Complexity in Environmental Chemistry: From Pollutants to Predictive Analytics (en Inglés) - Marco Minella

This textbook focuses on the management of complex problems in the field of environmental chemistry, demonstrating how chemical, physical, and biological processes interact across scales to shape environmental systems. It presents an integrated perspective that bridges conceptual foundations, analytical innovations, and real‑world applications, offering readers a coherent framework to understand and address the intricate challenges that define modern environmental research. Complexity is a central topic of the philosophy of science, the epistemology and, more generally, of the science in the twentieth century. Nowadays, the problem of addressing the questions posed by complexity science (i.e., the study of phenomena emerging from a collection of numerous interacting objects) in environmental studies can be addressed with new tools such as those developed for the management of multivariate and big (chemical) data (e.g., new chemometric tools and innovative artificial intelligence algorithms). Furthermore, a better understanding of environmental (chemo)dynamics requires an increasingly broad view of natural phenomena and of the large interaction between different environmental compartments.

In its first section, the textbook addresses the topic of complexity in the environment from a general point of view, especially in terms of the complex definition of what pollutants are and the complexity of the climate system. Furthermore, some analytical tools (e.g. innovative advanced separation techniques) capable of providing information on the complex composition of natural matter are presented, together with an in-depth description of the statistical tools to be used to address complexity in chemistry, from the basic principles of chemometrics to the application of artificial intelligence algorithms for environmental monitoring. The second section of this book showcases the application of several different approaches to solve complex environmental problems, including quantum chemistry approaches, environmental speciation studies, photodegradation processes, snowpack photochemistry, long‑term lake chemistry trends, and chemometric case studies that demonstrate the power of data‑driven environmental insights.

Appealing to graduate students, researchers, and professionals in environmental chemistry, environmental science, atmospheric chemistry, analytical chemistry, and climate science, this textbook equips readers with a comprehensive understanding of nature's complexity and the human-environment interaction, essential for achieving sustainable solutions. It is particularly valuable for scientists seeking to integrate complexity-aware thinking into their research or to adopt advanced analytical and computational approaches in the study of environmental systems.