How data collection may affect the carbon footprint – The case of carbon foodprint accounting for cities

Abstract

Evidence-based policymaking can foster climate justice in the light of climate change risks. For this reason, adopting environmental metrics such as Ecological Footprint or carbon footprint becomes imperative.

As carbon footprint assessments evolve, there remains a critical challenge in the availability of data representing lifestyles of inhabitants. Therefore, this research refers to the question What is the effect of utilizing currently available data to describe the current impact of cities and their inhabitants on the environment? The research focuses on foodprint assessment across multiple resource scales: national, city-wide, regional, urban-size (more local-level structural data), and urban-regional. Therefore, five individual CF results for each of the 18 Polish cities were obtained, followed by a one-to-one comparison, offering ten comparisons of results, that is, each with each.

On average, the differences in total CF results for different levels of data detail are at most ±3.5 %. Of interest seems to be the impact of regional conditions on the values of the footprint, especially the quantified urban-regional results. Differences in this scale of data, relative to other results, are associated with an increase in the foodprint from 0.001 to 0.003 global hectares per capita. It could be especially important for cities having the largest population. Even though on average for 200–499 K urban-size cities the results were the highest compared to the national ones (higher by 0.004 global hectares), it was for cities with over 500 000 inhabitants that the largest differences were observed at the level of individual products. In general, variations of ±20 % in results were registered for products such as poultry, cheese, vegetable fats, sugar, and potatoes.

The findings reveal that for cities with populations under 200,000, the reliance on high-resolution local data provides limited additional accuracy, suggesting that national or regional datasets are often sufficient. This insight can optimize resource allocation for evidence-based policymaking, particularly in the context of urban adaptation plans and climate action strategies.