Abstract

Abstract. We determined NOx emissions from Paris in summer 2009 and winter 2009/2010 by applying the closed integral method (CIM) to a large set of car multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements performed within the framework of the MEGAPOLI project (http://megapoli.dmi.dk/). MAX-DOAS measurements of the tropospheric NO2 vertical column density (VCD) were performed in large circles around Paris. From the combination of the observed NO2 VCDs with wind fields, the NO2 influx into and the outflux from the encircled area was determined. The difference between the influx and outflux represents the total emission. Compared to previous applications of the CIM, the large number of measurements during the MEGAPOLI campaign allowed the investigation of important aspects of the CIM. In particular, the applicability of the CIM under various atmospheric conditions could be tested. Another important advantage of the measurements during MEGAPOLI is that simultaneous atmospheric model simulations with a high spatial resolution (3 × 3 km2) are available for all days. Based on these model data, it was possible to test the consistency of the CIM and to derive information about favourable or non-favourable conditions for the application of the CIM. We found that in most situations the uncertainties and the variability in the wind data dominate the total error budget, which typically ranges between 30 and 50 %. Also, measurement gaps and uncertainties in the partitioning ratio between NO and NO2 are important error sources. Based on a consistency check, we deduced a set of criteria on whether measurement conditions are suitable or not for the application of the CIM. We also developed a method for the calculation of the total error budget of the derived NOx emissions. Typical errors are between ±30 and ±50 % for individual days (with one full circle around Paris). From the application of the CIM to car MAX-DOAS observations we derive daily average NOx emissions for Paris of 4.0 × 1025 molec s−1 for summer and of 6.9 × 1025 molec s−1 in winter. These values are a factor of about 1.4 and 2.0 larger than the corresponding emissions derived from the application of the CIM to the model data, using the Toegepast Natuurwetenschappelijk Onderzoek (TNO) MEGAPOLI emission inventory, in summer and winter, respectively. Similar ratios (1.5 and 2.3 for summer and winter, respectively) were found for the comparison with the Monitoring Atmospheric composition and climate III (MACC-III) emission inventory. The highest NOx emissions were found during some cold days in February. Enhanced domestic heating and a reduced conversion efficiency of catalytic converters might contribute to these enhanced NOx emissions.

Highlights

  • Emission estimates of atmospheric trace species are important as input for model simulations and for the quantification of air pollution

  • We applied the closed integral method (CIM) for the determination of the NOx emissions from Paris based on a large set of car MAXDOAS measurements during two measurement campaigns in summer 2009 and winter 2009/2010

  • The CIM was applied to car MAX-DOAS measurements made in large circles around Paris with diameters of about 20 to 40 km

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Summary

Introduction

Emission estimates of atmospheric trace species are important as input for model simulations and for the quantification of air pollution. In contrast to top–down approaches based on satellite observations (e.g. Ghude eta al., 2013 and references therein), emission estimates based on car MAXDOAS measurements are independent of model simulations. They depend much less on assumptions about the atmospheric lifetimes. In winter 2009/2010, NOx emissions could be quantified on 22 days Another important aspect of this study is that highly resolved (3 × 3 km2) model simulations were available for all days of the car MAX-DOAS measurements.

MEGAPOLI campaigns and car MAX-DOAS measurements
CHIMERE model simulations
Calculation of the NO2 fluxes
Effect of measurement gaps along the circles
Partitioning correction
Effect of NOx lifetime
Emission upscaling using nighttime lights
Error estimation
Errors caused by gaps in measurements
Errors caused due to upscaling
Errors caused by the variability in the wind field
Errors caused by the lifetime correction
Errors caused by the partitioning correction
Consistency check based on CHIMERE model simulations
Application to measurement data
Findings
Conclusions and perspectives
Full Text
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