Influence of the spatial resolution of satellite-derived vegetation parameters on the biogenic Volatile Organic Compounds (VOC) emission modeling

Vegetation is a natural source of Volatile Organic Compounds (VOC) that plays an important role in atmospheric chemistry. The main objective of the current study is to implement a model to quantify process-based VOC emissions from plants that focuses on the relationship between the sensitivity of VOC emission estimates to spatial resolution data, based on scientific knowledge and vegetation dynamics derived from satellite observations. The Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI) were elected to examine this issue using different resolutions of satellite-derived products: 22m from the DEIMOS-1 satellite, and 250m and 1000m provided by MODIS. The study is focused on an area of 80×80km2 in Portugal for 2011. Detailed land cover and meteorological data are also included in the emission quantification algorithm. The primary outcomes were determined using a multi-scale analysis showing spatial and temporal variations in the vegetation parameters and modeling results. The results confirm that the emissions model is highly sensitive to the spatial resolution of the satellite-derived data, resulting in about a 30% difference in total isoprene emissions for the study area

Seasonal Variability of Atmospheric Dust Over Cape Verde Islands.

International Congresso on Environmental Health (ICEH 2012). Lisboa, 29 Maio – 1 Junho

Temporal patterns and trends of particulate matter over Portugal: a long-term analysis of background concentrations

Air quality management regarding PM concentrations in the atmosphere is a complex problem to tackle. In this paper, we aim to characterize the temporal patterns and trends of aerosol background levels over Portugal. Hourly data from the national air quality monitoring network, gathered from 2007 to 2016, is analyzed using statistical methods. Data from 20 monitoring stations was processed to prepare datasets with different time scales, and results were grouped by their type of surrounding area (urban, suburban, or rural). Urban and suburban background sites are characterized by strong seasonal patterns, with higher monthly mean concentrations in winter than in summer. In contrast, rural background PM10 concentrations are highest during August and September. This study suggests that urban background concentrations are significantly influenced by anthropogenic non-combustion sources, which contribute to the coarser aerosol fraction (PMc). PMc is about 3 μg m−3 higher during weekdays than during Sundays, at urban sites. However, there is no clear relationship between the value of the PM2.5/PMc ratio and the type of monitoring station. During the 10-year period of study, a decrease of 1.83, 3.58, and 4.89%/year was registered in PM10 concentrations at Portuguese rural, urban, and suburban areas, respectively. Despite the higher decrease at suburban monitoring stations, those sites present the highest 10-year mean PM10 concentrations. This work provides an import insight on temporal variations of PM10, PM2.5, and PMc concentrations over Portugal and summarizes trends through the last decade, contributing to the discussion on sources and processes influencing those concentrations.Thanks also are due to the Portuguese Agency for the Environment (APA) and the Regional Coordination and Development Commissions (CCDRs) for their effort in establishing and maintaining the air quality monitoring sites used in this investigation.publishe

Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST_1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order to improve air pollution assessment

A comparative analysis of two highly spatially resolved European atmospheric emission inventories

A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling.This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS - High-Elective Resolution Modelling Emissions System - DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12×12km2was used to compare the three datasets spatially.The inter-comparative analysis was performed by source sector (SNAP - Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences.From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES-DIS for the first two sectors and to the distinct data sources that were used by the TNO and HERMES-DIS for road transport.Regarding the regression analysis, the greatest correlation occurred between the EMEParea and HERMES-DIS because the latter is derived from the first, which does not occur for the TNO emissions. The greatest correlations were encountered for agriculture NH3emissions, due to the common use of the CORINE Land Cover database for disaggregation. The point source emissions (energy industries, industrial processes, industrial combustion and extraction/distribution of fossil fuels) resulted in the lowest coefficients of determination. The spatial variability of SOxdiffered among the emissions that were obtained from the different disaggregation methods.In conclusion, HERMES-DIS and TNO are two distinct emission inventories, both very well discretized and detailed, suitable for air quality modelling. However, the different databases and distinct disaggregation methodologies that were used certainly result in different spatial emission patterns. This fact should be considered when applying regional atmospheric chemical transport models. Future work will focus on the evaluation of air quality models performance and sensitivity to these spatial discrepancies in emission inventories. Air quality modelling will benefit from the availability of appropriate resolution, consistent and reliable emission inventories

Analysis of long-range transport of aerosols for Portugal using 3D chemical transport model and satellite measurements

The objective of this work is to assess the contribution of long-range transport of mineral dust from North Africa to the air pollution levels in Portugal based on a combination of a modelling approach and satellite observations. The Comprehensive Air Quality Model (CAMx) was applied together with the updated Dust REgional Atmospheric Model (BSC-DREAM8b) to characterise anthropogenic and natural sources of primary aerosols as well as secondary aerosols formation. The modelling results, after their validation and bias removing process, have been used in combination with aerosol measurements provided by Ozone Monitoring Instrument (OMI), using OMAERUV Level-2 v003 product, aiming to better understand the advantages and shortcomings of both, satellite and modelling aerosol data. The data analysis is presented for Portugal for July 2006 focusing on aerosol optical depth (AOD) at 500 nm and aerosol type. Based on the modelling results, the importance of the long-range transport of mineral dust was demonstrated for the simulation days, achieving a 60% contribution to AOD levels. The mineral dust is affecting atmospheric layers up to 6 km but peak concentrations are presented at layers below 2 km. The model predicts a complex mixture of different types of aerosol for the pixels classified by OMI as "mineral dust" and "sulphates". Although a good agreement between the model outputs and OMI observations has been found in terms of the spatial pattern and AOD correlation is about 0.48 for mineral dust, several problems were identified. The model is systematically underestimating the aerosol concentration at near ground level in comparison with the air quality monitoring stations, while OMI is in general overestimating AOD for the analysed period based on the comparison with AERONET data. Additionally, misclassification of mineral dust for some geographical locations and discontinuity in AOD values along the coastal line at water/land interface in the OMI data are discussed

Emission and dispersion modelling of Lisbon air quality at local scale

The main objective of the paper is the study of air pollution in Lisbon city at local scale through the application of the modelling system developed at the University of Aveiro, linking two numerical tools: (i) the Transport Emission Model for Line Sources (TREM) and (ii) the Local Scale Dispersion Model (VADIS). Furthermore, analysis of the modelling system performance from the point of view of Quality Objectives established by the new European Legislation is one of the principal goals of the present work. TREM is designed to support quantification of emissions induced by road traffic. The emission rate is estimated as a function of average speed. Different technologies (engine type, model year) and engine capacities are distinguished. The model is particularly designed for line sources and is implemented in a Geographical Information System. VADIS is an integrated system, coupling a boundary layer flow module with a Lagrangian dispersion module, which was adapted to the simulation of urban air pollution, mainly in street canyon dispersion conditions. This model has the capability to support multi-obstacle and multi-source description, as well as time varying flow fields and time varying emissions. The modelling system TREM/VADIS was applied to the Lisbon downtown area and results concerning carbon monoxide concentration values are presented and analysed. Also, a comparison of simulated and measured data using European legislation criteria is discussed. This numerical tool has demonstrated a satisfactory performance to calculate the flow and dispersion around obstacles under variable wind conditions, providing important information to be used by decision-makers for air quality assessment

A Comparative analysis of two highly spatially resolved european atmospheric emission inventories

A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling. This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS – High-Elective Resolution Modelling Emissions System – DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12 × 12 km2 was used to compare the three datasets spatially. The inter-comparative analysis was performed by source sector (SNAP – Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences. From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES-DIS for the first two sectors and to the distinct data sources that were used by the TNO and HERMES-DIS for road transport. Regarding the regression analysis, the greatest correlation occurred between the EMEParea and HERMES-DIS because the latter is derived from the first, which does not occur for the TNO emissions. The greatest correlations were encountered for agriculture NH3 emissions, due to the common use of the CORINE Land Cover database for disaggregation. The point source emissions (energy industries, industrial processes, industrial combustion and extraction/distribution of fossil fuels) resulted in the lowest coefficients of determination. The spatial variability of SOx differed among the emissions that were obtained from the different disaggregation methods. In conclusion, HERMES-DIS and TNO are two distinct emission inventories, both very well discretized and detailed, suitable for air quality modelling. However, the different databases and distinct disaggregation methodologies that were used certainly result in different spatial emission patterns. This fact should be considered when applying regional atmospheric chemical transport models. Future work will focus on the evaluation of air quality models performance and sensitivity to these spatial discrepancies in emission inventories. Air quality modelling will benefit from the availability of appropriate resolution, consistent and reliable emission inventorie

Effect of silicon on the structure and low temperature strength of weld metal in welding low alloy steels with high-productivity basic coating electrodes

18.00; Translated from Russian (Avtom. Svarka 1987 (2) p. 1-6)SIGLEAvailable from British Library Document Supply Centre- DSC:9023.19(VR--3370)T / BLDSC - British Library Document Supply CentreGBUnited Kingdo