Analysis of PM10 measurements and comparison with model results during 2007 wildfire season

Transcription

1 Analysis of PM10 measurements and comparison with model results during 2007 wildfire season Autori S. Finardi, M. Mircea*, G.Righini* * ENEA/UTVALAMB-AIR Riferimento imento ARIANET R May 2011 ARIANET s.r.l. via Gilino, Milano ITALY tel Cap. Soc i.v. R.E.A. n Codice Fiscale e Partita IVA

2 Relazione ARIANET R Autori: S. Finardi, M. Mircea*, G.Righini* * ENEA/UTVALAMB-AIR ARIANET R Pagina I

3 Table of contents 1 Introduction Analysis of measured and modeled concentrations during selected days Analysis approach Analysis results Concluding remarks Acknowledgements ARIANET R Pagina II

4 1 Introduction Working on the development of a modelling system to estimate the air quality impact of fires at national scale over Italy, we face the problem to identify the areas affected by pollutants emissions from fires and to quantify the fraction of measured concentrations that can be attributed to fires. One of the main difficulties in building a modelling approach to describe fire impact is the lack of knowledge of the effective impact of fires emissions both in terms of area of impact and in concentration contribution. Detailed measurements of PM components allowing to perform a detailed source apportionment are rare, usually tied to field campaign covering a small areas and do not permit a nation-wide analysis. This short text reports the exploration of the possibility to give a first estimate of the impact of fires on the basis of PM10 measurements from the regional air quality network and available model simulations for anthropogenic sources (FARM simulations in QualeAria configuration), Sahara dust contribution (SKIRON/Dust simulations) and forest fires emissions (FARM simulations in QualeAria configuration with 2 emission data sets elaborated independently by ENEA and FMI starting from different MODIS satellite information). The target period of the analysis is summer 2007, that has been identified as one of the worst years ever recorded for fires in Italy. The month that concentrated the largest number of fires and the widest burnt area has been July; in more detail, most fires occurred during the second half of the month with the maximum number of events concentrated from day 23 to day 28. Out of the mentioned period, a second intense fires episode occurred during the last part of August. The analysis of Sahara dust and forest fires episodes occurred during July-August 2007 proved the frequent superposition of the episodes and didn t permit to identify periods with clear independent impact of forest fires. This behavior is not peculiar of the selected episodes but is a general feature of the analyzed phenomena over the Mediterranean basin, where meteorological circulation conditions favoring Sahara dust transport are one of the triggers of major forest fires events. A selection of the available PM10 stations has been operated applying the following criteria, that can be considered preliminary : in northern Italy, where the number of available measurements was large, only stations classified as background (both urban and rural) have been retained; in the central and southern Italy regions PM10 concentrations measured by the different stations have been briefly analyzed and cross-compared to select those apparently less affected by local features and more representative of large portion of the territory (Figure 1). The selection attempted to avoid superposition of stations and can be pushed forward to reduce the number of stations in overpopulated areas and maybe eliminate urban stations located within large conurbations. ARIANET R Pagina 3

5 Figure 1. All available PM measurements from regional air quality networks (left) and selected stations classified depending on their localization (right). ARIANET R Pagina 4

6 2 Analysis of measured and modeled concentrations during selected days To verify the possibility to derive information on the possible impact of fires from the cross comparison of measured concentrations and model results 3 different days have been analyzed: 17, 24, 26 July, when the following conditions have been recorded: 1. 17/07/2007: similar PM concentrations measured all over Italy, with values in the range 10-50; Sahara dust impact on the Alpine region; begin of the fire period with few small active fires, possible impact of fires from Balkans /07/2007: low PM concentrations over northern Italy, high values over the center/south; relevant Sahara dust impact over central-southern Italy; worst day of the fire season with highest number of fires of large size recorded /07/2007: low PM concentrations over northern Italy, high values in a few locations in the center/south; residual Sahara dust impact over the far southern Italy; relevant fires in Italy and in the Balkans. Easterly flow over southern Adriatic sea. 2.1 Analysis approach The approach of the analysis is mainly phenomenological and based on the following steps: analyze pm distribution over Italy compare with FARM simulation with anthropogenic emissions only compare with SKIRON Dust surface concentration fields compute residuals obtained from measured concentrations (FARM+SKIRON fields) verify residuals distribution and identify areas with anomalous high residuals check compatibility of anomalous residuals areas with areas of impact identified by concentration fields produced by farm with fires emission estimated by ENEA and FMI. 2.2 Analysis results The presentation of results starts from July 24, characterized by maximum fires emissions and relevant Sahara dust contribution, and proceeds later to days 26 and 17 when Fires emissions are weaker and desert dust contribution nearly negligible. To make comparison easier, FARM concentrations due to fires emissions estimated by ENEA have been multiplied by 3, while FARM concentrations due to fires emissions estimated by FMI have been multiplied by 0.5. This arbitrary approach is justified by the attempt to individuate the area of impact and it keeps into account that fires emission modelling in FARM is still to be tuned for Italy. 24/07/2007 Low PM10 daily average concentrations (mainly within the range µg/m 3 ) are measured over northern Italy (Figure 3a) due to a favorable meteorological circulation condition carrying westerly flow in the upper layers and light cloudiness (Figure 2). The rest of the peninsula remains free of cloud under the influence of a high pressure ridge and is affected by high PM10 concentrations ARIANET R Pagina 5

7 reaching values larger that 80 µg/m 3 (Figure 3a). Relevant Sahara dust transport is detected by satellite images. FARM simulation (with anthropogenic emissions only, Figure 3b) predicts the concentration gradient observed from northern to southern Italy due to meteorological effects. The concentration range is slightly underestimated over northern Italy and maximum values predicted over southern Italy reach 40 µg/m 3. SKIRON predicts an impact of Sahara dust over the whole country with surface daily average concentrations of PM10 ranging from few µg/m 3 to more than 30 µg/m 3 over Calabria and Sicily (Figure 3c). The superposition of the sum of concentration fields of anthropogenic and Sahara origin with local measurements shows good agreement for concentrations over northern Italy (yellow and cyan colors in Figure 3d) and an underestimation of the high values observed over central/southern Italy. It is worth noticing the anomaly of stations located in Campania and Molise, all of them measuring low concentrations in contrast with all the regional network in the area. This behavior is hardly understandable due to the large scale features of desert dust load affecting the area, that makes very unlikely to have plume split events capable to leave parts of the territory out of the impact. The analysis of residuals (Figure 4a) confirms the agreement of model concentration field over northern Italy, where light green/gray squares indicate that the model is slightly over/under the measurement and alternated green and gray squares indicate that the model is among measurements. High residual are concentrated in 5 anomalous areas: Marche, Abruzzo/Umbria, northern Sardegna, Puglia and western Sicily (with residuals ranging from 20 to 60 µg/m 3 ). The comparison of residuals with areas affected by fires concentrations (Figure 4b, c) shows that high concentrations observed in Puglia, Abruzzo, Sicilia and Sardinia can be justified by the impact of large fires affecting the areas. It is impressive the hit of the plume simulated over northern Sardinia on 2 stations measuring high concentrations, while it can be noticed that ENEA/MODIS emissions miss fires in southern Sardinia whose occurrence is not detected by monitors but it is proved by satellite images (Figure 4b,c,d). The high PM10 concentrations and corresponding residuals in Marche region seem not justifiable by fires contribution. Figure 2. 24/07/2007: 500Hpa geopotential and surface pressure fields on at 00:00 UTC (left) and meteosat image at 12:00 UTC (right). ARIANET R Pagina 6

8 Figure 3. PM10: 24/07/2007 measured concentrations (top left), FARM with anthropogenic emissions (top right), SKIRON Dust (bottom left), FARM+SKIRON vs measuremets (bottom right). ARIANET R Pagina 7

9 Figure 4. Residual PM10 concentrations [measured-(farm anthropogenic + SKIRON)]: 24/07/2007 (top left), comparison with FARM-ENEA-MODIS Fires contribution (top right), comparison with FARM-FMI-FAS Fires contribution (bottom left), satellite image of Sardinia (bottom right). 26/07/2007 The whole Italian peninsula is under the effect of Azores anticyclone and experiencing fair weather and cloudless sky (Figure 5). Weak easterly winds characterizes the lower atmospheric layers over the Adriatic sea and coastal regions. ARIANET R Pagina 8

10 Low PM10 concentrations are recorded over northern Italy and in background locations. Concentration values exceed 30 µg/m 3 only in large urban areas (e.g. Rome and Florence) and in a few small areas in central/southern Italy (Figure 6a). FARM simulation of anthropogenic emissions show low concentrations all over Italy, with daily average concentrations exceeding 20 µg/m 3 only around Milan and Taranto areas (Figure 6b). The Sahara dust plume has over passed the Italian peninsula moving southbound and a residual weak impact can affect only the southernmost regions as shown by SKIRON simulation (Figure 6c). The superposition of the sum of concentration fields of anthropogenic and Sahara origin with local measurements shows agreement with stations measuring low concentrations all over Italy (green and cyan colors in Figure 6d) with tendency to underestimation over central Italy. The observed agreement is confirmed by the analysis of residuals (Figure 7a) where light green/gray squares indicate that the model is near to the measurements. The analysis of high residual distribution allows to individuate 3 anomalous areas, with residuals ranging from 20 to 60 µg/m 3 : central-southern Puglia, Lazio-Abruzzo and southern Sicily coast (Figure 7a). It has to be noticed that a lower positive residuals characterizes nearly all the stations in Tuscany and Marche regions. The comparison of residuals with areas affected by fires concentrations (Figure 7b, c) shows that southern Puglia, Lazio-Abruzzo can be influenced by fires active in those areas, Moreover the presence of easterly flow can expose Puglia to the contribution of forest fires plumes from Balkan fires. This possible contribution, that is supported by FARM simulations (Figure 7c), it is suggested by satellite images too (Figure 7d). No relevant impact of forest fires is foreseen by FARM simulations over Tuscany and Marche. Large differences can be observed on concentration distribution due to the different fires emissions employed, in particular, FMI emission data have no fires in Sardinia while it has an active fire in Emilia-Romagna. Figure 5. 26/07/2007: 500HPa geopotential and surface pressure fields on at 00:00 UTC (left) and meteosat image at 12:00 UTC (right). ARIANET R Pagina 9

11 Figure 6. PM10: 26/07/2007 measured concentrations (top left), FARM with anthropogenic emissions (top right), SKIRON Dust (bottom left), FARM+SKIRON vs measuremets (bottom right). ARIANET R Pagina 10

12 Figure 7. Residual PM10 concentrations [measured-(farm anthropogenic + SKIRON)]: 26/07/2007 (top left), comparison with FARM-ENEA-MODIS Fires contribution (top right), comparison with FARM- FMI-FAS Fires contribution (bottom left), satellite image of southern Adriatic see with smoke from Balkan fires (bottom right). 17/07/2007 The Italian peninsula is influenced by an high pressure of African origin with very weak pressure gradient near the surface (Figure 8a), that causes fair weather with clear sky conditions and favors summer stagnation episodes (Figure 8b). ARIANET R Pagina 11

13 Similar PM10 concentrations are measured all over Italy, with values in the range µg/m 3 in remote/background locations and max values in the range µg/m 3 in major urban sites and other peak areas. (Figure 9a). FARM simulation shows daily average concentrations compatible with background locations measurements with maximum values reaching 30 µg/m 3 over the Po Valley and 20 µg/m 3 over the rest of Italy (Figure 9b). The impact of Sahara dust is limited to the Alpine region of northern Italy (Figure 9c, this area of impact is confirmed even by DREAM model forecast). The superposition of the sum of concentration fields of anthropogenic and Sahara origin with local measurements confirms the agreement with stations measuring low concentrations (yellow and cyan colors in Figure 9d). The reasonable agreement is confirmed by the analysis of residuals (Figure 10a) where light green/gray squares indicate that the model is slightly over/under the measurement and alternated green and gray squares indicate that the model is among measurements. The analysis of high residual distribution allows to individuate 3 anomalous areas: northern Sardegna, northern Puglia and Campania (with residuals ranging from 20 to 60 µg/m 3 ) and, with larger uncertainty a central Italy area. It has to be noticed that from previous analysis we have doubts on reliability of concentrations measured by Campania stations. The comparison of residuals with areas affected by fires concentrations (Figure 10b, c) shows that northern Sardegna and Puglia can be affected by fire contribution, while central Italy and Campania conditions are less evident. It has to be taken into account that available satellite images (Figure 10d) suggest that advection of fires plumes from Balkans fires over the Adriatic see towards Italian coasts, that could contribute to PM concentrations in Puglia. This possible contribution could be underestimated by our simulation due to limits in local wind field modeling. Figure 8. 17/07/2007: 500HPa geopotential and surface pressure fields on at 00:00 UTC (left) and meteosat image at 12:00 UTC (right). ARIANET R Pagina 12

14 Figure 9. PM10: 17/07/2007 measured concentrations (top left), FARM with anthropogenic emissions (top right), SKIRON Dust (bottom left), FARM+SKIRON vs measuremets (bottom right). ARIANET R Pagina 13

15 Figure 10. Residual PM10 concentrations [measured-(farm anthropogenic + SKIRON)]: 17/07/2007 (top left), comparison with FARM-ENEA-MODIS Fires contribution (top right), comparison with FARM-FMI-FAS Fires contribution (bottom left), satellite image with indication of Sahara dust plume over Sardinia and central/northern Italy and smoke from Balkan fires over south Adriatic and Ionian see (bottom right). ARIANET R Pagina 14

16 3 Concluding remarks The phenomenological analysis presented tries to identify the areas where contribution to air quality from forest fires can be identified and to provide a first evaluation of the quantitative contribution to PM10 concentration that can be caused by fires. The comparison of measured concentrations with available model simulations for anthropogenic emissions and Sahara dust allowed to correlate areas where anomalous high concentrations where observed with relevant fires detected by MODIS satellite data. The possible contribution of forest fires to PM10 concentrations is estimated in to be in the range µg/m 3 over areas that can have the scale of km for large fires. Concerning fires emission evaluation and dispersion modeling we have to notice that: the quantitative estimation of emissions has a large intrinsic uncertainty (up to 1 order of magnitude); the effective possibility to describe fires effects is tied to fires identification provided by satellite products, different products of the same satellite (MODIS) provide a different fires mapping; ENEA-MODIS emissions seem underestimated; FMI-FAS emissions seem overestimated; The emission height has to be tuned (we presently used FMI assumptions that are suitable for Nordic regions and not effective for Mediterranean). 4 Acknowledgements The authors would like to acknowledge the collaboration with FMI for forest fires emission and dispersion modelling started within COST Action ES0602. In particular we thank Mikhail Sofiev, Janne Hakkarainen and Jaakko Kukkonen. ARIANET R Pagina 15