51 resultados para Economic based allocation
Resumo:
Using a newly developed integrated indicator system with entropy weighting, we analyzed the panel data of 577 recorded disasters in 30 provinces of China from 1985–2011 to identify their links with the subsequent economic growth. Meteorological disasters promote economic growth through human capital instead of physical capital. Geological disasters did not trigger local economic growth from 1999–2011. Generally, natural disasters overall had no significant impact on economic growth from 1985–1998. Thus, human capital reinvestment should be the aim in managing recoveries, and it should be used to regenerate the local economy based on long-term sustainable development.
Resumo:
Experimental results from the open literature have been employed for the design and techno-economic evaluation of four process flowsheets for the production of microbial oil or biodiesel. The fermentation of glucose-based media using the yeast strain Rhodosporidium toruloides has been considered. Biodiesel production was based on the exploitation of either direct transesterification (without extraction of lipids from microbial biomass) or indirect transesterifaction of extracted microbial oil. When glucose-based renewable resources are used as carbon source for an annual production capacity of 10,000 t microbial oil and zero cost of glucose (assuming development of integrated biorefineries in existing industries utilising waste or by-product streams) the estimated unitary cost of purified microbial oil is $3.4/kg. Biodiesel production via indirect transesterification of extracted microbial oil proved more cost-competitive process compared to the direct conversion of dried yeast cells. For a price of glucose of $400/t oil production cost and biodiesel production cost are estimated to be $5.5/kg oil and $5.9/kg biodiesel, correspondingly. Industrial implementation of microbial oil production from oleaginous yeast is strongly dependent on the feedstock used and on the fermentation stage where significantly higher productivities and final microbial oil concentrations should be achieved.
Resumo:
Background: Health care literature supports the development of accessible interventions that integrate behavioral economics, wearable devices, principles of evidence-based behavior change, and community support. However, there are limited real-world examples of large scale, population-based, member-driven reward platforms. Subsequently, a paucity of outcome data exists and health economic effects remain largely theoretical. To complicate matters, an emerging area of research is defining the role of Superusers, the small percentage of unusually engaged digital health participants who may influence other members. Objective: The objective of this preliminary study is to analyze descriptive data from GOODcoins, a self-guided, free-to-consumer engagement and rewards platform incentivizing walking, running and cycling. Registered members accessed the GOODcoins platform through PCs, tablets or mobile devices, and had the opportunity to sync wearables to track activity. Following registration, members were encouraged to join gamified group challenges and compare their progress with that of others. As members met challenge targets, they were rewarded with GOODcoins, which could be redeemed for planet- or people-friendly products. Methods: Outcome data were obtained from the GOODcoins custom SQL database. The reporting period was December 1, 2014 to May 1, 2015. Descriptive self-report data were analyzed using MySQL and MS Excel. Results: The study period includes data from 1298 users who were connected to an exercise tracking device. Females consisted of 52.6% (n=683) of the study population, 33.7% (n=438) were between the ages of 20-29, and 24.8% (n=322) were between the ages of 30-39. 77.5% (n=1006) of connected and active members met daily-recommended physical activity guidelines of 30 minutes, with a total daily average activity of 107 minutes (95% CI 90, 124). Of all connected and active users, 96.1% (n=1248) listed walking as their primary activity. For members who exchanged GOODcoins, the mean balance was 4,000 (95% CI 3850, 4150) at time of redemption, and 50.4% (n=61) of exchanges were for fitness or outdoor products, while 4.1% (n=5) were for food-related items. Participants were most likely to complete challenges when rewards were between 201-300 GOODcoins. Conclusions: The purpose of this study is to form a baseline for future research. Overall, results indicate that challenges and incentives may be effective for connected and active members, and may play a role in achieving daily-recommended activity guidelines. Registrants were typically younger, walking was the primary activity, and rewards were mainly exchanged for fitness or outdoor products. Remaining to be determined is whether members were already physically active at time of registration and are representative of healthy adherers, or were previously inactive and were incentivized to change their behavior. As challenges are gamified, there is an opportunity to investigate the role of superusers and healthy adherers, impacts on behavioral norms, and how cooperative games and incentives can be leveraged across stratified populations. Study limitations and future research agendas are discussed.
Resumo:
Agriculture and food production are responsible for a substantial proportion of greenhouse gas emissions. An emission based food tax has been proposed as one option to reduce food related emissions. This study introduces a method to measure the impacts of emission based food taxes at a household level which involves the use of data augmentation to account for the fact that the data record purchases and not consumption. The method is applied to determine the distributional and nutritional impacts of an emission based food tax across socio-economic classes in the UK. We find that a tax of £2.841/tCO2e on all foods would reduce food related emissions by 6.3% and a tax on foods with above average levels of emissions would reduce emissions by 4.3%. The tax burden falls disproportionately on households in the lowest socio-economic class because they tend to spend a larger proportion of their food expenditure on emission intensive foods and because they buy cheaper products and therefore experience relatively larger price increases.
Resumo:
At the beginning of the Medieval Climate Anomaly, in the ninth and tenth century, the medieval eastern Roman empire, more usually known as Byzantium, was recovering from its early medieval crisis and experiencing favourable climatic conditions for the agricultural and demographic growth. Although in the Balkans and Anatolia such favourable climate conditions were prevalent during the eleventh century, parts of the imperial territories were facing significant challenges as a result of external political/military pressure. The apogee of medieval Byzantine socio-economic development, around AD 1150, coincides with a period of adverse climatic conditions for its economy, so it becomes obvious that the winter dryness and high climate variability at this time did not hinder Byzantine society and economy from achieving that level of expansion. Soon after this peak, towards the end of the twelfth century, the populations of the Byzantine world were experiencing unusual climatic conditions with marked dryness and cooler phases. The weakened Byzantine socio-political system must have contributed to the events leading to the fall of Constantinople in AD 1204 and the sack of the city. The final collapse of the Byzantine political control over western Anatolia took place half century later, thus contemporaneous with the strong cooling effect after a tropical volcanic eruption in AD 1257. We suggest that, regardless of a range of other influential factors, climate change was also an important contributing factor to the socio-economic changes that took place in Byzantium during the Medieval Climate Anomaly. Crucially, therefore, while the relatively sophisticated and complex Byzantine society was certainly influenced by climatic conditions, and while it nevertheless displayed a significant degree of resilience, external pressures as well as tensions within the Byzantine society more broadly contributed to an increasing vulnerability in respect of climate impacts. Our interdisciplinary analysis is based on all available sources of information on the climate and society of Byzantium, that is textual (documentary), archaeological, environmental, climate and climate model-based evidence about the nature and extent of climate variability in the eastern Mediterranean. The key challenge was, therefore, to assess the relative influence to be ascribed to climate variability and change on the one hand, and on the other to the anthropogenic factors in the evolution of Byzantine state and society (such as invasions, changes in international or regional market demand and patterns of production and consumption, etc.). The focus of this interdisciplinary
Resumo:
Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.