Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Faculty of Medicine, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, UK.
J Environ Public Health. 2013;2013:560342. doi: 10.1155/2013/560342. Epub 2013 Jul 14.
Research to date on health effects associated with incineration has found limited evidence of health risks, but many previous studies have been constrained by poor exposure assessment. This paper provides a comparative assessment of atmospheric dispersion modelling and distance from source (a commonly used proxy for exposure) as exposure assessment methods for pollutants released from incinerators.
Distance from source and the atmospheric dispersion model ADMS-Urban were used to characterise ambient exposures to particulates from two municipal solid waste incinerators (MSWIs) in the UK. Additionally an exploration of the sensitivity of the dispersion model simulations to input parameters was performed.
The model output indicated extremely low ground level concentrations of PM10, with maximum concentrations of <0.01 μ g/m(3). Proximity and modelled PM10 concentrations for both MSWIs at postcode level were highly correlated when using continuous measures (Spearman correlation coefficients ~ 0.7) but showed poor agreement for categorical measures (deciles or quintiles, Cohen's kappa coefficients ≤ 0.5).
To provide the most appropriate estimate of ambient exposure from MSWIs, it is essential that incinerator characteristics, magnitude of emissions, and surrounding meteorological and topographical conditions are considered. Reducing exposure misclassification is particularly important in environmental epidemiology to aid detection of low-level risks.
迄今为止，有关焚烧相关健康影响的研究发现，健康风险的证据有限，但许多先前的研究受到暴露评估不佳的限制。本文对大气扩散模型和与源的距离（通常用作暴露的替代物）作为评估焚化炉释放的污染物的暴露评估方法进行了比较评估。
使用源距离和大气扩散模型 ADMS-Urban 来描述英国两个城市固体废物焚烧厂（MSWI）产生的颗粒物的环境暴露。此外，还对扩散模型模拟对输入参数的敏感性进行了探索。
模型输出表明 PM10 的地面浓度极低，最大浓度<0.01μg/m3。当使用连续测量时，两个 MSWI 的邮政编码水平的接近程度和模型化的 PM10 浓度高度相关（Spearman 相关系数约为 0.7），但对于分类测量（十分位数或五分位数，Cohen's kappa 系数≤0.5）则一致性较差。
为了提供最适合的 MSWI 环境暴露估计，必须考虑焚化炉的特征、排放量的大小以及周围的气象和地形条件。减少暴露分类错误在环境流行病学中尤为重要，有助于检测低水平风险。
