Science Inventory

Unexpected air quality impacts from implementation of green infrastructure in urban environments: a Kansas City Case Study

Citation:

Zhang, Y., J. Bash, S. Roselle, Angela Shatas, A. Repinsky, R. Mathur, C. Hogrefe, J. Piziali, T. Jacobs, AND A. Gilliland. Unexpected air quality impacts from implementation of green infrastructure in urban environments: a Kansas City Case Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, 744(20):140960, (2020). https://doi.org/10.1016/j.scitotenv.2020.140960

Impact/Purpose:

The purpose of our study is to explore the air quality consequences of a feasible vegetative green infrastructure implementation strategy in the Kansas City, MO/KS area. We show that, urban surface temperatures would decrease, especially in the urban cores under the green infrastructure implementation. However, the reduced planetary boundary layer height resulting from the cooler surface temperatures, could also suppress the vertical mixing and transport of major primary air pollutants, which in turn increases concentrations of the near-surface primary air pollutants. This study indicates air quality changes in PM2.5 and O3 associated the additional shading and vegetation evaporation effects from an aggressive GI scenario would not outweigh broader ecologic and economic benefits from such as strategy.

Description:

Green infrastructure (GI) implementation can benefit an urban environment by minimizing the impacts of urban stormwater on aquatic ecosystems and human health. However, few studies have systematically analyzed the biophysical effects on regional air temperature and planetary boundary layer height (PBLH) that are triggered by changes in the urban vegetative coverage. In this study we use a state-of-the-art high-resolution air quality model to simulate the effects of a feasible vegetation-focused GI implementation scenario in Kansas City, MO/KS on regional meteorology and air quality. Full year simulations are conducted for both the base case and GI land use scenarios using two different land surface models (LSMs) schemes inside the meteorological model. While the magnitudes of the changes in air quality due to the GI implementation differ using the two LSMs, the model outputs consistently showed increases in summertime PM2.5 (1.1 µg m-3, approximately 10% increase using NOAH LSM), which occurred mostly during the night and arose from the primary components, due to the cooler surface temperatures and the decreased PBLH. Both the maximum daily 8-hour average ozone and 1hr daily maximum O3 during summertime, decreased over the downtown areas (maximum decreases of 0.9 and 1.4 ppbv respectively). The largest ozone decreases were predicted to happen during the night, mainly caused by the titration effect of increased NOx concentration from the lower PBLH. These results highlight the region-specific non-linear process feedback from GI on regional air quality, and further demonstrate the need for comprehensive coupled meteorological-air quality modeling systems for studying these impacts.