The characterization and accurate measurement of non-exhaust brake emissions address sustainable cities and communities from the United Nations Sustainable Development Goals. Multiple health studies correlate particulate matter (PM) with respiratory illness and the impacts on societies and economies in different ways. Even though the fate of PM from braking and the causality of direct health effects remains elusive, road transport is responsible for generating PM. The braking system has many nuances, making it challenging to establish overall targets for reduction without extensive measurements under controlled laboratory conditions. Some factors influencing PM generation include vehicle running mass, brake size, friction couple design, customer driving modes, and vehicles-in-operation. When testing using inertia dynamometers, other factors can influence the PM measurements - dynamometer design (enclosure, flow patterns, air duct, and sampling train), controls of speed, braking, and climatic conditions, emission instrumentation, filter media, weighing room operational practices, and general laboratory practices. To this effect, extensive laboratory measurement technologies have evolved over decades (as far back as the 1940s). These technologies reflect multiple systems and devices already standardized and used in other type approvals, regulatory, or corporate development and validation programs worldwide. This work presents systematically the different elements, industry standards, and technologies that can enable the industry (and other stakeholders) to quantify brake emissions reliably using inertia dynamometer systems. Successful implementation of strategies to address potential type approval or regulations to limit brake emissions potentially involves vehicle electrification, new friction designs, different brake control strategies, and (for certain applications) retrofit systems to sequester the brake PM. All of the above requires sound technologies and systems (which already exist) implemented in a well-rounded ensemble testing process to generate relevant, repeatable, and reproducible data to support timely decision processes across the industry and society.