašková, S., Zeman, R. & Vaníčková, R. Managerial preferences in relation to financial indicators regarding the mitigation of global change. Sci. Eng. Ethics 21, 203–207 (2014).Article 

Google Scholar 
Mašek, O., Buss, W. & Sohi, S. Standard biochar materials. Environ. Sci. Technol. 52, 9543–9544 (2018).Article 

Google Scholar 
Zhu, X. et al. Machine learning exploration of the direct and indirect roles of Fe impregnation on Cr(vi) removal by engineered biochar. Chem. Eng. J. 428, 131967 (2022).Article 

Google Scholar 
Palansooriya, K. N. et al. Prediction of soil heavy metal immobilization by biochar using machine learning. Environ. Sci. Technol. 56, 4187–4198 (2022).Article 

Google Scholar 
Marris, E. Black is the new green. Nature 442, 624–626 (2006).Article 

Google Scholar 
Lehmann, J. A handful of carbon. Nature 447, 143–144 (2007).Article 

Google Scholar 
Woods, W. I., Falcao, N. P. S. & Teixeira, W. G. Biochar trials aim to enrich soil for smallholders. Nature 443, 144–144 (2006).Article 

Google Scholar 
Chan, K. Y., Van Zwieten, L., Meszaros, I., Downie, A. & Joseph, S. Agronomic values of greenwaste biochar as a soil amendment. Aust. J. Soil. Res. 45, 629–634 (2007).Article 

Google Scholar 
Chan, K. Y., Van Zwieten, L., Meszaros, I., Downie, A. & Joseph, S. Using poultry litter biochars as soil amendments. Aust. J. Soil. Res. 46, 437–444 (2008).Article 

Google Scholar 
Sanchez, M. E., Lindao, E., Margaleff, D., Martinez, O. & Moran, A. Bio-fuels and bio-char production from pyrolysis of sewage sludge. Residuals Sci. Technol. 6, 35–41 (2009).
Google Scholar 
Cao, X. D., Ma, L. N., Gao, B. & Harris, W. Dairy-manure derived biochar effectively sorbs lead and atrazine. Environ. Sci. Technol. 43, 3285–3291 (2009).Article 

Google Scholar 
Warren, G. P., Robinson, J. S. & Someus, E. Dissolution of phosphorus from animal bone char in 12 soils. Nutr. Cycl. Agroecosyst. 84, 167–178 (2009).Article 

Google Scholar 
Yu, X. Y., Ying, G. G. & Kookana, R. S. Reduced plant uptake of pesticides with biochar additions to soil. Chemosphere 76, 665–671 (2009).Article 

Google Scholar 
Shen, Y. W., Linville, J. L., Urgun-Demirtas, M., Schoene, R. P. & Snyder, S. W. Producing pipeline-quality biomethane via anaerobic digestion of sludge amended with corn stover biochar with in-situ CO2 removal. Appl. Energy 158, 300–309 (2015).Article 

Google Scholar 
Ulrich, B. A., Im, E. A., Werner, D. & Higgins, C. P. Biochar and activated carbon for enhanced trace organic contaminant retention in stormwater infiltration systems. Environ. Sci. Technol. 49, 6222–6230 (2015).Article 

Google Scholar 
Fang, G., Liu, C., Gao, J., Dionysiou, D. D. & Zhou, D. Manipulation of persistent free radicals in biochar to activate persulfate for contaminant degradation. Environ. Sci. Technol. 49, 5645–5653 (2015).Article 

Google Scholar 
Yu, L. P., Yuan, Y., Tang, J., Wang, Y. Q. & Zhou, S. G. Biochar as an electron shuttle for reductive dechlorination of pentachlorophenol by Geobacter sulfurreducens. Sci. Rep. 5, 16221 (2015).Article 

Google Scholar 
Li, M. et al. Simultaneously promoting charge separation and photoabsorption of BiOX (X = Cl, Br) for efficient visible-light photocatalysis and photosensitization by compositing low-cost biochar. Appl. Surf. Sci. 386, 285–295 (2016).Article 

Google Scholar 
Maurer, D. L., Koziel, J. A., Kalus, K., Andersen, D. S. & Opalinski, S. Pilot-scale testing of non-activated biochar for swine manure treatment and mitigation of ammonia, hydrogen sulfide, odorous volatile organic compounds (VOCs), and greenhouse gas emissions. Sustainability 9, 929 (2017).Article 

Google Scholar 
Ayyappan, C. S., Bhalambaal, V. M. & Kumar, S. Effect of biochar on bio-electrochemical dye degradation and energy production. Bioresour. Technol. 251, 165–170 (2018).Article 

Google Scholar 
Chen, B. L., Chen, Z. M. & Lv, S. F. A novel magnetic biochar efficiently sorbs organic pollutants and phosphate. Bioresour. Technol. 102, 716–723 (2011).Article 

Google Scholar 
Nzediegwu, C., Naeth, M. A. & Chang, S. X. Feedstock type drives surface property, demineralization and element leaching of nitric acid-activated biochars more than pyrolysis temperature. Bioresour. Technol. 344, 126316 (2021).Article 

Google Scholar 
Li, B. et al. Adsorption of Cd(ii) from aqueous solutions by rape straw biochar derived from different modification processes. Chemosphere 175, 332–340 (2017).Article 

Google Scholar 
Yu, Y. et al. Synergistic role of bulk carbon and iron minerals inherent in the sludge-derived biochar for As(v) immobilization. Chem. Eng. J. 417, 129183 (2021).Article 

Google Scholar 
Sanford, J. R., Larson, R. A. & Runge, T. Nitrate sorption to biochar following chemical oxidation. Sci. Total. Environ. 669, 938–947 (2019).Article 

Google Scholar 
Sizmur, T., Fresno, T., Akgül, G., Frost, H. & Moreno-Jiménez, E. Biochar modification to enhance sorption of inorganics from water. Bioresour. Technol. 246, 34–47 (2017).Article 

Google Scholar 
Zhao, L. et al. Copyrolysis of biomass with phosphate fertilizers to improve biochar carbon retention, slow nutrient release, and stabilize heavy metals in soil. ACS Sustain. Chem. Eng. 4, 1630–1636 (2016).Article 

Google Scholar 
Cuong, D. V., Wu, P.-C., Chen, L.-I. & Hou, C.-H. Active MnO2/biochar composite for efficient As(iii) removal: insight into the mechanisms of redox transformation and adsorption. Water Res. 188, 116495 (2021).Article 

Google Scholar 
Liang, J. et al. Persulfate oxidation of sulfamethoxazole by magnetic iron-char composites via nonradical pathways: Fe(iv) versus surface-mediated electron transfer. Environ. Sci. Technol. 55, 10077–10086 (2021).Article 

Google Scholar 
Liu, L.-L. et al. Edge electronic vacancy on ultrathin carbon nitride nanosheets anchoring O2 to boost H2O2 photoproduction. Appl. Catal. B 302, 120845 (2022).Article 

Google Scholar 
Zhou, Y. et al. Sulfur and nitrogen self-doped carbon nanosheets derived from peanut root nodules as high-efficiency non-metal electrocatalyst for hydrogen evolution reaction. Nano Energy 16, 357–366 (2015).Article 

Google Scholar 
Zhang, Z. et al. A novel biochar electrode for efficient electroreduction of nitrate: selective and regulation of halogen. Chemosphere 288, 132400 (2022).Article 

Google Scholar 
Chen, P. et al. Nitrogen-doped nanoporous carbon nanosheets derived from plant biomass: an efficient catalyst for oxygen reduction reaction. Energy Environ. Sci. 7, 4095–4103 (2014).Article 

Google Scholar 
Hagemann, N. et al. Organic coating on biochar explains its nutrient retention and stimulation of soil fertility. Nat. Commun. 8, 1089 (2017).Article 

Google Scholar 
Farid, I. M. et al. Co-composted biochar derived from rice straw and sugarcane bagasse improved soil properties, carbon balance, and zucchini growth in a sandy soil: a trial for enhancing the health of low fertile arid soils. Chemosphere 292, 133389 (2022).Article 

Google Scholar 
Antonangelo, J. A., Sun, X. & Zhang, H. The roles of co-composted biochar (COMBI) in improving soil quality, crop productivity, and toxic metal amelioration. J. Environ. Manage. 277, 111443 (2021).Article 

Google Scholar 
Wang, Y., Xiao, X., Xu, Y. & Chen, B. Environmental effects of silicon within biochar (Sichar) and carbon–silicon coupling mechanisms: a critical review. Environ. Sci. Technol. 53, 13570–13582 (2019).Article 

Google Scholar 
Liang, J. et al. High oxygen reduction reaction performance nitrogen-doped biochar cathode: a strategy for comprehensive utilizing nitrogen and carbon in water hyacinth. Bioresour. Technol. 267, 524–531 (2018).Article 

Google Scholar 
Parsa, M., Nourani, M., Baghdadi, M., Hosseinzadeh, M. & Pejman, M. Biochars derived from marine macroalgae as a mesoporous by-product of hydrothermal liquefaction process: characterization and application in wastewater treatment. J. Water Process. Eng. 32, 100942 (2019).Article 

Google Scholar 
Zhao, L., Cao, X., Mašek, O. & Zimmerman, A. Heterogeneity of biochar properties as a function of feedstock sources and production temperatures. J. Hazard. Mater. 256–257, 1–9 (2013).
Google Scholar 
Xiao, X., Chen, B. & Zhu, L. Transformation, morphology, and dissolution of silicon and carbon in rice straw-derived biochars under different pyrolytic temperatures. Environ. Sci. Technol. 48, 3411–3419 (2014).Article 

Google Scholar 
Qiu, Y. et al. Contribution of different iron species in the iron–biochar composites to sorption and degradation of two dyes with varying properties. Chem. Eng. J. 389, 124471 (2020).Article 

Google Scholar 
Liu, X. N., Shen, F., Smith, R. L. & Qi, X. H. Black liquor-derived calcium-activated biochar for recovery of phosphate from aqueous solutions. Bioresour. Technol. 294, 122198 (2019).Article 

Google Scholar 
Luo, J., Yi, Y., Ying, G., Fang, Z. & Zhang, Y. Activation of persulfate for highly efficient degradation of metronidazole using Fe(ii)-rich potassium doped magnetic biochar. Sci. Total Environ. 819, 152089 (2022).Article 

Google Scholar 
Nan, H. et al. Pyrolysis temperature-dependent carbon retention and stability of biochar with participation of calcium: implications to carbon sequestration. Environ. Pollut. 287, 117566 (2021).Article 

Google Scholar  More