The rate of warming in the Arctic depends upon the response of low‐level microphysical and radiative cloud properties to aerosols advected from distant anthropogenic and biomass‐burning sources. Cloud droplet cross‐section density increases with higher concentrations of cloud condensation nuclei, leading to an increase of cloud droplet absorption and scattering radiative cross sections. The challenge of assessing the magnitude of the effect has been decoupling the aerosol impacts on clouds from how clouds change solely due to natural meteorological variability. Here we address this issue with large, multi‐year satellite, meteorological, and tracer transport model data sets to show that the response of low‐level clouds in the Arctic to anthropogenic aerosols lies close to a theoretical maximum and is between 2 and 8 times higher than has been observed elsewhere. However, a previously described response of arctic clouds to biomass‐burning plumes appears to be overstated because the interactions are rare and modification of cloud radiative properties appears better explained by coincident changes in temperature, humidity, and atmospheric stability.

Abstract. We report changes in surface nitrogen dioxide (NO2) across the UK during the COVID-19 pandemic when large and rapid emission reductions accompanied a nationwide lockdown (23 March–31 May 2020, inclusively), and compare them with values from an equivalent period over the previous 5 years. Data are from the Automatic Urban and Rural Network (AURN), which forms the basis of checking nationwide compliance with ambient air quality directives. We calculate that NO2 reduced by 42 %±9.8 % on average across all 126 urban AURN sites, with a slightly larger (48 %±9.5 %) reduction at sites close to the roadside (urban traffic). We also find that ozone (O3) increased by 11 % on average across the urban background network during the lockdown period. Total oxidant levels (Ox=NO2+O3) increased only slightly on average (3.2 %±0.2 %), suggesting the majority of this change can be attributed to photochemical repartitioning due to the reduction in NOx. Generally, we find larger, positive Ox changes in southern UK cities, which we attribute to increased UV radiation and temperature in 2020 compared to previous years. The net effect of the NO2 and O3 changes is a sharp decrease in exceedances of the NO2 air quality objective limit for the UK, with only one exceedance in London in 2020 up until the end of May. Concurrent increases in O3 exceedances in London emphasize the potential for O3 to become an air pollutant of concern as NOx emissions are reduced in the next 10–20 years.

Abstract. We describe the motivation, design, and execution of the Greenhouse gAs Uk and Global Emissions (GAUGE) project. The overarching scientific objective of GAUGE was to use atmospheric data to estimate the magnitude, distribution, and uncertainty of the UK greenhouse gas (GHG, defined here as CO2, CH4, and N2O) budget, 2013–2015. To address this objective, we established a multi-year and interlinked measurement and data analysis programme, building on an established tall-tower GHG measurement network. The calibrated measurement network comprises ground-based, airborne, ship-borne, balloon-borne, and space-borne GHG sensors. Our choice of measurement technologies and measurement locations reflects the heterogeneity of UK GHG sources, which range from small point sources such as landfills to large, diffuse sources such as agriculture. Atmospheric mole fraction data collected at the tall towers and on the ships provide information on sub-continental fluxes, representing the backbone to the GAUGE network. Additional spatial and temporal details of GHG fluxes over East Anglia were inferred from data collected by a regional network. Data collected during aircraft flights were used to study the transport of GHGs on local and regional scales. We purposely integrated new sensor and platform technologies into the GAUGE network, allowing us to lay the foundations of a strengthened UK capability to verify national GHG emissions beyond the project lifetime. For example, current satellites provide sparse and seasonally uneven sampling over the UK mainly because of its geographical size and cloud cover. This situation will improve with new and future satellite instruments, e.g. measurements of CH4 from the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P. We use global, nested, and regional atmospheric transport models and inverse methods to infer geographically resolved CO2 and CH4 fluxes. This multi-model approach allows us to study model spread in a posteriori flux estimates. These models are used to determine the relative importance of different measurements to infer the UK GHG budget. Attributing observed GHG variations to specific sources is a major challenge. Within a UK-wide spatial context we used two approaches: (1) Δ14CO2 and other relevant isotopologues (e.g. δ13CCH4) from collected air samples to quantify the contribution from fossil fuel combustion and other sources, and (2) geographical separation of individual sources, e.g. agriculture, using a high-density measurement network. Neither of these represents a definitive approach, but they will provide invaluable information about GHG source attribution when they are adopted as part of a more comprehensive, long-term national GHG measurement programme. We also conducted a number of case studies, including an instrumented landfill experiment that provided a test bed for new technologies and flux estimation methods. We anticipate that results from the GAUGE project will help inform other countries on how to use atmospheric data to quantify their nationally determined contributions to the Paris Agreement.

Reduced precipitation rates allow pollution within air parcels from midlatitudes to reach the Arctic without being scavenged. We use satellite and tracer transport model data sets to evaluate the degree of supercooling required for 50% of a chosen ensemble of low-level clouds to be in the ice phase for a given meteorological regime. Our results suggest that smaller cloud droplet effective radii are related to higher required amounts of supercooling but that, overall, pollution plumes from fossil fuel combustion lower the degree of supercooling that is required for freezing by approximately 4 ∘ C. The relationship between anthropogenic plumes and the freezing transition temperature from liquid to ice remains to be explained.Plain Language Summary Anthropogenic pollution plumes from midlatitudes can be transported long distances to the Arctic. In this study, we analyze the impact of these plumes on how easily liquid clouds over the Arctic Ocean freeze by using a novel combination of satellite measurements and a pollution transport model. We find that liquid clouds in polluted air switch phase to become ice clouds at temperatures that are 4 ∘ C higher they would otherwise in pristine air. Because ice clouds in the Arctic precipitate more easily than liquid clouds, the potential is that distant industrial pollution sources are acting to reduce arctic cloud life time.

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