Uncertainty and collaborative governance: the role of science in combating shipping air pollution in Hong Kong and the Greater Bay Area, China

Abstract

ABSTRACT Uncertainty has been considered both a driver of and barrier to collaborative governance. Uncertainty concerning pollution sources, its impacts, and the effectiveness of control measures can undermine incentive structures necessary for collaborative governance. This paper examines the uncertainties in air pollution policy formulation in Hong Kong and the Pearl River Delta Greater Bay Area, as well as the role of science in reducing such uncertainties to foster and sustain collaborative governance. Through a case study of shipping emissions control, we find that science can play a critical role in addressing substantive uncertainties, the mitigation of which facilitates voluntary agreements and other collaborative arrangements that reduce strategic and institutional uncertainties to enable the enactment of official policy solutions. This study shows that science can reduce uncertainties and facilitate collaborative governance under circumstances that permit the avoidance of key challenges raised by other scholars. The mitigation of these uncertainties can allow a collaborative governance framework to evolve across typological levels during the policy development process.