28 resultados para Carbon Disclosure Project
em CentAUR: Central Archive University of Reading - UK
Resumo:
The purpose of this paper is to explore how companies that hold carbon trading accounts under European Union Emissions Trading Scheme (EU ETS) respond to the climate change by using disclosures on carbon emissions as a means to generate legitimacy compared to others. The study is based on disclosures made in annual reports and stand-alone sustainability reports of UK listed companies from 2001- 2012. The study uses content analysis to capture both the quality and volume of the carbon disclosures. The results show that there is a significant increase in both the quality and volume of the carbon disclosures after the launch of EU ETS. Companies with carbon trading accounts provide greater detailed disclosures as compared to the others without an account. We also find that company size is positively correlated with the disclosures while the association with the industry produces an inconclusive result.
Resumo:
The paper investigates how energy-intensive industries respond to the recent government-led carbon emission schemes through the content analysis of 306 annual and standalone reports of 25 UK listed companies from 2004 to 2012. This period of reporting captures the trend and development of corporate disclosures on carbon emissions after the launch of EU Emissions Trading Schemes (ETS) and Climate Change Act (CCA) 2008. It is found that in corresponding to strategic legitimacy theory, there is an increase in both the quality and quantity of carbon disclosures as a response to these initiatives. However, the change is gradual, which reflects in the achievement of peak disclosure period two years after the launch. It indicates that the new legislations have a lasting impact on the discourses rather than an immediate legitimacy threat from the perspective of institutional legitimacy theory. The results also show that carbon disclosures are an institutionalised practice as companies in the same industries and/or with same carbon trading account status appear to imitate and adopt the industry’s ‘best practice’ disclosure strategy to maintain legitimacy. The trend analysis suggests that the overall disclosure practice is still in its infant stage, especially in the reporting of quantitative and monetary items. The paper contributes to the social and environmental accounting literature by adopting both strategic and institutional view of legitimacy, which explains why carbon disclosures evolve in a specific way to meet the expectation of various stakeholders.
Resumo:
Global warming has attracted attention from all over the world and led to the concern about carbon emission. Kyoto Protocol, as the first major international regulatory emission trading scheme, was introduced in 1997 and outlined the strategies for reducing carbon emission (Ratnatunga et al., 2011). As the increased interest in carbon reduction the Protocol came into force in 2005, currently there are already 191 nations ratifying the Protocol(UNFCCC, 2012). Under the cap-and-trade schemes, each company has its carbon emission target. When company’s carbon emission exceeds the target the company will either face fines or buy emission allowance from other companies. Thus unlike most of the other social and environmental issues carbon emission could trigger cost for companies in introducing low-emission equipment and systems and also emission allowance cost when they emit more than their targets. Despite the importance of carbon emission to companies, carbon emission reporting is still operating under unregulated environment and companies are only required to disclose when it is material either in value or in substances (Miller, 2005, Deegan and Rankin, 1997). Even though there is still an increase in the volume of carbon emission disclosures in company’s financial reports and stand-alone social and environmental reports to show their concern of the environment and also their social responsibility (Peters and Romi, 2009), the motivations behind corporate carbon emission disclosures and whether carbon disclosures have impact on corporate environmental reputation and financial performance have not yet to explore. The problems with carbon emission lie on both the financial side and non-financial side of corporate governance. On one hand corporate needs to spend money in reducing carbon emission or paying penalties when they emit more than allowed. On the other hand as the public are more interested in environmental issues than before carbon emission could also impact on the image of corporate regarding to its environmental performance. The importance of carbon emission issue are beginning to be recognized by companies from different industries as one of the critical issues in supply chain management (Lee, 2011) and 80% of companies analysed are facing carbon risks resulting from emissions in the companies’ supply chain as shown in a study conducted by the Investor Responsibility Research Centre Institute for Corporate Responsibility (IRRCI) and over 80% of the companies analysed found that the majority of greenhouse gas (GHG) emission are from electricity and other direct suppliers (Trucost, 2009). The review of extant literature shows the increased importance of carbon emission issues and the gap in the study of carbon reporting and disclosures and also the study which links corporate environmental reputation and corporate financial performance with carbon reporting (Lohmann, 2009a, Ratnatunga and Balachandran, 2009, Bebbington and Larrinaga-Gonzalez, 2008). This study would focus on investigating the current status of UK carbon emission disclosures, the determinant factors of corporate carbon disclosure, and the relationship between carbon emission disclosures and corporate environmental reputation and financial performance of UK listed companies from 2004-2012 and explore the explanatory power of classical disclosure theories.
Resumo:
Effective public policy to mitigate climate change footprints should build on data-driven analysis of firm-level strategies. This article’s conceptual approach augments the resource-based view (RBV) of the firm and identifies investments in four firm-level resource domains (Governance, Information management, Systems, and Technology [GISTe]) to develop capabilities in climate change impact mitigation. The authors denote the resulting framework as the GISTe model, which frames their analysis and public policy recommendations. This research uses the 2008 Carbon Disclosure Project (CDP) database, with high-quality information on firm-level climate change strategies for 552 companies from North America and Europe. In contrast to the widely accepted myth that European firms are performing better than North American ones, the authors find a different result. Many firms, whether European or North American, do not just “talk” about climate change impact mitigation, but actually do “walk the talk.” European firms appear to be better than their North American counterparts in “walk I,” denoting attention to governance, information management, and systems. But when it comes down to “walk II,” meaning actual Technology-related investments, North American firms’ performance is equal or superior to that of the European companies. The authors formulate public policy recommendations to accelerate firm-level, sector-level, and cluster-level implementation of climate change strategies.
Resumo:
Purpose – The purpose of this paper is to seek to shed light on the practice of incomplete corporate disclosure of quantitative Greenhouse gas (GHG) emissions and investigates whether external stakeholder pressure influences the existence, and separately, the completeness of voluntary GHG emissions disclosures by 431 European companies. Design/methodology/approach – A classification of reporting completeness is developed with respect to the scope, type and reporting boundary of GHG emissions based on the guidelines of the GHG Protocol, Global Reporting Initiative and the Carbon Disclosure Project. Logistic regression analysis is applied to examine whether proxies for exposure to climate change concerns from different stakeholder groups influence the existence and/or completeness of quantitative GHG emissions disclosure. Findings – From 2005 to 2009, on average only 15 percent of companies that disclose GHG emissions report them in a manner that the authors consider complete. Results of regression analyses suggest that external stakeholder pressure is a determinant of the existence but not the completeness of emissions disclosure. Findings are consistent with stakeholder theory arguments that companies respond to external stakeholder pressure to report GHG emissions, but also with legitimacy theory claims that firms can use carbon disclosure, in this case the incomplete reporting of emissions, as a symbolic act to address legitimacy exposures. Practical implications – Bringing corporate GHG emissions disclosure in line with recommended guidelines will require either more direct stakeholder pressure or, perhaps, a mandated disclosure regime. In the meantime, users of the data will need to carefully consider the relevance of the reported data and develop the necessary competencies to detect and control for its incompleteness. A more troubling concern is that stakeholders may instead grow to accept less than complete disclosure. Originality/value – The paper represents the first large-scale empirical study into the completeness of companies’ disclosure of quantitative GHG emissions and is the first to analyze these disclosures in the context of stakeholder pressure and its relation to legitimation.
Modelled soil organic carbon stocks and changes in the Indo-Gangetic Plains, India from 1980 to 2030
Resumo:
The Global Environment Facility co-financed Soil Organic Carbon (GEFSOC) Project developed a comprehensive modelling system for predicting soil organic carbon (SOC) stocks and changes over time. This research is an effort to predict SOC stocks and changes for the Indian, Indo-Gangetic Plains (IGP), an area with a predominantly rice (Oryza sativa) - wheat (Triticum aestivum) cropping system, using the GEFSOC Modelling System and to compare output with stocks generated using mapping approaches based on soil survey data. The GEFSOC Modelling System predicts an estimated SOC stock for the IGP, India of 1.27, 1.32 and 1.27 Pg for 1990, 2000 and 2030, respectively, in the top 20 cm of soil. The SOC stock using a mapping approach based on soil survey data was 0.66 and 0.88 Pg for 1980 and 2000, respectively. The SOC stock estimated using the GEFSOC Modelling System is higher than the stock estimated using the mapping approach. This is due to the fact that while the GEFSOC System accounts for variation in crop input data (crop management), the soil mapping approach only considers regional variation in soil texture and wetness. The trend of overall change in the modelled SOC stock estimates shows that the IGP, India may have reached an equilibrium following 30-40 years of the Green Revolution. This can be seen in the SOC stock change rates. Various different estimation methods show SOC stocks of 0.57-1.44 Pg C for the study area. The trend of overall change in C stock assessed from the soil survey data indicates that the soils of the IGP, India may store a projected 1.1 Pg of C in 2030. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
The new Max-Planck-Institute Earth System Model (MPI-ESM) is used in the Coupled Model Intercomparison Project phase 5 (CMIP5) in a series of climate change experiments for either idealized CO2-only forcing or forcings based on observations and the Representative Concentration Pathway (RCP) scenarios. The paper gives an overview of the model configurations, experiments related forcings, and initialization procedures and presents results for the simulated changes in climate and carbon cycle. It is found that the climate feedback depends on the global warming and possibly the forcing history. The global warming from climatological 1850 conditions to 2080–2100 ranges from 1.5°C under the RCP2.6 scenario to 4.4°C under the RCP8.5 scenario. Over this range, the patterns of temperature and precipitation change are nearly independent of the global warming. The model shows a tendency to reduce the ocean heat uptake efficiency toward a warmer climate, and hence acceleration in warming in the later years. The precipitation sensitivity can be as high as 2.5% K−1 if the CO2 concentration is constant, or as small as 1.6% K−1, if the CO2 concentration is increasing. The oceanic uptake of anthropogenic carbon increases over time in all scenarios, being smallest in the experiment forced by RCP2.6 and largest in that for RCP8.5. The land also serves as a net carbon sink in all scenarios, predominantly in boreal regions. The strong tropical carbon sources found in the RCP2.6 and RCP8.5 experiments are almost absent in the RCP4.5 experiment, which can be explained by reforestation in the RCP4.5 scenario.
Resumo:
Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. In addition, SOC is related to atmospheric CO, levels with soils having the potential for C release or sequestration, depending on land use, land management and climate. The United Nations Convention on Climate Change and its Kyoto Protocol, and other United Nations Conventions to Combat Desertification and on Biodiversity all recognize the importance of SOC and point to the need for quantification of SOC stocks and changes. An understanding of SOC stocks and changes at the national and regional scale is necessary to further our understanding of the global C cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. Several studies have considered SOC stocks at the plot scale, but these are site specific and of limited value in making inferences about larger areas. Some studies have used empirical methods to estimate SOC stocks and changes at the regional scale, but such studies are limited in their ability to project future changes, and most have been carried out using temperate data sets. The computational method outlined by the Intergovernmental Panel on Climate Change (IPCC) has been used to estimate SOC stock changes at the regional scale in several studies, including a recent study considering five contrasting eco regions. This 'one step' approach fails to account for the dynamic manner in which SOC changes are likely to occur following changes in land use and land management. A dynamic modelling approach allows estimates to be made in a manner that accounts for the underlying processes leading to SOC change. Ecosystem models, designed for site scale applications can be linked to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. Some studies have used variations on this approach to estimate SOC stock changes at the sub-national and national scale for areas of the USA and Europe and at the watershed scale for areas of Mexico and Cuba. However, a need remained for a national and regional scale, spatially explicit system that is generically applicable and can be applied to as wide a range of soil types, climates and land uses as possible. The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System was developed in response to this need. The GEFSOC system allows estimates of SOC stocks and changes to be made for diverse conditions, providing essential information for countries wishing to take part in an emerging C market, and bringing us closer to an understanding of the future role of soils in the global C cycle. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
Perturbations to the carbon cycle could constitute large feedbacks on future changes in atmospheric CO2 concentration and climate. This paper demonstrates how carbon cycle feedback can be expressed in formally similar ways to climate feedback, and thus compares their magnitudes. The carbon cycle gives rise to two climate feedback terms: the concentration–carbon feedback, resulting from the uptake of carbon by land and ocean as a biogeochemical response to the atmospheric CO2 concentration, and the climate–carbon feedback, resulting from the effect of climate change on carbon fluxes. In the earth system models of the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP), climate–carbon feedback on warming is positive and of a similar size to the cloud feedback. The concentration–carbon feedback is negative; it has generally received less attention in the literature, but in magnitude it is 4 times larger than the climate–carbon feedback and more uncertain. The concentration–carbon feedback is the dominant uncertainty in the allowable CO2 emissions that are consistent with a given CO2 concentration scenario. In modeling the climate response to a scenario of CO2 emissions, the net carbon cycle feedback is of comparable size and uncertainty to the noncarbon–climate response. To quantify simulated carbon cycle feedbacks satisfactorily, a radiatively coupled experiment is needed, in addition to the fully coupled and biogeochemically coupled experiments, which are referred to as coupled and uncoupled in C4MIP. The concentration–carbon and climate–carbon feedbacks do not combine linearly, and the concentration–carbon feedback is dependent on scenario and time.
Resumo:
Geological carbon dioxide storage (CCS) has the potential to make a significant contribution to the decarbonisation of the UK. Amid concerns over maintaining security, and hence diversity, of supply, CCS could allow the continued use of coal, oil and gas whilst avoiding the CO2 emissions currently associated with fossil fuel use. This project has explored some of the geological, environmental, technical, economic and social implications of this technology. The UK is well placed to exploit CCS with a large offshore storage capacity, both in disused oil and gas fields and saline aquifers. This capacity should be sufficient to store CO2 from the power sector (at current levels) for a least one century, using well understood and therefore likely to be lower-risk, depleted hydrocarbon fields and contained parts of aquifers. It is very difficult to produce reliable estimates of the (potentially much larger) storage capacity of the less well understood geological reservoirs such as non-confined parts of aquifers. With the majority of its large coal fired power stations due to be retired during the next 15 to 20 years, the UK is at a natural decision point with respect to the future of power generation from coal; the existence of both national reserves and the infrastructure for receiving imported coal makes clean coal technology a realistic option. The notion of CCS as a ‘bridging’ or ‘stop-gap’ technology (i.e. whilst we develop ‘genuinely’ sustainable renewable energy technologies) needs to be examined somewhat critically, especially given the scale of global coal reserves. If CCS plant is built, then it is likely that technological innovation will bring down the costs of CO2 capture, such that it could become increasingly attractive. As with any capitalintensive option, there is a danger of becoming ‘locked-in’ to a CCS system. The costs of CCS in our model for UK power stations in the East Midlands and Yorkshire to reservoirs in the North Sea are between £25 and £60 per tonne of CO2 captured, transported and stored. This is between about 2 and 4 times the current traded price of a tonne of CO2 in the EU Emissions Trading Scheme. In addition to the technical and economic requirements of the CCS technology, it should also be socially and environmentally acceptable. Our research has shown that, given an acceptance of the severity and urgency of addressing climate change, CCS is viewed favourably by members of the public, provided it is adopted within a portfolio of other measures. The most commonly voiced concern from the public is that of leakage and this remains perhaps the greatest uncertainty with CCS. It is not possible to make general statements concerning storage security; assessments must be site specific. The impacts of any potential leakage are also somewhat uncertain but should be balanced against the deleterious effects of increased acidification in the oceans due to uptake of elevated atmospheric CO2 that have already been observed. Provided adequate long term monitoring can be ensured, any leakage of CO2 from a storage site is likely to have minimal localised impacts as long as leaks are rapidly repaired. A regulatory framework for CCS will need to include risk assessment of potential environmental and health and safety impacts, accounting and monitoring and liability for the long term. In summary, although there remain uncertainties to be resolved through research and demonstration projects, our assessment demonstrates that CCS holds great potential for significant cuts in CO2 emissions as we develop long term alternatives to fossil fuel use. CCS can contribute to reducing emissions of CO2 into the atmosphere in the near term (i.e. peak-shaving the future atmospheric concentration of CO2), with the potential to continue to deliver significant CO2 reductions over the long term.
Resumo:
Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).
Resumo:
Global temperatures are expected to rise by between 1.1 and 6.4oC this century, depending, to a large extent, on the amount of carbon we emit to the atmosphere from now onwards. This warming is expected to have very negative effects on many peoples and ecosystems and, therefore, minimising our carbon emissions is a priority. Buildings are estimated to be responsible for around 50% of carbon emissions in the UK. Potential reductions involve both operational emissions, produced during use, and embodied emissions, produced during manufacture of materials and components, and during construction, refurbishments and demolition. To date the major effort has focused on reducing the, apparently, larger operational element, which is more readily quantifiable and reduction measures are relatively straightforward to identify and implement. Various studies have compared the magnitude of embodied and operational emissions, but have shown considerable variation in the relative values. This illustrates the difficulties in quantifying embodied, as it requires a detailed knowledge of the processes involved in the different life cycle phases, and requires the use of consistent system boundaries. However, other studies have established the interaction between operational and embodied, which demonstrates the importance of considering both elements together in order to maximise potential reductions. This is borne out in statements from both the Intergovernmental Panel on Climate Change and The Low Carbon Construction Innovation and Growth Team of the UK Government. In terms of meeting the 2020 and 2050 timeframes for carbon reductions it appears to be equally, if not more, important to consider early embodied carbon reductions, rather than just future operational reductions. Future decarbonisation of energy supply and more efficient lighting and M&E equipment installed in future refits is likely to significantly reduce operational emissions, lending further weight to this argument. A method of discounting to evaluate the present value of future carbon emissions would allow more realistic comparisons to be made on the relative importance of the embodied and operational elements. This paper describes the results of case studies on carbon emissions over the whole lifecycle of three buildings in the UK, compares four available software packages for determining embodied carbon and suggests a method of carbon discounting to obtain present values for future emissions. These form the initial stages of a research project aimed at producing information on embodied carbon for different types of building, components and forms of construction, in a simplified form, which can be readily used by building designers in optimising building design in terms of minimising overall carbon emissions. Keywords: Embodied carbon; carbon emission; building; operational carbon.
Resumo:
We describe a model-data fusion (MDF) inter-comparison project (REFLEX), which compared various algorithms for estimating carbon (C) model parameters consistent with both measured carbon fluxes and states and a simple C model. Participants were provided with the model and with both synthetic net ecosystem exchange (NEE) of CO2 and leaf area index (LAI) data, generated from the model with added noise, and observed NEE and LAI data from two eddy covariance sites. Participants endeavoured to estimate model parameters and states consistent with the model for all cases over the two years for which data were provided, and generate predictions for one additional year without observations. Nine participants contributed results using Metropolis algorithms, Kalman filters and a genetic algorithm. For the synthetic data case, parameter estimates compared well with the true values. The results of the analyses indicated that parameters linked directly to gross primary production (GPP) and ecosystem respiration, such as those related to foliage allocation and turnover, or temperature sensitivity of heterotrophic respiration, were best constrained and characterised. Poorly estimated parameters were those related to the allocation to and turnover of fine root/wood pools. Estimates of confidence intervals varied among algorithms, but several algorithms successfully located the true values of annual fluxes from synthetic experiments within relatively narrow 90% confidence intervals, achieving >80% success rate and mean NEE confidence intervals <110 gC m−2 year−1 for the synthetic case. Annual C flux estimates generated by participants generally agreed with gap-filling approaches using half-hourly data. The estimation of ecosystem respiration and GPP through MDF agreed well with outputs from partitioning studies using half-hourly data. Confidence limits on annual NEE increased by an average of 88% in the prediction year compared to the previous year, when data were available. Confidence intervals on annual NEE increased by 30% when observed data were used instead of synthetic data, reflecting and quantifying the addition of model error. Finally, our analyses indicated that incorporating additional constraints, using data on C pools (wood, soil and fine roots) would help to reduce uncertainties for model parameters poorly served by eddy covariance data.
Resumo:
Gaining public acceptance is one of the main issues with large-scale low-carbon projects such as hydropower development. It has been recommended by the World Commission on Dams that to gain public acceptance, publicinvolvement is necessary in the decision-making process (WCD, 2000). As financially-significant actors in the planning and implementation of large-scale hydropowerprojects in developing country contexts, the paper examines the ways in which publicinvolvement may be influenced by international financial institutions. Using the casestudy of the NamTheun2HydropowerProject in Laos, the paper analyses how publicinvolvement facilitated by the Asian Development Bank had a bearing on procedural and distributional justice. The paper analyses the extent of publicparticipation and the assessment of full social and environmental costs of the project in the Cost-Benefit Analysis conducted during the projectappraisal stage. It is argued that while efforts were made to involve the public, there were several factors that influenced procedural and distributional justice: the late contribution of the Asian Development Bank in the projectappraisal stage; and the issue of non-market values and discount rate to calculate the full social and environmental costs.
Resumo:
Housing in the UK accounts for 30.5% of all energy consumed and is responsible for 25% of all carbon emissions. The UK Government’s Code for Sustainable Homes requires all new homes to be zero carbon by 2016. The development and widespread diffusion of low and zero carbon (LZC) technologies is recognised as being a key solution for housing developers to deliver against this zero-carbon agenda. The innovation challenge to design and incorporate these technologies into housing developers’ standard design and production templates will usher in significant technical and commercial risks. In this paper we report early results from an ongoing Engineering and Physical Sciences Research Council project looking at the innovation logic and trajectory of LZC technologies in new housing. The principal theoretical lens for the research is the socio-technical network approach which considers actors’ interests and interpretative flexibilities of technologies and how they negotiate and reproduce ‘acting spaces’ to shape, in this case, the selection and adoption of LZC technologies. The initial findings are revealing the form and operation of the technology networks around new housing developments as being very complex, involving a range of actors and viewpoints that vary for each housing development.