Commuting, CO2 and the location of offices

This paper investigates the extent to which office activity contributes to travel-related CO2 emission. Using ‘end-user’ figures[1], travel accounts for 32% of UK CO2 emission (Commission for Integrated Transport, 2007) and commuting and business travel accounts for a fifth of transport-related CO2 emissions, equating to 6.4% of total UK emissions (Building Research Establishment, 2000). Figures from the Department for Transport (2006) report that 70% of commuting trips were made by car, accounting for 73% of all commuting miles travelled. In assessing the environmental performance of an office building, the paper questions whether commuting and business travel-related CO2 emission is being properly assessed. For example, are office buildings in locations that are easily accessible by public transport being sufficiently rewarded? The de facto method for assessing the environmental performance of office buildings in the UK is the Building Research Establishment’s Environmental Assessment Method (BREEAM). Using data for Bristol, this paper examines firstly whether BREEAM places sufficient weight on travel-related CO2 emission in comparison with building operation-related CO2 emission, and secondly whether the methodology for assigning credits for travel-related CO2 emission efficiency is capable of discerning intra-urban differences in location such as city centre and out-of-town. The results show that, despite CO2 emission per worker from building operation and travel being comparable, there is a substantial difference in the credit-weighting allocated to each. Under the current version of BREEAM for offices, only a maximum of 4% of the available credits can be awarded for ensuring the office location is environmentally sustainable. The results also show that all locations within the established city centre of Bristol will receive maximum BREEAM credits. Given the parameters of the test there is little to distinguish one city centre location from another and out of town only one office location receives any credits. It would appear from these results that the assessment method is not able to discern subtle differences in the sustainability of office locations

A method for merging flow-dependent forecast error statistics from an ensemble with static statistics for use in high resolution variational data assimilation

The background error covariance matrix, B, is often used in variational data assimilation for numerical weather prediction as a static and hence poor approximation to the fully dynamic forecast error covariance matrix, Pf. In this paper the concept of an Ensemble Reduced Rank Kalman Filter (EnRRKF) is outlined. In the EnRRKF the forecast error statistics in a subspace defined by an ensemble of states forecast by the dynamic model are found. These statistics are merged in a formal way with the static statistics, which apply in the remainder of the space. The combined statistics may then be used in a variational data assimilation setting. It is hoped that the nonlinear error growth of small-scale weather systems will be accurately captured by the EnRRKF, to produce accurate analyses and ultimately improved forecasts of extreme events.

The inflation hedging characteristics of US and UK investments: a multi-factor error correction approach

Historic analysis of the inflation hedging properties of stocks produced anomalous results, with equities often appearing to offer a perverse hedge against inflation. This has been attributed to the impact of real and monetary shocks to the economy, which influence both inflation and asset returns. It has been argued that real estate should provide a better hedge: however, empirical results have been mixed. This paper explores the relationship between commercial real estate returns (from both private and public markets) and economic, fiscal and monetary factors and inflation for US and UK markets. Comparative analysis of general equity and small capitalisation stock returns in both markets is carried out. Inflation is subdivided into expected and unexpected components using different estimation techniques. The analyses are undertaken using long-run error correction techniques. In the long-run, once real and monetary variables are included, asset returns are positively linked to anticipated inflation but not to inflation shocks. Adjustment processes are, however, gradual and not within period. Real estate returns, particularly direct market returns, exhibit characteristics that differ from equities.