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United States Department of Agriculture

Agricultural Research Service

Research Project: Management of Agricultural and Natural Resource Systems to Reduce Atmospheric Emissions and Increase Resilience to Climate Change Project Number: 5030-11610-001-00
Project Type: Appropriated

Start Date: Jun 03, 2010
End Date: Jun 02, 2015

Objective:
Project objectives are: 1) Measure and model the impact of agricultural systems (animal and cropping) on air quality components to identify and develop potential mitigation strategies, 2) Measure and model the impact of agricultural systems on greenhouse gas emissions and develop and evaluate potential mitigation strategies, 3) Measure and model soil and atmospheric factors limiting water, nitrogen, and light use efficiency of annual and perennial cropping systems to determine how they can become more resilient to climate change and 4) Develop science-based, region-specific information and technologies for agricultural and natural resource managers that enable climate-smart decision-making and where possible provide assistance to enable land managers to implement those decisions. The work will be conducted as the Midwest USDA Climate Change Hub and will be coordinated with NRCS, FS, and other USDA and non-USDA organizations in accordance with guidance found in the USDA Climate Change Hubs Charter, and Terms of Reference.

Approach:
Studies across the soil-plant-atmosphere continuum in this project will develop new methods for quantifying emission and dispersion (particulates, NH3, VOC’s) from animal and cropping systems, improve methods for measuring different compounds in the air to provide increased quantitative capability to measure impacts of CAFO’s on air quality, determine greenhouse gas emissions (N2O, CH4, CO2) from cropping systems, and quantify effects of changing climate on water, light, and nitrogen use by crops. The initial development of a lidar-based approach to measure plume dynamics from animal facilities will be evaluated to produce a remote-sensing approach that will be used to guide sampling methods that use point-based samplers. These data will be collected over a range of facilities and throughout the day to capture the range of atmospheric stability conditions. Air sampling methods for volatile organic compounds will be accomplished with a range of methods from sorbent tubes and canisters. These will also be coupled with methods to measure the volatile organic compounds attached to particulates. These observations will be collected in different livestock facilities. Greenhouse gas emissions will be quantified using soil chambers for a range of soil management and nitrogen management studies to quantify the emissions throughout a year. Measures of water, nitrogen, carbon accumulation, and light use efficiency will use an integrated approach that blends micrometeorological with physiological measurements. These experiments will be conducted using field-scale environments and will integrate all efficiency factors into a combined assessment. The energy balance approach used in these studies blends the fast response of CO2 and H2O vapor signals with sonic anemometers, net radiation components, soil heat flux, and surface temperature along with remote sensing to obtain growth characteristics of the crop. Studies will be conducted in the rhizotron to assess the impact of rapidly induced temperature changes on crop physiological responses under a range of soil water conditions. Accomplishing these three objectives will result in the development of agricultural practices and mitigation strategies that reduce environmental impact, while maintaining or increasing productivity. Mitigation strategies to reduce GHG emissions will balance agricultural production efficiency and increased carbon capture and nitrogen use efficiency. Climate change and its impact on cropping systems raise additional concerns regarding resilience of current production practices and plant adaption to those changes. Methods are needed to quantify plant-climate interaction to link field observations with simulation models for corn, soybean, wheat, and native prairie systems. Developing a long-term program to quantify plant response to climate anomalies will also establish a database for developing more resilient crop production systems. This research will enhance scientific knowledge and provide information for producers and policymakers to maintain the viability of agricultural systems.

Last Modified: 11/28/2014
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