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PurposeValue chain analysis (VCA) can expose strategic and operational misalignments within chains, and the consequential misallocation of resources, and hence opportunities for improvements which create value and economic sustainability. This paper's purpose is to argue why and how VCA needs to integrate the social and environmental aspects of sustainability in pursuit of sustainable competitive advantage.Design/methodology/approachBased on a review of existing methods and case studies, the paper proposes three dimensions of VCA, which illustrate the flaws in narrow tools, and the need to broaden the boundaries of VCA, the interpretation of “value” and relationships along the chain in order to highlight opportunities for creating sustainable value chains.FindingsTo date VCA has largely focused on economic sustainability and paid inadequate attention to social and environment consequences of firm behaviour and the (re) allocation of resources within and between firms in the chain. This risks producing recommendations which either ignore the competitive advantage offered from improving environmental management and social welfare, or have such detrimental external consequences as to render any proposals unsustainable when exposed to government or broader (public) scrutiny.Research limitations/implicationsVCA variants need to be developed which incorporate all three pillars of sustainability. Some initial experiences are presented and ideas for future research and applications proposed.Practical implicationsThe development of sustainable VCA tools should identify business opportunities consistent with Porter and Kramer's imperative for value chains to create shared value between business and society.Originality/valueAdopting the broader dimensions identified will allow VCA to become more widely applicable, and more relevant in business scenarios where there is a growing imperative to include social and environmental impacts into “mainstream” business strategies.

Abstract Around the world, cities are creating local climate change mitigation strategies and combining strengths in international efforts. In addition to making the strategies, it is important to follow, how they work in practice. The aim of the study is to examine, how climate change mitigation policies and other events affected the consumption-based household carbon footprints in the Helsinki Metropolitan Area (HMA) from 2006 until 2012. The cities of the HMA launched an ambitious climate change mitigation strategy in 2007. Furthermore, the study analyses the changes in the carbon footprints of six different types of urban zone within the HMA: the central pedestrian zone, the fringe of the central pedestrian zone, intensive public transport zone, public transport zone, car zone and the pedestrian zones of subcentres. The results of the study reveal that the average carbon footprint decreased 7% from 2006 to 2012, despite 1% increase in expenditure, which is encouraging. Emissions caused by housing energy consumption and motor fuel consumption decreased the most. Among the urban zones, public transport zone and car zone, which are the two outermost zones of the HMA, had the strongest emission reductions. Cleaner electricity and the improved energy efficiency of buildings had a strong effect. The regression analysis of the study suggests that the central pedestrian zone and the car zone, the two most affluent zones of the HMA, have higher carbon footprints than all the other zones have between them. However, this is only true when income is controlled, not when expenditure is controlled. The economic crisis in 2008, and changes in consumption behaviour because of it, seem to explain the result. The reduction of the average carbon footprint in the HMA was not only due to steered mitigation actions. Increased housing costs seem to have contributed to the decline of consumption-based emissions. The results of the study suggest that to achieve the ambitious international, national and local climate change mitigation targets, stronger measures are needed.

Along with total radiation received, the proportion of diffuse to direct solar radiation can influence forest photosynthesis and carbon cycling. However, tropical diffuse radiation regimes are poorly described, and to date there are few or no site-based or regional diffuse radiation datasets. The relationship between cloud fraction and diffuse solar radiation was investigated using data from two sites in western and eastern Amazonia. Radiation regimes for diffuse and total radiation were characterised for each site, and the variation in clear sky diffuse radiation fraction between wet and dry season demonstrated and quantified, as well as the dependence of diffuse radiation on cloud amount. Using high frequency measurements of diffuse and total solar radiation data from the two sites, and estimated top of the canopy clear-sky radiation, a number of alternative models to predict diffuse radiation fraction from cloud fraction were formulated and tested. Results showed that cloud fraction can be approximated using the relationship between observed and calculated top of canopy radiation, after which diffuse radiation can then be predicted from cloud fraction. We also demonstrate that satellite cloud data (from the International Satellite Cloud Climatology Project) can be used as inputs to the diffuse radiation model to provide estimates of annual and monthly diffuse radiation proportion.

Abstract Energy efficiency can boost economic growth and reduce greenhouse gas (GHG) emissions. However, the global rate of energy efficiency improvement is slowing – a trend that has implications for consumers, businesses and the environment as the adverse climate change and pollution impacts deepen. The emissions in the EU have decreased by 17% in the past decade while member countries such as Germany, United Kingdom and Poland were among the largest emitters of CO2. This paper examines the effect of energy efficiency, proxied by final energy consumption, on CO2 emissions in the EU using a generalized methods of moments based on a quantile regression approach. We use the Panel Quantile ARDL for inference at various quantiles and support the ARDL estimations by the 2SLS estimations for robustness checks. We use the final energy consumption data as an indicator of energy efficiency as included in the energy efficiency indicators database of the International Energy Agency and emissions for the time period spanning 1980–2018. The results indicate that energy efficiency has reduced emissions by 8.6% on average in all the quantiles. Improving efficiency in petroleum consumption will enable the EU to reduce emissions as well as improve energy security by reducing imports as per the aims of the European Green Deal and the Efficiency First Principle. We also recommend that energy efficiency policies should account for possible rebound effects, which can limit their effectiveness.

The paper applies the community resilience approach to the post‐disaster case of Pescomaggiore, an Italian village affected by the L'Aquila earthquake in 2009. A group of residents refused to accept the housing recovery solutions proposed by the government, opting for autonomous recovery. They developed a housing project in the form of a self‐built ecovillage, characterised by earthquake‐proof buildings made of straw and wood. The project is a paradigmatic example of a community‐based response to an external shock. It illustrates the concept of ‘community resilience’, which is widely explored in the scientific debate but still vaguely defined. Based on qualitative methodologies, the paper seeks to understand how the community resilience process can be enacted in alternative social practices such as ecovillages. The goal is to see under which conditions natural disasters can be considered windows of opportunity for sustainability.

In this study, the energy, exergy, exergoeconomic and exergoenvironmental (4E) analyses of a cogeneration system that combines photovoltaic thermal panels (PV/T), evacuated tube solar collectors, an organic Rankine cycle (ORC) and energy storage systems are performed. The cogeneration model is built to meet the load demand of independent houses in remote areas and avoids excessive consumption of traditional energy and environmental pollution. Here, the exergoenvironmental analysis adopts the Eco-indicator-99 method and the all life cycle assessment method is used to calculate the environmental impact of each component. Two comparative studies are conducted to the 4E analyses. The first one compares the comprehensive performance of the battery storage and hydrogen production for energy storage. The results indicate that the cogeneration system using both batteries and hydrogen production for energy storage has the best overall performance. According the exergoeconomic and exergoenvironmental analyses, its environmental impact is 23.6% lower than the cogeneration system using batteries alone and the PV/T can be fully utilized. In addition, the total cost rate is 6.2% lower than the cogeneration system using hydrogen production alone. The second case investigates the effect of adding the evacuated tube solar collectors between the PV/T and ORC on the cogeneration system. The analysis results demonstrate that the evacuated tube solar collectors can increase the heat source temperature of the ORC to increase the power generation of the ORC by 37.14%; however, the total cost rate of the cogeneration system increases by 3.7% and the environmental impact rate increases by 19.8%.

Biodiversity indicators provide a vital window on the state of the planet, guiding policy development and management. The most widely adopted marine indicator is mean trophic level (MTL) from catches, intended to detect shifts from high-trophic-level predators to low-trophic-level invertebrates and plankton-feeders. This indicator underpins reported trends in human impacts, declining when predators collapse ("fishing down marine food webs") and when low-trophic-level fisheries expand ("fishing through marine food webs"). The assumption is that catch MTL measures changes in ecosystem MTL and biodiversity. Here we combine model predictions with global assessments of MTL from catches, trawl surveys and fisheries stock assessments and find that catch MTL does not reliably predict changes in marine ecosystems. Instead, catch MTL trends often diverge from ecosystem MTL trends obtained from surveys and assessments. In contrast to previous findings of rapid declines in catch MTL, we observe recent increases in catch, survey and assessment MTL. However, catches from most trophic levels are rising, which can intensify fishery collapses even when MTL trends are stable or increasing. To detect fishing impacts on marine biodiversity, we recommend greater efforts to measure true abundance trends for marine species, especially those most vulnerable to fishing.

Abstract The inverse relationship between urban density and greenhouse gas (GHG) emissions caused by driving is well established. However, at the same time the few existing studies have observed higher levels of long-distance travel and particularly air travel in the same densely built parts of urban regions. This may lead to GHG emissions reduction in local travel offset by the concomitant increase in long-distance travel. With this study we aim to identify the main factors involved in differences in local, national and long-distance travel patterns and the resulting GHG emissions, with a special focus on the role of the different urban zones in the Helsinki Metropolitan Area (HMA) in Finland. We used a softGIS survey to collect data on the personal travel of young adults living in HMA. SoftGIS methodology provides the opportunity to obtain detailed spatial data on participants' residential locations, travel destinations, and destination characteristics such as travel modes, frequencies and trip purposes. Special attention was paid to national and international trips, for which data were collected over 12 months, a period long enough to capture actual travel patterns. GHG emissions were assessed with a wide scope life cycle assessment (LCA) approach, including vehicles and infrastructure, and the results were elaborated with a two-part regression model on participation in travel and amount of GHG emissions. The study found that the residential location was associated with travel emissions on all scales, and independently from major socioeconomic characteristics. Residents of centrally located and densely built urban zones have on average lower emissions from local travel but higher emissions from international travel than residents of car-oriented suburban zones, and the association holds true after controlling for income, education level and household type. Differences in emissions from local travel between most central and most suburban zones were almost completely offset by differences in emissions from international travel. International long-distance trips were a dominant source of travel-related GHG emissions in all urban zones, particularly due to plane flights.