45 research outputs found

    Detecting nitrogen oxide emissions in Qatar and quantifying emission factors of gas-fired power plants : a 4-year study

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    Nitrogen oxides (NOx = NO + NO2), produced in urban areas and industrial facilities (particularly in fossil-fuel-fired power plants), are major sources of air pollutants, with implications for human health, leading local and national authorities to estimate their emissions using inventories. In Qatar, these inventories are not regularly updated, while the country is experiencing fast economic growth. Here, we use spaceborne retrievals of nitrogen dioxide (NO2) columns at high spatial resolution from the TROPOspheric Monitoring Instrument (TROPOMI) to estimate NOx emissions in Qatar from 2019 to 2022 with a flux-divergence scheme, according to which emissions are calculated as the sum of a transport term and a sink term representing the three-body reaction comprising NO2 and hydroxyl radical (OH). Our results highlight emissions from gas power plants in the northeast of the country and from the urban area of the capital, Doha. The emissions from cement plants in the west and different industrial facilities in the southeast are underestimated due to frequent low-quality measurements of NO2 columns in these areas. Our top-down model estimates a weekly cycle, with lower emissions on Fridays compared to the rest of the week, which is consistent with social norms in the country, and an annual cycle, with mean emissions of 9.56 kt per month for the 4-year period. These monthly emissions differ from the Copernicus Atmospheric Monitoring Service global anthropogenic emissions (CAMS-GLOB-ANT_v5.3) and the Emissions Database for Global Atmospheric Research (EDGARv6.1) global inventories, for which the annual cycle is less marked and the average emissions are respectively 1.67 and 1.68 times higher. Our emission estimates are correlated with local electricity generation and allow us to infer a mean NOx emission factor of 0.557 t NOx GWh−1 for the three gas power plants in the Ras Laffan area

    The impact of using assimilated Aeolus wind data on regional WRF-Chem dust simulations

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    Land–atmosphere interactions govern the process of dust emission and transport. An accurate depiction of these physical processes within numerical weather prediction models allows for better estimating the spatial and temporal distribution of the dust burden and the characterisation of source and recipient areas. In the presented study, the ECMWF-IFS (European Centre for Medium-Range Weather Forecast – Integrated Forecasting System) outputs, produced with and without the assimilation of Aeolus quality-assured Rayleigh–clear and Mie–cloudy horizontal line-of-sight wind profiles, are used as initial or boundary conditions in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate 2-month periods in the spring and autumn of 2020, focusing on a case study in October. The experiments have been performed over the broader eastern Mediterranean and Middle East (EMME) region, which is frequently subjected to dust transport, as it encompasses some of the most active erodible dust sources. Aerosol- and dust-related model outputs (extinction coefficient, optical depth and concentrations) are qualitatively and quantitatively evaluated against ground- and satellite-based observations. Ground-based columnar and vertically resolved aerosol optical properties are acquired through AERONET sun photometers and PollyXT lidar, while near-surface concentrations are taken from EMEP. Satellite-derived vertical dust and columnar aerosol optical properties are acquired through LIVAS (LIdar climatology of Vertical Aerosol Structure) and MIDAS (ModIs Dust AeroSol), respectively. Overall, in cases of either high or low aerosol loadings, the model predictive skill is improved when WRF-Chem simulations are initialised with the meteorological fields of Aeolus wind profiles assimilated by the IFS. The improvement varies in space and time, with the most significant impact observed during the autumn months in the study region. Comparison with observation datasets saw a remarkable improvement in columnar aerosol optical depths, vertically resolved dust mass concentrations and near-surface particulate concentrations in the assimilated run against the control run. Reductions in model biases, either positive or negative, and an increase in the correlation between simulated and observed values was achieved for October 2020.</p

    Timely Update of Emission Inventories with the Use of Satellite Data

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    Cyprus is located in the eastern Mediterranean, an environmentally intriguing area that is subject to complex air pollution conditions, and has to be prepared for many climatic challenges. Air quality assessment and forecasting is an essential tool in strengthening the country’s adaptation strategy, providing relevant information to sectors such as agriculture and tourism, helping reduce health related financial and human life costs, as well as establishing a core national priority axis for knowledge outreach to neighbouring countries. The use of current and next genera- tion satellite information can open a new area in operational forecasting and scientific assessment of air quality and emissions in this complex region with past, current and projected societal, financial and geo-political influences. In this work we identify and elaborate on the discrepancies of emission inventories in the region and the use of satellite data for their timely update. Utilizing the EDGAR-HTAP emission invento- ries compiled by the Joint Research Center for the year 2010, we use a model-based methodology to update them based on satellite-derived trends. Initially we produce a model-based concentration-vertical column density (VCD) relation derived from sensitivity tests of NOx emission fluxes in the WRF-Chem regional atmospheric model. Consequently, we translate the monthly trends obtained by satellite obser- vations for the period 2010–2015 to produce updated emission inventories. Model simulations with the current and modified emission inventory are used to assess the discrepancies derived

    Uncertainties in estimates of mortality attributable to ambient PM<sub>2.5</sub> in Europe

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    The assessment of health impacts associated with airborne particulate matter smaller than 2.5 μm in diameter (PM2.5) relies on aerosol concentrations derived either from monitoring networks, satellite observations, numerical models, or a combination thereof. When global chemistry-transport models are used for estimating PM2.5, their relatively coarse resolution has been implied to lead to underestimation of health impacts in densely populated and industrialized areas. In this study the role of spatial resolution and of vertical layering of a regional air quality model, used to compute PM2.5 impacts on public health and mortality, is investigated. We utilize grid spacings of 100 km and 20 km to calculate annual mean PM2.5 concentrations over Europe, which are in turn applied to the estimation of premature mortality by cardiovascular and respiratory diseases. Using model results at a 100 km grid resolution yields about 535 000 annual premature deaths over the extended European domain (242 000 within the EU-28), while numbers approximately 2.4% higher are derived by using the 20 km resolution. Using the surface (i.e. lowest) layer of the model for PM2.5 yields about 0.6% higher mortality rates compared with PM2.5 averaged over the first 200 m above ground. Further, the calculation of relative risks (RR) from PM2.5, using 0.1 μg m−3 size resolution bins compared to the commonly used 1 μg m−3, is associated with ±0.8% uncertainty in estimated deaths. We conclude that model uncertainties contribute a small part of the overall uncertainty expressed by the 95% confidence intervals, which are of the order of ±30%, mostly related to the RR calculations based on epidemiological data

    Costs and benefits of agricultural ammonia emission abatement options for compliance with European air quality regulations

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    Background In Europe, ammonia (NH3) emissions strongly contribute to fine particulate matter (PM2.5) pollution and associated premature human mortality. The National Emission Ceilings Directive 2016/2284/EU has set an obligation for all European Union countries to reduce the NH3 emissions by 6%, relative to 2005, by 2020. This study aims to assess the costs and benefits of four NH3 emission abatement options for the compliance of the agricultural sector with the commitments of the European air quality regulatory framework. A regional atmospheric model (WRF/Chem) was used to assess the effects of regulating NH3 emissions reductions on PM2.5 concentrations over Europe. Non-market valuation techniques (value of statistical life) were used to monetize the associated health outcomes. Results We calculated that 16 out of the 28 EU member states exceeded their 2020 NH3 emission ceilings in 2016. The highest exceedances from the 2020 emission commitment level occurred in Latvia (15%), Germany (12%) and the UK (12%). Simulation of the required NH3 emission reduction by WRF/Chem showed that relatively large reductions in PM2.5 concentrations occur over central-western Europe and the UK. The largest health benefits (> 5% reduction in premature mortality) were found for Scandinavia. The economic benefit from avoided premature deaths over Europe amounts to 14,837 M€/year. The costs of four NH3 emission abatement options, where each would fully achieve the required emission reduction, range from 80 M€/year for low nitrogen feed to 3738 M€/year for low-emission animal housing, with covered manure storage (236 M€/year) and urea fertilizer application (253 M€/year), in between. Conclusion Our analysis indicates that the costs of compliance by the agricultural sector with the commitments of the European air quality regulations are much lower than the economic benefit. Thus, much more ambitious reduction commitments for NH3 emissions could be applied by the EU-28. The monetization of the health benefits of NH3 emission abatement policies and the assessment of the implementation costs can help policy-makers devise effective air pollution control programmes

    Density currents as a desert dust mobilization mechanism

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    The formation and propagation of density currents are well studied processes in fluid dynamics with many applications in other science fields. In the atmosphere, density currents are usually meso-I2/I3 phenomena and are often associated with storm downdrafts. These storms are responsible for the formation of severe dust episodes (haboobs) over desert areas. In the present study, the formation of a convective cool pool and the associated dust mobilization are examined for a representative event over the western part of Sahara desert. The physical processes involved in the mobilization of dust are described with the use of the integrated atmospheric-air quality RAMS/ICLAMS model. Dust is effectively produced due to the development of near surface vortices and increased turbulent mixing along the frontal line. Increased dust emissions and recirculation of the elevated particles inside the head of the density current result in the formation of a moving &quot;dust wall&quot;. Transport of the dust particles in higher layers - outside of the density current - occurs mainly in three ways: (1) Uplifting of preexisting dust over the frontal line with the aid of the strong updraft (2) Entrainment at the upper part of the density current head due to turbulent mixing (3) Vertical mixing after the dilution of the system. The role of the dust in the associated convective cloud system was found to be limited. Proper representation of convective processes and dust mobilization requires the use of high resolution (cloud resolving) model configuration and online parameterization of dust production. Haboob-type dust storms are effective dust sources and should be treated accordingly in dust modeling applications

    Modelling study of the atmospheric composition over Cyprus

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    In this study the online meteorological and chemical transport model “Weather Research and Forecasting coupled with Chemistry” (WRF/Chem) is implemented over Cyprus and evaluated against ground-based air quality and meteorological observations. Hourly O3 concentrations are strongly overestimated and a reduction in the lateral boundaries of ozone by 30% improved model agreement with observations. Utilization of grid spacing closer to the resolution of the emission data leads to an improvement in the simulation of air pollutants, while further reduction of the grid spacing mostly impacts the model performance related to meteorological parameters. The method of speciation of volatile organic compounds can also affect model results. Reduction of NOx emissions can reduce fine particulate (PM2.5) levels relatively effectively due to the important role of nitrate over Cyprus. The present case study indicates that the performance of the WRF/Chem model is reasonable for air quality and meteorological variables over Cyprus when boundary conditions are cautiously adjusted or improved, while there is a need to pursue a high-resolution local emission inventory

    Disease burden and excess mortality from coal-fired power plant emissions in Europe

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    We studied the contribution of coal-fired power plant (CPP) emissions (SO2 and NOx) to air pollution levels and annual excess mortality by cardiovascular and respiratory diseases in Europe, based on fine particulate matter (PM2.5) concentrations computed with a regional atmospheric chemistry-transport model. The health burden of European CPP emission-induced PM2.5, estimated with the Global Exposure Mortality Model, amounts to at least 16 800 (CI95 14 800–18 700) excess deaths per year over the European domain. We identified an underestimation of the emissions magnitude and correcting for it doubles CPP-attributed annual excess mortality to 33 900 (CI95 33 000–37 600) per year. Due to the non-linearity of exposure-responses, especially at relatively low concentrations, these estimates represent lower limits of possible health benefits for the EU-28 states. CPP emission phase-out would avoid 18 400 (CI95 16 000–20 500) excess deaths annually assuming background PM2.5 levels of 10 μg m−3, 25 500 (CI95 22 600–28 200) per year if pollution levels from other sources are reduced by 50% in parallel, and 105 900 (CI95 89 900–121 700) deaths by drastically reducing anthropogenic pollution from other sources to 2.4 μg m−3 that represents the threshold for health impacts. Depending on the emission scenario, large health gains can be achieved from the phase-out of CPP emissions, which calls for coordinated air pollution control strategies at the European level

    Air quality modelling over the Eastern Mediterranean: Seasonal sensitivity to anthropogenic emissions

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    We employ the online coupled WRF/Chem model to study air pollution over the eastern Mediterranean during winter and summer. We utilize three nested domains with horizontal resolutions down to 2 km, over the area of interest. Dust, sea-salt, and biogenic emissions are calculated online, while anthropogenic emissions are based on the EDGAR-HTAP global emission inventory. A new, up-to-date and high spatiotemporal resolution anthropogenic emission inventory for the high-resolution domain has been implemented. Its impact on the model skill to simulate the concentrations of atmospheric pollutants at background and urban sites over Cyprus, being strongly affected by polluted air masses of different origin and composition over the year, is examined. The model output from three simulations over the innermost domain using the EDGAR emission inventory, the new emission inventory, and zero emissions is compared with measurements from background and urban ground stations in Cyprus. The implementation of the updated emission inventory results in about 5% reduction in the normalized mean bias between the modelled and observed CO mixing ratios. Underestimation in wintertime CO mixing ratios and PM2.5 concentrations is attributed to missing residential heating sources from the emission inventory, while the absence of a PM2.5 re-suspension mechanism leads to underestimation in PM2.5 concentrations during summer. The normalized mean bias between the modelled and observed NOX mixing ratios at the urban sites is reduced from -67% to -29% and from -51% to -10% for the winter and summer, respectively, In sine with this, the overestimation in O3 mixing ratios was reduced from 45% to 28% during the winter and from 25% to 19% during summer. Taking into account the diurnal variability in the emission inventory is found to be crucial for the simulation of the daily profiles of NOX and O3 at urban sites, which is important both for policy making and air quality modelling
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