An accelerating global energy demand, paired with the harmful environmental effects of fossil fuels, has triggered the search for alternative, renewable energy sources. Biofuels are arguably a potential renewable energy source in the transportation industry as they can be used within current infrastructures and require less technological advances than other renewable alternatives, such as electric vehicles and nuclear power. The literature suggests biofuels can negatively impact food security and production; however, this is dependent on the type of feedstock used in biofuel production. Advanced biofuels, derived from inedible biomass, are heavily favoured but require further research and development to reach their full commercial potential. Replacing fossil fuels by biofuels can substantially reduce particulate matter (PM), carbon monoxide (CO) emissions, but simultaneously increase emissions of nitrogen oxides (NO_x), acetaldehyde (CH₃CHO) and peroxyacetyl nitrate (PAN), resulting in debates concerning the way biofuels should be implemented. The potential biofuel blends (FT-SPK, HEFA-SPK, ATJ-SPK and HFS-SIP) and their use as an alternative to kerosene-type fuels in the aviation industry have also been assessed. Although these fuels are currently more costly than conventional aviation fuels, possible reduction in production costs has been reported as a potential solution. A preliminary study shows that i-butanol emissions (1.8 Tg/year) as a biofuel can increase ozone levels by up to 6% in the upper troposphere, highlighting a potential climate impact. However, a larger number of studies will be needed to assess the practicalities and associated cost of using the biofuel in existing vehicles, particularly in terms of identifying any modifications to existing engine infrastructure, the impact of biofuel emissions, and their chemistry on the climate and human health, to fully determine their suitability as a potential renewable energy source.

The oil and gas (O&G) sector is a significant source of methane (CH₄) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH₄ emission fluxes from 21 offshore O&G facilities collected in 10 O&G fields over two regions of the Norwegian continental shelf in 2019. Emissions of CH₄ derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t yr⁻¹ (with a mean of 211 t yr⁻¹ across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes only 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH₄ emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representativity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH₄ emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritising targeted emission mitigation solutions. Future surveys of individual facilities would benefit from knowledge of facility operational status over time. Field-specific aggregated emissions (and uncertainty statistics), as presented here for the Norwegian Sea, can be meaningfully estimated from intensive aircraft surveys. However, field-specific estimates cannot be reliably extrapolated to other production fields without their own tailored surveys, which would need to capture a range of facility designs, oil and gas production volumes, and facility ages. For year-on-year comparison to annually updated inventories and regulatory emission reporting, analogous annual surveys would be needed for meaningful top-down validation. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of airborne measurement approaches to validate bottom-up accounting.

Atmospheric methane (CH₄) concentrations have more than doubled since the beginning of the industrial age, making CH₄ the second most important anthropogenic greenhouse gas after carbon dioxide (CO₂). The oil and gas sector represents one of the major anthropogenic CH₄ emitters as it is estimated to account for 22 % of global anthropogenic CH₄ emissions. An airborne field campaign was conducted in April–May 2019 to study CH₄ emissions from offshore gas facilities in the southern North Sea with the aim of deriving emission estimates using a top-down (measurement-led) approach. We present CH₄ fluxes for six UK and five Dutch offshore platforms or platform complexes using the well-established mass balance flux method. We identify specific gas production emissions and emission processes (venting and fugitive or flaring and combustion) using observations of co-emitted ethane (C₂H₆) and CO₂. We compare our top-down estimated fluxes with a ship-based top-down study in the Dutch sector and with bottom-up estimates from a globally gridded annual inventory, UK national annual point-source inventories, and operator-based reporting for individual Dutch facilities. In this study, we find that all the inventories, except for the operator-based facility-level reporting, underestimate measured emissions, with the largest discrepancy observed with the globally gridded inventory. Individual facility reporting, as available for Dutch sites for the specific survey date, shows better agreement with our measurement-based estimates. For all the sampled Dutch installations together, we find that our estimated flux of (122.9 ± 36.8) kg h⁻¹ deviates by a factor of 0.64 (0.33–12) from reported values (192.8 kg h⁻¹). Comparisons with aircraft observations in two other offshore regions (the Norwegian Sea and the Gulf of Mexico) show that measured, absolute facility-level emission rates agree with the general distribution found in other offshore basins despite different production types (oil, gas) and gas production rates, which vary by 2 orders of magnitude. Therefore, mitigation is warranted equally across geographies.

Sesquiterpenes are one of the precursors of secondary organic aerosol (SOA) which can be an important global sources of organic aerosol (OA). Updating the chemistry scheme in the global chemistry transport model by incorporating an oxidation mechanism for β‐caryophyllene (representing all sesquiterpenes), adding global sesquiterpene emissions of 29 Tg/yr, and revising global monoterpene emissions up to 162 Tg/yr [Guenther et al., 2012] led to an increase of SOA burden by 95% and SOA production rate by 106% relative to the base case described in Utembe et al. [2011]. Including the emissions of sesquiterpenes resulted in increase of SOA burden of 0.11 Tg and SOA production rate of 12.9 Tg/yr relative to the base case. The highest concentrations of sesquiterpene‐derived SOA (by up to 1.2 μg/m³) were found over central Africa and South America, the regions having high levels of biogenic emissions with significant biomass burning. In the updated model simulation, the multigeneration oxidation products from sesquiterpenes and monoterpenes transported above the boundary layer and condensed to the aerosol phase at higher altitude led to an increase of OA by up to 30% over the tropics and northern midlatitude to higher altitude. The model evaluation showed an underestimation of model OA mostly for the campaigns dominated by regional anthropogenic pollution. The increase of SOA production from sesquiterpenes reduced the discrepancies between modeled and observed OA concentrations over the remote and rural areas. The increase of SOA concentrations by up to 200% from preindustrial to present scenarios was found over the tropical oceans.

We present a method for estimating fossil fuel methane emissions using observations of methane and ethane, accounting for uncertainty in their emission ratio. The ethane:methane emission ratio is incorporated as a spatially and temporally variable parameter in a Bayesian model, with its own prior distribution and uncertainty. We find that using an emission ratio distribution mitigates bias from using a fixed, potentially incorrect emission ratio and that uncertainty in this ratio is propagated into posterior estimates of emissions. A synthetic data test is used to show the impact of assuming an incorrect ethane:methane emission ratio and demonstrate how our variable parameter model can better quantify overall uncertainty. We also use this method to estimate UK methane emissions from high-frequency observations of methane and ethane from the UK Deriving Emissions linked to Climate Change (DECC) network. Using the joint methane–ethane inverse model, we estimate annual mean UK methane emissions of approximately 0.27 (95 % uncertainty interval 0.26–0.29) Tg yr⁻¹ from fossil fuel sources and 2.06 (1.99–2.15) Tg yr⁻¹ from non-fossil fuel sources, during the period 2015–2019. Uncertainties in UK fossil fuel emissions estimates are reduced on average by 15 % and up to 35 % when incorporating ethane into the inverse model, in comparison to results from the methane-only inversion.