Environmental assessment Ämmässuo landfill (Finland) by means of LCA-modeling (EASEWASTE)
Department of Energy and Environmental Technology, Lappeenranta University of Technology, Lappeenranta, Finland. Waste Management & Research
(Impact Factor: 1.3).
06/2009; 27(5):542-50. DOI: 10.1177/0734242X08096976
The Old Ammässuo Landfill (Espoo, Finland) covers an area of 52 hectares and contains about 10 million tonnes of waste that was landfilled between 1987 and 2007. The majority of this waste was mixed, of which about 57% originated from households. This paper aims at describing the management of the Old Ammässuo Landfill throughout its operational lifetime (1987-2007), and at developing an environmental evaluation based on life-cycle assessment (LCA) using the EASEWASTE-model. The assessment criteria evaluate specific categories of impact, including standard impact categories, toxicity-related impact categories and an impact categorized as spoiled groundwater resources (SGR). With respect to standard and toxicity-related impact categories, the LCA results show that substantial impact potentials are estimated for global warming (GW), ozone depletion (OD), human toxicity via soil (HTs) and ecotoxicity in water chronic (ETwc). The largest impact potential was found for SGR and amounted to 57.6 person equivalent (PE) per tonne of landfilled waste. However, the SGR impact may not be viewed as a significant issue in Finland as the drinking water is mostly supplied from surface water bodies. Overall, the results demonstrate that gas management has great importance to the environmental performance of the Old Ammässuo Landfill. However, several chemicals related to gas composition (especially trace compounds) and specific emissions from on-site operations were not available or were not measured and were therefore taken from the literature. Measurement campaigns and field investigations should be undertaken in order to obtain a more robust and comprehensive dataset that can be used in the LCA-modelling, before major improvements regarding landfill management are finalized.
Available from: Montse Meneses
- "roved that site - specific data are essential for consistent data . Additionally , the results for global warming of the scenario ' land - fill ' and scenario 5 ' landfill with 20% recycling ' could have less environmental burden as it can be assumed that there is a lower production of biogas under Siberian versus European climatic con - ditions . Niskanen et al . ( 2009 ) also confirmed that a detailed data - set about special parameters such as gas composition or gas production from the landfill , which can be entered in the LCA model need to be obtained in order to get reliable results . Thereafter , improvement of the landfill can be planned . The time period cho - sen for the landfilling process al"
[Show abstract] [Hide abstract]
ABSTRACT: Khanty-Mansiysk Autonomous Okrug - Ugra in Siberia has recently started to play a major role in the Russian economy because key oil and gas extraction sites are located in this region. As a result, the extensions of infrastructure and higher incomes have been leading to an accelerated population growth and consequent increase in the generation of solid household waste. The current methods of waste disposal have now reached their limits, especially in the towns Khanty-Mansiysk and Surgut. The key objectives of this study were to identify the influence of waste composition and transport routes on the life cycle assessment (LCA) results and to assess the current waste treatment option for solid household waste and to compare it with proposed scenarios. Furthermore, recommendations for an optimal use of LCA within a decision-making process for a waste management plan are presented. LCA methodology was used to evaluate different waste management scenarios such as landfilling and incineration. One result was that the options 'incineration with recycling' and 'anaerobic mechanical-biological treatment with recycling' demonstrated lower environmental impact in both Khanty-Mansiysk and Surgut. Another finding was that there were hardly any differences in the ranking of the scenarios for Surgut and Khanty-Mansiysk. However, the special socio-cultural circumstances and location of each town have to be considered seriously in the development of a sustainable waste management plan.
02/2013; 31(3). DOI:10.1177/0734242X12473792
Available from: Davide Tonini
- "• Provision of electricity used for light on the site, administration buildings, pumps and fans. This may amount to 2– 12 kWh tonne –1 waste landfilled (Hunziker & Paterna 1995, Niskanen et al. 2009). Provision of electricity is here counted as 0.1–0.9 "
[Show abstract] [Hide abstract]
ABSTRACT: Accounting of greenhouse gas (GHG) emissions from waste landfilling is summarized with the focus on processes and technical data for a number of different landfilling technologies: open dump (which was included as the worst-case-scenario), conventional landfills with flares and with energy recovery, and landfills receiving low-organic-carbon waste. The results showed that direct emissions of GHG from the landfill systems (primarily dispersive release of methane) are the major contributions to the GHG accounting, up to about 1000 kg CO(2)-eq. tonne( -1) for the open dump, 300 kg CO(2)-eq. tonne( -1) for conventional landfilling of mixed waste and 70 kg CO(2)-eq. tonne(-1) for low-organic-carbon waste landfills. The load caused by indirect, upstream emissions from provision of energy and materials to the landfill was low, here estimated to be up to 16 kg CO(2)-eq. tonne(-1). On the other hand, utilization of landfill gas for electricity generation contributed to major savings, in most cases, corresponding to about half of the load caused by direct GHG emission from the landfill. However, this saving can vary significantly depending on what the generated electricity substitutes for. Significant amounts of biogenic carbon may still be stored within the landfill body after 100 years, which here is counted as a saved GHG emission. With respect to landfilling of mixed waste with energy recovery, the net, average GHG accounting ranged from about -70 to 30 kg CO(2)-eq. tonne(- 1), obtained by summing the direct and indirect (upstream and downstream) emissions and accounting for stored biogenic carbon as a saving. However, if binding of biogenic carbon was not accounted for, the overall GHG load would be in the range of 60 to 300 kg CO(2)-eq. tonne( -1). This paper clearly shows that electricity generation as well as accounting of stored biogenic carbon are crucial to the accounting of GHG of waste landfilling.
10/2009; 27(8):825-36. DOI:10.1177/0734242X09348529
Available from: Gurbakhash Bhander
[Show abstract] [Hide abstract]
ABSTRACT: Background, aim, and scopeThe management of municipal solid waste and the associated environmental impacts are subject of growing attention in industrialized
countries. European Union has recently strongly emphasized the role of LCA in its waste and resource strategies. The development
of sustainable solid waste management systems applying a life cycle perspective requires readily understandable tools for
modeling the life cycle impacts of waste management systems. The aim of the paper is to demonstrate the structure, functionalities,
and LCA modeling capabilities of the PC-based life cycle-oriented waste management model EASEWASTE, developed at the Technical
University of Denmark specifically to meet the needs of the waste system developer with the objective to evaluate the environmental
performance of the various elements of existing or proposed solid waste management systems.
Materials and methodsThe EASEWASTE model supports a full life cycle assessment of any user-defined residential, bulky, or garden waste management
system. The model focuses on the major components of the waste and reviews each component in terms of the available waste
management options, including biogasification and composting, thermal treatment, use on land, material sorting and recycling,
bottom and fly ash handling, material and energy utilization, and landfilling. In order to allow the use of the model in an
early stage where local data may be limited, default data sets are provided for waste composition and quantities as well as
for the waste technologies mentioned above. The model calculates environmental impacts and resource consumptions and allows
the user to trace all impacts to their source in a waste treatment processes or in a specific waste material fraction. In
addition to the traditional impact indicators, EASEWASTE incorporates impact categories on stored ecotoxicity, specifically
developed for representation of the long-term impacts of persistent pollutants in landfilled waste. The model reports data
at any stage of the LCA and supports identification of most sensitive parameters as well as overall sensitivity analysis and
material balances for all substances passing through the system.
Results and discussionThe structure of the model is presented, and its functionalities are demonstrated on a hypothetical case study based on waste
data from a large Danish municipality. The aim of the case is to demonstrate new waste treatment technologies and their modeling
capabilities as well as the LCA modeling capabilities in EASEWASTE to identify the most important impact categories and the
main sources of contributions to these in the system for treating the waste. Based on the results, the modeling features,
user flexibility, and transparency of the EASEWASTE model are discussed.
ConclusionsEASEWASTE is demonstrated to be a versatile and detailed (engineering) model with a strong differentiation of individual fractions,
but it requires an engineering background to use all the features. The model is especially developed for the modeling of the
handling of municipal solid wastes, and therefore, it does not support other wastes such as demolition and large commercial
waste. The model is useful for an iterative approach to waste system modeling; its database access supports a quick primary
calculation of the impacts from a designed waste system using default data, and based on this, a gradually refined focusing
on the parts which contribute the most to the total impacts. The EASEWASTE model allows the user to supply detailed data for
waste generation, waste composition including material fractions and chemical properties, sorting efficiencies, waste collection,
and waste treatment technologies. More generic LCA modeling tools developed for LCA of products do not support these steps
of the modeling to the same extent, and also the creation and evaluation of waste collection, waste transportation, and waste
treatment technology individually or in a designed scenario is much easier in EASEWASTE.
Recommendation and perspectivesEASEWASTE has been used in the modeling of a number of real case studies, and much data have been incorporated into it. Several
research projects are currently underway under the Danish 3R (Residual Resources Recovery) research school in support of its
further development. There are, however, still many issues that have to be improved significantly to facilitate application
by other users than model developers. The improvements in consideration are to provide data for more treatment and disposal
technologies and more flexibility. The current version of the model supports the environmental assessment (environmental impacts
and resource consumption) of household and small commercial business units waste treatment systems in a Danish context, but
it is the ambition that future versions of the model shall support the inclusion of other waste types as well as economic
evaluation and that the geographical coverage shall be extended to other countries.
KeywordsEASEWASTE model-Environmental assessment-Life cycle assessment-Material flow analysis-Sensitivity analysis-System modeling-Waste management system-Waste planning
The International Journal of Life Cycle Assessment 05/2010; 15(4):403-416. DOI:10.1007/s11367-010-0156-7 · 3.99 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.