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Fitting sulfur dioxide (SO2) differential slant column densities (dSCDs) from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of scattered sunlight is challenging because actinic light intensity is low in the wavelength regions where the SO2 absorption features are strongest. SO2 dSCDs were fit with different wavelength windows (λlow to λhigh) from ambient measurements with calibration cells of 2.2×1017 and 2.2×1016 molec. cm−2 inserted in the light path at different viewing elevation angles using an Ocean Optics USB2000 spectrometer in a miniature MAX-DOAS instrument. SO2 dSCDs were the least accurate, and fit errors were highest for fitting windows with λlow 312 nm. The SO2 dSCDs also exhibited an inverse relationship with the depth of the differential features in the SO2 absorption cross section for fitting windows with λlow 400 nm. Deviation of the SO2 dSCD from the true value depended on the SO2 concentration for some fitting windows rather than exhibiting a consistent bias. Uncertainties in the SO2 dSCD reported by the fit algorithm were more than 50 % less than the true error for many windows, particularly for the measurements without the filter or offset function. For retrievals with the filter or offset function, increasing λhigh > 320 nm tended to decrease the reported fit uncertainty but did not increase the accuracy. Based on the results of this study, a short-pass filter and a fitting window of 307.5

ObjectivesTo understand SARS-Co-V-2 infection and transmission in UK nursing homes in order to develop preventive strategies for protecting the frail elderly residents.DesignAn outbreak investigation.Setting4 nursing homes affected by COVID-19 outbreaks in central London.Participants394 residents and 70 staff in nursing homes.InterventionsTwo point-prevalence surveys one week apart where residents underwent SARS-CoV-2 testing and had relevant symptoms documented. Asymptomatic staff from three of the four homes were also offered SARS-CoV-2 testing.Main outcome measuresAll-cause mortality, and mortality attributed to COVID-19 on death certificates. Prevalence of SARS-CoV-2 infection and symptoms in residents and staff.ResultsOverall, 26% (95% confidence interval 22 to 31) of residents died over the two-month period. All-cause mortality increased by 203% (95% CI 70 to 336). Systematic testing identified 40% (95% CI 35 to 46) of residents, of whom 43% (95% CI 34 to 52) were asymptomatic and 18% (95% CI 11 to 24) had atypical symptoms, as well as 4% (95% CI -1 to 9) of asymptomatic staff who tested positive for SARS-CoV-2.ConclusionsThe SARS-CoV-2 outbreak was associated with a very high mortality rate in residents of nursing homes. Systematic testing of all residents and a representative sample of staff identified high rates of SARS-CoV-2 positivity across the four nursing homes, highlighting a potential for regular screening to prevent future outbreaks.

The oil and gas (O&G) sector represents a large source of greenhouse gas (GHG) emissions globally. However, estimates of O&G emissions rely upon bottom-up approaches, and are rarely evaluated through atmospheric measurements. Here, we use aircraft measurements over the Canadian oil sands (OS) to derive the first top-down, measurement-based determination of the their annual CO2 emissions and intensities. The results indicate that CO2 emission intensities for OS facilities are 13–123% larger than those estimated using publically available data. This leads to 64% higher annual GHG emissions from surface mining operations, and 30% higher overall OS GHG emissions (17 Mt) compared to that reported by industry, despite emissions reporting which uses the most up to date and recommended bottom-up approaches. Given the similarity in bottom-up reporting methods across the entire O&G sector, these results suggest that O&G CO2 emissions inventory data may be more uncertain than previously considered., Evaluating GHG emissions reported to inventories for the oil and gas (O&G) sector is important for countries with resource-based economies. Here the authors provide a top-down assessment of GHG emissions from the Canadian oil sands and find previous inventory reports underestimate emissions, by as much as 64% for surface mining facilities and 30% for the entire oil sands compared with their assessment.

Fitting SO2 dSCDs from MAX-DOAS measurements of scattered sunlight is challenging because actinic light intensity is low in wavelength regions where the SO2 absorption features are strongest. SO2 dSCDs were fit with different wavelength windows (λlow to λhigh) from ambient measurements with calibration cells of 2.2 × 1017 and 2.2 × 1016 molec cm−2 inserted in the light path at different viewing elevation angles. SO2 dSCDs were the least accurate and fit errors were the largest for fitting windows with λlow 312 nm. The SO2 dSCDs also exhibited an inverse relationship with the SO2 absorption cross-section for fitting windows with λlow 400 nm. Deviation of the SO2 dSCD from the true value depended on the SO2 concentration for some fitting windows rather than exhibiting a consistent bias. Uncertainties of the SO2 dSCD reported by the fit algorithm were significantly less than the true error for many windows, particularly for the measurements without the filter or offset function. For retrievals with the filter or offset function, increasing λhigh > 320 nm tended to decrease the reported fit uncertainty but did not increase the accuracy. Based on the results of this study, a short-pass filter and a fitting window of 307.5

Aircraft-based measurements of methane (CH4) and other air pollutants in the Athabasca Oil Sands Region (AOSR) were made during a summer intensive field campaign between 13 August and 7 September 2013 in support of the Joint Canada–Alberta Implementation Plan for Oil Sands Monitoring. Chemical signatures were used to identify CH4 sources from tailings ponds (BTEX VOCs), open pit surface mines (NOy and rBC) and elevated plumes from bitumen upgrading facilities (SO2 and NOy). Emission rates of CH4 were determined for the five primary surface mining facilities in the region using two mass-balance methods. Emission rates from source categories within each facility were estimated when plumes from the sources were spatially separable. Tailings ponds accounted for 45 % of total CH4 emissions measured from the major surface mining facilities in the region, while emissions from operations in the open pit mines accounted for ∼ 50 %. The average open pit surface mining emission rates ranged from 1.2 to 2.8 t of CH4 h−1 for different facilities in the AOSR. Amongst the 19 tailings ponds, Mildred Lake Settling Basin, the oldest pond in the region, was found to be responsible for the majority of tailings ponds emissions of CH4 ( > 70 %). The sum of measured emission rates of CH4 from the five major facilities, 19.2 ± 1.1 t CH4 h−1, was similar to a single mass-balance determination of CH4 from all major sources in the AOSR determined from a single flight downwind of the facilities, 23.7 ± 3.7 t CH4 h−1. The measured hourly CH4 emission rate from all facilities in the AOSR is 48 ± 8 % higher than that extracted for 2013 from the Canadian Greenhouse Gas Reporting Program, a legislated facility-reported emissions inventory, converted to hourly units. The measured emissions correspond to an emissions rate of 0.17 ± 0.01 Tg CH4 yr−1 if the emissions are assumed as temporally constant, which is an uncertain assumption. The emission rates reported here are relevant for the summer season. In the future, effort should be devoted to measurements in different seasons to further our understanding of the seasonal parameters impacting fugitive emissions of CH4 and to allow for better estimates of annual emissions and year-to-year variability.

Atmospheric emissions of gas and particulate matter from a large ocean-going container vessel were sampled as it slowed and switched from high-sulfur to low-sulfur fuel as it transited into regulated coastal waters of California. Reduction in emission factors (EFs) of sulfur dioxide (SO 2), particulate matter, particulate sulfate and cloud condensation nuclei were substantial (≥90%). EFs for particulate organic matter decreased by 70%. Black carbon (BC) EFs were reduced by 41%. When the measured emission reductions, brought about by compliance with the California fuel quality regulation and participation in the vessel speed reduction (VSR) program, are placed in a broader context, warming from reductions in the indirect effect of SO 4 would dominate any radiative changes due to the emissions changes. Within regulated waters absolute emission reductions exceed 88% for almost all measured gas and particle phase species. The analysis presented provides direct estimations of the emissions reductions that can be realized by California fuel quality regulation and VSR program, in addition to providing new information relevant to potential health and climate impact of reduced fuel sulfur content, fuel quality and vessel speed reductions. © 2011 American Chemical Society.

The Uintah Basin in northeastern Utah, a region of intense oil and gas extraction, experienced ozone (O3) concentrations above levels harmful to human health for multiple days during the winters of 2009–2010 and 2010–2011. These wintertime O3 pollution episodes occur during cold, stable periods when the ground is snow-covered, and have been linked to emissions from the oil and gas extraction process. The Uintah Basin Winter Ozone Study (UBWOS) was a field intensive in early 2012, whose goal was to address current uncertainties in the chemical and physical processes that drive wintertime O3 production in regions of oil and gas development. Although elevated O3 concentrations were not observed during the winter of 2011–2012, the comprehensive set of observations tests our understanding of O3 photochemistry in this unusual emissions environment. A box model, constrained to the observations and using the near-explicit Master Chemical Mechanism (MCM) v3.2 chemistry scheme, has been used to investigate the sensitivities of O3 production during UBWOS 2012. Simulations identify the O3 production photochemistry to be highly radical limited (with a radical production rate significantly smaller than the NOx emission rate). Production of OH from O3 photolysis (through reaction of O(1D) with water vapor) contributed only 170 pptv day−1, 8% of the total primary radical source on average (primary radicals being those produced from non-radical precursors). Other radical sources, including the photolysis of formaldehyde (HCHO, 52%), nitrous acid (HONO, 26%), and nitryl chloride (ClNO2, 13%) were larger. O3 production was also found to be highly sensitive to aromatic volatile organic compound (VOC) concentrations, due to radical amplification reactions in the oxidation scheme of these species. Radical production was shown to be small in comparison to the emissions of nitrogen oxides (NOx), such that NOx acted as the primary radical sink. Consequently, the system was highly VOC sensitive, despite the much larger mixing ratio of total non-methane hydrocarbons (230 ppbv (2080 ppbC), 6 week average) relative to NOx (5.6 ppbv average). However, the importance of radical sources which are themselves derived from NOx emissions and chemistry, such as ClNO2 and HONO, make the response of the system to changes in NOx emissions uncertain. Model simulations attempting to reproduce conditions expected during snow-covered cold-pool conditions show a significant increase in O3 production, although calculated concentrations do not achieve the highest seen during the 2010–2011 O3 pollution events in the Uintah Basin. These box model simulations provide useful insight into the chemistry controlling winter O3 production in regions of oil and gas extraction.

The MC2-CALGRID photochemical modeling system is used to simulate the impact of two fuel substitution scenarios on ozone levels for a future year in the Lower Fraser Valley of British Columbia, Canada. The relative impacts of selected natural gas and propane vehicle technologies are compared for the year 2005. The chosen natural gas technology imposes large reductions in nonmethane hydrocarbon emissions with moderate reductions in nitrogen oxide emissions, while the propane technology greatly lowers nitrogen oxide emissions with only small changes to nonmethane hydrocarbon emissions. The model results showed that replacing the entire light-duty gasoline car and truck fleet with the selected natural gas vehicle technology in the year 2005 in the Canadian portion of the Lower Fraser Valley yielded significant benefits in terms of reducing potential exposures to elevated ozone levels in suburban and rural areas. Sites closer to the urban core were less affected. For the propane fuel substitution, benefits were realized in terms of lowering ozone concentrations and ozone exposures in the rural areas. Within the urban and suburban areas, ozone exposures tended to increase. The exposures to peroxyacetyl nitrate were universally smaller in the alternative fuel scenarios. The nature of an effective control strategy for the Lower Fraser Valley is discussed, and it is suggested that in addition to the propane fuel substitution, moderate controls on the primary NOx sources in conjunction with moderate nonmethane hydrocarbon controls could be the preferred route to lower ozone exposures.

In this paper, we compare primary and secondary formation of air toxics and formation of ozone resulting from emissions from gasoline and M85 (85% methanol and 15% gasoline) fuelled vehicles using a photochemical model. Emissions from vehicles representing 1992 technology are taken from the CleanFleet demonstration program in the South Coast Air Basin of California, supplemented with data from the Auto/Oil Air Quality Improvement Research Program. The secondary formation of formaldehyde (H2CO), acetaldehyde (CH3CHO), and peroxyacetyl nitrate (PAN), are based on model scenarios of an ozone episode in southern Ontario, Canada. Also, the results indicate that relative to the gasoline scenarios, the M85 scenarios produce lower ambient concentrations of ozone, CH11CHO, and PAN, and slightly higher concentrations of H2CO for several exposure metrics

Laser-induced thermal modulation of electrical conductivity is a new photothermal method for the measurement of minute absorbance in sub-nanoliter liquid samples. In this paper, a model is presented for the technique. This model is based upon the interaction of a Gaussian laser beam with a cylindrical, homogeneous electrolytic resistor. Particularly simple results are produced if the laser beam spot size is much smaller than the diameter of the electrodes. The theory is verified with respect to the electrode spacing and to the laser power, spot size, and chopping frequency; the highest sensitivity occurs with low chopping frequency, high laser power, and small electrode spacing. The signal is independent of laser spot size, as long as the beam does not illuminate the electrode surface. The precision of the measurement is dominated by shot noise in the current flow through the electrolytic resistor. One point absorbance detection limits of 5.5 × 10−6 measured across the 76-μm diameter electrode wires are obtained in aqueous solution with a 5- mW helium–neon laser. With this instrument, the difference in the absorbance of water and deuterated water is easily determined at 632.8 nm. Keywords: thermal modulation of electrical conductivity.