Identifying and accounting for the Coriolis Effect in satellite NO2 observations and emission estimates

Recent developments in atmospheric remote sensing from satellites have made it possible to resolve daily emission plumes from industrial point sources, around the globe. Wind rotation aggregation coupled with statistical fitting is commonly used to extract emission estimates from these observations. These methods are used here to investigate how the Coriolis Effect influences the trajectory of observed emission plumes, and to assess the impact of this influence on satellite derived emission estimates. Of the 17 industrial sites investigated, nine showed the expected curvature for the hemisphere they reside in. Five showed no or negligible curvature, and two showed opposing or unusual curvature. The sites which showed conflicting curvature all reside in topographically diverse regions, where strong meso-gamma scale (2&ndash;20 km) turbulence dominates over larger synoptic circulation patterns. For high curvature cases the assumption that the wind-rotated plume aggregate is symmetrically distributed across the downwind axis breaks down, which impairs the quality of statistical fitting procedures. Using NOx emissions from Matimba power station as a test case, not compensating for Coriolis curvature resulted in an10 underestimation of &sim; 9 % on average for years 2018 to 2021. This study is the first formal observation of the Coriolis Effect and its influence on satellite observed emission plumes, and highlight both the variability of emission calculation methods and the need for a standardised scheme for this data to act as evidence for regulators.</p

Identifying and accounting for the Coriolis effect in satellite NO₂ observations and emission estimates

Recent developments in atmospheric remote sensing from satellites have made it possible to resolve daily emission plumes from industrial point sources around the globe. Wind rotation aggregation coupled with statistical fitting is commonly used to extract emission estimates from these observations. These methods are used here to investigate how the Coriolis effect influences the trajectory of observed emission plumes as well as to assess the impact of this influence on satellite-derived emission estimates. Of the 16 industrial sites investigated, 9 showed the expected curvature for the hemisphere that they reside in, 5 showed no or negligible curvature, and 2 showed opposing or unusual curvature. The sites that showed conflicting curvature reside in topographically diverse regions, where strong meso-γ-scale (2–20 km) turbulence dominates over larger synoptic circulation patterns. For high-curvature cases, the assumption that the wind-rotated plume aggregate is symmetrically distributed across the downwind axis breaks down, which impairs the quality of statistical fitting procedures. Using annual NOx emissions from Matimba power station as a test case, not compensating for Coriolis curvature resulted in an underestimation of ∼ 9 % on average for the years 2018 to 2021. This study is the first formal observation of the Coriolis effect and its influence on satellite-derived emission estimates, and it highlights both the variability in the emission calculation methods and the need for a standardised scheme for these data to act as evidence for regulators.</p

Satellite Data Applications for Site-Specific Air Quality Regulation in the UK:Pilot Study and Prospects

Atmospheric composition data from satellite platforms offers great potential for improving current understanding of anthropogenic emissions. Whilst this data has been used extensively in research, its use by governments to regulate and assess site-specific legislation compliance is minimal. Here, we outline the regulatory context for air quality regulation in the UK, and present a pilot study highlighting the potential of current instruments. The pilot study demonstrates the capabilities and limitations of the TROPOspheric Monitoring Instrument (TROPOMI) for detecting and isolating emissions of NO2 from regulated UK point sources. This study successfully isolated NO2 emissions from a cluster of three closely situated regulated sites in the north east of England, despite their proximity to large urban sources. This is the first time these sites have been resolved from satellite-based observations, and serves as a clear demonstration of the potential of current and future Earth observation data products for site-specific monitoring and investigation within the UK

High-resolution measurements from the airborne Atmospheric Nitrogen Dioxide Imager (ANDI)

Nitrogen dioxide is both a primary pollutant with direct health effects and a key precursor of the secondary pollutant ozone. This paper reports on the development, characterisation and test flight of the Atmospheric Nitrogen Dioxide Imager (ANDI) remote sensing system. The ANDI system includes an imaging UV/Vis grating spectrometer able to capture scattered sunlight spectra for the determination of tropospheric nitrogen dioxide (NO2) concentrations by way of DOAS slant column density and vertical column density measurements. Results are shown for an ANDI test flight over Leicester City in the UK on a cloud-free winter day in February 2013. Retrieved NO2 columns gridded to a surface resolution of 80 m × 20 m revealed hotspots in a series of locations around Leicester City, including road junctions, the train station, major car parks, areas of heavy industry, a nearby airport (East Midlands) and a power station (Ratcliffe-on-Soar). In the city centre the dominant source of NO2 emissions was identified as road traffic, contributing to a background concentration as well as producing localised hotspots. Quantitative analysis revealed a significant urban increment over the city centre which increased throughout the flight

Investigating the regional contributions to air pollution in Beijing:a dispersion modelling study using CO as a tracer

The rapid urbanization and industrialization of northern China in recent decades has resulted in poor air quality in major cities like Beijing. Transport of air pollution plays a key role in determining the relative influence of local emissions and regional contributions to observed air pollution. In this paper, dispersion modelling (Numerical Atmospheric Modelling Environment, NAME model) is used with emission inventories and in situ ground measurement data to track the pathways of air masses arriving in Beijing. The percentage of time the air masses spent over specific regions during their travel to Beijing is used to assess the effects of regional meteorology on carbon monoxide (CO), a good tracer of anthropogenic emissions. The NAME model is used with the MEIC (Multi-resolution Emission Inventory for China) emission inventories to determine the amount of pollution that is transported to Beijing from the immediate surrounding areas and regions further away. This approach captures the magnitude and variability of CO over Beijing and reveals that CO is strongly driven by transport processes. This study provides a more detailed understanding of relative contributions to air pollution in Beijing under different regional airflow conditions. Approximately 45% over a 4-year average (2013-2016) of the total CO pollution that affects Beijing is transported from other regions, and about half of this contribution comes from beyond the Hebei and Tianjin regions that immediately surround Beijing. The industrial sector is the dominant emission source from the surrounding regions and contributes over 20% of the total CO in Beijing. Finally, using PM2.5 to determine high-pollution days, three pollution classification types of pollution were identified and used to analyse the APHH winter campaign and the 4-year period. The results can inform targeted control measures to be implemented by Beijing and the surrounding provinces to tackle air quality problems that affect Beijing and China

Discrete-wavelength DOAS NO₂ slant column retrievals from OMI and TROPOMI

The use of satellite NO2 data for air quality studies is increasingly revealing the need for observations with higher spatial and temporal resolution. The study of the NO2 diurnal cycle, global sub-urban-scale observations, and identification of emission point sources are some examples of important applications not possible at the resolution provided by current instruments. One way to achieve increased spatial resolution is to reduce the spectral information needed for the retrieval, allowing both dimensions of conventional 2-D detectors to be used to record spatial information.In this work we investigate the use of 10 discrete wavelengths with the well-established differential optical absorption spectroscopy (DOAS) technique for NO2 slant column density (SCD) retrievals. To test the concept we use a selection of individual OMI and TROPOMI Level 1B swaths from various regions around the world, which contain a mixture of clean and heavily polluted areas. To discretise the data we simulate a set of Gaussian optical filters centred at various key wavelengths of the NO2 absorption cross section. We perform SCD retrievals of the discrete data using a simple implementation of the DOAS algorithm and compare the results with the corresponding Level 2 SCD products, namely QA4ECV for OMI and the operational TROPOMI product.For OMI the overall results from our discrete-wavelength retrieval are in very good agreement with the Level 2 data (mean difference <5 %). For TROPOMI the agreement is good (mean difference <11 %), with lower uncertainty owing to its higher signal-to-noise ratio. These discrepancies can be mostly explained by the differences in retrieval implementation. There are some larger differences around the centre of the swath and over water. While further research is needed to address specific retrieval issues, our results indicate that our method has potential. It would allow for simpler, more economic satellite instrument designs for NO2 monitoring at high spatial and temporal resolution. Constellations of small satellites with such instruments on board would be a valuable complement to current and upcoming high-budget hyperspectral instruments.</div

Practical Use of Metal Oxide Semiconductor Gas Sensors for Measuring Nitrogen Dioxide and Ozone in Urban Environments.

The potential of inexpensive Metal Oxide Semiconductor (MOS) gas sensors to be used for urban air quality monitoring has been the topic of increasing interest in the last decade. This paper discusses some of the lessons of three years of experience working with such sensors on a novel instrument platform (Small Open General purpose Sensor (SOGS)) in the measurement of atmospheric nitrogen dioxide and ozone concentrations. Analytic methods for increasing long-term accuracy of measurements are discussed, which permit nitrogen dioxide measurements with 95% confidence intervals of 20.0 μg m^-3 and ozone precision of 26.8 μg m^-3 , for measurements over a period one month away from calibration, averaged over 18 months of such calibrations. Beyond four months from calibration, sensor drift becomes significant, and accuracy is significantly reduced. Successful calibration schemes are discussed with the use of controlled artificial atmospheres complementing deployment on a reference weather station exposed to the elements. Manufacturing variation in the attributes of individual sensors are examined, an experiment possible due to the instrument being equipped with pairs of sensors of the same kind. Good repeatability (better than 0.7 correlation) between individual sensor elements is shown. The results from sensors that used fans to push air past an internal sensor element are compared with mounting the sensors on the outside of the enclosure, the latter design increasing effective integration time to more than a day. Finally, possible paths forward are suggested for improving the reliability of this promising sensor technology for measuring pollution in an urban environment

Experimental and modeling assessment of a novel automotive cabin PM_2.5 removal system

<p>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<i>_.</i>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<i>_.</i>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<i>_.</i>₅ filter into the main air handling system, cabin PM₂<i>_.</i>₅ concentrations could be reduced from 100 <i>µ</i>g m<i>⁻</i>³ to less than 25 <i>µ</i>g m<i>⁻</i>³ in 100 s and to 5 <i>µ</i>g m<i>⁻</i>³ in 250 s. A health impact assessment for hypothetical occupational driver populations using such technology long term showed considerable reductions in indicative PM₂<i>_.</i>₅ attributable mortality.</p> <p>Copyright © 2018 The Authors. Published with license by Taylor & Francis Group, LLC</p

Data Resource Profile: The ALSPAC birth cohort as a platform to study the relationship of environment and health and social factors.

This resource profile describes the information about the physical and social environment collected within the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. This includes spatial and temporal information gathered on three generations about: area-level built and social characteristics (e.g. density and location of fast-food outlets, crime rates within a neighbourhood); exposure measurements (e.g. air pollution concentrations, temperature records); participant-reported data directly related to the spaces and places they inhabit (e.g. neighbourhood safety, presence of damp within a home); information directly measured from participants (e.g. blood lead and total mercury concentrations, physical activity); the location information needed to link these diverse data. We describe the platform’s previous uses, strengths and weaknesses and access arrangements, emphasizing confidentiality safeguard controls. This profile highlights a particular class of ALSPAC data (with distinct access arrangements) to promote the potential for incorporating physical environment and other spatially-dependent data into research investigations