Inventory Analysis and Environmental Life Cycle Impact Assessment of Hotel Food Waste Management for Bio-Circular Economy Development in Zimbabwe

doi:10.21203/rs.3.rs-4657714/v1

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Inventory Analysis and Environmental Life Cycle Impact Assessment of Hotel Food Waste Management for Bio-Circular Economy Development in Zimbabwe

https://doi.org/10.21203/rs.3.rs-4657714/v1

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This study is an inventory analysis and environmental life cycle assessment (ELCA) of hotel food waste management (FWM) for bio-circular economy development in Zimbabwe. An audit of the food waste generation and inventory analysis of the prevailing FWM practices at the selected three hotels was undertaken. The greenhouse gas emissions from the prevailing disposal of FW at dumpsites and proposed biological treatment of FW were evaluated using the Tier 1 FOD method and Tier 1 method of biological treatment under the 2019 refined 2006 IPCC guidelines. ELCA was also conducted for the open dumping, composting and anaerobic digestion. The average FW generation within the Zimbabwean hospitality industry was estimated at 1.63 kg/guest/day with a maximum and minimum of 1.01 and 2.25 kg/guest/day respectively. These waste generation figures are lower than the reported figures from other studies and jurisdictions. Source separation of FW is currently being practiced though the source separated FW is indiscriminately collected by Municipal Waste collection trucks for final disposal at the official landfills or dumpsites rendering the FW source separation a futile exercise hence the need for an offtake system in the form of composting or anaerobic digestion (AD) for the FW. The disposal of FW at SWDS contributes to the highest GHG emissions followed by composting that brings about a maximum of 75% reduction in GHG emissions. AD brings about a maximum reduction in GHG emissions of 97%. ELCA results show that AD is the best methods leading to net negative environmental impacts.

Food waste

environmental life cycle assessment

landfill

composting

anaerobic digestion

hospitality industry

Tourism has become one of the fastest growing sectors globally resulting in increased municipal solid waste (MSW) generation especially food waste (FW). FW constitutes over 60% of the MSW being generated within the hospitality industry. FW generated from the hospitality industry constitutes 9% of the FW generated by the food sector globally (Pirani & Arafat, 2016). The generation of FW has multiple socio-economic and environmental implications. UNEP (2024) reported that FW generation is regarded both a market and environmental failure as it results dumping of FW worth over a US$1 trillion annually and contributes between 8 and 10% of the greenhouse gas emissions (GHG). Pirani & Arafat (2014) noted that environmental impacts from the hospitality industry thus partly manifests from the corresponding FW generation and management.

The considerate resource intensive nature of food production is attributable to the environmental impacts of FW. Silvennoinen et al.(2014) provided that an estimated 250 km³, 70% of the earth’s infinite and vulnerable freshwater resources, is used in food production. Food production leads to habitat loss as tracts of land are converted to agricultural land with an estimated 1.4 x 10⁹ ha constituting 28% of the total land area globally being used for food production. Apart from land and water food production, distribution and storage uses materials and energy which brings about increased environmental loads along the food value chain and life cycle. FW thus translates to the loss of all these resources that would have been used in its production and along the value chain.

The generation of FW is despite over 750 million suffering from hunger every year with 150 million children below five years have diets constrained of essential nutrients leading to suffering stunted growth and development (UNEP, 2024). The reduction of FW being generated currently will contribute towards the attainment of Sustainable Development Goal (SDG) 11 on zero hunger. Hence the importance of target 12.3 under SDG 12 which provides for the reduction of global FW per capita by 50% by retailers and consumers together with reducing food losses across the food supply chains by 2030.

The socio-economic and environmental impacts associated with FW generation and management have rendered it a global challenge that is getting increased attention towards the need to implement appropriate FW reduction and prevention, valorization pathways, and management systems that could address these impacts. Life cycle methodologies provide economic and environmental impacts evaluation of the various FW management including transportation, reduction, prevention, treatment, and disposal. ELCA has matured as a tool to assess the FW associated environmental impacts. Batool et al(2024) critically reviewed ELCA studies that assessed the environmental impacts of landfilling, AD, composting, hydrothermal carbonization and gasification of FW. This study assesses the environmental impacts of the current FW management practice (dumping in open dumpsites) at three selected hotels and compares them with the impacts from composting and anaerobic digestion using ELCA. In addition, ELCA derived global warming impacts for the open dumping, composting and anaerobic digestion are compared with those estimated from the IPCC guidelines.

2.1. Inventory Analysis of FW Management Practices

An audit of the waste generation and inventory analysis of the prevailing waste management practices at the selected three hotels was undertaken between November and December of 2023. The period is regarded the high peak periods hence the audit considered the maximum probable scenario regarding FW generation. Although waste generation varies across different temporal scales (weekday, week of month and month of year) and spatial scale or localities indicating the need for highlighting the need for longitudinal yearlong sampling and waste generation data measurements or audits (Abel, 2007), time, financial and human resources constrained the undertaking of audits outside the period between November 2023 and December 2023. It was assumed that the respective hotel operations are standardised with insignificant variations on its food value chain and behaviour of hotel guests regarding eating habits and FW generation. The annual average FW generation for the respective hotel (P_Ax) was computed from Eq. 1

$$\:{P}_{Ax}=\frac{{RO}_{Ax}}{{R0}_{ax}}\left({P}_{ax}\right)\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:1$$

Where RO_Ax is the annual average room occupancy for hotel x, RO_ax and P_ax are respectively the room occupancy and FW generation during the audit at hotel x.

2.2. GHG Emission Estimation Using IPPC Guidelines

Methane (CH₄) emissions from the disposal of FW generated at the hotels were estimated using the Tier 1 FOD method of the 2019 refined 2006 IPCC guidelines. This method was also used to estimate the waste sector emissions reported in the Zimbabwe’s Fourth National Communication to the United Nations Framework Convention on Climate Change with a 50-year timespan for all the food waste to decompose. Default IPPC parameter values were used together with actual field measurements. The respective RO_Ax, RO_ax, P_ax and P_Ax were used. It was assumed that a direct and positive relationship exists between solid waste generation and room occupancy levels.

GHG emissions from the composting and AD of the FW were also estimated using the Tier 1 method of biological treatment under the 2019 refined 2006 IPCC guidelines. The IPCC default CH₄ and N₂O emission factors of 4g CH₄/kg and 0.24 g N₂O/kg of waste treated were used for composting on a on a wet weight basis. The IPCC default CH₄ emission factor of 0.8g CH₄/kg of waste treated was used for anaerobic digestion on a wet weight basis with the N₂O emissions being considered negligible. The CH₄ and N₂O emissions from the composting and AD of the food waste generated in Gg were estimated using Equations 2 and 3.

$$\:{CH}_{4}=\sum\:_{i}{(M}_{i}*{EF}_{i})*{10}^{-3}-R\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:..2$$

$$\:{N}_{2}o=\sum\:_{i}{(M}_{i}*{EF}_{i})*{10}^{-3}\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:\dots\:.3$$

Where’

M_i is the mass of organic waste treated by biological treatment type i, Gg,

i is composting or anaerobic digestion,

EF is the emission factor for treatment i, g CH4/kg waste treated,

R is the total amount of CH₄ recovered under anaerobic digestion in inventory year, Gg CH4, which was regarded zero.

2.3. Environmental Life Cycle Assessment

A life cycle assessment was conducted to assess the environmental impacts of open dumping (the prevailing management practice), and proposed composting and anaerobic digestion of FW being generated at the respective hotels. SimaPro version 9.5.0.2 analyst was used during the LCA. Impacts loads of the processes and materials were collected from Ecoinvent 3v database. ReCiPe 2016 v1.1 method at midpoint was used (Huijbregts et al., 2017). The annual FW generation (P_Ax) was used as the functional unit. The ELCA used SimaPro inventory databases for institution 1, 2 and 3 are provided in Figs. 1, 2 and 3 respectively for the FW dumping at SWDS, composting and AD simulations.

The functional unit of 37.28 tons was used at institution 1. The avoided products were with regards to the production of 11.18 tons of chemical fertilisers for both composting and AD. A total of 171.50 GJ of energy was estimated to be avoided from the 7.46 x 10³ m³ of biogas produced from the AD process at institution 1. The energy was assumed to replace grid electricity and liquefied petroleum gas (LPG) based on an energy mix of 89% grid electricity and 11% LPG that was estimated at Institution 1 during the audit. Therefore 153.20 and 18.30 GJ of grid electricity and LPG are avoided. With regards to the avoided grid electricity, 91.92 and 61.28 GJ are produced from coal thermal power plants and large hydro respectively. This was based on the Zimbabwe grid electricity mix of 60% and 40% respectively.

The functional unit of 41.41 tons was used at institution 2. The avoided products were with regards to the production of 12.42 tons of chemical fertilisers for both composting and AD. A total of 190.47 GJ of energy was estimated to be avoided from the 8.28 x 10³ m³ of biogas produced from the AD process at institution 2. The energy was assumed to replace grid electricity and liquefied petroleum gas (LPG) based on an energy mix of 72% grid electricity and 28% LPG that was estimated at Institution 1 during the audit. Therefore 137.45 and 53.01GJ of grid electricity and LPG are avoided. With regards to the avoided grid electricity, 82.47 and 54.98 GJ are produced from coal thermal power plants and large hydro respectively based on the Zimbabwe grid electricity mix.

The functional unit of 18.64 tons was used at institution 3. The avoided products were with regards to the production of 5.59 tons of chemical fertilisers for both composting and AD. A total of 85.76 GJ of energy was estimated to be avoided from the 3.73 x 10³ m³ of biogas produced from the AD process at institution 3. The energy was assumed to replace grid electricity and liquefied petroleum gas (LPG) based on an energy mix of 94% grid electricity and 6% LPG that was estimated at Institution 1 during the audit. Therefore 80.19 and 5.57 GJ of grid electricity and LPG are avoided. With regards to the avoided grid electricity, 48.12 and 32.08 GJ are produced from coal thermal power plants and large hydro respectively based on the Zimbabwe grid electricity mix.

3.1. FW generation statistics and management practices

3.1.1. FW generation statistics

The average daily FW generated (W_A) from the operations at the hotels during the audit periods are provided in Table 1. The FW composition within the waste being generated at the hospitality institutions confirms the predominant composition of FW in the waste generated within the hospitality sector. The need for sustainable FW management arises that recover nutrients, materials, and energy from the FW.

Table 1

Audit findings of FW generation audit
Institution	$\:{\varvec{R}0}_{\varvec{a}\varvec{x}}$ (%)	$\:{\varvec{R}\varvec{O}}_{\varvec{A}\varvec{x}}$ (%)	Composition (%)	$\:{\varvec{P}}_{\varvec{a}\varvec{x}}$ (kg)	$\:{\varvec{P}}_{\varvec{A}\varvec{x}}$ (kg)	P_Ax/room occupied
1	100.00%	56.00%	72.00	182.05	101.95	1.01
2	61.95	47.58%	72.00	147.70	113.44	2.25
2	85.33	39.00	64.00	111.76	51.08	1.62

Table 2 shows the comparison of the waste generation estimates for the respective hotels against reported estimates in other jurisdictions. The waste generation figures for hotel 1 are well within the reported figures from other reports and jurisdictions. Though the waste generation figures are within the reported figures in Table 2 they are lower than the 4 kg/room/day reported by Giang et al. (2017) for a 4-star hotel in Hoi An, Vietnam (Hoang et al., 2017). The waste generation figures obtained during the assessment are generally within the ranges of 1.71, 2.32 and 6.57 kg/guest/day reported by Son et al.(2018) respectively for three, four and five-star hotels in in Hue City, Vietnam. Maximum values of 3.33 kg/guest/day were also reported in Asia (Chan & Lam, 2001; Omidiani & Hashemihezaveh, 2016).

Table 2

Comparison of the waste generation figures for the respective hotels against reported figures in other jurisdictions
Hotel	Estimated Waste Generation (kg/day per room occupied/guest)	Reported Figures from Other Sources (kg/day/ per room occupied/guest)
		UNEP 2003		(Bjørn Olsen et al., 2018)	(Pham Phu et al., 2018)
1	1.01	1.00*	2.00**	1.60	2.50***
2	2.25
3	1.62
*European tourists
** American tourists
*** In Vietnam with 58.5% being biodegradables

3.1.2. FW management practices

Table 3 provides the FW management regarding separation, collection, treatment, and disposal methods at the respective institutions. Source separation of FW is currently being practiced at 1 and 3 especially within their kitchens and dining rooms. However, the source separated FW at 1 is sent to a waste collection point where Municipal Waste collection trucks collect the waste indiscriminately mixing the source separated FW with other waste fractions for final disposal at the landfill or dumpsite. This renders the FW source separation a futile exercise hence the need for an offtake system in the form of composting or anaerobic digestion (AD) for the FW. At 2 FW is indiscriminately collected by Municipal Waste collection trucks for final disposal at the dumpsite.

Table 3

FW Management practices at the audited institutions
Institution	Source separation	Indiscriminate collection	Dumpsite	Composting
1	√	√	√
2		√	√
3	√			√

3.2. IPCC Guidelines Based GHG Emission Estimates

The GHG emissions from the disposal of FW generated at dumpsites, composting and AD estimated using the IPCC guidelines are given in Table 4. Figure 4 provides the graphical illustrations of the comparisons of the GHG emissions from the dumping, composting and AD of the FW being generated at the hotels. The disposal of FW at solid waste disposal sites (SWDS) or dumpsites contributes to the highest GHG emissions. Composting has lower GHG emissions than the dumping of the FW at dumpsites currently being practised as it brings about a maximum of 75% reduction in GHG emissions. AD brings about a maximum reduction in GHG emissions of 97%.

3.3. ELCA

The ELCA results provides the impacts of the disposal at SWDS, composting and AD of FW across several environmental impact categories unlike the IPCC guidelines which specifically focuses on the global warming impacts only. Individual ELCA studies on FW have focused on specific impact categories as indicated in the studies reviewed by Batool et al. (2024). The results herein presented are for all the impact categories under SimaPro shown in Table 5 with regards to disposal of SWDS, composting and AD of FW being generated at the selected three hotels.

Table 5

SimaPro impact categories
Impact category	Unit
Global warming potential (GW)	kg CO₂ eq
Stratospheric ozone depletion (SOD)	kg CFC11 eq
Ionizing radiation (IO)	kBq Co-60 eq
Ozone formation, Human health (OF-HH)	kg NOx eq
Fine particulate matter formation	kg PM2.5 eq
Ozone formation, Terrestrial ecosystems (OF-TE)	kg NOx eq
Terrestrial acidification (TA)	kg SO₂ eq
Freshwater eutrophication	kg P eq
Marine eutrophication	kg N eq
Terrestrial ecotoxicity (TE)	kg 1,4-DCB
Freshwater ecotoxicity	kg 1,4-DCB
Marine ecotoxicity	kg 1,4-DCB
Human carcinogenic toxicity (HCT)	kg 1,4-DCB
Human non-carcinogenic toxicity (HNCT)	kg 1,4-DCB
Land use (LU)	m²a crop eq
Mineral resource scarcity (MRS)	kg Cu eq
Fossil resource scarcity (FRS)	kg oil eq
Water consumption (WC)	m³

3.3.1. Global Warming

The disposal of FW in SWDS results in positive GW impact as shown in Fig. 5. This confirms findings from other ELCA studies reported by Fu et al.(2021) and Kurniawan et al(2023) that the disposal of FW in SWDS including landfills produces the greatest net positive GW impact. Batool et al.(2024) ranked the different FW management and treatment technologies based on findings from ELCA studies with the disposal of FW in SDWS having GW impact being the major environmental burden. The GWP is through the emission of methane (CH₄) that is generated from the anaerobic decomposition of the FW in the SWDS. The recovery and use of CH₄ significantly reduces the GW impact.

Both composting and AD have positive GW impact albeit lower than the disposal of FW in SWDS. However, if the avoided GHG emissions from the production of NPK fertilsers that are replaced by the compost are factored, composting will have net negative GW impact as shown in Fig. 5. In the same vein if the GHG emissions from the production of NKP fertilsers replaced by the compost or organic fertilizer from the AD digestate as well as the energy replaced by biogas produced during AD, AD will result in a net negative GW impact higher than that of composting shown in Fig. 5. A net negative GW impact indicates a net environmental benefit. This study findings confirm findings by Nyitrai et al. (2023) who reported that AD of FW leads to a net GWP benefit. AD is therefore more beneficia to the environment or preferrable to composting with regards to GW impact. Xu et al. (2015) have considered AD amongst the best FW management options and Eriksson et al. (2015) observed the comparative benefits of AD over composting.

Table 4

Estimates of GHG emissions from disposal at solid waste disposal sites (dumpsites), composting and AD of FW generated at selected hotels.
Institution	1			2			3
GHG	SWDS	Composting	AD	SWDS	Composting	AD	SWDS	Composting	AD
CH₄ (Gg)	1.03 x 10^− 3	1.95 x 10^− 4	2.98 x 10^− 5	1.15 x 10^− 3	2.17 x 10^− 4	4.33 x 10^− 5	5.79 x 10^− 4	8.40 x 10^− 5	1.68 x 10^− 5
N₂O (Gg)	-	8.95 x 10^− 6	-	-	1.30 x 10^− 5	-	-	5.04 x 10^− 6	0
Total GHG (kgCO₂eq)	2.57 x 10⁴	6.39 x 10³	7.46 x 10²	2.88 x 10⁴	9.29 x 10³	1.08 x 10³	1.45 x 10⁴	3.60 x 10³	4.20 x 10²
% Reduction	-	75%	97%	-	68%	96%	-	75%	97%

3.3.2. Stratospheric Ozone Depletion

Just like with GWP, the disposal of FW in SWDS yields net positive SOD whereas composting and AD yield almost equal net negative SOD signalling net positive environmental benefits of composting and AD. The results are shown in Fig. 5. Batool et al. (2024) in their review observed and reported that AD of FW is the best performing technology with regards to SOD i.e. performs better than both composting of FW and disposal FW in SWDS. This study shows that composting and AD performs almost the same which disagrees with the review findings from Batool et al. (2024) that indicated that composting performs badly compared to disposal at SWDS. The discrepancy could emanate from the SWDS considered in the review by Batool et al. (2024) being landfilling whilst this study considered open dumping in shallow unsanitary landfills with no landfill gas capture and recovery.

3.3.3. Ozone Formation

Ozone formation impact was assessed with regards to human health and terrestrial ecosystems. Results show the same magnitudes for both human health and terrestrial ecosystems based OF impacts. Results show slight variations wherein terrestrial ecosystems being 2% higher than the estimates for human health OF. Figure 6 shows the results with regards to human health OF. The disposal of FW in SWDS leads to positive OF estimated at 1.48 x 10³ kgNO_xeq per ton of FW for each of the human health and terrestrial ecosystems based OF. Resultantly a net positive OF for both the human health and terrestrial ecosystems based OF of 2.95 x 10³ kgNO_xeq per ton of FW disposed in an open dumpsite.

Composting and AD of FW produces volatile organic compounds (VOCs) (Cui et al., 2022; Mustafa et al., 2017; Nie et al., 2018, 2019) which were regarded by Shao et al. (2011) and Gong et al. (2017) as main precursors to ozone formation. Study results showed that composting results in human health and terrestrial ecosystems based OFP of 1.63 x 10^− 1 and 1.69 x 10^− 1 kgNO_xeq per ton of FW respectively. Composting therefore contributes 3.32 x 10^− 1 kgNO_xeq per ton of FW for both the human health and terrestrial ecosystems based OFP.With regards to AD, human health and terrestrial ecosystems based OF of 2.81 x 10^− 1 and 2.84 x 10^− 1 kgNO_xeq per ton of FW were respectively estimated. AD therefore contributes 5.65 x 10^− 1 kgNO_xeq per ton of FW for both the human health and terrestrial ecosystems based OF. However, when the associated avoided OFP from the production of replaced NPK fertilsers and renewable energy, composting and AD results in net negative OF as shown in Fig. 6.

3.3.4. Ionizing Radiation Potential

Results show that the disposal of FW at SWDS has no IR impact whereas composting has IR of 4.55 X 10¹ kBqCo-60eq per ton of FW thus positive IR impact thus bringing about negative impacts even after considering the avoided emissions from the avoidance of use of chemical fertilizers. Though the AD process has positive IR of 8.35 x 10^− 1 kBqCo-60eq per ton of FW, when the avoided emissions from the replacement of LPG gas, grid electricity and chemical fertilizers are considered, the AD system brings about negative IR impacts hence environmental benefits. IR potential from the disposal of FW at SWDS, composting and AD are shown in Fig. 7.

3.3.5. Fine Particulate Matter Formation

The AD and composting of FW were projected to generate 2.46 x 10^− 2 and 3.00 x 10^− 2 kg PM2.5eq per ton of FW respectively. This shows that AD and composting of FW leads to positive FPMF. However, when the avoided emissions from the replacement of chemical fertilizers by compost or organic fertilizer from composting and AD as well as replacement of LPG and grid electricity by AD derived biogas, both composting and AD systems results in negative FPMF. The disposal of FW at SWDS leads to no FPMF. These results are shown in Fig. 7.

3.3.6. Terrestrial Acidification

Disposal of FW at SWDS leads to positive TA impacts of 5.32 x 10 − 2 kgSO2eq per ton of FW whereas the composting and AD of FW lead to positive TA of 5.42 x 10 − 1 and 2.94 x 10 − 1 kgSO2eq per ton of FW respectively. Results showed that AD has the least TAP confirming findings by Batool et al. (2024) that identified TA amongst the high LCA impact categories for disposal of FW at SWDS and treatment of FW through composting. The avoided emissions from the replacement of chemical fertilizers by compost or organic fertilizer from composting and AD as well as replacement of LPG and grid electricity by AD derived biogas results in negative TA for both composting and AD systems shown in Fig. 8

3.3.7. Land use

The disposal of FW at SWDS and treatment of FW through the AD lead to LU I pacts of 2.61 and 2.53 m²acropeq per ton of FW respectively. Composting brings about the highest LU of 2.26 x 10³ m²acropeq per ton of FW. This also confirms findings by Batool et al. (2024) that identified LU amongst the high LCA impact categories for treatment of FW through composting. Factoring in the avoided emissions from replacing chemical fertilisers with organic fertiliser as well as LPG and grid electricity with biogas leads to overall negative LU for the AD system. LU results for the disposal of FW at SWDS, composting and AD are shown in Fig. 8.

3.3.8. Freshwater and Marine Eutrophication

The freshwater and marine eutrophication impacts assessment results are provided in Fig. 9. The disposal of FW at SWDS, composting and AD of FW were estimated to contribute to positive freshwater eutrophication of 9.27 x 10^− 2, 2.06 x 10^− 2 and 2.52 x 10^− 1 kgPeq per ton of FW respectively. AD has the highest freshwater eutrophication followed by disposal at SWDS. Regarding marine eutrophication potential, disposal at SWDS, composting and AD was estimated to contribute to 1.13, 1.14 x 10 − 1 and 1.45 x 10^− 2 kgNeq per ton of FW respectively. Avoided emissions from the replacement of chemical fertilisers with compost only results in net negative emissions with regards to freshwater eutrophication. Net positive marine eutrophication was estimated even after considering avoided emissions from the replacement of chemical fertilisers with compost from the composting. Net negative freshwater eutrophication and marine eutrophication were quantified when the avoided emissions from the replacement of chemical fertilisers with compost, LPG with biogas and grid electricity with biogas from the AD system.

3.3.9. Terrestrial, Freshwater and Marine Ecotoxicity

The TE, freshwater and marine ecotoxicity results are provided in Fig. 10. The disposal of FW at SWDS, composting and AD of FW were estimated to contribute to positive TE of 5.42 x 10^− 1, 1.07 x 10² and 5.06 x 10¹ kg 1,4-DCB per ton of FW respectively. Likewise, positive freshwater ecotoxicity for the disposal of FW at SWDS, composting and AD of FW of 1.53 x 10¹, 4.9 and 2.27 kg1,4-DCB per ton of FW were respectively observed. Positive marine ecotoxicity were also estimated for the disposal of FW at SWDS, composting and AD of FW of 4.88, 1.51 and 6.65 kg1,4-DCB per ton of FW respectively. When the avoided emissions from the use of compost or organic fertiliser and biogas are considered, both composting and AD systems results in net negative terrestrial, freshwater and marine ecotoxicity as shown in Fig. 10. with AD having the highest negative ecotoxicity indicating the greatest environmental benefit.

3.3.10. Human Toxicity

The results for human carcinogenic toxicity (HCT) and human non-carcinogenic toxicity (HNCT) are shown in Fig. 10. The disposal of FW at SWDS, composting and AD of FW were estimated to contribute to positive HCT of 4.18 x 10^− 2, 9.01 x 10^− 2 and 6.91 x 10^− 2 kg 1,4-DCB per ton of FW respectively. Likewise, positive HNCT for the disposal of FW at SWDS, composting and AD of FW of 7.52, 3.06 and 4.56 kg1,4-DCB per ton of FW were respectively observed. Just like for ecotoxicity, when the avoided emissions from the use of compost or organic fertiliser and biogas are considered, both composting and AD systems results in net negative HCT and HNC as shown in Fig. 10. with AD having the highest negative human toxicity indicating the greatest environmental benefit.

3.3.11. Mineral and Fossil Resource Scarcity

The results for MRS and FRS are shown in Fig. 11. No MRS and FRS impacts from the disposal of FW at SWDS. The composting and AD of FW were estimated to contribute to positive MRS of 4.68 x 10^− 1 kg Cu eq and 1.21 x 10^− 1 kg oil eq per ton of FW respectively. Likewise, positive FRS for the composting and AD of FW of 8.83 kg Cu eq and 1.35 x 10¹ kg oil eq per ton of FW were respectively observed. The avoided emissions from the use of compost or organic fertiliser and biogas for the composting and AD systems lead to net negative MRS and FRS as shown in Fig. 11. with AD also having the highest net negative MRS and FRS indicating the greatest environmental benefit.

3.3.12. Water Consumption

The results for WC are shown in Fig. 12. No WC impacts from the disposal of FW at SWDS. The composting and AD of FW were estimated to contribute to positive WC of 1.13 x 10¹ kg m³ and 2.10 x 10^− 1 m³ per ton of FW respectively. However, even after the avoided emissions from the use of compost or organic fertiliser, the composting of FW has a net positive WC of 4m³ per ton of FW. AD systems lead to net negative WC after considering the avoided emissions from the use of compost or organic fertiliser and biogas as shown in Fig. 12.

3.3.13. Ranking of the FW Management and Treatment Methods

The disposal of FW at SWDS, composting and AD of FW whose impacts were assessed were ranked based on their environmental performance against each of the life cycle impact categories. The ranking results are shown in Fig. 13. providing a clearer picture regarding the environmental performance of the FW management and treatment methods. It gives the best and worst environmental performing method per each impact category with the disposal of FW in SWDS being the worst method for most of the impact categories namely Global Warming, Stratospheric Ozone Depletion, Ozone Formation -Human Health, Ozone Formation -Terrestrial Ecosystems, Terrestrial Acidification, Freshwater Eutrophication, Marine Eutrophication, Ecotoxicity, and Human Toxicity. Composting was worst performing with regards to three impact categories namely, ionizing radiation, land use and water consumption. AD was the best performing methods across all the impact categories serve for Stratospheric Ozone Depletion where it came second after composting. Therefore, overall, AD is the best methods leading to net negative environmental impacts consistent with findings from Fu et al. (2023) and Batool et al. (2024). The disposal of FW at SWDS thus is the worst FW management and treatment method.

The average FW generation within the Zimbabwean hospitality industry was estimated at 1.63 kg/guest/day with a maximum and minimum of 1.01 and 2.25 kg/guest/day respectively. These waste generation figures are lower than the reported figures from other studies and jurisdictions. Interestingly, source separation of FW is currently being practiced though the source separated FW is indiscriminately collected by Municipal Waste collection trucks for final disposal at the official landfills or dumpsites. This renders the FW source separation a futile exercise hence the need for an offtake system in the form of composting or anaerobic digestion (AD) for the FW.

The GHG emissions from the disposal of FW generated at dumpsites, composting and AD estimated using the IPCC guidelines shows that the disposal of FW at SWDS contributes to the highest GHG emissions. Composting has lower GHG emissions than the dumping of the FW at dumpsites currently being practised as it brings about a maximum of 75% reduction in GHG emissions. AD brings about a maximum reduction in GHG emissions of 97%. Environmental life cycle assessment results also show that AD is the best methods leading to net negative environmental impacts whereas the disposal of FW at SWDS thus was found to be the worst FW management and treatment method. Therefore, steps need to be taken to ensure either the composting or AD of FW being generated within the hospitality industry in Zimbabwe.

Conflict of interest

The work was supported by the University of South Africa through the Postdoctoral fellowship to Dr Trust Nhubu. Therefore, no form of potential conflicts of interest (financial or non-financial) is declared. The work did not involve human participants and animals, hence informed consent and a statement on welfare of animals is not applicable.

Funding declaration

The work was supported with financial support from the University of South Africa under a Postdoctoral Research Fellowship awarded to Dr Trust Nhubu.

Author Contribution

T.N - Study conceptualization, literature review, data gathering during audit, data analysis, life cycle analysis, GHG emissions estimation using the IPCC guidelines and manuscript write upC.M - Data analysis, Environmental Life Cycle Assessment and providing the necessary manuscript review and editing

Data availability statement

The waste generation data at the respective institutions that was collected and used for the work has been provided as an attachment. SimaPro 9.5.2 databases that were used for the LCA have also been indicated within the manuscripts through Figs. 1, 2 and 3. In addition, the FW data as provided in the attachment can be used to replicate GHG emission estimation using the 2019 refined 2006 IPCC guidelines. LCA results datasets have also been provided as attachments.

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Inventory Analysis and Environmental Life Cycle Impact Assessment of Hotel Food Waste Management for Bio-Circular Economy Development in Zimbabwe

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Abstract

Figures

1. Introduction

2. Materials and Methods

2.1. Inventory Analysis of FW Management Practices

2.2. GHG Emission Estimation Using IPPC Guidelines

2.3. Environmental Life Cycle Assessment

3. Results and Discussion

3.1. FW generation statistics and management practices

3.1.1. FW generation statistics

3.1.2. FW management practices

3.2. IPCC Guidelines Based GHG Emission Estimates

3.3. ELCA

3.3.1. Global Warming

3.3.2. Stratospheric Ozone Depletion

3.3.3. Ozone Formation

3.3.4. Ionizing Radiation Potential

3.3.5. Fine Particulate Matter Formation

3.3.6. Terrestrial Acidification

3.3.7. Land use

3.3.8. Freshwater and Marine Eutrophication

3.3.9. Terrestrial, Freshwater and Marine Ecotoxicity

3.3.10. Human Toxicity

3.3.11. Mineral and Fossil Resource Scarcity

3.3.12. Water Consumption

3.3.13. Ranking of the FW Management and Treatment Methods

4. Conclusion

Declarations

Author Contribution

Data availability statement

References

Additional Declarations

Supplementary Files

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