scholarly journals Decomposing supply-side and demand-side impacts of climate change on the US electricity system through 2050

2020 ◽  
Vol 158 (2) ◽  
pp. 125-139 ◽  
Author(s):  
Daniel C. Steinberg ◽  
Bryan K. Mignone ◽  
Jordan Macknick ◽  
Yinong Sun ◽  
Kelly Eurek ◽  
...  

AbstractClimate change may affect the US electricity system through changes in electricity demand, mediated by increases in average surface temperature, and through changes in electricity supply, mediated by changes in both surface temperature and regional water availability. By coupling projections from four general circulation models (GCMs) with a state-of-the-art US electricity system model—the Regional Energy Deployment System (ReEDS)—this study evaluates both the isolated and combined effects of different climate-mediated drivers of US electricity system change through 2050. Comparing results across climate models allows us to evaluate which effects are robust to uncertainty in projected climate outcomes. Comparing effects of different drivers in isolation and in combination allows us to determine the relative contributions of the climate-mediated effects on system evolution. Our results indicate that national-level energy and economic impacts are largely driven by increases in electricity demand that follow from a consistent increase in surface air temperature that is largely robust to the choice of climate model. Other electricity system changes can be equally or more significant in some regions, but these effects are more regionally variable, less significant when aggregated to the national scale, and less robust to the choice of climate model. The findings show that the impacts of climate change on the electricity system can be understood in terms of fewer drivers and with greater certainty at the national level than at the regional level.

2020 ◽  
Vol 163 (2) ◽  
pp. 1107-1108
Author(s):  
Daniel C. Steinberg ◽  
Bryan K. Mignone ◽  
Jordan Macknick ◽  
Yinong Sun ◽  
Kelly Eurek ◽  
...  

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.


2020 ◽  
Vol 20 (8) ◽  
pp. 2133-2155
Author(s):  
Aynalem T. Tsegaw ◽  
Marie Pontoppidan ◽  
Erle Kristvik ◽  
Knut Alfredsen ◽  
Tone M. Muthanna

Abstract. Climate change is one of the greatest threats currently facing the world's environment. In Norway, a change in climate will strongly affect the pattern, frequency, and magnitudes of stream flows. However, it is challenging to quantify to what extent the change will affect the flow patterns and floods from small rural catchments due to the unavailability or inadequacy of hydro-meteorological data for the calibration of hydrological models and due to the tailoring of methods to a small-scale level. To provide meaningful climate impact studies at the level of small catchments, it is therefore beneficial to use high-spatial- and high-temporal-resolution climate projections as input to a high-resolution hydrological model. In this study, we used such a model chain to assess the impacts of climate change on the flow patterns and frequency of floods in small ungauged rural catchments in western Norway. We used a new high-resolution regional climate projection, with improved performance regarding the precipitation distribution, and a regionalized hydrological model (distance distribution dynamics) between a reference period (1981–2011) and a future period (2070–2100). The flow-duration curves for all study catchments show more wet periods in the future than during the reference period. The results also show that in the future period, the mean annual flow increases by 16 % to 33 %. The mean annual maximum floods increase by 29 % to 38 %, and floods of 2- to 200-year return periods increase by 16 % to 43 %. The results are based on the RCP8.5 scenario from a single climate model simulation tailored to the Bergen region in western Norway, and the results should be interpreted in this context. The results should therefore be seen in consideration of other scenarios for the region to address the uncertainty. Nevertheless, the study increases our knowledge and understanding of the hydrological impacts of climate change on small catchments in the Bergen area in the western part of Norway.


2012 ◽  
Vol 12 (12) ◽  
pp. 5367-5390 ◽  
Author(s):  
J. Kelly ◽  
P. A. Makar ◽  
D. A. Plummer

Abstract. Ten year simulations of North American current and future air-quality were carried out using a regional air-quality model driven by a regional climate model, in turn driven by a general circulation model. Three separate summer scenarios were performed: a scenario representing the years 1997 to 2006, and two SRES A2 climate scenarios for the years 2041 to 2050. The first future climate scenario makes use of 2002 anthropogenic precursor emissions, and the second applied emissions scaling factors derived from the IPCC Representative Concentration Pathway 6 (RCP 6) scenario to estimate emissions for 2050 from existing 2020 projections. Ten-year averages of ozone and PM2.5 at North American monitoring network stations were used to evaluate the model's current chemical climatology. The model was found to have a similar performance for ozone as when driven by an operational weather forecast model. The PM2.5 predictions had larger negative biases, likely resulting from the absence of rainwater evaporation, and from sub-regional negative biases in the surface temperature fields, in the version of the climate model used here. The differences between the two future climate simulations and the current climate simulation were used to predict the changes to air-quality that might be expected in a future warmer climate, if anthropogenic precursor emissions remain constant at their current levels, versus if the RCP 6 emissions controls were adopted. Metrics of concentration, human health, and ecosystem damage were compared for the simulations. The scenario with future climate and current anthropogenic emissions resulted in worse air-quality than for current conditions – that is, the effect of climate-change alone, all other factors being similar, would be a worsening of air-quality. These effects are spatially inhomogeneous, with the magnitude and sign of the changes varying with region. The scenario with future climate and RCP 6 emissions for 2050 resulted in an improved air-quality, with decreases in key pollutant concentrations, in acute human mortality associated with air-pollution, and in sulphur and ozone deposition to the ecosystem. The positive outcomes of the RCP 6 emissions reductions were found to be of greater magnitude than the negative outcomes of climate change alone. The RCP 6 scenario however resulted in an increase in the deposition of nitrogen, as a result of increased ammonia emissions expected in that scenario, compared to current ammonia emissions levels. The results of the study raise the possibility that simultaneous reductions of greenhouse gases and air pollution precursors may further reduce air pollution levels, with the added benefits of an immediate reduction in the impacts of air pollution on human and ecosystem health. Further scenarios to investigate this possibility are therefore recommended.


2013 ◽  
Vol 6 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
M. Trail ◽  
A. P. Tsimpidi ◽  
P. Liu ◽  
K. Tsigaridis ◽  
Y. Hu ◽  
...  

Abstract. Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF) model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM) to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.


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