Environmental assessment of global site-specific industrial air pollution

This thesis aims at providing an in-depth analysis of global industrial air emissions and resulting human health impacts from nearly all global fossil power plants, steel mills, oil refineries and cement plants individually. Thus, detailed inventories are developed that link the specific technologies in use at more than 125 000 industrial sites, information about their operational practices, and measured emissions. This inventory covers a majority of anthropogenic stationary carbon dioxide (CO2) emissions. Further air pollutants covered by this thesis include methane (CH4), fine particulate matter (PM2.5), sulphur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3) and mercury (Hg), which represent main drivers of human health impacts from pollution.

For power plants, air emissions have been modeled comprehensively including electricity and heat outputs, efficiencies depending on the thermodynamic cycles at each site, and the specific emission abatement technologies in use. Global coal supply chains including mining, preparation and transport are added as these contribute to human health impacts both directly with their emissions and through the properties of the supplied coal at each coal power plant. For steel mills, refineries and cement plants, the emission models focus on all main on-site air emission sources such as coke ovens, sinter plants, fluid catalytic crackers, sulphur recovery units, flares, furnaces, boilers, or kilns, and also take into account the site-specific flue gas treatment technologies as identified from satellite imagery. Modeled emissions for all sites are merged with emission measurements from a large number of databases to benefit from the level of detail of the emission models as well as the accuracy of emission measurements at the same time.

Life cycle assessment (LCA) is then applied to quantify current human health impacts. Thus, the global air emission inventory is coupled with current life cycle impact assessment (LCIA) methods, while the technological information for each site is then used to identify realistic improvement potentials. A new, more detailed atmospheric fate, exposure and health effect model is developed on a regionalized level for primary and secondary PM2.5 since the current LCIA methodologies are found to have key weaknesses. Thus, the emission heights, a consistent coverage of different precursor substances, non-linear atmospheric chemistry, temporal and spatial weather patterns throughout the year, the effects of background pollution concentrations, and the quantification of non-linear human health responses to exposure changes can be covered. This model is then used to generate LCIA characterization factors (CFs) that can be flexibly adjusted to regionalized and temporalized LCA studies.

The direct coupling of the health impact model with the detailed inventory for industrial sites, however, allows to avoid several of the simplifications of conventional LCA studies, as these multiply emissions with pre-calculated site-generic or site-dependent CFs based on simplified emission models or estimates from unrepresentative sets of data points. The overall model displays unprecedented detail and global coverage along the whole cause-effect chain of human health impacts caused by industrial emission sources. It improves the assessments of human health impacts per emission source by reducing spatiotemporal uncertainties by several orders of magnitude and enables new comparisons of health impacts based on key characteristics such as location and time of emission at such a high resolution.

The results demonstrate the central role that the continuing deployment of post-combustion flue gas treatment has for the mitigation of human health impacts, for example in Northern and North-Eastern India, where a low sulfur content in coal still leads to major health impacts from SO2 due to missing flue gas treatment, high population densities and low wind speeds. Health impacts are also observed to be high in other parts of the world (for example in Eastern China, the US and Europe) with high variability between the mainly contributing pollutants, but many opportunities for emission reductions from post-combustion flue gas treatment - at least related to particulate matter from industrial emission sources - have already been exploited in these regions. In such cases, the present thesis can highlight remaining reduction potentials, and also help to prioritize facilities in case of larger systemic changes in the local economies. Key industrial drivers for human health impacts from greenhouse gas emissions, for example, are identified all over the world with the largest shares of emissions originating from China, the US, Europe, India and Japan. Thus, the present thesis allows for the ranking of measures in the context of the Paris Agreement.

Local political frameworks are found to regulate air pollutants ineffectively, as several key gaps such as missing emission limits for individual substances or particularly lenient regulation for inefficient units are identified. Thus, a range of cases are observed where a change in regulation leads to the phase-out of the least harmful and most efficient facilities, while regulatory exemptions favor the operation of outdated equipment with high human health burdens.

Future work should prioritize the collection of emission data in least developed and developing countries, and broaden the coverage in terms of air pollutants and their speciation. Additionally, research towards quantifying health impact differences between PM compositions (based on elemental and organic carbon, sulfates, nitrates, etc.) is needed to improve PM emission CFs, as these are identified as key gaps for the present thesis.

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Life Cycle Sustainability Assessment

Author Christopher Oberschelp
Institution ETH Zurich
Advisor Prof. Stefanie Hellweg
Degree Doctoral
Expected graduation 2021