During the COVID‐19 outbreak that took place in early 2020, the economic activities in China were drastically reduced and accompanied by a strong reduction in the emission of primary air pollutants. On the basis of measurements made at the monitoring stations operated by the China National Environmental Monitoring Center, we quantify the reduction in surface PM_2.5, NO₂, CO, and SO₂ concentrations in northern China during the lockdown, which started on 23 January 2020. We find that, on the average, the levels of surface PM_2.5 and NO₂ have decreased by approximately 35% and 60%, respectively, between the period 1 and 22 January 2020 and the period 23 January and 29 February 2020. At the same time, the mean ozone concentration has increased by a factor 1.5–2. In urban area of Wuhan, where drastic measures were adopted to limit the spread of the coronavirus, similar changes in the concentrations of PM_2.5, NO₂, and ozone are found.

This perspective paper reviews progress made in the last decades to enhance the communication and use of climate information relevant to the political and economic decision process. It focuses, specifically, on the creation and development of climate services, and highlights a number of difficulties that have limited the success of these services. Among them are the insufficient awareness by societal actors of their vulnerability to climate change, the lack of relevant products and services offered by the scientific community, the inappropriate format in which the information is provided, and the inadequate business model adopted by climate services. The authors suggest that, to be effective, centers should host within the same center a diversity of staff including experts in climate science, specialists in impact, adaptation, and vulnerability, representatives of the corporate world, agents of the public service as well as social managers and communication specialists. The role and importance of environmental engineering is emphasized.

Under the Federal Aviation Administration’s (FAA) Aviation Climate Change Research Initiative (ACCRI), non-CO2 climatic impacts of commercial aviation are assessed for current (2006) and for future (2050) baseline and mitigation scenarios. The effects of the non-CO2 aircraft emissions are examined using a number of advanced climate and atmospheric chemistry transport models. Radiative forcing (RF) estimates for individual forcing effects are provided as a range for comparison against those published in the literature. Preliminary results for selected RF components for 2050 scenarios indicate that a 2% increase in fuel efficiency and a decrease in NOx emissions due to advanced aircraft technologies and operational procedures, as well as the introduction of renewable alternative fuels, will significantly decrease future aviation climate impacts. In particular, the use of renewable fuels will further decrease RF associated with sulfate aerosol and black carbon. While this focused ACCRI program effort has yielded significant new knowledge, fundamental uncertainties remain in our understanding of aviation climate impacts. These include several chemical and physical processes associated with NOx–O3–CH4 interactions and the formation of aviation-produced contrails and the effects of aviation soot aerosols on cirrus clouds as well as on deriving a measure of change in temperature from RF for aviation non-CO2 climate impacts—an important metric that informs decision-making.

In order to fight the spread of the global COVID-19 pandemic, most of the world's countries have taken control measures such as lockdowns during a few weeks to a few months. These lockdowns had significant impacts on economic and personal activities in many countries. Several studies using satellite and surface observations have reported important changes in the spatial and temporal distributions of atmospheric pollutants and greenhouse gases. Global and regional chemistry-transport model studies are being performed in order to analyze the impact of these lockdowns on the distribution of atmospheric compounds. These modeling studies aim at evaluating the impact of the regional lockdowns at the global scale. In order to provide input for the global and regional model simulations, a dataset providing adjustment factors (AFs) that can easily be applied to current global and regional emission inventories has been developed. This dataset provides, for the January–August 2020 period, gridded AFs at a 0.1×0.1 latitude–longitude degree resolution on a daily or monthly basis for the transportation (road, air and ship traffic), power generation, industry and residential sectors. The quantification of AFs is based on activity data collected from different databases and previously published studies. A range of AFs are provided at each grid point for model sensitivity studies. The emission AFs developed in this study are applied to the CAMS global inventory (CAMS-GLOB-ANT_v4.2_R1.1), and the changes in emissions of the main pollutants are discussed for different regions of the world and the first 6 months of 2020. Maximum decreases in the total emissions are found in February in eastern China, with an average reduction of 20 %–30 % in NO_x, NMVOCs (non-methane volatile organic compounds) and SO₂ relative to the reference emissions. In the other regions, the maximum changes occur in April, with average reductions of 20 %–30 % for NO_x, NMVOCs and CO in Europe and North America and larger decreases (30 %–50 %) in South America. In India and African regions, NO_x and NMVOC emissions are reduced on average by 15 %–30 %. For the other species, the maximum reductions are generally less than 15 %, except in South America, where large decreases in CO and BC (black carbon) are estimated. As discussed in the paper, reductions vary highly across regions and sectors due to the differences in the duration of the lockdowns before partial or complete recovery. The dataset providing a range of AFs (average and average ± standard deviation) is called CONFORM (COvid-19 adjustmeNt Factors fOR eMissions) (https://doi.org/10.25326/88; Doumbia et al., 2020). It is distributed by the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) database (https://eccad.aeris-data.fr/, last access: 23 August 2021).

We use the global Community Earth System Model to investigate the response of secondary pollutants (ozone O₃, secondary organic aerosols SOA) in different parts of the world in response to modified emissions of primary pollutants during the COVID‐19 pandemic. We quantify the respective effects of the reductions in NOx and in volatile organic carbon (VOC) emissions, which, in most cases, affect oxidants in opposite ways. Using model simulations, we show that the level of NOx has been reduced by typically 40% in China during February 2020 and by similar amounts in many areas of Europe and North America in mid‐March to mid‐April 2020, in good agreement with space and surface observations. We show that, relative to a situation in which the emission reductions are ignored and despite the calculated increase in hydroxyl and peroxy radicals, the ozone concentration increased only in a few NOx‐saturated regions (northern China, northern Europe, and the US) during the winter months of the pandemic when the titration of this molecule by NOx was reduced. In other regions, where ozone is NOx‐controlled, the concentration of ozone decreased. SOA concentrations decrease in response to the concurrent reduction in the NOx and VOC emissions. The model also shows that atmospheric meteorological anomalies produced substantial variations in the concentrations of chemical species during the pandemic. In Europe, for example, a large fraction of the ozone increase in February 2020 was associated with meteorological anomalies, while in the North China Plain, enhanced ozone concentrations resulted primarily from reduced emissions of primary pollutants.

We report on an evaluation of tropospheric ozone and its precursor gases in three atmospheric chemistry versions as implemented in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), referred to as IFS(CB05BASCOE), IFS(MOZART) and IFS(MOCAGE). While the model versions were forced with the same overall meteorology, emissions, transport and deposition schemes, they vary largely in their parameterisations describing atmospheric chemistry, including the organics degradation, heterogeneous chemistry and photolysis, as well as chemical solver. The model results from the three chemistry versions are compared against a range of aircraft field campaigns, surface observations, ozone-sondes and satellite observations, which provides quantification of the overall model uncertainty driven by the chemistry parameterisations. We find that they produce similar patterns and magnitudes for carbon monoxide (CO) and ozone (O₃), as well as a range of non-methane hydrocarbons (NMHCs), with averaged differences for O₃ (CO) within 10 % (20 %) throughout the troposphere. Most of the divergence in the magnitude of CO and NMHCs can be explained by differences in OH concentrations, which can reach up to 50 %, particularly at high latitudes. There are also comparatively large discrepancies between model versions for NO₂, SO₂ and HNO₃, which are strongly influenced by secondary chemical production and loss. Other common biases in CO and NMHCs are mainly attributed to uncertainties in their emissions. This configuration of having various chemistry versions within IFS provides a quantification of uncertainties induced by chemistry modelling in the main CAMS global trace gas products beyond those that are constrained by data assimilation.