Assessing the empirical relationship between agriculture, manure and ammonia in the Po Valley, Italy

Paolo Maranzano (University of Milano Bicocca)

Friday 5th May, 2023 15:00-16:00 Maths 311B

Abstract

Ammonia () is a crucial contributor to air pollution levels, as it can become particulate matter after combining with other pollutant materials from various sources. Around 75% of European ammonia emissions come from livestock production. Emissions occur at all stages of manure management: during manure storage; when spreading to the land; and from urine deposited by livestock on pastures during grazing. This article investigates the relationship between ammonia emissions and manure processed in the Lombardy region, Italy, at the sub-regional level (i.e., the agrarian subregions). The research is part of the Agrimonia project (https://agrimonia.net/), an international research group that aims to quantify agriculture's influence on local air quality for the Lombardy region using statistical learning and data science methodologies. We propose a two-step spatio-temporal statistical analysis. In the first step, the goal is to obtain credible estimates of the quantity of animal manure produced and processed for each agrarian subregion from 2016 to 2020. To do so, we considered several spatiotemporal specifications of area-level Small Area Models. The second step consists of a spatiotemporal analysis of the empirical relationship between  emissions and manure employing several spatiotemporal linear models: Linear, Linear Mixed, and Generalized Additive Mixed Models. In particular, LMMs and GAMMs are implemented to accommodate non-linear relationships and exploit the observations' spatiotemporal dynamics.

Email wei.zhang.2@glasgow.ac.uk for Zoom link.

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