CH4 emission estimates from an active landfill site inferred from a combined approach of CFD modelling and in situ FTIR measurements

Globally, the waste sector contributes to nearly a fifth of anthropogenic methane emitted to the atmosphere and is the second largest source of methane in the UK. In recent years great improvements to reduce those emissions have been achieved by installation of methane recovery systems at landfill sites and subsequently methane emissions reported in national emission inventories have been reduced. Nevertheless, methane emissions of landfills remain uncertain and quantification of emission fluxes is essential to verify reported emission inventories and to monitor changes in emissions. Here we present a new approach for methane emission quantification from a complex source like a landfill site by applying a Computational Fluid Dynamics (CFD) model to calibrated in situ measurements of methane as part of a field campaign at a landfill site near Ipswich, UK, in August 2014. The methane distribution for different meteorological scenarios is calculated with the CFD model and compared to methane mole fractions measured by an in situ Fourier Transform Infrared (FTIR) spectrometer downwind of the prevailing wind direction. Assuming emissions only from the active site, a mean daytime flux of 0.83 mg m−2 s−1, corresponding to 53.26 kg h−1, was estimated. The addition of a secondary source area adjacent to the active site, where some methane hotspots were observed, improved the agreement between the simulated and measured methane distribution. As a result, the flux from the active site was reduced slightly to 0.71 mg m−2 s−1 (45.56 kg h−1), at the same time an additional flux of 0.32 mg m−2 s−1 (30.41 kg h−1) was found from the secondary source area. This highlights the capability of our method to distinguish between different emission areas of the landfill site, which can provide more detailed information about emission source apportionment compared to other methods deriving bulk emissions

A measurement-based verification framework for UK greenhouse gas emissions: an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) project

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

What effect does VOC sampling time have on derived OH reactivity?

State-of-the-art techniques allow for rapid measurements of total OH reactivity. Unknown sinks of OH and oxidation processes in the atmosphere have been attributed to what has been termed “missing” OH reactivity. Often overlooked are the differences in timescales over which the diverse measurement techniques operate. Volatile organic compounds (VOCs) acting as sinks of OH are often measured by gas chromatography (GC) methods which provide low-frequency measurements on a timescale of hours, while sampling times are generally only a few minutes. Here, the effect of the sampling time and thus the contribution of unmeasured VOC variability on OH reactivity is investigated. Measurements of VOC mixing ratios by proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) conducted during two field campaigns (ClearfLo and PARADE) in an urban and a semi-rural environment were used to calculate OH reactivity. VOCs were selected to represent variability for different compound classes. Data were averaged over different time intervals to simulate lower time resolutions and were then compared to the mean hourly OH reactivity. The results show deviations in the range of 1 to 25 %. The observed impact of VOC variability is found to be greater for the semi-rural site. The selected compounds were scaled by the contribution of their compound class to the total OH reactivity from VOCs based on concurrent gas chromatography measurements conducted during the ClearfLo campaign. Prior to being scaled, the variable signal of aromatic compounds results in larger deviations in OH reactivity for short sampling intervals compared to oxygenated VOCs (OVOCs). However, once scaled with their lower share during the ClearfLo campaign, this effect was reduced. No seasonal effect on the OH reactivity distribution across different VOCs was observed at the urban site

Experimental and modelling assessment of a novel automotive cabin PM 2.5 removal system

Poor air quality inside vehicles and its impact on human health is an issue requiring attention, with drivers and passengers facing levels of air pollution potentially greater than street-side outdoor air. This paper assesses the potential effectiveness of a car cabin filtration system to remove fine particulate matter PM2.5 and improve air quality for car passengers. The study was conducted as a practical evaluation coupled to a model implementation. First, the effectiveness of PM2.5 filter material was investigated in a chamber experiment under a range of environmental and loading conditions using a realistic automotive auxiliary scrubber. Second, implementation of such a system was evaluated in a full air flow 3D computational fluid dynamical model configured for a realistic cabin and ventilation system, and related to the chamber results through a simple decay model. Additionally, performance of low-cost dust sensors was evaluated as potential cabin monitoring devices. The experiment and modeling support the feasibility of a robust system which could be integrated into automotive designs in a straightforward manner. Results suggest that an auxiliary scrubber in the rear of the cabin alone would provide suboptimal performance, but that by incorporating a PM2.5 filter into the main air handling system, cabin PM2.5 concentrations could be reduced from 100 µg m−3 to less than 25 µg m−3 in 100 s and to 5 µg m−3 in 250 s. A health impact assessment for hypothetical occupational driver populations using such technology long term showed considerable reductions in indicative PM2.5 attributable mortality