In this paper, within the framework of increasing the contributions to sustainable development goals and reducing the water footprint, the sustainable production potential of a factory producing denim fabrics have been studied in association with the sustainable development goals. For this purpose, Life Cycle Assessment and Material Input per Service methods were used to determine the environmental impact factors of the factory and the existing water footprint. Calculations were made in three different ways, taking the factory’s total production capacity, a selected product, and the wet processes into account. Although the sustainable production potential of the factory is demonstrated with the Sustainable Development Goals, it has been determined that the contribution rates differ according to both the calculation method and the production data taken into account. As a result of the evaluations, it has emerged as a more dominant view that the factory’s contribution to the Sustainable Development Goals should be evaluated according to the total production capacity. The sustainability evaluation made according to the total production capacity determined that the factory contributed approximately 12% to Sustainable Development Goal 12 in the period examined, according to both Life Cycle Assessment and Material Input per Service methods. Although there is inconsistency in the Life Cycle Assessment and Material Input per Service method results, it was predicted that there are economic and environmental gain potentials related to Sustainable Development Goals 13, 14, and 15, and the sustainable production potential of the factory can be increased.
This is the first study to evaluate the indoor air quality of markets using the “Indoor Environmental Index”. In the study, carbon dioxide (CO2), relative humidity, temperature, particulate matter, and total volatile organic compounds were measured as indoor air quality parameters in four different markets in Istanbul during the COVID-19 pandemic. Data were analyzed and evaluated using IBM SPSS Statistics 22 program. While CO2, PM2.5, PM10, humidity, and temperature had a statistically significant difference in different markets, no statistically significant difference was found for NO2 and total volatile organic compounds (p > 0.05). Considering the different hours in a day, it was determined that there was a statistically significant difference for all parameters. The highest and strongest correlation between the parameters was found between PM2.5 and PM10 (r = 0.703, p < 0.01). The IEI values for 4 different markets in different time intervals in a day were found as 6.862, 6.775, 8.816, and 6.244, respectively. The highest and lowest Indoor Environmental Index values were calculated in market2 (7,525) and market4 (4,936), respectively. Indoor air quality parameters had an impact on the IEI results as they affected the pollution index and the discomfort index. As a result of the study, it was seen that the density of customers and products, the size of the closed area of the markets, and the capacity of ventilation equipment affect the indoor air quality. All these results were evaluated and suggestions were made about the visit times to the markets.
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