Accepted Manuscripts

Mitigating short-term global warming is imperative, and a key strategy involves the reduction of
atmospheric methane (CH4) due to its high radiative forcing and short lifespan. This objective can be
achieved through methods such as oxidising methane at its source or implementing enhanced oxidation
techniques to effectively reduce atmospheric CH4
concentrations. In this study, we use a range of
metrics to analyse both the impact and value of enhanced CH4 oxidation relative to carbon dioxide (CO2)
removal on global temperature. We apply these metrics to a select group of model studies of thermalcatalytic,
photocatalytic, biological and capture-based oxidation processes under different greenhouse
gas (GHG) concentrations. Using a target cost of €100-800/tCO2 for CO2 removal, our findings indicate
that metrics valuing enhanced oxidation techniques based on their contribution to mitigating the longterm
level of warming show these techniques are uncompetitive with CO2 removal. However, when
using metrics that value enhanced oxidation of CH4 based on its impact on the immediate rate of
warming, photocatalytic methods may be competitive with CO2 removal, whereas biofiltration and
thermal-catalytic oxidation remain uncompetitive. We conclude that if the policy goal is to target the
immediate rate of warming, it may be more valuable to incentivise CO2 removal and enhanced oxidation
of methane under separate GHG targets.

Wildfires significantly change boreal forest ecosystem carbon balance through both direct combustion and post-fire carbon dynamics. Affected vegetation influences soil thermal regime and carbon cycling by impacting the surface energy balance of boreal forests. This study uses a process-based biogeochemistry model to quantify carbon budget of North American boreal forests during 1986-2020 based on satellite-derived burn severity data. During the study period, burn severity generally increases. Fires remove ecosystem carbon of 2.4 Pg C and reduce net ecosystem production (NEP) from 32.6 to 0.8 Tg C/year, making the forest ecosystems lose 3.5 Pg C, shifting a carbon sink to a source. The canopy's cooling effect leads to lower soil temperature and lower net primary production due to lower nitrogen mineralization and uptake. Post-fire NEP decreases from 1.6 to 0.8 Tg C/year. This reduction accounts for 50% of the simulated NEP when the effects of fire-affected canopy are not considered. Our study highlights the importance of wildfires and their induced-canopy changes in soil thermal and ecosystem carbon dynamics of boreal forests.

The UK plans to significantly increase offshore wind generation capacity as part of the effort to achieve net zero targets. Current installation is densely located in a few areas, particularly off the east coast of England, and although current siting proposals include new offshore regions, significant volumes of wind generation capacity are yet to be located to meet 2050 installation targets. This paper uses a recent dataset of multi-decadal offshore wind power capacity factor timeseries to assess how UK offshore wind generation is likely to be affected by both the spatial distribution of future wind farms, and by the impacts of near-future (2020-2050) climate change. We determine that a wider geographic spread of offshore capacity results in a much-improved and less-variable UK-aggregated power generation profile, with substantial reductions in periods of low generation and extreme wind power ramping events, without negatively impacting mean or peak generation outputs. The impact of near-term climate change appears to be minor, slightly reducing overall generation and possibly resulting in an underestimation of future installation requirements, but this climate signal is outweighed by the effects of spatial distribution, and even more so by inherent hourly to inter-annual wind speed variability. This study implies that the intermittency of wind generation can be partly mitigated through increasing the spatial diversity of the existing wind farm distribution. Alongside a more in depth investigation of future climate change, and a holistic assessment of relevant geospatial factors such as Levelised Cost of Energy, infrastructure, and environmental constraints, this study could be used for optimisation of future offshore wind siting.

Urbanisation is happening worldwide. In 2100, over 70% of the population is projected to live in highly urbanised areas. As a result, urban wastewater discharge may increase. This may add multiple pollutants to rivers and coastal waters. However, current knowledge on how urbanisation-related socio-economic developments affect coastal water pollution is limited. In this study, we analysed individual and combined impacts of wastewater treatment improvements, economic growth and city expansion on future coastal water pollution from point sources (sewage and open defecation) by sub-basin taking a multi-pollutant approach. We improved the existing MARINA-Multi model (version Global-1.0) by integrating hydrology and pollutant retentions in order to quantify river exports of total dissolved nitrogen, total dissolved phosphorus, microplastics and triclosan to coastal waters for 2010 and 2100 using scenario analysis. Globally, river exports from point sources are projected to more than double by 2100 for all pollutants, especially in Africa and Asia. Wastewater treatment improvements, economic growth and city expansion can have a positive (less pollution) or negative (more pollution) impact on future coastal water pollution. These impacts differ among pollutants and sub-basins. Wastewater treatment improvements may globally reduce multi-pollutant issues (-30% to -38% change on average) compared to the reference scenario (positive impact). Economic growth and city expansion may globally enhance multi-pollutant issues (+15% to +25% and +28% to +33% change on average, respectively) compared to the reference scenario (negative impact). A combined scenario, accounting for all three socio-economic developments simultaneously, may globally reduce or enhance pollutant issues (-21% to +50% change on average) compared to the reference scenario. In the combined scenario, the reinforcements of positive and negative impacts are pollutant- and region-dependent. Our study gives insights into future coastal water pollution, which aids in identifying management strategies for urban areas, hence contributing to reaching Sustainable Development Goal 14.

The United States (US) produces oil and gas from six offshore regions: the North Slope of Alaska, Cook Inlet in Alaska, offshore California, and three Gulf of Mexico (GOM) sub-regions: state shallow, federal shallow, and deep waters. Measurement-based assessment of direct greenhouse gas emissions from this production can provide real-world information on carbon emissions to inform decisions on current and future production. In evaluating the climate impact of production, the Carbon Intensity (CI, the ratio of greenhouse gases emitted compared to the energy of fuels produced) is often used, though it is rarely quantified with measurements. Here, we complete an observational evaluation of the US offshore sector and present the largest current set of measurement-based CIs. We collected airborne measurements of methane, carbon dioxide, and nitrogen oxides from the North Slope, Cook Inlet, and California and combined with prior GOM results. For Alaska and California, we found emissions agree with facility-level inventories, however, the inventories miss some facilities. The US offshore CI, on a 100-year GWP basis, is 5.7 gCO2e/MJ[4.5, 6.8, 95% confidence interval]. This is greater than double the CI based on the national US inventory, with the discrepancy attributed primarily to methane emissions from GOM shallow waters, with a methane dominated CI of 16[12, 22] for GOM federal shallow waters and 43[25-65] for state shallow waters. Regional intensities vary, with carbon dioxide emissions largely responsible for CI on the North Slope 11[7.5, 15], in Cook Inlet 22[13, 34], offshore California 7.2[3.2, 13], and in GOM deep waters 1.1[1.0, 1.1]. These observations indicate offshore operations outside of the GOM in the US have modest methane emissions, but the CI can still be elevated due to direct carbon dioxide emissions. Accurate assessment of different offshore basins, with differing characteristics and practices, is important for the climate considerations of expanded production.

Air pollution from coal-fired electricity generation is an important cause of premature mortality in India. Although pollution-related mortality from the sector has been extensively studied, the relative contribution of individual coal-fired units to the fleet-wide mortality burden remains unclear. Here, we find that emissions from a small number of units drive overall mortality. Units producing just 3.5% of total generation and constituting less than 3% of total capacity result in 25% of annual premature mortality from coal-fired generation. This is a direct consequence of the 200-fold variation that we find in the mortality intensity of electricity generation across units. We use a detailed emissions inventory, a reduced complexity air quality model, and non-linear PM2.5 concentration-response functions to estimate marginal premature mortality for over 500 units operational in 2019. Absolute annual mortality ranges from less than 1 to over 650 deaths/year across units, and the mortality intensity of generation varies from under 0.002 to 0.43 deaths/GWh. Our findings suggest the potential for large social benefits in the form of reduced PM2.5-related premature mortality in India if the highest mortality intensity units are prioritized for the implementation of pollution control technologies or accelerated retirement.

Microplastics are ubiquitous in marine environments and can be incorporated into biological aggregates including marine snows and faecal pellets. These aggregates are suspected to be a major removal mechanism for microplastics from the surface ocean, transporting them to deeper levels and the seafloor as they sink and remineralise. However, simple budget calculations, observations, and model parameter testing suggest that aggregation might also lead to retention of microplastics in the upper ocean, sustaining contamination in biologically-productive environments. The ability of the biological microplastic sink to reduce water column contamination has relevance to the setting of ocean plastics pollution reduction targets, as are currently under negotiation by the International Negotiating Committee of the United Nations Environment Assembly (UNEA). Here we apply 8 idealised global pollution reduction trajectories, from 1-100% per year, starting from the year 2026 and ending in the year 2100 to an Earth System Climate Model with a representation of ocean microplastics and their aggregation in biological particles. We find that the global ocean microplastic inventory and surface concentrations stabilize within this century for reduction rates exceeding 5% per year but the inventory does not substantially decrease under any trajectory. Furthermore, microplastics are retained by marine biology in the surface ocean, where concentrations stabilise to a non-zero value over decades. Lastly we find that irrespective of scenario, contamination of deeper ocean layers continues to increase for the duration of our simulations via the export of microplastics by biological aggregates. These results suggest that ambitious targets for pollution reduction exceeding 5\% per year will be required to progress the resolution of the UNEA to ``end plastic pollution'' in this century, and that ongoing microplastic contamination of the marine food web may be unavoidable.

The spreading of crushed olivine-rich rocks in coastal seas to accelerate weathering reactions sequesters atmospheric CO2 and reduces atmospheric CO2 concentrations. Their weathering rates depend on different factors, including temperature and the reaction surface area. Therefore, this study investigates the variations in olivine-based enhanced weathering rates across 13 regional coasts worldwide. In addition, it assesses the CO2 sequestration within 100 years and evaluates the maximum net-sequestration potential based on varying environmental conditions. Simulations were conducted using the geochemical thermodynamic equilibrium modeling software PHREEQC. A sensitivity analysis was performed, exploring various combinations of influencing parameters, including grain size, seawater temperature, and chemistry. The findings reveal significant variation in CO2 sequestration, ranging from 0.13 to 0.94 metric tons (t) of CO2 per ton of distributed olivine-rich rocks over 100 years. Warmer coastal regions exhibit higher CO2 sequestration capacities than temperate regions, with a difference of 0.4 t CO2/ t olivine distributed. Sensitivity analysis shows that smaller grain sizes (10 µm) exhibit higher net CO2 sequestration rates (0.87 t/t) in olivine-based enhanced weathering across all conditions, attributed to their larger reactive surface area. However, in warmer seawater temperatures, olivine with slightly larger grain sizes (50 and 100 µm) displays still larger net CO2 removal rates (0.97 and 0.92 t/t), optimizing the efficiency of CO2 sequestration while reducing grinding energy requirements. While relying on a simplified sensitivity analysis that does not capture the full complexity of real-world environmental dynamics, this study contributes to understanding the variability and optimization of enhanced weathering for CO2 sequestration, supporting its potential as a sustainable CO2 removal strategy.

Marine heatwaves are the extreme anomalously warm water events which are projected to cause more and more disastrous impacts on ecosystems and economies under global ocean warming. Our ability to forecast marine heatwaves determines what effective measures can be taken to help reduce the vulnerability of marine ecosystems and human communities. In this study, we combine deep learning model explicitly the Convolutional Neural Network with a real-time sub-seasonal to seasonal physical forecast model, improving the MHW forecast skills of about 10% on global average in leading two weeks through correcting the physical model bias with the observational data. This improvement has a nearly consistent influence (~10%-20%) on a global scale, reflecting the wide-coverage promotion by deep learning. This work reveals advantages and prospects of the combination between deep learning and physical models in the ocean forecast in future.

The microphysical properties of black carbon (BC) importantly determine its absorption and hygroscopic properties. However this long-term information is difficult to obtain from field. In this study, the BC properties including the mass concentration, the coating volume ratio (VR) relative to refractory BC (rBC), the rBC diameter and the fraction of cloud condensation nuclei (CCN), are derived from a number of field experiments by a random forest model. This model effectively derives the long-term BC microphysical properties in Beijing region from 2013 to 2020 using continuous measurements of particulate matter (PM), gas, BC mass concentration and the meteorological parameters. The results reveal notably higher BC coatings (mean VR = 7.2) and a greater fraction of CCN-like BC (51%) in winter compared to other seasons. Following the implementation of national air pollution control measures in 2017, BC mass exhibited a substantial reduction of 60% (29%) in winter (summer), and VR decreased by 45% (24%). Apart from the influence of meteorological variations, these can be attributed to the declined primary emissions and the gas precursors which are associated with secondary formation of BC coatings. The reductions of both BC mass loading and coatings lead to its solar absorption decreased by 50%, and the fraction of CCN-like BC (likely in clouds) decreased by 23%. The environmental regulation will therefore continue reducing both direct and indirect radiative impacts of BC in this region.