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Heavy Goods Vehicles, HGV, and Light Goods Vehicles, LGV, are a significant contributor to air pollution problems in urban areas. This paper quantifies the contribution to the environment of the deliveries to a single, large city employer addressing a research gap in the literature. Analysis of data from comprehensive surveys carried out over two years demonstrated that freight delivery traffic generated by an urban establishment with multiple properties in a compact urban setting, is characterised by a high proportion of LGV consistent with recent national and international trends. Also, despite freight traffic is only 10% of local traffic, more than 50% serves the single establishment, suggesting a different approach to policy making driven by the employer should be explored. The modelling results showed, relatively, the largest contribution to total emissions comes from HGVs in the AM peak, 13.8%, 43.7%, 9.2% for CO2, NOx and PM respectively. LGV contribute less, with 5.5%, 3.8%, 6% for CO2, NOx and PM respectively but more responsible for local congestion due to their numbers. This research is the first known study of its type and with the unique combination of measurement and traffic microsimulation allowed consideration of more effective traffic management strategies as well as providing evidence to support a consolidation centre for deliveries outside the city with fewer electric or low emissions last mile vehicles reducing substantially the environmental impact. The research outputs are relevant to many other similar cases in UK and Europe. The paper contributes to the ongoing development of research and policy looking to achieve sustainable urban logistics through receiver and purchasing led initiatives. [ABSTRACT FROM AUTHOR]

An 8-year (1998–2005), hourly data set of measurements of NOx, NO2, PM10, PM2.5, and PMcoarse (defined as PM2.5–10) from a busy roadside location in central London has been analyzed to identify important change-points in the time series using a cumulative sum (CUSUM) technique. Randomization methods were used to estimate the uncertainty level associated with the change-points with uncertainty intervals derived using a bootstrap approach. The results show that there is a clear change-point increase for NO2 coinciding with the introduction of the London congestion-charging in February 2003 (95% confidence interval from January–March 2003). At this time there was both an increase in bus numbers and buses fitted with catalyzed diesel particulate filters, which increase direct emissions of NO2. A highly statistically significant change-point was also observed for PMcoarse (95% confidence interval from December 2002–February 2003), which also occurred close to the time of the congestion charge introduction and is most closely related to the increase in bus flows. The increase in PMcoarse at this time has largely compensated for reductions in the concentration of PM2.5, such that the concentration of PM10 has remained almost constant. Comparing the 2 years before and after the introduction of congestion charging, the increment in NO2 above background increased from 22 to 34 ppb and PMcoarse increased from 4 to 9 μg m-3. These results could have important implications for meeting European air quality standards that currently set limits for PM10 rather than PM2.5. [ABSTRACT FROM AUTHOR]

Abstract: Plans to build a third runway at London Heathrow (LHR) airport have been held back because of concerns that the development would lead to annual mean concentrations of nitrogen dioxide (NO2) in excess of the EU Directive limit value, which must be met by 2010. The dominant effect of other sources of NO x close to the airport, primarily from road traffic, makes it difficult to detect and quantify the contribution made by the airport to local NO x and NO2 concentrations. This work presents approaches that aim to detect and quantify the airport contribution to NO x concentrations for a network of seven measurement sites close to the airport. Two principal approaches are used. First, a graphical technique using bivariate polar plots that develops the idea of a pollution rose is used to help discriminate between different source types. The sampling uncertainties associated with the technique have been calculated through a randomised re-sampling approach. Second, the unique pattern of aircraft activity at LHR enables data filtering techniques to be used to statistically verify the presence of aircraft sources. It is shown that aircraft NO x sources can be detected to at least 2.6km from the airport, even though the airport contribution at that distance is very small. Using these approaches, estimates have been made of the airport contribution to long-term mean concentrations of NO x and NO2. At the airfield boundary we estimate that approximately 27% of the annual mean NO x and NO2 is due to airport operations. At background locations 2–3km downwind of the airport we estimate that the upper limit of the airport contribution to be less than 15% (<10μgm−3). This work also provides approaches that would help validate and refine dispersion modelling studies used for airport assessments. [Copyright &y& Elsevier]