Purpose
The water footprint (WF) method is widely applied to quantify water use along the life cycle of products and organizations and to evaluate the resulting impacts on human health. This study analyzes the cause-effect chains for the human health damage related to the water use on a local scale in the Province Punjab of Pakistan, evaluates their consistency with existing WF models, and provides recommendations for future model development.
Method
Locally occurring cause-effect chains are analyzed based on site observations in Punjab and a literature review. Then, existing WF models are compared to the findings in the study area including their comprehensiveness (covered cause-effect chains), relevance (contribution of the modeled cause-effect chain to the total health damage), and representativeness (correspondence with the local cause-effect chain). Finally, recommendations for the development of new characterization models describing the local cause-effect chains are provided.
Results and discussion
The cause-effect chains for the agricultural water deprivation include malnutrition due to reduced food availability and income loss as well as diseases resulting from the use of wastewater for irrigation, out of which only the first one is addressed by existing WF models. The cause-effect chain for the infectious diseases due to domestic water deprivation is associated primarily with the absence of water supply systems, while the linkage to the water consumption of a product system was not identified. The cause-effect chains related to the water pollution include the exposure via agricultural products, fish, and drinking water, all of which are reflected in existing impact assessment models. Including the groundwater compartment may increase the relevance of the model for the study area.
Conclusions
Most cause-effect chains identified on the local scale are consistent with existing WF models. Modeling currently missing cause-effect chains for the impacts related to the income loss and wastewater usage for irrigation can enhance the assessment of the human health damage in water footprinting.TU Berlin, Open-Access-Mittel – 2021BMBF, 02WGR1422B, GROW - Verbundprojekt InoCottonGROW: Innovative Impulse zur Verringerung des Wasser-Fußabdrucks der globalen Baumwoll-Textilindustrie in Richtung UN-Nachhaltigkeitsziele, Teilprojekt