A new risk probability calculation method for urban ecological risk assessment

Abstract

The ecological risk associated with urbanization is of great concern where multiple stressors and risk receptors co-exist. Probabilistic risk characterization methods were rarely applied in past urban ecological risk assessments because of the difficulties in the derivation of theoretical probability distribution functions and the definite integral calculation. Therefore, we proposed a new method which is based on computer simulation and able to facilitate the calculation of risk probabilities. This method quantifies multiple ecological risk-related indicators using ecological models, implements Monte Carlo simulation to calculate the risk probability of single indicators, and applies the copula model to calculate the joint risk probability of multiple indicators. We conducted an assessment of urban ecological risk related to urban surface water environment in Beijing as a case study to validate this method. The results show that the means of surface runoff risk probability, total nitrogen pollutant load risk probability, and comprehensive (joint) risk probability were 0.33, 0.44, and 0.23, respectively, in the areas within Beijing Sixth Ring Road. All three types of risk were at moderate levels in the study areas, but exhibited high spatial heterogeneity and urban-suburban gradient. The average contributions of the three risk types were 25% (surface runoff risk), 32% (total nitrogen pollutant load risk), and 43% (comprehensive risk), indicating that the joint risk was overall the major risk type. In conclusion, our method considering multiple indicators and their probabilistic attributes can handle the uncertainties in ecological models and thus has potential to evaluate different types of urban ecological risks.

Measurement, Simulation, and Quantification of Lighting-Space Flicker Risk Levels Using Low-Cost TCS34725 Colour Sensor and IEEE 1789-2015 Standard

“…Similarly, in another research that aims to quantify the probability scale of the risk matrix, the authors devised clear and continuous probability ranges. Their approach was through implementing a Monte Carlo simulation of single indicators, hence applying the copula model to calculate the joint risk probability of multiple indicators [17]. Finally, in a building fire risk assessment, the researchers used event tree analysis to quantify the probability scale be more definite rather than estimates [18].…”

Calculation of dam risk probability of cascade reservoirs considering risk transmission and superposition

“…Moreover, most of them are limited to the risk analysis and calculation of unilateral factors (such as floods), which fail to consider the failure mode and actual risk status of cascade dams under the coupling action of multiple factors (Zhang et al, 2016;Zhou et al, 2018). Risk probability is usually used to describe the probability of accidents or risk events (Liu et al, 2020;Schwabe et al, 2015;Su et al, 2009). Considering that the risks faced by a single reservoir dam are also applicable to cascade reservoirs and its risk calculation method has been widely used, the calculation method of risk probability of cascade reservoir dams should be connected with the calculation method for a single reservoir dam to form a unified system.…”