Quantification of Gas Flaring from Satellite Imagery: A Comparison of Two Methods for SLSTR and BIROS Imagery.

Gas flaring is an environmental problem of local, regional and global concerns. Gas flares emit pollutants and greenhouse gases, yet knowledge about the source strength is limited due to disparate reporting approaches in different geographies, whenever and wherever those are considered. Remote sensing has bridged the gap but uncertainties remain. There are numerous sensors which provide measurements over flaring-active regions in wavelengths that are suitable for the observation of gas flares and the retrieval of flaring activity. However, their use for operational monitoring has been limited. Besides several potential sensors, there are also different approaches to conduct the retrievals. In the current paper, we compare two retrieval approaches over an offshore flaring area during an extended period of time. Our results show that retrieved activities are consistent between methods although discrepancies may originate for individual flares at the highly temporal scale, which are traced back to the variable nature of flaring. The presented results are helpful for the estimation of flaring activity from different sources and will be useful in a future integration of diverse sensors and methodologies into a single monitoring scheme.

Air quality in Germany as a contributing factor to morbidity from COVID-19.

BACKGROUND: The SARS-CoV-2 virus has been spreading in Germany since January 2020, with regional differences in incidence, morbidity, and mortality. Long-term exposure to air pollutants as nitrogen dioxide (NO2), nitrogen monoxide (NO), ozone (O3), and particulate matter (<10 µm PM10, <2.5 µm PM2.5) has a negative impact on respiratory functions. We analyze the association between long-term air pollution and the outcome of SARS-CoV-2 infections in Germany. METHODS: We conducted an observational study in Germany on county-level, investigating the association between long-term (2010-2019) air pollutant exposure (European Environment Agency, AirBase data set) and COVID-19 incidence, morbidity, and mortality rate during the first outbreak of SARS-CoV-2 (open source data Robert Koch Institute). We used negative binominal models, including adjustment for risk factors (age, sex, days since first COVID-19 case, population density, socio-economic and health parameters). RESULTS: After adjustment for risk factors in the tri-pollutant model (NO2, O3, PM2.5) an increase of 1 µg/m³ NO2 was associated with an increase of the need for intensive care due to COVID-19 by 4.2% (95% CI 1.011-1.074), and mechanical ventilation by 4.6% (95% CI 1.010-1.084). A tendency towards an association of NO2 with COVID-19 incidence was indicated, as the results were just outside of the defined statistical significance (+1.6% (95% CI 1.000-1.032)). Long-term annual mean NO2 level ranged from 4.6 µg/m³ to 32 µg/m³. CONCLUSIONS: Our results indicate that long-term NO2 exposure may have increased susceptibility for COVID-19 morbidity in Germany. The results demonstrate the need to reduce ambient air pollution to improve public health.

Learning from the COVID-19 lockdown in berlin: Observations and modelling to support understanding policies to reduce NO2.

Urban air pollution is a substantial threat to human health. Traffic emissions remain a large contributor to air pollution in urban areas. The mobility restrictions put in place in response to the COVID-19 pandemic provided a large-scale real-world experiment that allows for the evaluation of changes in traffic emissions and the corresponding changes in air quality. Here we use observational data, as well as modelling, to analyse changes in nitrogen dioxide, ozone, and particulate matter resulting from the COVID-19 restrictions at the height of the lockdown period in Spring of 2020. Accounting for the influence of meteorology on air quality, we found that reduction of ca. 30-50 % in traffic counts, dominated by changes in passenger cars, corresponded to reductions in median observed nitrogen dioxide concentrations of ca. 40 % (traffic and urban background locations) and a ca. 22 % increase in ozone (urban background locations) during weekdays. Lesser reductions in nitrogen dioxide concentrations were observed at urban background stations at weekends, and no change in ozone was observed. The modelled reductions in median nitrogen dioxide at urban background locations were smaller than the observed reductions and the change was not significant. The model results showed no significant change in ozone on weekdays or weekends. The lack of a simulated weekday/weekend effect is consistent with previous work suggesting that NOx emissions from traffic could be significantly underestimated in European cities by models. These results indicate the potential for improvements in air quality due to policies for reducing traffic, along with the scale of reductions that would be needed to result in meaningful changes in air quality if a transition to sustainable mobility is to be seriously considered. They also confirm once more the highly relevant role of traffic for air quality in urban areas.

APExpose_DE, an air quality exposure dataset for Germany 2010-2019.

Exposure to poor air quality is considered a major influence on the occurrence of cardiovascular and respiratory diseases. Air pollution has also been linked to the severity of the effects of epidemics such as COVID-19 caused by the SARS-CoV-2 virus. Epidemiological studies require datasets of the long-term exposure to air pollution. We present the APExpose_DE dataset, a long-term (2010-2019) dataset providing ambient air pollution metrics at yearly time resolution for NO2, NO, O3, PM10 and PM2.5 at the NUTS-3 spatial resolution level for Germany (corresponding to the Landkreis or Kreisfreie Stadt in Germany, 402 in total).

Variations in wood burning organic marker concentrations in the atmospheres of four European cities.

The particulate emissions from biomass burning are a growing concern due to the recent evidence of their ubiquitous and important contribution to the ambient aerosol load. A possible strategy to apportion the biomass burning share of particulate matter is the use of organic molecular tracers. Anhydrosugars (levoglucosan, mannosan and galactosan), together with two organic acids (dehydroabietic and pimaric acids), were previously reported as organic markers for particulate wood burning emissions. These five compounds were studied in four European cities (Helsinki, Copenhagen, Birmingham and Oporto), at both a Roadside and an Urban Background station, during a summer and a winter campaign in the fine (PM(2.5)) and the coarse (PM(10-2.5)) size-fractions of the ambient aerosol. Levoglucosan concentrations were highest in the city of Oporto. In winter, levoglucosan was more present in the fine fraction but in summer, concentrations were similar in both size fractions. Levoglucosan concentrations in the fine size fraction were higher in winter, but no seasonal differences were observed for the coarse size fraction. The lack of difference between the Roadside and Urban Background levoglucosan concentrations points towards a regional nature of this type of pollution. Wood burning was estimated to contribute to about 3.1% of the winter PM(10) mass in Oporto, and to 3.7% in Copenhagen. Mannosan followed the trends exhibited by levoglucosan. The ratio between the levoglucosan and mannosan concentrations allowed determination of a preference for softwood over hardwood in all four cities. Galactosan, pimaric acid and dehydroabietic acid were found to be minor compounds.

Application of the integrating sphere method to separate the contributions of brown and black carbon in atmospheric aerosols.

Until about a decade ago, black carbon (BC) was thought to be the only light absorbing substance in the atmospheric aerosol except for soil or desert dust In more recent years, light absorbing polymeric carbonaceous material was found in atmospheric aerosols. Absorption increases appreciably toward short wavelengths, so this fraction was called brown carbon. Because brown carbon is thermally rather refractory, it influences the split between organic carbon (OC) and elemental carbon (EC) in thermal methods and, through its light absorption characteristics, leads to overestimations of BC concentrations. The goal of the present study was to extend the integrating sphere method to correct the BC signal for the contribution of brown carbon and to obtain an estimate of brown carbon concentrations. Humic acid sodium salt was used as proxy for brown carbon. The extended method is first tested on mixtures of test substances and then applied to atmospheric samples collected during biomass smoke episodes (Easter bonfires) in Austria. The resulting concentrations of black and brown carbon are compared to EC obtained with a widely used thermal method, the Cachier method (Cachier et al. Tellus 1989, 41B, 379-390) and a thermal-optical method (Schmid et al. Atmos. Environ. 2001, 35, 2111-2121), as well as to concentrations of humic like substances (HULIS) and to biomass smoke POM (particulate organic matter). Both the thermal methods were found to overestimate BC on days with large contributions of woodsmoke, which agrees with the findings of the method intercomparison study by Reisinger et at. (Environ. Sci. Technol. 2008, 42, 884-889). During the days of the bonfires, the Cachier method gave EC concentrations that were higher by a factor of 3.8 than the BC concentrations, while the concentrations obtained with the thermal-optical method were higher by a factor of 2.6.

Source attribution of submicron organic aerosols during wintertime inversions by advanced factor analysis of aerosol mass spectra.

Real-time measurements of submicrometer aerosol were performed using an Aerodyne aerosol mass spectrometer (AMS) during three weeks at an urban background site in Zurich (Switzerland) in January 2006. A hybrid receptor model which incorporates a priori known source composition was applied to the AMS highly time-resolved organic aerosol mass spectra. Three sources and components of submicrometer organic aerosols were identified: the major component was oxygenated organic aerosol (OOA), mostly representing secondary organic aerosol and accounting on average for 52-57% of the particulate organic mass. Radiocarbon (14C) measurements of organic carbon (OC) indicated that approximately 31 and approximately 69% of OOA originated from fossil and nonfossil sources, respectively. OOA estimates were strongly correlated with measured particulate ammonium. Particles from wood combustion (35-40%) and 3-13% traffic-related hydrocarbon-like organic aerosol (HOA) accounted for the other half of measured organic matter (OM). Emission ratios of modeled HOA to measured nitrogen oxides (NOx) and OM from wood burning to levoglucosan from filter analyses were found to be consistent with literature values.

Determination of saccharides in atmospheric aerosol using anion-exchange high-performance liquid chromatography and pulsed-amperometric detection.

An improved method is described for the quantification of primary sugars, sugar alcohols and anhydrosugars in atmospheric aerosols, making use of separation by high-performance anion-exchange chromatography (HPAEC) with pulsed amperometric detection (PAD). Quartz fibre filters from high-volume samplers were extracted with water and the extract injected directly. Repeatability is typically 4% RSD, for e.g. levoglucosan at 50 ng m(-3) in air, better for winter levels around 700 ng m(-3). Limits of detection for individual sugars are in the range 0.02-0.05 microg mL(-1) in solution, corresponding to 2-5 ng m(-3) from a 20 m(3) air sample. The overlap of arabitol and levogluocosan is overcome by using a Dionex PA-1 column, with appropriate control of eluent composition, and peak deconvolution software, allowing quantification of both sugars in difficult summer samples containing low-levels of levoglucosan. Analysis of a set of ambient aerosol samples by both GC-flame ionization detection and HPAEC-PAD shows good agreement. The new method has the advantage of requiring no sample pretreatment or derivatization and is thus well suited to handling large numbers of samples.