Featured Projects

Establishing a Community Modeling and Analysis System (CMAS) for Models-3

The Institute for the Environment at UNC is the host of the Community Modeling and Analysis System (CMAS) through a cooperative agreement with the U.S. Environmental Protection Agency (EPA). Dr. Adel Hanna, Research professor, is the director of CMAS. CMAS is a technology transfer vehicle of the EPA Models-3 initiative to help regulatory analysts and scientists addressing air pollution problems in order to support environmental decision making. The CMAS is an approach to the development, application, and analysis of environmental models that leverages the community's complementary talents and resources in order to set new standards for quality in science and in the reliability of the application of the models. With the creation of the CMAS center, the Institute has developed a resource to distribute the features of the CMAS to the community. From research to training and application to software development and outreach, the goal of the CMAS center is to advance the community modeling paradigm through the establishment of a centralized resource to serve the members of the air quality modeling community.

Development and Application of a Regional Scale Integrated Meteorology - Atmospheric Chemistry Model

Goals:

• Develop and apply an air quality modeling system with integrated meteorology, emissions, and chemistry which is:
  • internally consistent both numerically and physically
  • computationally efficient
• Reduce uncertainty, redundancy, and inconsistency arising from separation of the three main interrelated components (meteorology, emissions, chemistry)
• Maintain flexibility and modularity to facilitate incorporation of alternate/improved process and numerical representations
• Use the integrated model as a platform to assess feedbacks between meteorology and chemistry - sensitivity study

Design and Implementation of a Real-Time Storm Surge and Flood Forecasting Capability for the State of North Carolina

A new real-time storm surge prediction system has been created for the State of North Carolina to assist emergency managers, policy-makers and other government officials with evacuation planning, decision-making and resource deployment during tropical storm landfall and flood inundation events. Working in collaboration with the Renaissance Computing Institute (RENCI) and the Institute of Marine Sciences (IMS) at UNC, scientists in the Institute for the Environment designed and built the North Carolina Forecast System (NCFS) from high-resolution versions of the ADCIRC (Advanced Circulation) coastal ocean model and the Weather Research & Forecasting (WRF) numerical weather prediction model. A "rapid response" assessment of hurricane threat is accomplished by driving the storm surge model with winds from a synthetic asymmetric gradient wind vortex generated from the National Hurricane Center (NHC) forecast advisories the moment they are inserted into the real-time weather data stream.

Integrated Assessment of the Influences of Emission Sources, Meteorology and Atmospheric Chemistry on Aerosol Loadings over South Asia: Implications for Regional Climate

There are growing trends to limit the anthropogenic emissions of greenhouse gases (e.g., CO2, methane), primary aerosols (e.g., soot, sulfate), and secondary aerosol precursor gases (e.g., SO2) in industrialized, and increasingly, in developing regions of the globe, to mitigate the potential adverse impacts of these substances on climate due to their perturbation of the atmospheric radiation budget. Emissions from Asian countries, in particular, are estimated to dominate the atmospheric loadings of these pollutants over the next 25 years due to the growing economies and the limited resources available for environmental protection in these countries. Measurements from the Indian Ocean Experiment (INDOEX) of 1999 have provided strong evidence that the continental emissions from South Asia may already be modifying climate patterns in the region. The proposed research thus seeks to use an integrated modeling approach to understand the relative contributions of natural and anthropogenic sources as well as the different source sectors in this region, to the observed aerosol loadings in the remote Indian Ocean, and their regional climate impacts, by examining the influences of meteorology, long-range transport, and atmospheric chemistry on these loadings. The unique signature of the atmospheric composition over this region (high carbon-to-sulfate ratios, low ozone) and the combination of industrial and widespread biofuel emission sources necessitate the use of regional- rather than global-scale models, and well-resolved emissions data for these studies.

The project team members' recent development of (1) a comprehensive, spatially resolved (0.25°x0.25°) emissions inventory of SO2, fine particulate matter (PM), and its constituents (black carbon [BC], organic carbon [OC], and inorganic fraction) for all of India, and (2) a fully coupled mesoscale meteorology and chemistry-transport model, METCHEM, for PM, trace gases, and their radiative effects, provides an effective approach to study these issues. The project will apply METCHEM over South Asia to examine the trends in observations from INDOEX for January-March 1999, and will use various sensitivity studies to understand the coupling between regional circulation patterns and aerosol and trace gas budgets and their radiative forcing. The research will examine the effects of natural vs. anthropogenic aerosols on the Indian monsoon pattern, the relative roles of biomass burning and fossil fuel combustion on the observed BC loadings, and the export of aerosol from various source sectors to the measurement sites under different circulations during the summer and winter monsoon. These studies can help resolve discrepancies noted in INDOEX literature between observational trends and the inventory data regarding the OC/BC ratio, and provide insights into the low observed ozone. Studies of alternative emission scenarios for a future year will also be conducted, accounting for regional economic development, to examine the effects on regional environmental problems of, for example, proposed alternative fuel use and automotive technologies. Findings from these future-year studies will be useful in formulating strategies to mitigate the adverse impacts of air pollution not only in South Asia, but in regions around the globe where similar development is happening or envisioned.

Collaborative Research: Evaluation of a Coupled Meteorology-Chemistry Model against Long-term Measurements of Elemental Carbon and Sulfate for Regional Climate Applications

This is a collaborative research proposal between the State University of New York (SUNY) and the Center for Environmental Modeling for Policy Development (CEMPD) at the University of North CarolinaInstitute for the Environment. Its primary objectives are to: (1) determine the elemental carbon concentrations, {EC}, in archived filters collected at Mayville, and ~530 km downwind at Whiteface Mt, NY, for a summer and a winter month in two different years; and (2) to use these data to evaluate a coupled meteorology-chemistry model developed by CEP researchers for the chemistry and transport of particulates, ozone and their precursors, and their radiative feedbacks to the atmospheric dynamics. The project is motivated by the fact that particulate black carbon (BC), which is treated equivalent to EC in the measurements, is a strong absorber of solar radiation, and thought to account for ~15-30% of global warming estimates, next only to greenhouse gases; however, the magnitude of this forcing on climate is highly uncertain. With a mean atmospheric residence time of about a week,, aerosol BC can travel thousands of kilometers before removal from the atmosphere; thus its measured concentrations are highly dependent on the distance from emission sources. Reliable estimation of the radiative impacts in the U.S. from nearby and remote sources of BC depends critically on obtaining region¬ally representative measurements. Atmospheric chemistry models driven by realistic emissions and meteorological inputs are often used to fill information gaps due to the spatial sparseness of such measurements; to improve the reliability of these models, they must in turn be evaluated against field observations. While intensive field campaigns provide temporally dense data for this purpose, they typically lack seasonality due to their short duration, and may not be regionally representative. Long-term, regionally representative observations are critical to the evaluation of such models under different meteorological conditions, to understand the seasonal and regional biases in their predictions, and reduce uncertainties in their climate forcing estimates for BC, and other radiatively important pollutants such as SO4 and O3. BC is particularly useful for evaluating predicted aerosol spatial distributions, and radiative impacts. Being chemically inert, it is a good tracer to examine the effects of meteorology on atmospheric loadings; and has strong radiative characteristics.

The project thus seeks to determine the {EC} in filters using the thermal-optical method collected every 6 h during summer and every 48 h during the winter of 1998 and 2002 at Whiteface Mt, and every 24 h at Mayville for the same years. In addition, {SO4} have already been determined, and real-time measurements of ozone are available for both the sites for the duration. Prior studies have shown EC and SO4 measurements from these two sites to be regionally representative and highly correlated with known import of upwind airmasses. The measurements will be used to evaluate METCHEM, a model that dynamically couples the mesoscale meteorology of the Fifth Generation Penn State/NCAR Mesoscale Model (MM5) with algorithms for particulates and gas-phase species chemistry and transport simulated by the Multiscale Air Quality Simulation Platform (MAQSIP), to simulate their radiative feedbacks to the atmospheric dynamics. Evaluation of such models is critical to improving our understanding of the regional climate forcing exerted by radiatively important atmospheric pollutants. Nested continental- to-regional-to-local-scale simulations over the observational sites will allow us to examine the effects of long-range transport and grid refinement on the model predictions. The model sensitivity to emissions growth and control, and to successive improvements in the representation of sources such as wild fires and wind-blown dust will be examined using three different emission inventories in the input data.

The proposed project will build upon, and considerably augment current NSF-funded measurement and modeling projects being performed by both participating organizations, and will help evaluate a model used to predict the downwind burden and climate impacts of EC and other emissions from fossil fuel consumption. The evaluated model and the spatially and temporally rich datasets it generates will provide valuable tools in illuminating the impacts of these emissions on climate.