Arja Asikainen

Challenges in estimating health effects of indoor exposures to outdoor particles: Considerations for regional differences

Ambient air pollution is a leading environmental risk factor causing substantial losses of life and significant morbidity. Concentration-response (CR) functions used globally to estimate such effects are largely based on ambient epidemiology, using centrally monitored outdoor air quality as an exposure indicator and various indices of population health as an outcome. Similar common understanding is mostly missing regarding indoor exposures. Less studied are health impact modifying factors such as particle size, infiltration, time-activity and population differences. In this discussion paper we aim at looking at one of these, infiltration. The sensitivity of overall personal exposure to indoor exposures was quantified by a simple probabilistic time-activity model to calculate fractional exposures for indoor, outdoor and in traffic time-activity. To demonstrate the potential regional differences in epidemiological C-R relationships we re-analysed the ESCAPE results for natural-cause mortality, focusing on geographical grouping of the cohorts: pooled estimates were calculated for the Nordic, Central European and Southern European cohorts. When comparing the relative differences in the regional hazard ratio increments, the Central European value (7%) is 1.75 times higher than the Nordic one, and Southern European value (12%) 3 times higher, respectively. While towards the expected direction when aiming to explain these differences at least partly with differences in PM2.5 infiltration, the differences are not statistically significant and only the Central European and the all cohorts combined estimates reach borderline statistical significance. As the analysis of PM2.5 infiltration factors by similar regions yielded only 10-15% differences, it seems possible that that the available data could also accommodate other regional factors, such as those originating from regional differences in population and contribution of indoor sources of PM, time-activity, behaviour, or compositional differences in the particulate matter.

City scale climate change policies: Do they matter for wellbeing?

Climate change mitigation policies aim to reduce climate change through reducing greenhouse gas (GHG) emissions whereas adaption policies seek to enable humans to live in a world with increasingly variable and more extreme climatic conditions. It is increasingly realised that enacting such policies will have unintended implications for public health, but there has been less focus on their implications for wellbeing. Wellbeing can be defined as a positive mental state which is influenced by living conditions. As part of URGENCHE, an EU funded project to identify health and wellbeing outcomes of city greenhouse gas emission reduction policies, a survey designed to measure these living conditions and levels of wellbeing in Kuopio, Finland was collected in December 2013. Kuopio was the northmost among seven cities in Europe and China studied. Generalised estimating equation modelling was used to determine which living conditions were associated with subjective wellbeing (measured through the WHO-5 Scale). Local greenspace and spending time in nature were associated with higher levels of wellbeing whereas cold housing and poor quality indoor air were associated with lower levels of wellbeing. Thus adaption policies to increase greenspace might, in addition to reducing heat island effects, have the co-benefit of increasing wellbeing and improving housing insulation.

Health Impacts of Ambient Air Pollution in Finland

Air pollution has been estimated to be one of the leading environmental health risks in Finland. National health impact estimates existing to date have focused on particles (PM) and ozone (O3). In this work, we quantify the impacts of particles, ozone, and nitrogen dioxide (NO2) in 2015, and analyze the related uncertainties. The exposures were estimated with a high spatial resolution chemical transport model, and adjusted to observed concentrations. We calculated the health impacts according to Word Health Organization (WHO) working group recommendations. According to our results, ambient air pollution caused a burden of 34,800 disability-adjusted life years (DALY). Fine particles were the main contributor (74%) to the disease burden, which is in line with the earlier studies. The attributable burden was dominated by mortality (32,900 years of life lost (YLL); 95%). Impacts differed between population age groups. The burden was clearly higher in the adult population over 30 years (98%), due to the dominant role of mortality impacts. Uncertainties due to the concentration–response functions were larger than those related to exposures.

Building-related health impacts in European and Chinese cities: a scalable assessment method

BackgroundPublic health is often affected by societal decisions that are not primarily about health. Climate change mitigation requires intensive actions to minimise greenhouse gas emissions in the future. Many of these actions take place in cities due to their traffic, buildings, and energy consumption. Active climate mitigation policies will also, aside of their long term global impacts, have short term local impacts, both positive and negative, on public health.Our main objective was to develop a generic open impact model to estimate health impacts of emissions due to heat and power consumption of buildings. In addition, the model should be usable for policy comparisons by non-health experts on city level with city-specific data, it should give guidance on the particular climate mitigation questions but at the same time increase understanding on the related health impacts and the model should follow the building stock in time, make comparisons between scenarios, propagate uncertainties, and scale to different levels of detail.We tested The functionalities of the model in two case cities, namely Kuopio and Basel. We estimated the health and climate impacts of two actual policies planned or implemented in the cities. The assessed policies were replacement of peat with wood chips in co-generation of district heat and power, and improved energy efficiency of buildings achieved by renovations.ResultsHealth impacts were not large in the two cities, but also clear differences in implementation and predictability between the two tested policies were seen. Renovation policies can improve the energy efficiency of buildings and reduce greenhouse gas emissions significantly, but this requires systematic policy sustained for decades. In contrast, fuel changes in large district heating facilities may have rapid and large impacts on emissions. However, the life cycle impacts of different fuels is somewhat an open question.ConclusionsIn conclusion, we were able to develop a practical model for city-level assessments promoting evidence-based policy in general and health aspects in particular. Although all data and code is freely available, implementation of the current model version in a new city requires some modelling skills.

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

BackgroundClimate 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.MethodsFive 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.ResultsThere 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.ConclusionsThe 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.

Public health impacts of city policies to reduce climate change

BackgroundClimate 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.MethodsFive 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.ResultsThere 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.ConclusionsThe 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.

Building-related health impacts in European and Chinese cities

BackgroundPublic health is often affected by societal decisions that are not primarily about health. Climate change mitigation requires intensive actions to minimise greenhouse gas emissions in the future. Many of these actions take place in cities due to their traffic, buildings, and energy consumption. Active climate mitigation policies will also, aside of their long term global impacts, have short term local impacts, both positive and negative, on public health.Our main objective was to develop a generic open impact model to estimate health impacts of emissions due to heat and power consumption of buildings. In addition, the model should be usable for policy comparisons by non-health experts on city level with city-specific data, it should give guidance on the particular climate mitigation questions but at the same time increase understanding on the related health impacts and the model should follow the building stock in time, make comparisons between scenarios, propagate uncertainties, and scale to different levels of detail.We tested The functionalities of the model in two case cities, namely Kuopio and Basel. We estimated the health and climate impacts of two actual policies planned or implemented in the cities. The assessed policies were replacement of peat with wood chips in co-generation of district heat and power, and improved energy efficiency of buildings achieved by renovations.ResultsHealth impacts were not large in the two cities, but also clear differences in implementation and predictability between the two tested policies were seen. Renovation policies can improve the energy efficiency of buildings and reduce greenhouse gas emissions significantly, but this requires systematic policy sustained for decades. In contrast, fuel changes in large district heating facilities may have rapid and large impacts on emissions. However, the life cycle impacts of different fuels is somewhat an open question.ConclusionsIn conclusion, we were able to develop a practical model for city-level assessments promoting evidence-based policy in general and health aspects in particular. Although all data and code is freely available, implementation of the current model version in a new city requires some modelling skills.