Effects of Urbanization on Water Pollution

Urbanization has become a growing issue across the United States; most people prefer to live in larger cities where there are more opportunities and arguably better ways of life. This increase in population in urban areas demands serious expansion outwards, most notably to the suburbs or rural areas, due to the lack of space. Thus, development is inevitable. Development may be beneficial for accommodating extra bodies, yet still has drastic consequences, especially on the environment, and on quality of life and the strain of infrastructure as well (Fox, 2010). Urban sprawl has also been shown to have an impact on human health, whether due to more vehicular accidents, increased obesity rates, higher emissions of carbon, or prolonged wait time for emergency medical assistance (Lambert et al., 2012). The increase in urban development in big cities, otherwise known as urban sprawl, has caused a drastic rise in pollution, especially in the United States. The pollution, both air and water, that results from this growth can destroy the environment and be detrimental to human health as well. Drinking water and groundwater can be polluted and the atmosphere can see an influx of gases and particles that contribute to global warming.

More traffic occurs during urban development due to the closing of roads or changes in traffic patterns. This backup of cars causes more pollutants to be released into the atmosphere, resulting in a slight increase in global warming. Carbon dioxide and nitrous oxide are the main greenhouse gases given off from combustion of gasoline by cars. Vehicles associated with the construction itself, such as dump trucks, cranes, bulldozers, or excavators, also give off these greenhouse gases, adding more harmful particles to the atmosphere. The deterioration of water quality following increased urban sprawl is due to the combination of population and land-use changes (Tu et al., 2007). Water pollution can often occur following bouts of rain that wash the chemicals from the sites to bodies of water. In addition to runoff, the pollutants in the air can fall to bodies of water, thus affecting both the atmosphere and the water sources.

To determine the amount of pollution associated with urban sprawl, Bereitschaft and Debbage used linear regression models with the (1) O3 precursors, NOx and volatile organic compounds, and PM2.5 (in 2000) from polluted runoff from land, (2) CO2 emissions, and (3) O3 and PM2.5 averaged ambient concentrations as the dependent variables and different measurements of urban sprawl as the independent variables (2013). The linear regression models also included some controls including temperature, moisture, wind speed, metropolitan population, and regional population to justify certain variations in concentration of pollutants or to distinguish between pollutants/emissions that were not associated with urban sprawl (Bereitschaft and Debbage, 2013). These models helped determine the relationships between the dependent and independent variables and the correlation between the two. To measure this relationship, data of air pollution (nonpoint source emissions and on-road emissions) was compiled from a database from 86 different cities in the United States with a 500,000 person population or greater.

The data from the other half of this relationship, regarding urban sprawl, was acquired from five different indexes and the experimenters also took into account urban continuity and shape complexity from satellites to better determine the relationship between pollution and urban sprawl. Land cover data was also used from the National Landcover Dataset (NLCD) to measure the boundary of the metropolitan area and to calculate landscape metrics. To better approximate the boundaries of the metropolitan area, they also used satellites to evaluate anthropogenic lighting intensity as shown by Figure 1C (Bereitschaft and Debbage, 2013). Another experiment, by Tu et al., demonstrated this same correlation between urban sprawl and pollution, but focusing on the water quality aspect, specifically in Massachusetts (2007). They used the Massachusetts Geographic Information System to procure data on land-use and population and many aerial photographs were obtained from the University of Massachusetts, Amherst Research Mapping Project to determine the developed land use areas. Data from the USGS National Water Information System Web was obtained to measure the water quality in 37 areas and many parameters were created to indicate certain water quality (dissolved nutrients, dissolved ions, dissolved solid, suspended sediment, specific conductance).

In the first phase of this experiment, the effects of urban sprawl on specific conductance (SC) of water was measured using ArcGIS software by creating water quality layers over different periods of time. They used this layering to overlap with the indicators of urban sprawl during those same time periods to see the correlation between the two variables (water quality and urban sprawl). For the second phase of this experiment, correlation analysis was used to measure spatial as well as temporal relationships between the two variables. For each of the 37 sites, watersheds were delineated using ArcGIS and this watershed layer, land-use layers, and population layers were all overlapped using this same software to determine certain indicators for urban sprawl. The implementation of Spearman rank correlation analysis was advantageous in determining the relationship of water quality and urban sprawl over time (Tu et al., 2007).

The experiment by Bereitschaft and Debbage, which looked at the relationship between urban sprawl and pollution, found that all of the linear regression models performed had statistically significant correlations (p<0.001) (2013), thus providing evidence that urban sprawl does in fact negatively impact the amount of pollution. In regards to urban continuity and urban shape complexity, the experiment results showed that decreasing urban continuity led to an increase in CO2, PM2.5, VOCs, and NOx emissions and increasing shape complexity led to an increase in NOx and PM2.5 emissions (Bereitschaft and Debbage, 2013). To reduce pollutants, it is better to have a more contiguous area, rather than more fragmentation, because more area between different developments can cause more emissions from vehicles due to greater travel. The urban area should also have less complexity to its shape or less irregularity to the boundary for this same automotive reason. Therefore, the urban sprawl associated with these areas should follow these continuity and shape complexity recommendations for less emissions. According to Bereitschaft and Debbage, continuity and shape complexity of urban areas affect ambient concentrations as well, including ozone; however, the urban sprawl indexes had a more compelling correlation with ambient concentrations than the other two urban formations as shown by Figure 2. Every index demonstrated that when there is an increase in urban sprawl, the concentrations and emissions of air pollutants significantly increased or remained consistent.

However, the Sutton index was the most accurate index due to it being the only one to have a significant correlation with ozone concentration and PM2.5 emissions. It was also shown that there was an increase in ozone concentration when there was a rise in temperature (Bereitschaft and Debbage, 2013). This demonstrates the positive feedback loop associated with global warming and how these pollutants, especially O3, that potentially result from urban sprawl can contribute to the detrimental warming of the Earth. The experiment by Tu et al., showed similar findings. Areas with higher population density (PD) were shown to have higher specific conductance (SC) concentrations in the water (Tu et al., 2007). The suburban and rural areas surrounding the metropolitan center of a city were increasing in population density and percentage of developed land use. The specific conductance is a great indicator of water pollution because more compounds in the water leads to more ions in the water which leads to a higher conductivity. Therefore, a high SC is indicative of pollutants in the water.

According to Tu et al., growth in a population around a metropolitan area (i.e., suburbs), results in a rise in SC concentrations within the metropolitan area (2007), which could be due to urban sprawl. Areas with increased percentage of developed land use (PDLU) around the metropolitan site were also associated with higher concentrations of specific conductance and areas with lower per capita developed land use (PCDLU) had an increase in SC concentrations (very urbanized area). The suburbs around Boston, as reported by Tu et al., showed a drastic rise in PD and PDLU, and, therefore, had higher SC concentrations, while the Boston area had a lower increase in PD, PDLU, and SC. As a result, it can be assumed that both population growth and development of land have a severe impact on the quality of water due to urban sprawl. For every season, it was found that there were significantly positive correlations between PD and SC, Ca, Mg, Na, Cl, and dissolved solid (DS) concentrations and between PDLU and and SC, Ca, Mg, Na, Cl, and DS concentrations (except for SC and Ca in winter). Dissolved nitrogen also had positive correlations with PDLU and PD, yet not all values were significant. The suspended sediment (SS) values were also positively correlated with PD and PDLU (Tu et al., 2007). Therefore, according to these values, it is shown that the higher concentrations of many of the indicators for water quality were found in areas with higher PD and PDLU. On the other hand, higher PCDLU areas had more indicators associated with urbanization (significant negative correlations) rather than PD or PDLU, including dissolved nitrogen, potassium, and sulfate concentrations. From these results, it was presumed that as the development of land increased, the water quality deteriorated more quickly, according to the PDLU (Tu et al., 2007).

Urban sprawl is a continuous problem in the United States that needs to be addressed. It is significantly adding to our global warming issue by supplementing the pollutants in the atmosphere and it is also drastically impacting our waterways and human health. In order to reduce these negative consequences, the problem at hand needs to be dealt with. Therefore, if we were to diminish the amount of urban development that is occurring, especially throughout developed nations, the overall pollution would decrease as well; this would dramatically improve our air and water quality. Some US cities, such as Seattle, have followed Vancouver's lead and have executed Smart Growth policies to reduce the amount of sprawl that is occurring within these large cities (Fox, 2010). These policies, according to Fox, are beneficial to the environment and human health while also balancing economic development by focusing on the transportation issues in very urbanized areas (2010). Canada has managed to use this approach much more effectively than in the United States; these principles could be extremely beneficial in the U.S. if more cities were to implement them.

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