Www.airqualitynow.eu, a common website and air quality indices to compare cities across europe

International audienceAir quality is a public concern. This is partly due to the "right to know" principle embodied in European legislation. Despite this common legislation, the way air quality is being interpreted and communicated differs considerably. For specialists raw monitoring data for Europe are available but these are not usable by the general public. Easy to understand and internationally comparable air quality information from one city to another is scarce: there are almost as many air quality indices as air quality monitoring networks. The CITEAIR II project (Common information to European Air, INTERREG IVc) facilitates the comparison of urban air quality in near real-time by introducing common air quality indices at hourly, daily and annual scales and by developing a forecast for those indices for D+0 and D+1.The implementation was based on a common website www.airqualitynow.eu using readily available simple IT-solutions. This paper describes those tools which both aimed at presenting the air quality of the participating cities in a comparable way and not to replace more targeted local information. Their added value is to provide, for the first time, a European and comparable picture of the air quality in near real-time easily accessible through a common platform and presentation of the results. The website is designed to receive and display data from any city wanting to join. The main part is dedicated to compare the cities index values using different time scales (hourly, daily or annual) and two types of exposure thanks to a background and a traffic index. In addition, space is offered to cities for presenting themselves according to a common template, providing background information on their specific air pollution situation and associated reduction measures. Participating is easy: cities upload their data through ftp and the indices calculations are automatically made. The website provides a dynamic picture of the air quality and is updated each hour enticing viewers to make repeated visits. However, participation with only a daily update or with yearly data is feasible as wel

Towards uncertainty mapping in air-quality modelling and assessment

The aim of this paper is to promote the use of uncertainty mapping when spatial assessments of air quality are made. A large number of air quality maps are produced for scientific and policy purposes but rarely are corresponding maps of their uncertainty included. The need for such maps and the methods to produce them are described. Several uncertainty parameters are discussed but it is recommended to use the probability density function as the basis of the uncertainty estimates. Several examples are provided discussing indicative uncertainty, ensemble methods, comparisons with observations, spatial representativeness, uncertainty in exceedances and probability of exceedance.publishe

High resolution exposure modelling of heat and air pollution and the impact on mortality

Background Elevated temperature and air pollution have been associated with increased mortality. Exposure to heat and air pollution, as well as the density of vulnerable groups varies within cities. The objective was to investigate the extent of neighbourhood differences in mortality risk due to heat and air pollution in a city with a temperate maritime climate. Methods A case-crossover design was used to study associations between heat, air pollution and mortality. Different thermal indicators and air pollutants (PM10, NO2, O3) were reconstructed at high spatial resolution to improve exposure classification. Daily exposures were linked to individual mortality cases over a 15 year period. Results Significant interaction between maximum air temperature (Tamax) and PM10 was observed. During “summer smog” days (Tamax > 25 °C and PM10 > 50 μg/m3), the mortality risk at lag 2 was 7% higher compared to the reference (Tamax 15 °C and PM10 15 μg/m3). Persons above age 85 living alone were at highest risk. Conclusion We found significant synergistic effects of high temperatures and air pollution on mortality. Single living elderly were the most vulnerable group. Due to spatial differences in temperature and air pollution, mortality risks varied substantially between neighbourhoods, with a difference up to 7%

Public health impacts of city policies to reduce climate change:Findings from the URGENCHE EU-China project

Climate change is a global threat to health and wellbeing. Here we provide findings of an international research project investigating the health and wellbeing impacts of policies to reduce greenhouse gas emissions in urban environments.; Five European and two Chinese city authorities and partner academic organisations formed the project consortium. The methodology involved modelling the impact of adopted urban climate-change mitigation transport, buildings and energy policy scenarios, usually for the year 2020 and comparing them with business as usual (BAU) scenarios (where policies had not been adopted). Carbon dioxide emissions, health impacting exposures (air pollution, noise and physical activity), health (cardiovascular, respiratory, cancer and leukaemia) and wellbeing (including noise related wellbeing, overall wellbeing, economic wellbeing and inequalities) were modelled. The scenarios were developed from corresponding known levels in 2010 and pre-existing exposure response functions. Additionally there were literature reviews, three longitudinal observational studies and two cross sectional surveys.; There are four key findings. Firstly introduction of electric cars may confer some small health benefits but it would be unwise for a city to invest in electric vehicles unless their power generation fuel mix generates fewer emissions than petrol and diesel. Second, adopting policies to reduce private car use may have benefits for carbon dioxide reduction and positive health impacts through reduced noise and increased physical activity. Third, the benefits of carbon dioxide reduction from increasing housing efficiency are likely to be minor and co-benefits for health and wellbeing are dependent on good air exchange. Fourthly, although heating dwellings by in-home biomass burning may reduce carbon dioxide emissions, consequences for health and wellbeing were negative with the technology in use in the cities studied.; The climate-change reduction policies reduced CO2 emissions (the most common greenhouse gas) from cities but impact on global emissions of CO2 would be more limited due to some displacement of emissions. The health and wellbeing impacts varied and were often limited reflecting existing relatively high quality of life and environmental standards in most of the participating cities; the greatest potential for future health benefit occurs in less developed or developing countries

Hitte-overlast en luchtverontreiniging versterken elkaar

Periodes met hitte gekoppeld aan stedelijke luchtverontreiniging hebben gevolgen voor de gezondheid en het welzijn van de inwoners in de stad. ze leiden tot hittestress en in het extreme geval tot vroegtijdige sterfte. Onderzoek uit 2011 liet zien dat temperatuur en luchtvervuiling vaak tegelijk verhoogd zijn. Of de twee elkaar versterken in hun effect op vroegtijdige sterfte kon toen niet worden bewezen. Uit een gedetailleerd onderzoek voor Rotterdam is die interactie nu wel vastgesteld. Hieruit blijkt ook dat de luchtkwaliteit en het aantal dagen met hittestress sterk per buurt kunnen verschillen

Improvements in air quality in the Netherlands during the corona lockdown based on observations and model simulations

The lockdown measures in response to the SARS-CoV-2 virus outbreak in 2020 have resulted in reductions in emissions of air pollutants and corresponding ambient concentrations. In the Netherlands, the most stringent lockdown measures were in effect from March to May 2020. These measures coincided with a period of unusual meteorological conditions with wind from the north-east and clear-sky conditions, which complicates the quantification of the effect of the lockdown measures on the air quality. Here we quantify the lockdown effects on the concentrations of nitrogen oxides (NOx and NO2), particulate matter (PM10 and PM2.5) and ozone (O3) in the Netherlands, by analyzing observations and simulations with the atmospheric chemistry-transport model EMEP/MSC-W in its EMEP4NL configuration, after eliminating the effects of meteorological conditions during the lockdown. Based on statistical analyses with a Random Forest method, we estimate that the lockdown reduced observed NO2 concentrations by 30% (95% confidence interval 25–35%), 26% (21–32%), and 18% (10–25%) for traffic, urban, and rural background locations, respectively. Slightly smaller reductions of 8–28% are found with the EMEP4NL simulations for urban and regional background locations based on estimates in reductions in economic activity and emissions of traffic and industry in the Netherlands and other European countries. Reductions in observed PM2.5 concentrations of about 20% (10–25%) are found for all locations, which is somewhat larger than the estimates of 5–16% based on the model simulations. A comparison of the calculated NO2 traffic contributions with observations shows a substantial drop of about 35% in traffic contributions during the lockdown period, which is similar to the estimated reductions in mobility data as reported by Apple and Google. Since the largest health effects related to air pollution in the Netherlands are associated with exposure to PM10 and PM2.5, the lockdown measures in spring of 2020 have temporarily improved the air quality in the Netherlands. The concentrations of the most health relevant compounds have only been reduced by about 10–25%

Improvements in air quality in the Netherlands during the corona lockdown based on observations and model simulations

The lockdown measures in response to the SARS-CoV-2 virus outbreak in 2020 have resulted in reductions in emissions of air pollutants and corresponding ambient concentrations. In the Netherlands, the most stringent lockdown measures were in effect from March to May 2020. These measures coincided with a period of unusual meteorological conditions with wind from the north-east and clear-sky conditions, which complicates the quantification of the effect of the lockdown measures on the air quality. Here we quantify the lockdown effects on the concentrations of nitrogen oxides (NOx and NO2), particulate matter (PM10 and PM2.5) and ozone (O3) in the Netherlands, by analyzing observations and simulations with the atmospheric chemistry-transport model EMEP/MSC-W in its EMEP4NL configuration, after eliminating the effects of meteorological conditions during the lockdown. Based on statistical analyses with a Random Forest method, we estimate that the lockdown reduced observed NO2 concentrations by 30% (95% confidence interval 25–35%), 26% (21–32%), and 18% (10–25%) for traffic, urban, and rural background locations, respectively. Slightly smaller reductions of 8–28% are found with the EMEP4NL simulations for urban and regional background locations based on estimates in reductions in economic activity and emissions of traffic and industry in the Netherlands and other European countries. Reductions in observed PM2.5 concentrations of about 20% (10–25%) are found for all locations, which is somewhat larger than the estimates of 5–16% based on the model simulations. A comparison of the calculated NO2 traffic contributions with observations shows a substantial drop of about 35% in traffic contributions during the lockdown period, which is similar to the estimated reductions in mobility data as reported by Apple and Google. Since the largest health effects related to air pollution in the Netherlands are associated with exposure to PM10 and PM2.5, the lockdown measures in spring of 2020 have temporarily improved the air quality in the Netherlands. The concentrations of the most health relevant compounds have only been reduced by about 10–25%

Improvements in air quality in the Netherlands during the corona lockdown based on observations and model simulations.

The lockdown measures in response to the SARS-CoV-2 virus outbreak in 2020 have resulted in reductions in emissions of air pollutants and corresponding ambient concentrations. In the Netherlands, the most stringent lockdown measures were in effect from March to May 2020. These measures coincided with a period of unusual meteorological conditions with wind from the north-east and clear-sky conditions, which complicates the quantification of the effect of the lockdown measures on the air quality. Here we quantify the lockdown effects on the concentrations of nitrogen oxides (NOx and NO2), particulate matter (PM10 and PM2.5) and ozone (O3) in the Netherlands, by analyzing observations and simulations with the atmospheric chemistry-transport model EMEP/MSC-W in its EMEP4NL configuration, after eliminating the effects of meteorological conditions during the lockdown. Based on statistical analyses with a Random Forest method, we estimate that the lockdown reduced observed NO2 concentrations by 30% (95% confidence interval 25–35%), 26% (21–32%), and 18% (10–25%) for traffic, urban, and rural background locations, respectively. Slightly smaller reductions of 8–28% are found with the EMEP4NL simulations for urban and regional background locations based on estimates in reductions in economic activity and emissions of traffic and industry in the Netherlands and other European countries. Reductions in observed PM2.5 concentrations of about 20% (10–25%) are found for all locations, which is somewhat larger than the estimates of 5–16% based on the model simulations. A comparison of the calculated NO2 traffic contributions with observations shows a substantial drop of about 35% in traffic contributions during the lockdown period, which is similar to the estimated reductions in mobility data as reported by Apple and Google. Since the largest health effects related to air pollution in the Netherlands are associated with exposure to PM10 and PM2.5, the lockdown measures in spring of 2020 have temporarily improved the air quality in the Netherlands. The concentrations of the most health relevant compounds have only been reduced by about 10–25%