Combined effect of high-resolution land cover and grid resolution on surface NO2 concentrations

High-resolution air quality simulations are often performed using different nested domains and resolutions. In this study, the variability of nitrogen dioxide (NO2) concentrations estimated from two nested domains focused on Portugal (D2 and D3), with 5 and 1 km horizontal grid resolutions, respectively, was investigated by applying the WRF-Chem model for the year 2015. The main goal and innovative aspect of this study is the simulation of a whole year with high resolutions to analyse the spatial variability under the simulation grids in conjunction with detailed land cover (LC) data specifically processed for these high-resolution domains. The model evaluation was focused on Portuguese air quality monitoring stations taking into consideration the station typology. As main results, it should be noted that (i) D3 urban LC categories enhanced pollution hotspots; (ii) generally, modelled NO2 was underestimated, except for rural stations; (iii) differences between D2 and D3 estimates were small; (iv) higher resolution did not impact model performance; and (v) hourly D2 estimates presented an acceptable quality level for policy support. These modelled values are based on a detailed LC classification (100 m horizontal resolution) and coarse spatial resolution (approximately 10 km) emission inventory, the latter suitable for portraying background air pollution problems. Thus, if the goal is to characterise urban/local-scale pollution patterns, the use of high grid resolution could be advantageous, as long as the input data are properly represented.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020), SusTEC (LA/P/0007/2020) and CESAM (UIDP/50017/2020 + UIDB/50017/2020 + LA/P/0094/2020), and for the contract granted to Joana Ferreira (2020.00622.CEECIND). Thanks are also due for financial support to OleaChain project “Skills for sustainability and innovation in the value chain of traditional olive groves in the Northern Interior of Portugal” (NORTE-06-3559-FSE-000188).info:eu-repo/semantics/publishedVersio

Wildfires impact on surface nitrogen oxides and ozone in Central Italy

AbstractA summer campaign in Central Italy was carried out to study the impact of fire emissions on the mixing ratios of surface trace gases. Observations with a selective and sensitive instrument that uses the laser induced fluorescence technique for direct measurements of nitrogen dioxide (NO2), show a significant increase of NO2 mixing ratios, in the evening, when a fire plume reached the observations site. The increase of NO2 mixing ratios is well correlated (R=0.83) with that of particulate matter (PM), which is one of the primary product of forest and grassland fires. The tight correlation between NO2 and PM is used to improve the performance of a statistical regression model to simulate the observed O3, and to highlight the effect of fire emissions on the O3 mixing ratios. The statistical regression model of O3 improves in terms of performance (bias reduction of 77% and agreement enhancement of 10% for slope and correlation coefficient) when PM2.5 is included as additional input and proxy of the fire emissions among the usual input parameters (meteorological data and NO2 mixing ratios). A case study, comparing observed and modeled O3 in different days (with and without fire plume), suggests an impact of fire emissions on the O3 mixing ratios of about 10%

Analysis of Summer Ozone Observations at a High Mountain Site in Central Italy (Campo Imperatore, 2388 m a.s.l.)

Tropospheric ozone (O3) is an important atmospheric pollutant and climate forcer. The Mediterranean basin is a hot-spot region in terms of short-term O3 distribution, with frequent episodes of high tropospheric O3, especially during summer. To improve the characterisation of summer O3 variability in the Mediterranean area, during the period 6–27 August 2009 an experimental campaign was conducted at Campo Imperatore, Mt Portella (CMP), a high mountain site (2,388 m a.s.l.) located in the central Italian Apennines. As deduced from analysis of atmospheric circulation, the measurement site was significantly affected by air masses originating over the Mediterranean basin, which affected the measurement site for 32 % of the time. Analysis of average values and diurnal and day-to-day variability revealed that CMP O3 observations (average value 60.0 ± 5.1 ppbv) were comparable with measurements at other European mountain stations, indicating a prevalent effect of meteorological conditions and atmospheric transport on the synoptic scale. In fact, only a small "reverse" diurnal variation typically characterises diurnal O3 variability because of local thermal wind circulation, which sporadically favours transport of air masses rich in O3 from the foothill regions. Statistical analysis of five-day back-trajectory ensembles indicates that synoptic-scale air-mass transport from the Mediterranean Sea usually results in decreasing O3 concentrations at CMP, whereas the highest hourly O3 values are mostly associated with air masses from central continental Europe, eastern Europe, and northern Italy. High O3 concentrations are also related to downward air-mass transport from higher altitudes. Comparison of in-situ O3 variability with tropospheric O3 satellite-based measurements reveals similar features of the two data sets. Together with the results from back-trajectory analysis, this indicates that CMP measurements might usefully improve characterisation of broad-scale O3 variability over the central Mediterranean basin

Monitoring the last Apennine glacier: recent in situ campaigns and modelling of Calderone glacial apparatus

The Calderone glacier is at present the most southern glacier in Europe (42° 28' 15’’ N). The little apparatus (about 20.000 m2 in surface area) has been giving an interesting response both to short- and long-term climatic variations which resulted in a considerable reduction in surface area and volume. The glacial apparatus is split into two ice bodies (glacierets) since 2000. The two glacierets are located in a deep northward valley below the top of the Corno Grande (2912 m asl) in the centre of the Gran Sasso d’Italia mountain range (Central Italy). Such glacial apparatus has been subjected to a strong reduction, with a loss of total surface area of about 50% and thickness of about 65%with respect to the hypothetical size (about 105.00 m2 and 55 m at the Little Ice Age). Since early 90s the Calderone glacier has been subjected to several multidisciplinary field campaigns to monitor and evaluate its role as an environmental indicator in the framework of global warming. Starting from historical series related to more than a century of records, the variability of the different glacier properties has been estimated by using classical geomorphologic methods as well as in situ and remote sensing techniques. In particular, the last field campaigns, in 2015, 2016 and 2019, have been carried out using Ground Penetrating Radar equipped with different antenna frequencies, drone-based survey, snow pit measurements and chemical-physical sampling. The measurement campaigns have been complemented by a regional climate analysis, spanning the last fifty years, and snowpack modelling initialized with microphysical snow data (e.g., snow density, crystal shape and size, hardness). The snowpack chemical analyses include the main and trace elements, soluble inorganic and organic ions, EC/OC and PAH, with different spatial resolution depending on the analytes. We present here the methodological approach used and some preliminary results

Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII Phase-2

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.Peer reviewedFinal Published versio

Improving the deterministic skill of air quality ensembles

<p><strong>Abstract.</strong> Forecasts from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as the model itself (e.g. physical parameterization, chemical mechanism). Multi-model ensemble forecasts can improve the forecast skill provided that certain mathematical conditions are fulfilled. We demonstrate through an intercomparison of two dissimilar air quality ensembles that unconditional raw forecast averaging, although generally successful, is far from optimum. One way to achieve an optimum ensemble is also presented. The basic idea is to either add optimum weights to members or constrain the ensemble to those members that meet certain conditions in time or frequency domain. The methods are evaluated against ground level observations collected from the EMEP and Airbase databases.<br><br> The two ensembles were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Verification statistics shows that the deterministic models simulate better O<sub>3</sub> than NO<sub>2</sub> and PM<sub>10</sub>, linked to different levels of complexity in the represented processes. The ensemble mean achieves higher skill compared to each station's best deterministic model at 39 %–63 % of the sites. The skill gained from the favourable ensemble averaging has at least double the forecast skill compared to using the full ensemble. The method proved robust for the 3-monthly examined time-series if the training phase comprises 60 days. Further development of the method is discussed in the conclusion.</p&gt

Impacts of air pollutants from rural Chinese households under the rapid residential energy transition

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent

Radiation absorbing aerosol

This a study about the impact of radiation-absorbing (or light-absorbing) aerosols (black carbon, dust, brown carbon) on the climate, through the direct effect and deposition on the snow. The results have been reported in these publications: Tuccella, P., Curci, G., Pitari, G., Lee, S., & Jo, D. S. ( 2020). Direct radiative effect of absorbing aerosols: sensitivity to mixing state, brown carbon and soil dust refractive index and shape. Journal of Geophysical Research: Atmospheres, 125, https://doi.org/10.1029/2019JD030967 Tuccella, P., Pitari, G., Colaiuda, V., Raparelli, E., and Curci, G.: Present-day radiative effect from radiation-absorbing aerosols in snow, Atmos. Chem. Phys., 21, 6875–6893, https://doi.org/10.5194/acp-21-6875-2021, 2021