Usefulness of an opportunistic data analysis approach to evaluate if environmental regulations aim at relevant applications

Environmental regulations aim to protect the environment from anthropogenic detrimental effects. To ensure their effectivity and to avoid unexpected results and budget losses, environmental regulations need careful designs grounded in observational data. Comprehensive monitoring campaigns are not always achievable in developing economies, since environmental monitoring is not always prioritized due to resource constraints. We propose to tackle the problem using an opportunistic data analysis approach as supplementary information for environmental monitoring. We applied this approach to evaluate the application of Chilean phosphorus (P) fertilization subsidy. A risk assessment for P surplus was performed using three datasets: (1) secondary data acquired from thousands of unclassified laboratory records from the private sector (n = 7957); (2) a dataset of soil available P from a budged-restricted monitoring campaign, and; (3) a conjoint dataset that comprises 1 and 2. Results indicate that while laboratory records represented the general characteristics of the study area, field monitoring data evidenced a surplus of soil P. Using the laboratory records to enrich the data acquired by field monitoring modified the reality reflected by the monitoring data alone. The use of the conjoint dataset leads to the conclusion that soils in the study area had enough available P for optimum production, and that farmers were already using external sources of P fertilizers within the current market structure. Our study constitutes an example of the use of private data to contribute to public soil monitoring programs and environmental regulation designs. The case study serves as a successful example of opportunistic data usage in environmental monitoring, as a low-cost alternative to complement field observations.