Uncertainty analysis: waste

The text on this page is taken from an equivalent page of the IEHIAS-project.

As part of the EU-funded INTARESE project, which contributed to the development of this Toolbox, a case study was undertaken to assess the health impacts associated with waste collection ,transport and treatment, under different management strategies. Below is an extract from the assessment report, summarising the resullts of the uncertainty analysis.

We have listed the sources of uncertainties for each step of our evaluation. Significant sources of uncertainty were assessed according to the IPCC (2005) classification. The level of confidence was systematically recorded for each step in the assessment indicating correctness of each model, analysis or statement using a score out of 10 where: 9 is very high confidence; 8 is high confidence; 5 is moderate confidence; 2 is low confidence; and <2 very low confidence.

Scenarios

The reduction of waste and the improvements in recycling and composting across Lazio, detailed in the two scenarios, will lead, in the long term, to environmental, social and economic benefits. However, a potential negative impact with both of the scenarios relates to the increase in road transport of waste as different services are introduced to collect more recyclables. The increase in road transport could have negative implications for local air pollution levels although vehicle emissions abatement technology should minimize this potential risk. Therefore, the main limitation of our scenarios was the uncertainty about the impact of the recycling industry. Overall, we think we have characterised the scenarios with a moderate level of confidence.

Waste generation and management

As expected, there were inadequacies in data availability and reliability on municipal solid waste (MSW) indicators. However, a crosscheck has been done between various sources and we have high confidence in the summary statistics reported and in the waste flows described.

Population characteristics and exposure to air pollutants

We had relatively high quality geo-referenced data for incinerators, landfills and mechanical and biological treatment plants (MBTs). Small problems, however, were faced in estimating the exposed population because the size of some landfills is not known, and the unit of the available population data (census block) did not fit our needs. Fortunately population data by age and sex were available at the local level even though they were based on the last census. Overall, we have very high confidence on the population data close to the plants.

The results of the air dispersion models depend on the quality of the input data. We had operational data or authorized values during recent years. However, some plant characteristics were missing and had to be estimated. On the other hand, we could rely on high quality meteorological data for most of the plants and topography was also considered. Overall, we have a high confidence in the estimated air pollution concentrations close to management plants and along roads.

Excess-risk and exposure-response functions

The application of excess-risk estimates based on distance from the plants has been problematic because of several difficulties in interpreting of epidemiological studies. We have tried to address the issue in a transparent way by conducting a systematic evaluation. However, as underlined on several occasions, we have moderate confidence in the excess risks used for the impact assessment of cancer cases and adverse reproductive outcomes. The effect estimates for respiratory symptoms and odour annoyance are also based on a limited number of studies and our confidence on them is moderate. On the other hand, we have high confidence in the coefficients for long-term effects of PM₁₀ and NO₂ on mortality.

Quantification of the health impact

The quantification has been straightforward in terms of calculating excess cases as there are no difficulties in finding the appropriate health statistics and taking into account the particular population characteristics near the facilities. However, the most difficult part is translating the effect studied from old plants using old technologies to new facilities. We have clearly stated our assumptions and also have tried to evaluate the consequence of changing some of the parameters. Overall, we have moderate confidence in our method to estimate excess cancer cases and reproductive outcomes. On the other hand, the life table approach is rather robust although it is difficult to verify some of the assumptions (time of the effect, stability of the population, constant mortality). Finally, because a variety of illegal disposal practices exists and because it is difficult to estimate the amount of waste that is disposed of illegally, to determine emissions, exposure levels and health effects is difficult. For all of these reasons, our quantification of the health impacts has a moderate level of confidence