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Modeling green infrastructure land use changes on future air quality in Kansas City
Zhang, Y., J. Bash, S. Roselle, A. Gilliland, C. Hogrefe, G. Pouliot, A. Shatas, R. DeYoung, AND J. Piziali. Modeling green infrastructure land use changes on future air quality in Kansas City. 2016 CMAS Conference, Chapel Hill, NC, October 24 - 26, 2016.
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Green infrastructure can be a cost-effective approach for reducing stormwater runoff and improving water quality as a result, but it could also bring co-benefits for air quality: less impervious surfaces and more vegetation can decrease the urban heat island effect, and also result in more removal of air pollutants via dry deposition with increased vegetative surfaces. Cooler surface temperatures can also decrease ozone formation through the increases of NOx titration; however, cooler surface temperatures also lower the height of the boundary layer resulting in more concentrated pollutants within the same volume of air, especially for primary emitted pollutants (e.g. NOx, CO, primary particulate matter). To better understand how green infrastructure impacts air quality, the interactions between all of these processes must be considered collectively. In this study, we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes that include green infrastructure in Kansas City (KC) on regional meteorology and air quality. Current and future land use data was provided by the Mid-America Regional Council for 2012 and 2040 (projected land use due to population growth, city planning and green infrastructure implementation). These land use datasets were incorporated into the WRF-CMAQ modeling system allowing the modeling system to propagate the changes in vegetation and impervious surface coverage on meteorology and air quality. The WRF-CMAQ model was run for the continental US using a 12km by 12km horizontal grid spacing and nested finer scale simulations using 4km by 4km. We found that the average 2-meter temperatures (T2) during summer (June, July and August) are projected to slightly decrease over the downtown of KC and slightly increase over the newly developed regions surrounding the urban core. The planetary boundary layer (PBL) height changes are consistent with the T2 changes: the PBL height was somewhat lowered over the downtown and was raised over the newly developed areas. We also saw relatively small decreases in O3 in the downtown area for the mean of all hours as well as for the maximum 8 hour average (MDA8), corresponding with the changes in T2 and PBL height. NOx increases during the night in the future case, which is likely caused by the lowered PBL height, and is consistent with the modeled changes in T2. However, we also found relatively small PM2.5 concentration increases over KC, especially over the downtown areas, with the largest contribution from components of organic carbon (OC), elementary carbon (EC), non-anion dust (SOIL), and unspeciated PM. More diagnostic analysis is needed to further investigate how these land use changes affect different processes (such as the dry deposition) and future work is needed to investigate the impact of temperature reduction on energy demand and anthropogenic emissions.