We found three barriers: (1) the uncertainty in risk estimates and the benefits of acknowledging and quantifying those uncertainties, as well as a discussion of the importance of estimating the costs for potential controls and the role of societal tradeoffs between health and wealth inherent in any such decisions, (2) compartmentalization of efforts and working in silos, and (3) challenges to decide how to prioritize risks in policy agendas.

The focus of the workshop was on risk management in environmental health, with the discussion driven towards regulating air pollution. A central focus was the dilemma of deciding what exposure controls to prioritize, acknowledging that science provides essential data and insights but cannot determine ‘acceptable levels of risk’, and that decisions often involve complex trade-offs, weighing the potential health benefits against economic, social, and political factors. Furthermore, many stakeholders involved in such decisions are unlikely to hold similar views about values and often have very different ideas about the inevitable tradeoffs between health and wealth. Differences in values are best brought into the open and recognized as legitimate elements of societal decision making.

An additional challenge is that this decision-making involves substantial uncertainty about the magnitude of risks and the health benefits of emission control policies. This uncertainty stems from fundamental limitations in scientific understanding of both the biology and toxicology underlying human disease development and in determining the impacts of specific emissions sources on human exposure to environmental contaminants. Decision-makers typically hold different preferences for risk—some may be risk averse, whereas others may be risk neutral or risk seeking. Recognizing these potential differences in attitudes towards uncertainty offers real potential to disentangle issues of science from issues of value and to improve the clarity and efficiency of decision and policy making.

To navigate some of these challenges, our approach emphasized: (i) the importance of incorporating uncertainty into the decision-making process and conducting value-of-information analyses to help plan future research aimed at reducing this uncertainty; and (ii) the benefits of recognizing the distinct and important role of societal values in decision-making, to avoid falling into the ‘let science speak’ trap—pretending that science itself can resolve complex public policy dilemmas that have economic costs, and other social consequences of policies, and ignoring tradeoffs between health benefits and economic costs or other consequences.

Structured expert judgment [4] is necessary to characterize the uncertainty about fine particulate matter (particulate matter with aerodynamic diameter less than 2.5 microns, PM2.5) health effects in Abu Dhabi due to lack of local studies and to the complexity of the issues involved in borrowing literature from the United States, Europe, and other countries, to apply to the Middle East, such as the possibility of differential toxicity of PM2.5 components, the multiplicity of possible concentration–response functions at high PM2.5 levels, among others [5]. The value of information analysis then plays a crucial role, using uncertainty to help determine which additional data and research can be most valuable, by considering whether the cost of research (financial or otherwise) justifies the added value it may provide in the form of improved decision-making due to reduced uncertainty [6]. This approach enables a more strategic allocation of resources. Ultimately, by placing these considerations of risk and uncertainty front and center in our discussion, we set the stage for more nuanced and effective decision-making processes (Fig. 1).

Process to decisions, risk, and uncertainty

We then found compartmentalization of efforts that were unintentional in monitoring and researching air pollution in the UAE. There were commendable initiatives led by each of the stakeholder groups. Since 2007, Abu Dhabi built an extensive network of 20 fixed and 2 mobile stations for measuring particulate pollution, accumulating over 1.5 billion valid minute-data points. The Emirate also commissioned innovative endeavors like remote sensing of vehicle emissions and ship monitoring. Nevertheless, the integration of this data into policymaking was requiring action. Similarly, detailed environmental health risk assessment work conducted in the past decade [3] has not been effectively synthesized nor translated into broader policy measures. Again, the root cause appears to be the siloed nature of the organization of these efforts, with those responsible for pollution monitoring, health effects analysis, and policy development working separately and largely independently of each other. Much of the crucial data and insights remain isolated within specific entities. These problems are not unique to Abu Dhabi or the UAE, but are common throughout the region and across the globe. This disconnect hinders the creation of comprehensive regulatory standards, such as for PM2.5, and limits the impact of these valuable datasets and assessments on policy formulation and implementation.

In our discussion of the barriers to effective policymaking, the main criterion that emerged regarding the prioritization of environmental exposures for control was their potential impact on public health. Specifically, the focus was drawn to air pollution, notably PM2.5, as a priority concern due to its high impact on public health as compared to other pollutants, such as those commonly found in contaminated soil. This prioritization recognizes the substantial body of evidence linking PM2.5 exposure to large effects on a range of adverse health outcomes, making it an immediate and substantial threat to public health [7]. The decision-making process, therefore, emphasized targeting those exposures that promise the highest yield in terms of health benefits.