• Energy Research

Abstract Urbanisation and the associated growing climate change burdens pose risks to urban and global climate resilience. Urban greenhouse gas emissions fluctuate over time in response to energy demand, which is influenced by government programmes, economic activity, and demographics. In this research, we investigate the influence of policy on urban energy demand and its consequences on mitigating climate change impacts. Using a case study of Lisbon, Portugal from 2008 to 2016, we illustrate a combined use of an urban energy metabolism assessment coupled with a logarithmic mean Divisia index to isolate the changes in energy-related carbon emissions associated with policy changes. We then link these energy flows to life cycle emissions factors to build a multi-level assessment between local and non-local global warming potential. We find that in 2016 Lisbon’s energy flows generated more than 2 Mt of CO2-equivalent emissions over their life cycles, 48% of which were direct emissions within the city. This corresponds to a decrease of around 37% in greenhouse gas emissions from 2008. Additionally, we estimate the potential of Lisbon’s urban forests to sequester these emissions to understand the potential for climate change mitigation. Results show that Lisbon’s urban forest can meet less than 1% of the emissions throughout the assessment period. We discuss the changes, concluding that urban forests are insufficient in size to meet the sequestration demands of the urban energy metabolism, and therefore the focus must be more attuned to reducing fossil fuel use in the urban trade and transport activities.

Scarcity of natural resources and productive land is a global issue affecting the provision of goods and services at the country scale. This is particularly true for small regions with highly developed economies such as Luxembourg, which usually balance the chronic unavailability of resources (in particular with regard to fossil fuels) with an increasing demand of imported raw materials, energy and manufactured commodities. Based on historical time-series analysis (from 1995 to 2009), this paper determines the state of natural capital (NC) utilization in Luxembourg and estimates its ecological deficit (ED). Accordingly, solar energy demand (SED) and ecological footprint (EF) for Luxembourg have been initially calculated based on a recently developed country-specific environmentally extended input-output model. Thereafter, these indicators have been compared to the corresponding annual trends of potential NC (estimated using the emergy concept) and biocapacity, respectively. Results show that the trends in ED and in the use of NC in Luxembourg have not increased substantially during the years surveyed. However, the estimates also highlight that the NC of Luxembourg is directly and indirectly overused by a factor higher than 20, while circa 9 additional 'Luxembourg states' would be ideally necessary to satisfy the current land's requirements of the country and thus balance the impact induced by the EF. An in-depth analysis of the methodological advantages and limitations behind our modelling approach has been performed to validate our findings and propose a road map to improve the environmental accounting for NC and biocapacity in Luxembourg.

The solar energy demand (SED) of the extraction of 232 atmospheric, biotic, fossil, land, metal, mineral, nuclear, and water resources was quantified and compared with other energy- and exergy-based indicators. SED represents the direct and indirect solar energy required by a product or service during its life cycle. SED scores were calculated for 3865 processes, as implemented in the Ecoinvent database, version 2.1. The results showed that nonrenewable resources, and in particular minerals, formed the dominant contribution to SED. This large share is due to the indirect solar energy required to produce these resource inputs. Compared with other energy- and exergy-based indicators, SED assigns higher impact factors to minerals and metals and smaller impact factors to fossil energetic resources, land use, and nuclear energy. The highest differences were observed for biobased and renewable energy generation processes, whose relative contribution of renewable resources such as water, biomass, and land occupation was much lower in SED than in energy- and exergy-based indicators.

Emergy evaluation (EME) is an environmental assessment method which is gaining international recognition and has increasingly been applied during the last decade. Emergy represents the memory of the geobiosphere exergy (environmental work) - measured in solar emjoules (seJ) - that has been used in the past or accumulated over time to make a natural resource available. The rationale behind the concept of Emergy is the consideration that all different forms of energy can be sorted under a hierarchy and measured with the common metric of the seJ, which is then the yardstick through which all energy inputs and outputs can be compared with each other. For this reason EME is suggested to be a suitable method of environmental accounting for a wide set of natural resources, and can be used to define guidelines for sustainable consumption of resources. Despite those interesting features, EME is still affected by several drawbacks in its calculation procedures and in its general methodological background, which prevent it from being accepted by a wider community. The main operational hurdle lays in the set of mathematical rules (known as Emergy algebra rules) governing EME, which do not follow logic of conservation and make their automatic implementation very difficult. This work presents an open source code specifically created for allowing a rigorous Emergy calculation (complying with all the Emergy algebra rules). We modeled the Emergy values circulating in multi-component systems with an oriented graph, formalized the problem in a matrix-based structure and developed a variant of the well-known track summing algorithm to obtain the total Emergy flow associated with the investigated product. The calculation routine (written in C++) implements the Depth First Search (DFS) strategy for graph searches. The most important features of the calculation routine are: (1) its ability to read the input in matrix form without the need of drawing a graph; (2) its rigorous implementation of the Emergy rules; (3) its low running time, which makes the algorithm applicable to any system described at the level of detail nowadays made possible by the use of the available life cycle inventory (LCI) databases. A version of the Emergy calculation routine based on the DFS algorithm has been completed and is being tested on case studies involving matrices of thousands of rows and columns, describing real product production systems.

Climate change and biodiversity loss are two pressing global environmental challenges that are tightly coupled to urban processes. Cities emit greenhouse gases through the consumption of materials and energy. Urban expansion encroaches on local habitats, while urban land teleconnections simultaneously degrade distant ecosystems. These processes decrease the supply of and increase the demand for ecosystem services inside and outside urban areas. Most cities are in a state of ecosystem services deficit, whereby demand exceeds local supply of ecosystem services. Methods to quantify this deficit by capturing multi-scale and multi-level ecological exchanges are incipient, leaving scholars with a partial understanding of the environmental impacts of cities. This paper deploys a novel method to simulate future urban supplies and demands of two key ecosystem services needed to combat climate change and biodiversity loss - global climate regulation and global habitat maintenance. Applying our model to eight representative European cities, we project growing ecosystems deficits (demand exceeds supply) between 8% and 214% in global climate regulation and 11% and 431% in global habitat maintenance between 2020 and 2050. Variation between cities stems from differing dietary patterns and electricity mixes, which have large implications for ecosystems outside the city. To combat these losses, urban sustainability strategies should complement local restoration with changes to local consumption alongside promoting remote ecological restoration to tackle the multi-level environmental impacts of cities.

Implementing nature-based solutions (NBSs) in cities, such as urban forests, can have multiple effects on the quality of life of inhabitants, acting on the mitigation of climate change, and in some cases also enhancing citizens’ social life and the transformation of customer patterns in commercial activities. Assessing this latter effect is the aim of this paper. An agent-based model (ABM) was used to assess change in commercial activities by small and midsize companies in retail due to the development of parks. The paper focuses on the potential capacity of NBS green spaces to boost retail companies’ business volumes, thus increasing their revenues, and at the same time create a pleasant feeling of space usability for the population. The type of NBS is not specified but generalized into large green spaces. The simulation contains two types of agents: (1) residents and (2) shop owners. Factors that attract new retail shops to be established in an area are simplified, based on attractor points, which identify areas such as large green spaces within and around which shops can form. The simulations provided insights on the number of retail shops that can be sustained based on the purchasing behavior of citizens that walk in parks. Four European cities were explored: Szeged (Hungary), Alcalá de Henares (Spain), Çankaya Municipality (Turkey) and Milan (Italy). The model allowed analyzing the indirect economic benefit of NBSs (i.e., large green spaces in this case) on a neighborhood’s economic structure. More precisely, the presence of green parks in the model boosted the visits of customers to local small shops located within and around them, such as cafés and kiosks, allowing for the emergence of 5–6 retail shops (on average, for about 800 walking citizens) in the case of Szeged and an average 12–14 retail shops for a simulated population of 2900 persons that walk in parks in the case of Milan. Overall, results from this modeling exercise can be considered representative for large urban green areas usually visited by a substantial number of citizens. However, their pertinence to support for local policies for NBS implementation and other decision-making related activities of socioeconomic nature is hampered by the low representativeness of source data used for the simulations.

Life Cycle Assessment (LCA) is a widely recognized, multicriteria and standardized tool for environmental assessment of products and processes. As an independent evaluation method, emergy assessment has shown to be a promising and relatively novel tool. The technique has gained wide recognition in the past decade but still faces methodological difficulties which prevent it from being accepted by a broader stakeholder community. This review aims to elucidate the fundamental requirements to possibly improve the Emergy evaluation by using LCA. Despite its capability to compare the amount of resources embodied in production systems, Emergy suffers from its vague accounting procedures and lacks accuracy, reproducibility, and completeness. An improvement of Emergy evaluations can be achieved via (1) technical implementation of Emergy algebra in the Life Cycle Inventory (LCI); (2) selection of consistent Unit Emergy Values (UEVs) as characterization factors for Life Cycle Impact Assessment (LCIA); and (3) expansion of the LCI system boundaries to include supporting systems usually considered by Emergy but excluded in LCA (e.g., ecosystem services and human labor). Whereas Emergy rules must be adapted to life-cycle structures, LCA should enlarge its inventory to give Emergy a broader computational framework. The matrix inversion principle used for LCAs is also proposed as an alternative to consistently account for a large number of resource UEVs.