Deuterium excess in Greenland snow: Analysis with simple and complex models

International audienceA simple Rayleigh-type isotope model, typical of those used to develop algorithms for extracting climatic information from stable water isotope paleodata, is evaluated against the more complex and presumably more reliable calculations of a general circulation model (GCM) fitted with isotope tracer diagnostics. The evaluation centers on an analysis of how the temperature T e of an oceanic moisture source affects the deuterium excess d of Greenland precipitation. The annual Te-d relationship derived from the GCM diagnostics is largely reproduced by the simple isotope model when the latter is properly initialized. This, coupled with the fact that the GCM itself reproduces observed isotope behavior, suggests that the simpler model's atmospheric calculations are indeed adequate for isotope studies. Furthermore, the GCM results support the idea, originally developed with the simpler models, that polar deuterium excess values contain information on meteorological conditions at distant evaporative sources. 1. Introduction The stable isotopes of water, HDO and H}sO, have been measured in ice cores and other paleowaters in varying concentrations. Through a detailed analysis of current isotope concentration fields, isotope/climate relationships have been derived which allow the extraction of paleoclimatic temperatures from paleowater measurements (see Jouzel et al. [1997] for a recent review). A related isotopic quantity, deuterium excess, is now being used to infer additional paleoclimatic information. Deuterium excess d was defined by Daansgaard [1964] as d = •D-8•sO, where • indicates a permil deviation from the corresponding isotope ratio in standard mean ocean water (SMOW). The factor 8 comes from the meteoric water line, which defines the locus of modern precipitation in a 5D/5•80 plot [Craig, 1961]. Using a simple evaporation model and a Rayleigh-type precipitation model, Merlivat and Jouzel [1979] inferred that the deuterium excess of precipitation primarily depends on the mean relative humidity above the evaporative (oceanic) source for the moisture. Jouzel et al. [1982] then interpreted the reduced glacial d values (relative to modern values) in an East Antarctic core as a reflection of higher relative humidity over the oceanic areas providing moisture for Antarctic precipitation. Johnsen et al. [1989] pointed out that d is also significantly affected by the temperature of the moisture source and examined d variations with respect to absolute (rather than relative) Paper number 98JD00274. 0148-0227/98/98JD-00274509.00 humidity, leading Daansgaard et al. [1989] to interpret the abrupt d change at the termination of the Younger-Dryas in Greenland's Dye 3 core in terms of a rapid retreat of sea-ice cover. The dual importance of humidity and temperature at the evaporative source has also been recognized for Antarctica [Petit et al., 1991; Ciais and Jouzel, 1994; Ciais et al., 1995; Fisher, 1991]. The Rayleigh or Rayleigh-type distillation models (herein-after often referred to as "simple isotope models") usually applied in these studies essentially model isotope behavior within isolated air masses transported poleward from an ocean source. The idealized paths traversed by these air masses are determined by prescribed initial and final states for temperature and pressure. The simple isotope models account for the interplay between cloud microphysics and the fractionation processes occurring at each phase change of the water. They cannot, however, account for the complexity of dynamical processes that lead to the formation of precipitation. Furthermore , Jouzel and Koster [1996] recently showed that the standard approach used in these models for specifying the initial isotope contents within the air parcels introduces a systematic bias that can significantly affect the simulated relationships between deuterium excess and evaporative source conditions. An alternative approach to studying global water isotope behavior is to incorporate the isotopic cycles into an atmospheric general circulation model (GCM), which does simulate the dynamical complexity of the atmosphere and which avoids the noted initial conditions bias in the simple Rayleigh-type models. Isotope tracer diagnostics have been incorporated into at least four different GCMs [Joussaume et al., 1984; Jouzel et 894

Simulation and evaluation of 2010 emission control scenarios in a Mediterranean area

International audienc

Urban-Scale NO2 Prediction with Sensors Aboard Bicycles: A Comparison of Statistical Methods Using Synthetic Observations

International audienceMobile devices for city-scale air quality monitoring is receiving increasing attention due to the advent of low-cost and miniaturized sensors. Mobility and crowdsensing have emerged as a new means to investigate the ambient air quality in urban areas. However, the design of the network (e.g., number of sensors per unit area) and the scientific interpretation of collected data with an ad hoc method are still challenging. In this paper, we focus on the use of a fleet of private bicycles to monitor NO 2 concentrations in the city of Marseille, France. The study is based on synthetic observations generated by means of a regional air quality simulation system at a spatial resolution of 25 m × 25 m and simulated bike trips that are randomly generated in the city. The bike trips correspond to a maximum of 4500 bike commuters and are generated using a web-based navigation service. Simulated bike tracks are validated using available statistics on bike counts. Each bike track is associated with the along-track corresponding NO 2 concentrations collected from the air quality simulations and physical features on the ground collected from Open Street Map. Spatialization of the information collected aboard the bikes is tested by using three different algorithms: kriging, land-use regression (LUR) and neural network (NN). LUR and NN show that the fleet can be limited to below 100 bikes while the performance of kriging is steadily increasing with the number of bikes. Increasing the sample distance above 200 m also impairs the citywide prediction of simulated NO 2 concentrations

Monitoring of Glyphosate, Glufosinate-ammonium, and (Aminomethyl)phosphonic acid in ambient air of Provence-Alpes-Côte-d’Azur Region, France

International audienceGlyphosate, AMPA, its main metabolite, and Glufosinate-ammonium were monitored in ambient air samples collected for two years (2015–2016), at four sampling sites in Provence-Alpes-Côte-d’Azur Region (PACA, France) in different areas typologies (non-agricultural areas: city center, ‘zero pesticide’ policy, and industrial area but also agricultural sectors: mainly orchards and vineyards). Neither Glufosinate-ammonium nor AMPA were detected. Glyphosate was detected at a global frequency of 7% with frequencies ranging from 0% (Nice) to 23% (Cavaillon), according to the sampling site. Glyphosate concentration reached a maximum level of 1.04 ng m−3 in the rural site of Cavaillon. This is despite the physicochemical characteristics of Glyphosate which are not favorable to its passage into the atmosphere. The absence of simultaneous detection of Glyphosate and AMPA suggests that drift during spraying operation is the main atmospheric source of Glyphosate and that resuspension from soil particles is minor. The present study offers one of the few report of Glyphosate, Glufosinate-ammonium, and AMPA in the air

Diurnal and Seasonal Variability of the Atmospheric Boundary-Layer Height in Marseille (France) for Mistral and Sea/Land Breeze Conditions

International audienceMarseille (France) is a city on the Mediterranean coast characterized by two specific wind patterns: mistral (northwesterly wind blowing above 10 m/s) and sea/land breezes (southwesterly wind during daytime/northeasterly wind during the nighttime, blowing below 6 m/s). For the first time, this study investigates the diurnal and seasonal variability in the atmospheric boundary-layer height (ABLH) in Marseille for both wind patterns. A 532 nm aerosol lidar was installed in the urban center in the summer of 2021. The lidar installed in the winter of 2021–2022 had an additional near-infrared channel at 808 nm. The ABLH was extracted from the lidar datasets using a Haar wavelet method. For well-established mistral conditions, the ABLH reached to about 1000 m and showed a diurnal amplitude of ~650 m in winter and 740 m in summer, with a morning growth rate limited by turbulence. During sea breeze situations, the ABLH maxima were lower in both seasons (300–600 m) due to the sea’s thermal inertia. During land breeze situations, ABLH minima were estimated to be lower than 150 m. In summer, the Haar method was unable to calculate them because of unpronounced aerosol layers. While the near-infrared channel gives better results, the polarization of the green channel allows us to understand the type of aerosols and thus the origin of the air mass; a combination of the two gives complementary information

Use of Polyphemus Plume in Grid model to reproduce the full chemistry and physics of Particulate matter in industrial plumes. Applications and validation for Refinery during the TEMMAS project "Teledetection, Measure, Modeling of Atmospheric pollutants on industrial Sites"

International audienceThe Polyphemus Plume-in-Grid (PinG) model, based on a 3D Eulerian model and a subgrid scaled Gaussian puff model was developed to represent the dispersion and transformation of air pollutants in industrial plumes. The PinG model computes the formation of secondary gases and PM in the plumes, resulting from the oxidation of emitted precursors in interaction with background pollutant concentrations. The model was improved to treat PM number concentrations, allowing a better representation of the ultra-fine fraction of PM concentrations. In comparison with the conventional CTM approach, this tool is able to provide a realistic assessment of the impacts of industrial sites in the first ten kilometers. To improve the validation of the Plume In Grid Model, from the stack to the ground, a research project called TEMMAS (TEledetection, Measure, Modeling of Atmospheric pollutants on industrial Sites) was supported by the French environment agency (ADEME). The project included two intensive measurement campaigns, which were conducted around a refinery in the south of France. The aim of these campaigns were to study the refinery PM microphysical signatures and its evolution with distance to the source in the first kilometers. During the campaigns different observation protocols of PM were deployed: • sample collection inside the principal stacks and around the refinery. • online measurements of microphysical properties of PM and trace gas concentrations; • optical measurement: airborne hyperspectral imagery in the reflective domain, According to the different techniques, two types of models were used, with different spatial resolutions, meteorological input (meso-scale meteorology or local measurements), and chemical transformations representations: • The Polyphemus Plume-in-Grid (PinG) model, which results are compared to measured PM in the vicinity of the refinery in terms of gas, PM mass and number concentrations, as a function of particle sizes and PM chemical compositions. • The Safety LAgrangian Model (SLAM), a lagrangian non reactive dispersion model using pre calculated CFD winds fields. The fine resolution (meter) allows to reproduce complex flows in industrial installations. This approach is better fitted for the comparison of the local scale plume dispersion with optical imaging

Improvement of PMF methodology using an extended suite of specific organic tracers : What benefits/what drawbacks ?

Receptor models (RMs) as Positive Matrix Factorization (PMF) have become, one of the most used methodology for PM source apportionment in Europe. Evidence for this is given by the recent common protocol for RMs users, proposed by JRC of the European Commision in 2014. These last decades, the chemical composition of Particulate Matter (PM) is increasingly important in order to understand their atmospheric behavior and their emission sources. With this respect, the interest in the individual organic constituents of PM has grown, all the more since most of them can also be used as tracers in source apportionment models. Currently, many research groups try to include additional chemical compounds as PMF input data to better constraint the particles emission sources. Indeed, the contribution made by organic tracers on the PMF output increases the ability to identify some PM sources. Several recent French programs were developed in this regard. For these programs PM have been collected on quartz filters over one year period at several site types, and a large chemical speciation has been performed on samples. In this presentation, a review of these PMF studies including a wide range of specific organic tracers is proposed. New organic markers such as polyols (arabitol, mannitol, sorbitol), methane sulfonic acid (MSA), hopanes, or PAH and sulfured PAH (BNT) were quantified for each site. These organic compounds allowed to improve the factor identification and the quantification of PM sources in PMF studies (Waked et al. 2014). The identified sources, comprise biogenic (marine and soil) factors, secondary aerosols (nitrate and sulfate factors), fresh and aged sea salt particles and various anthropogenic sources (industrial factor, traffic exhaust, biomass burning…). In a first part, the different sources and their chemical profiles (such as those presented in Figure 1) will be compared and discussed. The presentation will also focus on the benefits and the drawbacks to use organic compounds within PMF analysis. This will includes discussion on the sources clearly identified and the factors still presenting evident indication of mixing

Effect of mid-term drought on <i>Quercus pubescens</i> BVOCs' emission seasonality and their dependency on light and/or temperature

International audienceBiogenic volatile organic compounds (BVOCs) emitted by plants represent a large source of carbon compounds released into the atmosphere, where they account for precursors of tropospheric ozone and secondary organic aerosols. Being directly involved in air pollution and indirectly in climate change, understanding what factors drive BVOC emissions is a prerequisite for modeling their emissions and predict air pollution. The main algorithms currently used to model BVOC emissions are mainly light and/or temperature dependent. Additional factors such as seasonality and drought also influence isoprene emissions, especially in the Mediterranean region, which is characterized by a rather long drought period in summer. These factors are increasingly included in models but only for the principal studied BVOC, namely isoprene, but there are still some discrepancies in estimations of emissions. In this study, the main BVOCs emitted by Quercus pubescens – isoprene, methanol, acetone, acetaldehyde, formaldehyde, MACR, MVK and ISOPOOH (these three last compounds detected under the same m/z) – were monitored with a PTR-ToF-MS over an entire seasonal cycle during both in situ natural and amplified drought, which is expected with climate change. Amplified drought impacted all studied BVOCs by reducing emissions in spring and summer while increasing emissions in autumn. All six BVOCs monitored showed daytime light and temperature dependencies while three BVOCs (methanol, ace-tone and formaldehyde) also showed emissions during the night despite the absence of light under constant temperature. Moreover, methanol and acetaldehyde burst in the early morning and formaldehyde deposition and uptake were also punctually observed, which were not assessed by the classical temperature and light models