Guus J. M. Velders

The importance of the Montreal Protocol in protecting climate

The 1987 Montreal Protocol on Substances that Deplete the Ozone Layer is a landmark agreement that has successfully reduced the global production, consumption, and emissions of ozone-depleting substances (ODSs). ODSs are also greenhouse gases that contribute to the radiative forcing of climate change. Using historical ODSs emissions and scenarios of potential emissions, we show that the ODS contribution to radiative forcing most likely would have been much larger if the ODS link to stratospheric ozone depletion had not been recognized in 1974 and followed by a series of regulations. The climate protection already achieved by the Montreal Protocol alone is far larger than the reduction target of the first commitment period of the Kyoto Protocol. Additional climate benefits that are significant compared with the Kyoto Protocol reduction target could be achieved by actions under the Montreal Protocol, by managing the emissions of substitute fluorocarbon gases and/or implementing alternative gases with lower global warming potentials.

The large contribution of projected HFC emissions to future climate forcing

The consumption and emissions of hydrofluorocarbons (HFCs) are projected to increase substantially in the coming decades in response to regulation of ozone depleting gases under the Montreal Protocol. The projected increases result primarily from sustained growth in demand for refrigeration, air-conditioning (AC) and insulating foam products in developing countries assuming no new regulation of HFC consumption or emissions. New HFC scenarios are presented based on current hydrochlorofluorocarbon (HCFC) consumption in leading applications, patterns of replacements of HCFCs by HFCs in developed countries, and gross domestic product (GDP) growth. Global HFC emissions significantly exceed previous estimates after 2025 with developing country emissions as much as 800% greater than in developed countries in 2050. Global HFC emissions in 2050 are equivalent to 9–19% (CO2-eq. basis) of projected global CO2 emissions in business-as-usual scenarios and contribute a radiative forcing equivalent to that from 6–13 years of CO2 emissions near 2050. This percentage increases to 28–45% compared with projected CO2 emissions in a 450-ppm CO2 stabilization scenario. In a hypothetical scenario based on a global cap followed by 4% annual reductions in consumption, HFC radiative forcing is shown to peak and begin to decline before 2050.

Global tropospheric NO2 column distributions: Comparing three‐dimensional model calculations with GOME measurements

Tropospheric NO2 columns derived from the data products of the Global Ozone Monitoring Experiment (GOME), deployed on the ESA ERS-2 satellite, have been compared with model calculations from two global three-dimensional chemistry transport models, IMAGES and MOZART. The main objectives of the study are an analysis of the tropospheric NO2 data derived from satellite measurements, an interpretation of it and evaluation of its quality using global models, and an estimation the role of NO2 in radiative forcing. The measured and modeled NO2 columns show similar spatial and seasonal patterns, with large tropospheric column amounts over industrialized areas and small column amounts over remote areas. The comparison of the absolute values of the measured and modeled tropospheric column amounts are particularly dependent upon uncertainties in the derivation of the tropospheric NO2 columns from GOME and the difficulty of modeling the boundary layer in global models, both of which are discussed below. The measured tropospheric column amounts derived from GOME data are of the same order as those calculated by the MOZART model over the industrialized areas of the United States and Europe, but a factor of 2-3 larger for Asia. The modeled tropospheric NO2 columns from MOZART as well as the column amounts measured by GOME are in good agreement with NO2 columns derived from observed NO2 mixing ratios in the boundary layer in eastern North America. The comparison of the models to the GOME data illustrates the degree to which present models reproduce the hot spots seen in the GOME data. The radiative forcing of NO2 has been estimated from the calculated tropospheric NO2 columns. The local maxima in the radiative forcing of tropospheric NO2 for cloud-free conditions over the eastern United States and western Europe represent 0.1-0.15 W m -2, while values of 0.04-0.1 W m -2 are estimated on a continental scale in these regions, of the same order of magnitude as the forcing of N20 and somewhat smaller than the regional forcing of tropospheric ozone. The globally averaged radiative forcing of tropospheric NO2 is negligible, --0.005 W m -2.

Disentangling the effects of CO2 and short-lived climate forcer mitigation

Significance Climate change is one of the greatest challenges of our times. Human activities, like fossil-fuel burning, result in emissions of radiation-modifying substances that have a detectable, either warming or cooling, influence on our climate. Some, like soot (black carbon), are very short lived, whereas others, like carbon dioxide (CO2), are very persistent and remain in the atmosphere for centuries to millennia. Importantly, these substances are often emitted by common sources. As climate policy is looking at options to limit emissions of all these substances, understanding their linkages becomes extremely important. Our study disentangles these linkages and therewith helps to avoid crucial misconceptions: Measures reducing short-lived climate forcers are complementary to CO2 mitigation, but neglecting linkages leads to overestimating their climate benefits. Anthropogenic global warming is driven by emissions of a wide variety of radiative forcers ranging from very short-lived climate forcers (SLCFs), like black carbon, to very long-lived, like CO2. These species are often released from common sources and are therefore intricately linked. However, for reasons of simplification, this CO2–SLCF linkage was often disregarded in long-term projections of earlier studies. Here we explicitly account for CO2–SLCF linkages and show that the short- and long-term climate effects of many SLCF measures consistently become smaller in scenarios that keep warming to below 2 °C relative to preindustrial levels. Although long-term mitigation of methane and hydrofluorocarbons are integral parts of 2 °C scenarios, early action on these species mainly influences near-term temperatures and brings small benefits for limiting maximum warming relative to comparable reductions taking place later. Furthermore, we find that maximum 21st-century warming in 2 °C-consistent scenarios is largely unaffected by additional black-carbon-related measures because key emission sources are already phased-out through CO2 mitigation. Our study demonstrates the importance of coherently considering CO2–SLCF coevolutions. Failing to do so leads to strongly and consistently overestimating the effect of SLCF measures in climate stabilization scenarios. Our results reinforce that SLCF measures are to be considered complementary rather than a substitute for early and stringent CO2 mitigation. Near-term SLCF measures do not allow for more time for CO2 mitigation. We disentangle and resolve the distinct benefits across different species and therewith facilitate an integrated strategy for mitigating both short and long-term climate change.

Preserving Montreal Protocol Climate Benefits by Limiting HFCs

With no impending global controls on HFCs, the Montreal Protocol offers a near-term path to preserve its climate benefits. The Montreal Protocol is perhaps the most successful international environmental treaty, responsible for global phaseout of the consumption and production of ozone-depleting substances (ODSs), e.g., chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs). Hydrofluorocarbons (HFCs), which do not destroy stratospheric ozone, were considered long-term substitutes for ODSs and are not controlled by the Montreal Protocol. Because most HFCs are potent greenhouse gases (GHGs), they are included in the Kyoto Protocol. But climate benefits provided by this protocol are limited as they apply only to developed countries and over a short time (2008–2012). As we describe below, with no impending global controls on HFCs, inclusion of HFCs under the Montreal Protocol offers a path, starting in the short term, to preserve the climate benefits already achieved by this protocol.

Reduction of solar UV by clouds: A comparison between satellite‐derived cloud effects and ground‐based radiation measurements

Assessment of the effects of ozone depletion on biologically effective solar UV at ground level has been greatly advanced through the use of remote sensing data. Satellite data on atmospheric properties allow the construction of geographically distributed surface UV radiation maps based on radiative transfer calculations. In this respect, clouds play a dominant but rather complex role. We compared the reduction of daily UV doses due to clouds, as derived from satellite cloud data, with the reduction derived from routine ground-based measurements of global solar radiation (i.e., broadband total solar irradiances with wavelengths between 0.3 and 2.8 μm). An empirical relationship is used to link the reduction due to clouds of global solar radiation and UV radiation. The abundance of global solar radiation measurements (data from over 125 stations in 30 satellite grid cells) for the European region ensured a sound basis for the data analysis for the period considered (May, June, and July of 1990, 1991, and 1992). Approximately 6500 daily UV-reduction factors, defined as the ratio of daily UV doses calculated with and without clouds, were thus obtained applying both methods. The daily UV-reduction factors (and 10-day averaged UV reduction factors) from the two independent sources correlated well, with r 2 = 0.83 (r 2 = 0.89), and had a standard deviation of 0.06 (0.03). Over 90% of the satellite-derived results agreed within a range of ±0.14 (±0.07) with the ground-based measurement-derived results. We evaluated sources of uncertainty related to spatial and temporal resolution, and optical properties, and estimated their consequences and range. Among these different sources the largest uncertainties are caused by the sampling error, i.e., grid-cell average versus station average, which is on average 0.10 for daily UV-reduction factors. Information on the atmospheric optical properties during the measurements may reduce the stated range of uncertainty from ±0.14 to ±0.07. The variation of the measurements from station to station is then the limiting factor. We concluded that the reduction of daily UV based on satellite-derived cloud cover and cloud optical thickness relates well with the UV reduction due to clouds derived from ground-based global solar radiation measurements.

Data assimilation of ground‐level ozone in Europe with a Kalman filter and chemistry transport model

[1] A Kalman filter coupled to the atmospheric chemistry transport model EUROS has been used to estimate the ozone concentrations in the boundary layer above Europe. Two Kalman filter algorithms, the reduced rank square root (RRSQRT) and the ensemble Kalman filter (ENKF), were implemented in this study. Both required, in general, a large number of EUROS model simulations for an assimilation. The observations consisted of hourly ozone data in a set of 135 ground-based stations in Europe for the period, June 1996. Half of these stations were used for the assimilation and the other half only for validation of the results. The combination between data assimilation (Kalman filter) and the atmospheric chemistry transport model, EUROS, gave more accurate results for boundary layer ozone than the EUROS model or measurements used separately. The average difference between assimilated and measured ozone concentrations decreased from 27.4 to 20.5 m gm � 3 for the average of the stations used for validation in Europe. Both algorithms tend to converge to about the same accuracy, with an increasing number of EUROS model runs. About 10–20 EUROS model calculations were found sufficient for a good assimilation. The results are supported by a number of simulations that also reveal a local character for the assimilation process. INDEX TERMS: 3337 Meteorology and Atmospheric Dynamics: Numerical modeling and data assimilation; 3307 Meteorology and Atmospheric Dynamics: Boundary layer processes; 0345 Atmospheric Composition and Structure: Pollution—urban and regional (0305); 0368 Atmospheric Composition and Structure: Troposphere—constituent transport and chemistry; KEYWORDS: atmospheric NOx, VOC

Ozone depletion and skin cancer incidence: a source risk approach

The atmospheric ozone layer serves as a protective filter against (part of) the harmful ultraviolet (UV) radiation from the sun. The depletion of the ozone layer, which was observed on a global scale over the past decades, is most probably caused by the global emission of halocarbons, and leads to an increase in UV at groundlevel, and thus, to increases in UV-related risks, like skin cancer incidence. Using satellite data on ozone depletion, a location specific estimate of changes in UV-levels is made for Europe. A source-risk model is used to illustrate effects of countermeasures on future skin cancer risks. Geographical differences and uncertainties are indicated.

External drift kriging of NOx concentrations with dispersion model output in a reduced air quality monitoring network

In the mid nineteen eighties the Dutch NOx air quality monitoring network was reduced from 73 to 32 rural and city background stations, leading to higher spatial uncertainties. In this study, several other sources of information are being used to help reduce uncertainties in parameter estimation and spatial mapping. For parameter estimation, we used Bayesian inference. For mapping, we used kriging with external drift (KED) including secondary information from a dispersion model. The methods were applied to atmospheric NOx concentrations on rural and urban scales. We compared Bayesian estimation with restricted maximum likelihood estimation and KED with universal kriging. As a reference we also included ordinary least squares (OLS). Comparison of several parameter estimation and spatial interpolation methods was done by cross-validation. Bayesian analysis resulted in an error reduction of 10 to 20% as compared to restricted maximum likelihood, whereas KED resulted in an error reduction of 50% as compared to universal kriging. Where observations were sparse, the predictions were substantially improved by inclusion of the dispersion model output and by using available prior information. No major improvement was observed as compared to OLS, the cause presumably being that much good information is contained in the dispersion model output, so that no additional spatial residual random field is required to explain the data. In all, we conclude that reduction in the monitoring network could be compensated by modern geostatistical methods, and that a traditional simple statistical model is of an almost equal quality.

A Hybrid Kalman Filter Algorithm for Large-Scale Atmospheric Chemistry Data Assimilation

Abstract In the past, a number of algorithms have been introduced to solve data assimilation problems for large-scale applications. Here, several Kalman filters, coupled to the European Operational Smog (EUROS) atmospheric chemistry transport model, are used to estimate the ozone concentrations in the boundary layer above Europe. Two Kalman filter algorithms, the reduced-rank square root (RRSQRT) and the ensemble Kalman filter (EnKF), were implemented in a prior study. To combine the best features of these two filters, a hybrid filter was constructed by making use of the reduced-rank approximation of the covariance matrix as a variance reducer for the EnKF. This hybrid algorithm, complementary orthogonal subspace filter for efficient ensembles (COFFEE), is coupled to the EUROS model. The performance of all algorithms is compared in terms of residual errors and number of EUROS model evaluations. The COFFEE results score somewhere between the EnKF and RRSQRT results for less than approximately 30 model eval...