This paper presents the findings of a 12-year study on radon conducted from January 2011 to December 2022 at the Giordan Lighthouse station on the island of Gozo, Malta. Located in the Central Mediterranean, Gozo’s strategic position enables effective monitoring of air mass movements between Africa and Europe (from south to north) and between Europe and Central Asia (from west to east). Our research involves an analysis of seasonal and diurnal variations in radon levels, alongside analysis of relevant meteorological variables, clustering of air mass back trajectories, and assessment of local and remote radon production. The findings provide critical insights into the dynamics of atmospheric radon, which are significant not only for the Maltese islands, but also for enhancing our understanding of transcontinental radon transport in the Central Mediterranean, a region that has remained largely unexplored.

Background The Maltese islands are subject to substantial climate variability, with implications for ecosystems and human activities. This study leverages a 26-year dataset from the Giordan Lighthouse Background Monitoring Station (GL) on the island of Gozo to analyse short-term climate variability and its alignment with broader regional tendencies. Methods Hourly meteorological data collected from 1997 to 2022, including wind speed, wind direction, air temperature, relative humidity, and air pressure, were analysed. The study examined diurnal and annual cycles, probability distribution functions, and climate indices to characterise local climate dynamics. Qualitative comparisons were made to existing findings based in Malta to corroborate the results. Results The analysis revealed pronounced seasonal variability in all parameters. Rising air temperatures were detected, consistent with regional warming tendencies. Humidity and wind conditions showed seasonal shifts aligning with observations from other regional monitoring stations. The high-resolution dataset also captured fine-scale temporal patterns, reinforcing the critical value of localised, long-term meteorological monitoring for understanding climatic shifts. Conclusions This study underscores the value of long-term meteorological datasets in detecting climate variability, including a clear warming pattern and seasonal shifts in temperature, humidity, and wind conditions. Continuous monitoring and improved data reliability are essential for enhancing climate assessments and supporting effective adaptation strategies in the Maltese Islands.

Background The Maltese islands are subject to substantial climate variability, with implications for ecosystems and human activities. This study leverages a 26-year dataset from the Giordan Lighthouse Background Monitoring Station (GL) on the island of Gozo to analyse short-term climate variability and its alignment with broader regional tendencies. Methods Hourly meteorological data collected from 1997 to 2022, including wind speed, wind direction, air temperature, relative humidity, and air pressure, were analysed. The study examined diurnal and annual cycles, probability distribution functions, and climate indices to characterise local climate dynamics. Qualitative comparisons were made to existing findings based in Malta to corroborate the results. Results The analysis revealed pronounced seasonal variability in all parameters. Rising air temperatures were detected, consistent with regional warming tendencies. Humidity and wind conditions showed seasonal shifts aligning with observations from other regional monitoring stations. The high-resolution dataset also captured fine-scale temporal patterns, reinforcing the critical value of localised, long-term meteorological monitoring for understanding climatic shifts. Conclusions This study underscores the value of long-term meteorological datasets in detecting climate variability, including a clear warming pattern and seasonal shifts in temperature, humidity, and wind conditions. Continuous monitoring and improved data reliability are essential for enhancing climate assessments and supporting effective adaptation strategies in the Maltese Islands.

Atmospheric new particle formation (NPF) is a naturally occurring phenomenon, during which high concentrations of sub-10 nm particles are created through gas to particle conversion. The NPF is observed in multiple environments around the world. Although it has observable influence onto annual total and ultrafine particle number concentrations (PNC and UFP, respectively), only limited epidemiological studies have investigated whether these particles are associated with adverse health effects. One plausible reason for this limitation may be related to the absence of NPF identifiers available in UFP and PNC data sets. Until recently, the regional NPF events were usually identified manually from particle number size distribution contour plots. Identification of NPF across multi-annual and multiple station data sets remained a tedious task. In this work, we introduce a regional NPF identifier, created using an automated, machine learning based algorithm. The regional NPF event tag was created for 65 measurement sites globally, covering the period from 1996 to 2023. The discussed data set can be used in future studies related to regional NPF.

Long-term data analysis of the hourly ozone volume fractions in the middle of the Mediterranean Seawas carried out covering a period of 22 years. It was noticed that the amount of ozone during this period very rarely exceeded the recommended upper limit value of 80 ppb and that the amount of tropospheric ozone in the area is rather low. Fourier data analysis shows the presence of only a seasonal cycle in ozone concentrations. Statistical analysis of the data is showing a slightly negative trend in ozone concentrations of −0.46 ± 0.08 ppb/year for average values and a slightly higher negative trend of −0.54 ± 0.11 ppb/year for the 95th percentile values. These results obtained through simple linear regression were confirmed using the more appropriate Mann–Kendall test. The possible quadratic trend was not observed for the whole series of data. Air mass trajectories were calculated for those days in the year with the highest pollution, indicating that during those days horizontal air transfer, in most cases, brings the air mass from the North and from Sicily in Southern Italy.

The northern wetland methane emission estimates have large uncertainties. Inversion models are a qualified method to estimate the methane fluxes and emissions in northern latitudes but when atmospheric observations are sparse, the models are only as good as their a priori estimates. Thus, improving a priori estimates is a competent way to reduce uncertainties and enhance emission estimates in the sparsely sampled regions. Here, we use a novel way to integrate remote sensing soil freeze/thaw (F/T) status from SMOS satellite to better capture the seasonality of methane emissions in the northern high latitude. The SMOS F/T data provide daily information of soil freezing state in the northern latitudes, and in this study, the data is used to define the cold season in the high latitudes and, thus, improve our knowledge of the seasonal cycle of biospheric methane fluxes. The SMOS F/T data is implemented to LPX-Bern DYPTOP model estimates and the modified fluxes are used as a biospheric a priori in the inversion model CarbonTracker Europe-CH4. The implementation of the SMOS F/T soil state is shown to be beneficial in improving the inversion model's cold season biospheric flux estimates. Our results show that cold season biospheric CH4 emissions in northern high latitudes are approximately 0.60 Tg lower than previously estimated, which corresponds to 17% reduction in the cold season biospheric emissions. This reduction is partly compensated by increased anthropogenic emissions in the same area (0.23 Tg), and the results also indicates that the anthropogenic emissions could have even larger contribution in cold season than estimated here.

Giordan Lighthouse, located on the island of Gozo in the Malta-Sicily Channel within the central Mediterranean region, is ideally located to study the primary sources of atmospheric pollution. A total of 10 years of data have been accumulated from the reactive gas and greenhouse gas detectors and the aerosol analyzers found at this Global Atmosphere Watch (GAW) regional station. The data has been evaluated, resulting in trends in emissions from shipping recorded within the same region coming to the fore. The other source of emissions that was evident within the recorded data originated from Mt. Etna, located on the island of Sicily and representing the highest active volcano in Europe. The aim of this paper is to investigate the effect of ship emissions on trace gases and aerosol background measurements at Giordan Lighthouse, including the putative influence of COVID-19 on the same emissions. The model used to evaluate ship emissions was the Ship Traffic Emission Assessment Model (STEAM). From trace gas measurements at Giordan Lighthouse, a slowly decreasing trend in sulfur oxide (SOx) and nitrogen oxide (NOx) emissions was noted. To better understand the air quality results obtained, the STEAM model was fed, as an input, an Automatic Identification System (AIS) dataset to describe the vessel activity in the area concerned. This study also investigates the effects of the COVID19 pandemic on marine traffic patterns within the area and any corresponding changes in the air quality. Such an analysis was carried out through the use of SENTINEL 5 data.

We present a global distribution of surface methane (CH4) emission estimates for 2000–2012 derived using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, anthropogenic and biospheric CH4 emissions are simultaneously estimated based on constraints of global atmospheric in situ CH4 observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH4 to surface in situ observations, vertical profiles of CH4 made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH4) from the Total Carbon Column Observing Network (TCCON), and XCH4 from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH4 is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000–2012 are 516 ± 51 Tg CH4 yr−1, with an increase of 18 Tg CH4 yr−1 from 2000–2006 to 2007–2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations ( < 2 Tg CH4 yr−1 difference), and much smaller than suggested by EDGAR v4.2 FT2010 inventory (33 Tg CH4 yr−1), which was used for prior anthropogenic emission estimates. The result is in good agreement with other published estimates from inverse modelling studies (16–20 Tg CH4 yr−1). However, this study could not conclusively separate a small trend in biospheric emissions (−5 to +6.9 Tg CH4 yr−1) from the much larger trend in anthropogenic emissions (15–27 Tg CH4 yr−1). Finally, we find that the global and North American CH4 balance could be closed over this time period without the previously suggested need to strongly increase anthropogenic CH4 emissions in the United States. With further developments, especially on the treatment of the atmospheric CH4 sink, we expect the data assimilation system presented here will be able to contribute to the ongoing interpretation of changes in this important greenhouse gas budget.

Gobal methane emissions were estimated for 2000-2012 using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, the anthropogenic and biosphere emissions of CH4 are simultaneously constrained by global atmospheric in-situ methane mole fraction observations. We use three configurations developed in Tsuruta et al. (2016) to assess the sensitivity of the CH4 flux estimates to (a) the number of unknown flux scaling factors to be optimized 30 which in turn depends on the choice of underlying land-ecosystem map, and (b) on the parametrization of vertical mixing in the atmospheric transport model TM5. The posterior emission estimates were evaluated by comparing simulations to surface in-situ observation sites, to profile observations made by aircraft, to dry air total column-averaged mole fractions (XCH4) observations from the Total Carbon Column Observing Network (TCCON), and to XCH4 retrievals from the Greenhouse gases Observing SATellite (GOSAT). Our estimated posterior mean global total emissions during 2000-2012 are 516±51 Tg 35 CH4 yr, and emission estimates during 2007-2012 are 18 Tg CH4 yr greater than those from 2001-2006, mainly driven by an increase in emissions from the south America temperate region, the Asia temperate region and Asia tropics. The Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-182, 2016 Manuscript under review for journal Geosci. Model Dev. Published: 19 August 2016 c © Author(s) 2016. CC-BY 3.0 License.

CarbonTracker Europe-CH4 (CTE-CH4) inverse model versions 1.0 and 1.1 are presented. The model optimizes global surface methane emissions from biosphere and anthropogenic sources using an ensemble Kalman filter (EnKF) based optimization method, using the TM5 chemistry transport model as an observation operator, and assimilating global in-situ atmospheric methane mole fraction observations. In this study, we examine sensitivity of our CH4 emission estimates on the 20 ensemble size, covariance matrix, prior estimates, observations to be assimilated, assimilation window length, convection scheme in TM5, and model structure in the emission estimates by performing CTE-CH4 with several set-ups. The analyses show that the model is sensitive to most of the parameters and inputs that were examined. Firstly, using a large enough ensemble size stabilises the results. Secondly, using an informative covariance matrix reduces uncertainty estimates. Thirdly, agreement with discrete observations became better when assimilating continuous observations. Finally, the posterior 25 emissions were found sensitive to the choice of prior estimates, convection scheme and model structure, particularly to their spatial distribution. The distribution of posterior mole fractions derived from posterior emissions is consistent with the observations to the extent prescribed in the various covariance estimates, indicating a satisfactory performance of our system.

Gobal methane emissions were estimated for 2000–2012 using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, the anthropogenic and biosphere emissions of CH4 are simultaneously constrained by global atmospheric in-situ methane mole fraction observations. We use three configurations developed in Tsuruta et al. (2016) to assess the sensitivity of the CH4 flux estimates to (a) the number of unknown flux scaling factors to be optimized which in turn depends on the choice of underlying land-ecosystem map, and (b) on the parametrization of vertical mixing in the 30 atmospheric transport model TM5. The posterior emission estimates were evaluated by comparing simulations to surface in-situ observation sites, to profile observations made by aircraft, to dry air total column-averaged mole fractions (XCH4) observations from the Total Carbon Column Observing Network (TCCON), and to XCH4 retrievals from the Greenhouse gases Observing SATellite (GOSAT). Our estimated posterior mean global total emissions during 2000–2012 are 516 ± 51 Tg CH4 yr−1, and emission estimates during 2007–2012 are 18 Tg CH4 yr−1 greater than those from 2001–2006, mainly driven by an 35 increase in emissions from the south America temperate region, the Asia temperate region and Asia tropics. The sensitivity of the flux estimates to the underlying ecosystem map was large for the Asia temperate region and Australia, but not significant in the northern latitude regions, i.e. the north American boreal region, the north American temperate region and Europe. Instead, the posterior estimates for the northern latitude regions show larger sensitivity to the choice of convection scheme in TM5. The Gregory et al. (2000) mixing scheme with faster interhemispheric exchange leads to higher estimated CH4 emissions at northern latitudes, and lower emissions in southern latitudes, compared to the estimates using Tiedtke (1989) convection scheme. Our evaluation with non-assimilated observations showed that posterior mole fractions were better matched with the 5 observations when Gregory et al. (2000) convection scheme was used.

CarbonTracker Europe-CH4 (CTE-CH4) inverse model versions 1.0 and 1.1 are presented. The model optimizes global surface methane emissions from biosphere and anthropogenic sources using an ensemble Kalman filter (EnKF) based optimization method, using the TM5 chemistry transport model as an observation operator, and assimilating global in-situ atmospheric methane mole fraction observations. In this study, we examine sensitivity of our CH4 emission estimates on the ensemble size, covariance matrix, prior estimates, observations to be assimilated, assimilation window length, convection scheme in TM5, and model structure in the emission estimates by performing CTE-CH4 with several set-ups. The analyses show that the model is sensitive to most of the parameters and inputs that were examined. Firstly, using a large enough ensemble size stabilises the results. Secondly, using an informative covariance matrix reduces uncertainty estimates. Thirdly, agreement with discrete observations became better when assimilating continuous observations. Finally, the posterior emissions were found sensitive to the choice of prior estimates, convection scheme and model structure, particularly to their spatial distribution. The distribution of posterior mole fractions derived from posterior emissions is consistent with the observations to the extent prescribed in the various covariance estimates, indicating a satisfactory performance of our system.

The concentration of ozone at the Earth's surface is measured at many locations across the globe for the purposes of air quality monitoring and atmospheric chemistry research. We have brought together all publicly available surface ozone observations from online databases from the modern era to build a consistent data set for the evaluation of chemical transport and chemistry-climate (Earth System) models for projects such as the Chemistry-Climate Model Initiative and Aer-Chem-MIP. From a total data set of approximately 6600 sites and 500 million hourly observations from 1971–2015, approximately 2200 sites and 200 million hourly observations pass screening as high-quality sites in regionally representative locations that are appropriate for use in global model evaluation. There is generally good data volume since the start of air quality monitoring networks in 1990 through 2013. Ozone observations are biased heavily toward North America and Europe with sparse coverage over the rest of the globe. This data set is made available for the purposes of model evaluation as a set of gridded metrics intended to describe the distribution of ozone concentrations on monthly and annual timescales. Metrics include the moments of the distribution, percentiles, maximum daily 8-hour average (MDA8), sum of means over 35 ppb (daily maximum 8-h; SOMO35), accumulated ozone exposure above a threshold of 40 ppbv (AOT40), and metrics related to air quality regulatory thresholds. Gridded data sets are stored as netCDF-4 files and are available to download from the British Atmospheric Data Centre (doi:10.5285/08fbe63d-fa6d-4a7a-b952-5932e3ab0452). We provide recommendations to the ozone measurement community regarding improving metadata reporting to simplify ongoing and future efforts in working with ozone data from disparate networks in a consistent manner.

Abstract. CarbonTracker Europe-CH4 (CTE-CH4) inverse model versions 1.0 and 1.1 are presented. The model optimizes global surface methane emissions from biosphere and anthropogenic sources using an ensemble Kalman filter (EnKF) based optimization method, using the TM5 chemistry transport model as an observation operator, and assimilating global in-situ atmospheric methane mole fraction observations. In this study, we examine sensitivity of our CH4 emission estimates on the ensemble size, covariance matrix, prior estimates, observations to be assimilated, assimilation window length, convection scheme in TM5, and model structure in the emission estimates by performing CTE-CH4 with several set-ups. The analyses show that the model is sensitive to most of the parameters and inputs that were examined. Firstly, using a large enough ensemble size stabilises the results. Secondly, using an informative covariance matrix reduces uncertainty estimates. Thirdly, agreement with discrete observations became better when assimilating continuous observations. Finally, the posterior emissions were found sensitive to the choice of prior estimates, convection scheme and model structure, particularly to their spatial distribution. The distribution of posterior mole fractions derived from posterior emissions is consistent with the observations to the extent prescribed in the various covariance estimates, indicating a satisfactory performance of our system.

The Mediterranean basin represents a hot spot area for short-term O-3 distribution and anthropogenic contributions to it. This is why we analysed in this work the surface O-3 variability observed at Mt. Cimone WMO/GAW global station (CMN, 44 degrees 12' N, 10 degrees 42' E, 2165 m a.s.l., Italy) from 1991 to 2011. The measurements performed at this mountain observatory represent the longest surface O-3 record at a baseline site in the Mediterranean basin.Monthly O-3 averages at CMN show a typical seasonal cycle characterised by a winter minimum and a spring - summer maxima. The shape of the mean annual variation of O-3 is well comparable with those observed at other four baseline sites in the Alps and in the Mediterranean region: Jungfraujoch - Swiss Alps, Sonnblick - Austrian Alps, Mt Krvavec- Slovenia and Giordan Lightouse - Island of Gozo, Malta. In general, O-3 levels at CMN show higher values during warm months, which is likely to be related both to vertical transport of polluted air-masses at regional and continental scales and to enhanced photochemistry.Here, we also investigate the influence of specific atmospheric processes (i.e. the occurrence of heat-waves, North Atlantic Oscillation, thermal transport of air-masses from the regional PBL and strato-spheric intrusions) in affecting O-3 variability at CMN.Overall, a significant positive (95% confidence level) linear trend in monthly O-3 mole fraction was observed over the period 1991-2011 (0.21 +/- 0.10 nmol/mol yr(-1)) while no trend (-0.02 +/- 0.12 nmol/ mol yr(-1)) was detected for the 1996-2011, when measurements were carried out by an homogeneous set-up. On a seasonal basis, a positive trend has been observed for 1996-2011 (0.34 +/- 032 nmol/mol yr(-1)) only for spring. Significant decreases of the seasonal O-3 growth-rates have been detected at CMN during 1991-2011 from winter to spring and only for summer during 1996-2011. (C) 2014 The Authors. Published by Elsevier Ltd.

In this paper, we have studied in depth the effect of Etna volcanic ash clouds on the Maltese Islands. Research was carried out to gather information about Etna's eruptions that impacted the Maltese Islands, starting with historical eruptions dating back to the 14th century continuing to present day. A statistical approach was utilized to provide tephra deposit load and ash concentration using PUFF — a model which simulates the transport, dispersion and sedimentation of volcanic ash. Three different eruptive scenarios that characterize Etna's recent activity were considered; the first scenario representing the 2001 eruption (Sc1), the second scenario representing the July 1998 eruption (Sc2) whilst the third scenario represents the recent activity in 2011–2012 (Sc3). We found that the time taken for the volcanic ash cloud to reach the Maltese Islands, when the wind direction is toward the south-west ranges from 4 to 6h. The probability that an Etna volcanic cloud reaches Malta during an eruption is about 15% per annum. The now calibrated model may be now used to produce deposit load and cumulative columnar load (i.e. summation from maximum height of volcanic cloud to ground) of volcanic ash in atmosphere for the Maltese area and help the aviation authorities and Malta airport to make decisions during Etna eruptions. This will be of direct use to local communities and aviation.

A 10-year study of surface ozone mixing ratios in the Central Mediterranean was conducted based on continuous ozone measurements from 1997 to 2006 by a background regional Global Atmospheric Watch (GAW) station on the island of Gozo. The mean annual maximum mixing ratio is of the order of 66 ppbv in April–May with a broad secondary maximum of 64 ppbv in July–September. No long-term increase or decrease in the background level of surface ozone could be observed over the last 10 years. This is contrary to observations made in the Eastern Mediterranean, where a slow decrease in the background ozone mixing ratio was observed over the past 7 years. Despite the very high average annual ozone mixing ratio exceeding 50 ppbv—in fact, the highest average background ozone mixing ratio ever measured in Europe—, the diurnal O 3 max / O 3 min index of <1.40 indicates that the island of Gozo is a good site for measuring background surface ozone. However, frequent photosmog events from June to September during the past 10 years with ozone mixing ratios exceeding 90 ppbv indicate that the Central Mediterranean is prone to long-range transport of air pollutants from Europe by northerly winds. This was particularly evident during the so-called “August heatwave” of the year 2003 when the overall ozone mixing ratio was 4.6 ppbv higher than the average of all other 9 months of August since 1997. Air mass back-trajectory analysis of the August 2003 photosmog episodes on Gozo confirmed that ozone pollution originated from the European continent. Regression analysis was used to analyse the 10-year data set in order to model the behaviour of the ozone mixing ratio in terms of the meteorological parameters of wind speed, relative humidity, global radiation, temperature, month of year, wind sector, atmospheric pressure, and time of day (predictors). Most of these predictors were found to significantly affect the ozone mixing ratios. From March to November, the monthly average of the AOT40 threshold value for the protection of crops and vegetation against ozone was constantly exceeded on Gozo during the past 10 years.

A study on the spatial distribution as well as an investigation of the possible factors influencing the observed variations of summer (JJA) rural and marine surface ozone background in the Central and Eastern Mediterranean is performed, following observations showing that the 60ppb EU Air Quality Standard for Human Health Protection is frequently exceeded in the area. For this purpose the measurements of the following four Eastern Mediterranean stations are analyzed: Giordan Lighthouse-Gozo, Malta; Aliartos-Central Greece; Finokalia-Crete, Greece and Ag. Marina, Cyprus. The measured summer afternoon rural and marine ozone levels in Central Greece and on Crete Island are quite comparable, but are found to be significantly higher (by about 15–20%) than the corresponding levels in Malta and Cyprus. After investigating the characteristic meteorological conditions associated with high and low rural and marine surface ozone concentrations, it appears that an important factor leading to high tropospheric ozone values in the Eastern Mediterranean area is the anticyclonic influence of the high-pressure domination over the Central Mediterranean and the Balkans. The rural and marine surface ozone stations located across the Aegean Channel are also influenced by the long-range transport of polluted air masses from the European continent in the boundary layer during summer and the subsequent photochemical ozone production. This characteristic northern flow during summer is created by the combination of the Central Mediterranean anticyclone with the Middle-East low-pressure system. On the other hand, the lowest ozone levels, particularly in the Crete and Cyprus stations, are associated with an extension to the west of the Middle-East low and weak pressure gradients over the Eastern Mediterranean and an upper air trough in the North Eastern Europe.