Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1016/j.scitotenv.2024.174262
Document author version
Title (Primary) Improving rapeseed carbon footprint evaluation via the integration of remote sensing technology into an LCA approach
Author Yang, X.; Dong, X.; Bezama, A.; Liu, Y.
Source Titel Science of the Total Environment
Year 2024
Department BIOENERGIE
Volume 946
Page From art. 174262
Language englisch
Topic T5 Future Landscapes
Supplements https://ars.els-cdn.com/content/image/1-s2.0-S0048969724044103-mmc1.docx
Keywords Climate change; Spatial-temporal heterogeneity; Life cycle assessment; Environmental effects; Soil organic carbon; Greenhouse gas emissions
Abstract Agricultural carbon footprint (CF) evaluation plays an important role in climate change mitigation and national food security. Many studies have been conducted worldwide to evaluate the CF of rapeseed and its byproducts; however, only a few of these studies have considered finer-scale spatial-temporal heterogeneity. Considering the advantages of using detailed crop information extracted by remote sensing (RS) techniques, we attempted to integrate RS into life cycle assessments to improve rapeseed CF evaluation. A case study was conducted from 2021 to 2023 in one of the most important grain- and rapeseed-producing areas in Southwest China, namely, the Chengdu Plain, covering an area of 18,810.00 km2. The results of our study suggest that: (1) the proposed approach is applicable for high-resolution (10 m ∗ 10 m) rapeseed distribution mapping; (2) the farm-based CFs of rapeseed in the studied region range from 3333.08 to 4572.82 kgCO2-eq ha−1, while the product-based CFs (PCFs) vary from 1316.23 to 2443.95 kgCO2-eq t−1. Nitrogen fertilizer processing and its application are identified as the dominant contributors to upstream and downstream greenhouse emissions (GHGs), respectively; (3) the significant role of soil properties and soil organic carbon in influencing crop PCFs indicates good GHG offsets. The method used in the current study has strong adaptability and universality in different areas with various climatic conditions and can provide a solid basis for policymakers to formulate differentiated agricultural carbon reduction policies.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=29334
Yang, X., Dong, X., Bezama, A., Liu, Y. (2024):
Improving rapeseed carbon footprint evaluation via the integration of remote sensing technology into an LCA approach
Sci. Total Environ. 946 , art. 174262 10.1016/j.scitotenv.2024.174262