Satellite instruments have been providing measurements of global volcanic emissions of sulfur dioxide (SO2) since 1978, based on observations in the ultraviolet (UV), infrared (IR) and microwave spectral bands. We review recent advances in satellite remote sensing of volcanic gases, focusing on increased instrument sensitivity to tropospheric SO2 emissions and techniques to determine volcanic plume altitude. A synthesis of ~36 years of global UV, IR and microwave satellite measurements yields an updated assessment of the volcanic SO2 flux to the upper troposphere and lower stratosphere (UTLS) between 1978 and 2014 (~1-Tg/yr). The present availability of multiple UV and IR satellite SO2 products provides increased confidence in calculated SO2 loadings for many eruptions. We examine the temporal and latitudinal distribution of volcanic SO2 emissions and reassess the relationship between eruptive SO2 discharge and eruption magnitude, finding a first-order correlation between SO2 emission and volcanic explosivity index (VEI), but with significant scatter. Based on the observed SO2-VEI relation, we estimate the fraction of eruptive SO2 emissions released by the smallest eruptions (~0.48 Tg/yr), which is not recorded by satellite observations. A detailed breakdown of the sources of measured SO2 emissions reveals intuitively expected correlations between eruption frequency, SO2 loading and volcanic degassing style. We discuss new constraints on e-folding times for SO2 removal in volcanic plumes, and highlight recent measurements of volcanic hydrogen chloride (HCl) injections into the UTLS. An analysis of passive volcanic emissions of SO2 detected in Ozone Monitoring Instrument (OMI) SO2 data since 2004 provides new insight into the location and stability of the dominant sources of volcanic SO2 over the past decade. Since volcanic SO2 emissions constitute a random, highly variable perturbation to the atmosphere-climate system, continued monitoring of volcanic SO2 emissions from space by multiple UV and IR instruments to extend the current multi-decadal record is essential, and near-global, geostationary measurements of SO2 may be available by the end of the current decade.SCOPUS: re.jinfo:eu-repo/semantics/publishe

To mitigate the impact of greenhouse gas (GHG) and air pollutant emissions, it is of utmost importance to understand where emissions occur. In the real world, atmospheric pollutants are produced by various human activities from point sources (e.g. power plants and industrial facilities) but also from diffuse sources (e.g. residential activities and agriculture). However, as tracking all these single sources of emissions is practically impossible, emission inventories are typically compiled using national-level statistics by sector, which are then downscaled at the grid-cell level using spatial information. In this work, we develop high-spatial-resolution proxies for use in downscaling the national emission totals for all world countries provided by the Emissions Database for Global Atmospheric Research (EDGAR). In particular, in this paper, we present the latest EDGAR v8.0 GHG, which provides readily available emission data at different levels of spatial granularity, obtained from a consistently developed GHG emission database. This has been achieved through the improvement and development of high-resolution spatial proxies that allow for a more precise allocation of emissions over the globe. A key novelty of this work is the potential to analyse subnational GHG emissions over the European territory and also over the United States, China, India, and other high-emitting countries. These data not only meet the needs of atmospheric modellers but can also inform policymakers working in the field of climate change mitigation. For example, the EDGAR GHG emissions at the NUTS 2 level (Nomenclature of Territorial Units for Statistics level 2) over Europe contribute to the development of EU cohesion policies, identifying the progress of each region towards achieving the carbon neutrality target and providing insights into the highest-emitting sectors. The data can be accessed at https://doi.org/10.2905/b54d8149-2864-4fb9-96b9-5fd3a020c224 specifically for EDGAR v8.0 (Crippa et al., 2023a) and https://doi.org/10.2905/D67EEDA8-C03E-4421-95D0-0ADC460B9658 for the subnational dataset (Crippa et al., 2023b).

Ammonia (NH3) emissions in the atmosphere have increased substantially over the past decades, largely because of intensive livestock production and use of fertilizers. As a short-lived species, NH3 is highly variable in the atmosphere and its concentration is generally small, except near local sources. While ground-based measurements are possible, they are challenging and sparse. Advanced infrared sounders in orbit have recently demonstrated their capability to measure NH3, offering a new tool to refine global and regional budgets. In this paper we describe an improved retrieval scheme of NH3 total columns from the measurements of the Infrared Atmospheric Sounding Interferometer (IASI). It exploits the hyperspectral character of this instrument by using an extended spectral range (800–1200 cm−1) where NH3 is optically active. This scheme consists of the calculation of a dimensionless spectral index from the IASI level1C radiances, which is subsequently converted to a total NH3 column using look-up tables built from forward radiative transfer model simulations. We show how to retrieve the NH3 total columns from IASI quasi-globally and twice daily above both land and sea without large computational resources and with an improved detection limit. The retrieval also includes error characterization of the retrieved columns. Five years of IASI measurements (1 November 2007 to 31 October 2012) have been processed to acquire the first global and multiple-year data set of NH3 total columns, which are evaluated and compared to similar products from other retrieval methods. Spatial distributions from the five years data set are provided and analyzed at global and regional scales. In particular, we show the ability of this method to identify smaller emission sources than those previously reported, as well as transport patterns over the ocean. The five-year time series is further examined in terms of seasonality and interannual variability (in particular as a function of fire activity) separately for the Northern and Southern Hemispheres.

Excess atmospheric ammonia (NH₃) leads to deleterious effects on biodiversity, ecosystems, air quality and health, and it is therefore essential to monitor its budget and temporal evolution. Hyperspectral infrared satellite sounders provide daily NH₃ observations at global scale for over a decade. Here we use the version 3 of the Infrared Atmospheric Sounding Interferometer (IASI) NH₃ dataset to derive global, regional and national trends from 2008 to 2018. We find a worldwide increase of 12.8 ± 1.3 % over this 11-year period, driven by large increases in east Asia (5.80 ± 0.61% increase per year), western and central Africa (2.58 ± 0.23 % yr⁻¹), North America (2.40 ± 0.45 % yr⁻¹) and western and southern Europe (1.90 ± 0.43 % yr⁻¹). These are also seen in the Indo-Gangetic Plain, while the southwestern part of India exhibits decreasing trends. Reported national trends are analyzed in the light of changing anthropogenic and pyrogenic NH₃ emissions, meteorological conditions and the impact of sulfur and nitrogen oxides emissions, which alter the atmospheric lifetime of NH₃. We end with a short case study dedicated to the Netherlands and the ‘Dutch Nitrogen crisis’ of 2019.

Producing a global and comprehensive description of atmospheric aerosols requires integration of ground-based, airborne, satellite and model datasets. Due to its complexity, aerosol monitoring requires the use of several data records with complementary information content. This paper describes the lessons learned while developing and qualifying algorithms to generate aerosol Climate Data Records (CDR) within the European Space Agency (ESA) Aerosol_cci project. An iterative algorithm development and evaluation cycle involving core users is applied. It begins with the application-specific refinement of user requirements, leading to algorithm development, dataset processing and independent validation followed by user evaluation. This cycle is demonstrated for a CDR of total Aerosol Optical Depth (AOD) from two subsequent dual-view radiometers. Specific aspects of its applicability to other aerosol algorithms are illustrated with four complementary aerosol datasets. An important element in the development of aerosol CDRs is the inclusion of several algorithms evaluating the same data to benefit from various solutions to the ill-determined retrieval problem. The iterative approach has produced a 17-year AOD CDR, a 10-year stratospheric extinction profile CDR and a 35-year Absorbing Aerosol Index record. Further evolution cycles have been initiated for complementary datasets to provide insight into aerosol properties (i.e., dust aerosol, aerosol absorption).