TY - JOUR A1 - Saravia, Christian A1 - Trachte, Katja T1 - Spatiotemporal analysis of NH³ emission sources and their relation to land use types in the eastern German lowlands JF - Atmosphere N2 - Ammonia (NH³) emissions, which are key precursors of fine particulate matter, pose significant environmental challenges. This study investigated the spatiotemporal variations in NH³ emissions across the eastern German lowlands from 2013 to 2022 using IASI-B satellite data. Five major Land Cover Classes (LCC) –tree, grassland, cropland, built-up areas, and water bodies– were analyzed. The results showed distinct diurnal variations, with nighttime NH³ concentrations exceeding 2.0 × 10¹⁶ molecules cm⁻² in the peak months. Seasonal patterns indicated significant emissions in March (1.2 × 10¹⁶ molecules cm⁻²), April (1.1 × 10¹⁶ molecules cm⁻²), and August (9.6 × 10¹⁵ molecules cm⁻²), while the lowest concentrations occurred in September (0.6 × 10¹⁵ molecules cm⁻²). Persistent hotspots were identified in the northwestern region, where emissions peaked in spring (1.8 × 10¹⁶ molecules cm⁻²) and summer (1.3 × 10¹⁶ molecules cm⁻²), primarily due to agricultural activities. Over the study period, the annual NH³ concentration peaked in 2015, 2018, and 2022. Using k-means clustering, three distinct emission zones were identified, with Cluster 3 showing the highest NH³ emission values, particularly in urban centers, and agricultural zones were identified, covering less than 20% of the study area, where cropland predominates (8%). Meteorological factors significantly influenced NH³ levels, with negative correlations obtained for precipitation, wind speed, and evaporation, while solar radiation, boundary layer height, and instantaneous moisture fluxes showed positive correlations. A case study from March 2022, employing the HYSPLIT trajectory model, confirmed that agricultural practices are the dominant NH³ source, with emissions reaching 3.2 × 10¹⁶ molecules cm⁻² in hotspot regions. KW - Ammonia KW - Remote sensing KW - Land cover type KW - Spatiotemporal variability KW - Cluster k-means Y1 - 2025 U6 - https://doi.org/10.3390/atmos16030346 SN - 2073-4433 VL - 16 IS - 3 PB - MDPI CY - Basel ER -