Impact of Clear Air Act Regulations on Nitrogen Fate and Transport in the Neuse River Basin

2012 S.C. Water Resources Conference - Exploring Opportunities for Collaborative Water Research, Policy and Managemen

Projections of Atmospheric Nitrogen Deposition to the Chesapeake Bay Watershed

Atmospheric deposition is among the largest pathways of nitrogen loading to the Chesapeake Bay Watershed (CBW). The interplay between future climate and emission changes in and around the CBW will likely shift the future nutrient deposition abundance and chemical regime (e.g., oxidized vs. reduced nitrogen). In this work, a Representative Concentration Pathway from the Community Earth System Model is dynamically downscaled using a recently updated Weather Research and Forecasting model that subsequently drives the Community Multiscale Air Quality model coupled to the agroeconomic Environmental Policy Integrated Climate model. The relative impacts of emission and climate changes on atmospheric nutrient deposition are explored for a recent historical period and a period centered on 2050. The projected regional emissions in Community Multiscale Air Quality reflect current federal and state regulations, which use baseline and projected emission years 2011 and 2040, respectively. The historical simulations of 2-m temperature (T2) and precipitation (PRECIP) have cool and dry biases, and temperature and PRECIP are projected to both increase. Ammonium wet deposition agrees well with observations, but nitrate wet deposition is underpredicted. Climate and deposition changes increase simulated future ammonium fertilizer application. In the CBW by 2050, these changes (along with widespread decreases in anthropogenic nitrogen oxide and sulfur oxide emissions, and relatively constant ammonia emissions) decrease total nitrogen deposition by 21%, decrease annual average oxidized nitrogen deposition by 44%, and increase reduced nitrogen deposition by 10%. These results emphasize the importance of decreased anthropogenic emissions on the control of future nitrogen loading to the Chesapeake Bay in a changing climate

The assessment of climatological impacts on agricultural production and residential energy demand /

Two user groups of major economic importance were selected for study; agriculture and gas utilities. The broad agricultural sector is further defined as U.S.A. corn production. The general category of utilities is narrowed to Oklahoma residential gas heating demand.The CERES physiological growth model was selected as the process model for corn production. The statistical analysis for corn production suggests that (1) although this is a statistically complex model, it can yield useful impact information, (2) as a result of output distributional biases, traditional statistical techniques are not adequate analytical tools, (3) the model yield distribution as a whole is probably non-Gausian, particularly in the tails and (4) there appears to be identifiable weekly patterns of forecasted yields throughout the growing season. Agricultural quantities developed include point yield impact estimates and distributional characteristics, geographic corn weather distributions, return period estimates, decision making criteria (confidence limits) and time series of indices. These products were communicated in economic terms through the use of a Bayesian decision example and an econometric model.The NBSLD energy load model was selected to represent residential gas heating consumption. A cursory statistical analysis suggests relationships among weather variables across the Oklahoma study sites. No linear trend in "technology-free" modeled energy demand or input weather variables which would correspond to that contained in observed state-level residential energy use was detected. It is suggested that this trend is largely the result of non-weather factors such as population and home usage patterns rather than regional climate change. Year-to-year changes in modeled residential heating demand on the order of 10('6) Btu's per household were determined and later related to state-level components of the Oklahoma economy. Products developed include the definition of regional forecast areas, likelihood estimates of extreme seasonal conditions and an energy/climate index. This information is communicated in economic terms through an input/output model which is used to estimate changes in Gross State Product and Household income attributable to weather variability.The assessment of climatological impacts on selected economic activities is presented as a multi-step, inter-disciplinary problem. The assessment process which is addressed explicitly in this report focuses on (1) user identification, (2) direct impact model selection, (3) methodological development, (4) product development and (5) product communication

A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA

Vegetative leaf area is a critical input to models that simulate human and ecosystem exposure to atmospheric pollutants. Leaf area index (LAI) can be measured in the field or numerically simulated, but all contain some inherent uncertainty that is passed to the exposure assessments that use them. LAI estimates for minimally managed or natural forest stands can be particularly difficult to develop as a result of interspecies competition, age and spatial distribution. Satellite-based LAI estimates hold promise for retrospective analyses, but we must continue to rely on numerical models for alternative management analysis. Our objective for this study is to calculate and validate LAI estimates generated from the USDA Environmental Policy Impact Climate (EPIC) model (a widely used, field-scale, biogeochemical model) on four forest complexes spanning three physiographic provinces in Virginia and North Carolina. Measurements of forest composition (species and number), LAI, tree diameter, basal area, and canopy height were recorded at each site during the 2002 field season. Calibrated EPIC results show stand-level temporally resolved LAI estimates with R2 values ranging from 0.69 to 0.96, and stand maximum height estimates within 20% of observation. This relatively high level of performance is attributable to EPIC’s approach to the characterization of forest stand biogeochemical budgets, stand history, interspecies competition and species-specific response to local weather conditions. We close by illustrating the extension of this site-level approach to scales that could support regional air quality model simulations

Comparison of EPIC-Simulated and MODIS-Derived Leaf Area Index (LAI) across Multiple Spatial Scales

Modeled leaf area index (LAI) in conjunction with satellite-derived LAI data streams may be used to support various regional and local scale air quality models for retrospective and future meteorological assessments. The Environmental Policy Integrated Climate (EPIC) model holds promise for providing LAI within a dynamic range for input into climate and air quality models, improving on current LAI distribution assumptions typical within atmospheric modeling. To assess the potential use of EPIC LAI, we first evaluated the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product collections 5 and 6 (i.e., Mc5, Mc6) with in situ LAI estimates upscaled at four 1.0 km resolution research sites distributed over the Albemarle-Pamlico Basin in North Carolina and Virginia, USA. We then compared the EPIC modeled 12.0 km resolution LAI to aggregated MODIS LAI (Mc5, Mc6) over a 3 × 3 grid (or 36 km × 36 km) centered over the same four research sites. Upscaled in situ LAI comparison with MODIS LAI showed improvement with the newer collection where the Mc5 overestimate of +2.22 LAI was reduced to +0.97 LAI with the Mc6. On three of the four sites, the EPIC/MODIS LAI comparison at 12.0 km resolution grid showed similar weighted mean LAI differences (LAI 1.29–1.34), with both Mc5 and Mc6 exceeding EPIC LAI across most dates. For all four research sites, both MODIS collections showed a positive bias when compared to EPIC LAI, with Mc6 (LAI = 0.40) aligning closer to EPIC than the Mc5 (LAI = 0.61) counterpart. Despite modest differences between both MODIS collections and EPIC LAI, the overestimation trend suggests the potential for EPIC to be used for future meteorological alternative management applications on a regional or national scale

Alternative futures of dissolved inorganic nitrogen export from the Mississippi River Basin: influence of crop management, atmospheric deposition, and population growth

Nitrogen (N) export from the Mississippi River Basin contributes to seasonal hypoxia in the Gulf of Mexico (GOM). We explored monthly dissolved inorganic N (DIN) export to the GOM for a historical year (2002) and two future scenarios (year 2022) by linking macroeonomic energy, agriculture market, air quality, and agriculture land management models to a DIN export model. Future scenarios considered policies aimed at encouraging bioenergy crop production and reducing atmospheric N-emissions, as well as the effect of population growth and the states’ infrastructure plans on sewage fluxes. Model-derived DIN export decreased by about 9% (from 279 to 254 kg N km−2year−1) between 2002 and 2022 due to a 28% increase in area planted with corn, 24% improvement in crop N-recovery efficiency (NRE, to 0.52), 22% reduction in atmospheric N deposition, and 23% increase in sewage inputs. Changes in atmospheric and sewage inputs had a relatively small effect on DIN export and the effect of bioenergy crop production depended on nutrient management practices. Without improved NRE, increased production of corn would have increased DIN export by about 14% (to 289 kg N km−2year−1) between 2002 and 2022. Model results suggest that meeting future crop demand while reducing the areal extent of hypoxia could require aggressive actions, such improving basin-level crop NRE to 0.62 or upgrading N-removal capabilities in waste water treatment plants beyond current plans. Tile-drained cropland could contribute up to half of DIN export; thus, practices that reduce N losses from tile drains could also have substantial benefit