First UK field application and performance of microcapsule-based self-healing concrete

Maintaining the health and reliability of our infrastructure is of strategic importance. The current state of the UK infrastructure, and the associated huge costs of inspection, maintenance, repair and eventual replacement, is not sustainable and is no longer environmentally viable. The design of infrastructure, mainly concrete, remains traditional and poor material performance continues to be the main cause of deterioration and failure in our infrastructure systems. Biomimetic materials, that emulate natural biological systems in their ability to self-healing, provide an exciting and plausible solution. Embedding cementitious materials with in-built capabilities to sense and respond to their environmental triggers could potentially eliminate all external interventions and deliver a resilience infrastructure. The work presented in this paper forms part of a national initiative that has been developing biomimetic cementitious infrastructure materials which culminated in the first large-scale field trials of self-healing concrete in the UK testing four different but complementary technologies that were developed. This paper focuses on one self-healing technology, namely microcapsules, which contain a healing agent that is released on their rupture as a result of crack propagation. The paper will present details of the microcapsules used, their implementation in concrete and in the field trials and time-related, field and laboratory, assessment of the self-healing process. It also highlights challenges faced and improvements that are now on-going to produce the next generation of the microcapsule self-healing cementitious system

A comprehensive approach for the simulation of the Urban Heat Island effect with the WRF/SLUCM modeling system: The case of Athens (Greece)

This study presents a comprehensive modeling approach for simulating the spatiotemporal distribution of urban air temperatures with a modeling system that includes the Weather Research and Forecasting (WRF) model and the Single-Layer Urban Canopy Model (SLUCM) with a modified treatment of the impervious surface temperature. The model was applied to simulate a 3-day summer heat wave event over the city of Athens, Greece. The simulation, using default SLUCM parameters, is capable of capturing the observed diurnal variation of urban temperatures and the Urban Heat Island (UHI) in the greater Athens Area (GAA), albeit with systematic biases that are prominent during nighttime hours. These biases are particularly evident over low-intensity residential areas, and they are associated with the surface and urban canopy properties representing the urban environment. A series of sensitivity simulations unravels the importance of the sub-grid urban fraction parameter, surface albedo, and street canyon geometry in the overall causation and development of the UHI effect. The sensitivities are then used to determine optimal values of the street canyon geometry, which reproduces the observed temperatures throughout the simulation domain. The optimal parameters, apart from considerably improving model performance (reductions in mean temperature bias from 0.30 °C to 1.58 °C), are also consistent with actual city building characteristics - which gives confidence that the model set-up is robust, and can be used to study the UHI in the GAA in the anticipated warmer conditions in the future. © 2017 Elsevier B.V

First UK field application and performance of microcapsule-based self-healing concrete

Maintaining the health and reliability of our infrastructure is of strategic importance. The current state of the UK infrastructure, and the associated huge costs of inspection, maintenance, repair and eventual replacement, is not sustainable and is no longer environmentally viable. The design of infrastructure, mainly concrete, remains traditional and poor material performance continues to be the main cause of deterioration and failure in our infrastructure systems. Biomimetic materials, that emulate natural biological systems in their ability to self-healing, provide an exciting and plausible solution. Embedding cementitious materials with in-built capabilities to sense and respond to their environmental triggers could potentially eliminate all external interventions and deliver a resilience infrastructure. The work presented in this paper forms part of a national initiative that has been developing biomimetic cementitious infrastructure materials which culminated in the first large-scale field trials of self-healing concrete in the UK testing four different but complementary technologies that were developed. This paper focuses on one self-healing technology, namely microcapsules, which contain a healing agent that is released on their rupture as a result of crack propagation. The paper will present details of the microcapsules used, their implementation in concrete and in the field trials and time-related, field and laboratory, assessment of the self-healing process. It also highlights challenges faced and improvements that are now on-going to produce the next generation of the microcapsule self-healing cementitious system

A model for European Biogenic Volatile Organic Compound emissions: Software development and first validation

A grid-oriented Biogenic Emission Model (BEM) has been developed to calculate Non-Methane Volatile Organic Compound (NMVOC) emissions from vegetation in high spatial and temporal resolutions. The model allows the emissions calculation for any modeling domain covering Europe on the basis of: 1) the U.S. Geological Survey 1-km resolution land-use database, 2) a land-use specific, monthly isoprene, monoterpene and Other Volatile Organic Compound (OVOC) emission potentials and foliar biomass densities database, 3) temperature and solar radiation data provided by the mesoscale meteorological model MM5. The model was applied for Europe in 30-km spatial resolution for the year 2003. The European total emissions for 2003 consist of 33.0% isoprene, 25.5% monoterpenes and 41.5% OVOC. BEM results are compared with those from the well-documented global Model of Emissions of Gases and Aerosols from Nature (MEGAN). The BEM total emissions compare well with the MEGAN ones. In July 2003, the results of both models agree within a factor of 1.2 for total isoprene emissions and within a factor of 2 for total monoterpene emissions. The comparison of the spatial distributions of the July 2003 isoprene and monoterpene emissions calculated with BEM and MEGAN shows that, in the greater part of the study area, the differences are below the current uncertainty limit for the estimation of spatially-resolved biogenic VOC emissions in Europe being equal to about ±600 kg km-2 month-1. Differences that are above this limit are found mainly in the eastern European countries for isoprene and in the Mediterranean countries for monoterpenes. © 2010 Elsevier Ltd

Comparisons of ground-based tropospheric NO₂ MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01  ×  1015 molecules cm−2