Synchronous degassing patterns of the neighbouring volcanoes Llaima and Villarrica in south-central Chile: the influence of tidal forces

The neighbouring volcanoes Villarrica and Llaima are two of the most active volcanoes in Chile and both currently degas continuously. We present a semi-continuous time series of SO2 fluxes for Villarrica and Llaima volcanoes. The time series was obtained using five scanning Mini-Differential Optical Absorption Spectrometers (Mini-DOAS, UV spectrometers) over 6 months (13 February to 31 July 2010) and is based on 6,829 scans for Villarrica and 7,165 scans for Llaima. Statistical analyses of the SO2 flux time series reveal a periodicity of degassing maxima about every 7 days, and further a conspicuous synchronicity of the degassing maxima and minima between the two volcanoes. Intra-day variations in SO2 fluxes also show a striking correlation between Villarrica and Llaima. All these patterns correlate well with the trend of the modelled solid Earth tide curves, where the 7-day degassing maxima correspond with both the fortnightly tidal maxima and minima. The intra-day degassing peaks mostly correlate well with the periods of maximum deformation rates during the diurnal tidal cycle, and further with semidiurnal minima in atmospheric pressure, a phenomenon we refer to as “the tidal pump”. As there is little time lag between the tidal action and the changes in degassing rates, we infer that degassing at both volcanoes is controlled by conduit convection, involving physical separation between gas and magma at comparatively shallow levels. Variations in daily degassing rates were up to a factor of ca. 12 and 10 for Villarrica and Llaima, respectively, without any noticeable changes in the periodicity. We thus suggest that the described cyclic variations must be taken into account for all comparable volcanoes when using gas monitoring as a tool for volcanic hazard mitigation

Together at Last bHLH and LIM-HD Regulators Cooperate to Specify Motor Neurons

AbstractbHLH and LIM-HD transcription factors were originally thought to act at different stages of neurogenesis: bHLHs as neuronal “inducers” and LIM-HDs as postmitotic subtype determinants. These distinctions are becoming blurred, and a current study by Lee and Pfaff in this issue of Neuron shows that interaction between these factors functions to synchronize neurogenesis with neuronal cell type specification

A comparative analysis of building energy estimation methods in the context of demand response

A critical element of assessing a building’s suitability for Demand Side Response (DSR) is understanding its turndown potential to ensure that DSR participation will be financially viable. While research has been undertaken on site level DSR estimation methods, there is currently no research that compares the outcomes of these methods. This paper compares four non-domestic energy estimation methods used for understanding the DSR potential of electrical appliances in a building to provide insights about uncertainty levels based on input requirements. Each method is deployed to estimate the DSR potential of HVAC chiller assets at two UK hotels over two years. The results show the methods have a range of error levels from the highest Mean Average Percentage Error (MAPE) of 159% to the lowest MAPE of 39%. The input requirements followed a general trend of more complex informational inputs resulting in lower error values. The outcomes of this research enable users to make informed decisions in selecting DSR estimation methods based on information availability and acceptable estimation error levels

Modelling the overheating risk in an uniform high-rise building design with a consideration of urban context and heatwaves

Overheating in buildings is one of the increasing concerns related to climate change and can lead to an increase in heat-related health issues and higher energy consumption due to the use of air conditioning systems. Literature shows that internal conditions and demand on environmental control systems can vary with height within buildings. However, an architectural trend towards highly glazed façades for tall buildings suggests the vertical gradient of performance is not always considered in the design process. By simulating a high-rise residential building in London, a comparative analysis of the overheating risks and daylighting at different levels in the building was conducted. In this study the model was able to consider the influence of surrounding built environment on solar gain and so influence of urban location on overheating risk was taken into account. Simulations were conducted using typical reference years as well as meteorological data for specific heat-wave periods experienced in London and that are expected to become more intense and frequent due to climate change. Passive mitigation options (external shading) are demonstrated to help reduce overheating occurrence by 74%, at the same time the impact of decreased daylighting (30%) is less problematic at higher levels where daylight factor is greater

Small power load disaggregation in office buildings based on electrical signature classification

This paper assesses the application of Non-Intrusive Appliance Load Monitoring (NIALM) methods for disaggregating electricity consumption in office buildings. The focus of the research is on small power equipment, which can represent up to 50% of the electricity use in buildings fitted with high efficiency building services. Research in this field has led to numerous algorithms being developed for use with NIALM systems, however, due to the highly variable nature of electrical appliances no suitable common characteristic has been identified for disaggregation. This paper presents an analysis of a set of electrical signatures based on transient and current-voltage phase shift during steady-state conditions for which subsets of the signatures are considered for identifying different small power loads. The ability of this approach to disaggregate appliance loads is demonstrated with the idea of applying disaggregation techniques during energy audits of office buildings

Modelling thermal loads for a non-domestic building stock: associating a priori probability with building form and construction - using building control laws and regulations.

Building Energy Assessment at stock level is an important task in identifying the best strategies for achieving a more energy efficient and low carbon society. Non-domestic buildings are identified to make up 17% of total energy consumption in England and Wales and 19% of CO2 emissions. To understand the energy requirement of the non-domestic stock, large scale (empirically based) energy surveying has been carried out namely in the Non-Domestic Building Stock project and Carbon Reductions in Buildings project. It is recognised that building energy surveys are difficult to carry out; expensive on time, technical resources, and metered energy use is (on a large scale) necessarily crude. With improving computer ability, dynamic energy modelling tools allow for detailed assessment of building energy use and comfort performance. Using Monte Carlo simulation a method of assessing the probable variability in non-domestic building thermal energy loads was developed. The method was developed to capture the heterogeneity in non-domestic buildings at national stock level and determine how stock level physical form variations impact thermal loading. Non-domestic building form and surrounding topography are considered to be influenced by building control laws and building regulations. Control documentation often stipulates guidelines and best practice - hence building heterogeneity. As such, historical regulations were used to develop basic probability distributions of potential physical characteristics associated with non-domestic buildings. Stating that form and site characteristics are randomly determined from the defined probability distributions, a stochastic modelling process to represent thermal variation in a building stock was developed. This provided potential for categorising building thermal performance by period of construction. The model utilised a dynamic simulation model as a 'black-box' for predicting base thermal loads