Stationary Distribution and Eigenvalues for a de Bruijn Process

We define a de Bruijn process with parameters n and L as a certain continuous-time Markov chain on the de Bruijn graph with words of length L over an n-letter alphabet as vertices. We determine explicitly its steady state distribution and its characteristic polynomial, which turns out to decompose into linear factors. In addition, we examine the stationary state of two specializations in detail. In the first one, the de Bruijn-Bernoulli process, this is a product measure. In the second one, the Skin-deep de Bruin process, the distribution has constant density but nontrivial correlation functions. The two point correlation function is determined using generating function techniques.Comment: Dedicated to Herb Wilf on the occasion of his 80th birthda

Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2

The new version of the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) compiles gaseous and particulate air pollutant emissions, making use of the same anthropogenic sectors, time period (1970–2012), and international activity data that is used for estimating GHG emissions, as described in a companion paper (Janssens-Maenhout et al., 2017). All human activities, except large scale biomass burning and land use, land-use change, and forestry are included in the emissions calculation. The bottom-up compilation methodology of sector-specific emissions was applied consistently for all world countries, providing methodological transparency and comparability between countries. In addition to the activity data used to estimate GHG emissions, air pollutant emissions are determined by the process technology and end-of-pipe emission reduction abatements. Region-specific emission factors and abatement measures were selected from recent available scientific literature and reports. Compared to previous versions of EDGAR, the EDGAR v4.3.2 dataset covers all gaseous and particulate air pollutants, has extended time series (1970–2012), and has been evaluated with quality control and quality assurance (QC and QA) procedures both for the emission time series (e.g. particulate matter – PM – mass balance, gap-filling for missing data, the split-up of countries over time, few updates in the emission factors, etc.) and grid maps (full coverage of the world, complete mapping of EDGAR emissions with sector-specific proxies, etc.). This publication focuses on the gaseous air pollutants of CO, NOx, SO2, total non-methane volatile organic compounds (NMVOCs), NH3, and the aerosols PM10, PM2.5, black carbon (BC), and organic carbon (OC). Considering the 1970–2012 time period, global emissions of SO2 increased from 99 to 103&thinsp;Mt, CO from 441 to 562&thinsp;Mt, NOx from 68 to 122&thinsp;Mt, NMVOC from 119 to 170&thinsp;Mt, NH3 from 25 to 59&thinsp;Mt, PM10 from 37 to 65&thinsp;Mt, PM2.5 from 24 to 41&thinsp;Mt, BC from 2.7 to 4.5&thinsp;Mt, and OC from 9 to 11&thinsp;Mt. We present the country-specific emission totals and analyze the larger emitting countries (including the European Union) to provide insights on major sector contributions. In addition, per capita and per GDP emissions and implied emission factors – the apparent emissions per unit of production or energy consumption – are presented. We find that the implied emission factors (EFs) are higher for low-income countries compared to high-income countries, but in both cases decrease from 1970 to 2012. The comparison with other global inventories, such as the Hemispheric Transport of Air Pollution Inventory (HTAP v2.2) and the Community Emission Data System (CEDS), reveals insights on the uncertainties as well as the impact of data revisions (e.g. activity data, emission factors, etc.). As an additional metric, we analyze the emission ratios of some pollutants to CO2 (e.g. CO∕CO2, NOx∕CO2, NOx∕CO, and SO2∕CO2) by sector, region, and time to identify any decoupling of air pollutant emissions from energy production activities and to demonstrate the potential of such ratios to compare to satellite-derived emission data. Gridded emissions are also made available for the 1970–2012 historic time\ud series, disaggregated for 26 anthropogenic sectors using updated spatial proxies. The analysis of the evolution of hot spots over time allowed us to identify areas with growing emissions and where emissions should be constrained to improve global air quality (e.g. China, India, the Middle East, and some South American countries are often characterized by high emitting areas that are changing rapidly compared to Europe or the USA, where stable or decreasing emissions are evaluated). Sector- and component-specific contributions to grid-cell emissions may help the modelling and satellite communities to disaggregate atmospheric column amounts and concentrations into main emitting sectors. This work addresses not only the emission inventory and modelling communities, but also aims to broaden the usefulness of information available in a global emission inventory such as EDGAR to also include the measurement community. Data are publicly available online through the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432_AP and registered under https://doi.org/10.2904/JRC_DATASET_EDGAR.</p

Evaluation of Black Carbon Estimations in Global Aerosol Models

We evaluate black carbon (BC) model predictions from the AeroCom model intercomparison project by considering the diversity among year 2000 model simulations and comparing model predictions with available measurements. These 5 model-measurement intercomparisons include BC surface and aircraft concentrations, aerosol absorption optical depth (AAOD) from AERONET and Ozone Monitoring Instrument (OMI) retrievals and BC column estimations based on AERONET. In regions other than Asia, most models are biased high compared to surface concentration measurements. However compared with (column) AAOD or BC burden retreivals, the models 10 are generally biased low. The average ratio of model to retrieved AAOD is less than 0.7 in South American and 0.6 in African biomass burning regions; both of these regions lack surface concentration measurements. In Asia the average model to observed ratio is 0.6 for AAOD and 0.5 for BC surface concentrations. Compared with aircraft measurements over the Americas at latitudes between 0 and 50 N, the average model is a 15 factor of 10 larger than observed, and most models exceed the measured BC standard deviation in the mid to upper troposphere. At higher latitudes the average model to aircraft BC is 0.6 and underestimates the observed BC loading in the lower and middle troposphere associated with springtime Arctic haze. Low model bias for AAOD but overestimation of surface and upper atmospheric BC concentrations at lower latitudes 20 suggests that most models are underestimating BC absorption and should improve estimates for refractive index, particle size, and optical effects of BC coating. Retrieval uncertainties and/or differences with model diagnostic treatment may also contribute to the model-measurement disparity. Largest AeroCom model diversity occurred in northern Eurasia and the remote Arctic, regions influenced by anthropogenic sources. 25 Changing emissions, aging, removal, or optical properties within a single model generated a smaller change in model predictions than the range represented by the full set of AeroCom models. Upper tropospheric concentrations of BC mass from the aircraft measurements are suggested to provide a unique new benchmark to test scavenging and vertical dispersion of BC in global models.JRC.H.2-Climate chang

Assessing the effect of marine isoprene and ship emissions on ozone, using modelling and measurements from the South Atlantic Ocean

International audienceShip-borne measurements have been made in air over the remote South Atlantic and Southern Oceans in January–March 2007. This cruise encountered a large-scale natural phytoplankton bloom emitting reactive hydrocarbons (e.g. isoprene); and a high seas squid fishing fleet emitting NO$_x$ (NO and NO$_2$). Using an atmospheric chemistry box model constrained by in-situ measurements, it is shown that enhanced ozone production ensues from such juxtaposed marine biogenic and anthropogenic emissions. The relative impact of shipping and phytoplankton emissions on ozone was examined on a global scale using the EMAC model. Ozone in the marine boundary layer was found to be over ten times more sensitive to NOx emissions from ships, than to marine isoprene in the region south of 45°. Although marine isoprene emissions make little impact on the global ozone budget, co-located ship and phytoplankton emissions may explain the increasing ozone reported for the 40–60°S southern Atlantic regio

What can we learn about ship emission inventories from measurements of air pollutants over the Mediterranean Sea?

Ship emission estimates diverge widely for all chemical compounds for several reasons: use of different methodologies (bottom-up or top-down), activity data and emission factors can easily result in a difference ranging from a factor of 1.5 to even an order of magnitude. Combining three sets of observational data – ozone and black carbon measurements sampled at three coastal sites and on board of a Mediterranean cruise ship, as well as satellite observations of atmospheric NO&lt;sub&gt;2&lt;/sub&gt; column concentration over the same area – we assess the accuracy of the three most commonly used ship emission inventories, EDGAR FT (Olivier et al., 2005), emissions described by Eyring et al. (2005) and emissions reported by EMEP (Vestreng et al., 2007). Our tool is a global atmospheric chemistry transport model which simulates the chemical state of the Mediterranean atmosphere applying different ship emission inventories. The simulated contributions of ships to air pollutant levels in the Mediterranean atmosphere are significant but strongly depend on the inventory applied. Close to the major shipping routes relative contributions vary from 10 to 50% for black carbon and from 2 to 12% for ozone in the surface layer, as well as from 5 to 20% for nitrogen dioxide atmospheric column burden. The relative contributions are still significant over the North African coast, but less so over the South European coast because densely populated regions with significant human activity contribute relatively more to air pollution than ships, even if these regions attract a lot of ship traffic. The observations poorly constrain the ship emission inventories in the Eastern Mediterranean where the influence of uncertain land based emissions, the model transport and wet deposition are at least as important as the signal from ships. In the Western Mediterranean, the regional EMEP emission inventory gives the best match with most measurements, followed by Eyring for NO&lt;sub&gt;2&lt;/sub&gt; and ozone and by EDGAR for black carbon. Given the uncertainty of the measurements and the model, each of the three emission inventories could actually be right, implying that large uncertainties in ship emissions need to be considered for future scenario analysis

Origin of anthropogenic hydrocarbons and halocarbons measured in the summertime european outflow (on Crete in 2001)

International audienceDuring the Mediterranean Intensive Oxidant Study MINOS in August 2001, 87 air samples were collected at the ground-based station Finokalia (35°19'N, 25°40'E) on the north coast of Crete and subsequently analysed by GC-MS. The analysis includes various hydrocarbons, organo-halogens, HCFCs and CFCs. These compounds have a wide variety of sources and sinks and a large range of atmospheric lifetimes. We evaluated the characteristics of the sampling site in terms of proximity to individual sources by plotting the measured variability of these species against lifetime. The resulting linear relationship suggests that the sampling site is representative of intermediate conditions between a remote site and one that is in the vicinity of a wide variety of sources. Our analysis of air mass origin and chemical ratios also shows that several distinct anthropogenic sources influenced the atmospheric composition over Crete. Propane observations are compared to a global model to assess the fossil fuel related emission inventory. Although the model reproduces the general pattern of the propane variations, the model mixing ratios are systematically too low by a factor of 1.5 to 3, probably due to an underestimation of the propane emissions from east European countries in the underlying global database EDGAR. Another important finding was that methyl chloroform, a compound banned under the Montreal protocol, showed significant enhancements from background, which were well correlated with CFC-113. This suggests continued use and emission of methyl chloroform by one or more European countries. We also discuss the observed variations of methyl bromide and suggest that the significant peak observed on 12 August 2001 reflects heavy agricultural use as a soil fumigant in Italy