A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production

While traditional methods for modelling the thermal and electrical behaviour of photovoltaic (PV) modules rely on analytical and empirical techniques, machine learning is gaining interest as a way to reduce the time, expertise, and tools required by designers or experts while maintaining high accuracy and reliability. This research presents a data-driven machine learning tool based on artificial neural networks (ANNs) that can forecast yearly PV electricity directly at the optimal PV inclination angle without geographic restrictions and is valid for a wide range of electrical characteristics of PV modules. Additionally, empirical correlations were developed to easily determine the optimal PV inclination angle worldwide. The ANN algorithm, developed in Matlab, systematically and quantitatively summarizes the behaviour of eight PV modules in 48 worldwide climatic conditions. The algorithm's applicability and robustness were proven by considering two different PV modules in the same 48 locations. Yearly climatic variables and electrical/thermal PV module parameters serve as input training data. The yearly PV electricity is derived using dynamic simulations in the TRNSYS environment, which is a simulation program primarily and extensively used in the fields of renewable energy engineering and building simulation for passive as well as active solar design. Multiple performance metrics validate that the ANN-based machine learning tool demonstrates high reliability and accuracy in the PV energy production forecasting for all weather conditions and PV module characteristics. In particular, by using 20 neurons, the highest value of R-square of 0.9797 and the lowest values of the root mean square error and coefficient of variance of 14.67 kWh and 3.8%, respectively, were obtained in the training phase. This high accuracy was confirmed in the ANN validation phase considering other PV modules. An R-square of 0.9218 and values of the root mean square error and coefficient of variance of 31.95 kWh and 7.8%, respectively, were obtained. The results demonstrate the algorithm's vast potential to enhance the worldwide diffusion and economic growth of solar energy, aligned with the seventh sustainable development goal

Loop Quantum Cosmology, Boundary Proposals, and Inflation

Loop quantum cosmology of the closed isotropic model is studied with a special emphasis on a comparison with traditional results obtained in the Wheeler-DeWitt approach. This includes the relation of the dynamical initial conditions with boundary conditions such as the no-boundary or the tunneling proposal and a discussion of inflation from quantum cosmology.Comment: 20 pages, 6 figure

Spatially coordinated conservation auctions: a framed field experiment focusing on farmland wildlife conservation in China

How best to incentivize land managers to achieve conservation goals in an economically and ecologically effective manner is a key policy question that has gained increased relevance from the setting of ambitious new global targets for biodiversity conservation. Conservation (reverse) auctions are a policy tool for improving the environmental performance of agriculture, which has become well-established in the academic literature and in policy making in the US and Australia. However, little is known about the likely response of farmers to incentives within such an auction to (1) increase spatial connectivity and (2) encourage collective participation. This paper presents the first framed field experiment with farmers as participants that examines the effects of two features of conservation policy design: joint (collective) participation by farmers and the incentivization of spatial connectivity. The experiment employs farmers in China, a country making increasing use of payments for ecosystem services to achieve a range of environmental objectives. We investigate whether auction performance—both economic and ecological—can be improved by the introduction of agglomeration bonus and joint bidding bonus mechanisms. Our empirical results suggest that, compared to a baseline spatially coordinated conservation auction, the performance of an auction with an agglomeration bonus, a joint bidding bonus, or both, is inferior on two key metrics—the environmental benefits generated and cost effectiveness realized

Bosonic field equations from an exact uncertainty principle

A Hamiltonian formalism is used to describe ensembles of fields in terms of two canonically conjugate functionals (one being the field probability density). The postulate that a classical ensemble is subject to nonclassical fluctuations of the field momentum density, of a strength determined solely by the field uncertainty, is shown to lead to a unique modification of the ensemble Hamiltonian. The modified equations of motion are equivalent to the quantum equations for a bosonic field, and thus this exact uncertainty principle provides a new approach to deriving and interpreting the properties of quantum ensembles. The examples of electromagnetic and gravitational fields are discussed. In the latter case the exact uncertainty approach specifies a unique operator ordering for the Wheeler-DeWitt and Ashtekar-Wheeler-DeWitt equations.Comment: 24 pages, extended version of part (B) of hep-th/0206235, to appear in J. Phys.

Wave functions for arbitrary operator ordering in the de Sitter minisuperspace approximation

We derive exact series solutions for the Wheeler-DeWitt equation corresponding to a spatially closed Friedmann-Robertson-Walker universe with cosmological constant for arbitrary operator ordering of the scale factor of the universe. The resulting wave functions are those relevant to the approximation which has been widely used in two-dimensional minisuperspace models with an inflationary scalar field for the purpose of predicting the period of inflation which results from competing boundary condition proposals for the wave function of the universe. The problem that Vilenkin's tunneling wave function is not normalizable for general operator orderings, is shown to persist for other values of the spatial curvature, and when additional matter degrees of freedom such as radiation are included.Comment: 12 pages, revTeX-3.

The Warden Attitude: An investigation of the value of interaction with everyday wildlife

Using a discrete choice experiment, we elicit valuations of engagement with ‘everyday wildlife’ through feeding garden birds. We find that bird-feeding is primarily but not exclusively motivated by the direct consumption value of interaction with wildlife. The implicit valuations given to different species suggest that people prefer birds that have aesthetic appeal and that evoke human feelings of protectiveness. These findings suggest that people derive wellbeing by adopting a warden-like role towards ‘their’ wildlife. We test for external validity by conducting a hedonic analysis of sales of bird food. We discuss some policy implications of the existence of warden attitudes

The impact of COVID-19 on the management of European protected areas and policy implications

The COVID-19 pandemic led to many European countries imposing lockdown measures and limiting people’s movement during spring 2020. During the summer 2020, these strict lockdown measures were gradually lifted while in autumn 2020, local restrictions started to be re-introduced as a second wave emerged. After initial restrictions on visitors accessing many Nature Protected Areas (PAs) in Europe, management authorities have had to introduce measures so that all users can safely visit these protected landscapes. In this paper, we examine the challenges that emerged due to COVID-19 for PAs and their deeper causes. By considering the impact on and response of 14 popular European National and Nature Parks, we propose tentative longer-term solutions going beyond the current short-term measures that have been implemented. The most important challenges identified in our study were overcrowding, a new profile of visitors, problematic behavior, and conflicts between different user groups. A number of new measures have been introduced to tackle these challenges including information campaigns, traffic management, and establishing one-way systems on trail paths. However, measures to safeguard public health are often in conflict with other PA management measures aiming to minimize disturbance of wildlife and ecosystems. We highlight three areas in which management of PAs can learn from the experience of this pandemic: managing visitor numbers in order to avoid overcrowding through careful spatial planning, introducing educational campaigns, particularly targeting a new profile of visitors, and promoting sustainable tourism models, which do not rely on large visitor numbers.European Research Council (ERC) under the European Union’s Horizon 2020 research programme (Project FIDELIO, grant agreement no. 802605)

Biophilic architecture: a review of the rationale and outcomes

Contemporary cities have high stress levels, mental health issues, high crime levels and ill health, while the built environment shows increasing problems with urban heat island effects and air and water pollution. Emerging from these concerns is a new set of design principles and practices where nature needs to play a bigger part called “biophilic architecture”. This design approach asserts that humans have an innate connection with nature that can assist to make buildings and cities more effective human abodes. This paper examines the evidence for this innate human psychological and physiological link to nature and then assesses the emerging research supporting the multiple social, environmental and economic benefits of biophilic architecture

Meta-analysis of nature conservation values in Asia & Oceania: Data heterogeneity and benefit transfer issues

We conduct a meta-analysis (MA) of around 100 studies valuing nature conservation in Asia and Oceania. Dividing our dataset into two levels of heterogeneity in terms of good characteristics (endangered species vs. nature conservation more generally) and valuation methods, we show that the degree of regularity and conformity with theory and empirical expectations is higher for the more homogenous dataset of contingent valuation of endangered species. For example, we find that willingness to pay (WTP) for preservation of mammals tends to be higher than other species and that WTP for species preservation increases with income. Increasing the degree of heterogeneity in the valuation data, however, preserves much of the regularity, and the explanatory power of some of our models is in the range of other MA studies of goods typically assumed to be more homogenous (such as water quality). Subjecting our best MA models to a simple test forecasting values for out-of-sample observations, shows median (mean) forecasting errors of 24 (46) percent for endangered species and 46 (89) percent for nature conservation more generally, approaching levels that may be acceptable in benefit transfer for policy use. We recommend that the most prudent MA practice is to control for heterogeneity in regressions and sensitivity analysis, rather than to limit datasets by non-transparent criteria to a level of heterogeneity deemed acceptable to the individual analyst. However, the trade-off will always be present and the issue of acceptable level of heterogeneity in MA is far from settle