# Assessing Crisis Management Tools for Sustainability of Industrial Safety
## 6 Discussion  
The findings from this study confirmed the critical role of ALOHA in modelling hazardous substance releases and its application to emergency management strategies. Through detailed scenario analysis, ALOHA demonstrated its ability to predict the spread of ammonia in Scenario 1 and the thermal radiation risks posed by a pool fire in Scenario 2. The precise mapping of danger zones--ERPG-3 (C \(\geq\) 1500 ppm), ERPG-2 (C \(\geq\) 150 ppm), and ERPG-1 (C \(\geq\) 25 ppm)--proved vital in informing evacuation protocols and protective measures. The accurate identification of these zones underscores ALOHA's strength in assessing immediate risks, particularly in industrial settings where timely intervention is crucial [19; 27; 28]. Scenario 2 highlighted ALOHA's capability to model fire hazards, focusing on the effects of thermal radiation. The results delineated the most dangerous areas based on thermal radiation intensity, showing how evacuation routes and rescue interventions can be optimised to minimise exposure risks. The thermal radiation danger zones--ERPG-3 (q \(\geq\) 10.0 kW.m\({}^{-2}\)), ERPG-2 (5.0 kW.m\({}^{-2}\)), and ERPG-1 (2.0 kW.m\({}^{-2}\))--provided clear guidance for the deployment of protective measures, ensuring safety in areas where heat could cause fatal injuries or burns within a short exposure time [21; 24; 29; 30]. Despite its effectiveness, the study revealed several opportunities for enhancing ALOHA's performance. One key area for improvement is the expansion of ALOHA's chemical database, which would allow for more comprehensive risk assessments across a broader range of substances and scenarios. By extending the database, users could model a wider variety of industrial chemicals, thereby improving emergency preparedness across multiple sectors [19; 25; 31]. This would also make ALOHA more versatile and applicable in diverse settings where different hazardous materials are in use [21; 27; 28]. The integration of modern technologies, such as Geographic Information Systems (GIS), Artificial Intelligence (AI), and drones, represents another significant opportunity for enhancing ALOHA's capabilities. GIS could provide real-time mapping of danger zones,enabling more dynamic visualisation and improved decision-making during emergencies. Combining GIS with ALOHA's predictive models would allow responders to update evacuation routes and risk zones in real time, based on continuously changing environmental conditions [13; 17; 31]. Furthermore, AI could improve the accuracy of ALOHA's predictions by enabling real-time analysis of incoming data. By leveraging AI algorithms, ALOHA could continuously refine its hazard models as new environmental data--such as wind speed and temperature--become available, ensuring more adaptive and precise emergency responses [22; 32]. Drones equipped with chemical sensors could further enhance real-time data collection, providing critical information from hazardous zones that would be otherwise difficult to access. This would allow ALOHA to incorporate real-time data into its simulations, increasing the accuracy of risk assessments and offering a more comprehensive view of the evolving situation [17; 31]. However, ALOHA's reliance on static input data, such as pre-configured meteorological conditions, remains a limitation, particularly in dynamic scenarios where environmental factors can change rapidly. Integrating real-time weather data, as well as more advanced monitoring systems, would significantly improve the reliability of ALOHA's predictions. This would reduce the uncertainty in emergency scenarios where quick decision-making is essential to protect public health and infrastructure [21; 29; 31]. Additionally, comparisons with other risk assessment tools, such as PHAST or SAFER, could provide further insights into ALOHA's strengths and areas for improvement.