ABSTRACT
Environmental challenges in low-income countries, such as Haiti, persist due to inadequate sanitation infrastructure. This study assesses the environmental impacts of nine on-site sanitation systems to identify those with the least environmental impacts and explore improvement options. Nine scenarios were developed, each representing different systems for managing 1 ton of fecal sludge over 1 year. The ‘Impact World + ’ and ‘IPCC 2013 GWP 100a’ methods evaluated impacts on ecosystems, human health, and climate change. Data sources included interviews, weighing records, and scientific publications. Results show that Scenario 8 (Flush Toilet – Evacuation – Planted Drying Beds) is most impactful on health (1.17 × 10−2 DALY), while Scenario 1 (Composting Toilet – Evacuation – Unplanted Drying Beds) is least impactful (1.77 × 10−3 DALY). For ecosystem impacts, Scenario 2 (Container-based Toilet – Evacuation – Planted Drying Beds) is most impactful (3.81 × 103 PDF·m2·year), while Scenario 6 (VIP latrine – Evacuation – Lagoons) is least impactful (3.52 × 103 PDF·m2·year). Key hotspots include toilet paper, wood shavings, GHG emissions, and water use. The study recommends an integrated approach combining environmental life cycle assessment (LCA) with life cycle cost assessment and social LCA for sustainable decision-making on sanitation systems in low-income countries.
HIGHLIGHTS
This study evaluates the entire on-site sanitation system, including toilet access, sludge emptying and evacuation, and treatment via lagoons or drying beds (planted or unplanted).
Unlike earlier studies that focused primarily on fecal sludge treatment technologies, this research assesses potential health and environmental impacts across the complete sanitation chain, from initial access to final treatment (of sludge).
INTRODUCTION
Low-income countries frequently face sanitary and environmental challenges, one of the most concerning being fecal pollution (Hyun et al. 2019). The multiple health and environmental issues resulting from this pollution have been documented in the scientific literature (Mara 2004; Strande et al. 2014; Odey et al. 2017; Jean-Baptiste et al. 2023). This situation often stems from the lack of adequate sanitation infrastructure to manage blackwater or human excreta.
Low-income countries have often attempted to replicate the conventional sanitation systems employed in developed countries (Aguilar et al. 2014; Jha & Bajracharya 2014; Egloso et al. 2015; Mng'ombe et al. 2023), without considering that their socio-economic and geoclimatic contexts generally differ from those of developed countries. Indeed, these countries often do not have the same level of sanitation infrastructure, frequently face water availability constraints, and, in most cases, they have a tropical climate (Koottatep et al. 2005; Bouquet 2013). Consequently, the conventional sanitation system used in developed countries is not necessarily adapted to low-income tropical countries. This situation suggests that these countries should instead develop their own sanitation systems, capitalizing on the advantages that the tropical climate offers in terms of drying, stabilization, and hygienization of fecal sludge. These climatic advantages are, moreover, widely demonstrated in the literature (Koottatep et al. 2005; Strande et al. 2014; Pocock et al. 2022; Samal et al. 2022; Sorrenti et al. 2022).
Extensive sanitation technologies, which mimic natural sanitation processes, could prove beneficial for low-income countries due to their generally low cost, low energy and water consumption, and adaptation to tropical regions (Sasse 1998; Monvois et al. 2010; Uggetti et al. 2011; Strande et al. 2014; Tilley et al. 2016). Currently, three sanitation technologies stand out: lagoons, unplanted drying beds (UDBs), and planted drying beds (PDBs). However, from these three sanitation technologies, it is essential to objectively identify the one most suited to the environmental context of low-income countries, as well as those that can be improved.
Life cycle assessment (LCA), as a multicriteria environmental assessment method (Jolliet et al. 2015), is the most appropriate tool to address this question. LCA allows the identification of the stages, activities, and materials responsible for the environmental impact of a system or product throughout its life cycle, from the extraction of raw materials necessary for its manufacture to its end-of-life management (Jolliet et al. 2015, 2017). As an ecodesign tool, it also facilitates the identification of improvement levers by highlighting critical variables.
Despite the numerous scientific studies devoted to the LCA of sludge treatment processes, no research has been reported in the scientific literature on the LCA of complete on-site sanitation systems, including downstream treatment by lagoons or drying beds, whether planted or unplanted. Existing studies focus primarily on fecal sludge treatment technologies, representing the final link in an on-site sanitation system. A study conducted in Brazil by Moni Silva et al. (2023) investigated the potential environmental impacts of three scenarios for the treatment of sludge from UDBs, namely landfilling, anaerobic digestion, and incineration. The results showed that the use of sludge to produce energy through anaerobic digestion can reduce environmental impacts, although greenhouse gas (GHG) emissions and heavy metals must be considered.
In Spain, Uggetti et al. (2011) compared four sludge treatment scenarios: (S1) drying reed beds followed by biosolids application in fields, (S2) drying reed beds followed by biosolids composting, (S3) centrifugation followed by composting, and (S4) treatment in a conventional wastewater treatment plant (activated sludge). The scenario of drying reed beds followed by biosolids land application (S1) was identified as the least environmentally impactful and most economically beneficial for the following reasons: (i) it does not require transporting sludge to a post-treatment site, thus eliminating transportation-related impacts, (ii) it does not require additional treatment such as composting, avoiding impacts associated with these additional processes, (iii) the raw materials required for the construction of the system in question are responsible for most of the impact in this scenario, but this impact remains low compared to other scenarios involving transportation, and (iv) the contribution to impacts from direct GHG emissions as well as indirect emissions related to energy consumption and transportation is minor compared to other scenarios.
Other studies have compared lagoons to conventional sanitation systems. In a study conducted in Iran, Mohammadi & Fataei (2019) compared a lagoon system with an activated sludge plant. They concluded that the lagoon system was more impactful overall than activated sludge, mainly due to significantly higher methane (CH4) production (29,090 kg/day versus 7,527 kg/day for activated sludge) and its lower performance in terms of reducing levels of nitrogen and phosphorus, which are responsible for water eutrophication. In contrast, Thompson et al. (2022) in Nebraska (USA) found opposite results, concluding that the lagoon system is less impactful because it requires less operational energy and leads to fewer emissions into water and air. These divergences can be attributed to differences in the environmental indicators studied.
Finally, Flores et al. (2019) compared drying reed beds to activated sludge systems in Spain, demonstrating that drying reed beds are less harmful to the environment due to the avoidance of wastewater and sludge transportation, as they are treated on-site, as well as reduced electricity and chemical consumption, compared to the activated sludge system.
These studies highlight the need for further research to more comprehensively assess the LCA of autonomous sanitation systems, considering the three components in the system: access to toilets, fecal sludge evacuation, and fecal sludge treatment. This is particularly crucial for systems integrating lagoons or drying bed links in order to better understand the factors influencing their environmental performance. The present study aims to fill these gaps in the scientific literature by providing new data on the LCA of sanitation systems used in low-income tropical countries.
METHODOLOGY
Geophysical framework of the study
The Republic of Haiti occupies the western portion of the island of Hispaniola, which it shares with the Dominican Republic (World Population Review 2024). Situated in the Caribbean basin at approximate geographical coordinates of 19°00′N and 72°25′W, Haiti is characterized by a tropical climate (Singh & Cohen 2014; World Population Review 2024). The climate is generally warm and humid, with variations depending on altitude (World Bank 2021). The mean annual temperature ranges between 24 and 27 °C (Jean-Baptiste 2019).
The average annual precipitation for the period 1981–2020 was 118 cm, with a value of 115.3 cm recorded in 2020 (UNDP 2021). The mean potential evapotranspiration for the same period amounted to 155.9 cm per annum, reaching 158 cm in 2020 (UNDP 2021). This evapotranspiration exceeding precipitation indicates a generally arid climate. Haiti is a mountainous country, with 60% of its area presenting slopes greater than 20% (Pierre 2020). The country is frequently exposed to natural disasters such as hurricanes, floods, and earthquakes, phenomena exacerbated by extensive deforestation (Singh & Cohen 2014; Pierre 2020; Preux 2022).
Objective and scope of the study
The main objective of this study is to compare, through LCA, the autonomous sanitation systems used in low-income tropical countries such as Haiti (a tropical climate country), focusing on the following on-site sanitation technologies as downstream links: PDB, UDB, and lagoons. This analysis is part of a broader research project aimed at identifying sanitation technologies and systems with the least environmental impact, while considering the socio-economic and climatic context of low-income countries, particularly Haiti. Furthermore, this study will pinpoint opportunities for improving the examined sanitation systems. This study is addressed to policymakers, donors funding sanitation projects in developing countries, as well as academics and researchers interested in the issue of on-site sanitation.
Description of the systems studied
As indicated in the introduction of the study, each studied system consists of three distinct links. Data related to the ‘toilet’ and ‘fecal sludge evacuation’ links are detailed by Jean-Baptiste & Monette (2024). Therefore, this section focuses on the description of the technologies comprising the ‘sludge treatment’ link.
Unplanted drying bed
Planted drying bed
Lagoon systems
Function and functional unit
The primary function of the studied sanitation systems is to treat human excreta in order to preserve the environment and human health from potential contamination and nuisances generated by these sludges. Furthermore, these systems fulfill a secondary function by producing biosolids (dried sludge) that can be used as fertilizer in agriculture. The functional unit chosen for this study is the management of 1 ton of fecal sludge (wet basis) over 1 year in Haiti.
The analyzed fecal sludges exhibit the following characteristics, in accordance with Jean-Baptiste & Monette (2024): (i) 23.4% dry solids (DS), equivalent to 234 kg of dry solids per ton (sludges from composting toilets contain 40.0% DS due to the addition of litter), (ii) 25.5 kg/t of total nitrogen, (iii) 3.68 kg/t of total phosphorus, (iv) 8.00 kg/t of potassium, and (v) a chemical oxygen demand (COD) of 635 kg/t. These data are based on the average of information provided by Strande et al. (2014) and Andriani et al. (2015). Information regarding annual feces production per person comes from the study by Jean et al. (2017), which estimates that a Haitian produces an average of between 120 and 130 g of feces (wet mass) per day. Thus, an average of 125 g of feces per person per day was used.
Scenarios considered
The studied system consists of the three links of on-site sanitation: toilet, evacuation, and sludge treatment. To achieve the objectives of the study, nine sanitation system scenarios were developed in accordance with these three links, which are listed in Table 1. Scenario 6 (VIP latrine – Evacuation – Lagoon) corresponds to the system most widely used in urban areas with a sludge treatment plant in Haiti, followed by Scenario 9 (Flush toilet – Evacuation – Lagoon), which is primarily used in relatively affluent areas.
Scenario . | First component . | Second component . | Third component . |
---|---|---|---|
Scenario 1 | Container-based toilet (CBT) | Evacuation | Unplanted drying bed (UDB) |
Scenario 2 | Planted drying bed (PDB) | ||
Scenario 3 | Lagoon | ||
Scenario 4 | Ventilated improved pit (VIP) latrine | Unplanted drying bed | |
Scenario 5 | Planted drying bed | ||
Scenario 6 | Lagoon | ||
Scenario 7 | Flush toilet (W.C.) | Unplanted drying bed | |
Scenario 8 | Planted drying bed | ||
Scenario 9 | Lagoon |
Scenario . | First component . | Second component . | Third component . |
---|---|---|---|
Scenario 1 | Container-based toilet (CBT) | Evacuation | Unplanted drying bed (UDB) |
Scenario 2 | Planted drying bed (PDB) | ||
Scenario 3 | Lagoon | ||
Scenario 4 | Ventilated improved pit (VIP) latrine | Unplanted drying bed | |
Scenario 5 | Planted drying bed | ||
Scenario 6 | Lagoon | ||
Scenario 7 | Flush toilet (W.C.) | Unplanted drying bed | |
Scenario 8 | Planted drying bed | ||
Scenario 9 | Lagoon |
System boundaries and impact assessment methods
Life cycle inventory assessment
The necessary data for modeling the systems studied were collected using a life cycle inventory (LCI) in accordance with ISO 14040 (2006). In this process, the ecoinvent database version 3.7, integrated into the OpenLCA application version 1.11.0, was utilized for background data. The data sources collected during this inventory and the quality of these data are referenced in Table 2. The data quality was assessed according to the criteria of Weidema et al. (2013) and Bicalho et al. (2017). These criteria are defined in Supplementary data, Table SD-12.
Types of data . | Data quality . | References . |
---|---|---|
Container-based toilet (CBT) | Good quality (1, 4, 5, 1, 1) | Julien Boyer, manager of Lécopot, manufacturer of CBT (Fabulous toilettes 2016) |
VIP latrine | Good quality (2, 4, 5, 3, 1) | (Mara 1984; DINEPA et al. 2013; Tilley et al. 2016) |
Flush toilet (W.C.) | Good quality (1, 4, 5, 1, 2) | Direct measurements |
Gulper pump | Good quality (3, 4, 4, 2, 1) | (Strande et al. (2014); Gabert et al. 2018) |
Fecal sludge | Good quality (2, 2, 5, 1, 1) | (Strande et al. (2014); Andriani et al. 2015) |
Sewage truck | Good quality (1, 2, 5, 2, 3) | Ecoinvent version 3.7 |
Planted drying bed (PDB) | Good quality (2, 3, 4, 1, 2) | EAWAG – SANDEC |
Unplanted drying bed (UDB) | Good quality (2, 3, 4, 1, 2) | EAWAG – SANDEC |
Lagoon | Good quality (2, 3, 3, 1, 2) | Adapted from Thompson et al. (2022)) |
Types of data . | Data quality . | References . |
---|---|---|
Container-based toilet (CBT) | Good quality (1, 4, 5, 1, 1) | Julien Boyer, manager of Lécopot, manufacturer of CBT (Fabulous toilettes 2016) |
VIP latrine | Good quality (2, 4, 5, 3, 1) | (Mara 1984; DINEPA et al. 2013; Tilley et al. 2016) |
Flush toilet (W.C.) | Good quality (1, 4, 5, 1, 2) | Direct measurements |
Gulper pump | Good quality (3, 4, 4, 2, 1) | (Strande et al. (2014); Gabert et al. 2018) |
Fecal sludge | Good quality (2, 2, 5, 1, 1) | (Strande et al. (2014); Andriani et al. 2015) |
Sewage truck | Good quality (1, 2, 5, 2, 3) | Ecoinvent version 3.7 |
Planted drying bed (PDB) | Good quality (2, 3, 4, 1, 2) | EAWAG – SANDEC |
Unplanted drying bed (UDB) | Good quality (2, 3, 4, 1, 2) | EAWAG – SANDEC |
Lagoon | Good quality (2, 3, 3, 1, 2) | Adapted from Thompson et al. (2022)) |
Technology . | Emission rate (ER) . | References . |
---|---|---|
CBT | 0.454 kg CH4/capita/year | Johnson et al. (2022) |
0.0661 kg N2O/capita/year | ||
VIP latrine | 1.134 kg CH4/capita/year | |
0.0661 kg N2O/capita/year | ||
W.C. | 1.804 kg CH4/capita/year | |
0.0441 kg N2O/capita/year | ||
UDB | 13.3 g CO2 eq./m2/day or 0.532 g CH4/m2/day | Adapted from Cui et al. (2015) |
PDB | 1,653 mg CH4/m2/day | Adapted from Uggetti et al. (2012) and Cui et al. (2015) |
485 mg N2O/m2/day | Adapted from Uggetti et al. (2012) | |
Lagoons | 0.0018 kg CH4/m3 | Adapted from Thompson et al. (2022) |
0.000629 kg N2O/m3 | ||
0.000608 kg NH3/m3 |
Technology . | Emission rate (ER) . | References . |
---|---|---|
CBT | 0.454 kg CH4/capita/year | Johnson et al. (2022) |
0.0661 kg N2O/capita/year | ||
VIP latrine | 1.134 kg CH4/capita/year | |
0.0661 kg N2O/capita/year | ||
W.C. | 1.804 kg CH4/capita/year | |
0.0441 kg N2O/capita/year | ||
UDB | 13.3 g CO2 eq./m2/day or 0.532 g CH4/m2/day | Adapted from Cui et al. (2015) |
PDB | 1,653 mg CH4/m2/day | Adapted from Uggetti et al. (2012) and Cui et al. (2015) |
485 mg N2O/m2/day | Adapted from Uggetti et al. (2012) | |
Lagoons | 0.0018 kg CH4/m3 | Adapted from Thompson et al. (2022) |
0.000629 kg N2O/m3 | ||
0.000608 kg NH3/m3 |
The information regarding the inputs and outputs used in modeling the studied systems is available in Supplementary material.
RESULTS AND DISCUSSION
Potential impact assessment of the sanitation systems analyzed
Scenario . | Climate change (kg CO2 eq.) . | Ecosystems (PDF·m2·year) . | Human health (DALY) . |
---|---|---|---|
S1 (CBT-Eva-UDB) | 2.35 × 103 | 2.79 × 103 | 1.76 × 10−3 |
S2 (CBT-Eva-PDB) | 6.09 × 103 | 3.81 × 103 | 2.76 × 10−3 |
S3 (CBT-Eva-Lag) | 5.64 × 102 | 3.76 × 103 | 2.71 × 10−3 |
S4 (VIP-Eva-UDB) | 2.71 × 103 | 3.56 × 103 | 1.93 × 10−3 |
S5 (VIP-Eva-PDB) | 6.45 × 103 | 3.58 × 103 | 2.93 × 10−3 |
S6 (VIP-Eva-Lag) | 9.28 × 102 | 3.52 × 103 | 2.88 × 10−3 |
S7 (WC-Eva-UDB) | 3.12 × 103 | 3.66 × 103 | 1.07 × 10−2 |
S8 (WC-Eva-PDB) | 6.86 × 103 | 3.68 × 103 | 1.17 × 10−2 |
S9 (WC-Eva-Lag) | 1.33 × 103 | 3.62 × 103 | 1.16 × 10−2 |
Scenario . | Climate change (kg CO2 eq.) . | Ecosystems (PDF·m2·year) . | Human health (DALY) . |
---|---|---|---|
S1 (CBT-Eva-UDB) | 2.35 × 103 | 2.79 × 103 | 1.76 × 10−3 |
S2 (CBT-Eva-PDB) | 6.09 × 103 | 3.81 × 103 | 2.76 × 10−3 |
S3 (CBT-Eva-Lag) | 5.64 × 102 | 3.76 × 103 | 2.71 × 10−3 |
S4 (VIP-Eva-UDB) | 2.71 × 103 | 3.56 × 103 | 1.93 × 10−3 |
S5 (VIP-Eva-PDB) | 6.45 × 103 | 3.58 × 103 | 2.93 × 10−3 |
S6 (VIP-Eva-Lag) | 9.28 × 102 | 3.52 × 103 | 2.88 × 10−3 |
S7 (WC-Eva-UDB) | 3.12 × 103 | 3.66 × 103 | 1.07 × 10−2 |
S8 (WC-Eva-PDB) | 6.86 × 103 | 3.68 × 103 | 1.17 × 10−2 |
S9 (WC-Eva-Lag) | 1.33 × 103 | 3.62 × 103 | 1.16 × 10−2 |
CBT, container-based toilet; VIP, ventilated improved pit latrine; WC, flush toilet; UDB, unplanted drying bed; PDB, planted drying bed; Lag, lagoon.
Regarding potential ecosystem impacts, the scenarios (S) are ranked in descending order of impact as follows: S2 > S1 > S3 > S8 > S7 > S9 > S5 > S4 > S6. The analysis of results also reveals that systems equipped with a CBT are, on average, 1.04 times more impactful than those equipped with a flush toilet (WC), and 1.07 times more impactful than those equipped with a VIP latrine. Consequently, CBT emerges as the most impactful technology in terms of ecosystem impact (3.48 × 10³ PDF·m²·year), followed by W.C. (3.31 × 10³ PDF·m²·year) and VIP latrine (3.21 × 10³ PDF·m²·year). Regarding treatment technologies, scenarios incorporating a PDB are 1.02 times more impactful than those with a lagoon, and 1.01 times more impactful than those with an UDB. Therefore, PDB emerges as the most impactful treatment technology in terms of ecosystem impact (2.69 × 10² PDF·m²·year), followed by UDB (2.48 × 10² PDF·m²·year) and lagoon (2.12 × 10² PDF·m² year). These data suggest that both the examined sanitation systems and treatment technologies show relatively insignificant differences in terms of ecosystem impact.
Regarding potential impacts on human health, the ranking in descending order is as follows: S8 > S9 > S7 > S5 > S6 > S2 > S3 > S4 > S1. The results have also highlighted that, in terms of health impacts, systems equipped with a flush toilet are on average 4.51 times more impactful than those equipped with a VIP latrine and 4.85 times more impactful than those equipped with a CBT. Thus, the flush toilet appears as the most impactful toilet in terms of health impact (1.15 × 10−2 DALY), followed by the VIP latrine (2.74 × 10−3 DALY) and the CBT (2.64 × 10−3 DALY). Regarding treatment technologies, systems equipped with a PDB are on average 1.21 times more impactful than those equipped with an UDB and 1.01 times more impactful than those equipped with a lagoon. This suggests that the PDB is the most impactful treatment technology in terms of health impact (5.15 × 10−5 DALY), followed by the lagoon (1.62 × 10−6 DALY) and the UDB (−9.51 × 10−4 DALY).
Contribution analysis
A contribution analysis was carried out to identify the technologies and life cycle phases with the most impact, as well as the critical variables (hotspots). Three impact categories were selected: climate change, ecosystem quality, and human health. For ecosystems and human health, aquatic ecotoxicity and water availability were chosen respectively, as Figures 6 and 7 show that these indicators have the highest impact scores for these two impact categories.
Contribution to climate change
Table 5 presents the results of the contribution analysis related to climate change. The data indicate that, in scenarios including a drying bed (i.e., 66.7% of scenarios), it is the treatment technologies, particularly their utilization phase, that have the greatest impact on climate. Indeed, in these scenarios, the utilization phase of the drying bed is responsible for 57.1–90.7% of the total impact, depending on the scenario considered. This is mainly explained by GHG emissions resulting from the degradation process of fecal sludge in these technologies.
Elements evaluated . | S1 . | S2 . | S3 . | S4 . | S5 . | S6 . | S7 . | S8 . | S9 . |
---|---|---|---|---|---|---|---|---|---|
CBT-Eva-UDB . | CBT-Eva-PDB . | CBT-Eva-Lag . | VIP-Eva-UDB . | VIP-Eva-PDB . | VIP-Eva-Lag . | WC-Eva-UDB . | WC-Eva-PDB . | WC-Eva-Lag . | |
Toilet construction | 0.04% | 0.02% | 0.17% | 0.08% | 0.03% | 0.24% | 0.09% | 0.04% | 0.21% |
Toilet utilization | 23.4% | 9.01% | 97.7% | 33.5% | 14.1% | 98.0% | 42.1% | 19.2% | 98.6% |
– GHG emission | 11.8% | 4.5% | 49.0% | 25.4% | 10.7% | 74.3% | 35.0% | 16.0% | 82.0% |
– Toilet paper | 9.37% | 3.61% | 39.0% | 8.11% | 3.41% | 23.7% | 7.09% | 3.22% | 16.6% |
– Wood shavings | 2.33% | 0.90% | 9.71% | N/A | N/A | N/A | N/A | N/A | N/A |
Toilet end-of-life | −0.02% | −0.01% | −0.08% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | −0.01% |
Evacuation | 0.53% | 0.20% | 2.19% | 0.61% | 0.26% | 1.78% | 0.53% | 0.24% | 1.24% |
Treatment tech. construction | 0.29% | 0.11% | 0.02% | 0.25% | 0.10% | 0.01% | 0.22% | 0.09% | 0.01% |
Treatment tech. utilization | 75.8% | 90.7% | 0.00% | 65.6% | 85.5% | 0.00% | 57.1% | 80.5% | 0.00% |
– GHG emission | 75.7% | 90.7% | 0.00% | 65.5% | 85.5% | 0.0% | 57.0% | 80.5% | 0.00% |
– Sands extraction | 0.12% | N/A | 0.00% | 0.10% | N/A | 0.00% | 0.09% | N/A | 0.00% |
Treatment tech. end-of-life | −0.06% | −0.02% | 0.00% | −0.05% | −0.02% | 0.00% | −0.05% | −0.02% | 0.00% |
Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Elements evaluated . | S1 . | S2 . | S3 . | S4 . | S5 . | S6 . | S7 . | S8 . | S9 . |
---|---|---|---|---|---|---|---|---|---|
CBT-Eva-UDB . | CBT-Eva-PDB . | CBT-Eva-Lag . | VIP-Eva-UDB . | VIP-Eva-PDB . | VIP-Eva-Lag . | WC-Eva-UDB . | WC-Eva-PDB . | WC-Eva-Lag . | |
Toilet construction | 0.04% | 0.02% | 0.17% | 0.08% | 0.03% | 0.24% | 0.09% | 0.04% | 0.21% |
Toilet utilization | 23.4% | 9.01% | 97.7% | 33.5% | 14.1% | 98.0% | 42.1% | 19.2% | 98.6% |
– GHG emission | 11.8% | 4.5% | 49.0% | 25.4% | 10.7% | 74.3% | 35.0% | 16.0% | 82.0% |
– Toilet paper | 9.37% | 3.61% | 39.0% | 8.11% | 3.41% | 23.7% | 7.09% | 3.22% | 16.6% |
– Wood shavings | 2.33% | 0.90% | 9.71% | N/A | N/A | N/A | N/A | N/A | N/A |
Toilet end-of-life | −0.02% | −0.01% | −0.08% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | −0.01% |
Evacuation | 0.53% | 0.20% | 2.19% | 0.61% | 0.26% | 1.78% | 0.53% | 0.24% | 1.24% |
Treatment tech. construction | 0.29% | 0.11% | 0.02% | 0.25% | 0.10% | 0.01% | 0.22% | 0.09% | 0.01% |
Treatment tech. utilization | 75.8% | 90.7% | 0.00% | 65.6% | 85.5% | 0.00% | 57.1% | 80.5% | 0.00% |
– GHG emission | 75.7% | 90.7% | 0.00% | 65.5% | 85.5% | 0.0% | 57.0% | 80.5% | 0.00% |
– Sands extraction | 0.12% | N/A | 0.00% | 0.10% | N/A | 0.00% | 0.09% | N/A | 0.00% |
Treatment tech. end-of-life | −0.06% | −0.02% | 0.00% | −0.05% | −0.02% | 0.00% | −0.05% | −0.02% | 0.00% |
Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
The utilization phase of toilets comes second, with a contribution of 9.00–42.1% in scenarios involving a drying bed, and first in scenarios equipped with a lagoon (97.7–98.6% of the overall impact). The impact of toilets is mainly due to GHG emissions resulting from the degradation of fecal sludge (4.50–82.0%), the use of toilet paper (3.41–39.0%), and the use of wood shavings in scenarios involving a CBT (0.90–9.71%).
The sludge evacuation phase ranks third, with an impact ranging from 0.20 to 1.78%. However, in scenarios equipped with a lagoon (i.e., 33.3% of scenarios), it is the utilization phase of toilets that proves to be the most impactful, with a contribution ranging from 97.7 to 98.6% depending on the scenario considered, followed by the sludge evacuation process, which contributes 1.24–2.19% of the overall climate impact of the system.
As indicated in the work of Jean-Baptiste & Monette (2024), the adoption of practices such as the use of locally manufactured recycled paper, wood residues from carpentry and joinery workshops, and the use of ash as litter could mitigate the environmental impact of sanitation systems on climate change.
Ecosystem impact: contribution to long-term aquatic ecotoxicity
Table 6 presents the contribution to long-term aquatic ecotoxicity. The analysis of the results reveals that the utilization phase of toilets represents 92.5–97.9% of the total impact. Again, toilet paper is the main contributor, representing 83.8–95.8% of the impact, followed by litter, responsible for 12.0–12.2%. In second position, the evacuation link contributes 1.84–4.00% to the total impact. Treatment remains, once again, the least impactful link of the system, with an impact ranging from 0.06 to 2.53%.
Elements evaluated . | S1 . | S2 . | S3 . | S4 . | S5 . | S6 . | S7 . | S8 . | S9 . |
---|---|---|---|---|---|---|---|---|---|
CBT-Eva-UDB . | CBT-Eva-PDB . | CBT-Eva-Lag . | VIP-Eva-UDB . | VIP-Eva-PDB . | VIP-Eva-Lag . | WC-Eva-UDB . | WC-Eva-PDB . | WC-Eva-Lag . | |
Toilet construction | 0.50% | 0.49% | 0.50% | 0.64% | 0.63% | 0.64% | 1.65% | 1.62% | 1.66% |
Toilet utilization | 97.1% | 95.8% | 97.9% | 95.0% | 93.5% | 95.8% | 94.0% | 92.5% | 94.8% |
– Toilet paper | 85.0% | 83.8% | 85.7% | 95.0% | 93.5% | 95.8% | 94.0% | 92.5% | 94.8% |
– Wood shavings | 12.1% | 12.0% | 12.2% | N/A | N/A | N/A | N/A | N/A | N/A |
End-of-life | −0.38% | −0.37% | −0.38% | −0.53% | −0.52% | −0.53% | −0.54% | −0.53% | −0.54% |
Evacuation | 1.87% | 1.84% | 1.89% | 3.96% | 3.90% | 4.00% | 3.96% | 3.89% | 4.00% |
Treatment | 0.87% | 2.27% | 0.06% | 0.97% | 2.53% | 0.07% | 0.97% | 2.52% | 0.07% |
Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Elements evaluated . | S1 . | S2 . | S3 . | S4 . | S5 . | S6 . | S7 . | S8 . | S9 . |
---|---|---|---|---|---|---|---|---|---|
CBT-Eva-UDB . | CBT-Eva-PDB . | CBT-Eva-Lag . | VIP-Eva-UDB . | VIP-Eva-PDB . | VIP-Eva-Lag . | WC-Eva-UDB . | WC-Eva-PDB . | WC-Eva-Lag . | |
Toilet construction | 0.50% | 0.49% | 0.50% | 0.64% | 0.63% | 0.64% | 1.65% | 1.62% | 1.66% |
Toilet utilization | 97.1% | 95.8% | 97.9% | 95.0% | 93.5% | 95.8% | 94.0% | 92.5% | 94.8% |
– Toilet paper | 85.0% | 83.8% | 85.7% | 95.0% | 93.5% | 95.8% | 94.0% | 92.5% | 94.8% |
– Wood shavings | 12.1% | 12.0% | 12.2% | N/A | N/A | N/A | N/A | N/A | N/A |
End-of-life | −0.38% | −0.37% | −0.38% | −0.53% | −0.52% | −0.53% | −0.54% | −0.53% | −0.54% |
Evacuation | 1.87% | 1.84% | 1.89% | 3.96% | 3.90% | 4.00% | 3.96% | 3.89% | 4.00% |
Treatment | 0.87% | 2.27% | 0.06% | 0.97% | 2.53% | 0.07% | 0.97% | 2.52% | 0.07% |
Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Human health impact: contribution to water availability
Table 7 presents the contribution to water availability. These data indicate that the toilet utilization phase is the most impactful (except in Scenarios 1 and 4), ranging from 98.8 to 112%. This predominance is primarily attributed to water used for handwashing and toilet flushing in Scenarios 7–9. Toilet paper ranks second, contributing from 2.67 to 26.7% depending on the scenario considered, and litter wood shavings third, contributing from −2.00 to 26.4%.
Elements evaluated . | S1 . | S2 . | S3 . | S4 . | S5 . | S6 . | S7 . | S8 . | S9 . |
---|---|---|---|---|---|---|---|---|---|
CBT-Eva-UDB . | CBT-Eva-PDB . | CBT-Eva-Lag . | VIP-Eva-UDB . | VIP-Eva-PDB . | VIP-Eva-Lag . | WC-Eva-UDB . | WC-Eva-PDB . | WC-Eva-Lag . | |
Toilet construction | −0.24% | 0.02% | 0.02% | −0.92% | 0.06% | 0.06% | 0.01% | 0.01% | 0.01% |
Toilet utilization | −1,282% | 98.8% | 99.1% | −1,600% | 99.4% | 99.7% | 112% | 99.9% | 100% |
– Toilet paper | −345% | 26.6% | 26.7% | −422% | 26.2% | 26.3% | 2.99% | 2.67% | 2.70% |
– Wood shavings | 26.4% | −2.00% | −2.00% | N/A | N/A | N/A | N/A | N/A | N/A |
– Water | −964% | 74.2% | 74.4% | −1,178% | 73.2% | 73.4% | 109% | 97.2% | 97.3% |
End-of-life | 0.08% | −0.01% | −0.01% | 0.30% | −0.02% | −0.02% | 0.00% | 0.00% | 0.00% |
Evacuation | −11.9% | 0.91% | 0.92% | −4.11% | 0.26% | 0.26% | 0.03% | 0.03% | 0.00% |
Treatment | 1,394% | 0.32% | 0.01% | 1,705% | 0.32% | 0.01% | −12.1% | 0.03% | 0.00% |
Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Elements evaluated . | S1 . | S2 . | S3 . | S4 . | S5 . | S6 . | S7 . | S8 . | S9 . |
---|---|---|---|---|---|---|---|---|---|
CBT-Eva-UDB . | CBT-Eva-PDB . | CBT-Eva-Lag . | VIP-Eva-UDB . | VIP-Eva-PDB . | VIP-Eva-Lag . | WC-Eva-UDB . | WC-Eva-PDB . | WC-Eva-Lag . | |
Toilet construction | −0.24% | 0.02% | 0.02% | −0.92% | 0.06% | 0.06% | 0.01% | 0.01% | 0.01% |
Toilet utilization | −1,282% | 98.8% | 99.1% | −1,600% | 99.4% | 99.7% | 112% | 99.9% | 100% |
– Toilet paper | −345% | 26.6% | 26.7% | −422% | 26.2% | 26.3% | 2.99% | 2.67% | 2.70% |
– Wood shavings | 26.4% | −2.00% | −2.00% | N/A | N/A | N/A | N/A | N/A | N/A |
– Water | −964% | 74.2% | 74.4% | −1,178% | 73.2% | 73.4% | 109% | 97.2% | 97.3% |
End-of-life | 0.08% | −0.01% | −0.01% | 0.30% | −0.02% | −0.02% | 0.00% | 0.00% | 0.00% |
Evacuation | −11.9% | 0.91% | 0.92% | −4.11% | 0.26% | 0.26% | 0.03% | 0.03% | 0.00% |
Treatment | 1,394% | 0.32% | 0.01% | 1,705% | 0.32% | 0.01% | −12.1% | 0.03% | 0.00% |
Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
The evacuation phase comes after the utilization phase and represents −11.9 to 0.92% of the overall impact. Finally, the treatment phase ranks third, responsible for −12.1 to 0.32%. However, Scenarios 1 and 4 have particularly high values compared to the other seven scenarios, reaching 1,394 and 1,705%, respectively. These high values are associated with the process of extracting sand from riverbeds for the utilization phase of the UDB, which seems to strongly affect river ecosystems, particularly by reducing water availability. These high values are mainly offset by the utilization phase of the CBT (−1,282%) and the VIP toilet (−1,600%), as these systems save water by not requiring flushing water.
The design and use of water-efficient toilets, requiring a smaller volume of water for flushing and handwashing, represents an effective solution to reduce the environmental impact associated with water consumption. Furthermore, previous recommendations on the use of recycled paper as well as sawdust or ash as alternatives to toilet paper and wood shavings remain relevant to mitigate this impact.
Sensitivity analysis
CONCLUSION
This study aimed to compare different on-site sanitation systems using drying beds or lagoons for the treatment of human excreta in Haiti, by applying the environmental LCA. Nine scenarios were developed, comprising three successive stages: toilet, evacuation, and treatment of fecal sludge, with the functional unit being the management of 1 ton of fecal sludge (wet basis) over 1 year.
The results indicate that toilets, particularly their utilization phase, are the most impactful component, while the treatment phase is the least impactful. The critical variables identified include the use of toilet paper, wood shavings, GHG emissions, water usage, and the transportation of fecal sludge. The use of recycled paper, sawdust, or ash as litter, as well as water-efficient toilets, could reduce health and environmental impacts.
To better guide decisions on sanitation systems to be prioritized in low-income tropical countries, the study suggests combining LCA with Life Cycle Cost Assessment (LCCA) and Social Life Cycle Assessment (SLCA). This integrated approach will allow for the consideration of environmental, economic, and social aspects, thus promoting more informed and sustainable decisions regarding on-site sanitation.
ACKNOWLEDGEMENTS
The lead author expresses gratitude to Lécopot for providing the necessary data for modeling the container-based toilet and to EAWAG-SANDEC for providing the data related to drying beds.
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.