SignificanceNationally recommended diets are a prominent method for informing the public on dietary choices. Although dietary choices drive both health and environmental outcomes, these diets make almost no reference to environmental impacts. Our study provides a comparison between the environmental impacts of average dietary intakes and a nation-specific recommended diet across 37 middle- and high-income nations. We find that following a nationally recommended diet in high-income nations results in a reduction in greenhouse gases, eutrophication, and land use. In upper-middle–income nations, we find a smaller reduction in impacts, and in lower-middle–income nations we find a substantial increase. The net result from large-scale adoption of nationally recommended diets for countries studied here results in a reduction in environmental impacts.
Consumption-based
carbon accounts (CBCAs) track how final demand
in a region causes carbon emissions elsewhere due to supply chains
in the global economic network, taking into account international
trade. Despite the importance of CBCAs as an approach for understanding
and quantifying responsibilities in climate mitigation efforts, very
little is known of their uncertainties. Here we use five global multiregional
input-output (MRIO) databases to empirically calibrate a stochastic
multivariate model of the global economy and its GHG emissions in
order to identify the main drivers of uncertainty in global CBCAs.
We find that the uncertainty of country CBCAs varies between 2 and
16% and that the uncertainty of emissions does not decrease significantly
with their size. We find that the bias of ignoring correlations in
the data (that is, independent sampling) is significant, with uncertainties
being systematically underestimated. We find that both CBCAs and source
MRIO tables exhibit strong correlations between the sector-level data
of different countries. Finally, we find that the largest contributors
to global CBCA uncertainty are the electricity sector data globally
and Chinese national data in particular. We anticipate that this work
will provide practitioners an approach to understand CBCA uncertainties
and researchers compiling MRIOs a guide to prioritize uncertainty
reduction efforts.
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