CO2 Capture and Storage with Leakage in an Energy-Climate Model

Geological CO₂ capture and storage (CCS) is among the main near-term contenders for addressing the problem of global climate change. Even in a baseline scenario, with no comprehensive international climate policy, a moderate level of CCS technology is expected to be deployed, given the economic benefits associated with enhanced oil and gas recovery. With stringent climate change control, CCS technologies will probably be installed on an industrial scale. Geologically stored CO₂, however, may leak back to the atmosphere, which could render CCS ineffective as climate change reduction option. This article presents a long-term energy scenario study for Europe, in which we assess the significance for climate policy making of leakage of CO₂ artificially stored in underground geological formations. A detailed sensitivity analysis is performed for the CO₂ leakage rate with the bottom-up energy systems model MARKAL, enriched for this purpose with a large set of CO₂ capture technologies (in the power sector, industry, and for the production of hydrogen) and storage options (among which enhanced oil and gas recovery, enhanced coal bed methane recovery, depleted fossil fuel fields, and aquifers). Through a series of model runs, we confirm that a leakage rate of 0.1%/year seems acceptable for CCS to constitute a meaningful climate change mitigation option, whereas one of 1%/year is not. CCS is essentially no option to achieve CO₂ emission reductions when the leakage rate is as high as 1%/year, so more reductions need to be achieved through the use of renewables or nuclear power, or in sectors like industry and transport. We calculate that under strict climate control policy, the cumulative captured and geologically stored CO₂ by 2100 in the electricity sector, when the leakage rate is 0.1%/year, amounts to about 45,000 MtCO₂. Only a little over 10,000 MtCO₂ cumulative power-generation-related emissions are captured and stored underground by the end of the century when the leakage rate is 1%/year. Overall marginal CO₂ abatement costs increase from a few €/tCO₂ today to well over 150 €/tCO₂ in 2100, under an atmospheric CO₂ concentration constraint of 550 ppmv. Carbon costs in 2100 turn out to be about 40 €/tCO₂ higher when the annual leakage rate is 1%/year in comparison to when there is no CO₂ leakage. Irrespective of whether CCS deployment is affected by gradual CO₂ seepage, the annual welfare loss in Europe induced by the implementation of policies preventing “dangerous anthropogenic interference with the climate system” (under our assumption, implying a climate stabilisation target of 550 ppmv CO₂ concentration) remains below 0.5% of GDP during the entire century.

Assessing the Relative Importance of Spatial Variability in Emissions Versus Landscape Properties in Fate Models for Environmental Exposure Assessment of Chemicals

Multimedia mass balance models differ in their treatment of spatial resolution from single boxes representing an entire region to multiple interconnected boxes with varying landscape properties and emission intensities. Here, model experiments were conducted to determine the relative importance of these two main factors that cause spatial variation in environmental chemical concentrations: spatial patterns in emission intensities and spatial differences in environmental conditions. In the model, experiments emissions were always to the air compartment. It was concluded that variation in emissions is in most cases the dominant source of variation in environmental concentrations. It was found, however, that variability in environmental conditions can strongly influence predicted concentrations in some cases, if the receptor compartments of interest are soil or water—for water concentrations particularly if a chemical has a high octanol–air partition coefficient (K _oa). This information will help to determine the required level of spatial detail that suffices for a specific regulatory purpose.     

Assessment of anthropogenic influences on surface water quality in urban estuary, northern New Jersey: multivariate approach

Concentrations of selected heavy metals (Cd, Cr, Cu, Pb, Ni, Fe, and Zn), nutrients (NO ₃ ^? and NH₃), fecal coliform colonies, and other multiple physical–chemical parameters were measured seasonally from 12 locations in an urban New Jersey estuary between 1994 and 2008. Stepwise regression, principal component analysis, and cluster analysis were used to group water quality results and sampling locations, as well as to assess these data’s relationship to sewage treatment effluents and the distance to the mouth of the river. The BOD₅, NH₃, NO ₃ ^? and fecal coliform counts clustered as one group and positively correlated to the distances from treated effluent and the measures of magnitude at the discharge points. Dissolved solids and most metal species scored high along a single principal component axes and were significantly correlated with the proximity to the industrialized area. From these data, one can conclude that the effluent discharge has been a main source of anthropogenic input to the Hackensack River over the past 15 years. Therefore, the greatest improvement to water quality would come from eliminating the few remaining combined sewer overflows and improving the removal of nutrients from treated effluents before they are discharged into the creeks and river.     

The Use of Atmospheric Dispersion Models in Risk Assessment Decision Support Systems for Pesticides

In the evaluation of potentially adverse effects oforganic chemicals such as pesticides on theenvironment the atmosphere may play an important role.After its release to the atmosphere the chemical willbe transported/dispersed in the atmosphere and finallyit will be removed either by atmospheric-chemicaldestruction or by deposition to the underlying soil orsurface water. In a risk assessment decision supportsystem both ambient concentrations and depositionfluxes must be known to evaluate the risk of directexposure (inhalation) or the risk of soil and watercontamination caused by deposition. This paperdiscusses the use of atmospheric dispersion models insuch risk assessment decision support systems.     

Mapping nitrate leaching to upper groundwater in the sandy regions of The Netherlands, using conceptual knowledge

The European Community asks its Member States to provide a comprehensive and coherent overview of their groundwater chemical status. It is stated that simple conceptual models are necessary to allow assessments of the risks of failing to meet quality objectives. In The Netherlands two monitoring networks (one for agriculture and one for nature) are operational, providing results which can be used for an overview. Two regression models, based upon simple conceptual models, link measured nitrate concentrations to data from remote sensing images of land use, national forest inventory, national cattle inventory, fertiliser use statistics, atmospheric N deposition, soil maps and weather monitoring. The models are used to draw a nitrate leaching map and to estimate the size of the area exceeding the EU limit value in the early 1990s. The 95% confidence interval for the fraction nature and agricultural areas where the EU limit value for nitrate (50 mg/l) was exceeded amounted to 0.77–0.85 while the lower 97.5% confidence limit for the fraction agricultural area where the EU limit value was exceeded amounted to 0.94. Although the two conceptual models can be regarded as simple, the use of the models to give an overview was experienced as complex.     

Xeno-estrogenic compounds in precipitation

The exposure to some chemicals can lead to hormone disrupting effects. Presently, much attention is focused on so-called xeno-estrogens, synthetic compounds that interact with hormone receptors causing a number of reactions that eventually lead to effects related to reproduction and development. The current study was initiated to investigate the presence of a number of such compounds in precipitation as a follow-up on a previous study in which pesticide concentrations in air and precipitation were determined. Rainwater samples were collected at about 50 locations in The Netherlands in a four week period. The samples were analysed for bisphenol-A, alkylphenols and alkylphenol ethoxylates, phthalates, flame retardants and synthetic musk compounds. The results clearly indicated the presence of these compounds in precipitation. The concentrations ranged from the low ng l(-1) range for flame retardants to several thousands of ng l(-1) for the phthalates. Bisphenol-A was found in 30% of the samples in concentrations up to 130 ng l(-1), while alkylphenols and alkylphenol ethoxylates were found in virtually all locations in concentrations up to 920 ng l(-1) for the individual compounds. Phthalates were by far the most abundant xeno-estrogens in the precipitation samples and were found in every sample. Di-isodecyl phthalate was found in a surprisingly high concentration of almost 100 000 ng l(-1). Polybrominated flame retardants were found in the low ng l(-1) range and generally in less than 20% of the samples. Noticeable was the finding of hexabromocyclododecane, a replacement for the polybrominted diphenyl ethers at one location in a concentration of almost 2000 ng l(-1). Finally, as expected, synthetic musk compounds were detected in almost all samples. This is especially true for the polycyclic musks HHCB and AHTN. Nitro musks were found, but only on a few locations. Kriging techniques were used to calculate precipitation concentrations in between actual sampling locations to produce contour plots for a number of compounds. These plots clearly show located emission sources for a number of compounds such as bisphenol-A, nonylphenol ethoxylate, phthalates and AHTN. On the contrary, the results for HHCB and some phthalates indicated diffuse emission patterns, probably as the result of the use of consumer products containing these compounds.