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The development in uncrewed aerial vehicle (UAV) technologies over the past decade has led to a plethora of platforms that can potentially enable greenhouse gas emission quantification. Here, we report the development of a new air sampler, consisting of a pumped stainless coiled tube of 150 m in length with controlled time stamping, and its deployment from an industrial UAV to quantify CO2 and CH4 emissions from the main coking plant stacks of a major steel maker in eastern China. Laboratory tests show that the time series of CO2 and CH4 measured using the sampling system is smoothed when compared to online measurement by the cavity ring-down spectrometer (CRDS) analyzer. Further analyses show that the smoothing is akin to a convolution of the true time series signals with a heavy-tailed digital filter. For field testing, the air sampler was mounted on the UAV and flown in virtual boxes around two stacks in the coking plant of the Shagang Group (steel producer). Mixing ratios of CO2 and CH4 in air and meteorological parameters were measured from the UAV during the test flight. A mass-balance computational algorithm was used on the data to estimate the CO2 and CH4 emission rates from the stacks. Using this algorithm, the emission rates for the two stacks from the coking plant were calculated to be 0.12±0.014 t h−1 for CH4 and 110±18 t h−1 for CO2, the latter being in excellent agreement with material-balance-based estimates. A Gaussian plume inversion approach was also used to derive the emission rates, and the results were compared with those derived using the mass-balance algorithm, showing a good agreement between the two methods.

Multiphase chemistry is an important pathway for the formation of secondary organic aerosols (SOAs) in the atmosphere. In this study, an indoor 2 m3 Teflon chamber system (Aerosol multIphase chemistry Research chamber, AIR) was developed and characterized to specifically simulate atmospheric multiphase chemistry processes. The temperature and humidity controls, diurnal variation simulation, and seed particle generation unit in this chamber system were designed to meet the needs of simulating multiphase atmospheric chemical reactions. The AIR chamber is able to accurately control temperature (2.5–31 ± 0.15 ∘C) and relative humidity (RH %–>95 % ± 0.75 %) over a relatively broad range. In addition, an RH regulation module inside the chamber was designed to simulate the diurnal variation of ambient atmospheric RH. The aerosol generation unit is able to generate pre-deliquescent seed particles with an organic coating across a wide range of phase states or morphologies. The organic coating thickness of the aerosols within the chamber can be precisely controlled through adjusting the condensation temperature, further helping to elucidate the roles of seed particles in multiphase chemical reactions. The inner walls of the AIR chamber are passivated to reduce the wall loss rates of reactive gases. Yield experiments of α-pinene ozonolysis with and without seed particles combined with a box model simulation demonstrate the high-quality performance of secondary aerosol formation simulation using the AIR chamber.

To combat global warming, Canada has committed to reducing greenhouse gases to be (GHGs) 40 %–45 % below 2005 emission levels by 2025. Monitoring emissions and deriving accurate inventories are essential to reaching these goals. Airborne methods can provide regional and area source measurements with small error if ideal conditions for sampling are met. In this study, two airborne mass-balance box-flight algorithms were compared to assess the extent of their agreement and their performance under various conditions. The Scientific Aviation's (SciAv) Gaussian algorithm and the Environment and Climate Change Canada's top-down emission rate retrieval algorithm (TERRA) were applied to data from five samples. Estimates were compared using standard procedures, by systematically testing other method fits, and by investigating the effects on the estimates when method assumptions were not met. Results indicate that in standard scenarios the SciAv and TERRA mass-balance box-flight methods produce similar estimates that agree (3 %–25 %) within algorithm uncertainties (4 %–34 %). Implementing a sample-specific surface extrapolation procedure for the SciAv algorithm may improve emission estimation. Algorithms disagreed when non-ideal conditions occurred (i.e., under non-stationary atmospheric conditions). Overall, the results provide confidence in the box-flight methods and indicate that emissions estimates are not overly sensitive to the choice of algorithm but demonstrate that fundamental algorithm assumptions should be assessed for each flight. Using a different method, the Airborne Visible InfraRed Imaging Spectrometer – Next Generation (AVIRIS-NG) independently mapped individual plumes with emissions 5 times larger than the source SciAv sampled three days later. The range in estimates highlights the utility of increased sampling to get a more complete understanding of the temporal variability of emissions and to identify emission sources within facilities. In addition, hourly on-site activity data would provide insight to the observed temporal variability in emissions and make a comparison to reported emissions more straightforward.

Aircraft-based lidar measurements of atmospheric aerosol and ozone were conducted to study air pollution from the oil sands extraction industry in northern Alberta. Significant amounts of aerosol were observed in the polluted air within the surface boundary layer, up to heights of 1 to 1.6 km above ground. The ozone mixing ratio measured in the polluted boundary layer air directly above the oil sands industry was equal to or less than the background ozone mixing ratio. On one of the flights, the lidar measurements detected a layer of forest fire smoke above the surface boundary layer in which the ozone mixing ratio was substantially greater than the background. Measurements of the linear depolarization ratio in the aerosol backscatter were obtained with a ground-based lidar and this aided in the discrimination between the separate emission sources from industry and forest fires. The retrieval of ozone abundance from the lidar measurements required the development of a method to account for the interference from the substantial aerosol content within the polluted boundary layer.

The wealth of air quality information provided by satellite infrared observations of ammonia (NH3), carbon monoxide (CO), formic acid (HCOOH), and methanol (CH3OH) is currently being explored and used for a number of applications, especially at regional or global scales. These applications include air quality monitoring, trend analysis, emissions, and model evaluation. This study provides one of the first direct validations of Tropospheric Emission Spectrometer (TES) satellite-retrieved profiles of NH3, CH3OH, and HCOOH through comparisons with coincident aircraft profiles. The comparisons are performed over the Canadian oil sands region during the intensive field campaign (August–September, 2013) in support of the Joint Canada–Alberta Implementation Plan for Oil Sands Monitoring (JOSM). The satellite/aircraft comparisons over this region during this period produced errors of (i) +0.08 ± 0.25 ppbv for NH3, (ii) +7.5 ± 23 ppbv for CO, (iii) +0.19 ± 0.46 ppbv for HCOOH, and (iv) −1.1 ± 0.39 ppbv for CH3OH. These values mostly agree with previously estimated retrieval errors; however, the relatively large negative bias in CH3OH and the significantly greater positive bias for larger HCOOH and CO values observed during this study warrant further investigation. Satellite and aircraft ammonia observations during the field campaign are also used in an initial effort to perform preliminary evaluations of Environment Canada's Global Environmental Multi-scale – Modelling Air quality and CHemistry (GEM-MACH) air quality modelling system at high resolution (2.5 × 2.5 km2). These initial results indicate a model underprediction of ~ 0.6 ppbv (~ 60 %) for NH3, during the field campaign period. The TES/model CO comparison differences are ~ +20 ppbv (~ +20 %), but given that under these conditions the TES/aircraft comparisons also show a small positive TES CO bias indicates that the overall model underprediction of CO is closer to ~ 10 % at 681 hPa (~ 3 km) during this period.

Top-down approaches to measure total integrated emissions provide verification of bottom-up, temporally resolved, inventory-based estimations. Aircraft-based measurements of air pollutants from sources in the Canadian oil sands were made in support of the Joint Canada–Alberta Implementation Plan for Oil Sands Monitoring during a summer intensive field campaign between 13 August and 7 September 2013. The measurements contribute to knowledge needed in support of the Joint Canada–Alberta Implementation Plan for Oil Sands Monitoring. This paper describes the top-down emission rate retrieval algorithm (TERRA) to determine facility emissions of pollutants, using SO2 and CH4 as examples, based on the aircraft measurements. In this algorithm, the flight path around a facility at multiple heights is mapped to a two-dimensional vertical screen surrounding the facility. The total transport of SO2 and CH4 through this screen is calculated using aircraft wind measurements, and facility emissions are then calculated based on the divergence theorem with estimations of box-top losses, horizontal and vertical turbulent fluxes, surface deposition, and apparent losses due to air densification and chemical reaction. Example calculations for two separate flights are presented. During an upset condition of SO2 emissions on one day, these calculations are within 5 % of the industry-reported, bottom-up measurements. During a return to normal operating conditions, the SO2 emissions are within 11 % of industry-reported, bottom-up measurements. CH4 emissions calculated with the algorithm are relatively constant within the range of uncertainties. Uncertainty of the emission rates is estimated as less than 30 %, which is primarily due to the unknown SO2 and CH4 mixing ratios near the surface below the lowest flight level.

Here we compare volatile organic compound (VOC) measurements using a standard proton-transfer-reaction quadrupole mass spectrometer (PTR-QMS) with a new proton-transfer-reaction time of flight mass spectrometer (PTR-TOF) during the Uintah Basin Winter Ozone Study 2013 (UBWOS2013) field experiment in an oil and gas field in the Uintah Basin, Utah. The PTR-QMS uses a quadrupole, which is a mass filter that lets one mass to charge ratio pass at a time, whereas the PTR-TOF uses a time of flight mass spectrometer, which takes full mass spectra with typical 0.1 s–1 min integrated acquisition times. The sensitivity of the PTR-QMS in units of counts per ppbv (parts per billion by volume) is about a factor of 10–35 times larger than the PTR-TOF, when only one VOC is measured. The sensitivity of the PTR-TOF is mass dependent because of the mass discrimination caused by the sampling duty cycle in the orthogonal-acceleration region of the TOF. For example, the PTR-QMS on mass 33 (methanol) is 35 times more sensitive than the PTR-TOF and for masses above 120 amu less than 10 times more. If more than 10–35 compounds are measured with PTR-QMS, the sampling time per ion decreases and the PTR-TOF has higher signals per unit measuring time for most masses. For UBWOS2013 the PTR-QMS measured 34 masses in 37 s and on that timescale the PTR-TOF is more sensitive for all masses. The high mass resolution of the TOF allows for the measurements of compounds that cannot be separately detected with the PTR-QMS, such as oxidation products from alkanes and cycloalkanes emitted by oil and gas extraction. PTR-TOF masses do not have to be preselected, allowing for identification of unanticipated compounds. The measured mixing ratios of the two instruments agreed very well (R2 ≥ 0.92 and within 20%) for all compounds and masses monitored with the PTR-QMS.

Natural gas production is associated with emissions of several trace gases, some of them classified as air toxics. While volatile organic compounds (VOCs) have received much attention, hydrogen sulfide (H2S) can also be of concern due to the known health impacts of exposure to this hazardous air pollutant. Here, we present quantitative, fast time-response measurements of H2S using proton-transfer-reaction mass-spectrometry (PTR-MS) instruments. An ultra-light-weight PTR-MS (ULW-PTR-MS) in a mobile laboratory was operated for measurements of VOCs and H2S in a gas and oil field during the Uintah Basin Winter Ozone Study (UBWOS) 2012 campaign. Measurements of VOCs and H2S by a PTR-MS were also made at the Horse Pool ground site in the Uintah Basin during UBWOS 2013. The H2S measurement by PTR-MS is strongly humidity dependent because the proton affinity of H2S is only slightly higher than that of water. The H2S sensitivity of PTR-MS ranged between 0.6–1.4 ncps ppbv−1 during UBWOS 2013. We compare the humidity dependence determined in the laboratory with in-field calibrations and determine the H2S mixing ratios for the mobile and ground measurements. The PTR-MS measurements at Horse Pool are evaluated by comparison with simultaneous H2S measurements using a PTR time-of-flight MS (PTR-ToF-MS) and a Picarro cavity ring down spectroscopy (CRDS) instrument for H2S / CH4. On average 0.6 ± 0.3 ppbv H2S was present at Horse Pool during UBWOS 2013. The correlation between H2S and methane enhancements suggests that the source of H2S is associated with oil and gas extraction in the basin. Significant H2S mixing ratios of up to 9 ppmv downwind of storage tanks were observed during the mobile measurements. This study suggests that H2S emissions associated with oil and gas production can lead to short-term high levels close to point sources, and elevated background levels away from those sources. In addition, our work has demonstrated that PTR-MS can make reliable measurements of H2S at levels below 1 ppbv.

Absorption photometers for real time application have been available since the 1980s, but the use of filter-based instruments to derive information on aerosol properties (absorption coefficient and black carbon, BC) is still a matter of debate. Several workshops have been conducted to investigate the performance of individual instruments over the intervening years. Two workshops with large sets of aerosol absorption photometers were conducted in 2005 and 2007. The data from these instruments were corrected using existing methods before further analysis. The inter-comparison shows a large variation between the responses to absorbing aerosol particles for different types of instruments. The unit to unit variability between instruments can be up to 30% for Particle Soot Absorption Photometers (PSAPs) and Aethalometers. Multi Angle Absorption Photometers (MAAPs) showed a variability of less than 5%. Reasons for the high variability were identified to be variations in sample flow and spot size. It was observed that different flow rates influence system performance with respect to response to absorption and instrumental noise. Measurements with non absorbing particles showed that the current corrections of a cross sensitivity to particle scattering are not sufficient. Remaining cross sensitivities were found to be a function of the total particle load on the filter. The large variation between the response to absorbing aerosol particles for different types of instruments indicates that current correction functions for absorption photometers are not adequate.