Impact of air pollution induced climate change on water availability and ecosystem productivity in the conterminous United States
- 1.3k Downloads
Air pollution from greenhouse gases and atmospheric aerosols are the major driving force of climate change that directly alters the terrestrial hydrological cycle and ecosystem functions. However, most current Global Climate Models (GCMs) use prescribed chemical concentrations of limited species; they do not explicitly simulate the time-varying concentrations of trace gases and aerosols and their impacts on climate change. This study investigates the individual and combined impacts of climate change and air pollution on water availability and ecosystem productivity over the conterminous US (CONUS). An ecohydrological model is driven by multiple regional climate scenarios with and without taking into account the impacts of air pollutants on the climate system. The results indicate that regional chemistry-climate feedbacks may largely offset the future warming and wetting trends predicted by GCMs without considering air pollution at the CONUS scale. Consequently, the interactions of air pollution and climate change are expected to significantly reduce water availability by the middle of twenty-first century. On the other hand, the combined impact of climate change and air pollution on ecosystem productivity is less pronounced, but there may still be notable declines in eastern and central regions. The results suggest that air pollution could aggravate regional climate change impacts on water shortage. We conclude that air pollution plays an important role in affecting climate and thus ecohydrological processes. Overlooking the impact of air pollution may cause evident overestimation of future water availability and ecosystem productivity.
KeywordsAir pollution Climate change Water availability Ecosystem productivity
This work was supported by the National Science Foundation EaSM program (AGS-1049200) awarded to North Carolina State University, and the Eastern Forest Environmental Threat Assessment Center (EFETAC), USDA Forest Service. The emissions for chemical species that are not available from the RCP emissions in WRF/Chem simulations are taken from the 2008 NEI-derived emissions for 2006 and 2010 provided by the U.S. EPA, Environment Canada, and Mexican Secretariat of the Environment and Natural Resources (Secretaría de Medio Ambiente y Recursos Naturales-SEMARNAT) and National Institute of Ecology (Instituto Nacional de Ecología-INE) as part of the Air Quality Model Evaluation International Initiative (AQMEII). The authors acknowledge use of the WRF-Chem preprocessor tool mozbc provided by the Atmospheric Chemistry Observations and Modeling Lab (ACOM) of NCAR and the script to generate initial and boundary conditions for WRF based on CESM results provided by Ruby Leung, PNNL. The authors acknowledge high-performance computing support for CESM, WRF, and WRF/Chem simulations from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation and Information Systems Laboratory. Some development work, testing, and initial applications of WRF/Chem were performed on the Stampede Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing system, which is supported by the National Science Foundation grant number ACI-1053575.
- Burnash R (1995) The NWS river forecast system-catchment modeling. Computer models of watershed hydrology. Water Resources Publications, Littleton, ColoradoGoogle Scholar
- Duan K et al. (2016b) Divergence of ecosystem services in U.S. National Forests and Grasslands under a changing climate. Sci Rep. doi: 10.1038/srep24441
- Forkel R et al (2015) Analysis of the WRF-Chem contributions to AQMEII phase2 with respect to aerosol radiative feedbacks on meteorology and pollutant distributions. Atmos Environ:630–645Google Scholar
- He J et al. (2015b) CESM/CAM5 improvement and application: comparison and evaluation of updated CB05_GE and MOZART-4 gas-phase mechanisms and associated impacts on global air quality and climate. Geosci Model Dev:3999–4025 doi: 10.5194/gmd-8-3999-2015
- Krinner G et al. (2005) A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Glob Biogeochem Cycles 19. doi: 10.1029/2003GB002199
- Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Wang W, Powers JG (2005) A description of the advanced research WRF version 2. DTIC DocumentGoogle Scholar
- Sun G et al (2011) Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model. J Geophys Res Biogeosci 2005–2012:116Google Scholar
- Tao W-K, Chen J-P, Li Z, Wang C, Zhang C (2012) Impact of aerosols on convective clouds and precipitation. Rev Geophys. doi: 10.1029/2011RG000369
- USGS, USDA (2013) Federal standards and procedures for the national watershed boundary dataset (WBD) http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/water/watersheds/dataset/.
- Wang G, Yu M, Pal JS, Mei R, Bonan GB, Levis S, Thornton PE (2015a) On the development of a coupled regional climate–vegetation model RCM–CLM–CN–DV and its validation in Tropical Africa. Clim Dyn:1–25Google Scholar
- Wang K, Zhang Y, Yahya K, Wu S-Y, Grell G (2015b) Implementation and initial application of new chemistry-aerosol options in WRF/Chem for simulating secondary organic aerosols and aerosol indirect effects for regional air quality. Atmos Environ:716–732Google Scholar
- Zhang Y, Chen Y, Sarwar G, Schere K (2012a) Impact of gas-phase mechanisms on weather research forecasting model with chemistry (WRF/Chem) predictions: mechanism implementation and comparative evaluation. J Geophys Res Atmos 117. doi: 10.1029/2011JD015775
- Zhang Y et al (2012b) Development and initial application of the global-through-urban weather research and forecasting model with chemistry (GU-WRF/Chem). J Geophys Res Atmos 117. doi: 10.1029/2012JD017966