Waste cooking oil as an energy resource: review of Chinese policies

Converting waste cooking oil into biofuel represents a three-win solution, dealing simultaneously with food security, pollution, and energy security. In this paper, we encode the policy documents of waste cooking oil refining biofuel in China based on content analysis, and explore the related policies from the two dimensions as basic policy tools and enterprises supply chain. Research indicates the weak institution coordination of policy issuing entities. Also, the findings show that tools of regulatory control and goal planning are overused. Policies of government procurement, outsourcing and biofuel consumption are relatively scarce. Generally, government focuses more on formulating policies from the strategic, administrative and regulatory aspects, while less on market-oriented initiatives as funding input and financial support.

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

Changing building user attitude and organisational policy towards sustainable resource use in healthcare

Health care provision is significantly impacted by the ability of the health providers to engineer a viable healthcare space to support care stakeholders needs. In this paper we discuss and propose use of organisational semiotics as a set of methods to link stakeholders to systems, which allows us to capture clinician activity, information transfer, and building use; which in tern allows us to define the value of specific systems in the care environment to specific stakeholders and the dependence between systems in a care space. We suggest use of a semantically enhanced building information model (BIM) to support the linking of clinician activity to the physical resource objects and space; and facilitate the capture of quantifiable data, over time, concerning resource use by key stakeholders. Finally we argue for the inclusion of appropriate stakeholder feedback and persuasive mechanism, to incentivise building user behaviour to support organisational level sustainability policy.

Enriching enterprise resource planning systems for strategic advantage: a semiotic motivated approach

Enterprise Resource Planning is often endorsed as a means to facilitate strategic advantage for businesses. The scarcity of resources is the method by which some businesses maintain their position. However, the ubiquitous trend towards the adoption of Enterprise Resourcing Planning systems coupled with market saturation makes the promise of advantage less compelling. Reported in this paper is a proposed solution based upon semiotic theory that takes a typical Enterprise Resource Planning deployment scenario and shapes it according to the needs of people in post-implementation contexts to leverage strategic advantage in different ways.

Doing more harm than good? Community based natural resource management and the neglect of local institutions in policy development

Approaches to natural resource management emphasise the importance of involving local people and institutions in order to build capacity, limit costs, and achieve environmental sustainability. Governments worldwide, often encouraged by international donors, have formulated devolution policies and legal instruments that provide an enabling environment for devolved natural resource management. However, implementation of these policies reveals serious challenges. This article explores the effects of limited involvement of local people and institutions in policy development and implementation. An in-depth study of the Forest Policy of Malawi and Village Forest Areas in the Lilongwe district provides an example of externally driven policy development which seeks to promote local management of natural resources. The article argues that policy which has weak ownership by national government and does not adequately consider the complexity of local institutions, together with the effects of previous initiatives on them, can create a cumulative legacy through which destructive resource use practices and social conflict may be reinforced. In short, poorly developed and implemented community based natural resource management policies can do considerably more harm than good. Approaches are needed that enable the policy development process to embed an in-depth understanding of local institutions whilst incorporating flexibility to account for their location-specific nature. This demands further research on policy design to enable rigorous identification of positive and negative institutions and ex-ante exploration of the likely effects of different policy interventions.

Precipitation scaling with temperature in warm and cold climates: an analysis of CMIP5 simulations

We investigate the scaling between precipitation and temperature changes in warm and cold climates using six models that have simulated the response to both increased CO2 and Last Glacial Maximum (LGM) boundary conditions. Globally, precipitation increases in warm climates and decreases in cold climates by between 1.5%/°C and 3%/°C. Precipitation sensitivity to temperature changes is lower over the land than over the ocean and lower over the tropical land than over the extratropical land, reflecting the constraint of water availability. The wet tropics get wetter in warm climates and drier in cold climates, but the changes in dry areas differ among models. Seasonal changes of tropical precipitation in a warmer world also reflect this “rich get richer” syndrome. Precipitation seasonality is decreased in the cold-climate state. The simulated changes in precipitation per degree temperature change are comparable to the observed changes in both the historical period and the LGM.

Evidence of a universal scaling relationship for leaf CO2 drawdown along an aridity gradient

The leaf carbon isotope ratio (δ13C) of C3 plants is inversely related to the drawdown of CO2 concentration during photosynthesis, which increases towards drier environments. We aimed to discriminate between the hypothesis of universal scaling, which predicts between-species responses of δ13C to aridity similar to within-species responses, and biotic homoeostasis, which predicts offsets in the δ13C of species occupying adjacent ranges. The Northeast China Transect spans 130–900 mm annual precipitation within a narrow latitude and temperature range. Leaves of 171 species were sampled at 33 sites along the transect (18 at ≥ 5 sites) for dry matter, carbon (C) and nitrogen (N) content, specific leaf area (SLA) and δ13C. The δ13C of species generally followed a common relationship with the climatic moisture index (MI). Offsets between adjacent species were not observed. Trees and forbs diverged slightly at high MI. In C3 plants, δ13C predicted N per unit leaf area (Narea) better than MI. The δ13C of C4 plants was invariant with MI. SLA declined and Narea increased towards low MI in both C3 and C4 plants. The data are consistent with optimal stomatal regulation with respect to atmospheric dryness. They provide evidence for universal scaling of CO2 drawdown with aridity in C3 plants.

The coevolution of two phytoplankton species on a single resource: allelopathy as a pseudo-mixotrophy

Without the top-down effects and the external/physical forcing, a stable coexistence of two phytoplankton species under a single resource is impossible — a result well known from the principle of competitive exclusion. Here I demonstrate by analysis of a mathematical model that such a stable coexistence in a homogeneous media without any external factor would be possible, at least theoretically, provided (i) one of the two species is toxin producing thereby has an allelopathic effect on the other, and (ii) the allelopathic effect exceeds a critical level. The threshold level of allelopathy required for the coexistence has been derived analytically in terms of the parameters associated with the resource competition and the nutrient recycling. That the extra mortality of a competitor driven by allelopathy of a toxic species gives a positive feed back to the algal growth process through the recycling is explained. And that this positive feed back plays a pivotal role in reducing competition pressures and helping species succession in the two-species model is demonstrated. Based on these specific coexistence results, I introduce and explain theoretically the allelopathic effect of a toxic species as a ‘pseudo-mixotrophy’—a mechanism of ‘if you cannot beat them or eat them, just kill them by chemical weapons’. The impact of this mechanism of species succession by pseudo-mixotrophy in the form of alleopathy is discussed in the context of current understanding on straight mixotrophy and resource-species relationship among phytoplankton species.

Natural disaster accounting bias and its equivalence across genetic resource stocks

Two sources of bias arise in conventional loss predictions in the wake of natural disasters. One source of bias stems from neglect of accounting for animal genetic resource loss. A second source of bias stems from failure to identify, in addition to the direct effects of such loss, the indirect effects arising from implications impacting animal-human interactions. We argue that, in some contexts, the magnitude of bias imputed by neglecting animal genetic resource stocks is substantial. We show, in addition, and contrary to popular belief, that the biases attributable to losses in distinct genetic resource stocks are very likely to be the same. We derive the formal equivalence across the distinct resource stocks by deriving an envelope result in a model that forms the mainstay of enquiry in subsistence farming and we validate the theory, empirically, in a World-Society-for-the-Protection-of-Animals application

The drivers of multinational enterprise subsidiary entrepreneurship in China: a new resource-based view perspective

This paper extends the resource-based view (RBV) of the firm, as applied to multinational enterprises (MNEs), by distinguishing between two critical resource dimensions, namely relative resource superiority (capabilities) and slack. Both dimensions, in concert with specific environmental conditions, are required to increase entrepreneurial activities. We propose distinct configurations (three-way moderation effects) of capabilities, slack, and environmental factors (i.e. dynamism and hostility) to explain entrepreneurship. Using survey data from 66 Canadian subsidiaries operating in China, we find that higher subsidiary entrepreneurship requires both HR slack and strong downstream capabilities in subsidiaries, subject to the industry environment being dynamic and benign. However, high HR slack alone, in a dynamic and benign environment, but without the presence of strong capabilities, actually triggers the fewest initiatives, with HR slack redirected from entrepreneurial experimentation towards complacency and inefficiency. This paper has major implications for MNEs seeking to increase subsidiary entrepreneurship in fast growing emerging markets.

Estimating the potential yield of small wind turbines in urban areas: a case study for Greater London, UK

To optimise the placement of small wind turbines in urban areas a detailed understanding of the spatial variability of the wind resource is required. At present, due to a lack of observations, the NOABL wind speed database is frequently used to estimate the wind resource at a potential site. However, recent work has shown that this tends to overestimate the wind speed in urban areas. This paper suggests a method for adjusting the predictions of the NOABL in urban areas by considering the impact of the underlying surface on a neighbourhood scale. In which, the nature of the surface is characterised on a 1 km2 resolution using an urban morphology database. The model was then used to estimate the variability of the annual mean wind speed across Greater London at a height typical of current small wind turbine installations. Initial validation of the results suggests that the predicted wind speeds are considerably more accurate than the NOABL values. The derived wind map therefore currently provides the best opportunity to identify the neighbourhoods in Greater London at which small wind turbines yield their highest energy production. The model does not consider street scale processes, however previously derived scaling factors can be applied to relate the neighbourhood wind speed to a value at a specific rooftop site. The results showed that the wind speed predicted across London is relatively low, exceeding 4 ms-1 at only 27% of the neighbourhoods in the city. Of these sites less than 10% are within 10 km of the city centre, with the majority over 20 km from the city centre. Consequently, it is predicted that small wind turbines tend to perform better towards the outskirts of the city, therefore for cities which fit the Burgess concentric ring model, such as Greater London, ‘distance from city centre’ is a useful parameter for siting small wind turbines. However, there are a number of neighbourhoods close to the city centre at which the wind speed is relatively high and these sites can only been identified with a detailed representation of the urban surface, such as that developed in this study.

Enforcing service level agreements using an economically enhanced resource manager

Traditional resource management has had as its main objective the optimisation of throughput, based on parameters such as CPU, memory, and network bandwidth. With the appearance of Grid Markets, new variables that determine economic expenditure, benefit and opportunity must be taken into account. The SORMA project aims to allow resource owners and consumers to exploit market mechanisms to sell and buy resources across the Grid. SORMA’s motivation is to achieve efficient resource utilisation by maximising revenue for resource providers, and minimising the cost of resource consumption within a market environment. An overriding factor in Grid markets is the need to ensure that desired Quality of Service levels meet the expectations of market participants. This paper explains the proposed use of an Economically Enhanced Resource Manager (EERM) for resource provisioning based on economic models. In particular, this paper describes techniques used by the EERM to support revenue maximisation across multiple Service Level Agreements.

Enforcing service level agreements using an economically enhanced resource manager

Traditional resource management has had as its main objective the optimisation of throughput, based on pa- rameters such as CPU, memory, and network bandwidth. With the appearance of Grid Markets, new variables that determine economic expenditure, benefit and opportunity must be taken into account. The SORMA project aims to allow resource owners and consumers to exploit market mechanisms to sell and buy resources across the Grid. SORMA’s motivation is to achieve efficient resource utilisation by maximising revenue for resource providers, and minimising the cost of resource consumption within a market environment. An overriding factor in Grid markets is the need to ensure that desired Quality of Service levels meet the expectations of market participants. This paper explains the proposed use of an Economically Enhanced Resource Manager (EERM) for resource provisioning based on economic models. In particular, this paper describes techniques used by the EERM to support revenue maximisation across multiple Service Level Agreements.