Data Analysis-IS

Data Analysis

Project Site: Donora 1948 Smog

Donora Smog Report 1949: Unequal Distribution of Smog Affection

Figure 2 from Air Pollution in Donora, PA.: Epidemiology of the Unusual Smog Episode of October 1948. The figure shows the location of households interviewed for the study along with providing a visual to understand where Donora is in relation to the river and the plants.

            During the final week of October 1948, a thick layer of smog coated the valley of the West bank of the Monongahela river, where the town of Donora is located. Not only did this smog reduce visibility in the town, but it also caused those living in the town to experience sickness. As a result, a year long study was conducted with the intention of determining the cause of the smog incident and determining how to prevent future incidents (which can be found here). The report is then broken down into two primary sections: “Biological Studies” and “Atmospheric Studies,”. “Biological Studies” looks at the demographic makeup of Donora and Webster, a neighboring town also affected, along with the affects the smog had on the population. “Atmospheric Studies” analyzes the contaminants being put out by the three plants along the river in Donora. The year long study concludes that age, residence, and previous health status affected how severely the smog affected someone and determined that a weather phenomenon preventing air pollution from leaving the valley is what caused the illnesses. It could not determine that a singular pollutant was responsible for the illnesses and deaths, but that it came from the exposure of a cocktail of pollutants from both the local plants and the local traffic on the streets, river, and railroads. This report orients itself as a scientific and objective study shying away from suggestions that may seem political in nature. The data only shows inequality of who was affected by the smog and how it affected different populations, but does not do further analysis of causes of the inequality, yet the data does still show data suggesting that one’s socio-economic status was relevant to how they may have been affected by the smog.  

            Using data from the 1940 census, the demographics of Donora are broken down and are compared to national, state, and South-West Pennsylvania trends. Overall, only about 42.7 percent of the population reported being affected by the smog. When crossing referencing the demographic data with data from interviews and medical records of those who reported being affected by the smog, trends begin to emerge. These trends lead the study to conclude that age, residence, and previous health status were linked to how severely the smog affected someone. Generally, as the age of persons increased, so did the percent reporting affection from the smog. All age groups above and including 35-39 have over half the respective population reporting affection from the smog. The report also broke the population into residence districts, which showed that district one in Donora and Webster had higher rates of affection from smog. Yet it only crosses residence with age of residents, it does not consider any other factors than may influence affection from smog. Finally, previous health status was noted as a significant factor for affection. Persons who were already inflicted with a cardiovascular disease or condition also reported higher rates of affection from smog. This also relates to housing conditions. Residences that had higher amounts of affection also had the least amount of satisfactory housing. While there is no chart to display this data, the report states that as the number of dwellings rated as satisfactory and above increase, the percentage of reports decreases. While the report does suggest further research into housing conditions, it does not suggest improving housing as a way to prevent such an incident in the future. Yet for housing to be such a significant factor in the study for degree of affection shows the reader that one’s socio-economic status was also important for determining how the smog affected someone.

            Throughout the year after the incident, weather and atmospheric tests were done. These tests analyzed the pollutants being put into the air by the local plants. The report broke the pollutants down into the average amount found in the air and broke down the amount of each pollutant coming from each plant. This report does conclude that none of the plants individually are putting out amounts of pollutants that are considered harmful to the population or go above current (current being regulations in 1949) regulations, it does not rule out the possibility of the cocktail of pollutants being emitted from the factories along with the pollutants from traffic from the river, railroads, and streets as being harmful to the population. In the “Recommendations” section, reducing the pollutants, especially sulfur dioxide and particulate matter, from the plants are directly listed as a way to prevent such an incident. However, it does not suggest how the plants go about lowing the emissions of pollutants. The report shies away from making specific suggestions on how to regulate the plants via policy or technological changes to the plants. The report makes no suggestions that could be read as political, yet the fact that the pollutants from the plants are not ruled out as being harmful and that reduction measures are suggested also shows that the corporations owning and running the plants are not innocent in the issue.

            The report also investigates the meteorological conditions that caused the smog to sit in the town for several days. It compared known conditions from the incident with data collected daily from the area. It concludes that the weather event from the incident was an extreme version of “smokey mornings”. Smokey mornings are when there tends to be less wind to blow smoke out of the valley along with air temperatures preventing the smoke from rising – these mornings may also be accompanied with fog. While these were not uncommon, it is uncommon for the smoke to stay in the valley past noon. In this extreme smokey morning, there was little wind and the air was not rising out of the valley, trapping the smog in the valley. Along with noting the weather conditions that caused this incident, it also notes that on days with less or slower wind there were higher concentrations of pollutants in the air. This extreme weather condition is likely to occur, but the report says it would only be in intervals of ten to fifteen years. Extreme weather is then suggested to be the primary factor responsible for the incident and the report suggests that the weather should be monitored a system in place to warn of poor weather conditions.

            Once the report discusses the primary cause of the incident as extreme weather mixed with significant amounts of pollutants, it suggests that while the plants were responsible, it was not primarily their fault. Still, it does suggest a reduction of pollution from the plants. While it credits the weather for trapping the smog, the data seems to also imply a reliance on the weather to push the smog and pollution out of the area. It also fails to acknowledge the fact that a weather phenomenon such as this would not have been dangerous if the plants were not emitting harmful pollutants. It also vaguely suggests the importance of socio-economic standing when looking at rates of affection from the smog, yet the report shows evidence of it. While the primary piece of evidence is the housing conditions, it also notes a higher mortality rate for black persons affected than white persons affected from the smog. Yet it also states multiple times that race was not an important factor for determining affection, which means there was some sort of inequality in the treatment of white persons affected and black persons affected. This report primary orients itself as an objective, scientific report driven by data, but it still shows remnants of issues of societal inequalities as factors for who was affected by the smog.

Keywords: class, toxics, air, pollution, factories