A model-based approach for a life cycle assessment of the nitrogen emissions of tomato production in Colombia

This thesis develops methodologies for a technical sustainability assessment of agricultural systems through the integration of soil-crop modelingand standard life cycle assessment (LCA). In addition, we propose a strategy to facilitate communication of the results of the comparative LCAs to stakeholders. As case studies, the proposed methods are applied to open field and greenhouse tomato production systems in the Colombian Andes, focusing on nitrogen fertilization practices.The thesis begins with a detailed characterization of the selected tomato production systems under both open field and greenhouse conditions. This characterization was necessary since the information available for these smallholder-based cropping systems is very limited in the Colombian context. This characterization included biophysical factors related to climatic conditions and soil fertility level, and an inventory of inputs, management practices, and productivity factors. Two data collection tools, namely, surveys and a procedure based on direct observation of the production cycles referred to as detailed follow-ups or input-output accounting, were used to gather the information from two major production regions. Since local growers usually do not keep records of their activities, detailed follow-ups are recommended for obtaining reliable data under these conditions, despite their cost and time-consuming nature. Nevertheless, as a first screening of the production systems, surveys are very useful. As a result of this first phase, some features of the growers were highlighted, such as a high dose of fertilizers without a proportional increase in yield. Heterogeneity with respect to management practices and varying levels of yield gaps, especially in the open field system, were also evident.A comparative LCA between the two systems was carried out and included the infrastructure, machinery, pest management, and fertilization subsystems. In this case study, the field emissions derived from the nitrogen fertilizers were obtained through standard methods based on empirical regression meta-analysis allowing the modification of cropping parameters as a function of the production system. The outcome of the LCA was not clear enough to differentiate the environmental performance among the two production systems. For instance, the greenhouse system showed better environmental performance according to indicators such as acidification and eutrophication, while the opposite was observed with indicators such as global warming potential and human toxicity potential. In this section, the stochastic multi-attribute analysis (SMAA) was introduced as a way to build a single indicator that would objectively rank the environmental performance of the two systems. However, an important constraint not considered by the SMAA method had to be overcome first, namely, the high degree of correlation between environmental indicators. Thus, the copula method was introduced to fit the required joint-statistical distributions for all environmental indicator based on the estimated marginal distributions of the individual impact categories. The successful implementation of the SMAA method, supported by the copula method, resulted in the better overall environmental performance of the open field than the greenhouse system. In conclusion, intensification of tomato production in Colombia by shifting to protected conditions has led to a relatively high environmental impact because of inadequate and inefficient implementation of greenhouse technology. As a consequence, it is necessary that greenhouse farmers optimize resource use and greenhouse methodologies to achieve higher production and lower environmental impact.To evaluate strategies that improve the environmental performance of tomato production systems in terms of nitrogen fertilization, a tomato plant growth and development model was calibrated and validated for open field and greenhouse conditions. In the first stage, the growth and development of tomato plants under Colombian conditions was effectively simulated by the calibrated model. This plant model was adapted by incorporating modules to represent root growth and nitrogen demand to couple it to a soil model. The soil model was previously calibrated and validated under Belgian conditions and can represent water and nitrogen dynamics as well as all N and C processes. The soil-plant model was validated for Colombian conditions based on trials carried out on commercial fields. Although the validation results presented varying degrees of fit, overall, the model showed a workable level of accuracy. The resulting soil-plant model was driven by meteorological data, soil and plant properties and management practices such as nitrogen fertilization and irrigation. The model simulated, on a daily basis, crop growth and development, heat, water and nitrogen flows through the soil profile, and soil nitrogen and carbon dynamics, including emissions of environmental pollutants to the atmosphere and groundwater.Finally, the soil-plant model was used to evaluate a set of nitrogen fertilization scenarios. The scenarios included currently applied strategies by commercial growers and two alternative prospective scenarios. In the grower scenario, nitrogen fertilization was applied based on a fixed dose, while the alternative scenarios applied nitrogen as a function of plant demand over time. Each of the scenarios was evaluated over 52 weather periods, corresponding to weekly plantings over a period of one year. From each simulation, the predicted yield and the emissions of ammonia, nitrous oxide, and nitrates were extracted and used as inputs for a posterior comparative LCA. The results revealed that some scenarios showed better environmental performance for some impact categories, while others performed better in a different set of categories. Therefore, the SMAA method supplemented by the copula method was applied again to rank the environmental performance of the scenarios. The results showed that greenhouse production systems in which the fertilization strategy is based on plant demands have the best environmental performance. The method proposed in this thesis adds dynamic properties to the classic static LCA in terms of predicting nitrogen emissions through integration with soil-crop modeling. Additionally, the proposed framework incorporates an optimized single performance indicator method to enhance communication of the LCA results to stakeholders and decision-makers.

Jaar van publicatie:2019