Building and characterizing regional and global emission inventories of toxic pollutants.
To define consistent strategies for managing the environmental sustainability of chemicals, it is important to quantify the magnitude of their emissions and their associated impacts. Not all countries monitor and report emissions related to their activities. This is particularly the case for chemical emissions, whose toxic impacts on human health and ecosystems cannot be readily determined because of gaps in the available data. Emission data that can be retrieved from publicly available databases are typically restricted to a limited number of toxic substances, for a few countries, or for aggregated regions. Extrapolation strategies are thus needed to fill in those data gaps and to move from the consideration of single countries or regions to the world scale. Little is known about how effective these strategies are in extrapolating emissions. With the use of emission data available in public databases in the world, the current work explores different opportunities to compile representative inventories of toxic emissions. In this study, we build global and European emission inventories using three extrapolation proxies, namely the gross domestic product, the emissions of carbon dioxide, and the emissions of mercury. The three proxies are compared and their efficacies are tested statistically to identify the best performer for specific classes of substances. The potential impacts associated with the emissions in the European and global inventory are further tested by using an impact system adopted for the comparative assessment of chemicals in the field of life cycle assessment.
Institute of Environmental Sciences (CML), Leiden University , P.O. Box 9518, 2300 RA Leiden, The Netherlands.
Stefano
S
Cucurachi
Serenella
S
Sala
Alexis
A
Laurent
Reinout
R
Heijungs
D000393:Air Pollutants / Q000032:analysis; D004785:Environmental Pollutants / Q000032:analysis* / Q000633:toxicity*; D004787:Environmental Pollution / Q000032:analysis*; D005843:Geography; D006801:Humans; D038622:Internationality; D016014:Linear Models; D012989:Soil Pollutants / Q000032:analysis; D035501:Uncertainty; D014873:Water Pollutants / Q000032:analysis
D000393:Air Pollutants; D004785:Environmental Pollutants; D012989:Soil Pollutants; D014873:Water Pollutants