Nitrogen- and climate impact-based metrics in biomass supply chains
Lidija Čučeka,*, Jiří Jaromír Klemeša, Zdravko Kravanjab
a
Centre for Process Integration and Intensification (CPI2), Research Institute of Chemical and Process
Engineering, Faculty of Information Technology, University of Pannonia, Egyetem utca 10, 8200
Veszprém, Hungary
b
Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova ulica 17, 2000
Maribor, Slovenia
cucek@cpi.uni-pannon.hu
Published in Computer Aided Chemical Engineering (2014), Volume 34, Pages 483-488
Summary
Over several decades of the past, and especially nowadays, there has been widespread awareness
regarding environmental burdening, especially due to CO2 emissions. There are numerous regulations
and targets that are intended to improve the quality of the environment. However, there is much lower
awareness regarding the other important emissions and their consequences, such as e.g. nitrogen,
water, and phosphorus footprints. This contribution presents the importance of currently lesser-known
nitrogen footprints in addition to the highly popular indicators of global warming and climate change.
Trade-offs between these environmental metrics are evaluated in terms of their burdening and
unburdening effects which together form total effects. Two case studies are applied for considering
biomass energy supply chains. These case studies indicate that global warming potential and also
carbon footprint are positive in terms of total effects. Nitrogen footprint is, on the other hand, usually
negative and brings a significant accumulation of detrimental reactive nitrogen to biomass supply
chains.
Background
Global warming and climatic changes are generally considered as dangerous environmental threats for
the 21st century (Abbott, 2008). These threats are often associated with greenhouse gas (GHG)
emissions mainly simplified to CO2 from the burning of fossil-based energy and deforestation.
However, considering just carbon footprint or global warming potential may result in underestimating
other burdens, as is demonstrated in this paper. The human creation of reactive nitrogen and its
destructive effects on the environment and human health (N-Print Team, 2011) has so far been
insufficiently accepted by the public. Nutrient pollution is namely one of the more costly and
challenging environmental problems (EPA, 2012). The main issue relating to nitrogen footprint is in
its non-point sources and therefore it is difficult to measure and regulate (Carpenter et al., 1998).
Aims
This paper stresses the importance of considering nitrogen-based metrics in addition to the carbonbased metrics. Life Cycle Assessment (LCA) is used to account for those metrics associated with all
the life-cycle stages. The total effects (Kravanja and Čuček, 2013) are considered, which are defined
as the difference between burdening and unburdening effects. The burdening effects of systems on the
environment represent burdens related to the whole life-cycle of the system from the extraction of
resources to the final disposal of products – conventional LCA analysis approach. The unburdening
effects are those effects that indirectly unburden or benefit the environment (Kravanja and Čuček,
2013), e.g. when environmentally harmful waste is utilised rather than being deposited, or harmful
Suggested citation: Čuček, L., Klemeš, J. J., & Kravanja, Z. (2014). Nitrogen- and Climate Impactbased Metrics in Biomass Supply Chains. In Mario R. Eden, John D. Siirola & Gavin P. Towler
(Eds.), Computer Aided Chemical Engineering (Volume 34, pp. 483-488): Elsevier.
products are substituted by green ones. Two demonstration case studies on renewable energy
production from biomass are performed which show importance of dealing with nitrogen footprints.
Methods
Global warming potential and carbon and nitrogen footprints evaluation are demonstrated by two
cases, biogas production from animal waste (Drobež et al., 2011), and by regional biomass energy
supply chains (Čuček et al., 2010). Those case studies on energy generation from biomass consider the
total effects (Kravanja and Čuček, 2013) on the environment. Environmental metrics were mostly
obtained using the LCA software GaBi® (PE, LBP, 2011) and the Ecoinvent database (Frischknecht et
al., 2007). Those demonstration cases are based on multi-objective optimisation framework (Čuček et
al., 2014), on the mixed-integer linear programming (MILP) synthesis. The profit is maximised as the
main criterion, whilst the environmental metrics are minimised as additional criteria. A whole range of
profit and environmental metrics’ solutions is obtained (4-dimensional (4-D) Pareto projections).
Functional unit for environmental assessment is defined as the solution at the maximal economic
profit.
Results
The environmental metrics for two demonstration case studies (biogas production and regional
biomass energy supply chains) are evaluated in terms of total effects. Figure 1 shows the entire range
of profits and environmental metrics solutions (4-D Pareto projections) for biogas production and
regional biomass energy supply chains.
a)
b)
Figure 1: The entire range of profit and environmental metrics for a) biogas production, b) regional
biomass energy supply chain
It can be seen from Figure 1 that for biogas production almost all the solutions are positive from the
sustainable development viewpoint. The environmental metrics are mostly negative (positive for the
environment), whilst profit is positive. All the environmental metrics decrease and therefore improve
when increasing the profit.
However, regarding regional biomass energy supply chains the most profitable solutions are obtained
by the lowest carbon footprint and global warming potential, whilst by the highest nitrogen footprints.
Therefore, by improving the profit, better solutions in terms of global warming and climate change are
obtained, but worse in terms of reactive nitrogen accumulation. Several solutions are even obtained
that have worse carbon footprint even with higher profits. Also, it can be seen that the range of optimal
solutions is greater than that of the biogas supply chain. The reason is that several technologies could
be selected which could use various biomass sources.
Suggested citation: Čuček, L., Klemeš, J. J., & Kravanja, Z. (2014). Nitrogen- and Climate Impactbased Metrics in Biomass Supply Chains. In Mario R. Eden, John D. Siirola & Gavin P. Towler
(Eds.), Computer Aided Chemical Engineering (Volume 34, pp. 483-488): Elsevier.
Acknowledgments
The authors acknowledge the financial supports from Slovenian Research Agency (Program No. P20032), from the EC FP7 project ENER/FP7/296003/EFENIS ‘Efficient Energy Integrated Solutions
for Manufacturing Industries – EFENIS’, and from the Hungarian State and European Union under the
TAMOP-4.2.2.A-11/1/KONV-2012-0072 “Design and optimisation of modernisation and efficient
operation of energy supply and utilisation systems using renewable energy sources and ICTs“.
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Suggested citation: Čuček, L., Klemeš, J. J., & Kravanja, Z. (2014). Nitrogen- and Climate Impactbased Metrics in Biomass Supply Chains. In Mario R. Eden, John D. Siirola & Gavin P. Towler
(Eds.), Computer Aided Chemical Engineering (Volume 34, pp. 483-488): Elsevier.