Climate-Induced Tradeoffs in Planning and Operating Costs of a Regional Electricity System.

Electricity grid planners design the system to supply electricity to end-users reliably and affordably. Climate change threatens both objectives through potentially compounding supply- and demand-side climate-induced impacts. Uncertainty surrounds each of these future potential impacts. Given long planning horizons, system planners must weigh investment costs against operational costs under this uncertainty. Here, we developed a comprehensive and coherent integrated modeling framework combining physically based models with cost-minimizing optimization models in the power system. We applied this modeling framework to analyze potential tradeoffs in planning and operating costs in the power grid due to climate change in the Southeast U.S. in 2050. We find that planning decisions that do not account for climate-induced impacts would result in a substantial increase in social costs associated with loss of load. These social costs are a result of under-investment in new capacity and capacity deratings of thermal generators when we included climate change impacts in the operation stage. These results highlight the importance of including climate change effects in the planning process.

Effects of Climate Change on Capacity Expansion Decisions of an Electricity Generation Fleet in the Southeast U.S.

The electric power sector in the United States faces many challenges related to climate change. On the demand side, climate change could shift demand patterns due to increased air temperatures. On the supply side, climate change could lead to deratings of thermal units due to changes in air temperature, water temperature, and water availability. Past studies have typically analyzed these risks separately. Here, we developed an integrated, multimodel framework to analyze how compounding risks of climate-change impacts on demand and supply affect long-term planning decisions in the power system. In the southeast U.S., we found that compounding climate-change impacts could result in a 35% increase in installed capacity by 2050 relative to the reference case. Participation of renewables, particularly solar, in the fleet increased, driven mostly by the expected increase in summertime peak demand. Such capacity requirements would increase investment costs by approximately 31 billion (USD 2015) over the next 30 years, compared to the reference case. These changes in investment decisions align with carbon emission mitigation strategies, highlighting how adaptation and mitigation strategies can converge.

Evaluation of a proposal for reliable low-cost grid power with 100% wind, water, and solar.

A number of analyses, meta-analyses, and assessments, including those performed by the Intergovernmental Panel on Climate Change, the National Oceanic and Atmospheric Administration, the National Renewable Energy Laboratory, and the International Energy Agency, have concluded that deployment of a diverse portfolio of clean energy technologies makes a transition to a low-carbon-emission energy system both more feasible and less costly than other pathways. In contrast, Jacobson et al. [Jacobson MZ, Delucchi MA, Cameron MA, Frew BA (2015) Proc Natl Acad Sci USA 112(49):15060-15065] argue that it is feasible to provide "low-cost solutions to the grid reliability problem with 100% penetration of WWS [wind, water and solar power] across all energy sectors in the continental United States between 2050 and 2055", with only electricity and hydrogen as energy carriers. In this paper, we evaluate that study and find significant shortcomings in the analysis. In particular, we point out that this work used invalid modeling tools, contained modeling errors, and made implausible and inadequately supported assumptions. Policy makers should treat with caution any visions of a rapid, reliable, and low-cost transition to entire energy systems that relies almost exclusively on wind, solar, and hydroelectric power.

The Economic Merits of Flexible Carbon Capture and Sequestration as a Compliance Strategy with the Clean Power Plan.

Carbon capture and sequestration (CCS) may be a key technology for achieving large CO2 emission reductions. Relative to "normal" CCS, "flexible" CCS retrofits include solvent storage that allows the generator to temporarily reduce the CCS parasitic load and increase the generator's net efficiency, capacity, and ramp rate. Due to this flexibility, flexible CCS generators provide system benefits that normal CCS generators do not, which could make flexible CCS an economic CO2 emission reduction strategy. Here, we estimate the system-level cost effectiveness of reducing CO2 emissions with flexible CCS compared to redispatching (i.e., substituting gas- for coal-fired electricity generation), wind, and normal CCS under the Clean Power Plan (CPP) and a hypothetical more stringent CO2 emission reduction target ("stronger CPP"). Using a unit commitment and economic dispatch model, we find flexible CCS achieves more cost-effective emission reductions than normal CCS under both reduction targets, indicating that policies that promote CCS should encourage flexible CCS. However, flexible CCS is less cost effective than wind under both reduction targets and less and more cost effective than redispatching under the CPP and stronger CPP, respectively. Thus, CCS will likely be a minor CPP compliance strategy but may play a larger role under a stronger emission reduction target.

Uncertainty in the Life Cycle Greenhouse Gas Emissions from U.S. Production of Three Biobased Polymer Families.

Interest in biobased products has been motivated, in part, by the claim that these products have lower life cycle greenhouse gas (GHG) emissions than their fossil counterparts. This study investigates GHG emissions from U.S. production of three important biobased polymer families: polylactic acid (PLA), polyhydroxybutyrate (PHB) and bioethylene-based plastics. The model incorporates uncertainty into the life cycle emission estimates using Monte Carlo simulation. Results present a range of scenarios for feedstock choice (corn or switchgrass), treatment of coproducts, data sources, end of life assumptions, and displaced fossil polymer. Switchgrass pathways generally have lower emissions than corn pathways, and can even generate negative cradle-to-gate emissions if unfermented residues are used to coproduce energy. PHB (from either feedstock) is unlikely to have lower emissions than fossil polymers once end of life emissions are included. PLA generally has the lowest emissions when compared to high emission fossil polymers, such as polystyrene (mean GHG savings up to 1.4 kg CO2e/kg corn PLA and 2.9 kg CO2e/kg switchgrass PLA). In contrast, bioethylene is likely to achieve the greater emission reduction for ethylene intensive polymers, like polyethylene (mean GHG savings up to 0.60 kg CO2e/kg corn polyethylene and 3.4 kg CO2e/kg switchgrass polyethylene).

Comparison of life cycle greenhouse gases from natural gas pathways for medium and heavy-duty vehicles.

The low-cost and abundant supply of shale gas in the United States has increased the interest in using natural gas for transportation. We compare the life cycle greenhouse gas (GHG) emissions from different natural gas pathways for medium and heavy-duty vehicles (MHDVs). For Class 8 tractor-trailers and refuse trucks, none of the natural gas pathways provide emissions reductions per unit of freight-distance moved compared to diesel trucks. When compared to the petroleum-based fuels currently used in these vehicles, CNG and centrally produced LNG increase emissions by 0-3% and 2-13%, respectively, for Class 8 trucks. Battery electric vehicles (BEVs) powered with natural gas-produced electricity are the only fuel-technology combination that achieves emission reductions for Class 8 transit buses (31% reduction compared to the petroleum-fueled vehicles). For non-Class 8 trucks (pick-up trucks, parcel delivery trucks, and box trucks), BEVs reduce emissions significantly (31-40%) compared to their diesel or gasoline counterparts. CNG and propane achieve relatively smaller emissions reductions (0-6% and 19%, respectively, compared to the petroleum-based fuels), while other natural gas pathways increase emissions for non-Class 8 MHDVs. While using natural gas to fuel electric vehicles could achieve large emission reductions for medium-duty trucks, the results suggest there are no great opportunities to achieve large emission reductions for Class 8 trucks through natural gas pathways with current technologies. There are strategies to reduce the carbon footprint of using natural gas for MHDVs, ranging from increasing vehicle fuel efficiency, reducing life cycle methane leakage rate, to achieving the same payloads and cargo volumes as conventional diesel trucks.

Emissions and Cost Implications of Controlled Electric Vehicle Charging in the U.S. PJM Interconnection.

We develop a unit commitment and economic dispatch model to estimate the operation costs and the air emissions externality costs attributable to new electric vehicle electricity demand under controlled vs uncontrolled charging schemes. We focus our analysis on the PJM Interconnection and use scenarios that characterize (1) the most recent power plant fleet for which sufficient data are available, (2) a hypothetical 2018 power plant fleet that reflects upcoming plant retirements, and (3) the 2018 fleet with increased wind capacity. We find that controlled electric vehicle charging can reduce associated generation costs by 23%-34% in part by shifting loads to lower-cost, higher-emitting coal plants. This shift results in increased externality costs of health and environmental damages from increased air pollution. On balance, we find that controlled charging of electric vehicles produces negative net social benefits in the recent PJM grid but could have positive net social benefits in a future grid with sufficient coal retirements and wind penetration.

Quantifying the hurricane risk to offshore wind turbines.

The U.S. Department of Energy has estimated that if the United States is to generate 20% of its electricity from wind, over 50 GW will be required from shallow offshore turbines. Hurricanes are a potential risk to these turbines. Turbine tower buckling has been observed in typhoons, but no offshore wind turbines have yet been built in the United States. We present a probabilistic model to estimate the number of turbines that would be destroyed by hurricanes in an offshore wind farm. We apply this model to estimate the risk to offshore wind farms in four representative locations in the Atlantic and Gulf Coastal waters of the United States. In the most vulnerable areas now being actively considered by developers, nearly half the turbines in a farm are likely to be destroyed in a 20-y period. Reasonable mitigation measures--increasing the design reference wind load, ensuring that the nacelle can be turned into rapidly changing winds, and building most wind plants in the areas with lower risk--can greatly enhance the probability that offshore wind can help to meet the United States' electricity needs.

Evaluating the benefits of commercial building energy codes and improving federal incentives for code adoption.

The federal government has the goal of decreasing commercial building energy consumption and pollutant emissions by incentivizing the adoption of commercial building energy codes. Quantitative estimates of code benefits at the state level that can inform the size and allocation of these incentives are not available. We estimate the state-level climate, environmental, and health benefits (i.e., social benefits) and reductions in energy bills (private benefits) of a more stringent code (ASHRAE 90.1-2010) relative to a baseline code (ASHRAE 90.1-2007). We find that reductions in site energy use intensity range from 93 MJ/m(2) of new construction per year (California) to 270 MJ/m(2) of new construction per year (North Dakota). Total annual benefits from more stringent codes total $506 million for all states, where $372 million are from reductions in energy bills, and $134 million are from social benefits. These total benefits range from $0.6 million in Wyoming to $49 million in Texas. Private benefits range from $0.38 per square meter in Washington State to $1.06 per square meter in New Hampshire. Social benefits range from $0.2 per square meter annually in California to $2.5 per square meter in Ohio. Reductions in human/environmental damages and future climate damages account for nearly equal shares of social benefits.

Valuation of plug-in vehicle life-cycle air emissions and oil displacement benefits.

We assess the economic value of life-cycle air emissions and oil consumption from conventional vehicles, hybrid-electric vehicles (HEVs), plug-in hybrid-electric vehicles (PHEVs), and battery electric vehicles in the US. We find that plug-in vehicles may reduce or increase externality costs relative to grid-independent HEVs, depending largely on greenhouse gas and SO(2) emissions produced during vehicle charging and battery manufacturing. However, even if future marginal damages from emissions of battery and electricity production drop dramatically, the damage reduction potential of plug-in vehicles remains small compared to ownership cost. As such, to offer a socially efficient approach to emissions and oil consumption reduction, lifetime cost of plug-in vehicles must be competitive with HEVs. Current subsidies intended to encourage sales of plug-in vehicles with large capacity battery packs exceed our externality estimates considerably, and taxes that optimally correct for externality damages would not close the gap in ownership cost. In contrast, HEVs and PHEVs with small battery packs reduce externality damages at low (or no) additional cost over their lifetime. Although large battery packs allow vehicles to travel longer distances using electricity instead of gasoline, large packs are more expensive, heavier, and more emissions intensive to produce, with lower utilization factors, greater charging infrastructure requirements, and life-cycle implications that are more sensitive to uncertain, time-sensitive, and location-specific factors. To reduce air emission and oil dependency impacts from passenger vehicles, strategies to promote adoption of HEVs and PHEVs with small battery packs offer more social benefits per dollar spent.

Diverse decarbonization pathways under near cost-optimal futures.

Energy system optimization models offer insights into energy and emissions futures through least-cost optimization. However, real-world energy systems often deviate from deterministic scenarios, necessitating rigorous uncertainty exploration in macro-energy system modeling. This study uses modeling techniques to generate diverse near cost-optimal net-zero CO2 pathways for the United States' energy system. Our findings reveal consistent trends across these pathways, including rapid expansion of solar and wind power generation, substantial petroleum use reductions, near elimination of coal combustion, and increased end-use electrification. We also observe varying deployment levels for natural gas, hydrogen, direct air capture of CO2, and synthetic fuels. Notably, carbon-captured coal and synthetic fuels exhibit high adoption rates but only in select decarbonization pathways. By analyzing technology adoption correlations, we uncover interconnected technologies. These results demonstrate that diverse pathways for decarbonization exist at comparable system-level costs and provide insights into technology portfolios that enable near cost-optimal net-zero CO2 futures.

Quantifying the hurricane catastrophe risk to offshore wind power.

The U.S. Department of Energy has estimated that over 50 GW of offshore wind power will be required for the United States to generate 20% of its electricity from wind. Developers are actively planning offshore wind farms along the U.S. Atlantic and Gulf coasts and several leases have been signed for offshore sites. These planned projects are in areas that are sometimes struck by hurricanes. We present a method to estimate the catastrophe risk to offshore wind power using simulated hurricanes. Using this method, we estimate the fraction of offshore wind power simultaneously offline and the cumulative damage in a region. In Texas, the most vulnerable region we studied, 10% of offshore wind power could be offline simultaneously because of hurricane damage with a 100-year return period and 6% could be destroyed in any 10-year period. We also estimate the risks to single wind farms in four representative locations; we find the risks are significant but lower than those estimated in previously published results. Much of the hurricane risk to offshore wind turbines can be mitigated by designing turbines for higher maximum wind speeds, ensuring that turbine nacelles can turn quickly to track the wind direction even when grid power is lost, and building in areas with lower risk.

Implications of near-term coal power plant retirement for SO2 and NOX and life cycle GHG emissions.

Regulations monitoring SO(2), NO(X), mercury, and other metal emissions in the U.S. will likely result in coal plant retirement in the near-term. Life cycle assessment studies have previously estimated the environmental benefits of displacing coal with natural gas for electricity generation, by comparing systems that consist of individual natural gas and coal power plants. However, such system comparisons may not be appropriate to analyze impacts of coal plant retirement in existing power fleets. To meet this limitation, simplified economic dispatch models for PJM, MISO, and ERCOT regions are developed in this study to examine changes in regional power plant dispatch that occur when coal power plants are retired. These models estimate the order in which existing power plants are dispatched to meet electricity demand based on short-run marginal costs, with cheaper plants being dispatched first. Five scenarios of coal plant retirement are considered: retiring top CO(2) emitters, top NO(X) emitters, top SO(2) emitters, small and inefficient plants, and old and inefficient plants. Changes in fuel use, life cycle greenhouse gas emissions (including uncertainty), and SO(2) and NO(X) emissions are estimated. Life cycle GHG emissions were found to decrease by less than 4% in almost all scenarios modeled. In addition, changes in marginal damage costs due to SO(2), and NO(X) emissions are estimated using the county level marginal damage costs reported in the Air Pollution Emissions Experiments and Policy (APEEP) model, which are a proxy for measuring regional impacts of SO(2) and NO(X) emissions. Results suggest that location specific parameters should be considered within environmental policy frameworks targeting coal plant retirement, to account for regional variability in the benefits of reducing the impact of SO(2) and NO(X) emissions.

Potentials for sustainable transportation in cities to alleviate climate change impacts.

Reducing greenhouse gas emissions (GHG) is an important social goal to mitigate climate change. A common mitigation paradigm is to consider strategy "wedges" that can be applied to different activities to achieve desired GHG reductions. In this policy analysis piece, we consider a wide range of possible strategies to reduce light-duty vehicle GHG emissions, including fuel and vehicle options, low carbon and renewable power, travel demand management and land use changes. We conclude that no one strategy will be sufficient to meet GHG emissions reduction goals to avoid climate change. However, many of these changes have positive combinatorial effects, so the best strategy is to pursue combinations of transportation GHG reduction strategies to meet reduction goals. Agencies need to broaden their agendas to incorporate such combination in their planning.

International alliance and AGREE-ment of 71 clinical practice guidelines on the management of critical care patients with COVID-19: a living systematic review.

OBJECTIVE: We aimed to systematically identify and critically assess the clinical practice guidelines (CPGs) for the management of critically ill patients with COVID-19 with the AGREE II instrument. STUDY DESIGN AND SETTING: We searched Medline, CINAHL, EMBASE, CNKI, CBM, WanFang, and grey literature from November 2019 - November 2020. We did not apply language restrictions. One reviewer independently screened the retrieved titles and abstracts, and a second reviewer confirmed the decisions. Full texts were assessed independently and in duplicate. Disagreements were resolved by consensus. We included any guideline that provided recommendations on the management of critically ill patients with COVID-19. Data extraction was performed independently and in duplicate by two reviewers. We descriptively summarized CPGs characteristics. We assessed the quality with the AGREE II instrument and we summarized relevant therapeutic interventions. RESULTS: We retrieved 3,907 records and 71 CPGs were included. Means (Standard Deviations) of the scores for the 6 domains of the AGREE II instrument were 65%(SD19.56%), 39%(SD19.64%), 27%(SD19.48%), 70%(SD15.74%), 26%(SD18.49%), 42%(SD34.91) for the scope and purpose, stakeholder involvement, rigor of development, clarity of presentation, applicability, editorial independence domains, respectively. Most of the CPGs showed a low overall quality (less than 40%). CONCLUSION: Future CPGs for COVID-19 need to rely, for their development, on standard evidence-based methods and tools.

Uncertainty analysis of life cycle greenhouse gas emissions from petroleum-based fuels and impacts on low carbon fuel policies.

The climate change impacts of U.S. petroleum-based fuels consumption have contributed to the development of legislation supporting the introduction of low carbon alternatives, such as biofuels. However, the potential greenhouse gas (GHG) emissions reductions estimated for these policies using life cycle assessment methods are predominantly based on deterministic approaches that do not account for any uncertainty in outcomes. This may lead to unreliable and expensive decision making. In this study, the uncertainty in life cycle GHG emissions associated with petroleum-based fuels consumed in the U.S. is determined using a process-based framework and statistical modeling methods. Probability distributions fitted to available data were used to represent uncertain parameters in the life cycle model. Where data were not readily available, a partial least-squares (PLS) regression model based on existing data was developed. This was used in conjunction with probability mixture models to select appropriate distributions for specific life cycle stages. Finally, a Monte Carlo simulation was performed to generate sample output distributions. As an example of results from using these methods, the uncertainty range in life cycle GHG emissions from gasoline was shown to be 13%-higher than the typical 10% minimum emissions reductions targets specified by low carbon fuel policies.

Uncertainty in life cycle greenhouse gas emissions from United States natural gas end-uses and its effects on policy.

Increasing concerns about greenhouse gas (GHG) emissions in the United States have spurred interest in alternate low carbon fuel sources, such as natural gas. Life cycle assessment (LCA) methods can be used to estimate potential emissions reductions through the use of such fuels. Some recent policies have used the results of LCAs to encourage the use of low carbon fuels to meet future energy demands in the U.S., without, however, acknowledging and addressing the uncertainty and variability prevalent in LCA. Natural gas is a particularly interesting fuel since it can be used to meet various energy demands, for example, as a transportation fuel or in power generation. Estimating the magnitudes and likelihoods of achieving emissions reductions from competing end-uses of natural gas using LCA offers one way to examine optimal strategies of natural gas resource allocation, given that its availability is likely to be limited in the future. In this study, the uncertainty in life cycle GHG emissions of natural gas (domestic and imported) consumed in the U.S. was estimated using probabilistic modeling methods. Monte Carlo simulations are performed to obtain sample distributions representing life cycle GHG emissions from the use of 1 MJ of domestic natural gas and imported LNG. Life cycle GHG emissions per energy unit of average natural gas consumed in the U.S were found to range between -8 and 9% of the mean value of 66 g CO(2)e/MJ. The probabilities of achieving emissions reductions by using natural gas for transportation and power generation, as a substitute for incumbent fuels such as gasoline, diesel, and coal were estimated. The use of natural gas for power generation instead of coal was found to have the highest and most likely emissions reductions (almost a 100% probability of achieving reductions of 60 g CO(2)e/MJ of natural gas used), while there is a 10-35% probability of the emissions from natural gas being higher than the incumbent if it were used as a transportation fuel. This likelihood of an increase in GHG emissions is indicative of the potential failure of a climate policy targeting reductions in GHG emissions.

Air pollution emission effects of changes in transport supply: the case of Bogotá, Colombia.

Transportation policy and planning decisions, including decisions on new infrastructure and public transport improvements, affect local and global environmental conditions. This work studies the effect of increased road capacity on traffic-related emissions in Bogotá using a tool that couples a transportation model with emission factors from COPERT IV. We followed a parametric approach varying transport supply and demand, comparing three scenarios: a baseline scenario that represents the transportation system in Bogota in 2015; scenario 1 incorporates five highway capacity-enhancement projects in Bogotá and assumes insensitive travel demand; scenario 2 incorporates the new highway projects but assumes a demand increase of 13% in vehicle trips with private cars. Results include daily and annual values of traffic-related emissions of five air pollutant criteria: CO, NOx, PM10, SO2, and VOC for the baseline scenario, scenario 1, and scenario 2. We found a reduction in emissions after adding highway capacity and assuming inelastic demand (scenario 1). Scenario 1 results in a 15% reduction in PM10 emissions and a 10% reduction in NOx emissions. In contrast, results for scenario 2 suggest increased emissions for all air pollutant criteria (e.g., VOC and CO emissions increase by 21% and 22% compared with the baseline scenario). Therefore, new traffic demand would eliminate the emission savings observed in scenario 1 and could potentially further degrade air quality in Bogotá. While an exact estimate of induced demand that may result from highway expansion in Bogotá is not available, this analysis highlights that such projects could lead to an increase in emissions unless there is a combined effort to managing demand of private vehicle trips.

Development of a high-resolution traffic emission model: Lessons and key insights from the case of Bogotá, Colombia.

This paper presents a traffic-related air emissions inventory of a developing megacity using a traffic assignment model that results in a detailed temporal and spatial emission representation, disaggregating emissions sources by vehicle type and hour of the day, for five criteria air pollutants.

Biochemical and genotoxic effects in women exposed to pesticides in Southern Ecuador.

Toxicity refers to the potential of a substance such as a pesticide to cause damage to the structure or functions of an exposed organism. Pesticides can lead to harmful biological effects in exposed animals and their offspring over the medium and long term. They can affect the immunological, nervous, endocrine, and reproductive systems. DNA damage has also been linked to exposure to pesticides, and this damage can cause abortions, degenerative diseases, and cancer. The aim of this work was to establish whether women who are indirectly exposed to pesticides exhibit a compromised health status, including genotoxic effect. Women exposed indirectly to pesticides in Chimchanga and Colaisaca in the south of Ecuador underwent hematological and biochemical tests and micronucleus assay in buccal cells. The subjects were also genotyped for GSTM1, GSTT1, GSTP1, and PON1 polymorphisms, which can modify an individual's capacity to metabolize pesticides and relation with damage of DNA. The study revealed hepatic toxicity in Colaisaca women (AST and ALT) and an increase in the rate of micronucleus (MN) in Colaisaca individuals. In addition, genetic polymorphisms in PON1 and GSTP1 showed effects of modulating the frequency of karyolytic cells, karyorrhectic cells, and condensed chromatin cells.