Lifestyle trends for heating and cooling in Maltese households

According to the EU Directive 2009/28/EC Malta is obliged to reach a 10% renewable energy share of the total final energy consumption by the year 2020. Due to the challenging targets, Malta seems to be finding it hard to achieve the agreed trajectories. Renewable energy applications in an island state like Malta are hard to achieve due to various constraints, including: lack of space, multiple land-uses and land-use conflicts, few natural resources, low social acceptance, lack of financial resources, lack of expertise, and lack of capacity building. Hence, it would be more feasible to also focus on energy efficiency in buildings which is one of the major consumers of energy on the island. More than 30% of the energy production in Malta is used by buildings, including households. Primarily, this is where the authorities lack information, in the light of heating and cooling of air and water heating in buildings. This paper investigates the status-quo of existing lifestyle trends for space heating and cooling, and water heating, in Maltese households. The scope is to evaluate the potential of shifting to more energy efficient systems that can positively contribute towards the decline of energy consumption in houses, and thus indirectly help to attain the renewable energy targets set for year 2020 and beyond. Energy behaviour and attitudes of Maltese citizens have also been analysed.peer-reviewe

Statistical analysis of particulate matter data in Doha, Qatar

Pollution in Doha is measured using passive, active and automatic sampling. In this paper we consider data automatically sampled in which various pollutants were continually collected and analysed every hour. At each station the sample is analysed on-line and in real time and the data is stored within the analyser, or a separate logger so it can be downloaded remotely by a modem. The accuracy produced enables pollution episodes to be analysed in detail and related to traffic flows, meteorology and other variables. Data has been collected hourly over more than 6 years at 3 different locations, with measurements available for various pollutants – for example, ozone, nitrogen oxides, sulphur dioxide, carbon monoxide, THC, methane and particulate matter (PM1.0, PM2.5 and PM10), as well as meteorological data such as humidity, temperature, and wind speed and direction. Despite much care in the data collection process, the resultant data has long stretches of missing values, when the equipment has malfunctioned – often as a result of more extreme conditions. Our analysis is twofold. Firstly, we consider ways to “clean” the data, by imputing missing values, including identified outliers. The second aspect specifically considers prediction of each particulate (PM1.0, PM2.5 and PM10) 24 hours ahead, using current (and previous) pollution and meteorological data. In this case, we use vector autoregressive models, compare with decision trees and propose variable selection criteria which explicitly adapt to missing data. Our results show that the regression tree models, with no variable transformations, perform the best, and that attempts to impute missing values are hampered by non-random missingness

An innovative approach to manage uncertainties and stock diversity in the EPBD cost-optimal methodology

The EU Energy Performance of Buildings Directive (EPBD) 2010/31/EU is a step in the right direction to promote near zero energy buildings (NZEB) in a step-wise manner, starting with minimum energy performance and cost optimal thresholds for “reference buildings” (RBs) for each category. Nevertheless, a standard method for defining RBs does not exist, which led to a great divergence between MS in the level of detail used to define RBs for the EPBD cost-optimal analysis. Such lack of harmonisation between MS is further evident given the resulting large discrepancies in energy performance indicators even between countries having similar climate. Furthermore, discrepancies of 30% or higher between measured energy performance and that derived from the EPBD software induces uncertainty in the actual operational savings of measures leading to cost-optimality or NZEB in the simulated environment. This research proposes a robust and innovative framework to better handle uncertainties in the EPBD cost-optimal method both in the building software input parameters and in the global Life Cycle Costings (LCC), making the EPBD more useful for policy makers and ensuring a more harmonised approach among MS. The concept behind the proposed framework is the combination of a stochastic EPBD cost-optimal approach with Bayesian bottom-up calibrated stock-modelling. A new concept of “reference zoning” versus the “reference buildings” approach is also introduced in this research, which aims at providing a simpler and more flexible aggregation of energy performance for the more complex commercial building stock.peer-reviewe

Contribution of solar applications towards achieving a renewable energy target for Malta

Based on applied research and demonstration activities carried out during the past decade at the Institute for Energy Technology, solar photovoltaic applications offer a good prospective towards achieving a significant percentage of Malta’s electricity needs. This paper summarises the most important conclusions reached, describes the current installed systems in Malta, sets the achievable targets and discusses the challenges that face the widespread applications of this technology. Moreover, consideration is given to the widespread applications of solar water heating systems and their contribution towards lowering electricity consumption.peer-reviewe