Nudging technique for scale bridging in air quality/climate atmospheric composition modelling

Abstract. The interaction between air quality and climate involves dynamical scales that cover a very wide range. Bridging these scales in numerical simulations is fundamental in studies devoted to megacity/hot-spot impacts on larger scales. A technique based on nudging is proposed as a bridging method that can couple different models at different scales. Here, nudging is used to force low resolution chemical composition models with a run of a high resolution model on a critical area. A one-year numerical experiment focused on the Po Valley hot spot is performed using the BOLCHEM model to asses the method. The results show that the model response is stable to perturbation induced by the nudging and that, taking the high resolution run as a reference, performances of the nudged run increase with respect to the non-forced run. The effect outside the forcing area depends on transport and is significant in a relevant number of events although it becomes weak on seasonal or yearly basis

Numerical vs. turbulent diffusion in geophysical flow modelling

Numerical advection schemes induce the spreading of passive tracers from localized sources. The effects of changing resolution and Courant number are investigated using theWAF advection scheme, which leads to a sub-diffusive process. The spreading rate from an instantaneous source is compared with the physical diffusion necessary to simulate unresolved turbulent motions. The time at which the physical diffusion process overpowers the numerical spreading is estimated, and is shown to reduce as the resolution increases, and to increase as the wind velocity increases

Assessment of the numerical diffusion effect in the advection of a passive tracer in BOLCHEM

The effects of the numericalsc heme implemented in the advection equation of BOLCHEM have been quantified with reference to the diffusion of a passive tracer. An equivalent horizontal diffusion coefficient has been measured and is found to be dependent on wind field and resolution

Corrigendum to "Effects of resolution on the relative importance of numerical and physical horizontal diffusion in atmospheric composition modelling" published in Atmos. Chem. Phys., 10, 2737–2743, doi:10.5194/acp-10-2737-2010, 2010

No abstract available

A cooperation project in lesotho: Renewable energy potential maps embedded in a webgis tool

In this paper the background, activities undertaken, and main outcomes of the cooperation project “Renewable Energy Potential Maps for Lesotho” are presented. The project was launched in 2018 in fulfilment of the Paris Agreement by the Italian Ministry for the Environment and the Lesotho Ministry of Energy and Meteorology, with the aim to facilitate the local Government in the future planning and development of renewable energy in the country. A user-oriented WebGIS platform was utilised to share and analyse the outcomes of the project: a hydrological map to recognize potential areas for power generation; a wind atlas to identify specific sites with the most potential for wind energy generation; a solar radiation map, defining the different levels of radiation intensity, useful to localise sites for photovoltaic production. Human capacity building and technology transfer were carried out to strengthen the local expertise and ability to manage and plan renewable energy sources exploitation. The implementation of the project was based on a fruitful collaboration between scientists and stakeholders at the same time giving the local authorities a useful dataset and tool for renewable energy growth in Lesotho

Vegetation Effects on Air Pollution: A Comprehensive Assessment for Two Italian Cities

The role of urban vegetation in urban air quality is usually assessed by considering only the pollutant removal capacity of the plants. This study aims to show, for the first time, the effects of vegetation on air pollutant concentrations through its effects on meteorology, separately from its biogenic emissions. It also investigates how air quality changes when only biogenic emissions are altered by using plants with different emission factors, as well as the potential effects of introducing new vegetation into urban areas. These assessments were conducted using atmospheric modelling systems currently employed for air quality forecasting and planning, configured specifically for the cities of Bologna and Milan. Simulations were performed for two representative months, July and January, to capture summer and winter conditions, respectively. The variability in air concentrations of ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10) within the municipal boundaries was assessed monthly. When evaluating the impact of future vegetation, changes in temperature, wind speed, and relative humidity were also considered. The results indicate that vegetation influences air quality more significantly through changes in meteorological conditions than through biogenic emissions. Changes in biogenic emissions result in similar behaviours in O3 and PM10 concentrations, with the latter being affected by the changes in the concentrations of secondary biogenic aerosols formed in the atmosphere. Changes in NO2 concentrations are controlled by the changes in O3 concentrations, increasing where O3 concentrations decrease, and vice versa, as expected in highly polluted areas. Meteorologically induced vegetation effects also play a predominant role in depositions, accounting for most of the changes; however, the concentrations remain high despite increased deposition rates. Therefore, understanding only the removal characteristics of vegetation is insufficient to quantify its effects on urban air pollution

The impact of the spatial resolution of vegetation cover on the prediction of airborne pollen concentrations over northern Italy

Accurate pollen forecasting models can help the self-management of allergic respiratory diseases. Our study introduces and validates, for the first time, a pollen modelling system covering the Veneto Region (Italy) at the 3 km spatial resolution for 2019. The model simulated the pollen dispersion, diffusion and deposition processes, using vegetation cover (VC) maps, phenological pollen emission algorithms, and meteorological forecasting. We have specifically analysed the influence of the spatial resolution of VC maps on predicted airborne pollen concentrations for alder, birch, olive, grass, and ragweed. Two VC datasets were used: CAMS VC: the European CAMS dataset at ca. 10 km horizontal resolution; detailed VC: high-resolution datasets (from 250 m to 1 km spatial resolution). Predicted daily averaged concentrations obtained with CAMS and detailed VC were compared to the observations collected at 15 monitoring stations using model performance indicators and pollen seasonal-derived parameters. A stratified analysis assessed performance variations in lowland versus mountain environments. The results showed a reduction of the root mean square error (RMSE) for alder and birch pollen using the detailed VC (detailed VC vs. CAMS VC: 15.7 vs. 133.6; 17.8 vs. 52.5 p/m3, respectively), while higher RMSE resulted for grass (24.5 vs. 20.7 p/m3). Similar RMSEs were obtained for olive and ragweed pollen (3.8 vs. 4.0; 3.9 vs. 3.9 p/m3, respectively). Results from the differences in Seasonal Pollen Integrals (SPIn) were consistent with the RMSE patterns. The onset of pollen seasons was more accurately predicted than their end. The general improvement of pollen predictions obtained with the detailed VC was particularly evident in the mountains. Incorporating data from detailed vegetation maps into atmospheric dispersion models has significantly improved predictions for arboreal pollen (alder, birch, olive), especially in complex surfaces where high-resolution input data is crucial

AMS-MINNI national air quality simulation on Italy for the calendar year 2015. Annual air quality simulation of MINNI Atmospheric Modelling System: results for the calendar year 2015 and comparison with observed data

Il sistema modellistico atmosferico (AMS) del modello integrato nazionale MINNI, sviluppato da ENEA nell’ambito dell’omonimo progetto finanziato dal Ministero dell’Ambiente e della Tutela del Territorio e del Mare (MATTM), fornisce su tutto il territorio nazionale e su lungo periodo, tipicamente un anno, dati meteorologici e di qualità dell’aria con risoluzione temporale oraria e con risoluzione spaziale orizzontale di 4 km. Dal 2010, in adempimento del D.Lgs. 155/2010, ENEA è tenuta a elaborare ogni 5 anni, e per la prima volta con riferimento all’anno 2010, simulazioni modellistiche della qualità dell’aria su base nazionale e a rendere disponibili i risultati di tali elaborazioni. In questo rapporto sono presentati i risultati della simulazione nazionale di AMS-MINNI relativa all’anno 2015, insieme alla loro validazione tramite il confronto con i dati di misura disponibili sul territorio nazionale. Allo scopo di fornire una valutazione oggettiva della qualità dei risultati della simulazione, basata su criteri condivisi dalla comunità scientifica, la validazione è stata effettuata seguendo l’approccio e la metodologia proposti da FAIRMODE e, in dettaglio, utilizzando il software DELTA Tool. L’analisi dei risultati ha mostrato complessivamente la buona qualità dei campi di concentrazioni simulati. In particolare, tutti i Criteri di Qualità delle performances sono risultati soddisfatti per O3 e PM2.5. Sia punti di forza sia margini di miglioramento sono invece emersi dalla validazione di NO2 e PM10 che tendono ad essere globalmente sottostimati, come del resto accade comunemente nello stato dell’arte della modellistica a scala regionale. In riferimento all’assessment di qualità dell’aria dell’anno meteorologico 2015 nell’ambito del D.Lgs. 155/2010, in accordo con i dati di misura raccolti da ISPRA, diverse criticità sono emerse per quanto riguarda il rispetto dei limiti di legge, in particolare in riferimento alla media giornaliera di PM10, al massimo delle medie mobili su 8 ore di O3 e alle medie annuali di NO2 e PM2.5. I campi prodotti sono ora disponibili sia come condizioni iniziali e al contorno per studi a scala locale (come da D.Lgs. 155/2010), sia come dati in ingresso per analisi d’impatto a scala nazionale.The Atmospheric Modelling System (AMS) of the Italian National Integrated Assessment Model MINNI, developed by ENEA and funded by the Italian Ministry for the Environment, Land and Sea (IMELS), may compute anthropogenic, biogenic and other natural emissions, meteorological parameters and air quality concentrations with hourly time resolution at a spatial resolution of 4 km over the Italian territory. Since 2010 and every five years, ENEA is required to carry out national air quality simulations and to make the simulation results available for supporting air quality policy, in fulfillment of Legislative Decree 155/2010 (implementing EU Directive 2008/50/EC). This report presents the AMS-MINNI national simulation for the year 2015, along with its validation by comparisons with available measurement data. In order to provide an objective assessment of the quality of AMS-MINNI results, with respect to criteria currently adopted and applied by the scientific community, FAIRMODE evaluation methodology and criteria, consolidated in the DELTA Tool software, were used for the validation. An overall good quality of simulated concentrations fields was obtained. More in detail, all the Model Performance Criteria turned out to be satisfied for O3 and PM2.5. Concerning NO2 and PM10, both strengths and weaknesses are highlighted; in particular AMS-MINNI tends to underestimate both of them, as shown by other state of the art regional air quality models. Concerning 2015 air quality assessment in the framework of Legislative Decree 155/2010, AMS-MINNI simulation, in agreement with monitoring data collected by ISPRA, pointed out the non-compliance with EU requirements, particularly for daily PM10, 8h daily maximum O3 and yearly NO2 and PM2.5. The simulated concentration fields are now available to be used as initial and boundary conditions for local scale air quality assessments (according to Legislative Decree 155/2010) and as input data for impact studies at the national level

Analisi di backtrajectories a supporto dell'interpretazione di dati di monitoraggio di qualità dell'aria. Un'applicazione di M-TraCe nell'ambito del Progetto CAMPANIA TRASPARENTE

Lo studio della provenienza delle masse d’aria, ossia la ricostruzione delle traiettorie in arrivo (backward trajectories) in un punto di interesse, è utilizzato a supporto di molte tipologie di studi di qualità dell’aria e alcuni modelli sono disponibili in letteratura per il calcolo delle backward trajectories al livello globale. Il laboratorio di inquinamento atmosferico di ENEA ha recentemente sviluppato MTraCE (MINNI module for Trajectories Calculation and statistical Elaboration), un nuovo tool per il calcolo e l’elaborazione statistica di backward trajectories sul dominio italiano predisposto per l’accesso diretto alla base dati meteorologica italiana, prodotta nell’ambito del progetto MINNI. Con lo scopo di mostrarne le potenzialità e la replicabilità in contesti diversi, è illustrata in questo rapporto una metodologia di applicazione del tool M-TraCE a supporto dell’interpretazione dei dati di monitoraggio integrato della qualità dell’aria: a titolo di esempio, sono riportati i risultati ottenuti su un sito di monitoraggio in territorio campano localizzato nel comune di Acerra. È stata realizzata la caratterizzazione climatologica della circolazione prevalente nel sito in esame calcolando un ampio campione di traiettorie relative a cinque diverse annualità (1999, 2003, 2005, 2007, 2010), disponibili nella base dati MINNI a risoluzione spaziale di 4 km. Per supportare l’interpretazione dei dati di monitoraggio raccolti negli anni 2016 e 2017, sono stati calcolati anche i campi meteorologici relativi a quei periodi e su questi sono state calcolate ed elaborate le backward trajectories per l’analisi della circolazione specifica. Successivamente, a partire da un approccio già presente in letteratura, è stata proposta una nuova metodologia per l’identificazione dell’area di influenza di un sito basata sul calcolo di un indicatore spaziale sintetico. L’esempio illustrato dimostra in maniera esauriente le principali caratteristiche e la potenzialità della metodologia sviluppata, che costituisce un valido supporto per l’analisi della variabilità spaziale, l’identificazione dei punti più critici e l’interpretazione di dati sperimentali di una determinata area di studio.The analyses of the provenance of air masses, namely backward trajectories calculations, are commonly used to support air quality studies and several models are available in literature. The ENEA air quality laboratory has recently developed M-TraCE (MINNI module for Trajectories Calculation and statistical Elaboration), a new tool for the calculation and statistical elaboration of backward trajectories over the Italian territory, with direct access to the MINNI meteorological database. In this report a methodology for the application of M-TraCE tool to support the interpretation of experimental air quality data is illustrated, aiming at demonstrating its potentiality and portability. As an example, the results of M-TraCE application to a monitoring site located near Acerra, Campania Region, are described; indeed, the Acerra site is of valuable interest to evaluate the exposition of the population to atmospheric pollution and the impacts on agricultural ecosystems. The characterization of the climatological circulation was carried out considering the years 1999, 2003, 2005, 2007, 2010 available in the MINNI meteorological database at spatial resolution of 4 km; moreover, in order to support the interpretation of experimental data collected in the years 2016 and 2017, meteorological fields and backward trajectories concerning those years were also computed. Then, by extending a scientific approach referenced in literature, a new methodology is proposed for the evaluation of the site region of influence, based on the computation of a synthetic spatial index. The illustrated example comprehensively shows the potentiality of the applied methodology, which represents a valuable tool for the analysis of spatial variability, the identification of critical sites and the interpretation of experimental data in the framework of air pollution concerns

An atmospheric modelling system for Lebanon

Viene qui descritto lo sviluppo e l’applicazione di un sistema modellistico atmosferico messo a punto per il territorio del Libano (AMS-Libano) nell’ambito dell’assistenza tecnica fornita da ENEA al Ministero dell’Ambiente Libanese tra il 2013 ed il 2014. AMS-Libano rappresenta uno strumento modellistico di riferimento per le politiche di qualità dell’aria in Libano, permettendo di approfondire ipotesi di gestione della qualità dell’aria in maniera efficace ed economica. Il sistema modellistico nasce dall’esperienza di ENEA nel progetto MINNI in supporto al Ministero Italiano dell’Ambiente e della Tutela del Territorio e del Mare sulle politiche nazionali di qualità dell’aria e nell’ambito di esperienze di ricerca su confronti di modelli a livello Europeo. La catena modellistica unisce un modello meteorologico di mesoscala (RAMS), un elaboratore di inventari di emissioni (EMMA) e un modello di trasporto e chimica in atmosfera (FARM). Le concentrazioni tridimensionali di inquinanti atmosferici (NO2, O3, PM10, PM2.5, SO2) sono calcolate considerando le dinamiche dell’atmosfera e le reazioni chimiche fra gas e la speciazione del particolato con una risoluzione spaziale di 5 Km sul Libano. L’inventario atmosferico delle emissioni di sorgenti antropogeniche per il Libano, compilato dal CEREA (Francia) e dall’Università Saint Joseph (Libano), è stato adattato per AMS-Libano e integrato con nuove informazioni su grandi sorgenti puntuali e simulazioni specifiche di emissioni biogeniche. La mappe delle concentrazioni medie annuali di NO2, O3, PM10, PM2.5 e SO2 mostrano la distribuzione dell’inquinamento atmosferico su tutto il dominio di studio ed evidenziano situazioni di superamento dei limiti in vigore nell’Unione Europea, considerati come riferimento. Il sistema è stato testato su un caso di base rappresentato dalle emissioni del 2010, e su due scenari emissivi: nuovi limiti ai valori emissivi per i cementifici e nuove configurazioni funzionali per le centrali elettriche situate a Zouk e Jyeh. La messa a punto di un sistema modellistico atmosferico per il Libano ha fornito un quadro completo delle aree più inquinanti della regione dove le misure di mitigazione appaiono più urgenti, i piani di sviluppo devono essere rivisti o devono essere applicati valori limite delle emissioni più stringenti. I valori di concentrazione forniscono anche un caso base per gli studi di valutazione di impatto ambientale e per la proposta di nuove attività con impatto in atmosfera. Inoltre il sistema modellistico è in grado di valutare l’efficacia di nuovi scenari di emissione, dati per esempio dal cambiamento di valori limite di emissioni delle diverse sorgenti, dalla trasformazioni pianificate di alcune centrali o da future attività estrattive off-shore.The development and application of a dedicated atmospheric modelling system (AMS) on the territory of Lebanon is here described as part of technical assistance provided by ENEA to the Lebanese Ministry of Environment during 2013 and 2014. AMS-Lebanon aims to provide a reference modelling tool for air quality policy in Lebanon, allowing to investigate hypotheses on air quality management in a quick and cost-effective way. The modelling system is derived from ENEA’s experience in the MINNI project, supporting to the Italian Ministry of Environment for national air pollution policies, and in research exercises involving model intercomparisons at European scale. The modelling chain connects a mesoscale meteorological model (RAMS), an emission inventory processor (EMMA) and a Chemical Transport Model (FARM). Three dimensional concentrations of atmospheric pollutants (NO2, O3, PM10, PM2.5, SO2) are calculated keeping into account atmospheric dynamics and chemical reactions among gas and particulate species, on a 5 km horizontal resolution grid covering Lebanon. The Atmospheric Emission Inventory of Anthropogenic Sources for Lebanon, compiled by CEREA (France) and University of Saint Joseph (Lebanon), was adapted to AMS Lebanon and integrated with new information on large point sources and dedicated simulation of biogenic VOC emissions. The maps of average annual concentrations for NO2, O3, PM10, PM2.5 and SO2 show the distribution of atmospheric pollution all over the study domain and point out the hot-spots of exceedances of EU limit values, taken as reference. The system has been tested on a base case, represented by the 2010 emission inventory of Lebanon, and two scenarios: new emission limit values for cement industries and new functional layouts for the power plants in Zouk and Jyeh. The setup of the AMS modelling system over Lebanon provided a comprehensive picture of the most polluted areas of the country, where mitigation measures are more urgent, development plans have to be reconsidered or more stringent emission limit values have to be applied. The concentration values can serve as the base case for environmental impact assessments studies and for new activities proposed with atmospheric impact. Moreover the modelling system is able to provide responses on effectiveness of new emissions scenarios, like changes of Emission Limit Values for the various sources, planned power plants transformation, future offshore drilling activities