Temporality, causation

To obtain the mass emissions of pollutants from e-waste recycling processes, it is essential that the inputs of pollutants are truly e-waste related. To fulfill this requirement, a causal analysis is desirable. However, the concept of causation is rather problematic because causal mechanisms are complex [26]. Nonetheless, we are compelled to identify causes, in an attempt to minimize the uncertainties associated with our estimates. In this chapter, the strict empiricist, David Hume s empirical criterion, was adopted. This approach requires only a combination of (1) e-waste processing and environmental pollution are associated in space and time (contiguity) (2) e-waste processing precede to environmental pollution (temporal succession) and (3) e-waste processing is always conjoined with environmental pollution (consistent conjunction). These are always the cases judged from a number of previous studies [6, 27-35]. 

The WoE approach (Chapman et al. 2002) combines lines of evidence (LoE) including the presence of a proposed stressor, the ability of the stressor to cause an effect, and the observed effect in the field to establish causation. This is a powerful approach especially for systems that are limited in spatial and temporal scales, have clearly characterized stressors, and have extensive effects datasets. 

The phenomenon risk obeys a necessary causation. According to the ISO 12100 standard, which is meant to explain the Machinery Directive (MD) 2006/42/EG for the practical design, the risk assessment is the combination of risk analysis and risk evaluation. Risk analysis subsumes specifying the machine s limits (e.g., spatial and temporal limit), identifying the hazards involved, and estimating the extent of damage and the probability of its incidence. The risk fH is thus defined as a two-dimensional variable (damage severity S and expected frequency EF) which due to the EF element features a time-dependence ... 

In the context of medical causation. Sir Austin Bradford Hill, suggested in 1965 that to imply causation from the observation of association we should consider its (1) strength, (2) consistency, (3) specificity - the restriction to specific conditions, (4) temporality - the order of events, (5) dose-response relationship, (6) theoretical plausibility, and (7) coherence - the consistency with other related phenomena. Although these guidelines were presented in the context of medicine and epidemiology, it would be very usefiil to keep these necessary conditions for causality in mind when evaluating crash causation on the basis of statistical associations. 

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