The increasingly urgent need for action under the 2020 Agenda has shown weaknesses in traditional environmental planning methods that view Sustainable Development Goals (SDGs) as independent and linearly achievable targets. In this paper, we establish a model that uses mathematics to reconfigure environmental planning into a nonlinear process, driven by interactions and bound by ecological principles. Considering biosphere-centered SDGs, the research formulates sustainability as a human-environment system where the dimensions of goals are shaped by inherent dynamics, intergoal linkages, and optimal policies. The suggested model framework employs a network of interactions to model the contextual dependency among the SDGs, state dynamics characterized by non-linearities to account for threshold and feedback effects, and planetary boundary restrictions for ecological plausibility. The environmental decision-making process is designed as a dynamic optimization model under uncertainty, where the total accomplishment of the SDGs is traded off against costs and the ecological bounds imposed by the planetary boundaries. To make use of the model, a database structure based on multiple sources of information, including earth observation systems, development indicators, and SDG databases, is created. The example of the Amazon basin application shows the importance of the framework both analytically and practically. The comparison between the Business-as-Usual scenarios and the mathematically optimal interventions shows that traditional methods result in fragmented progress and growing pressure on ecosystems, while the use of optimization improves system integration and leads to better results. The sensitivity analysis performed via Monte Carlo methods proves that this effect remains even under conditions of high uncertainty and worsened climatic conditions. The results will help advance the field of sustainability science because they will provide a replicable and policy-relevant structure to study the interaction between the SDGs. The research concludes that meeting the objectives of the SDGs would require an approach that moves away from optimizing individual sectors and goals independently towards using more holistic and dynamic approaches to planning that incorporate interactions between goals and constraints imposed by natural boundaries.
Jitin Yadav (Fri,) studied this question.