Transitioning Hochschule Geisenheim University: A Shift from NET Source to NET Sink Regarding Its CO₂ Emissions

Abstract

Various Higher Education Institutions (HEIs) set themselves goals to become carbon neutral through the implementation of different reduction strategies such as the replacement of fossil-fueled vehicles with electric cars. However, even if all reduction measures are taken, residual GHG emissions will still remain. Therefore, most HEIs have to compensate for the remaining emissions by, for example, buying carbon credits. However, due to growing criticism of carbon credit purchases, HEIs need to explore options for establishing carbon sinks on their own premises to offset their remaining, unavoidable emissions. This study aimed to assess the CO₂ footprint of Hochschule Geisenheim University (HGU) as an exemplary HEI, identify emission hot-spots, and investigate the potential of biomass utilization for achieving carbon neutrality or even negative emissions. The analysis found that HGU’s main emissions were scope 1 emissions, primarily caused by on-site heat supply. The research determined that conversion to a wood chip-based heating system alone was insufficient to achieve climate neutrality, but this goal could be achieved through additional carbon dioxide removal (CDR). By operating a pyrolysis-based bivalent heating system, the study demonstrated that heat demand could be covered while producing sufficient C-sink certificates to transform HGU into the first carbon-negative HEI, at a comparable price to conventional combustion systems. Surplus C-sink certificates could be made available to other authorities or ministries. The results showed that bivalent heating systems can play an important role in HEI transitions to CO₂ neutrality by contributing significantly to the most urgent challenge of the coming decades: removing CO₂ from the atmosphere to limit global warming to as far below 2 °C as possible at nearly no extra costs.

1. Introduction

Higher Education Institutions (HEIs) play an important role in reaching the Sustainable Development Goals (SDGs) and integrating these into teaching and research [1,2]. Furthermore, HEIs should not only consider the SDGs theoretically in their core activities but also act accordingly in their own operations, as they have a role model function [3]. Among SDGs, combatting climate change is crucial, as climate change is a major barrier to achieving nearly all SDGs except SDG 17 (Partnership for the goals) [4]. Therefore, various universities have already set themselves the goal of becoming carbon neutral, for example, in the UK and Germany [5,6].

The CO₂ footprint of HEIs can differ substantially depending (besides other factors) on the selected time metric and functional unit, as well as the data collection boundary applied [7]. However, the review of Valls-Val and Bovea (2021), which analyzed 35 publications focusing on the CO₂ footprint of HEIs, showed that independently of these factors, scope 1 and 2 emissions represent a major emission hotspot for most of the HEIs assessed [7]. In accordance with the GHG protocol, the scopes encompass direct greenhouse gas (GHG) emissions caused by sources that are controlled or owned by the HEI (scope 1) and indirect GHG emissions that occur due to the generation of purchased electricity (scope 2) [8]. To reduce the scope 1 and 2 emissions of HEIs, several measures were proposed. A reduction in scope 1 emissions could, for example, be achieved through the replacement of fossil-fueled vehicles by electric cars [9]. As scope 2 encompasses the indirect GHG emissions caused by the generation of purchased electricity, several studies emphasize the importance of purchasing electricity from renewable sources or producing renewable energy on campus [10,11,12,13]. Another possible measure is a reduction in the electricity consumption of the HEI, for example, through the implementation of an energy management system [14].

However, even if all reduction measures are taken, residual GHG emissions will remain that are hard to avoid. Therefore, most HEIs must compensate for the remaining emissions by, for example, buying carbon credits that are generated by emission reduction projects somewhere else. This approach, however, has been criticized because it bears the risk of over-crediting the reduction projects or even incentivizing the production of waste gases to generate credits [15,16,17,18]. The latter means that there is a probability that purchased carbon credits will not truly lead to emission reductions. In agriculture, a large amount of biomass is produced annually, including crop residues like stalks and husks and pruning residues from fruit trees and grapevines, as well as other plant-based byproducts. These materials form a relatively easily usable source of energy and carbon that can be harnessed through various technologies [19]. HEIs with a focus on agriculture, viticulture, horticulture, or forestry, which often own and manage agricultural or forest land for research and education purposes, are in a unique situation regarding other options as they have waste biomass. Hence, these HEIs have the possibility to offset GHG emissions on their own premises, for example, through carbon sequestration in the form of living biomass, or organic carbon in the soil, as well as through the production and utilization of biochar (BC) or the use of silicate rock powder (enhanced weathering) [20,21].

One example of such an agricultural HEI is Hochschule Geisenheim University (HGU), which is located in the federal state of Hesse in Southwest Germany. HGU focuses on viticulture, horticulture, and landscape architecture research and education and has over 60 ha of open land, research areas, and parks. According to a resolution of the state government of Hesse from 2009, the state administration, including all public universities in Hesse, have to become climate neutral until 2030. By 2020, there was still a gap of 206,966 t CO₂, or even 357,788 t CO₂, if the purchasing of additional certificates and other market instruments were not taken into account [22].

Therefore, the question arises of how HGU can become carbon neutral without relying on external carbon offsets, but instead by using their own unique resource basis in the framework of a sustainable circular bioeconomy. To answer this question, the current study assessed in a first step scope 1, 2, and, as far as these are reported, scope 3 emissions of HGU. In addition, the available biomass resources were analyzed. We show that even in the best-case scenario, due to unavoidable emissions, the carbon footprint will not fall below 594 t CO₂eq per year. Therefore, carbon dioxide removal (CDR) technologies need to be implemented if both the objectives of the state for climate neutrality by 2030 in the administration and the federal goal of CO₂ neutrality by 2045 are to be met. This study identifies reduction potentials and develops cost-effective pathways to explore how HGU may become net CO₂ negative before the year 2030.

For this purpose, we investigate bivalent heating systems—configurations that combine two different heating technologies to optimize performance across varying load demands. In such systems, one technology typically serves as the base load provider (covering constant heating needs), while the second serves peak demand. This approach allows for optimized sizing and improved operational efficiency compared to single-technology solutions.

We include the investigation of pyrolyzing local residual biomass to generate thermal energy and biochar, a solid product [23]. Pyrolysis is a thermal process in which biomass is heated in the absence of oxygen and the resulting syngases (mainly CO₂, CO, H₂, and CH₄) and oils, with their relative proportions determined by feedstock characteristics, temperature, heating rate, and residence time. These products can be utilized as fossil fuel substitutes [24,25]. As no external oxygen is supplied to the process, most carbon undergoes aromatization and condensation rather than oxidation, resulting in stable carbonaceous structures [26]. Depending on the process design, the gases can also be condensed, resulting in a larger fraction of pyrolysis oil, and condensing the oil itself, leads to enhanced quality [27,28].

This process, known as pyrolysis with carbon capture and storage (PyCCS) or biochar carbon removal (BCR) [29] offers significant environmental benefits, especially when the biochar is applied in soils such as the reduction of N₂O emissions [30] and the creation of reliable and permanent carbon sinks [31,32]. In contrast to other CDR methods, this technology is permanent, almost irreversible, and, above all, technically mature today (technology readiness level TRL 9) [33,34].

The carbon sequestered in biochar can be quantified and verified through carbon sink certificates (C-sink certificates), which document the permanent removal of CO₂ from the atmosphere, as opposed to conventional carbon credits that typically focus on emission reductions rather than removal. These certificates follow strict measurement, reporting, and verification (MRV) protocols established by certification bodies [31] to ensure the permanence and legitimacy of carbon removal claims, making them particularly valuable for institutions seeking to address unavoidable emissions through verified carbon removal.

2. Materials and Methods

2.1. Study Design and Overview

A case study methodology combined with life cycle assessment principles, techno-economic modeling, and scenario analysis was employed to assess HGU’s potential transition from a CO₂ source to a CO₂ sink. The research followed a three-stage approach (Figure 1). First, a comprehensive analysis of the university’s current greenhouse gas emissions was conducted following the GHG Protocol guidelines, including scope 1–3 emissions (scope 3 where data was available). Second, the theoretical and technical biomass potential with a focus on woody residues from viticulture and horticulture was evaluated through field data and literature-derived calculations. To assess biomass availability, three spatial scenarios were established, comprising (a) the HGU activity area, (b) an extended area encompassing HGU and 3 municipalities, and (c) the Rheingau region.

As a third step, technical and economic feasibility analyses of different heating systems were performed, with particular attention being paid to hybrid solutions combining pyrolysis with conventional wood chip combustion. The environmental impact was assessed through carbon sink (i.e., BCR-) potential calculations according to European Biochar Certificate (EBC) methodology, while economic viability was evaluated using the levelized cost of energy (LCOE) approach. Both one-at-a-time and multivariate sensitivity analyses were conducted to test the robustness of the results under varying parameters.

2.2. Site Description and Infrastructure

Geisenheim University was founded in 1872 by Eduard von Lade as the “Royal College for Fruit and Wine Growing in Geisenheim”, with the first buildings dating back to this time. Over time, the university expanded, and since 2013, Geisenheim University has been established as a new type of technical university with PhD granting status. In 2022, the portfolio comprised more than 50 buildings of all types (from transformer housings to institute buildings) from different construction periods and with varying energy efficiency levels. Between 2024 and 2026, 5 new buildings will be added, including training, laboratory, and lecture hall buildings.

The property is divided into three energy supply clusters (Figure 2). The central campus (cluster CC) represents the largest cluster, generating the highest energy demand for both electricity and heat. This area includes 4500 m² of greenhouse cultivation area, the largest institute building with laboratories, the majority of administrative buildings and lecture halls, as well as the canteen and library. The viticulture/oenology institute buildings are located to the east (cluster VO), while the Department of Plant Breeding (cluster PB) is situated to the west, both featuring smaller lecture and laboratory facilities. Additional buildings on campus are supplied with heat and electricity on a decentralized basis. Each cluster contains one building with oil or liquified gas heating scheduled for replacement, though these are negligible regarding the CO₂ balance (<0.5% of scope 1).

Currently, almost 100% of heat is provided by fossil gas, generated centrally by boilers for each cluster. The heating system in CC will be modeled for renewable heat generation in this study. The other heating systems in clusters VO and GB are assumed to be switching to wood chips (WC) in 2029 due to their expected end of life. After generation, energy is distributed to individual buildings via local heating networks. The university operates four electrical transformer stations that step down the incoming medium voltage to low voltage levels required for building operations and laboratory equipment, one in each of the plant breeding and viticulture clusters, and two on the central campus.

The transmission infrastructure for heat (local heating network) and electricity (transformers and supply lines) is crucial for the university’s future energy supply, enabling reduced transmission losses and distribution of self-generated energy through photovoltaic systems on campus.

2.3. System Boundaries and Greenhouse Gas Accounting

The system boundaries for GHG accounting were defined spatially, temporally, and operationally. The spatial boundaries include all university-owned and -operated facilities within the main campus (approx. 60 ha), including buildings, technical infrastructure, agricultural areas (vineyards, orchards, experimental fields), campus greenhouses, and university-owned vehicles. The principles of GHG accounting were established in the Greenhouse Gas Protocol and shaped in the ISO 14064-1:2006, following three central principles: completeness (inclusion of all relevant sources), relevance (consideration of significant gases and activities), and comparability, accuracy, transparency and reproducibility [35,36].

Within these boundaries, all activities were categorized according to the GHG Protocol scope definitions:

• Scope 1: Direct emissions from university-owned facilities and vehicles;
• Scope 2: Indirect emissions from purchased electricity and district heating;
• Scope 3: Other indirect emissions, although it should be noted that scope 3 has not yet been recorded in sufficient detail to enable full reporting.

Calendar year 2019 was chosen as the reference year as 2020 and 2021 were characterized by the global COVID-19 pandemic and 2022 by the Russian war of aggression against Ukraine. Due to Germany’s dependence on Russian gas, this had a major impact on the supply situation and the global market price and resulted in federal legislative ordinances on energy saving. Osorio et al. [37] estimate that scope 3 emissions account for 37% of total emissions at higher education institutions. However, such percentage estimates of scope 3 emissions should be interpreted with caution as they are highly dependent on the magnitude of scope 1 and 2 emissions at individual institutions. Klein-Banai and Theis [38] found that an institution’s GHG emissions are a function of the size of the institution (building area and number of students), number of laboratories, and other factors. For this study, the CO₂ emission factors were taken from the GEMIS database and can be found in

Table 1. CO₂-equivalent emission factors and annual energy consumption at Hochschule Geisenheim University in 2019. LNG = liquified natural gas, RE = renewable energy, PV poly. = polycrystal photovoltaic.

Type	Emission Factor (kg CO2*kWh−1)	MWh Consumed (2019)	Database
Fossil gas	0.2378	8620	GEMIS 5.1
LNG	0.2378	27	GEMIS 5.0
Biomethane (manure/maize)	0.13274	0	GEMIS 5.0
Electricity (RE, hydropower)	0.0375	4325	Energy Provider
Electricity (PV poly.)	0.04	0	GEMIS 5.1
Electricity (mix 2019)	0.411	0	Statista
wood chips	0.0223	0	GEMIS 5.1

.

Due to local conditions, some emission sources are particularly relevant or negligible at HGU. For example, the fertile soils in Rheingau make additional fertilization in perennial crops like grapevine and fruits obsolete, so no additional nitrogen fertilizer has been applied since 2018. Conversely, around 15% of the campus’ heating demand is attributed to heating the greenhouses.

2.4. Biomass Assessment

The assessment of available biomass resources was conducted across three defined collection areas. The first collection area comprised exclusively the biomass available on the Geisenheim University premises and through its activities. The second collection area considered the biomass of the three directly neighboring municipalities of Rüdesheim, Geisenheim, and Oestrich-Winkel (approx. 2138 ha of vineyards). The third collection area included the total biomass of the “Rheingau” wine-growing region (3200 ha of vineyards).

The theoretical potential of biomass was determined based on dry matter (DM) by combining literature values and on-site pruning residue harvest determined in long-term trials by the Institute of Viticulture and the Institute of Plant Nutrition and Soil Science of Geisenheim University [24,39,40,41,42]. Technical potential was calculated accounting for physical collection losses of 19% during mechanical harvesting and baling operations (e.g., material left on the ground, losses during baling process) [41,43]. The calculation of the stem wood produced was based on a standing time of 25 years for the vineyards and orchards.

Additional biomass sources were evaluated from bundle wood collections, where non-compostable, woody branches and trunks up to a length of 1.5 m can be handed in by citizens. According to Richter and Raussen [44], this results in approx. 60 kg/inhabitant/year of material throughout Germany.

“Soft” biomass, such as pomace from wine production, is not considered in this study. In principle, anaerobic digestion of pomace in a biogas plant would enable energy production, but the space required is large, the investment costs high and the associated logistic flows impractical for the densely built-up university [45,46].

2.5. Biomass Utilization and Carbon Sink Potential

This study investigated the effects of utilizing local ligneous biomass in a pyrolysis plant on Geisenheim University’s carbon balance. The analysis assumed a biochar mass yield of 19% (w/w) at a pyrolysis temperature of 600 °C [47]. Biochar offers a wide range of utilization options. For example, biochar use in agriculture, composting, and animal husbandry (feeding, bedding) has already been extensively scientifically examined [21,23]. Industrial applications, such as admixture as an additive in concrete, cement, and asphalt, reduce the carbon footprint, can enhance material properties of the mixed products (or both), and are practiced by start-up companies [48,49].

During pyrolysis, approximately 50–70% of the feedstock carbon is converted to syngas or condensable vapors (pyrolysis oil), depending on the reactor type and process conditions. The non-condensable gases are subsequently combusted to generate heat and maintain the process, releasing biogenic CO₂ emissions [32]. The remaining carbon is stabilized in the solid biochar fraction, resulting in lower overall heat yield compared to conventional wood chip heating systems where the entire feedstock undergoes complete oxidation.

While pyrolysis is initially an endothermic process requiring energy input for startup, commercial systems can achieve substantial heat generation once operational. For this study, calculations were based on parameters from existing commercial pyrolysis units designed for regular operation, specifically the C500-I system by Biomacon, which converts biomass to heat with approximately 59% efficiency (ratio of nominal thermal output to feedstock energy content) [50].

However, the fixation of the carbon contained in the biomass through pyrolysis effectively enables CO₂ to be removed from the atmosphere. This is achieved by converting the CO₂ originally removed from the atmosphere by the plant into biochar, thereby fixing atmospheric carbon in a solid, persistent form [26]. Provided that it is ensured that the carbon fixed in the biochar does not return to the atmosphere (e.g., through combustion), it is possible to certify and trade the fixed CO₂ in the form of C-sink certificates [31]. These certificates can be sold in voluntary CO₂ markets or used to offset unavoidable emissions.

According to the calculation method for carbon sinks defined by the European Biochar Certificate [31] the C-sink potential for biochar produced at Geisenheim University was calculated. This calculation incorporated:

• Collection and baling diesel consumption;
• Transport diesel consumption;
• Chipping electricity demand;
• Carbon content of grapevine pruning biochar;
• Collection and transport carbon efficiency;
• Biochar production carbon efficiency (CE);
• Safety margins of 10%.

2.6. Heating System Analysis

The heating demand analysis was based on hourly load profiles, which were recorded and analyzed for the years 2018 to 2022. For system optimization, ordered annual load curves were generated to determine base and peak load requirements. For the comparative assessment, six system variants were analyzed. These comprised a fossil gas system (Reference System), a biomethane system (BM), a pure wood chip firing system (WC), a pure pyrolysis system (PY), and two hybrid systems combining pyrolysis base load with wood chip peak load boilers. The hybrid systems were configured as 1.5 MW pyrolysis with 3.0 MW wood chip (PY15/WC30) and 2.0 MW pyrolysis with 2.5 MW wood chip (PY20/WC25) capacity.

Operating parameters for all systems were derived from manufacturer specifications and validated using literature values from Möhren et al. [51]. The detailed parameters are provided in the Supplementary Materials, Table S1, Sheet ‘Technologies’.

Additionally, the analysis included a localized sourcing scenario in which 100% of the biomass feedstock was obtained within a maximum transportation radius of 10 km, thereby substantially reducing fuel costs associated with transportation. The economic analysis followed the methodology of DIN 2067 [52].

This methodology incorporates investment costs including base installation costs, peripheral equipment, and planning. Operating costs were determined by considering maintenance (3% of total investment annually) and fuel costs (0.05 EUR/kWh for wood chips purchased). Personnel requirements apply only in proportion to an increased effort in handling residual biomasses in PY scenarios. Additional revenue streams from carbon sink certificates, heat sales, and biochar market value were incorporated into the calculation. A period of 20 years was considered and prices were adjusted with an annual increase of 2%. The calculation sheet with detailed calculations and additional parameters are provided in Supplementary Table S1, Sheet ‘Calculations’.

The necessary prices for CO₂ to reach the EU’s emission reduction goals were derived from Pietzcker et al. [53] and revenues for the sequestration of carbon on the voluntary market for BCR were estimated according to Carbonfuture GmbH [54] to EUR 200 in 2026. The 2045 price of EUR 300 is in accordance with the mean of the projected price of a ton of CO₂ removed by direct air capture (DAC) [55]. The proposed system does not include revenues from the sale of biochar in the first five years, as this serves as an incentive for biomass suppliers to participate in the exchange system in the early years.

The operating costs consist of costs for maintenance and servicing, fuel supply, and CO₂ emissions; in the case of pyrolysis solutions, revenues from carbon sink trading are added. The decision variable is the heat generation price (EUR/MWh), which was calculated according to the widely used levelized cost of energy (LCOE) approach [56,57].

For sensitivity analysis, eight key parameters were identified and varied within defined boundaries as shown in

Table 2. Parameter ranges for one-at-a-time (OAT) sensitivity analysis of the PY20/WC25 hybrid heating system scenario. Upper and lower boundaries were established based on current market data and future projections. (*) CO₂ credit price variation applies exclusively to the pure wood chip (WC) scenario.

Parameter	Unit	Lower Boundary	Upper Boundary
Maintenance costs	%	−50%	50%
Price C-Sink Certificate	EUR	100	300
Price CO2 Credit *	EUR	50	190
Planning/Engineering overheads	%	−20%	20%
Price biochar	EUR	100	500
Price biomass	EUR	0.05	0.1
Heat production	MWh	4500	10,000
Share of locally sourced biomass	%	0%	100%

. Both one-at-a-time (OAT) and multivariate analyses were performed to assess result robustness.

2.7. C-Sink Calculation Scheme

CO₂ certificates usually certify the reduction of emissions compared to a reference scenario and thus contribute to the avoidance of emissions. A fully certified carbon sink guarantees the traceable storage of carbon at all times and results from the active removal of CO₂ from the atmosphere. CDR or negative emissions (NET) are vital to limit global warming to 2 °C [58]. Carbon sinks are created according to the following scheme:

• Removal of CO₂ from the atmosphere;
• Conversion of the carbon into a stable form;
• Storage in soil or materials.

To calculate the carbon footprint of biochar produced at the university, the European Biochar Certificate (EBC) was developed in 2020 in Switzerland as a methodology to determine the sink potential [31]; EBC C-sink is now hosted by Carbon Standards International (1). Following the measurement, reporting, and verification (MRV) principles, C-sink certificates are tradable on the voluntary carbon market.

(1)

https://www.carbon-standards.com/de/home

In fact, of the top 40 companies delivering CDR, 30 were biochar producers (https://www.cdr.fyi/leaderboards, accessed on 7 January 2025).

2.8. Sensitivity Analysis

To assess the robustness of the economic analysis, both one-at-a-time (OAT) and multivariate sensitivity analyses were conducted. For the OAT analysis, eight parameters were identified as potentially influential factors affecting the levelized cost of energy (LCOE). The parameter ranges for the analysis were defined based on current market data and future projections (Table 2). The PY20/WC25 scenario was selected as the reference case for detailed analysis, as it achieved the highest carbon sequestration rate of 1.656 t CO₂eq*year⁻¹ while maintaining heat production costs at the same level as the wood chip reference scenario, representing an optimal compromise between environmental and economic objectives.

For the multivariate analysis, parameter combinations were systematically varied within their defined ranges to investigate potential interaction effects. The complete analysis methodology and parameter boundaries are documented in the Supplementary Materials.

3. Results

3.1. Carbon Footprint Analysis

The analysis of Geisenheim University’s carbon footprint revealed that heat generation was the dominant source of emissions throughout the observation period (

Table 3. Annual greenhouse gas emissions of Hochschule Geisenheim University from 2018 to 2022, categorized by emission scopes according to Section 2.3. Values are presented in t CO₂eq*year⁻¹, with percentage distribution across scopes. Institutional metrics including student numbers, employee count, and facility area are provided for contextual reference.

Scope		2018	%	2019	%	2020	%	2021	%	2022	%
1	Heat generation	1965		2071		2023		2179		1628
1	Vehicle Fuels	99	90.3	100	87.2	71	94.2	70	95.0	71	90.9
2	Electricity	128	5.6	162	6.5	117	5.3	110	4.7	118	6.3
3	Air travel	86		147		8		3		46
	Water	6	4.0	11	6.3	5	0.6	4	0.3	5	2.7
	Total	2285		2502		2234		2366		1868
	Students	1655		1750		1750		1750		1750
	Employees	404		450		542		542		542
	area (m2)	50,579		50,579		50,579		50,579		50,579

). Despite increasing student and employee numbers, total emissions showed a declining trend from 2019 to 2022. This reduction was particularly pronounced in 2022, mainly due to decreased heating energy consumption following the implementation of energy-saving measures in response to the energy price crisis/the Ukrainian war. The pandemic years 2020 and 2021 showed significantly reduced scope 3 emissions due to travel restrictions.

These findings identify heat generation as the key leverage point for achieving the university’s emission reduction goals.

3.2. Biomass Availability

The assessment of biomass resources across the three defined collection areas revealed substantial differences in potential availability (

Table 4. Technical biomass potential from viticulture residues and municipal biomass collection across Rheingau region municipalities. Data includes municipality characteristics (population, total area), vineyard area, and calculated biomass availability from different sources. All biomass values are reported as dry matter (DM) in metric tons per year. n.a. = not applicable.

Municipality	Inhabitants	Total Area (km2)	Vinyard Area (ha) *	Biomass Viticulture (t)	Mun. Biomass Collection (t)	Biomass Total (t)
HGU	n.a.	n.a.	33	68	76	144
Rüdesheim	10,054	51.41	652	1344	302	1646
Geisenheim	11,699	40.34	512	1055	351	1406
Oestrich-Winkel	11,873	59.51	1019	2100	356	2457
Subtotal 3 municipalities		151	2183	4567	1009	5651
Kiedrich	4075	12.34	157	323	122	445
Eltville	8476	10.08	128	264	254	518
Martinsthal	1226	4.73	60	124	37	160
Rauenthal	1800	7.27	92	190	54	244
Erbach	3429	12.69	161	332	103	435
Hattenheim	2181	12.00	152	314	65	379
Walluf	5523	6.75	86	176	166	342
Lorch	4017	54.43	182	375	121	496
Total Rheingau (all municip.)		272	3200	6664	1931	8670

* = If there were no data available, the cultivation area was estimated based on a municipality’s total area as a share of the total area of the Rheingau.

).

For vineyards, the long-term biomass yield was calculated as 2.12 t DM*ha⁻¹*year⁻¹ of pruning residues, minus 19% harvesting losses, plus 8.6 t DM*ha⁻¹ of stem wood from vineyard replacement every 25 years. This resulted in an average annual technical potential of 2.06 t DM*ha⁻¹*year⁻¹ for vineyard areas. These values represented long-term averages from multi-year field trials, and unlike annual crops, perennial vineyards exhibited minimal seasonal fluctuations in biomass production, providing a reliable and consistent feedstock source.

The university grounds alone provided a technical biomass potential of 144 t DM*year⁻¹. Expanding the collection radius to include the three neighboring municipalities of Rüdesheim, Geisenheim, and Oestrich-Winkel increased the technical biomass potential to 5651 t DM*year⁻¹. The full Rheingau region showed a technical biomass potential of 8670 t DM*year⁻¹.

These findings indicate that biomass availability within a 10 km radius of the university campus is sufficient to sustain the proposed heating systems, with the potential to establish multiple comparable units before encountering biomass supply limitations. The proximity of the biomass sources to the university ensures favorable transport logistics and maintains low associated emissions.

3.3. Heating System Performance

Analysis of the ordered load profiles revealed that the heating demand rarely reached maximum capacity. The peak load of 3.24 MW occurred only once during the observation period in 2021 (

Table 5. Historical heating load analysis and proposed generation allocation for the central campus cluster (2018–2022). Data show power demand distribution and corresponding energy consumption across load ranges, with mean values and proposed technology assignment (PY = pyrolysis, WC = wood chip combustion). All power values in kW, and energy values in kWh. n.a. = not applicable.

	2018	2019	2020	2021	2022	Mean	Proposed
Power	Energy	Energy	Energy	Energy	Energy	Energy	Generation
500	630,157	624,149	750,404	453,636	629,973	617,664	PY
1000	1,356,316	1,556,154	1,670,776	1,663,317	1,616,567	1,572,626	PY
1500	2,330,150	2,565,807	2,450,804	2,628,596	1,731,281	2,341,328	PY
2000	1,333,699	1,222,191	914,787	1,303,106	629,572	1,080,671	PY
3000	316,658	228,003	43,074	212,201	40,068	168,001	WC
4500	0	0	0	3245	0	649	WC
Total energy	5,966,980	6,194,804	5,829,846	6,264,100	4,647,460	n.a.	n.a.
Min power	0	0	0	0	0	n.a.	n.a.
Max power	2743	2866	2469	3245	2457	n.a.	n.a.
Av. power	682	707	666	715	531	n.a.	n.a.
Med. power	575	654	602	739	413	n.a.	n.a.

), while 90.55% of the heating demand was below 1.5 MW (Figure 3).

3.4. Optimized Heating System

The comparative analysis of different heating systems revealed distinct performance profiles (

Table 6. Technical–economic comparison of heating system alternatives following DIN 2067 methodology. Analysis includes system specifications, investment requirements, operational parameters, and environmental impact metrics across different technology configurations. PY = Pyrolysis, WC = Wood Chips, BM = Biomethane, * water content. n.a. = not applicable.

	Reference	BM	WC	PY45	PY10/WC35	PY20/WC25	PY20/WC25 (II.)
Plant 1	Cond. boiler	Cond. boiler	wood chip boiler	PY plant	PY plant	PY plant	PY plant
Hybrid System	no	no	no	no	yes	yes	yes
Plant 2	n.a.	n.a.	n.a.	n.a.	WC boiler	WC boiler	WC boiler
Plant 1 power (kW)	4500	4500	4500	4500	1000	2000	2000
Plant 1 energy (MWh)	6150	6150	6150	6150	2200	5600	5600
Plant 2 Power (kW)	n.a.	n.a.	n.a.	n.a.	3500	2500	2500
Plant 2 energy (MWh)	n.a.	n.a.	n.a.	n.a.	3950	550	550
Local fuel % (residues)	0%	0%	0%	0%	0%	35%	100%
Energy source plant 1	natural gas	biomethane	wood chips	wood chips	wood chips	35% local bm	local bm
Energy source plant 2	n.a.	n.a.	n.a.	n.a.	wood chips	wood chips	local bm
Period of use (a)	20	20	20	20	20	20	20
Investment per kW/EUR	141.37	141.37	594.93	1225.00	734.95	874.96	874.96
Total investment/EUR	1,463,180	1,463,180	6,157,548	12,678,750	7,606,704	9,055,860	9,055,860
Total project costs/EUR	23,127,425	24,183,942	24,321,639	35,530,299	27,783,204	24,475,103	16,308,901
Amortization (a)		>20	>20	>20	>20	>20	18.6
LCOE (EUR/MWh)	188	197	198	289	226	199	133
Emissions Plant 1 (t CO2eq.)	1746	938	109	−1769	−633	−1611	−1611
Emissions Plant 2 (t CO2eq.)	0	0	0	0	70	10	10
Total emissions (t CO2eq)	34,921	18,767	2171	−35,380	−11,262	−32,022	−32,022
Biochar produced (t/a)	n.a.	n.a.	n.a.	701	251	638	638
Biomass demand t/a (@20%) *	n.a.	n.a.	1855	2673	2148	2600	2600

Abbreviations: as above, PY10/WC35 = bivalent system of 1000 kW Pyrolysis and 3500 kW Wood Chip, PY20/WC25 = bivalent system of 2000 kW Pyrolysis and 2500 kW Wood Chip, PY20/WC25 (II.) = biomass is delivered according to the system proposed.

). All pyrolysis-based systems demonstrated significant carbon dioxide removal potential, though their economic performance varied. The reference fossil gas and biomethane (BM) systems, despite being technically simple, showed LCOE of 188 and 197 EUR/MWh respectively. Pure wood chip firing (WC) achieved 198 EUR/MWh, while pure pyrolysis (PY) reached 287 EUR/MWh but provided the highest carbon removal at −36,376 t CO₂eq.

Hybrid systems combining pyrolysis with wood chip boilers showed improved performance characteristics. The smaller hybrid configuration (PY10/WC35) achieved a carbon removal of −11,619 t CO₂eq but at an above-average LCOE of 225 EUR/MWh. The larger hybrid system (PY20/WC25) emerged as optimal, removing −32,929 t CO₂eq while maintaining an LCOE of 198 EUR/MWh when partially supplied with residual biomass—comparable to the pure wood chip system.

The economic performance improved substantially when operating with locally sourced biomass (PY20/WC25 II), reducing LCOE to 131 EUR/MWh. This configuration requires approximately 2600 t of annual biomass input to produce 638 t of biochar, aligning with the identified local biomass availability.

3.5. C-Sink Calculation

According to the calculation method for carbon sinks defined in [31], the C-sink potential for biochar produced at Geisenheim University was calculated to be 70.75%. For parameters used see

Table 7. Parameters and emission factors used in carbon sink potential calculations for biochar production from vineyard pruning residues. Values include operational energy requirements, carbon content specifications, and efficiency factors according to the European Biochar Certificate methodology [31]. CE = carbon expenditure. n.a. = not applicable.

Parameter	Type	Unit	Amount	Source
collecting and baling	diesel	liter	5.5	[59]
transport 10 km	diesel	liter	8.6	[59]
chipping	electricity	kWh	30	own measurements
Carbon content grapevine prunings	biochar	%	75	[24,60]
CE collection and transport	n.a.	%	1.58	Supplementary Materials, Table S1, Sheet ‘C-Sink Potential’
CE production biochar	n.a.	%	2.26	Supplementary Materials, Table S1, Sheet ‘C-Sink Potential’
CE safety margin	n.a.	%	0.38	Supplementary Materials, Table S1, Sheet ‘C-Sink Potential’

; the entire calculation is provided in the Supplementary Materials, Table S1, sheet ‘C-Sink potential’. This means that after calculating the carbon expenditure (CE) for providing the biomass and producing the biochar, 1000 kg of BC contains 707.5 kg of net sequestered carbon or 2594 kg CO₂eq of tradeable C sinks. Depending on the capacity of the pyrolysis plant, this results in up to 1656 t C-sink certificates or 638 t of BC annually. The certification of the C-sinks can be achieved through a contractual agreement with the biomass supplier. He receives an equivalent in biochar for the biomass supplied, which must then be mixed with pomace or co-composted and incorporated into the supplier’s agricultural soil to convert the sink potential into a verified C-sink.

3.6. Economic Analysis and Sensitivity Assessment

The economic feasibility analysis revealed significant variations in investment requirements and operating costs across the systems. Initial investments ranged from 141 EUR/kW for conventional systems to 1225 EUR/kW for pyrolysis-based configurations, resulting in total investments of between EUR 1.5 and 12.7 million. The amortization period of 18.5 years for the PY20/WC25 systems reflects the significant initial investment but demonstrates long-term economic viability when considering the complete lifecycle costs and revenues.

The system’s revenue streams are derived from three main sources: reduced fuel costs through biomass utilization, sales of certified carbon removal certificates, and marketing of the produced biochar. These revenue components significantly influence the overall economic viability of the system.

The sensitivity analysis identified the share of locally sourced biomass and heat production as the most influential parameters affecting the LCOE (Figure 4). A shift from 0% to 100% local biomass resulted in an LCOE reduction of 77 EUR/MWh from the base case. Similarly, increasing heat production from 4500 to 10,000 MWh/year, decreased the LCOE by 73 EUR/MWh. Other parameters showed less significant impacts: planning and engineering overheads demonstrated a moderate impact range of −25 to +42 EUR/MWh, while maintenance costs showed the lowest sensitivity with deviations between −15 and +13 EUR/MWh from the base case.

The surface plot (Figure 5) demonstrates the combined effect of heat production and locally sourced biomass share on the LCOE. The lowest LCOE values (76 EUR/MWh) were observed at maximum heat production (10,000 MWh) and 100% locally sourced biomass, while the highest values (256 EUR/MWh) occurred at minimum heat production (5500 MWh) and 0% locally sourced biomass. A clear gradient can be observed, showing that increasing either parameter leads to improved economic performance, with the steepest improvements occurring in the transition from 0% to 50% local biomass share.

For the multivariate analysis, more conservative assumptions were applied to test system robustness. These included additional infrastructure costs of EUR 1,000,000 for increased heat production capacity and lower revenue projections from carbon sink certificates (EUR 100 fixed instead of increasing to EUR 300) and biochar sales (200 EUR/t). Even under these conservative conditions, the analysis revealed that the lowest LCOE values (66 EUR/MWh) were achieved with maximum heat production and 100% locally sourced biomass, while the highest values (248 EUR/MWh) occurred at minimum heat production and 0% locally sourced biomass.

3.7. Reduction Pathway

As can be seen in Table 3, the purchase of (renewable) electricity only accounts for around 4.7–6.5% of the carbon footprint. With a factor of 0.0375 kg CO₂ *kWh⁻¹ from the university’s energy contractor, measures like the expansion of PV generation capacities, which make sense from an economic and sustainability perspective, have no relevant influence on the CO₂ balance and thus were not the objective of this study. By far the largest proportion is influenced by the generation of heat. Accordingly, only the carbon-relevant measures are dealt with in this section. The measures shown in Figure 6 are briefly described in the following.

Neither the biomethane nor the wood chip scenario were able to reduce the university’s CO₂ balance to near zero, leaving 594 t of unavoidable CO₂ emissions, with 274 t in scope 1, and 162 t and 158 t in scopes 2 and 3, respectively. This clearly contravenes the Hessian state government’s plan for achieving CO₂-neutral state administration by 2030 and, in view of the time horizon left for the use of heat generators (20 years), most likely also contravenes the German climate targets for CO₂ neutrality by 2045. Since PY20/WC25 is the most cost-effective solution, the bivalent system should be selected in view of the only slightly higher sink capacity of the “pure” PY variant.

3.7.1. Electrification of Vehicle Fleet

The electrification of the university fleet has the potential to reduce CO₂ emissions by 70 to 100 t annually within scope 1. However, this transition is expected to incur a marginal increase of 8 t within scope 2, attributable to the increasing electricity consumption associated with the process. In the immediate future, the feasibility of electrification is primarily applicable to the university’s car fleet, with the substitution of heavy machines like tractors being achievable in the mid-term. Given the prevalence of smaller agricultural machinery in viticulture and fruit growing, promising solutions exist for electrified tractors (e.g., Fendt e100 Vario, Monarch MK-V) to commence operations in the late 2020s and be fully deployed in the 2030s.

3.7.2. Avoidance of Medium-Haul Flights

The COVID-19 pandemic has made it clear that entire conferences can also be held online. Assuming that half of medium-haul flights and a third of long-haul flights are canceled, a saving of 67 t CO₂ can be achieved within scope 3.

4. Discussion

4.1. Key Findings

This study demonstrates that higher education institutions with access to agricultural and municipal residual biomass can establish economically viable carbon removal systems while meeting their heating demands. The proposed hybrid pyrolysis–wood chip system achieves three crucial objectives simultaneously: it provides renewable heat generation, creates certified and tradeable carbon sinks, and produces valuable biochar for local agricultural applications. Most notably, when operated with locally sourced biomass, the system achieves lower levelized costs of energy (132 EUR/MWh) compared to conventional heating systems while removing substantial amounts of CO₂ from the atmosphere (−32,929 t CO₂eq over service life). This shows that BCR technology can be implemented cost-effectively when integrated into existing infrastructure needs.

4.2. Comparison with Similar Studies

The findings can be compared with and extended upon previous research on carbon neutrality initiatives in higher education institutions. The transition of Leuphana University Lueneburg towards climate neutrality was documented by Opel et al. [5], where significant emission reductions through conventional measures were achieved. In this study, however, it is demonstrated that, beyond carbon neutrality, a carbon-negative status can be achieved through innovative technological integration.

In the economic analysis by Latter and Capstick [6], where UK universities’ climate emergency declarations were examined, it was found that most institutions struggle with the financial feasibility of carbon reduction measures. In contrast, it is demonstrated by our hybrid pyrolysis–wood chip system that cost competitiveness (132 EUR/MWh with local biomass) can be achieved, while additional carbon removal benefits are provided, indicating a viable pathway for institutions with access to biomass resources.

Scope 1 emissions, particularly from heating, were identified as a major challenge in the comprehensive review of Valls-Val and Bovea [7] of 35 higher education institutions’ carbon footprints. These findings are confirmed by our observations, but it is uniquely demonstrated how these emissions can be transformed into carbon sinks through pyrolysis technology. This approach differs from conventional offsetting strategies that were criticized by Haya et al. [15], as verifiable, permanent carbon removal within the institution’s operational boundary is created.

The economic viability of the proposed system (18.5-year amortization period) can be favorably compared with other institutional carbon reduction measures. Longer payback periods for conventional renewable energy installations at universities were reported by Mendoza-Flores et al. [9]. However, it is demonstrated by this study that the business case can be improved through the integration of heat generation with carbon removal while environmental benefits are delivered by the use of biochar in agriculture such as reduced nitrate leaching to groundwaters or reduced nitrous oxide emissions [30]. Such indirect effects on GHG balances were not part of this assessment.

This work also contributes to the broader discussion of carbon dioxide removal (CDR) implementation pathways. While Young et al. [55] project high costs for direct air capture technologies (USD 200–600/t CO₂), our pyrolysis-based approach achieves removal at lower costs while providing additional benefits through heat generation and biochar utilization. This supports Werner et al.’s [29] assertion that biomass pyrolysis systems offer significant potential for limiting global warming to 1.5 °C.

4.3. Transferability to Other Higher Education Institutions

The transferability of the pyrolysis-based approach depends primarily on biomass availability, infrastructural requirements, and institutional circumstances.

Institutions with agricultural, horticultural, or forestry programs possess a natural advantage due to their access to residual biomass. However, other HEIs could explore alternative sources such as landscaping waste from campus grounds or partnerships with local municipalities for green waste collection and processing. The technical potential identified at Geisenheim University (144 t DM*year⁻¹ from university grounds alone) suggested that even modest biomass collection programs could support smaller-scale implementations.

Institutions with existing centralized heating systems offer more favorable conditions for the integration of pyrolysis technologies. For universities without such infrastructure, modular units operating at smaller scales could provide an alternative pathway, with commercial systems now available in capacities ranging from 50 kW to 5 MW thermal output.

Urban campuses with limited biomass access could establish partnerships with municipal waste management systems, participate in regional biomass utilization networks, or implement smaller demonstration units while pursuing alternative carbon neutrality strategies.

As demonstrated in the sensitivity analysis, locally sourced biomass significantly improved economic performance, suggesting that proximity to biomass resources remained a critical success factor for successful implementation at other institutions.

Another transferability pathway might emerge through new business concepts like carbon neutrality contracting. Institutions with less favorable conditions for direct implementation could benefit from purchasing carbon-neutral heat as a service from specialized providers operating pyrolysis-based heating systems. This approach would allow HEIs to achieve climate goals without requiring the technical expertise or biomass access needed for on-site implementation while creating regional economic opportunities for agricultural institutions to monetize their carbon removal capabilities beyond their own needs.

4.4. Cost and Price Estimations

The economic viability of CDR systems faces significant uncertainties regarding future price developments. Current forecasts for carbon removal costs vary widely between USD 100 and 600 per ton of CO₂eq [55]. While optimistic studies project prices below USD 100, such scenarios could create problematic market incentives if removal costs fall below emission costs [58]. Our sensitivity analysis demonstrates that the system’s economic viability is less dependent on carbon prices than previously assumed, with local biomass sourcing and heat utilization being the key economic drivers. The cost calculations following DIN 2067 may be conservative, particularly regarding maintenance costs and peripheral equipment for pyrolysis systems, as they are derived from conventional heating systems.

4.5. Technical and Methodological Limitations

Several methodological and data-related limitations should be considered when interpreting the results of this study. The biomass availability assessment relies on literature values and limited field measurements, which may not fully capture local variations in biomass productivity [19,41]. While pruning residue quantities were validated through long-term trials at HGU, the technical collection potential could vary significantly based on vineyard management practices and actual collection efficiency [40,61]. The assumed collection loss of 19% represents an average value that may fluctuate seasonally [39,62].

The establishment and maintenance of reliable biomass supply chains presents additional challenges. Initial stakeholder communications indicate strong interest in the circular biochar utilization model, as participants would benefit from reduced disposal costs and improved soil quality through biochar application; however, the model requires consistent feedstock quality standards [23,63]. A particular consideration in viticulture-derived feedstocks is the presence of copper from plant protection treatments, which are commonly applied in both conventional and organic vineyard management. Analysis of pruning residues showed copper concentrations between 8.5 and 19.2 mg*kg⁻¹. While these concentrations are expected to increase during pyrolysis due to mass reduction and element conservation, the projected copper content in the resulting biochar would remain below the regulatory threshold of 70 mg*kg⁻¹ [64,65].

The successful operation of the system depends on establishing effective quality control systems and biochar application protocols that comply with evolving regulatory frameworks.

Our economic analysis is based on current market prices and technological parameters, with projections extending to 2045. While sensitivity analyses were conducted, long-term price developments for all carbon removal certificates, biochar, and other resources remain uncertain. The investment cost calculations for pyrolysis systems are derived from conventional heating system standards (DIN 2067), which may not fully capture specific maintenance requirements or peripheral equipment needs of pyrolysis technology.

While current German regulations on biochar soil application are more restrictive than EU standards, the system’s biochar will be produced at >550 °C from pruning residues and is expected to result in an H/C_org ratio of 0.17, thus meets internationally recognized stability criteria [24,66,67].

4.6. Risk of Mitigation Deterrence and Increased Macroeconomic Costs

The deployment of the sink option by BC or any other CDR technology generally poses the risk of mitigation deterrence [68]. In particular, the petrochemical industry employs circular carbon strategy approaches to mitigate the need for ambitious emission reductions [69]. Governments that endorse technological openness and rely on future measures, rather than actively shaping pathways toward a far below 2 °C future, risk burdening the economy and society with unnecessarily high costs through their policy of postponement [70,71].

5. Conclusions

The implementation of carbon sinks has been identified as indispensable for atmospheric carbon dioxide removal. Higher education institutions and other public institutions can play an important role as ideal testing grounds for sustainable transitions, combining both institutional responsibility and technical capabilities.

The results demonstrate that heat production, carbon sink certificate generation, and biochar creation from local biomass can be achieved while maintaining economic viability at Geisenheim University. Although CDR implementation costs currently exceed conventional emission offsetting, this difference maintains incentives for emission reduction measures, ensuring that carbon sinks are reserved for genuinely unavoidable emissions.

Several research priorities have been identified for future investigation. Governmental public institutions need to develop a comprehensive understanding of carbon sinks to facilitate their timely integration into respective net-zero strategies. Investigations of synergies with additional institutional sustainability initiatives and scalability assessments for broader public institution implementation have been determined as necessary next steps.

The findings align with both Hesse’s state objectives for climate-neutral administration by 2030 and federal neutrality goals by 2045, providing an evidence-based implementation framework for other institutions. Our results demonstrate that economic viability and ambitious climate action can be achieved through integrated technological solutions.