An increase in human activity on the earth has increased the amount of waste emission on the planet. The Environmental Protection Agency (EPA) is a body that sets guidelines and rules that promote industrial and regional practices that reduce pollution, providing cleaner air for the American citizens. The rate of pollution has significantly decreased across America since the inauguration of the FDA. Cleaner air reduces the risk of all ages developing lung-related health complications, among other diseases and infections.
Air contaminants contain gases and particles emitted from industrial machinery, stationary home appliances, and transportation motor vehicles. There are seven common pollutants, namely: carbon monoxide largely emitted from motor-powered machines, volatile organic compounds that react in the presence of light to emit air pollutants, ammonia commonly emitted from industrial machinery, fine particles (PM2.5) are linked to causing lung cancer when harmful particles in the air enter the lungs and possibly the bloodstream (Dedovic, Avdakovic, Turkovic, Dautbasic, & Konjic, 2016), sulfur dioxide mostly a waste product of stationary machinery, and large particles (PM10) that causes nose, throat and eyes irritation.
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The city of El Paso, Texas, has two refining industries that conduct industrial activities in the region. The air quality index around the factories shows a hazardous air quality (Sowlat, Gharibi, Yunesian, Mahmoudi, & Lotfi, 2011). However, in places such as Ascarate Park, where there is small motor equipment, air quality is good. El Paso has a low population of 649,133 as of 2010, which reduces the amount of waste generated per person. Air pollutants influence human behavior and response. For example, a high air contaminant level will require people to shift their outdoor workouts to gyms. This enables people to be aware of their health and safeguard their wellbeing.
References
Dedovic, M. M., Avdakovic, S., Turkovic, I., Dautbasic, N., & Konjic, T. (2016). Forecasting PM10 concentrations using neural networks and systems for improving air quality. 2016 XI International Symposium on Telecommunications (BIHTEL) , 1-6.
Sowlat, M. H., Gharibi, H., Yunesian, M., Mahmoudi, M. T., & Lotfi, S. (2011). A novel, fuzzy-based air quality index (FAQI) for air quality assessment. Atmospheric Environment , 2050-2059.
