M. Van Roozendael

Bio: M. Van Roozendael is an academic researcher from Belgian Institute for Space Aeronomy. The author has contributed to research in topics: SCIAMACHY & Differential optical absorption spectroscopy. The author has an hindex of 59, co-authored 175 publications receiving 9081 citations. Previous affiliations of M. Van Roozendael include Royal Netherlands Meteorological Institute.

Trends, seasonal variability and dominant NOx source derived from a ten year record of NO2 measured from space

Abstract: [1] For the period 1996–2006, global distributions of tropospheric nitrogen dioxide (NO2) have been derived from radiances measured with the satellite instruments GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY). A statistical analysis is applied to derive trends and seasonal variability for this period on a global scale. The time series of the monthly NO2 columns for these ten years have been fitted with a linear function superposed on an annual seasonal cycle on a grid with a spatial resolution of 1 by 1 .W e see significant reductions (up to 7% per year) in NO2 in Europe and parts of the eastern United States, and a strong increase in Asia, most particularly in China (up to 29% per year) but also in Iran and Russia. By comparing the data with the cloud information derived from the same satellite observations, the contribution of lightning to the total column of NO2 is estimated. The estimated NO2 from lightning is, especially in the tropics, in good agreement with lightning flash rate observations from space. The satellite observed seasonal variability of NO2 generally correlates well with independent observations and estimates of the seasonal cycle of specific NOx sources. Source categories considered are anthropogenic (fossil fuel and biofuel), biomass burning, soil emissions and lightning. Using the characteristics of the seasonal variability of these source categories, the dominant source of NOx emissions has been identified on a global scale and on a 1 by 1 grid.

The ESA Climate Change Initiative: Satellite Data Records for Essential Climate Variables

Abstract: Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties. There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together. This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science.

Detection of the trend and seasonal variation in tropospheric NO2 over China

Abstract: [1] The results of a trend study on the tropospheric NO2 column over China are presented, on the basis of measurements from the satellite instruments GOME and SCIAMACHY. From these observations, monthly averaged tropospheric NO2 distributions are determined for the period 1996 to 2005 on a 1° by 1° grid. A linear model with a seasonal component is used to fit these time series. The variance and the autocorrelation of the noise are used to calculate the significance of the trend. The results show a large growth of tropospheric NO2 over eastern China, especially above the industrial areas with a fast economical growth. For instance, Shanghai had a linear significant increase in NO2 columns of 20% ± 6% per year (reference year 1996) in the period 1996–2005. The seasonal pattern of the NO2 concentration shows a difference between east and west China. In the east a NO2 maximum is found during wintertime, because of chemistry and anthropogenic activity. Contrary to this, in the western part of China the NO2 concentration reaches a maximum in summertime. This spatial difference correlates with the population distribution of China. Since there is negligible anthropogenic activity in west China this difference in seasonality of NO2 is attributed to natural emissions in west China.

Global isoprene emissions estimated using MEGAN, ECMWF analyses and a detailed canopy environment model

Abstract: The global emissions of isoprene are calculated at 0.5 resolution for each year between 1995 and 2006, based on the MEGAN (Model of Emissions of Gases and Aerosols from Nature) version 2 model (Guenther et al., 2006) and a detailed multi-layer canopy environment model for the cal- culation of leaf temperature and visible radiation fluxes. The calculation is driven by meteorological fields - air temper- ature, cloud cover, downward solar irradiance, windspeed, volumetric soil moisture in 4 soil layers - provided by anal- yses of the European Centre for Medium-Range Weather Forecasts (ECMWF). The estimated annual global isoprene emission ranges between 374 Tg (in 1996) and 449 Tg (in 1998 and 2005), for an average of ca. 410 Tg/year over the whole period, i.e. about 30% less than the standard MEGAN estimate (Guenther et al., 2006). This difference is due, to a large extent, to the impact of the soil moisture stress factor, which is found here to decrease the global emissions by more than 20%. In qualitative agreement with past studies, high annual emissions are found to be generally associated with El Ni˜ no events. The emission inventory is evaluated against flux measurement campaigns at Harvard forest (Massachus- sets) and Tapaj ´ os in Amazonia, showing that the model can capture quite well the short-term variability of emissions, but that it fails to reproduce the observed seasonal variation at the tropical rainforest site, with largely overestimated wet season fluxes. The comparison of the HCHO vertical columns calcu- lated by a chemistry and transport model (CTM) with HCHO

Validation of Ozone Monitoring Instrument nitrogen dioxide columns

Abstract: [1] We review the standard nitrogen dioxide (NO2) data product (Version 1.0.), which is based on measurements made in the spectral region 415–465 nm by the Ozone Monitoring Instrument (OMI) on the NASA Earth Observing System-Aura satellite. A number of ground- and aircraft-based measurements have been used to validate the data product’s three principal quantities: stratospheric, tropospheric, and total NO2 column densities under nearly or completely cloud-free conditions. The validation of OMI NO2 is complicated by a number of factors, the greatest of which is that the OMI observations effectively average the NO2 over its field of view (minimum 340 km 2 ), while a ground-based instrument samples at a single point. The tropospheric NO2 field is often very inhomogeneous, varying significantly over tens to hundreds of meters, and ranges from 10 16 cm � 2 over urban and industrial areas. Because of OMI’s areal averaging, when validation measurements are made near NO2 sources the OMI measurements are expected to underestimate the ground-based, and this is indeed seen. Further, we use several different instruments, both new and mature, which might give inconsistent NO2 amounts; the correlations between nearby instruments is 0.8–0.9. Finally, many of the validation data sets are quite small and span a very short length of time; this limits the statistical conclusions that can be drawn from them. Despite these factors, good agreement is generally seen between the OMI and ground-based measurements, with OMI stratospheric NO2 underestimated by about 14% and total and tropospheric columns underestimated by 15–30%. Typical correlations between OMI NO2 and ground-based measurements are generally >0.6.

Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009)

Abstract: . New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year−1 with significant interannual variability during 1997–2001 (2.8 Pg C year−1 in 1998 and 1.6 Pg C year−1 in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year−1) before declining in 2008 (1.7 Pg C year−1) and 2009 (1.5 Pg C year−1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

The model of emissions of gases and aerosols from nature version 2.1 (MEGAN2.1): An extended and updated framework for modeling biogenic emissions

Abstract: . The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1) is a modeling framework for estimating fluxes of biogenic compounds between terrestrial ecosystems and the atmosphere using simple mechanistic algorithms to account for the major known processes controlling biogenic emissions. It is available as an offline code and has also been coupled into land surface and atmospheric chemistry models. MEGAN2.1 is an update from the previous versions including MEGAN2.0, which was described for isoprene emissions by Guenther et al. (2006) and MEGAN2.02, which was described for monoterpene and sesquiterpene emissions by Sakulyanontvittaya et al. (2008). Isoprene comprises about half of the total global biogenic volatile organic compound (BVOC) emission of 1 Pg (1000 Tg or 1015 g) estimated using MEGAN2.1. Methanol, ethanol, acetaldehyde, acetone, α-pinene, β-pinene, t-β-ocimene, limonene, ethene, and propene together contribute another 30% of the MEGAN2.1 estimated emission. An additional 20 compounds (mostly terpenoids) are associated with the MEGAN2.1 estimates of another 17% of the total emission with the remaining 3% distributed among >100 compounds. Emissions of 41 monoterpenes and 32 sesquiterpenes together comprise about 15% and 3%, respectively, of the estimated total global BVOC emission. Tropical trees cover about 18% of the global land surface and are estimated to be responsible for ~80% of terpenoid emissions and ~50% of other VOC emissions. Other trees cover about the same area but are estimated to contribute only about 10% of total emissions. The magnitude of the emissions estimated with MEGAN2.1 are within the range of estimates reported using other approaches and much of the differences between reported values can be attributed to land cover and meteorological driving variables. The offline version of MEGAN2.1 source code and driving variables is available from http://bai.acd.ucar.edu/MEGAN/ and the version integrated into the Community Land Model version 4 (CLM4) can be downloaded from http://www.cesm.ucar.edu/ .

The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions

Abstract: . The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1) is a modeling framework for estimating fluxes of biogenic compounds between terrestrial ecosystems and the atmosphere using simple mechanistic algorithms to account for the major known processes controlling biogenic emissions. It is available as an offline code and has also been coupled into land surface and atmospheric chemistry models. MEGAN2.1 is an update from the previous versions including MEGAN2.0, which was described for isoprene emissions by Guenther et al. (2006) and MEGAN2.02, which was described for monoterpene and sesquiterpene emissions by Sakulyanontvittaya et al. (2008). Isoprene comprises about half of the total global biogenic volatile organic compound (BVOC) emission of 1 Pg (1000 Tg or 1015 g) estimated using MEGAN2.1. Methanol, ethanol, acetaldehyde, acetone, α-pinene, β-pinene, t-β-ocimene, limonene, ethene, and propene together contribute another 30% of the MEGAN2.1 estimated emission. An additional 20 compounds (mostly terpenoids) are associated with the MEGAN2.1 estimates of another 17% of the total emission with the remaining 3% distributed among >100 compounds. Emissions of 41 monoterpenes and 32 sesquiterpenes together comprise about 15% and 3%, respectively, of the estimated total global BVOC emission. Tropical trees cover about 18% of the global land surface and are estimated to be responsible for ~80% of terpenoid emissions and ~50% of other VOC emissions. Other trees cover about the same area but are estimated to contribute only about 10% of total emissions. The magnitude of the emissions estimated with MEGAN2.1 are within the range of estimates reported using other approaches and much of the differences between reported values can be attributed to land cover and meteorological driving variables. The offline version of MEGAN2.1 source code and driving variables is available from http://bai.acd.ucar.edu/MEGAN/ and the version integrated into the Community Land Model version 4 (CLM4) can be downloaded from http://www.cesm.ucar.edu/ .

Asian emissions in 2006 for the NASA INTEX-B mission

Abstract: . A new inventory of air pollutant emissions in Asia in the year 2006 is developed to support the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B) funded by the National Aeronautics and Space Administration (NASA). Emissions are estimated for all major anthropogenic sources, excluding biomass burning. We estimate total Asian anthropogenic emissions in the year 2006 as follows: 47.1 Tg SO2, 36.7 Tg NOx, 298.2 Tg CO, 54.6 Tg NMVOC, 29.2 Tg PM10, 22.2 Tg PM2.5, 2.97 Tg BC, and 6.57 Tg OC. We emphasize emissions from China because they dominate the Asia pollutant outflow to the Pacific and the increase of emissions from China since 2000 is of great concern. We have implemented a series of improved methodologies to gain a better understanding of emissions from China, including a detailed technology-based approach, a dynamic methodology representing rapid technology renewal, critical examination of energy statistics, and a new scheme of NMVOC speciation for model-ready emissions. We estimate China's anthropogenic emissions in the year 2006 to be as follows: 31.0 Tg SO2, 20.8 Tg NOx, 166.9 Tg CO, 23.2 Tg NMVOC, 18.2 Tg PM10, 13.3 Tg PM2.5, 1.8 Tg BC, and 3.2 Tg OC. We have also estimated 2001 emissions for China using the same methodology and found that all species show an increasing trend during 2001–2006: 36% increase for SO2, 55% for NOx, 18% for CO, 29% for VOC, 13% for PM10, and 14% for PM2.5, BC, and OC. Emissions are gridded at a resolution of 30 min×30 min and can be accessed at our web site ( http://mic.greenresource.cn/intex-b2006 ).

An inventory of gaseous and primary aerosol emissions in Asia in the year 2000 : NASA global tropospheric experiment transport and chemical evolution over the pacific (TRACE-P): Measurements and analysis (TRACEP1)

Abstract: [i] An inventory of air pollutant emissions in Asia in the year 2000 is developed to support atmospheric modeling and analysis of observations taken during the TRACE-P experiment funded by the National Aeronautics and Space Administration (NASA) and the ACE-Asia experiment funded by the National Science Foundation (NSF) and the National Oceanic and Atmospheric Administration (NOAA). Emissions are estimated for all major anthropogenic sources, including biomass burning, in 64 regions of Asia. We estimate total Asian emissions as follows: 34.3 Tg SO 2 , 26.8 Tg NO x , 9870 Tg CO 2 , 279 Tg CO, 107 Tg CH 4 , 52.2 Tg NMVOC, 2.54 Tg black carbon (BC), 10.4 Tg organic carbon (OC), and 27.5 Tg NH 3 . In addition, NMVOC are speciated into 19 subcategories according to functional groups and reactivity. Thus we are able to identify the major source regions and types for many of the significant gaseous and particle emissions that influence pollutant concentrations in the vicinity of the TRACE-P and ACE-Asia field measurements. Emissions in China dominate the signature of pollutant concentrations in this region, so special emphasis has been placed on the development of emission estimates for China. China's emissions are determined to be as follows: 20.4 Tg SO 2 , 11.4 Tg NO x , 3820 Tg CO 2 , 116 Tg CO, 38.4 Tg CH 4 , 17.4 Tg NMVOC, 1.05 Tg BC, 3.4 Tg OC, and 13.6 Tg NH 3 . Emissions are gridded at a variety of spatial resolutions from 1° × 1° to 30 s x 30 s, using the exact locations of large point sources and surrogate GIS distributions of urban and rural population, road networks, landcover, ship lanes, etc. The gridded emission estimates have been used as inputs to atmospheric simulation models and have proven to be generally robust in comparison with field observations, though there is reason to think that emissions of CO and possibly BC may be underestimated. Monthly emission estimates for China are developed for each species to aid TRACE-P and ACE-Asia data interpretation. During the observation period of March/ April, emissions are roughly at their average values (one twelfth of annual). Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of ±16% for SO 2 to a high of ±450% for OC.