Assessment of COVID-19 control strategies in a steel industry using a SWOT matrix

Dispersion of SO2 emissions in a gas refinery by AERMOD modeling and human health risk: a case study in the Middle East

This study aimed to model the dispersion of emitted SO2 from stacks and flares in one of the largest Gas Refinery Companies in the Middle East . Pollutant emission coefficients and air pollution's various sources contributions were determined based on the collected data after measuring SO2 concentrations in a fixed monitoring station (stack) and across different distances from it for a year. The SO2 release pattern was simulated, and annual pollutant concentrations in average periods of 1-hr and 24-hr were predicted using AERMOD 8.9.0. The maximum simulated ambient SO2 were 27,447 and 4592 µg/m3 in average sampling times of 1-hr and 24-hr, respectively. The hazard quotient of 95% percentile for children, teenagers, and adults due to inhalation of SO2 was more than one.The maximum concentration of SO2 in the 1-hour and 24-hour period in the study area was higher than the amount introduced by Iran's clean air standard and the WHO standard.

Presented and prioritizing waste management strategies using SWOT and QSPM approach in two private hospitals in Yazd in 2021

BACKGROUND

This study aimed to present a strategic waste management in two private hospitals in Yazd using models of the strengths, weaknesses, opportunities, and threats (SWOT) and quantitative strategic planning matrix (QSPM).

METHODS

The strengths, weaknesses, opportunities, and threats of the organization was identified according to existing documents and expert team. The internal and external factors were identified by internal factor evaluation (IFE) and external factor evaluation (EFE) matrices. The strategies to improve waste management in two hospitals were presented by comparing internal and external factors. Finally, the attractiveness table was compiled and weighted using the QSPM method to prioritize the strategies.

RESULTS

The results demonstrated that 24 strengths, 30 weaknesses, 16 opportunities, and 22 threats were identified. The final score of internal and external factors for hospital A and B were (X: 2.37, Y:1.88) and (X: 2.37, Y: 2.01), respectively. Based on the results, 12 strategies were presented. Finally, the strategy of "the improvement of green management indicators" was implemented as a priority according to QSPM matrix.

CONCLUSION

The result of this study duplicated that using the QSPM and SWOT models is assist to present viable strategies to improve the health-care waste management.

A district-level vulnerability assessment of next COVID-19 variant (Omicron BA.2) in Uttarakhand using quantitative SWOT analysis

COVID-19 has had an impact on the entire humankind and has been proved to spread in deadly waves. As a result, preparedness and planning are required to better deal with the epidemic's upcoming waves. Effective planning, on the other hand, necessitates detailed vulnerability assessments at all levels, from the national to the state or regional. There are several issues at the regional level, and each region has its own features. As a result, each region needs its own COVID-19 vulnerability assessment. In terms of climate, terrain and demographics, the state of Uttarakhand differs significantly from the rest of India. As a result, a vulnerability assessment of the next COVID-19 variation (Omicron BA.2) is required for district-level planning to meet regional concerns. A total of 17 variables were chosen for this study, including demographic, socio-economic, infrastructure, epidemiological and tourism-related factors. AHP was used to compute their weights. After applying min-max normalisation to the data, a district-level quantitative SWOT is created to compare the performance of 13 Uttarakhand districts. A COVID-19 vulnerability index (normalised R i ) ranging between 0 and 1 was produced, and district-level vulnerabilities were mapped. Quantitative SWOT results depict that Dehradun is a best performing district followed by Haridwar, while Bageshwar, Rudra Prayag, Champawat and Pithoragarh are on the weaker side and the normalised Ri proves Dehradun, Nainital, Champawat, Bageshwar and Chamoli to be least vulnerable to COVID-19 (normalised R i ≤ 0.25) and Pithoragarh to be the most vulnerable district (normalised R i > 0.90). Pauri Garwal and Uttarkashi are moderately vulnerable (normalised R i 0.50 to 0.75).

Environmental impact assessment of a steel industry development plan using combined method involving Leopold matrix and RIAM

The present study was conducted to determine positive and negative impacts of Sepid-Farab Kavir steel (SKS) complex development plan and to propose suitable managerial strategies by a combined method involving Leopold matrix and Rapid Impact Assessment matrix (RIAM). The SKS complex is located in Aran-Bidgol city, Isfahan, Iran. Two scenarios of project implementation and project cancellation were formulated for SKS complex development plan, which has two sub-phases: construction and operation Using Leopold and RIAM matrices, the direct and indirect impacts of the project on the study area was investigated. The impact analysis for project cancellation scenario showed that the obtained scores of construction and operation phases were -119 and -52, respectively. Also, for project implementation scenario, the obtained scores of construction and operation phases were + 302 and + 382, respectively. The number of positive impacts in the implementation and cancellation scenarios were 354 and 48, respectively, and the number of negative impacts in implementation and cancellation scenarios were 270 and 127, respectively. Also, comparison of positive and negative impacts frequency in the two scenarios, and in the two sub-phases, in RIAM indicated the project implementation will have positive impacts in social-cultural and economic-operational aspects compared to option of prevention, especially in operation phase. The results of environmental impact assessment of the mentioned project indicated the superiority of positive impacts over the negative ones.