The impact on passenger car emissions associated with the promotion and demise of diesel fuel.

The promotion and growth in the use of diesel fuel in passenger cars in the UK and Europe over the past two decades led to considerable adverse air quality impacts in urban areas and more widely. In this work, we construct a multi-decade analysis of passenger car emissions in the UK based on real driving emissions data. An important part of the study is the use of extensive vehicle emission remote sensing data covering multiple measurement locations, time periods, environmental conditions and consisting of over 600,000 measurements. These data are used to consider two scenarios: first, that diesel fuel use was not promoted in the early 2000s for climate mitigation reasons, and second, that there was not a dramatic decline in diesel fuel use following the Dieselgate scandal. The strong growth of diesel fuel use coincided with a time when diesel NOx emissions were high and, conversely, the strong decrease of diesel fuel use coincided with a time when diesel vehicle after-treatment systems for NOx control were effective. We estimate that the growth in diesel car use in the UK results in excess NOx emissions of 721 kt over a three decade period; equivalent to over 7 times total annual passenger car NOx emissions and greater than total UK NOx emissions of 681.8 kt in 2021 and with an associated damage cost of £5.875 billion. However, the sharp move away from diesel fuel post-Dieselgate only reduced NOx emissions by 41 kt owing to the effectiveness of modern diesel aftertreatment systems.

Emission ratio determination from road vehicles using a range of remote emission sensing techniques.

The development of remote emission sensing techniques such as plume chasing and point sampling has progressed significantly and is providing new insight into vehicle emissions behaviour. However, the analysis of remote emission sensing data can be highly challenging and there is currently no standardised method available. In this study we present a single data processing approach to quantify vehicle exhaust emissions measured using a range of remote emission sensing techniques. The method uses rolling regression calculated over short time intervals to derive the characteristics of diluting plumes. We apply the method to high time-resolution plume chasing and point sampling data to quantify gaseous exhaust emission ratios from individual vehicles. Data from a series of vehicle emission characterisation experiments conducted under controlled conditions is used to demonstrate the potential of this approach. First, the method is validated through comparison with on-board emission measurements. Second, the ability of this approach to detect changes in NOx / CO2 ratios associated with aftertreatment system tampering and different engine operating conditions is shown. Third, the flexibility of the approach is demonstrated by varying the pollutants used as regression variables and quantifying the NO2 / NOx ratios for different vehicle types. A higher proportion of total NOx is emitted as NO2 when the selective catalytic reduction system of the measured heavy duty truck is tampered. In addition, the applicability of this approach to urban environments is illustrated using mobile measurements conducted in Milan, Italy in 2021. Emissions from local combustion sources are distinguished from a complex urban background and the spatiotemporal variability in emissions is shown. The mean NOx / CO2 ratio of 1.61 ppb/ppm is considered representative of the local vehicle fleet. It is envisaged that this approach can be used to quantify emissions from a range of mobile and stationary fuel combustion sources, including non-road vehicles, ships, trains, boilers and incinerators.

The air quality impacts of pre-operational hydraulic fracturing activities.

Hydraulic fracturing (fracking) is a short phase in unconventional oil and natural gas (O&G) development. Before fracking there is a lengthy period of preparation, which can represent a significant proportion of the well lifecycle. Extensive infrastructure is delivered onto site, leading to increased volumes of heavy traffic, energy generation and construction work on site. Termed the "pre-operational" period, this is rarely investigated as air quality evaluations typically focus on the extraction phase. In this work we quantify the change in air pollution during pre-operational activities at a shale gas exploration site near Kirby Misperton, North Yorkshire, England. Baseline air quality measurements were made two years prior to any shale gas activity and were used as a training dataset for random forest (RF) machine learning models. The models allowed for a comparison between observed air quality during the pre-operational phase and a counterfactual business as usual (BAU) prediction. During the pre-operational phase a significant deviation from the BAU scenario was observed. This was characterised by significant enhancements in NOx and a concurrent reduction in O3, caused by extensive additional vehicle movements and the presence of combustion sources such as generators on the well pad. During the pre-operational period NOx increased by 274 % and O3 decreased by 29 % when compared to BAU model values. There was also an increase in primary emissions of NO2 during the pre-operational phase which may have implications for the attainment of ambient air quality standards in the local surroundings. Unconventional O&G development remains under discussion as a potential option for improving the security of supply of domestic energy, tensioned however against significant environmental impacts. Here we demonstrate that the preparative work needed to begin fracking elevates air pollution in its own right, a further potential disbenefit that should be considered.

δ13C methane source signatures from tropical wetland and rice field emissions.

The atmospheric methane (CH4) burden is rising sharply, but the causes are still not well understood. One factor of uncertainty is the importance of tropical CH4 emissions into the global mix. Isotopic signatures of major sources remain poorly constrained, despite their usefulness in constraining the global methane budget. Here, a collection of new δ13CCH4 signatures is presented for a range of tropical wetlands and rice fields determined from air samples collected during campaigns from 2016 to 2020. Long-term monitoring of δ13CCH4 in ambient air has been conducted at the Chacaltaya observatory, Bolivia and Southern Botswana. Both long-term records are dominated by biogenic CH4 sources, with isotopic signatures expected from wetland sources. From the longer-term Bolivian record, a seasonal isotopic shift is observed corresponding to wetland extent suggesting that there is input of relatively isotopically light CH4 to the atmosphere during periods of reduced wetland extent. This new data expands the geographical extent and range of measurements of tropical wetland and rice δ13CCH4 sources and hints at significant seasonal variation in tropical wetland δ13CCH4 signatures which may be important to capture in future global and regional models. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.

Isotopic signatures of methane emissions from tropical fires, agriculture and wetlands: the MOYA and ZWAMPS flights.

We report methane isotopologue data from aircraft and ground measurements in Africa and South America. Aircraft campaigns sampled strong methane fluxes over tropical papyrus wetlands in the Nile, Congo and Zambezi basins, herbaceous wetlands in Bolivian southern Amazonia, and over fires in African woodland, cropland and savannah grassland. Measured methane δ13CCH4 isotopic signatures were in the range -55 to -49‰ for emissions from equatorial Nile wetlands and agricultural areas, but widely -60 ± 1‰ from Upper Congo and Zambezi wetlands. Very similar δ13CCH4 signatures were measured over the Amazonian wetlands of NE Bolivia (around -59‰) and the overall δ13CCH4 signature from outer tropical wetlands in the southern Upper Congo and Upper Amazon drainage plotted together was -59 ± 2‰. These results were more negative than expected. For African cattle, δ13CCH4 values were around -60 to -50‰. Isotopic ratios in methane emitted by tropical fires depended on the C3 : C4 ratio of the biomass fuel. In smoke from tropical C3 dry forest fires in Senegal, δ13CCH4 values were around -28‰. By contrast, African C4 tropical grass fire δ13CCH4 values were -16 to -12‰. Methane from urban landfills in Zambia and Zimbabwe, which have frequent waste fires, had δ13CCH4 around -37 to -36‰. These new isotopic values help improve isotopic constraints on global methane budget models because atmospheric δ13CCH4 values predicted by global atmospheric models are highly sensitive to the δ13CCH4 isotopic signatures applied to tropical wetland emissions. Field and aircraft campaigns also observed widespread regional smoke pollution over Africa, in both the wet and dry seasons, and large urban pollution plumes. The work highlights the need to understand tropical greenhouse gas emissions in order to meet the goals of the UNFCCC Paris Agreement, and to help reduce air pollution over wide regions of Africa. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.

Methane flux from flowback operations at a shale gas site.

We report measurements of methane (CH4) mixing ratios and emission fluxes derived from sampling at a monitoring station at an exploratory shale gas extraction facility in Lancashire, England. Elevated ambient CH4 mixing ratios were recorded in January 2019 during a period of cold-venting associated with a nitrogen lift process at the facility. These processes are used to clear the well to stimulate flow of natural gas from the target shale. Estimates of CH4 flux during the emission event were made using three independent modeling approaches: Gaussian plume dispersion (following both a simple Gaussian plume inversion and the US EPA OTM 33-A method), and a Lagrangian stochastic transport model (WindTrax). The three methods yielded an estimated peak CH4 flux during January 2019 of approximately 70 g s-1. The total mass of CH4 emitted during the six-day venting period was calculated to be 2.9, 4.2 ± 1.4(1σ) and 7.1 ± 2.1(1σ) tonnes CH4 using the simple Gaussian plume model, WindTrax, and OTM-33A methods, respectively. Whilst the flux approaches all agreed within 1σ uncertainty, an estimate of 4.2 (± 1.4) tonnes CH4 represents the most confident assessment due to the explicit modeling of advection and meteorological stability permitted using the WindTrax model. This mass is consistent with fluxes calculated by the Environment Agency (in the range 2.7 to 6.8 tonnes CH4), using emission data provided by the shale site operator to the regulator. This study provides the first CH4 emission estimate for a nitrogen lift process and the first-reported flux monitoring of a UK shale gas site, and contributes to the evaluation of the environmental impacts of shale gas operations worldwide. This study also provides forward guidance on future monitoring applications and flux calculation in transient emission events. Implications: This manuscript discusses atmospheric measurements near to the UK's first hydraulic fracturing facility, which has very high UK public, media, and policy interest. The focus of this manuscript is on a single week of data in which a large venting event at the shale gas site saw emissions of ~4 tonnes of methane to atmosphere, in breach of environmental permits. These results are likely to beresults are likely to be reported by the media and may influence future policy decisions concerning the UK hydraulic fracturing industry.

A baseline of atmospheric greenhouse gases for prospective UK shale gas sites.

We report a 24-month statistical baseline climatology for continuously-measured atmospheric carbon dioxide (CO2) and methane (CH4) mixing ratios linked to surface meteorology as part of a wider environmental baselining project tasked with understanding pre-existing local environmental conditions prior to shale gas exploration in the United Kingdom. The baseline was designed to statistically characterise high-precision measurements of atmospheric composition gathered over two full years (between February 1st 2016 and January 31st 2018) at fixed ground-based measurement stations on, or near to, two UK sites being developed for shale gas exploration involving hydraulic fracturing. The sites, near Blackpool (Lancashire) and Kirby Misperton (North Yorkshire), were the first sites approved in the UK for shale gas exploration since a moratorium was lifted in England. The sites are operated by Cuadrilla Resources Ltd. and Third Energy Ltd., respectively. A statistical climatology of greenhouse gas mixing ratios linked to prevailing local surface meteorology is presented. This study diagnoses and interprets diurnal, day-of-week, and seasonal trends in measured mixing ratios and the contributory role of local, regional and long-range emission sources. The baseline provides a set of contextual statistical quantities against which the incremental impacts of new activities (in this case, future shale gas exploration) can be quantitatively assessed. The dataset may also serve to inform the design of future case studies, as well as direct baseline monitoring design at other potential shale gas and industrial sites. In addition, it provides a quantitative reference for future analyses of the impact, and efficacy, of specific policy interventions or mitigating practices. For example, statistically significant excursions in measured concentrations from this baseline (e.g. >99th percentile) observed during phases of operational extraction may be used to trigger further examination in order to diagnose the source(s) of emission and links to on-site activities at the time, which may be of importance to regulators, site operators and public health stakeholders. A guideline algorithm for identifying these statistically significant excursions, or "baseline deviation events", from the expected baseline conditions is presented and tested. Gaussian plume modelling is used to further these analyses, by simulating approximate upper-limits of CH4 fluxes which could be expected to give observable enhancements at the monitoring stations under defined meteorological conditions.

Effects of 'pre-fracking' operations on ambient air quality at a shale gas exploration site in rural North Yorkshire, England.

Rural observations of air quality and meteorological parameters (NOx, O3, NMHCs, SO2, PM) were made over a 2.5-year period (2016-2018) before, during and after preparations for hydraulic fracturing (fracking) at a shale gas exploration site near Kirby Misperton, North Yorkshire, England. As one of the first sites to apply for permits to carry out hydraulic fracturing, it has been subject to extensive regulatory and public scrutiny, as well as the focus for a major programme of long-term environmental monitoring. A baseline period of air quality monitoring (starting 2016) established the annual climatology of atmospheric composition against which a 20-week period of intensive activity on the site in preparation for hydraulic fracturing could be compared. During this 'pre-operational phase' of work in late 2017, the most significant effect was an increase in ambient NO (3-fold) and NOx (2-fold), arising from a combination of increased vehicle activity and operation of equipment on site. Although ambient NOx increased, air quality limit values for NO2 were not exceeded, even close to the well-site. Local ozone concentrations during the pre-operational period were slightly lower than the baseline phase due to titration with primary emitted NO. The activity on site did not lead to significant changes in airborne particulate matter or non-methane hydrocarbons. Hydraulic fracturing of the well did not subsequently take place and the on-site equipment was decommissioned and removed. Air quality parameters then returned to the original (baseline) climatological conditions. This work highlights the need to characterise the full annual climatology of air quality parameters against which short-term local activity changes can be compared. Based on this study, changes to ambient NOx appear to be the most significant air quality ahead of hydraulic fracturing. However, in rural locations, concentrations at individual sites are expected to be below ambient air quality limit thresholds.

Clustering approaches to improve the performance of low cost air pollution sensors.

Low cost air pollution sensors have substantial potential for atmospheric research and for the applied control of pollution in the urban environment, including more localized warnings to the public. The current generation of single-chemical gas sensors experience degrees of interference from other co-pollutants and have sensitivity to environmental factors such as temperature, wind speed and supply voltage. There are uncertainties introduced also because of sensor-to-sensor response variability, although this is less well reported. The sensitivity of Metal Oxide Sensors (MOS) to volatile organic compounds (VOCs) changed with relative humidity (RH) by up to a factor of five over the range of 19-90% RH and with an uncertainty in the correction of a factor of two at any given RH. The short-term (second to minute) stabilities of MOS and electrochemical CO sensor responses were reasonable. During more extended use, inter-sensor quantitative comparability was degraded due to unpredictable variability in individual sensor responses (to either measurand or interference or both) drifting over timescales of several hours to days. For timescales longer than a week identical sensors showed slow, often downwards, drifts in their responses which diverged across six CO sensors by up to 30% after two weeks. The measurement derived from the median sensor within clusters of 6, 8 and up to 21 sensors was evaluated against individual sensor performance and external reference values. The clustered approach maintained the cost competitiveness of a sensor device, but the median concentration from the ensemble of sensor signals largely eliminated the randomised hour-to-day response drift seen in individual sensors and excluded the effects of small numbers of poorly performing sensors that drifted significantly over longer time periods. The results demonstrate that for individual sensors to be optimally comparable to one another, and to reference instruments, they would likely require frequent calibration. The use of a cluster median value eliminates unpredictable medium term response changes, and other longer term outlier behaviours, extending the likely period needed between calibration and making a linear interpolation between calibrations more appropriate. Through the use of sensor clusters rather than individual sensors, existing low cost technologies could deliver significantly improved quality of observations.