Monitoring Atmospheric Composition And Climate Research Articles

Climatological Study of Air Pollutant Emissions in Saudi Arabia

This study aims to investigate the spatio-temporal distribution, variation, abrupt change, and long-term trends of major pollutant emissions in the Kingdom of Saudi Arabia (KSA) over the period 1960–2020 using the Monitoring Atmospheric Composition and Climate (MACC)/CityZEN EU projects (MACCity) emissions dataset inventory. These pollutants are carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), volatile organic compounds (VOCs), black carbon (BC), and organic carbon (OC). Seven stations were selected (Al-Bahah, Abha, Dahra, Jeddah, Riyadh, Qassim, and Ahsa), which correspond to the highest (hotspot) annual pollutant emissions. The annual cycle analysis of the six pollutant emissions revealed that there are four distinct patterns; the first one has one interannual wave while the other three patterns have two interannual waves. The analysis of the different sectors’ contributions to pollutant emissions revealed that the energy, transportation, and industries sectors have the highest percentage contributions. Significant abrupt change points were detected in 1970, 1980, 1990, 2000, 2005, and 2010. The development and growth rates in the KSA starting from the early 1970s are attributed to the oil boom. The great increase in pollutant emissions in the early 1980s followed by that in the 1990s up to 2000 is due to an increase in fossil fuel demand, industries, transportation, and energy consumption.

Evaluation and comparison of MERRA-2 AOD and DAOD with MODIS DeepBlue and AERONET data in Australia

Validated dust and aerosol datasets provide valuable information for dust and other atmospheric research. A reanalysis product called ‘MERRA-2’ developed by NASA's Global Modeling and Assimilation Office (GMAO) in recent years provides long-term, high frequency, global coverage aerosol simulations, in terms of AOD (aerosol optical depth) and dust AOD (DAOD). The AOD assimilation system including AERONET (Aerosol Robotic Network) as constraints has led to difficulties with independent validation of MERRA-2 AOD and DAOD. The existing validation and evaluation of MERRA-2 tend to focus on central inland Australia, and comparison of DAOD with MACC (Monitoring Atmospheric Composition and Climate) is insufficient to indicate which one is more appropriate for dust research in Australia. In this study, MERRA-2 output was compared with MODIS DeepBlue (MODIS-DB) (2002–2020) and AERONET (1998–2020) AOD and DAOD in Australia. The expected error (EE) for MERRA-2 AOD was estimated to be ±(0.03+0.15τA) containing 66% of data points. MERRA-2 is less well correlated with AERONET in terms of DAOD, but with a tighter distribution of data points (78%) within the EE. The EE for MODIS-DB AOD was found to be the same and the correlation between MODIS-DB DAOD and AERONET DAOD is stronger than that between MERRA-2 DAOD and AERONET DAOD. Comparison of MERRA-2 and MODIS-DB AOD showed that MERRA-2 AOD was 22.5% higher than MODIS-DB AOD at AERONET sites on average. MERRA-2 AOD was generally lower than MODIS-DB AOD away from AERONET sites when AOD >0.1, and the spatial distribution of the difference between the two is consistent with the spatial variation in AOD. Large differences between MODIS-DB AOD and MERRA-2 occurred in areas where AOD is greater than 0.3. AOD and DAOD based on MODIS-DB could be used for areas away from AERONET sites in Australia, as they are less dependent on AERONET data compared to MERRA-2. When compared to MODIS brightness temperature difference (BTD) for two known severe storm events in Australia, MODIS-DB product is better than MERRA-2 in terms of detecting the spatial extent of dust storms and estimating the storm intensity. MERRA-2 would underestimate the magnitude and spatial extent of AOD, especially for thick dust plumes, and AERONET was likely to have misclassified dust as cloud.

Classification of synoptic weather clusters associated with dust accumulation over southeastern areas of the Caspian Sea (Northeast Iran and Karakum desert)

• Determination of weather clusters associated with high dust-AODs over northeast Iran/Karakum desert. • Six identified weather clusters from PCA with highest frequency in spring. • The dust hotpot areas are attributed to convergence of northerly and southwesterly winds over NE Iran. • The Siberian High and Qibla wind in central Iran modulate the dust accumulation. • Changes in position, intensity and expansion of the upper-level subtropical jet modulate the dust distribution. In this study, daily-mean total and dust aerosol optical depth (TAOD, DAOD, respectively) obtained from the Monitoring Atmospheric Composition and Climate (MACC) and meteorological fields from ERA-Interim reanalysis are used to identify spatial patterns of dust accumulation over northeast Iran and Karakum Desert during 2003–2012. The most dust-affected area is defined using highest variances of DAOD by S-mode and weather clusters by T-mode principal component analysis (PCA). Six weather clusters are classified via the statistical analysis, associated with high DAOD values, with larger frequency in spring, while PC1 (41 cases) dominates in summer. The results show that changes in the intensity and expansion of the Siberian/European high-pressures in spring modulate strong northeasterlies or northwesterlies over Central Asia, which are associated with frontal dust storms over the desert areas (Aralkum, Karakum). In addition, dynamic conditions associated with the sub-tropical jet stream and the Iranian trough, and combined with convective conditions at areas of thermal lows in east Iran, create a strong southwesterly wind – called Qibla – over the Iranian Plateau. These two contrasting wind regimes converge over northeast Iran/Karakum Desert, facilitating dust accumulation over the area. In summer, northerly winds dominate over Central Asia, but the absence of Qibla flow allows them to traverse till the north coast of the Arabian Sea, where they converge with the southwest monsoon flow. The accumulation of dust over northeast Iran/Karakum is lesser than that over Pakistan and Thar desert. Furthermore, the upper-level sub-tropical jet stream moves northward in summer, with core over Turkmenistan/Uzbekistan.

Classification of weather clusters over the Middle East associated with high atmospheric dust-AODs in West Iran

Daily aerosol optical depth (AOD) and meteorological fields obtained from Monitoring Atmospheric Composition and Climate (MACC) and ERA-Interim reanalysis, respectively are used to analyze spatial patterns of AOD in the west part of Iran during the period 2003–2012. The areas affected by high daily AODs in southwest and west/northwest parts of Iran are identified using principal component analysis (PCA) and the atmospheric circulation patterns for these high AODs are classified in six clusters for each region, with larger frequencies in spring and summer. Despite their between differences, the weather clusters are mostly associated with a strong westerly/northwesterly flow (Shamal wind) across the Iraqi plains and southwest Iran from May to September, which is triggered by the pressure gradient between the North Africa/Mediterranean high and the monsoon low over southeast Iran. In the cold season, the pressure gradient between the Kurdi cut-off low and the high pressure over North Africa facilitates frontal dust storms that enhance the dust AOD over the west parts of Iran. The Caspian Sea high-pressure system during summer intensifies the easterly-northeasterly winds from the Karakum Desert to northwest Iran, while in winter, the strengthening of the Siberian High and its expansion over the Caspian Sea trigger strong cold northerlies over central/northwest Iran. In addition, the convergence of south/southwesterly winds, as a result of the surface low-pressure in the southern Arabian Peninsula, facilitates pre-frontal dust storms toward southwestern Iran, mostly during March–April. In summer, the gradient zone between the Iraq low-pressure and the Zagros high-pressure enables transport of dust aerosols toward west-northwest Iran. Identification of the weather clusters associated with intense dust storms over the west part of Iran is critical for the prevention of the deleterious effects of dust on climate, ecosystems and human health.

The Diurnal Variation in Stratospheric Ozone from MACC Reanalysis, ERA-Interim, WACCM, and Earth Observation Data: Characteristics and Intercomparison

In this study, we compare the diurnal variation in stratospheric ozone of the MACC (Monitoring Atmospheric Composition and Climate) reanalysis, ECMWF Reanalysis Interim (ERA-Interim), and the free-running WACCM (Whole Atmosphere Community Climate Model). The diurnal variation of stratospheric ozone results from photochemical and dynamical processes depending on altitude, latitude, and season. MACC reanalysis and WACCM use similar chemistry modules and calculate a similar diurnal cycle in ozone when it is caused by a photochemical variation. The results of the two model systems are confirmed by observations of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) experiment and three selected sites of the Network for Detection of Atmospheric Composition Change (NDACC) at Mauna Loa, Hawaii (tropics), Bern, Switzerland (midlatitudes), and Ny-Ålesund, Svalbard (high latitudes). On the other hand, the ozone product of ERA-Interim shows considerably less diurnal variation due to photochemical variations. The global maxima of diurnal variation occur at high latitudes in summer, e.g., near the Arctic NDACC site at Ny-Ålesund, Svalbard. The local OZORAM radiometer observes this effect in good agreement with MACC reanalysis and WACCM. The sensed diurnal variation at Ny-Ålesund is up to 8% (0.4 ppmv) due to photochemical variations in summer and negligible during the dynamically dominated winter. However, when dynamics play a major role for the diurnal ozone variation as in the lower stratosphere (100–20 hPa), the reanalysis models ERA-Interim and MACC which assimilate data from radiosondes and satellites outperform the free-running WACCM. Such a domain is the Antarctic polar winter where a surprising novel feature of diurnal variation is indicated by MACC reanalysis and ERA-Interim at the edge of the polar vortex. This effect accounts for up to 8% (0.4 ppmv) in both model systems. In summary, MACC reanalysis provides a global description of the diurnal variation of stratospheric ozone caused by dynamics and photochemical variations. This is of high interest for ozone trend analysis and other research which is based on merged satellite data or measurements at different local time.

Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran

Extraordinary dry conditions on the desert and arid areas in Iran, along with strong influences from surrounding dust sources in the Middle East and Arabia, have exposed the country to substantial amounts of dust aerosols with serious impacts on environment, health and socio-economic aspects. Considering this threat, daily aerosol optical depth (AOD) data over Iran obtained from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis during 2003–2012 were used to analyze the spatial and temporal patterns of total AOD (TAOD) and dust AOD (DAOD). This study identifies the areas mostly affected by TAOD and DAOD in terms of daily average values and the areas associated with distinct temporal patterns, utilizing S-mode and T-mode principal component analysis (PCA). The analysis reveals six distinct sub-regions in southeast, west-northwest, northeast, east, central and southwest of Iran, which are among the major centers influenced by TAOD and DAOD extremes. The main findings of the T-mode results, consistent with TAOD and DAOD S-mode patterns, are (i) the maximum dust loading over the eastern, southeastern and southwestern subregions in March and May, (ii) dust loading with peaks in November over the eastern and northeastern sub-regions; (iii) maximum number of dusty days in July and August over southwest, (iv) maximum dust in July over southeastern and Central Iran, (v) a dust pattern with identical extent over the west and northwest sub-region in March and October and, (vi) a prevailing dust loading over the dry areas (Lut desert, Sistan plain and southwest edge of the territory) in October. The spatiotemporal evolution of dust is a function of the growth and expansion of dust extremes originated from various sources in Iran and the Middle East. The PCA methodology, through simplification of aerosol distribution to simpler structures, was also incorporated to provide a geographical interpretation of the highly sensitive territory of Iran.

Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China

Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO2 concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO2 dry air mole fraction (XCO2) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO2 changes during growing season for 13 years. We derived a relationship between XCO2 and surface net CO2 fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO2 flux enhancement based on satellite observed XCO2 changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO2 emissions, we estimated an enhanced XCO2 drawdown during the GP of −0.070 to −0.084 ppm yr−1. Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2–3% of EC’s annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO2 to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord.

Comparison of Regional Simulation of Biospheric CO2 Flux from the Updated Version of CarbonTracker Asia with FLUXCOM and Other Inversions over Asia

There are still large uncertainties in the estimates of net ecosystem exchange of CO2 (NEE) with atmosphere in Asia, particularly in the boreal and eastern part of temperate Asia. To understand these uncertainties, we assessed the CarbonTracker Asia (CTA2017) estimates of the spatial and temporal distributions of NEE through a comparison with FLUXCOM and the global inversion models from the Copernicus Atmospheric Monitoring Service (CAMS), Monitoring Atmospheric Composition and Climate (MACC), and Jena CarboScope in Asia, as well as examining the impact of the nesting approach on the optimized NEE flux during the 2001–2013 period. The long-term mean carbon uptake is reduced in Asia, which is −0.32 ± 0.22 PgC yr−1, whereas −0.58 ± 0.26 PgC yr−1 is shown from CT2017 (CarbonTracker global). The domain aggregated mean carbon uptake from CTA2017 is found to be lower by 23.8%, 44.8%, and 60.5% than CAMS, MACC, and Jena CarboScope, respectively. For example, both CTA2017 and CT2017 models captured the interannual variability (IAV) of the NEE flux with a different magnitude and this leads to divergent annual aggregated results. Differences in the estimated interannual variability of NEE in response to El Niño–Southern Oscillation (ENSO) may result from differences in the transport model resolutions. These inverse models’ results have a substantial difference compared to FLUXCOM, which was found to be −5.54 PgC yr−1. On the one hand, we showed that the large NEE discrepancies between both inversion models and FLUXCOM stem mostly from the tropical forests. On the other hand, CTA2017 exhibits a slightly better correlation with FLUXCOM over grass/shrub, fields/woods/savanna, and mixed forest than CT2017. The land cover inconsistency between CTA2017 and FLUXCOM is therefore one driver of the discrepancy in the NEE estimates. The diurnal averaged NEE flux between CTA2017 and FLUXCOM exhibits better agreement during the carbon uptake period than the carbon release period. Both CTA2017 and CT2017 revealed that the overall spatial patterns of the carbon sink and source are similar, but the magnitude varied with seasons and ecosystem types, which is mainly attributed to differences in the transport model resolutions. Our findings indicate that substantial inconsistencies in the inversions and FLUXCOM mainly emerge during the carbon uptake period and over tropical forests. The main problems are underrepresentation of FLUXCOM NEE estimates by limited eddy covariance flux measurements, the role of CO2 emissions from land use change not accounted for by FLUXCOM, sparseness of surface observations of CO2 concentrations used by the assimilation systems, and land cover inconsistency. This suggested that further scrutiny on the FLUXCOM and inverse estimates is most likely required. Such efforts will reduce inconsistencies across various NEE estimates over Asia, thus mitigating ecosystem-driven errors that propagate the global carbon budget. Moreover, this work also recommends further investigation on how the changes/updates made in CarbonTracker affect the interannual variability of the aggregate and spatial pattern of NEE flux in response to the ENSO effect over the region of interest.

Evaluation of MACC Reanalysis Ozone Data over China Using Ground-based and AIRS Satellite Observations

A comparative analysis was conducted using total ozone products derived from monitoring atmospheric composition and climate (MACC) reanalysis data validated with ozone data from the atmospheric infrared sounder (AIRS) satellite and ground-based ozone measurements. The results indicate that the relative deviation of total ozone from the MACC reanalysis data and the ground-based ozone total data is controlled within 17%, and all of the correlation coefficients were between 0.79 and 0.97. The total ozone values from the MACC reanalysis data showed good consistency with the ground-based ozone measurements. With respect to the spatial distribution of multi-year averages, the relative deviation of total ozone values in the MACC reanalysis data and the AIRS satellite data was between -3% and 5%. The total ozone values in the MACC reanalysis data were higher than those from AIRS measurements for the Qinghai-Tibet Plateau and the coastal areas of South China, and were lower for northeast China. Furthermore, the seasonal variations in total ozone values in the MACC reanalysis data were consistent with AIRS data. At Mt. Waliguan station, the monthly averaged trends for near-surface ozone in the MACC reanalysis data were also consistent with surface ozone concentrations; the MACC reanalysis data reflect the observed trends for surface-based ozone measurements in spring, summer, and autumn, but show a large deviation in winter.

Distribution of volatile organic compounds over Indian subcontinent during winter: WRF-chem simulation versus observations

We investigate the distribution of volatile organic compounds (VOCs) over Indian subcontinent during a winter month of January 2011 combining the regional model WRF-Chem (Weather Research and Forecasting model coupled with Chemistry) with ground- and space-based observations and chemical reanalysis. WRF-Chem simulated VOCs are found to be comparable with ground-based observations over contrasting environments of the Indian subcontinent. WRF-Chem results reveal the elevated levels of VOCs (e. g. propane) over the Indo-Gangetic Plain (16 ppbv), followed by the Northeast region (9.1 ppbv) in comparison with other parts of the Indian subcontinent (1.3–8.2 ppbv). Higher relative abundances of propane (27–31%) and ethane (13–17%) are simulated across the Indian subcontinent. WRF-Chem simulated formaldehyde and glyoxal show the western coast, Eastern India and the Indo-Gangetic Plain as the regional hotspots, in a qualitative agreement with the MACC (Monitoring Atmospheric Composition and Climate) reanalysis and satellite-based observations. Lower values of RGF (ratio of glyoxal to formaldehyde <0.04) suggest dominant influences of the anthropogenic emissions on the distribution of VOCs over Indian subcontinent, except the northeastern region where higher RGF (∼0.06) indicates the role of biogenic emissions, in addition to anthropogenic emissions. Analysis of HCHO/NO2 ratio shows a NOx-limited ozone production over India, with a NOx-to-VOC transition regime over central India and IGP. The study highlights a need to initiate in situ observations of VOCs over regional hotspots (Northeast, Central India, and the western coast) based on WRF-Chem results, where different satellite-based observations differ significantly.

Investigation of Carbon Dioxide Variations in Selected Points in Nigeria Using Neural Network Model

Atmospheric pollution due to carbon dioxide emission from different fossil fuels and deforestations are considered as a great and important international challenge to the societies. This study is to investigate carbon dioxide (CO2) distributions in selected points in Nigeria using neural network. Neural network model were used to estimate daily values of carbon dioxide, study spatial temporal variations of carbon dioxide, and study the annual variations of estimated and observed carbon dioxide in Nigeria. The study areas used in this work are thirty six (36) points location over Nigeria. The data used in this work is a satellite carbon dioxide () data were obtained from Global Monitoring for Environment and Security (GMES) under the programme of Monitoring Atmospheric Composition And Climate (MACC) www.gmes-atmosphere.eu/data between 2009-2014. The neural network architecture used comprises of three main layers; an input layer, a hidden layer and an output layer. Four input data were considered which include year, day of year (DOY) representing the time, latitude and longitude. Twenty hidden neurons were employed, while the output is the desired data of carbon dioxide. The results show that the increase in trend of CO2 in dry season in every part of the country is on yearly bases. In the wet season, the concentration of CO2 in Nigeria is not as much as in the dry season case, probably due to absorption of the gas by precipitation. The continuous annual increase of CO2 distribution suggests continuous increase of the greenhouse gas in Nigeria. This reveals continuous contribution of CO2 in Nigeria. The similarity in the estimated and observed signatures reveals that neural network model performance were excellent and efficient in determination of spatial distribution of CO2, thereby proving to be useful tool in modeling the greenhouse gases. The results show that neural network model has the capacity of investigating greenhouse gases variations in Nigeria.

The CAMS reanalysis of atmospheric composition

Abstract. The Copernicus Atmosphere Monitoring Service (CAMS) reanalysis is the latest global reanalysis dataset of atmospheric composition produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), consisting of three-dimensional time-consistent atmospheric composition fields, including aerosols and chemical species. The dataset currently covers the period 2003–2016 and will be extended in the future by adding 1 year each year. A reanalysis for greenhouse gases is being produced separately. The CAMS reanalysis builds on the experience gained during the production of the earlier Monitoring Atmospheric Composition and Climate (MACC) reanalysis and CAMS interim reanalysis. Satellite retrievals of total column CO; tropospheric column NO2; aerosol optical depth (AOD); and total column, partial column and profile ozone retrievals were assimilated for the CAMS reanalysis with ECMWF's Integrated Forecasting System. The new reanalysis has an increased horizontal resolution of about 80 km and provides more chemical species at a better temporal resolution (3-hourly analysis fields, 3-hourly forecast fields and hourly surface forecast fields) than the previously produced CAMS interim reanalysis. The CAMS reanalysis has smaller biases compared with most of the independent ozone, carbon monoxide, nitrogen dioxide and aerosol optical depth observations used for validation in this paper than the previous two reanalyses and is much improved and more consistent in time, especially compared to the MACC reanalysis. The CAMS reanalysis is a dataset that can be used to compute climatologies, study trends, evaluate models, benchmark other reanalyses or serve as boundary conditions for regional models for past periods.

The role of biomass burning as derived from the tropospheric CO vertical profiles measured by IAGOS aircraft in 2002–2017

Abstract. This study investigates the role of biomass burning and long-range transport in the anomalies of carbon monoxide (CO) regularly observed along the tropospheric vertical profiles measured in the framework of the In-service Aircraft for a Global Observing System (IAGOS). Considering the high interannual variability of biomass burning emissions and the episodic nature of long-range pollution transport, one strength of this study is the amount of data taken into account, namely 30 000 vertical profiles at nine clusters of airports in Europe, North America, Asia, India and southern Africa over the period 2002–2017. As a preliminary, a brief overview of the spatiotemporal variability, latitudinal distribution, interannual variability and trends of biomass burning CO emissions from 14 regions is provided. The distribution of CO mixing ratios at different levels of the troposphere is also provided based on the entire IAGOS database (125 million CO observations). This study focuses on the free troposphere (altitudes above 2 km) where the long-range transport of pollution is favoured. Anomalies at a given airport cluster are here defined as departures from the local seasonally averaged climatological vertical profile. The intensity of these anomalies varies significantly depending on the airport, with maximum (minimum) CO anomalies of 110–150 (48) ppbv in Asia (Europe). Looking at the seasonal variation of the frequency of occurrence, the 25 % strongest CO anomalies appear reasonably well distributed throughout the year, in contrast to the 5 % or 1 % strongest anomalies that exhibit a strong seasonality with, for instance, more frequent anomalies during summertime in the northern United States, during winter/spring in Japan, during spring in south-east China, during the non-monsoon seasons in south-east Asia and south India, and during summer/fall in Windhoek, Namibia. Depending on the location, these strong anomalies are observed in different parts of the free troposphere. In order to investigate the role of biomass burning emissions in these anomalies, we used the SOFT-IO (SOft attribution using FlexparT and carbon monoxide emission inventories for In-situ Observation database) v1.0 IAGOS added-value products that consist of FLEXible PARTicle dispersion model (FLEXPART) 20-day backward simulations along all IAGOS aircraft trajectories, coupled with anthropogenic Monitoring Atmospheric Composition and Climate (MACC)/CityZEN EU projects (MACCity) and biomass burning Global Fire Assimilation System (GFAS) CO emission inventories and vertical injections. SOFT-IO estimates the contribution (in ppbv) of the recent (less than 20 days) primary worldwide CO emissions, tagged per source region. Biomass burning emissions are found to play an important role in the strongest CO anomalies observed at most airport clusters. The regional tags indicate a large contribution from boreal regions at airport clusters in Europe and North America during the summer season. In both Japan and south India, the anthropogenic emissions dominate all throughout the year, except for the strongest summertime anomalies observed in Japan that are due to Siberian fires. The strongest CO anomalies at airport clusters located in south-east Asia are induced by fires burning during spring in south-east Asia and during fall in equatorial Asia. In southern Africa, the Windhoek airport was mainly impacted by fires in Southern Hemisphere Africa and South America. To our knowledge, no other studies have used such a large dataset of in situ vertical profiles for deriving a climatology of the impact of biomass burning versus anthropogenic emissions on the strongest CO anomalies observed in the troposphere, in combination with information on the source regions. This study therefore provides both qualitative and quantitative information for interpreting the highly variable CO vertical distribution in several regions of interest.

Analysis of spatio-temporal dust aerosol frequency over Iran based on satellite data

Iran is located in the dust-belt region and so dust is a main environmental issue over the country. The main purpose of this study is to better understand of the spatial and temporal properties of the Dust Aerosol Frequency (DAF) over Iran using satellite data. Daily Moderate Resolution Imaging Spectroradiometer (MODIS) deep blue Aerosol Optical Depth (AOD), Angstrom Exponent (AE) (both Terra and Aqua, Level 3, Collection 6.1) and Ozone Monitoring Instrument (OMI) Absorption Aerosol Index (AAI) were obtained at 1° × 1° spatial resolution over Iran for the 10 years from 2006 to 2015. In this study observations with AOD higher than 0.3, AE < 0.75 and AAI >0.7 are considered to be dust aerosols. Results showed that the maximum areas with high DAF are located in the Khuzestan province in the southwest and Sistan in the east of the country. The other areas with peak DAF were observed in the low elevation areas of the country, namely coastal plain of the Oman Sea, Jaz Murian depression and Lut desert in the southeast, and Southern Dasht-e Kavir in central northern. DAF is decreased significantly at latitudes higher than 34.5° N. The maximum and minimum DAFs over Iran occur in July (Terra = 2.02, Aqua = 2.1) and November (Terra = 0.1, Aqua = 0.05), respectively. We found good spatial relationship between DAF with the meteorological codes frequency related to the dust from weather stations as well as with the fraction of dust AOD and from Monitoring Atmospheric Composition and Climate (MACC) project. In addition, results showed that dust frequencies based on both weather station and satellite data exhibited corresponding relationships with latitude, elevation, vegetation cover, precipitation and temperature.

Assessment of atmospheric aerosols from two reanalysis products over Australia

Assessments of atmospheric aerosols from reanalysis are important for understanding uncertainty in model simulations, and ultimately predictions, such as for solar power or air quality forecasts and assessments. This study intercompares total aerosol optical depth (AOD) and dust AOD (DAOD) from two global reanalyses datasets, the European Centre for Medium-Range Weather Forecasts (ECMWF) Monitoring Atmospheric Composition and Climate (MACC) and the NASA Modern-Era Retrospective Analysis for Research-2 (MERRA-2). These are evaluated against AeroSpan (Aerosol characterisation via Sun photometry: Australian Network) ground observations which forms part of the Aerosol Robotic Network (AERONET) over the Australian continent for the 2002–2012 period. During dust storms, AeroSpan/AERONET AOD measurements were missing due to cloud screening. To overcome validation limitations in sun photometry for dust events, a nephelometer's scattering coefficient is qualitatively compared against reanalysis of DAOD at a key dust storm activation site, Tinga Tingana in South Australia (~200 km east of Lake Eyre). A specific extreme event that occurred in 2009 originating from the Lake Eyre basin, a major dust source covering one-sixth of Australia, was studied. The results show that MERRA-2 reanalysis overestimates monthly total AOD twice as much compared to AeroSpan/AERONET ground observations but seems better correlated against AeroSpan/AERONET than ECMWF/MACC. Mean data of MERRA-2 time series over 10 years provide lower DAOD values and lower dust aerosol estimates than ECMWF/MACC reanalysis (over the Lake Eyre basin with spatial averaging). Specifically at Tinga Tingana, the correlation from MERRA-2 (0.45 correlation) and ECMWF/MACC (0.43 correlation) against AeroSpan/AERONET's AOD were similar. Between MERRA-2 and ECMWF/MACC decade long daily gridded DAOD, the correlation coefficient was high at 0.73, again indicating similarity between the datasets. MERRA-2 total AOD correlation is significantly higher (by 0.26) against AeroSpan/AERONET than ECMWF/MACC. MERRA-2 also provides higher AOD values in extreme cases which may correspond to dust storms. During dust storms, a hybrid strategy using nephelometers and hourly reanalysis from MERRA-2 is able to identify dust storms better than AeroSpan/AERONET. Overall, this work can enable and inform better aerosol data assimilation into forecast models such as for solar energy, agriculture or air quality over Australia.

Methane profiles from GOSAT thermal infrared spectra

Abstract. This paper discusses the retrieval of atmospheric methane profiles from the thermal infrared band of the Japanese Greenhouse Gases Observing Satellite (GOSAT) between 1210 and 1310 cm−1, using the RemoTeC analysis software. Approximately one degree of information on the vertical methane distribution is inferred from the measurements, with the main sensitivity at about 9 km altitude but little sensitivity to methane in the lower troposphere. For verification, we compare the GOSAT-TIR methane profile retrieval results with profiles from model fields provided by the Monitoring Atmospheric Composition and Climate (MACC) project, scaled to the total column measurements of the Total Carbon Column Observing Network (TCCON) at ground-based measurement sites. Without any radiometric corrections of GOSAT observations, differences between both data sets can be as large as 10 %. To mitigate these differences, we developed a correction scheme using a principal component analysis of spectral fit residuals and airborne observations of methane during the HIAPER pole-to-pole observations (HIPPO) campaign II and III. When the correction scheme is applied, the bias in the methane profile can be reduced to less than 2 % over the whole altitude range with respect to MACC model methane fields. Furthermore, we show that, with this correction, the retrievals result in smooth methane fields over land and ocean crossings and no differences can be discerned between daytime and nighttime measurements. Finally, a cloud filter is developed for the nighttime and ocean measurements. This filter is rooted in the GOSAT-TIR (thermal infrared) measurements and its performance, in terms of biases, is consistent with the cloud filter based on the GOSAT-SWIR (shortwave infrared) measurements. The TIR filter shows a higher acceptance rate of observations than the SWIR filter, at the cost of a higher uncertainty in the retrieved methane profiles.

A revised global ozone dry deposition estimate based on a new two-layer parameterisation for air–sea exchange and the multi-year MACC composition reanalysis

Abstract. Dry deposition at the Earth's surface is an important sink of atmospheric ozone. Currently, dry deposition of ozone to the ocean surface in atmospheric chemistry models has the largest uncertainty compared to deposition to other surface types, with implications for global tropospheric ozone budget and associated radiative forcing. Most global models assume that the dominant term of surface resistance in the parameterisation of ozone dry deposition velocity at the oceanic surface is constant. There have been recent mechanistic parameterisations for air–sea exchange that account for the simultaneous waterside processes of ozone solubility, molecular diffusion, turbulent transfer, and first-order chemical reaction of ozone with dissolved iodide and other compounds, but there are questions about their performance and consistency. We present a new two-layer parameterisation scheme for the oceanic surface resistance by making the following realistic assumptions: (a) the thickness of the top water layer is of the order of a reaction–diffusion length scale (a few micrometres) within which ozone loss is dominated by chemical reaction and the influence of waterside turbulent transfer is negligible; (b) in the water layer below, both chemical reaction and waterside turbulent transfer act together and are accounted for; and (c) chemical reactivity is present through the depth of the oceanic mixing layer. The new parameterisation has been evaluated against dry deposition velocities from recent open-ocean measurements. It is found that the inclusion of only the aqueous iodide–ozone reaction satisfactorily describes the measurements. In order to better quantify the global dry deposition loss and its interannual variability, modelled 3-hourly ozone deposition velocities are combined with the 3-hourly MACC (Monitoring Atmospheric Composition and Climate) reanalysis ozone for the years 2003–2012. The resulting ozone dry deposition is found to be 98.4 ± 30.0 Tg O3 yr−1 for the ocean and 722.8 ± 87.3 Tg O3 yr−1 globally. The new estimate of the ocean component is approximately a third of the current model estimates. This reduction corresponds to an approximately 20 % decrease in the total global ozone dry deposition, which (with all other components being unchanged) is equivalent to an increase of approximately 5 % in the modelled tropospheric ozone burden and a similar increase in tropospheric ozone lifetime.

Spatial-temporal variations in surface ozone over Ushuaia and the Antarctic region: observations from in situ measurements, satellite data, and global models.

The Antarctic continent is known to be an unpopulated region due to its extreme weather and climate conditions. However, the air quality over this continent can be affected by long-lived anthropogenic pollutants from the mainland. The Argentinian region of Ushuaia is often the main source area of accumulated hazardous gases over the Antarctic Peninsula. The main objective of this study is to report the first in situ observations yet known of surface ozone (O3) over Ushuaia, the Drake Passage, and Coastal Antarctic Peninsula (CAP) on board the RV Australis during the Malaysian Antarctic Scientific Expedition Cruise 2016 (MASEC'16). Hourly O3 data was measured continuously for 23days using an EcoTech O3 analyzer. To understand more about the distribution of surface O3 over the Antarctic, we present the spatial and temporal of surface O3 of long-term data (2009-2015) obtained online from the World Meteorology Organization of World Data Centre for greenhouse gases (WMO WDCGG). Furthermore, surface O3 satellite data from the free online NOAA-Atmospheric Infrared Sounder (AIRS) database and online data assimilation from the European Centre for Medium-Range Weather Forecasts (ECMWF)-Monitoring Atmospheric Composition and Climate (MACC) were used. The data from both online products are compared to document the data sets and to give an indication of its quality towards in situ data. Finally, we used past carbon monoxide (CO) data as a proxy of surface O3 formation over Ushuaia and the Antarctic region. Our key findings were that the surface O3 mixing ratio during MASEC'16 increased from a minimum of 5ppb to ~10-13ppb approaching the Drake Passage and the Coastal Antarctic Peninsula (CAP) region. The anthropogenic and biogenic O3 precursors from Ushuaia and the marine region influenced the mixing ratio of surface O3 over the Drake Passage and CAP region. The past data from WDCGG showed that the annual O3 cycle has a maximum during the winter of 30 to 35ppb between June and August and a minimum during the summer (January to February) of 10 to 20ppb. The surface O3 mixing ratio during the summer was controlled by photochemical processes in the presence of sunlight, leading to the depletion process. During the winter, the photochemical production of surface O3 was more dominant. The NOAA-AIRS and ECMWF-MACC analysis agreed well with the MASEC'16 data but twice were higher during the expedition period. Finally, the CO past data showed the surface O3 mixing ratio was influenced by the CO mixing ratio over both the Ushuaia and Antarctic regions. Peak surface O3 and CO hourly mixing ratios reached up to ~38ppb (O3) and ~500ppb (CO) over Ushuaia. High CO over Ushuaia led to the depletion process of surface O3 over the region. Monthly CO mixing ratio over Antarctic (South Pole) were low, leading to the production of surface O3 over the Antarctic region.

Evaluating near-surface ozone levels simulated from MACC global and regional modelling systems in Eastern Mediterranean under the influence of Etesian winds

The aim of this study is to examine the ability of two modelling systems, a global and a regional, to reproduce the influence of Etesian winds on the ozone zonal distribution over Eastern Mediterranean. Specifically, the results of the global MACC (Monitoring Atmospheric Composition and Climate) reanalysis model (Integrated Forecast System - MOZART (IFS-MOZART)) and an ensemble of MACC regional air quality models (ENS) are compared versus observed data from three background monitoring stations in Central and Eastern Mediterranean (i.e. Gharb (ARB) - Malta, Finokalia (FIN) (Crete) - Greece and Agia Marina (CAO) - Cyprus). Two distinct group of days characterized by different wind flows are used for the evaluation assessment for a 5-month period (May to September) for two years (2011−2012). During the selected period, the Etesians are the predominant winds that blow from northern directions over the Aegean Sea, affecting ozone levels. The observed mean ozone concentrations at Eastern Mediterranean stations are about 5ppbv higher during Etesian days than during non-selected days whereas at the Central Mediterranean station (ARB), the difference between the two groups of days is small. Furthermore, the Eastern Mediterranean stations present generally higher observed ozone levels than the Central Mediterranean station with these differences intensifying during Etesian days. The evaluation results suggest that although the two modelling systems underestimate surface ozone concentrations systematically, they can capture to a certain extend the effect of the Etesian winds on the ozone zonal distribution. Specifically, FIN station which is directly under the influence of the Etesian winds presents higher simulated ozone values compared to the other two stations in agreement with the observations. For both modelling systems, the statistical evaluation metrics are better for the Central Mediterranean station, but there is a considerable improvement for the regional modelling system indicating that the ENS reproduces better the observed ozone values and zonal distribution in comparison to the IFS-MOZART.

Influence of Northeast Monsoon cold surges on air quality in Southeast Asia

Ozone (O3) is an important ground-level pollutant. O3 levels and emissions of O3 precursors have increased significantly over recent decades in East Asia and export of this O3 eastward across the Pacific Ocean is well documented. Here we show that East Asian O3 is also transported southward to tropical Southeast (SE) Asia during the Northeast Monsoon (NEM) season (defined as November to February), and that this transport pathway is especially strong during ‘cold surges’. Our analysis employs reanalysis data and measurements from surface sites in Peninsular Malaysia, both covering 2003–2012, along with trajectory calculations. Using a cold surge index (northerly winds at 925 hPa averaged over 105–110°E, 5°N) to define sub-seasonal strengthening of the NEM winds, we find the largest changes in a region covering much of the Indochinese Peninsula and surrounding seas. Here, the levels of O3 and another key pollutant, carbon monoxide, calculated by the Monitoring Atmospheric Composition and Climate (MACC) Reanalysis are on average elevated by, respectively, >40% (∼15 ppb) and >60% (∼80 ppb) during cold surges. Further, in the broader region of SE Asia local afternoon exceedances of the World Health Organization's air quality guideline for O3 (100 μg m−3, or ∼50 ppb, averaged over 8 h) largely occur during these cold surges. Day-to-day variations in available O3 observations at surface sites on the east coast of Peninsular Malaysia and in corresponding parts of the MACC Reanalysis are similar, and are clearly linked to cold surges. However, observed O3 levels are typically ∼10–20 ppb lower than the MACC Reanalysis. We show that these observations are also subject to influence from local urban pollution. In agreement with past work, we find year-to-year variations in cold surge activity related to the El Nino-Southern Oscillation (ENSO), but this does not appear to be the dominant influence of ENSO on atmospheric composition in this region. Overall, our study indicates that the influence of East Asian pollution on air quality in SE Asia during the NEM could be at least as large as the corresponding, well-studied spring-time influence on North America. Both an enhanced regional observational capability and chemical modelling studies will be required to fully untangle the importance of this long-range influence relative to local processes.