This post is to announce an recent paper we got published:
Blending multiple nitrogen dioxide data sources for neighborhood estimates of long-term exposure for health research. Ivan Charles Hanigan, Grant J Williamson, Luke David Knibbs, Joshua Horsley, Margaret Rolfe, Martin Cope, Adrian Barnett, Christine Cowie, Jane S Heyworth, Marc L Serre, Bin Jalaludin, Geoffrey G Morgan. 2017, Environmental Science & Technology, http://dx.doi.org/10.1021/acs.est.7b03035
Exposure to nitrogen dioxide (NO2) pollution has been associated with a range of adverse health outcomes for both the respiratory and cardiovascular systems. This pollutant is primarily emitted by traffic and can reach very high levels next to roads, and diminish quickly away from the source. Spatial models of pollution concentrations are often used to estimate exposure levels that are then fed into models that estimate health impacts. However, these estimates can be imprecise due to difficulty modelling spatial patterns at the resolution of neighbourhoods (e.g. a scale of tens of metres) rather than at a coarse scale (around several kilometres). This is especially challenging at low concentrations, such as the level found in Sydney Australia. The Sydney region has globally low levels of air pollution compared with similar economically developed cities. Rome for example is a similar size yet mean NO2 was three times higher than the average in Sydney.
The objective of our research was to derive improved estimates of neighbourhood level pollutant concentrations for health studies by blending air pollutant measurements with modelled predictions using the Bayesian statistical philosophy. The improved estimates of exposure will theoretically reduce bias when used in second stage analyses of the impacts on health. This improved evidence will guide decision makers in the delicate balance between the costs of reducing air pollution emissions, while minimising health impacts.
In our paper that has just been accepted for publication in the journal Environmental Science & Technology we implemented a high-tech method called the Bayesian Maximum Entropy (BME) model to blend data based on our prior knowledge of the probabilities and uncertainty surrounding the information sources. We brought together all the different NO2 data from measuring stations (monitors), chemical transport models (physical models that mimic the dispersion of emissions and weather patterns), and statistical ‘land use regression’ models (which incorporated satellite-based data) to estimate neighbourhood level annual average NO2 concentrations in Sydney. Our validation assessment using independent data from a separate set of samples showed an improvement compared to either the land use regression and chemical transport model used alone.
How low should we go? Is there a ‘safe’ low threshold of air pollution for Australians?
Future outputs of our work will seek to enable the policy and management communities to develop further improvements to air pollution maps and to explore health cost-benefit estimates under various emission reduction scenarios. For example, the Australian National Environment Protection Council decides on the National Environment Protection Measures (NEPMs) which have the goal of achieving a safe threshold of exposure in our cities. The results of our research will inform these stakeholders as they revise the regulations, and try to achieve the National Clean Air Agreement (made between the Commonwealth and each state and territory jurisdictions) which aims to implement strengthened laws that move to even tighter standards on air pollution emissions by 2025.
Key talking points:
- Air pollution health impacts are well known from studies in high concentration cities (e.g. Rome) but there is a lack of knowledge about how low we need to go to minimise health impacts.
- Sydney has globally low levels of NO2 (a traffic related air pollutant) and this makes Australia one of the best places in the world to study this low end of the exposure spectrum.
- Our study produced an air pollution map with the best validation statistics for NO2 made so far for Sydney, at a scale of hundreds of metres.
- These more precise exposure estimates will produce better knowledge about the health impacts.
- With this evidence we can make better choices on regulatory interventions that seek to maximise the health benefits of reducing air pollution emissions while also delivering the lifestyle and economic prosperity afforded by burning fossil fuel for energy.
A breath of fresh air – new pollution research from Australia
Calculating whether traffic-related air pollution exposure can make us sick even at low levels has stumped experts around the world, but new research from a collaboration among eight universities and the CSIRO is now filling in the blanks. Nitrogen dioxide (NO2) is a pollutant mostly emitted by traffic and has been associated with respiratory and cardiovascular health problems.
The research, Blending Multiple Nitrogen Dioxide Data Sources for Neighborhood Estimates of Long-Term Exposure for Health Research has been published in the journal Environmental Science and Technology.
Lead author Dr Ivan Hanigan from the University of Canberra’s Health Research Institute and the Centre for air quality and health Research and evaluation (CAR) based at University of Sydney says past studies of NO2 pollution have focused on major cities around the world, mostly with severe problems.
“We know about the health impacts because of research which examined cities like Rome, which have very high concentrations of pollution,” Dr Hanigan said. “While, Sydney is about the same size as Rome; the Italian capital has three times higher levels of NO2 pollution. It is still a big unknown if there might be a safe lower threshold where health impacts are minimal. If there is, then emission reduction policies can use this as a target, but if not then continual pollution reduction measures may be justified. Sydney is therefore one of the best places in the world to study this, and we can help answer this globally significant question.”
“Using the very precise air quality monitors installed around Sydney, along with sophisticated modelling by my collaborators, we are gaining insights that other studies have missed about the lower levels of NO2 exposure. We’ve been able to produce the best maps so far of air pollution for Sydney, and the scale is down to a hundred metres or so.”
Previous analysis used scales of several kilometres, Dr Hanigan says his new maps are much closer to the level of detail needed to accurately determine health impacts and plan for the future. “I expect health policy experts, infrastructure planners and even environmental managers will be keenly interested in this analysis,” he said. “This work can help to develop improvements to Australia’s air pollution regulations and lead to better health cost-benefit estimates for emission reduction scenarios.” “With this evidence we can make better choices on interventions to maximise the health benefits of reducing air pollution emissions while also delivering the lifestyle and economic prosperity afforded by burning fossil fuels for energy.”
The work is a collaboration between Dr Hanigan and colleagues from around Australia and the United States, including from University of Tasmania, University of Queensland, University of Sydney, CSIRO, Queensland University of Technology, University of New South Wales, University of Western Australia and the University of North Carolina.