Chemical Transport Model CHIMERE Research Articles

Integrated air quality modeling for urban policy: A novel approach with olympus-chimere

This paper presents a novel approach to air quality modeling for megacities, focusing on the Paris region for the year 2009. The simulation is conducted by coupling the transport, energy demand, and emission model OLYMPUS with the atmospheric chemical transport model CHIMERE. OLYMPUS's emission calculations are based on the representation of an urban configuration, the simulation of a synthetic population, and the calculation of transport demand and energy consumption in buildings using an activity-based statistical approach. Emissions derived from this simulation, along with biogenic and additional industrial emissions, were used as input data in the CHIMERE model to predict pollutant concentrations. CHIMERE outputs were compared with observations from the local AIRPARIF air quality monitoring network, and with a reference simulation conducted using a benchmark bottom-up emission inventory. The results indicate that the platform provides a comprehensive representation of emissions and the resulting air quality. They also highlight the excellent representation of the spatial and temporal distribution of urban pollutant concentrations in comparison with both model and observational data. OLYMPUS tends to emit more primary pollutants than the reference emission inventory in the dense urban center. However, this often improves model scores for NO2, and these deviations remain within the uncertainty margins set for emission inventories. The approach to emission production, rooted in the connection between urban configuration and individual behaviors, allows for the exploration of innovative air quality scenarios centered on energy consumption practices. The validation of our results furnishes the OLYMPUS-CHIMERE coupling with a dependable framework for addressing numerous research inquiries related to the impact of urban policies on air quality.

Ozone Effects on Douro Vineyards under Climate Change

Tropospheric ozone (O3) levels in southern Europe have an increasing tendency, in close relation with the higher incidence of hot summers and heatwaves. Given that O3 is one of the most damaging pollutants for vegetation, known to affect productivity and quality of crops, it is necessary to develop more rigorous and consistent methods of risk assessment that consider climate change conditions. Studying the O3 deposition over the Douro Demarcated Region (DDR), which is one of the most productive wine areas in Portugal, and assessing its potential effects under a climate change scenario, was the purpose of this study. To that end, the chemical transport model CHIMERE, with a spatial resolution of 1 km2, fed by meteorological data from the WRF model, was applied for a recent past climate (2003 to 2005) and future mid-term (2049 and 2064) and long-term (2096 and 2097) scenarios. Simulations for future climate were performed considering: (i) only the climate change effect, and (ii) the effect of climate change together with future air pollutant emissions. The assessment of the potential damage in terms of wine productivity and quality (sugar content) was performed through analysis of O3 deposition and the application of concentration–response functions, based on AOT40 values. Modeling results show that a reduction in emission of O3 precursors can successfully decrease AOT40 levels in the DDR, but it is not enough to accomplish the European Commission target value for the protection of vegetation. If the emissions remain constant, the exposure–response functions indicate that, in the long-term, AOT40 levels could worsen wine productivity and quality.

Assessing Douro Vineyards Exposure to Tropospheric Ozone

Tropospheric ozone (O3) can strongly damage vegetation. Grapevines (Vitis vinifera L.), in particular, have intermediate sensitivity to ozone. Wine production is an important economic activity, as well as a pillar to the cultural identity of several countries in the world. This study aims to evaluate the risk of Douro vineyards exposure to ozone, by estimating its concentration and deposition in the Demarcated Region of Douro in Portugal. Based on an assessment of the climatology of the area, the years 2003 to 2005 were selected among the hottest years of the recent past, and the chemical transport model CHIMERE was used to estimate the three-dimensional field of ozone and its dry deposition over the Douro region with 1 km2 of horizontal resolution. Model results were validated by comparison with measured data from the European air quality database (AirBase). The exposure indicator AOT40 (accumulated concentration of ozone above 40 ppb) was calculated and an exposure–response function was applied to determine the grapevine risk to ozone exposure. The target value for the protection of vegetation established by the Air Quality Framework Directive was exceeded on most of the Douro region, especially over the Baixo Corgo and Cima Corgo sub-regions. The results of the exposure–response functions suggest that the productivity loss can reach 27% and that the sugar content of the grapes could be reduced by 32%, but these values are affected by the inherent uncertainty of the used methodology.

Urban aerosol assessment and forecast: Coimbra case study

The objective of this study is to explore the existing services at a regional scale and study their applicability to the assessment and forecast of air quality at the urban scale. Two approaches were evaluated to characterize urban background pollution levels from the regional operational forecast: (i) Copernicus Atmosphere Monitoring Service (CAMS) and (ii) Chemical Transport Model CHIMERE from the national forecast system. The local contribution from road traffic was analysed using transportation (VISUM) -emission (QTraffic) - dispersion (ADMS-Roads) modelling chain with 10 m grid resolution. The methodology was applied to Coimbra city to estimate PM10 concentrations for the period of one year (2018). In order to validate the model outputs against the daily observations, the FAIRMODE Delta Tool was applied separately for regional and urban scale. The results obtained for Coimbra satisfy the modelling performance criteria. However, both approaches used to characterize background concentrations underestimate PM10 levels. The modelling bias at urban traffic station is about 6 μg m−3 for annual mean concentration. Local highest contribution of road traffic to PM10 annual mean obtained with high grid resolution (10 m) achieves 22 μg m−3. Spatial distribution of PM10 concentrations highlights the limitations to characterize urban hot spots based on the measurements from only one traffic station available within the study area and used to validate the urban scale model.

Implementación de Mejoras Físicas y Químicas a un Sistema de Modelado de Calidad del Aire para la Argentina y su Validación, Utilizando Información Satelital.

La investigación y el monitoreo de calidad del aire fueron ganando iportancia en Argentina yLationamérica, principalmente en megaciudades donde la contaminación alcanza niveles críticos.Otro instrumento muy usado en el estudio de la composición atmosférica y sus procesos físicos yquímicos, y también para obtener el pronósstico de calidad de aire en una región, es un modelo de transporte químico. Este tipo de modelos estima las condiciones del aire que respiramos, la concentración de contaminantes en el nivel superficial y niveles superiores, y cómo sonconsumidos/producidos y transportados por las condiciones meteorológicas. El objetivo principal de la tesis es realizar mejoras en el sistema de modelado WRF-CHIMERE-EDGAR, ya implementado anteriormente en Argentina, que consideren una evaluación del sistema utilizando información satelital, y una implementación operativa para brindar pronóstico de calidad del aire a la población. El sistema se compone de un inventario de emisiones antropogénicas global EDGAR, el modelo de predicción numérica del tiempo WRF y el modelo de transporte químico CHIMERE. La evaluación del sistema fue realizada en términos de densidad diaria en columna total atmosférica de NO2, CO y espesor óptico de aerosoles, utilizando datos de los sensores OMI, MOPITT y MODIS, respectivamente. El dominio espacial definido incluye a toda la Argentina continental, y el temporal es de marzo a mayo del 2009 para evaluar NO2 en condiciones de emisiones regulares antropogénicas y al período diciembre 2016 a febrero 2017 para evaluar el destino de la emisión de contaminantes por incendios de vegetación en un gran evento en la Patagonia Nororiental. Para esto último, fue implementado el modelo de emisiones de incendios APIFLAME que estima la tasa de emisión para cada foco de incendios, en función de datos satelitales dinámicos y estáticos que brindan información sobre la ubicación, potencia radiativa, tipo de cobertura vegetal, cantidad de biomasa disponible y factores de emisión. La evaluación del sistema de modelado con información satelital da resultados optimistas en cuanto a la distribución espacial y temporal de los contaminantes presentes en la atmósfera, aunque aún hay una subestimación en las emisiones producto de los inventarios de emisiones antropogénicas y de incendios. Por otro lado, aún es necesaria una evaluación del perfil vertical de contaminantes. Finalmente, en el sitio de la CONAE http://meteo.caearte.conae.gov.ar/wrf/chimere.php ya se encuentra la implementación operativa del Pronóstico Experimental de Calidad del Aire WRF-CHIMERE-EDGAR, junto con la documentación descriptiva y publicaciones relacionadas; esperamos agregar a este sistema la implementación de las emisiones de incendios en los próximos meses.

A statistical physics approach to perform fast highly-resolved air quality simulations – A new step towards the meta-modelling of chemistry transport models

A methodology rested on model-based machine learning using simple linear regressions and the parameterizations of the main physics and chemistry processes has been developed to perform highly-resolved air quality simulations. The training of the methodology is (i) completed over a 6-month period using the outputs of the chemical transport model CHIMERE, and (ii) then applied over the subsequent 6 months. Despite rough assumptions, this new methodology performs as well as the raw CHIMERE simulation for daily mean concentrations of the main criteria air pollutants (NO2, Ozone, PM10 and PM2.5) with correlations ranging from 0.75 to 0.83 for the particulate matter and up to 0.86 for the maximum ozone concentrations. Some improvements are investigated to expand this methodology to several other uses, but at this stage the method can be used for air quality forecasting, analysis of pollution episodes and mapping. This study also confirms that including a minimum set of selected physical parameterizations brings a high added value on machine learning processes.

NO<sub><i>x</i></sub> emission estimates during the 2014 Youth Olympic Games in Nanjing

Abstract. The Nanjing Government applied temporary environmental regulations to guarantee good air quality during the Youth Olympic Games (YOG) in 2014. We study the effect of those regulations by applying the emission estimate algorithm DECSO (Daily Emission estimates Constrained by Satellite Observations) to measurements of the Ozone Monitoring Instrument (OMI). We improved DECSO by updating the chemical transport model CHIMERE from v2006 to v2013 and by adding an Observation minus Forecast (OmF) criterion to filter outlying satellite retrievals due to high aerosol concentrations. The comparison of model results with both ground and satellite observations indicates that CHIMERE v2013 is better performing than CHIMERE v2006. After filtering the satellite observations with high aerosol loads that were leading to large OmF values, unrealistic jumps in the emission estimates are removed. Despite the cloudy conditions during the YOG we could still see a decrease of tropospheric NO2 column concentrations of about 32 % in the OMI observations when compared to the average NO2 columns from 2005 to 2012. The results of the improved DECSO algorithm for NOx emissions show a reduction of at least 25 % during the YOG period and afterwards. This indicates that air quality regulations taken by the local government have an effect in reducing NOx emissions. The algorithm is also able to detect an emission reduction of 10 % during the Chinese Spring Festival. This study demonstrates the capacity of the DECSO algorithm to capture the change of NOx emissions on a monthly scale. We also show that the observed NO2 columns and the derived emissions show different patterns that provide complimentary information. For example, the Nanjing smog episode in December 2013 led to a strong increase in NO2 concentrations without an increase in NOx emissions. Furthermore, DECSO gives us important information on the non-trivial seasonal relation between NOx emissions and NO2 concentrations on a local scale.

Impact of dry deposition of semi-volatile organic compounds on secondary organic aerosols

Dry deposition of semi-volatile organic compounds (SVOC) is not currently treated in most chemical transport models of air quality and this omission has been identified as a possible major source of uncertainty. The effect of dry deposition of SVOC on the concentration of secondary organic aerosols (SOA) is investigated in summertime with the chemical transport model CHIMERE that simulates SOA concentrations by means of molecular SOA surrogate species. Omitting dry deposition could overestimate SOA concentrations by as much as 50%. This overestimation is larger during nighttime due to higher relative humidity.