One of the most pressing questions in economics is “why are some countries richer than others?” One methodology designed to help answer the question is known as “Development Accounting,” a framework that organizes the determinants of income into two categories: differences in inputs and differences in efficiency. The objective of our work is to study to what extent differences in the levels of pollution can help explain income differences across countries. To do this, we adjusted a factor-only model to allow us to enter PM2.5, a measure of pollution that tracks the concentration of fine particulate matter in the air and looked to see if the model’s predictive power improved. We ultimately find that we can improve the model’s success in predicting GDP by .5 - 6%. Thus, pollution is unlikely to be a major force in understanding cross-country income differences, but it can be used with other economic factors to potentially magnify its impact with other additions in the future.

Using the Development Accounting methodology specified in Caselli (2004), we investigate the potential of PM2.5, a measure of pollution, as an explanation of cross-country differences in GDP using available Macroeconomic data from the Penn World Table and the WHO. We find that the addition of PM2.5 makes improvements to the model within the expectations of the literature. This adjustment shows promise for use in cooperation with other, more potent economic factors.

Urban ecosystems are subjected to high temperatures—extreme heat events, chronically hot weather, or both—through interactions between local and global climate processes. Urban vegetation may provide a cooling ecosystem service, although many knowledge gaps exist in the biophysical and social dynamics of using this service to reduce climate extremes. To better understand patterns of urban vegetated cooling, the potential water requirements to supply these services, and differential access to these services between residential neighborhoods, we evaluated three decades (1970–2000) of land surface characteristics and residential segregation by income in the Phoenix, Arizona, USA metropolitan region. We developed an ecosystem service trade‐offs approach to assess the urban heat riskscape, defined as the spatial variation in risk exposure and potential human vulnerability to extreme heat. In this region, vegetation provided nearly a 25°C surface cooling compared to bare soil on low‐humidity summer days; the magnitude of this service was strongly coupled to air temperature and vapor pressure deficits.

To estimate the water loss associated with land‐surface cooling, we applied a surface energy balance model. Our initial estimates suggest 2.7 mm/d of water may be used in supplying cooling ecosystem services in the Phoenix region on a summer day. The availability and corresponding resource use requirements of these ecosystem services had a strongly positive relationship with neighborhood income in the year 2000. However, economic stratification in access to services is a recent development: no vegetation–income relationship was observed in 1970, and a clear trend of increasing correlation was evident through 2000. To alleviate neighborhood inequality in risks from extreme heat through increased vegetation and evaporative cooling, large increases in regional water use would be required. Together, these results suggest the need for a systems evaluation of the benefits, costs, spatial structure, and temporal trajectory for the use of ecosystem services to moderate climate extremes. Increasing vegetation is one strategy for moderating regional climate changes in urban areas and simultaneously providing multiple ecosystem services. However, vegetation has economic, water, and social equity implications that vary dramatically across neighborhoods and need to be managed through informed environmental policies.

The incidence of childhood obesity has become increasingly prevalent in the United States in recent years. The development of obesity at any age, but especially in adolescence, can have lasting negative effects in the form of cardiometabolic disease, increased incurred healthcare costs, and potential negative effects on quality of life. In recent years, a rising trend of obesity, in both adults and adolescents, has been observed in lower income and ethnic groups. Increased adiposity can be influenced by modifiable factors -(physical activity, caloric intake, or sleep) or by non-modifiable factors (ethnicity, genetic predispositions, and socioeconomic status). The influence of these factors can be observed in individuals of all ages, including infants. A common indicator of the development of childhood obesity is rapid weight gain (RWG) within an infant’s first year of life. The composition of the gut microbiome can act as a predictor for RWG and the development of childhood obesity. Infants are exposed to an immense microbial load when they are born and their gut microbiome is continually diversified through their method of feeding and the subsequent introduction to solid foods. While currently understudied, it is understood that cultural and socioeconomic factors influence the development of the gut microbiome, which is further explored in this analysis. The DNA from 51 fecal samples from infants ranging from 3 weeks to 12 months in age was extracted and sequenced using next-generation sequencing, and the resulting sequences were analyzed using QIIME 2. Results from alpha-diversity and beta-diversity metrics showed significant differences in the gut microbiome of infants when comparing groups based on baby race/ethnicity, household income, and mom’s education. These findings suggest the importance of sociodemographic characteristics in shaping the gut microbiome and suggest the importance of future studies including diverse populations in gut microbiome work.