The energy demand for heating and cooling buildings is changing with global warming. Using proxies of climate-driven energy demand based on the heating and cooling Degree-Days methodology applied to thirty global climate model simulations, we show that, over all continental areas, the climate-driven energy demand trends for heating and cooling were weak, changing by less than 10% from 1950 to 1990, but become stronger from 1990 to 2030, changing by more than 10%. With the multi-model mean, the increasing trends in cooling energy demand are more pronounced than the decreasing trends in heating. The changes in cooling, however, are highly variable depending on individual simulations, ranging from a few to several hundred percent in most of the densely populated mid-latitude areas. This work presents an example of the challenges that accompany future energy demand quantification as a result of the uncertainty in the projected climate.

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).

In June and July 2016 the Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa (DACCIWA) project organised a major international field campaign in southern West Africa (SWA) including measurements from three inland ground supersites, urban sites in Cotonou and Abidjan, radiosondes, and three research aircraft. A significant range of different weather situations were encountered during this period, including the monsoon onset. The purpose of this paper is to characterise the large-scale setting for the campaign as well as synoptic and mesoscale weather systems affecting the study region in the light of existing conceptual ideas, mainly using objective and subjective identification algorithms based on (re-)analysis and satellite products. In addition, it is shown how the described synoptic variations influence the atmospheric composition over SWA through advection of mineral dust, biomass burning and urban pollution plumes.The boreal summer of 2016 was characterised by Pacific La Niña, Atlantic El Niño and warm eastern Mediterranean conditions, whose competing influences on precipitation led to an overall average rainy season. During the relatively dusty pre-onset Phase 1 (1–21 June 2016), three westward-propagating coherent cyclonic vortices between 4 and 13° N modulated winds and rainfall in the Guinea coastal area. The monsoon onset occurred in connection with a marked extratropical trough and cold surge over northern Africa, leading to a breakdown of the Saharan heat low and African easterly jet and a suppression of rainfall. During this period, quasi-stationary low-level vortices associated with the trough transformed into more tropical, propagating disturbances resembling an African easterly wave (AEW). To the east of this system, moist southerlies penetrated deep into the continent. The post-onset Phase 2 (22 June–20 July 2016) was characterised by a significant increase in low-level cloudiness, unusually dry conditions and strong northeastward dispersion of urban pollution plumes in SWA as well as rainfall modulation by westward-propagating AEWs in the Sahel. Around 12–14 July 2016 an interesting and so-far undocumented cyclonic–anticyclonic vortex couplet crossed SWA. The anticyclonic centre had its origin in the Southern Hemisphere and transported unusually dry air filled with aged aerosol into the region. During Phase 3 (21–26 July 2016), a similar vortex couplet slightly farther north created enhanced westerly moisture transports into SWA and extraordinarily wet conditions, accompanied by a deep penetration of the biomass burning plume from central Africa. Finally, a return to more undisturbed monsoon conditions took place during Phase 4 (27–31 July 2016). The in-depth synoptic analysis reveals that several significant weather systems during the DACCIWA campaign cannot be attributed unequivocally to any of the tropical waves and disturbances described in the literature and thus deserve further study.

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.

The presence of airborne aerosols affects the meteorology as it induces a perturbation in the radiation budget, the number of cloud condensation nuclei and the cloud micro-physics. Those effects are difficult to model at regional scale as regional chemistry-transport models are usually driven by a distinct meteorological model or data. In this paper, the coupling of the CHIMERE chemistry-transport model with the WRF meteorological model using the OASIS3-MCT coupler is presented. WRF meteorological fields along with CHIMERE aerosol optical properties are exchanged through the coupler at a high frequency in order to model the aerosol–radiation interactions. The WRF-CHIMERE online model has a higher computational burden than both models run separately in offline mode (up to 42 % higher). This is mainly due to some additional computations made within the models such as more frequent calls to meteorology treatment routines or calls to optical properties computation routines. On the other hand, the overall time required to perform the OASIS3-MCT exchanges is not significant compared to the total duration of the simulations. The impact of the coupling is evaluated on a case study over Europe, northern Africa, the Middle East and western Asia during the summer of 2012, through comparisons of the offline and two online simulations (with and without the aerosol optical properties feedback) to observations of temperature, aerosol optical depth (AOD) and surface PM10 (particulate matter with diameters lower than 10 µm) concentrations. The result shows that using the optical properties feedback induces a radiative forcing (average forcing of −4.8 W m−2) which creates a perturbation in the average surface temperatures over desert areas (up to 2.6° locally) along with an increase in both AOD and PM10 concentrations.

In the framework of the Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa (DACCIWA) project, the tropospheric chemical composition in large cities along the Gulf of Guinea is studied using the Weather and Research Forecast and CHIMERE regional models. Simulations are performed for the May–July 2014 period, without and with biomass burning emissions. Model results are compared to satellite data and surface measurements. Using numerical tracer release experiments, it is shown that the biomass burning emissions in Central Africa are impacting the surface aerosol and gaseous species concentrations in Gulf of Guinea cities such as Lagos (Nigeria) and Abidjan (Ivory Coast). Depending on the altitude of the injection of these emissions, the pollutants follow different pathways: directly along the coast or over land towards the Sahel before being vertically mixed in the convective boundary layer and transported to the south-west and over the cities. In July 2014, the maximum increase in surface concentrations due to fires in Central Africa is ≈ 150 µg m⁻³ for CO, ≈ 10 to 20 µg m⁻³ for O₃ and ≈ 5 µg m⁻³ for PM₁₀. The analysis of the PM₁₀ chemical composition shows that this increase is mainly related to an increase in particulate primary and organic matter.