The impact of the congestion charging scheme on ambient air pollution concentrations in London

On 17th February 2003, a congestion charging scheme (CCS), operating Monday–Friday, 07:00–18:00, was introduced in central London along with a programme of traffic management measures. We investigated the potential impact of the introduction of the CCS on measured pollutant concentrations (oxides of nitrogen (NO_X, NO and NO₂), particles with a median diameter less than 10 microns (PM₁₀), carbon monoxide (CO) and ozone (O₃)) measured at roadside and background monitoring sites across Greater London. Temporal changes in pollution concentrations within the congestion charging zone were compared to changes, over the same time period, at monitors unlikely to be affected by the CCS (the control zone) and in the boundary zone between the two. Similar analyses were done for CCS hours during weekends (when the CCS was not operating).Based on the single roadside monitor with the CCS Zone, it was not possible to identify any relative changes in pollution concentrations associated with the introduction of the scheme. However, using background monitors, there was good evidence for a decrease in NO and increases in NO₂ and O₃ relative to the control zone. There was little change in background concentrations of NO_X. There was also evidence of relative reductions in PM₁₀ and CO. Similar changes were observed during the same hours in weekends when the scheme was not operating.The causal attribution of these changes to the CCS per se is not appropriate since the scheme was introduced concurrently with other traffic and emissions interventions which might have had a more concentrated effect in central London. This study provides important pointers for study design and data requirements for the evaluation of similar schemes in terms of air quality. It also shows that results may be unexpected and that the overall effect on toxicity may not be entirely favourable.     

Selections from the history of environmental pollution, with special attention to air pollution. Part 1.

Several comprehensive publications have been issued recently on the environmental pollution of past times (e.g. Tylecote, 1976; Nriagu, 1983a; Brimblecombe, 1987a; Goldstein, 1988; Healy, 1988; Brimblecombe and Pfister, 1990; Hughes, 1993; Markham, 1994; Brimblecombe, 1995; Karatzas, 2000, 2001; McNeill, 2001; Meszaros, 2001). The aim of this study is to give an overview of information on the subject – mainly related to ancient times.     

Lichen and bryophyte distribution on oak in London in relation to air pollution and bark acidity

Epiphytic lichen and bryophyte distribution and frequency were investigated on the trunks of 145 young oak trees throughout London and surrounding counties, and compared with pollution levels and bark pH. Sixty-four lichen and four bryophyte species were recorded. Three major zones were identified: (i) two central regions with a few lichens, bryophytes absent; (ii) a surrounding region with a more diverse flora including a high cover of nitrophyte lichens; and (iii) an outer region, characterised by species absent from central London, including acidophytes. Nineteen species were correlated with nitrogen oxides and 16 with bark pH, suggesting that transport-related pollution and bark acidity influence lichen and bryophyte distribution in London today. Lichens and bryophytes are responding to factors that influence human and environmental health in London. Biomonitoring therefore has a practical role to assess the effects of measures to improve London's air quality.     

Analysis and evaluation of selected local-scale PM10 air pollution episodes in four European cities: Helsinki,London, Milan and Oslo

We have analysed in detail four selected episodes involving substantially high concentrations of PM₁₀ that occurred in Oslo on 4–10 January 2003, in Helsinki on 3–14 April 2002, in London on 18–27 February 2003 and in Milan on 14–19 December 1998. We have also utilised a more extensive dataset containing relevant information regarding 21 episodes from seven cities in six countries. The four episodes analysed in detail were recently occurring cases that were at least partly caused by various local emission sources. In particular, we have addressed the evolution of the measured concentrations in terms of the measured, meteorologically pre-processed and predicted (using numerical weather prediction models and a meso-scale meteorological model) meteorological variables. All the four episodes addressed were associated with areas of high pressure (Oslo, Helsinki and London) or a high-pressure ridge (Milan). The best meteorological prediction variables were found to be the temporal evolution of the temperature inversions and atmospheric stability and, in some of the cases, wind speed. Strong ground-based or slightly elevated temperature inversions prevailed in the course of the episodes in Oslo, Helsinki and Milan, and there was a slight ground-based inversion also in London; their occurrence coinciding with the highest PM₁₀ concentrations. The same result was also obtained by considering an additional set of seven PM₁₀ episodes from the larger dataset. The inversions in Oslo and Milan were mainly caused by the advection of warmer air above a relatively colder surface, and that in Helsinki by radiation cooling of snow-covered ground. It was also found that a low wind speed is not necessarily a good indicator of episodes; this is the case, e.g., in the Po valley, due to the frequently occurring calm and low wind speed conditions there.     

Self-organized criticality of air pollution

In this work, we investigate the frequency-size distribution of three pollution indexes (PM₁₀, NO₂ and SO₂) in Shanghai. They are well approximated by power-law distributions, which suggest that air pollution might be a manifestation of self-organized criticality. We introduce a new numerical sandpile model with decay coefficient to reveal inherent dynamic mechanism of air pollution. Only changing the number value of decay coefficient of pollutants, this model gives a good simulation of three pollutants' statistical characteristic. This work shows that it is the self-organized criticality of the air pollutants that results in the temporal variation of air pollutant indexes and the minor air pollution sources can trigger the occurrence of large pollutant events by SOC behavior.     

空气污染暴露评价研究进展

介绍了暴露及暴露评价的基本概念、人体空气污染暴露评价的指示物及其特征,讨论暴露评价方法的类型,对各种方法的优、缺点进行了比较分析。根据综述和案例分析情况,对空气污染暴露评价研究的发展趋势进行了展望。