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Zhou, Yuyu,Clarke, Leon,Eom, Jiyong,Kyle, Page,Patel, Pralit,Kim, Son H.,Dirks, James,Jensen, Erik,Liu, Ying,Rice, Jennie,Schmidt, Laurel,Seiple, Timothy Elsevier 2014 APPLIED ENERGY Vol.113 No.-
<P><B>Abstract</B></P> <P><B>Objective</B></P> <P>Because long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate change impact on buildings energy use at the sub-national level will offer useful insights into climate policy and regional energy system planning.</P> <P><B>Methods</B></P> <P>In this study, we present a detailed buildings energy model with U.S. state-level representation, nested in an integrated assessment framework of the Global Change Assessment Model (GCAM). We project state-level buildings energy demand and its spatial pattern through the end of the century, considering the impact of climate change based on the estimates of heating and cooling degree days derived from downscaled USGS CASCaDE temperature data.</P> <P><B>Results</B></P> <P>The results indicate that climate change has a large impact on heating and cooling buildings energy and fuel use at the state level and that the 48 U.S. contiguous states exhibit a large spatial heterogeneity (ranges from −10% to+10% for total, −10% to+20% for electricity use and −20% to −5% for oil and gas use in the A2 scenario). Sensitivity analysis explores the potential implications of multiple driving forces, including climate action that would both change the price of energy and reduce climate change, the choice of climate models, and population and GDP growth. In addition, the 50-state building model is compared to a comparable version of the model which represents the entire United States as one region.</P> <P><B>Conclusions</B></P> <P>The study clearly demonstrates the spatially varying nature of fuel consumption changes that might occur from a changing climate. Although the study illustrates the importance of incorporating climate change into infrastructure-planning exercises, it also demonstrates that uncertainties about underlying drivers still must weigh heavily on these planning decisions. Finally, the study demonstrates that the 50-state building model provides both insights at the regional level and potentially better national-level estimates.</P> <P><B>Practice implication</B></P> <P>The findings from this study will help the climate-based policy decision and energy system, especially utility planning related to the buildings sector at the U.S. state and regional level facing the potential climate change.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Climate change has spatially heterogeneous impact on heating and cooling energy and fuel uses in building sector. </LI> <LI> Building energy and fuel uses are sensitive to other factors such as climate policy as well as climate change. </LI> <LI> The 50-state building model provides both insights at the regional level and potentially better national-level estimates. </LI> <LI> Climate change impact on building electricity use is critical, and needs to be incorporated in infrastructure planning. </LI> </UL> </P>
Soil Profile Measurement of Carbon Contents using a Probe-type VIS-NIR Spectrophotometer
Kweon, Gi-Young,Lund, Eric,Maxton, Chase,Drummond, Paul,Jensen, Kyle Korean Society for Agricultural Machinery 2009 바이오시스템공학 Vol.34 No.5
An in-situ probe-based spectrophotometer has been developed. This system used two spectrometers to measure soil reflectance spectra from 450 nm to 2200 nm. It collects soil electrical conductivity (EC) and insertion force measurements in addition to the optical data. Six fields in Kansas were mapped with the VIS-NIR (visible-near infrared) probe module and sampled for calibration and validation. Results showed that VIS-NIR correlated well with carbon in all six fields, with RPD (the ratio of standard deviation to root mean square error of prediction) of 1.8 or better, RMSE of 0.14 to 0.22%, and $R^2$ of 0.69 to 0.89. From the investigation of carbon variability within the soil profile and by tillage practice, the 0-5 cm depth in a no-till field contained significantly higher levels of carbon than any other locations. Using the selected calibration model with the soil NIR probe data, a soil profile map of estimated carbon was produced, and it was found that estimated carbon values are highly correlated to the lab values. The array of sensors (VIS-NIR, electrical conductivity, insertion force) used in the probe allowed estimating bulk density, and three of the six fields were satisfactory. The VIS-NIR probe also showed the obtained spectra data were well correlated with nitrogen for all fields with RPD scores of 1.84 or better and coefficient of determination ($R^2$) of 0.7 or higher.