Water demand for electricity in deep decarbonisation scenarios: a multi-model assessment

This study assesses the effects of deep electricity decarbonisation and shifts in the choice of power plant cooling technologies on global electricity water demand, using a suite of five integrated assessment models. We find that electricity sector decarbonisation results in co-benefits for water resources primarily due to the phase-out of water-intensive coal-based thermoelectric power generation, although these co-benefits vary substantially across decarbonisation scenarios. Wind and solar photovoltaic power represent a win-win option for both climate and water resources, but further expansion of nuclear or fossil- and biomass-fuelled power plants with carbon capture and storage may result in increased pressures on the water environment. Further to these results, the paper provides insights on the most crucial factors of uncertainty with regards to future estimates of water demand. These estimates varied substantially across models in scenarios where the effects of decarbonisation on the electricity mix were less clear-cut. Future thermal and water efficiency improvements of power generation technologies and demand-side energy efficiency improvements were also identified to be important factors of uncertainty. We conclude that in order to ensure positive effects of decarbonisation on water resources, climate policy should be combined with technology-specific energy and/or water policies.     

A wedge-based approach to estimating health co-benefits of climate change mitigation activities in the United States

While it has been recognized that actions reducing greenhouse gas (GHG) emissions can have significant positive and negative impacts on human health through reductions in ambient fine particulate matter (PM_2.5) concentrations, these impacts are rarely taken into account when analyzing specific policies. This study presents a new framework for estimating the change in health outcomes resulting from implementation of specific carbon dioxide (CO₂) reduction activities, allowing comparison of different sectors and options for climate mitigation activities. Our estimates suggest that in the year 2020, the reductions in adverse health outcomes from lessened exposure to PM_2.5 would yield economic benefits in the range of $6 to $30 billion (in 2008 USD), depending on the specific activity. This equates to between $40 and $198 per metric ton of CO₂ in health benefits. Specific climate interventions will vary in the health co-benefits they provide as well as in potential harms that may result from their implementation. Rigorous assessment of these health impacts is essential for guiding policy decisions as efforts to reduce GHG emissions increase in scope and intensity.     

Financing REDD in developing countries: a supply and demand analysis

Reducing emissions from deforestation and forest degradation (REDD) in developing countries has been at the centre of negotiations on a renewed international climate regime. Developing countries have made it clear that their ability to engage in REDD activities would depend on obtaining sufficient and stable funding. Two alternative REDD financing options are examined to find possible ways forward: financing through a future compliance market and financing through a non-offset fund. First, global demand for hypothetical REDD credits is estimated. The demand for REDD credits would be highest with a base year of 1990, using gross—net accounting. The key factors determining demand in this scenario are the emission reduction targets and the allowable cap. A proportion of emission reduction targets available for offsets lower than 15% would fail to generate a sufficient demand for REDD. Also examined is the option of financing REDD through a fund. Indirectly linking the replenishment of a REDD fund to the market is a promising mechanism, but its feasibility depends on political will. The example of overseas development assistance for global health indicates the conditions for possible REDD financing. The best financial approach for REDD would be a flexible REDD mechanism with two tracks: a market track serving as a mitigation option for developed countries, and a fund track serving as a mitigation option for developing countries.     

The measurement of natural sulfur emissions from soils and vegetation: Three sites in the Eastern United States revisited

Sulfur fluxes from bare soils, naturally vegetated surfaces and from several agricultural crops were measured at two mid-continent sites (Ames, Iowa and Celeryville, Ohio) and from one salt water marsh site (Cedar Island, North Carolina) during a field program conducted jointly by the NOAA Aeronomy Laboratory, Washington State University Laboratory for Atmospheric Research and University of Idaho Department of Chemistry during July and August 1985. The sites were chosen specifically because they had been characterized by previous studies (Anejaet al., 1979; Adamset al., 1980, 1981). The NOAA gas chromatographic/dynamic-enclosure measurements yielded bare soil surfaces fluxes from the mid-continent sites composed predominantly of COS, H₂S, CH₃–S–CH₃ (DMS) and CS₂, all of which were strongly correlated with air temperature. Net fluxes of approximately 5 and 15 ng S/m² min were observed in Iowa and Ohio, respectively, at appropriate weighted mean July temperatures. These fluxes are roughly a factor of 10 smaller than the earlier measurements, the greatest difference being in the measurement of the H₂S flux. The presence of growing vegetation was observed to measurably increase the flux of H₂S, significantly increase that of DMS and to decrease that of COS. Sulfur fluxes in the Cedar Island environs were observed to be both spatially and temporally much more variable and to include CH₃SH as a measurable contributor. Net fluxes, composed predominantly of DMS and H₂S, were estimated to be about 300 ngS/m²min during August; again about a factor of 10 lower than previous estimates. All measurements were corroborated to within about a factor of 2 by those of the other participating laboratories.     

Climate Change Impacts on the Potential Productivity of Corn and Winter Wheat in Their Primary United States Growing Regions

We calculate the impacts of climate effects inferred from three atmospheric general circulation models (GCMs) at three levels of climate change severity associated with change in global mean temperature (GMT) of 1.0, 2.5 and 5.0 °C and three levels of atmospheric CO2 concentration ([CO2]) – 365 (no CO2 fertilization effect), 560 and 750 ppm – on the potential production of dryland winter wheat (Triticum aestivum L.) and corn (Zea mays L.) for the primary (current) U.S. growing regions of each crop. This analysis is a subset of the Global Change Assessment Model (GCAM) which has the goal of integrating the linkages and feedbacks among human activities and resulting greenhouse gas emissions, changes in atmospheric composition and resulting climate change, and impacts on terrestrial systems. A set of representative farms was designed for each of the primary production regions studied and the Erosion Productivity Impact Calculator (EPIC) was used to simulate crop response to climate change. The GCMs applied were the Goddard Institute of Space Studies (GISS), the United Kingdom Meteorological Transient (UKTR) and the Australian Bureau of Meteorological Research Center (BMRC), each regionalized by means of a scenario generator (SCENGEN). The GISS scenarios have the least impact on corn and wheat production, reducing national potential production for corn by 6% and wheat by 7% at a GMT of 2.5 °C and no CO2 fertilization effect; the UKTR scenario had the most severe impact on wheat, reducing production by 18% under the same conditions; BMRC had the greatest negative impact on corn, reducing production by 20%. A GMT increase of 1.0°C marginally decreased corn and wheat production. Increasing GMT had a detrimental impact on both corn and wheat production, with wheat production suffering the greatest losses. Decreases for wheat production at GMT 5.0 and [CO2] = 365 ppm range from 36% for the GISS to 76% for the UKTR scenario. Increases in atmospheric [CO2] had a positive impact on both corn and wheat production. AT GMT 1.0, an increase in [CO2] to 560 ppm resulted in a net increase in corn and wheat production above baseline levels (from 18 to 29% for wheat and 2 to 5% for corn). Increases in [CO2] help to offset yield reductions at higher GMT levels; in most cases, however, these increases are not sufficient to return crop production to baseline levels.     

Impacts of different diffusion scenarios for mitigation technology options and of model representations regarding renewables intermittency on evaluations of CO2 emissions reductions

This paper evaluated the impacts of climate change mitigation technology options on CO₂ emission reductions and the effects of model representations regarding renewable intermittency on the assessment of reduction by using a world energy systems model. First, different diffusion scenarios for carbon dioxide capture and storage (CCS), nuclear power, and wind power and solar PV are selected from EMF27 scenarios to analyze their impacts on CO₂ emission reductions. These technologies are important for reducing CO₂ intensity of electricity, and the impacts of their diffusion levels on mitigation costs are significant, according to the analyses. Availability of CCS in particular, among the three kinds of technologies, has a large impact on the marginal CO₂ abatement cost. In order to analyze effects of model representations regarding renewables intermittency, four different representations are assumed within the model. A simplistic model representation that does not take into consideration the intermittency of wind power and solar PV evaluates larger contributions of the energy sources than those evaluated by a model representation that takes intermittency into consideration. Appropriate consideration of renewables intermittency within global energy systems models will be important for realistic evaluations of climate change mitigation scenarios.     

Climate change beliefs, concerns, and attitudes toward adaptation and mitigation among farmers in the Midwestern United States

A February 2012 survey of almost 5,000 farmers across a region of the U.S. that produces more than half of the nation’s corn and soybean revealed that 66 % of farmers believed climate change is occurring (8 % mostly anthropogenic, 33 % equally human and natural, 25 % mostly natural), while 31 % were uncertain and 3.5 % did not believe that climate change is occurring. Results of initial analyses indicate that farmers’ beliefs about climate change and its causes vary considerably, and the relationships between those beliefs, concern about the potential impacts of climate change, and attitudes toward adaptive and mitigative action differ in systematic ways. Farmers who believed that climate change is occurring and attributable to human activity were significantly more likely to express concern about impacts and support adaptive and mitigative action. On the other hand, farmers who attributed climate change to natural causes, were uncertain about whether it is occurring, or did not believe that it is occurring were less concerned, less supportive of adaptation, and much less likely to support government and individual mitigative action. Results suggest that outreach with farmers should account for these covariances in belief, concerns, and attitudes toward adaptation and mitigation.     

Climate model errors, feedbacks and forcings: a comparison of perturbed physics and multi-model ensembles

Ensembles of climate model simulations are required for input into probabilistic assessments of the risk of future climate change in which uncertainties are quantified. Here we document and compare aspects of climate model ensembles from the multi-model archive and from perturbed physics ensembles generated using the third version of the Hadley Centre climate model (HadCM3). Model-error characteristics derived from time-averaged two-dimensional fields of observed climate variables indicate that the perturbed physics approach is capable of sampling a relatively wide range of different mean climate states, consistent with simple estimates of observational uncertainty and comparable to the range of mean states sampled by the multi-model ensemble. The perturbed physics approach is also capable of sampling a relatively wide range of climate forcings and climate feedbacks under enhanced levels of greenhouse gases, again comparable with the multi-model ensemble. By examining correlations between global time-averaged measures of model error and global measures of climate change feedback strengths, we conclude that there are no simple emergent relationships between climate model errors and the magnitude of future global temperature change. Algorithms for quantifying uncertainty require the use of complex multivariate metrics for constraining projections.     

Coupling biophysical and micro-economic models to assess the effect of mitigation measures on greenhouse gas emissions from agriculture

Agricultural soils are a major source of atmospheric nitrous oxide (N₂O), a potent greenhouse gas (GHG). Because N₂O emissions strongly depend on soil type, climate, and crop management, their inventory requires the combination of biophysical and economic modeling, to simulate farmers’ behavior. Here, we coupled a biophysical soil-crop model, CERES-EGC, with an economic farm type supply model, AROPAj, at the regional scale in northern France. Response curves of N₂O emissions to fertilizer nitrogen (Nf) inputs were generated with CERES-EGC, and linearized to obtain emission factors. The latter ranged from 0.001 to 0.0225 kg N₂O-N kg^???1 Nf, depending on soil and crop type, compared to the fixed 0.0125 value of the IPCC guidelines. The modeled emission factors were fed into the economic model AROPAj which relates farm-level GHG emissions to production factors. This resulted in a N₂O efflux 20% lower than with the default IPCC method. The costs of abating GHG emissions from agriculture were calculated using a first-best tax on GHG emissions, and a second-best tax on their presumed factors (livestock size and fertilizer inputs). The first-best taxation was relatively efficient, achieving an 8% reduction with a tax of 11 €/ t-CO₂-equivalent, compared to 68 €/t-CO₂ eq for the same target with the second-best scheme.     

A composite study of the MJO influence on the surface air temperature and precipitation over the Continental United States

The influence of the MJO on the continental United States (CONUS) surface air temperature (SAT) and precipitation is examined based on 30?years of daily data from 1979–2008. Composites are constructed for each of the eight phases of the Wheeler-Hendon MJO index over 12 overlapping three-month seasons. To ensure that the MJO signal is distinguished from other patterns of climate variability, several steps are taken: (a) only days classified as “MJO events” are used in the composites, (b) statistical significance of associated composites is assessed using a Monte Carlo procedure, and (c) intraseasonal frequencies are matched to the unfiltered data. Composites of other fields are also shown in order to examine how the SAT and precipitation anomalies are associated with large-scale circulations providing a link between the tropics and extratropics. The strongest and most significant MJO effects on SAT are found during the northern winter seasons. When enhanced convection is located over the equatorial Indian Ocean, below-average SAT tends to occur in New England and the Great Lakes region. As enhanced tropical convection shifts over the Maritime continent, above-average SAT appears in the eastern states of the US from Maine to Florida. The MJO influence on precipitation is also significant during northern winter seasons. When enhanced convection is located over the Maritime continent, more precipitation is observed in the central plains of the US. Enhanced precipitation also occurs over the west coast of the US when convective activity is stronger over the Indian Ocean. During the northern summer and fall, the MJO impact on precipitation is mainly significant at lower latitudes, over Mexico and southeastern US.     

The effect of weather on grid systems and the reliability of electricity supply

A reliable public electricity supply depends in part on a reliable electricity grid system to transmit and distribute electrical power from generating stations to consumers. The grid system comprises many components that are exposed to the weather and can experience faults as a result of weather events. As climate change is expected to alter the number and severity of weather events, then the reliability of the grid and hence the reliability of electricity supplies can be affected. This paper reviews the effects of weather events on grid systems, illustrated by reference to experience on the grid systems in Europe and North America. It is shown that the effects on the high voltage transmission networks are different from the effects on lower voltage distribution networks and that generally the most significant extreme weather is high winds. Some remedial measures that can mitigate the effects of weather events are also described.     

Inventory of anthropogenic emissions and air pollution in the USSR

This paper gives data on air pollutant emissions from industrial sources and motor vehicles in the USSR. It discusses their distribution over the territory and trends during recent years. It studies methods of application of the emission data to assess air pollution.     

湖南省用电需求气象条件等级特征分析

利用气象行业标准《用电需求气象条件等级》中的气象敏感用电量条件指数统计方法,对湖南省97个地面气象观测站1971~2012年逐日气温资料,分析了湖南省各级气象敏感用电量条件日数的时空分布特征,结果表明：洞庭湖区、湘江流域为三级以上高气象敏感用电量日数相对大值区,高气象敏感用电量日数在近年来有上升的趋势,三级气象敏感用电量日数较多的月份集中在7月和8月。