Emissões de Gases de Efeito Estufa no Saneamento

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Greenhouse gas emissions from sanitation and wastewater management systems: a
review
Layla Lambiasia, Daniel Ddiba b,*, Kim Anderssonc, Masud Parvaged and Sarah Dickin e
a Center for Sustainability Studies of Fundação Getulio Vargas (FGVces), Avenida 9 de julho, 2029, Bela Vista – 01313-902, São Paulo, Brazil
b Stockholm Environment Institute, Sweden
c Stockholm Environment Institute, Linnégatan 87D, Box 24218, Stockholm 104 51, Sweden
d Swedish Veterinary Agency, Department of Chemistry, Environment and Feed Hygiene, Travvägen 20, SE-756 51 Uppsala, Sweden
e Department of Women and Children’s Health, Swedesd – Sustainability Learning and Research Centre, Uppsala University, 751 85 Uppsala, Sweden
*Corresponding author. E-mail: daniel.ddiba@sei.org
DD, 0000-0001-5908-6417; SD, 0000-0003-0437-3755
ABSTRACT
There is growing awareness of the contribution of sanitation systems to greenhouse gas (GHG) emissions globally, and hence to climate
change. However, there is a lack of comprehensive insight into emission sources dis-aggregated across the entire sanitation chain. This
study presents a detailed review and analysis of emission sources from both sewer-based and non-sewered sanitation systems, with a
focus on both fugitive emissions and those related to system operation. Our analysis highlights evidence gaps in several areas in the litera-
ture: quantifying emissions from non-sewered sanitation systems, with particular gaps related to technologies like biogas toilets and
composting toilets; oversight of contextual factors such as environmental conditions and infrastructure operational status in GHG accounting;
a dearth of holistic GHG emission studies across the entire sanitation chain comparable to those in the solid waste management sector; and
inconsistencies in GHG measurement methods. By pinpointing these gaps, this review provides a robust reference for planning climate miti-
gation strategies for sanitation and wastewater management systems, emphasizes the urgent need for the incorporation of climate-smart
solutions in the sector e.g. in the design of new and retrofitted infrastructure, and aims to bridge the sustainable development goals related
to sanitation and climate action.
Key words: climate change, faecal sludge management, GHG emissions, mitigation, non-sewered sanitation, wastewater
HIGHLIGHTS
• Comprehensive mapping of GHG emission sources in sewer-based and non-sewered sanitation systems.
• Identifies crucial evidence gaps in non-sewered sanitation systems’ GHG emissions.
• Highlights overlooked aspects of environmental and operational conditions in GHG accounting.
• Emphasizes the need for holistic GHG emission studies and provides insights for developing climate-smart sanitation and wastewater
management strategies.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and
redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).
© 2024 The Authors Journal of Water and Climate Change Vol 00 No 0, 1 doi: 10.2166/wcc.2024.603
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https://orcid.org/0000-0001-5908-6417
https://orcid.org/0000-0003-0437-3755
mailto:daniel.ddiba@sei.org
http://orcid.org/
http://orcid.org/0000-0001-5908-6417
http://orcid.org/0000-0003-0437-3755
http://creativecommons.org/licenses/by/4.0/
https://crossmark.crossref.org/dialog/?doi=10.2166/wcc.2024.603&domain=pdf&date_stamp=2024-02-16
GRAPHICAL ABSTRACT
1. INTRODUCTION
While sanitation is a fundamental basis for public health, there is lower awareness of the associated contributions to environ-
mental pollution (Gwenzi et al. 2023). Sanitation systems, including all their components in the sanitation service chain from
containment to conveyance, treatment, and disposal or reuse, are responsible for an often-overlooked share of greenhouse gas
(GHG) emissions, especially nitrous oxide (N2O) and methane (CH4) whose global warming potential (GWP) over a 100-year
period is 273 and 28, respectively (IPCC 2023). These emissions include direct emissions from decomposition of organic
matter found in excreta, as well as indirect emissions due to e.g. energy and transport used for operating treatment facilities.
Wastewater and sludge management are estimated to be responsible for 257 million tonnes of carbon dioxide equivalents
(CO2-eq) while non-sewered sanitation is responsible for 267 million tonnes CO2-eq annually (Lutkin et al. 2022). This
altogether accounts for approximately 1.3% of global GHG emissions (Ritchie & Roser 2020), roughly similar to the
global aviation sector. With regards to methane, non-sewered sanitation is estimated to be contributing up to 4.7% of
global anthropogenic methane emissions (Cheng et al. 2022). At a city level, recent modelling estimates of direct and indirect
emissions from both sewer-based and non-sewered sanitation technologies in Kampala, Uganda, indicated that sanitation
could be responsible for more than 50% of the city’s emissions (Johnson et al. 2022).
While emissions from sanitation systems have been small relative to other sectors, recent trends point to increases in rela-
tive contributions globally. In the United States, a growing proportion of CH4 emissions arise from wastewater treatment
(10% in 1990 to 14% in 2019) (Moore et al. 2023). In regions such as South Asia and sub-Saharan Africa which still
have a huge sanitation gap and which are also experiencing rapid population growth and urbanization, GHG emissions
from sanitation systems are projected to increase, mainly due to a reliance on pit latrines (Reid et al. 2014). Globally,
about 3.3 billion people are dependent on non-sewered sanitation technologies today and this number will possibly reach
5 billion by 2030 (Strande et al. 2014; Cheng et al. 2022). This will involve the construction of many new sanitation facilities,
and thus may result in an increase in GHG emissions (Orner & Mihelcic 2018; IPCC 2022). It is therefore important to
consider options for sanitation technologies with lower emissions, while also ensuring that users themselves, particularly
in low-income countries, should not have to bear the burden of the potential extra costs of lower-emissions sanitation sys-
tems entirely alone.
One key challenge to improving identification of sanitation options with lower emissions is that GHG emissions account-
ing across the sanitation service chain remains limited due to barriers rooted in the inherent complexity around designing,
implementing, and operating sanitation systems (see e.g. Spuhler et al. 2020). Relatively little research has been focused
on trying to systematize the relevant information concerning GHG emissions throughout the entire sanitation chain, with
most work typically addressing isolated components especially in the treatment part of the chain without integrated systems
approaches as indicated by Shaw et al. (2021). Therefore, it is critical to understand the main factors influencing emissions
and the current evidence gaps in the sanitation and wastewater sector across the entire sanitation chain.
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In this paper, we aim to contribute to better consideration of climate change in planning sanitation services by reviewing
and synthesizing information on GHG emissions from the sanitation and wastewater management chain. We categorize
results according to the type of sanitation system, either sewer-based with wastewater treatment or non-sewered systems,
describe the key emissions sources at each stage of the sanitation service chain, and discuss three key aspects related to
GHG emissions from the sanitationMoreover, the methods for empirically quantifying GHG emissions necessitate more nuanced scrutiny. A multitude of
methodologies exist, ranging from static chambers for localized measurements (see e.g. Reddy et al. 2022) to remote-sensing
techniques for capturing emissions over expansive regions (Bastviken et al. 2022). Recent studies by e.g. Foy et al. (2023) and
Gålfalk et al. (2022) have unveiled potential disparities in results stemming from different methods, underlining the impera-
tive of methodological rigour. The interplay between empirical measurements and model-based inferences highlights the need
for precision in emissions quantification and a critical examination of methodological variations. However, there is also a
need for empirical methods that are suitable for low-income contexts, where conventional methods that rely on access to lab-
oratory facilities may be limited (Poudel et al. 2023).
4.2. The need to monitor emissions across the entire sanitation chain
Our findings indicate that prior research often focuses on specific technologies, lacking a comprehensive view of the entire
sanitation chain. Even ground-breaking studies such as the city-wide assessment of sanitation emissions in Kampala (Johnson
et al. 2022) exclude crucial aspects like resource recovery or end-disposal. Spuhler et al. (2020) underscored that the environ-
mental ramifications of sanitation systems are intrinsically linked to the configuration and synergistic amalgamation of
diverse technologies. This implies that GHG emissions from sanitation systems are also influenced by the configuration of
the technology combinations across the entire sanitation chain, and hence a whole system perspective is necessary to achieve
a good understanding of the carbon footprint thereof.
Exemplifying this perspective, comprehensive assessments of GHG emissions have been undertaken for solid waste man-
agement systems as part of LCA studies, covering everything from waste collection bins at household level through
transportation and treatment up to end-use of resource recovery products or disposal of the waste residues (see e.g. Laurent
et al. 2014a, 2014b). The integration of this approach within the sanitation discourse is not only feasible but also essential. A
comprehensive understanding of emissions necessitates the monitoring of emissions all the way from user interface through
treatment to end-use and disposal. Moreover, the diverse juxtaposition of non-sewered sanitation alongside sewer-based cen-
tralized systems in heterogeneous infrastructure configurations (Lawhon et al. 2018) calls for an integrative approach that
considers the multiplicity of sanitation configurations. Furthermore, a comprehensive emissions assessment must encompass
resource recovery, recognizing the varying mitigation potential associated with different recovery options.
4.3. Opportunities for mitigation strategies across the sanitation chain
Although sanitation contributes only 1.3% of global emissions (Ritchie & Roser 2020), recent research unearths a contextual
variance. For instance, findings from Kampala indicate that the sanitation sector’s emissions could possibly account for about
50% of the city’s total emissions (Johnson et al. 2022). This creates an imperative to explore avenues for reducing the carbon
footprint of sanitation systems and hence contribute to climate mitigation efforts. Our findings in this review point to three
avenues to explore for the development of mitigation strategies in the sanitation sector, as described in the following.
The strategic role of technology choices: Zeng et al. (2017) underscores the efficiency of bioreactors and anaerobic–anoxic
processes in WWTPs, indicating that targeted technology choices can yield substantial emissions reductions. The implications
span across various sanitation and wastewater management processes, from CH4 emissions in technologies that foster
anaerobic conditions to N2O emissions in aeration-based processes, and constructed wetlands which may act as carbon
sinks despite their large land footprints. With regards to non-sewered sanitation, studies have highlighted how efforts to
increase access to sanitation through massive construction of pit latrines could impede climate mitigation efforts
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(Reid et al. 2014; Shaw et al. 2021; Cheng et al. 2022), hence pointing to the need to consider alternative lower emission
technology options. At the end of the sanitation chain, the various options for resource recovery have different emissions pro-
files, thus advocating the need for careful technology selection.
Operational conditions and continuous monitoring: As highlighted in our findings, studies by e.g. Molinos-Senante et al.
(2014) and Noyola et al. (2018) indicate a correlation between efficient WWTP operations and reduced GHG emissions,
while the influence of operational conditions on sewer systems’ emissions underscores the significance of this aspect. In
the realm of non-sewered sanitation, operational optimization is crucial under varying environmental conditions such as
temperature and water table depth. This approach is particularly emphasized in maintaining aerobic conditions within sys-
tems, for instance, through frequent emptying so as to limit CH4 emissions. This is particularly important in contexts
where climate change is worsening flooding or water-logging from sea level rise. The dynamic nature of sanitation systems
also underscores the indispensability of continuous real-time monitoring to identify emergent emissions hotspots, hence
the need for comprehensive data collection.
Resource recovery: Recovering and reusing resources like water, energy and nutrients which are embedded in excreta-
derived waste streams in sanitation systems mainly contributes to mitigation through the avoidance of emissions from pro-
ducts that are replaced by resource recovery products. The mitigation potential of anaerobic digestion and subsequent use
of biogas for energy has been extensively covered in the literature, as well as that of using various excreta-derived fertilizers
and soil amendments as an alternative to artificial fertilizers (see e.g. Otoo & Drechsel 2018). Other options include water
reuse and fly larvae composting for animal feed production, all of which contribute to climate mitigation by reducing the
need for primary production (Ddiba et al. 2022). These strategies not only circumvent the emissions associated with conven-
tional products but also contribute to sustainable resource management.
4.4. Study limitations
It is important to highlight that we aimed to identify literature that is relevant to understand the emission sources across the
sanitation chain, not to comprehensively cover all literature that exists on the topic. As a result, certain studies may not have
been incorporated, which could impact some of the insights resented in this review. In addition, the accuracy and consistency
of data across different studies also pose a limitation. Comparability can be challenging due to the diverse range of methods,
data sources and techniques employed for GHG measurements and the variations in assumptions and reporting standards.
5. CONCLUSIONS
This paper reviews evidence on emission sources and hotspots across the sanitation chain for both non-sewered and sewer-
based sanitation systems, covering all the stages of the sanitation service chain. We review existing literature on key GHGs
like CH4 and N2O in both types of systems and present the current state of knowledge, providing a comprehensive overview
for understanding the factors that influence the quantity of emissions including system design and configuration, system oper-
ation, characterization of waste streams, energy consumption and resource recovery.
Our findings underscoresignificant gaps in the literature and the imperative for further research on sanitation-climate
change linkages. First, we found few empirical studies on GHG emissions from non-sewered sanitation. While there are
some studies focused on pit latrines, septic tanks and CBS in a few locations, there is inadequate attention to other types
of non-sewered sanitation technologies such as composting toilets, biogas toilets and fossa alternae and their variations
across diverse geographical contexts. Secondly, we report that contextual factors such as climatic conditions, soil properties
and the status of operation of sanitation infrastructure are sometimes not considered in GHG emissions accounting, despite
their significant impact on emissions. Thirdly, few studies account for GHG across the whole sanitation chain, a holistic
approach long established in the solid waste management sector, through empirical and LCA-based research. Finally, we
highlight variations in GHG measurement results from methods like flux chambers and remote-sensing, underscoring the
need to explore and clarify methodological discrepancies. The above gaps point to areas where further research efforts
could be directed.
This paper’s comprehensive review can serve as a valuable reference in the design of climate mitigation strategies in the
sanitation sector by practitioners and policy-makers. For instance, we provide insights to inform the design, implementation
and operation of so-called low-emission or climate-smart sanitation infrastructure. Practitioners should also pursue real-time
GHG emissions monitoring in the sanitation and wastewater systems they operate, to bolster evidence and hence advance
synergies between sustainable development goal 6.2 (sanitation and hygiene) and 13 (climate action).
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ACKNOWLEDGEMENTS
Funding for this research was provided by the Swedish International Development Cooperation Agency (Sida), through core
support to the Stockholm Environment Institute.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.
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	Greenhouse gas emissions from sanitation and wastewater management systems: a review
	INTRODUCTION
	Background: data gaps related to estimating emissions from the sanitation chain
	METHODS
	RESULTS: GHG EMISSIONS IN THE SANITATION CHAIN
	Sewer-based sanitation systems with centralized treatment
	Emission sources across the sewer-based sanitation chain
	User interface
	Conveyance
	(Semi-) centralized treatment
	Use and/or disposal
	System design and configuration
	System operation
	Energy consumption and energy recovery
	Non-sewered sanitation systems
	Emission sources across non-sewered sanitation systems
	User interface
	Containment and storage/treatment
	Conveyance
	(Semi-) centralized treatment
	Use and/or disposal
	Pit latrines
	Septic tanks
	Container-based sanitation
	Energy consumption and resource recovery in non-sewered sanitation systems
	DISCUSSION
	Empirical measurements of GHG emissions versus model-based emissions quantification
	The need to monitor emissions across the entire sanitation chain
	Opportunities for mitigation strategies across the sanitation chain
	Study limitations
	CONCLUSIONS
	ACKNOWLEDGEMENTS
	DATA AVAILABILITY STATEMENT
	CONFLICT OF INTEREST
	REFERENCESchain: systems configuration; systems operation; and energy consumption.
1.1. Background: data gaps related to estimating emissions from the sanitation chain
The choice of sanitation technologies and systems determines where GHG emissions occur and at which rate. In this paper,
we conceptualize a sanitation system using the five functional groups of sanitation technologies proposed by Tilley et al.
(2014): (1) user interface, (2) containment and storage/treatment, (3) conveyance or transport, (4) (semi-)centralized treat-
ment, and (5) use and/or disposal, as described in Table 1. This framework is used as the basis to describe the flow of
emissions from where human excreta is generated to the point of reuse or ultimate disposal. In Figure 1, examples are pro-
vided for how the various sanitation technologies can be arranged into sewer-based or non-sewered sanitation systems. A
more in-depth discussion about how to arrange various sanitation technologies into different system configurations is avail-
able in Tilley et al. (2014, pp. 15–37).
Estimating GHG emissions from sanitation technologies can be highly uncertain (Doorn et al. 2006). The IPCC (Intergo-
vernmental Panel on Climate Change) approach for estimation of GHG emissions is based on the application of emissions
factors, i.e. a maximum emission capacity for each treatment technology. Such parameters are always established based on
measurements of some kind, although those can be challenging and difficult to validate (Hobson 1999; Johnson et al. 2022).
The IPCC differentiates three possible tiers of methods (Rypdal et al. 2006), which vary according to the availability and qual-
ity of data, progressively. The first tier involves using default values in countries with limited data, the second tier involves
Table 1 | Functional groups of the sanitation service chain with examples of technologies in each group (Tilley et al. 2014)
Functional group Description Examples of technologies in the functional group
User interface The way the user accesses the sanitation system,
including configuration of the technology removing
excreta (with the use of water or not).
Any type of toilet including dry toilets, urine-diverting
dry toilets (UDDT), urinals, pour-flush toilet, cistern
flush toilets, urine-diverting flush toilet (UDFT)
Containment and
storage/treatment
Ways in which the products generated at the User
Interface are collected, stored, and possibly passively
treated, as in the case of on-site technologies.
Urine storage tank/container, single pit, single ventilated
improved pit (VIP), double ventilated improved pit
(VIP), fossa alternae, twin pits for pour-flush,
dehydration vaults, composting chamber, septic tank,
anaerobic baffled reactor (ABR), anaerobic filters and
biogas reactors
Conveyance/
transport
Describes the ways products are transported between
functional groups, such as from the User Interface or
Collection point to Storage/Treatment.
Jerrycan/tank, human-powered emptying and transport,
motorized emptying and transport, simplified sewer,
solids-free sewer, conventional gravity sewer, transfer
station (underground holding tank)
(Semi-)centralized
treatment
Treatment technologies used when a larger number of
users are being served. It can include pre- and post-
treatment of wastewater, brownwater, greywater, as
well as sludge.
Settler, Imhoff tank, anaerobic baffled reactor (ABR),
anaerobic filter, waste stabilization ponds (WSP),
aerated pond, free-water surface constructed wetland,
horizontal subsurface flow constructed wetland,
vertical flow constructed wetland, trickling filter, up-
flow anaerobic sludge blanket reactor (UASB),
activated sludge, sedimentation/thickening ponds,
unplanted drying beds, planted drying beds, co-
composting, biogas reactor
Use and/or disposal Includes the ways that products are reintroduced in the
environment, either as reduced-risk waste materials,
or as recycled resources, inside or outside the system.
Fill and cover/ arborloo, application of stored urine,
application of dehydrated faeces, application of pit
humus and compost, application of sludge, irrigation,
soak pit, leach field, fishpond, floating plant pond,
water disposal/ groundwater recharge, surface disposal
and storage, biogas combustion
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Figure 1 | Three examples of the sanitation service chain with different system configurations where System A consists of water flush toilets
connected to sewers with a centralized wastewater treatment plant, System B is non-sewered and consist of dry or flush toilets where the
treatment of sludge happens on-site, and System C is also non-sewered and consists of dry or flush toilets where the sludge is collected in a
tank on-site but then later emptied and taken via road-based transport to a treatment facility off-site. (Images adapted from Paul Clarkin and
Wenger et al. 2023).
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using default values but with the incorporation of country-specific emission factors and activity data, and the third tier
involves using local measurements and specific methods developed at the country level in those contexts with advanced
methods and sufficient data.
Despite rising concerns regarding GHG emissions and the sustainability of sanitation systems, estimates of GHG emissions
are still mostly focused on large centralized treatment facilities (Orner & Mihelcic 2018; Johnson et al. 2022). There has been
relatively less interest in the GHG production dynamics of non-sewered sanitation technologies, and therefore a limited
understanding of emissions from these technologies persists. The lack of focus on comprehending and quantifying GHG
emissions from non-sewered sanitation systems pervades both low- and middle-income countries, where these systems are
prevalent, and high-income countries. In Switzerland and Sweden, GHG emissions from non-sewered sanitation systems
are not included in the national GHG inventories due to the assumption that low average temperatures imply negligible pro-
duction and release of gases like CH4 (SEPA 2022; Ulrich & Etter 2023). However, rising temperatures due to global warming
challenge this assumption, and a recent report found that CH4 emissions from on-site sanitation systems in Switzerland could
be contributing as much as 15% of the country’s wastewater related CH4 emissions (Ulrich & Etter 2023). Even while quanti-
fication of GHG emissions from centralized systems is a common practice, emissions sources and mechanisms connected to
biological processes are not yet fully understood, especially given the complexity of such processes and the inadequacy of
applicable data (Mannina et al. 2016). Achieving sustainability in the sector will require deepening our knowledge on emis-
sions from the perspective of the whole sanitation chain, as well as from different types of sanitation systems.
A challenge to the dissemination of adequate information is the complexity of the sanitation chain, which by combining a
growing number of possible technologies and system configurations, can reach thousands of potential combinations (Spuhler
et al. 2020). However, this complexity also means there are a wide range of possibilities for mitigation of GHG emissions and
hence opportunities to contribute to more sustainable sanitation systems. It is important to note that sanitation systems con-
sist of more than just the technological choices along the chain, and include institutional and governance arrangements for
operating and managing the systems (Ddiba et al. 2020). However, an analysis of governance arrangements and their role in
mitigating GHG emissions is beyond thescope of this paper.
2. METHODS
Given the complexity and multiplicity of system configurations within the sanitation service chain, we used a narrative litera-
ture review approach (Benoot et al. 2016) but integrated some insights from systematic review methodology in our search
process (see e.g. Haddaway et al. 2015). To identify literature sources for this review, we searched in Web of Science,
Scopus, and Google Scholar for eligible studies based on titles, abstracts, and keywords, enabling us to cover a wide range
of sources for scientific and grey literature (see Gusenbauer & Haddaway 2020). The search strings comprised a combination
of different words and synonyms to retrieve relevant results, including four central terms as the main components: sanitation,
wastewater, GHGs, and emissions. For the first two databases, the resulting articles were exported to a reference management
software. In Google Scholar, only literature from the first 10 pages of results was considered. The retrieved search results were
analyzed to remove duplicates and non-relevant articles. The sampling process was iterative, with ongoing identification,
assessment, and synthesis of relevant information.
The narrative review approach drew on a combination of three purposeful sampling techniques as proposed by Suri (2011):
maximum variation sampling, criterion sampling and theoretical sampling. Maximum variation sampling sought to under-
stand the phenomenon, in this case emissions from sanitation services. This step aimed to delineate the key dimensions of
the problem and its variations across different contexts. Papers were retrieved considering their broad relationship with
the topic, such as describing sanitation-related emissions and without considering further details related to specific study
design or approach. A first screening of the results showed that most articles were centred around centralized sanitation sys-
tems, especially in the treatment phase. Therefore, focused searches were conducted to retrieve articles on other parts of the
sanitation chain, such as conveyance and on-site treatment technologies.
The criterion sampling step involved retrieving articles with information-rich cases, providing further detail into emissions
along the sanitation chain. The criteria used at this stage was that each paper should; (i) describe part of the sanitation chain
and/or technology, (ii) describe GHG emissions from the sanitation technologies, and (iii) discuss the factors influencing
emissions. In the last stage, theoretical sampling was used, and the collected evidence was placed along the sanitation
chain. This allowed the identification of knowledge gaps that then led to new focused searches given that there were gaps
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related to non-sewered sanitation systems and treatment technologies. This step was implemented to ensure a diverse range of
studies for mapping of emissions throughout the sanitation chain in line with the study objectives. Additional references were
also identified through snowballing and citation tracing (Dixon-Woods et al. 2005). At full text review, evidence was coded
and extracted into spreadsheets, including information about type of sanitation system, system configuration, energy con-
sumption, emissions’ sources, wastewater characteristics, and system operation.
3. RESULTS: GHG EMISSIONS IN THE SANITATION CHAIN
This section describes GHG emission sources within two sanitation system configurations: (i) sewer-based systems with cen-
tralized wastewater treatment plants (WWTPs) and (ii) non-sewered sanitation systems. In the first case, aspects such as
systems design and operation, energy consumption, and limitations in GHG accounting are analyzed. In the second case,
we describe the evidence about GHG emission sources at various stages of non-sewered sanitation chains, and also discuss
the influence of resource recovery as well as system design and operational conditions on GHG emissions from pit latrines,
septic tanks, and container-based sanitation (CBS). In Figure 2, we provide an overview of potential sources of GHG emis-
sions throughout the sanitation chain in both system configurations while in Figure 3, we highlight the emission potential of
CH4 and N2O from different treatment technologies, as well as from uncollected and discharged wastewater.
3.1. Sewer-based sanitation systems with centralized treatment
3.1.1. Emission sources across the sewer-based sanitation chain
This section explores how various functional groups within centralized sewer-based sanitation systems have been addressed
in the context of GHG emissions accounting.
3.1.1.1. User interface. In the context of sewer-based sanitation systems, the user interface functional group of technologies,
such as cistern flush toilets, has been largely overlooked in the assessment of GHG emissions. This oversight may stem from
the prevailing belief that these interfaces merely act as points of entry to the broader sanitation network, with the assumption
being that waste does not remain within this segment long enough to produce notable emissions. Consequently, any emissions
originating from these user interfaces are typically considered to be encompassed within the overall emissions attributed to
the sewerage system, specifically under the conveyance category. However, it is essential to recognize the indirect emissions
associated with flush toilets, which arise from the processes involved in water extraction, treatment, and distribution for
Figure 2 | Possible sources of GHG emissions along the sanitation chain. ‘Substantial’ refers to sources of emissions that are well recognized
in the literature and which lead to significant quantities of emissions, while ‘Possible’ refers to sources of emissions that have been identified
but for which there are uncertainties in quantifying their contribution to quantities of emissions. Some areas have both types of sources,
indicating that some emission processes are well-studied while others are not.
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flushing purposes. This aspect, underscored by several studies (see e.g. Reffold et al. 2008; Hackett & Gray 2009; Shimizu
et al. 2012) necessitates a more comprehensive evaluation of emissions in this area.
3.1.1.2. Conveyance. Within the conveyance functional group, sewer networks may be of the simplified type, solids-free type
or gravity-driven sewers (Tilley et al. 2014). One of the significant sources of CH4 emissions in centralized sanitation systems
is sewer lines. Improper construction and insufficient maintenance of sewer lines leads to stagnation of wastewater in a closed
environment and results in anaerobic conditions which can produce significant amounts of CH4 (Chaosakul et al. 2014).
Foley et al. (2009) estimated an additional 6–9% increase in the annual GHG inventory for a WWTP due to CH4
emissions from the sewer network, while Liu et al. (2015) estimate that CH4 from sewers can contribute up to 18% of the
carbon footprint of wastewater management systems.
A review by Liu et al. (2015) indicates that CH4 in sewers is mainly produced by methanogens from acetate and hydrogen
under anaerobic conditions in sewer biofilms and sediments, both in rising and gravity sewers, with gas release occurring in
ventilated spaces under turbulence. However, there is substantial spatial and temporal variation in the production of CH4
within sewers and while there have been some indications of CH4 sinks in sewers, their potential is not yet well understood
nor quantified, limiting our understanding of the full extent of CH4 emissions from sewers. Factors that influencethe gener-
ation of CH4 in sewers include the hydraulic retention time, temperature, COD loading and the pipe area-to-volume ratio.
Given that several field studies have acknowledged this source of CH4 emissions (Noyola et al. 2018), it cannot be disre-
garded in GHG emissions accounting. The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas
Inventories (hereinafter, the 2019 refinement to the IPCC guidelines) acknowledges this issue but only includes emission fac-
tors for stagnant sewers which are assumed to have anaerobic conditions, while sewers in which wastewater is freely flowing
are assumed to have negligible CH4 emissions.
Some studies have also pointed to the fact that underground gravity sewers are a likely source of N2O emissions due to
nitrification and denitrification processes in biofilms (see e.g. Short et al. 2014; Eijo-Río et al. 2015). Particularly, sewers
with bigger head space, i.e. lower wastewater levels, tend to generate higher emissions of N2O. However, more research is
still needed to characterize the spatial and temporal variabilities of N2O production and release, particularly at hotpots
like pumping stations, gas relief valves and other turbulence zones (Short et al. 2014).
Figure 3 | CH4 and N2O emission potentials for various wastewater and (faecal) sludge management pathways. Source: Based on Bartram
et al. (2019) and this review.
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3.1.1.3. (Semi-) centralized treatment. Most of the research on fugitive emissions from sanitation systems has focused on
technologies that fall within the centralized treatment functional group (Johnson et al. 2022). Wastewater treatment units
are the biggest source of N2O emissions in centralized systems particularly in the biological treatment and nutrient
removal processes (Lutkin et al. 2022), with even low quantities of N2O possibly accounting for up to 90% of the total
GWP from these systems in some instances (Préndez & Lara-González 2008). This implies that even low emissions of
N2O cannot be disregarded. In that sense, it is necessary to understand the factors behind N2O production and release to
the atmosphere. In studying N2O production on a laboratory-scale activated sludge process, Schneider et al. (2012)
observed how the availability of nitrite and organic carbon had a direct role in denitrification and hence the formation of
N2O. Their analysis indicated that if an overload of nitrate and organic carbon sources can be avoided, substrates for
denitrification would become limited and consequently lead to decreased production of N2O. Brotto et al. (2015) reached
similar conclusions regarding nitrite accumulation. Similarly, Adouani et al. (2015) investigated N2O emissions in a batch
reactor and observed that temperature is critical for nitrogen abatement, with low temperatures inducing more emissions
of N2O. They, however, point out the necessity of fully understanding the mechanisms behind such phenomena.
Additionally, per capita protein and water consumption also influence N2O formation, given that together they affect the
properties and volume of wastewater being treated (Ramírez-Melgarejo et al. 2019). The 2019 refinement to the IPCC guide-
lines includes two supporting equations to determine the total nitrogen in domestic wastewater, which show that N2O
emissions are function of protein consumption per capita, the fraction of nitrogen in protein, the additional nitrogen from
household products, the portion of nitrogen in non-consumed protein that is disposed in sewers via food waste, the portion
of nitrogen in industrial and commercial co-discharged protein, the fraction of total nitrogen removed during wastewater
treatment and the degree of utilization of the treatment system (Bartram et al. 2019, p. 6.40, 6.42).
Additionally, it is stressed how the 2019 refinement to the IPCC guidelines properly considers emissions from discharges
only when the environment is sufficiently clean and well-oxygenated. In the case of eutrophic or stagnant conditions how-
ever, emissions would be significantly higher than those estimated. Conversely, not only biological processes will
influence emissions, but also operational conditions. Rodriguez-Caballero et al. (2014) analyzed data from aerated and
non-aerated zones in WWTP with activated sludge and concluded that process perturbations such as highly irregular aeration
flow and nitrification instability can affect N2O emission patterns, which provides more evidence to the hypothesis of N2O
formation being strongly related to process design and operation as stated by the IPCC (Bartram et al. 2019).
The potential for CH4 production from WWTPs is highly dependent on the chosen treatment technology and its release to
the atmosphere is related to the place of its occurrence in the treatment process and where it is stripped out to the surface
(Préndez & Lara-González 2008). Rodriguez-Caballero et al. (2014) observed the release of dissolved CH4 during aeration of
inflow and reject wastewater entering the bioreactor. Préndez & Lara-González (2008) estimated that sludge digestion could
account for up to 98% of the emissions in WWTP. Similarly, direct measurements of CH4 emissions from anaerobic sludge
digestion by Daelman et al. (2012) indicated that the emissions could correspond to three-quarters of the total CH4 produced
by WWTP. Besides, Daelman and colleagues bring attention to how digested sludge still has a high potential for producing
residual CH4 during storage, a factor that has been broadly overlooked.
Parravicini et al. (2016) and Daelman et al. (2012) observed how certain conditions can make anaerobic digestors and
anaerobic sludge storage tanks significant sources of CH4 and why controlling such emissions’ sources is paramount.
Measurement of GHG emissions at a Swedish wastewater treatment plant serving 145,000 people indicated large quantities
of CH4 emissions from the storage piles of digested sludge (81,500+ 3,800 kg CH4/year) and that it was the largest source of
CH4 emissions at the entire plant (Gålfalk et al. 2022). Rodriguez-Caballero et al. (2014) indicated the possibility of convert-
ing CH4 before aeration, while Daelman et al. (2012) observed the potential to aerobically oxidize CH4 in the activated sludge
tanks, both aiming at decreasing emissions. Therefore, it becomes clear how CH4 emissions are dependent both on oper-
ational conditions and the system’s configuration. As an example, when comparing anaerobic and aerobic treatment
options for sewage sludge, Parravicini et al. (2016) estimated that the carbon footprint of an activated sludge WWTP
using anaerobic digestion for sludge treatment is close to those using simultaneous aerobic stabilization of sewage sludge
(SAS), resulting in a similar total nitrogen removal while CH4 emissions from sludge stabilization are avoided.
Furthermore, aerators and the circulating flow of dissolved gases in wastewater treatment processes have a great impact on
GHG emissions. The maximum releases of CO2, N2O and CH4 happens in aerobic areas independent of the treatment tech-
nologies used (Yan et al. 2014; Liu et al. 2015). This indicates that dissolved gases in the wastewater together with turbulent
processes play an important role in stripping out GHG to the surface. Parravicini et al. (2016) noticed that activated sludge
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tanks in conventional treatment systems dominate the carbon footprint of WWTPs with moderate nitrogen removal, mainly
due to direct N2O emissions.
3.1.1.4. Use and/or disposal. Turning attention to the end-use and/or disposal functional group, sewer-based wastewatermanagement systems yield two main products: effluent and sludge. Emissions that occur during effluent discharge into
receiving water bodies are important to consider for accurate modelling of the complex processes governing GHG release
into the atmosphere (Koutsou et al. 2018). The quality of effluent, local environmental conditions like temperature
variations and ambient pressure, and various other factors intricately influence these emissions, contributing to
uncertainties in their quantification. For example, the discharge of wastewater increases nutrient concentrations in
recipient waters, leading to eutrophication which enhances the production and release of N2O. The quantities of these
emissions fluctuate significantly between summer and winter seasons (Masuda et al. 2018). The IPCC (Bartram et al.
2019; Hergoualc’h et al. 2019) provides default emission factors for N2O and CH4 emissions, as well as methane
correction factors (MCF), differentiated by effluent discharge pathways such as discharge to aquatic environments and
discharge to soil. The concentration of organic matter and total nitrogen in wastewater effluent significantly influences
CH4 and N2O emissions, respectively. Notably, nitrogen, mainly concentrated in the effluent after treatment, contributes
to N2O emissions when applied to land through irrigation or groundwater recharge, where denitrification of nitrate can
release N2O (Rivett et al. 2008).
Emissions from the discharge of untreated wastewater are also significant sources of CH4 with some studies estimating that
they could be as high as three times the emissions from WWTPs (Giné-Garriga et al. 2022). A recent study based on remote-
sensing data indicated that emissions from untreated wastewater in urban areas could range from 3 to 7 kg CH4/m
3 of
untreated wastewater (Foy et al. 2023). However, there are some uncertainties around these estimates, the processes for
CH4 formation in post-discharge wastewater and about how increasing the proportion of wastewater that is treated could
influence the overall emissions from the sanitation sector. Miller-Robbie et al. (2017) estimated that there would be 32%
less emissions due to the implementation of centralized systems and reduction of untreated wastewater in recipient streams
in growing cities. In contrast, Singh et al. (2017) estimated that the construction of WWTPs for the wastewater that is cur-
rently not treated in India could increase GHG emissions by up to 269%, depending on which treatment technologies are
deployed.
With regards to sludge, studies indicate that CH4 emissions from agricultural land after applying excreta-derived fertilizers
e.g. sewage sludge pellets, composted sewage sludge and digested sludge, are negligible (Ball et al. 2004; Jones et al. 2006).
Most of the GHG emissions when these kinds of excreta-derived fertilizers are applied to land are a result of the release of
N2O, especially in warmer conditions and soils with poor drainage (Brown et al. 2010). Excreta-derived fertilizers, when
applied to land, also contribute to the release of carbon dioxide (CO2), but this is considered to be of biogenic origin and
hence does not contribute to global warming. However, energy related emissions can be generated due to the use of vehicles
and other machinery when applying the fertilizers.
Field experiments in Canada indicated that the average N2O emissions over a 2-year period were much higher for soils
where digested sludge (biosolids) was applied than for soils where composted sludge or alkaline-stabilized sludge was applied.
In one year for example, 6.3% of the total N applied in digested sludge was emitted as N2O, as opposed to 0.24% for alkaline-
stabilized sludge and 0.17% for composted sludge (Obi-Njoku et al. 2022). For comparison, the N2O emissions factor for all
kinds of sludge, wastewater and animal manure in the IPCC guidelines (Hergoualc’h et al. 2019) is 1%, while a review by
Charles et al. (2017) recommends an emissions factor of 1.21+ 0.14% for the same three amendments. However, these
N2O emissions are highly influenced by other factors like the C:N ratio, moisture content, soil texture and climatic factors
like precipitation (Charles et al. 2017).
In some cases, surface disposal or storage is used as an option for sludge management but this is associated with significant
CH4 emissions, mainly due to anaerobic conditions created in the pile of material when it is disposed (Roy et al. 2011;
Majumder et al. 2014; Bora et al. 2020). Significant CH4 emissions are generated when sewage sludge is disposed of at land-
fills, but also when it is placed in temporary storage, as found in a recent study in Sweden where sludge storage at a WWTP
was found to be the single biggest source of CH4 emissions (Gålfalk et al. 2022). In another study, measurements at landfill
sites in Sweden where sludge was disposed indicated that there were significantly higher N2O emissions compared to those
where sludge was not disposed (Börjesson & Svensson 1997). This also suggests that landfilling of excreta-derived waste
streams can also be a significant source of N2O emissions, and not only CH4.
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Sludge from WWTPs can also be used to generate energy through biogas production and via incineration. Incinerating
sewage sludge contributes to significant emissions of N2O, as well as CH4 in some instances (Chen & Kuo 2016; Piippo
et al. 2018). Biogas production through anaerobic digestion and the use of the biogas can also contribute to GHG emissions
through e.g. CH4 leakages and incomplete combustion (Brown et al. 2010). Further details about anaerobic digestion are
described in Section 3.1.4.
3.1.2. System design and configuration
Falk et al. (2013) evaluated five different levels of wastewater treatment according to treatment objectives with technologies
ranging from conventional activated sludge to more advanced tertiary biological and nutrient removal processes, and con-
cluded that GHG emissions linearly increase together with the number of additional facilities and chemical demand.
Besides that, if nitrogen/phosphorus removal processes are included, then emissions increase exponentially. Similarly,
Mamais et al. (2014) concluded that while indirect emissions increase together with the treatment capacity of WWTPs,
direct emissions decrease. However, this does not mean that fugitive emissions are not significant in large-scale treatment
plants. Emissions related to energy and chemical use, for example, can increase at a faster rate depending on the system’s
design, such as features related to removal of pollutants, and the volume of influent wastewater (Gémar et al. 2018).
For treatment processes that include constructed wetlands, Laitinen et al. (2017) highlighted the complexity of the pro-
cesses governing the exchange of gases with the atmosphere, such as the chosen features of the wetland, the vegetation
implemented, seasonal variations, and regional characteristics. The natural cycles of a wetland e.g. nutrient recycling pro-
cesses act as a biomass sink (Machado et al. 2007), possibly avoiding GHG emissions by up to 20% (Laitinen et al. 2017).
Indeed, comparing activated sludge processes, sequencing batch reactors, up-flow anaerobic sludge blanket reactors, and con-
structed wetlands in an Indian context, Kalbar et al. (2013) observed that constructed wetlands have the lowest overall
environmental footprint and even have the potential to mitigate GHG emissions naturally by sequestering atmospheric
carbon. Regarding energy consumption, chemical use, and investments costs, constructed wetlands are two folds better
and can be a viable alternative to conventional WWTP (Laitinen et al. 2017). Similarly, Singh et al. (2017) indicated that oxi-
dation ponds have lower GHG emissions than many otherWWTPs since they require almost no energy input and have low
operation and maintenance requirements. A conventional WWTP has an environmental impact between two and five-fold
higher than a nature-based solution (Garfí et al. 2017).
3.1.3. System operation
Life-cycle assessments frequently quantify indirect emissions, encompassing sources within the construction and operation
phases of wastewater treatment systems. It has been indicated that a significant quantity of GHG emissions result from
energy consumption in the operational phase of centralized sewer-based sanitation systems. For example, Singh & Kansal
(2018) analyzed 35 WWTPs in Delhi and observed that operating the infrastructure accounted for 70% of the total energy
demand for wastewater treatment.
Efficiency in the sanitation system also plays an important role in determining total GHG emissions. From the analysis of
1,079 WWTPs in China, Zeng et al. (2017) concluded that, depending on specific configurations and operational conditions,
emissions could be mitigated by up to 32% if all plants were fully efficient. Large-scale plants often outperform smaller ones in
efficiency, particularly those employing bioreactors or anaerobic–anoxic processes, though tertiary treatment steps may lower
efficiency. Similarly, Molinos-Senante et al. (2014) analyzed 60 WWTPs in Spain and found that maintaining WWTPs in
Spain at full capacity and optimal conditions could directly or indirectly mitigate GHG emissions, potentially reducing
them by 30%. In contrast, if a WWTP does not work properly, it can result in a higher carbon footprint per unit volume
of wastewater treated (Singh & Kansal 2018).
In the 2019 refinement to the IPCC guidelines, centralized aerobic WWTPs are recognized as a possible source of CH4
given the formation of anaerobic pockets in poorly designed or managed facilities (Bartram et al. 2019). However, Noyola
et al. (2018) assert that even well-managed treatment facilities are actual, not just potential, sources of CH4 emissions.
Noyola et al. (2018) do not support the assumption of CH4-neutral plants, and instead propose a standard MCF of 0.06, focus-
ing on intertropical countries. Studying two facilities in Mexico, they also discuss how sewers in such climate zones possibly
produce higher concentrations of CH4. The 2019 refinement to the IPCC guidelines incorporated new MCF to account for
such emissions (Bartram et al. 2019). Although climatic factors significantly affect GHG emissions in sanitation systems,
studies seldom include them as contributing factors in total emissions analyses, particularly in low- and middle-income
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countries. This has been pointed out by several authors such as Chaosakul et al. (2014) with regards to low- and middle-
income countries within the tropics.
Noyola et al. (2018) further observed large amounts of CH4 emissions from two municipal Mexican WWTPs, indicating
their poor operational conditions. However, by assuming full WWTP efficiency, national inventories in Mexico likely under-
estimate CH4 emissions, a situation that may be common worldwide. A similar picture can be observed for N2O accounting.
Brotto et al. (2015) reported higher emission factors for full-scale activated sludge plants in Brazil than recent values observed
in international inventories. The deviation is linked to variations in temperature. Furthermore, malfunctioning plants were
linked to higher N2O emissions, underscoring the need for improved efficiency as a means to control GHG emissions in simi-
lar contexts.
However, some studies have indicated that GHG emissions from the operation of wastewater treatment facilities (i.e. elec-
tricity and fuels to run the operations and equipment) could be much lower than the direct emissions of CH4 and N2O from
the treatment processes in some cases. In Kampala for example, the direct emissions from wastewater treatment were esti-
mated at 29,629 tonnes CO2-eq annually, while operational emissions were only 2,950 tonnes CO2-eq annually (Johnson
et al. 2022). The ratio of operational to direct fugitive GHG emissions from wastewater treatment hinges on the treatment
technologies’ energy intensity, the required chemical inputs, and the carbon footprint of the local or national energy mix.
3.1.4. Energy consumption and energy recovery
Although CH4 emissions contribute significantly to higher GWP in centralized WWTPs, biogas production and use at
WWTPs often meet up to 40–60% of energy requirements (Daelman et al. 2013; Singh & Kansal 2018). Biogas production
and use has been found to possibly reduce GHG emissions by around 5% to 12% according to Singh & Kansal (2018) and
Lahmouri et al. (2019), respectively. Daelman et al. (2012) also estimated that additional biogas valorization from residual
CH4 in storage tanks could further decrease CH4 emissions from a WWTP by around 22% to 48%.
However, leakages of CH4 from anaerobic digestion and biogas valorization processes can significantly diminish the GHG
reduction potential of biogas-based energy recovery (Daelman et al. 2013). For example, Koutsou et al. (2018) analyzed data
from 128 WWTPs in Greece and concluded that biogas use was the biggest contributor to CH4 emissions, after sludge dis-
posal to landfills. A study using ground-based remote-sensing methods identified previously unknown leakages of large
quantities of CH4 from biogas production facilities at a wastewater treatment plant in Sweden (Gålfalk et al. 2022). According
to Noyola et al. (2018), around 8% of the captured CH4 from anaerobic sludge digesters at WWTPs can end up in the atmos-
phere due to leakages. Therefore, it can be observed that while biogas production at a WWTP can reduce the need for
external energy sources significantly, fulfilling 40–60% of the internal demand (Daelman et al. 2013; Singh & Kansal
2018), in some circumstances it offers no benefits regarding GHG mitigation due to methane leakages (Daelman et al. 2012).
3.2. Non-sewered sanitation systems
Non-sewered sanitation systems include on-site sanitation technologies like pit latrines, septic tanks, CBS, composting toilets
etc, as well as the infrastructure for managing and treating the waste streams emanating from these technologies. They are
mostly used in low- and middle-income countries, but significant portions of the population in high-income countries also
use non-sewered sanitation systems including 12% to 15% of the population in some Nordic countries (Laukka et al.
2022) and a fifth of the population in the USA and the European Economic Area in general (Somlai et al. 2019). In some
areas of the world where open defecation is still prevalent, non-sewered sanitation systems are seen as an ideal intervention.
While open defecation has minimal contribution to GHG emissions compared to improved sanitation solutions, its elimin-
ation is a necessity for human dignity, public health and well-being (Shaw et al. 2021).
Field-based measurements of GHG emissions from non-sewered sanitation remain relatively sparse (Ryals et al. 2019;
Poudel et al. 2023). This is despite the fact that some studies have indicated that non-sewered sanitation systems might
have a relatively higher contributions to GHG emissions e.g. in the USA where septic tanks are estimated to contribute to
about 65% of GHG emissions from sanitation systems even though they account for only a quarter of the wastewater treat-
ment capacity in the country (US EPA 2012).
3.2.1. Emission sources across non-sewered sanitation systems
3.2.1.1. User interface. Just like the case of sewer-based sanitation systems, the user interface functional group has not
received much attention in the literature on GHG emissions accounting within non-sewered sanitation technologies,
except for emissions related to the use of waterfor toilet flushing where applicable (as in Section 3.1.1.1).
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3.2.1.2. Containment and storage/treatment. Most research on GHG emissions from non-sewered sanitation technologies
focuses on the containment and storage functional group, i.e. pit latrines, septic tanks, and CBS, as described in Sections
3.2.2–3.2.4. There are other technologies within this functional group such as composting toilets, dehydration vaults and
biogas toilets (see Tilley et al. 2014, pp. 56–81), but there seems to be no studies quantifying their GHG emissions. This is
also reflected in the IPCC guidelines which only include emission factors for septic tanks and four pit latrines types
(Doorn et al. 2006).
3.2.1.3. Conveyance. With regards to the conveyance functional group, no literature was found with data on fugitive
emissions from the transportation of faecal sludge or other excreta-derived waste streams within jerrycans or containers,
as well as manual or motorized emptying and transport options, although the motorized options come with indirect
transport-related emissions. Recent studies based on modelling have considered these emissions to be negligible due to the
relatively short time that faecal sludge spends during transportation processes in comparison to the containment and
treatment processes (Johnson et al. 2022). For transfer stations, the emissions could likely be similar to those from
containment or storage depending on the presence of anaerobic conditions and the residence time of the excreta under
those conditions.
3.2.1.4. (Semi-) centralized treatment. With regards to the treatment functional group, there are some overlaps between non-
sewered sanitation systems and sewer-based sanitation systems as far as emissions sources are concerned. In many instances
where faecal sludge in pit latrines and septic tanks is not emptied, then treatment occurs in the containment and storage
phase in which case the emissions are as described in Sections 3.2.2–3.2.4. In some instances however, faecal sludge is
emptied and transported to decentralized or centralized facilities for treatment as shown in Figure 1 – System C (see also
Strande et al. 2014). Depending on the technology configuration and environmental conditions, the GHG emissions from
these facilities can be governed by similar mechanisms to those in treatment technologies within sewer-based sanitation
systems, with anaerobic conditions facilitating CH4 emissions while biological treatment and nutrient removal processes
facilitate N2O emissions (see Section 3.1.1.3).
3.2.1.5. Use and/or disposal. Non-sewered sanitation systems produce liquid products, including effluent, urine, and
digestate, as well as semi-solid products like compost, sludge and pit humus. The mechanisms influencing GHG emissions
from effluent and digestate disposal in non-sewered sanitation systems are similar to those in centralized sewer-based
systems (see Section 3.1.1.4). This also includes instances where sludge from pit latrines or septic tanks is released
untreated into urban drains or other surface waters. In the USA, studies suggest that leach fields and drainage fields for
septic tank effluent are significant sources of N2O emissions (Leverenz et al. 2010; Truhlar et al. 2016), due to the
nitrification and denitrification processes that occur in the soil where the effluent is dispersed. In contrast, non-sewered
sanitation technologies that dispose of effluent in soak pits mainly emit CO2 and CH4, as observed in Irish field
investigations (Somlai-Haase et al. 2017; Somlai et al. 2019), likely due to the presence of anaerobic conditions in the
soak pit. The CO2 is deemed to be biogenic.
With regards to urine, negligible amounts of CH4 are released when urine is applied to soil (Tidåker et al. 2007). There are
relatively few experimental studies about N2O emissions from fields where urine or urine-derived fertilizers have been applied
(Martin et al. 2020). An incubation study in Denmark indicated that N2O emissions were lower for urine-applied soil than
from that where mineral fertilizers had been applied (Gómez-Muñoz et al. 2017), while a pot experiment in Germany indi-
cated higher N2O emission rates for urine than for mineral fertilizers (Simons 2008). LCA studies involving the application of
stored urine and urine-derived fertilizers on agricultural land indicate that the majority of the GWP impact arises from N2O
emissions after spreading on land (Spångberg et al. 2014; Medeiros et al. 2020; Martin et al. 2023). These N2O emissions are
partly resulting from a portion of the total nitrogen added to soil that is later emitted into air, and partly from ammonia-nitro-
gen that is emitted into air through volatilization (Eggleston et al. 2006). Mineral fertilizers, when applied to agricultural land,
also release large amounts of N2O due to the action of soil micro-organisms breaking down excess nitrogen that is not
absorbed by plants. Unlike urine-derived or organic fertilizers however, mineral fertilizers also have significant emissions
released from their extraction, production and distribution chains (Walling & Vaneeckhaute 2020).
Solid or semi-solid products like compost, dehydrated faeces, sludge, and insect frass, applied to arable land, have GHG
emissions mechanisms similar to sewage sludge from centralized sewer systems (see Section 3.1.1.4). Incubation experiments
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with black soldier fly frass as an organic amendment to arable soil indicate significant N2O and CH4 emissions, especially
immediately after application of the amendment (Rummel et al. 2021). However, more extensive field-based studies are
yet to be done to determine the extent of emissions from BSF frass resulting from larvae fed on human excreta-derived
feedstock.
3.2.2. Pit latrines
Pit latrines are used by approximately 1.6 billion people globally (Cheng et al. 2022). Lutkin et al. (2022) estimated that pit
latrines globally contribute about 42 million tonnes of CO2-eq/year while Reid et al. (2014) estimated that they are responsible
for about 3.8 million tonnes of CH4 emissions annually. Pit latrines can also be significant sources of N2O emissions, depend-
ing on the presence of nitrate to facilitate denitrification (Doorn & Liles 1999; Poudel et al. 2023). Pit latrine design and
construction typically promote anaerobic degradation of excreta, facilitating GHG production in the pit. Analyzing samples
from 45 different pits in Tanzania, Van Eekert et al. (2019) identified anaerobic digestion as the main pathway for organic
degradation in pit latrines, with biogas production being observed in 73% of the pits within 40 days, although Bourgault
et al. (2019) contend that there is a significant extent of aerobic decomposition. Van Eekert et al. (2019) also identified
higher moisture content as a crucial factor for increasing anaerobic digestion and hence CH4 production. This indicates
the influence of the characteristics of the faecal sludge in pit latrines which is determined by factors like whether greywater
is also disposed of in the pit. Moreover, it aligns with modelling results from Trimmer et al. (2020) which suggest that fugitive
emissions from pit latrines with 50% anaerobic conditions can contribute to between 6 and 22% of the total per capita emis-
sions in Kampala. If the latrines are further submerged due to water table rise, direct emissions may increase by 58%
(Trimmer et al. 2020).
Besides aeration status, temperature variations and the number of users are important factors of estimating pit latrine GHG
emissions. Trimmer et al. (2020) conducted a detailedanalysis of how single-household facilities can reduce CH4 emissions
through improved management practices. They also estimated that the widespread construction of pit latrines for households
without access to improved sanitation worldwide could lead to an increase in emissions of up to 34%. The trade-offs between
improving access to basic sanitation and reducing GHG emissions raise concerns regarding the use of pit latrines to close the
sanitation gap instead of employing other technologies. This is because a drastic increase in the number and use of pit latrines
would more than double the GHG emissions contributions from this source, currently estimated around 0.3% of the global
emission according to the experimental measurements of Van Eekert et al. (2019). Based on these considerations, a crucial
challenge in climate mitigation within the sanitation chain is addressing the significant source of CH4 emissions represented
by pit latrines. However, there is potential for reducing GHG emissions from pit latrines by promptly and routinely emptying
the pits (Johnson et al. 2022), and directing the collected sludge to anaerobic treatment facilities (Trimmer et al. 2020).
3.2.3. Septic tanks
About 1.7 billion people use septic tanks globally (Cheng et al. 2022). This prevalence is primarily in low- and middle-income
countries, though significant usage is also observed in high-income countries, including about 20% of the USA population
(Diaz-Valbuena et al. 2011). Estimates by Lutkin et al. (2022) suggest that septic tanks globally contribute about 210 million
tonnes of CO2-eq annually.
GHG emission rates from septic tanks are influenced by their design and the components to which they are connected.
Diaz-Valbuena et al. (2011) measured GHG emissions from different compartments of septic tanks in the USA and found
that they varied significantly, suggesting that the number of compartments affects the overall emissions. Moreover, the dis-
charge of septic tank effluent to leach fields, soak pits, or sewers affects emissions, as varying biogeochemical processes
occur in the soil or water. Leverenz et al. (2010) and Truhlar et al. (2016) showed that nitrification and denitrification in
the soil after effluent dispersal contribute to N2O and CO2 emissions. Huynh et al. (2021) studied septic tanks in Hanoi, Viet-
nam that discharged their effluent to the sewerage network, which then released most of it to water bodies. While direct
discharge emissions were not measured, other studies have documented high N2O emissions from wastewater effluent enter-
ing surface water bodies (Kampschreur et al. 2009; Wang et al. 2022).
With regards to emissions sources from septic tanks, Leverenz et al. (2010) conducted experiments on eight septic tank
systems in the USA and indicated that CH4 emissions come mainly from the septic tank while CO2 and N2O emissions orig-
inate mainly from the soil dispersal system due to nitrification and denitrification of the effluent as it disperses. This is in
agreement with Truhlar et al. (2016) whose experiments on septic tanks in New York indicated that N2O emissions
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mainly originated from the leach field and the roof vent, as well as Huynh et al. (2021) whose measurements on septic tanks
in Vietnam indicated that N2O emissions from the first compartment of the septic tank were negligible compared to CH4 and
CO2 emissions. In septic tanks, CH4 emissions arise from anaerobic reactions in the sludge layer, whereas CO2 emissions
stem from anaerobic, facultative, and aerobic reactions within the tank. Higher temperatures and influent loading rates
tended to result in higher CH4 emissions from septic tanks. However, no correlation was found between the thickness of
scum layers in septic tanks and the rates of CH4 emissions according to Diaz-Valbuena et al. (2011). Leverenz et al.
(2010) also indicated that septic tank installations linked to soft water supply tend to result in higher CO2 fluxes. In contrast
to the IPCC which indicates a MCF of 0.5, Diaz-Valbuena et al. (2011) suggest a MCF of 0.22 based on results from their field
measurements.
Characterization of waste is another important factor that influences GHG emissions from septic tanks. If influent waste-
water to septic tanks contains sulphate compounds, then hydrogen sulphide can also be released in septic tanks according to
Leverenz et al. (2010). Diaz-Valbuena et al. (2011) suggest that other factors such as COD loading and their variability may
have more influence over CH4 emission rates in septic tanks compared to temperature of the influent wastewater. Septic
tanks in some areas in low- and middle-income countries receive only black water since greywater is commonly discharged
into open drains. This implies that the influent wastewater has lower organic loading rates, compared to septic tanks in high-
income countries which receive black water, greywater and even food waste from macerator in sinks. Considering that
anaerobic processes primarily decompose organic pollutants in septic tanks, the variations in influent wastewater compo-
sition may account for the observed differences in GHG emissions across studies in the USA (Leverenz et al. 2010; Diaz-
Valbuena et al. 2011; Truhlar et al. 2016) and Ireland (Somlai et al. 2019) in comparison to Vietnam (Huynh et al. 2021).
How septic tanks are operated throughout the seasons also plays a significant role in determining GHG emissions, given
that microbial activity in a septic tank varies over the seasons, especially in places with significant seasonal temperature vari-
ations. During the spring and early summer, increasing temperatures result in an increase in microbial activity in the sludge
layer of septic tanks, which leads to more gas production according to Leverenz et al. (2010). The solubility of the gases also
decreases and hence results in higher gas release. Furthermore, septic tanks that have been de-sludged tend to have an
initiation period before production of CH4 and CO2 fully resumes according to Diaz-Valbuena et al. (2011). Huynh et al.
(2021) and Moonkawin et al. (2023) found that septic tanks with longer de-sludging intervals had higher CH4 emission
rates, which is consistent with the findings of Johnson et al. (2022) in Kampala. They also expected that the tropical temp-
eratures in Vietnam would increase the emissions from septic tanks compared to colder climates in high-income countries
of the Global North. However, they did not observe a significant influence of influent temperature on emission rates,
which is similar to the results of Leverenz et al. (2010) in the USA. They suggested that this could be due to the low variability
of influent temperature in their study. Furthermore, they reported that the septic tanks had low treatment efficiency and pro-
duced effluent with high concentrations of organic pollutants, which could lead to more GHG emissions in the post-
treatment components of the septic tank system. This demonstrates the importance of effective treatment and the influence
that it can have on GHG emissions from septic tanks. Addressing the often-ineffective performance of on-site treatment tech-
nologies in many low- and middle-income countries, as discussed by Strande et al. (2014), is therefore essential for climate
mitigation efforts.
3.2.4. Container-based sanitation
CBS systems are made of sealed, waterless, and portable containers that capture human excreta. Once filled, they are replaced
with clean containers, and the filled ones are taken for treatment, such as thermophilic composting, and resource recovery
(Russel et al. 2019). CBS is considered as an integrated solution for meeting the sanitation gap in some contexts of low- and
middle-income countries. In CBS, human excreta stays on-site for a limitedperiod and in a confined impermeable container.
Therefore, fugitive emissions are reduced, nutrient leaching in soil is avoided, and the potential for nutrient recovery is
increased (Trimmer et al. 2020). In contrast, using a large container for a longer period could favor anaerobic conditions
and consequently increase GHG emissions (Johnson et al. 2022).
Moreover, off-site composting of excreta also emits GHG where the intensity depends on operational decisions, such as
turning of compost piles and the permeability of the pile lining-material. Research by Ryals et al. (2019) in Haiti indicated
a three-fold reduction of N2O and a four-fold reduction of CH4 emissions when using permeable soil lining instead of
cement lining for compost piles of excreta from CBS. Conversely, pile turning doubled NO2 and CO2 emissions while
nearly eliminating CH4 production (Ryals et al. 2019). McNicol et al. (2020) observed that CBS along with composting of
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the excreta presents lower CH4 and higher NO2 emissions overall than systems such as pit latrines, and considerably smaller
GWP than other sanitation solutions typically used in the Global South.
Considering the full cycle of sanitation services, CBS along with off-site composting have the potential to mitigate up to
92% of the sanitation-related emissions for the global population living in slums, mainly by reducing up to 99% of CH4 emis-
sions compared to the emission levels from typical pit latrines and similar sanitation technologies used by this demographic
(McNicol et al. 2020). Consequently, implementing CBS alone for 1 billion slum residents could mitigate between 13 and 44%
of the CH4 emissions from the global sanitation sector. However, uncertainties remain due to the paucity of emissions data
from composting excreta in diverse geographical contexts, despite composting’s reliance on aerobic processes that primarily
produce climate-neutral CO2 emissions (McNicol et al. 2020). Also, few studies have quantified the flows and transformation
of organic compounds within non-sewered technologies (Lourenço & Nunes 2020). This raises questions about the actual
fraction of possible non-biogenic carbon in these non-sewered sanitation systems, and how this could be accounted for in
CBS more specifically.
Furthermore, not all CBS toilets currently include urine collection due to higher costs of conveyance and treatment (Russel
et al. 2019). This complexity affects how emissions from urine management, disposal, and waste transportation might negate
anticipated mitigation benefits (Reid 2020). Transportation and conveyance are usually a significant source of indirect emis-
sions from non-sewered sanitation in some contexts (Lehtoranta et al. 2013), even though they may be relatively low in
comparison with fugitive emissions from faecal sludge management systems (Johnson et al. 2022). Anastasopoulou et al.
(2018) compared sanitation systems in South Africa and concluded that for both urine-diverting dry toilets (UDDTs) and
pour-flush toilets, transportation was among the biggest contributors to the overall climate impact of these technologies.
3.2.5. Energy consumption and resource recovery in non-sewered sanitation systems
To mitigate the climate impacts of sanitation systems, non-sewered sanitation systems that are dry and controlled offer a
promising alternative to conventional centralized systems that consume more energy and resources (Lourenço & Nunes
2020). Several studies have compared different scenarios of sanitation systems and their contributions to GHG emissions
and resource recovery. For instance, Prado et al. (2020) found that centralized systems had higher overall climate impacts
due to their higher energy consumption. Zhou et al. (2010), compared scenarios from traditional centralized treatment to
decentralized ecological sanitation (EcoSan) systems, noting that EcoSan systems emit fewer GHGs due to lower gasoline
and electricity consumption. Xue et al. (2016) demonstrated that dry composting toilets when used along with septic
tanks for greywater treatment were less energy intensive than centralized sewer-based systems.
The context and configuration of the system also influences the energy consumption and GHG emissions. Remy & Jekel
(2008), noted that, in small urban settlements in Germany, source-separating systems with composting might require similar
or greater energy due to the construction of parallel pipe networks and associated greywater treatment, compared to conven-
tional combined-flow sewer networks with centralized treatment. However, they could also reduce GHG emissions by 15% to
30% compared to activated sludge treatment. Fan et al. (2017), observed that waterless urinals and vacuum source-separation
toilets had 73% lower climate impact than conventional systems in China, mainly due to their capacity for resource recovery.
Additionally, by analyzing four different scenarios of sanitation systems in Tanzania, Krause & Rotter (2017) concluded that
by implementing UDDTs, emissions could be significantly reduced in comparison to pit latrines and septic tanks, while reach-
ing higher levels of carbon, nitrogen, and phosphorus recovery. UDDT systems had up to 55% lower GHG emissions than pit
latrines and even much lower than septic tanks. Pit latrines had higher carbon recovery potential than septic tanks, but this
was not realized as sludge was often left in the ground. Therefore, dry controlled systems can present lower GHG production
at different stages of the sanitation chain by being less resource-intensive or promoting higher resource recovery (Reid et al.
2014; Lourenço & Nunes 2020).
4. DISCUSSION
4.1. Empirical measurements of GHG emissions versus model-based emissions quantification
While most studies identified in this review have predominantly emphasized sewer-based sanitation and WWTPs, non-sew-
ered sanitation systems exhibit a paucity of empirical investigations. While some studies have focused on pit latrines, septic
tanks, and CBS, a broader understanding of other non-sewered technologies like composting toilets, biogas toilets, and fossa
alternae, their GHG footprint, and emissions variability across geographical contexts is crucial. Knowledge gaps about these
other types of non-sewered technologies impedes the effective translation of findings from experimental studies into
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comprehensive model-based studies, as regional variations in environmental factors such as climatic conditions and seasonal
temperature variations, water table depth and soil drainage properties are possibly overlooked. As a corollary, the emphasis
on WWTPs within experimental studies engenders model-based studies that are skewed towards these systems, leaving a criti-
cal void in the representation of emissions from non-sewered sanitation across diverse locations. There are ongoing efforts
through research projects like SCARE (University of Bristol 2023), but these are still insufficient to cover the wide variety
of non-sewered sanitation technologies and systems spread across the globe. Given the extensive use of non-sewered sani-
tation globally, significant investment in research to address these gaps is imperative for a robust empirical foundation in
emissions modelling. Innovative approaches to indirectly measure emissions, such as assessment of seasonal changes in
groundwater to account for the changing inundation of pit latrines and associated CH4 emissions, can also play a role in
low-income regions where there are limited resources for monitoring, but still rely on empirical data for validation (Reddy
et al. 2022).