Characterizing the State of the Urban Surface Layer Using Radon‐222

Chambers, Scott D.; Podstawczyńska, Agnieszka; Pawlak, Włodzimierz; Fortuniak, Krzysztof; Williams, Alastair G.; Griffiths, Alan D.

doi:10.1029/2018jd029507

Cited by 33 publications

(21 citation statements)

References 72 publications

(184 reference statements)

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“…When the fetch-related component of a radon time series has been separated from the diurnally-varying component, averages of the diurnal radon signal over a 10-11 h nocturnal window can be related to the mean-nocturnal mixing state [17,19,20,23,36,37]. This separation can either be made directly, using vertical radon gradient measurements [13,22], or be approximated using pseudo-gradient estimates based on single-height observations ( [19] and references therein). For the sake of brevity, a full description of the stability-classification technique will not be repeated here.…”

Section: Radon-based Stability Classificationmentioning

confidence: 99%

“…Continuous monitoring of atmospheric Radon-222 (radon) is known to be a convenient, economical, and highly-effective alternative to conventional meteorological approaches (e.g., Pasquill-Gifford typing, the Bulk Richardson method, Monin-Obukhov Similarity Theory) for classifying the nocturnal-mean (as opposed to hourly) atmospheric mixing state (e.g., [13,[17][18][19][20]). Furthermore, with the exception of highly non-stationary synoptic conditions (i.e.,~80% of the time), the average mixing state of the daytime period following each classified night can usually be inferred, based on an assumption of short-term atmospheric persistence [19]. This enables objective meteorological class-typing to be performed simply and efficiently for large datasets over whole 24-h periods.…”

Section: Introductionmentioning

confidence: 99%

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Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

Chambers

Guérette

Monk³

et al. 2019

Atmosphere

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We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

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Section: Radon-based Stability Classificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

Chambers

Guérette

Monk³

et al. 2019

Atmosphere

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“…The technique developed in this study adds another dimension to contemporary radon-based methods of characterising the atmospheric mixing state (Chambers et al, 2015(Chambers et al, , 2018Williams et al, 2016) that were developed for less complex topographic regions. Under PTI conditions contributions to radon concentration variability on synoptic timescales can dominate variability on diurnal timescales, thereby violating a 15…”

Section: Urban Air Quality During 'Persistent Temperature Inversion' mentioning

confidence: 99%

“…fundamental assumption of the approach employed by Chambers et al (2018). Consequently, nocturnal periods under PTI conditions would be misclassified below their actual degree of atmospheric stability.…”

Section: Urban Air Quality During 'Persistent Temperature Inversion' mentioning

confidence: 99%

“…The use of radon as a tracer in atmospheric studies dates back from the early 1900s (Eve, 1908;Satterly, 1910;Wigand and Wenk, 1928;Wright and Smith, 1915). In particular, however, radon has achieved considerable credibility in the field of atmospheric science as an 20 indicator of vertical mixing and transport near the Earth's surface from 1960s until nowadays (Moses et al, 1960;Kirichenko, 1962;Cohen et al, 1972;Allegrini et al, 1994;Perrino et al, 2001;Sesana et al, 2003;Galmarini, 2006;Avino and Manigrasso, 2008;Chambers et al, 2011;Williams et al, 2011Williams et al, , 2013Pitari et al, 2014;Chambers et al, 2015;Wang et al, 2016;Williams et al, 2016;Chambers et al, 2018).…”

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confidence: 99%

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Identifying ‘persistent temperature inversion’ events in a Subalpine Basin using Radon-222

Kikaj¹,

Vaupotič²,

Chambers³

2019

Preprint

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Abstract. One year of meteorological and atmospheric radon observations in a topographically-complex Subalpine Basin are used to identify ‘persistent temperature inversion’ (PTI) events. PTI events play a key role in public health due to the accumulation of urban pollutants that they cause. Two identification techniques are compared: a new method, based on single-height radon measurements from a single centrally-located station, and an existing approach based on observations from eight weather stations around the Subalpine Basin. After describing the radon-based method (RBM), its efficacy is compared with that of the existing pseudo-vertical temperature gradient method (TGM). The RBM identified 6 PTI events over the year (4 in winter, 2 in autumn), a subset of the 17 events identified by the TGM. The RBM is demonstrated to be more consistent in its identification of PTI events, and more selective of persistent strongly stable conditions. Furthermore, its performance is seasonally independent. The comparatively poor performance of the TGM was attributed to seasonal inconsistencies in the validity of the method’s key assumptions (influenced by mesoscale processes, such as local drainage flows, nocturnal jets, and intermittent turbulence influence), and a lack of snow cover in the basin for the 2016–2017 winter period. Corresponding meteorological quantities for RBM PTI events (constituting 27 % of the autumn–winter cold season), were well characterised. PTI wind speeds in the basin were consistently low over the whole diurnal cycle (typically 0.2–0.6 m s−1). The comparative efficacy of the RBM for PTI air quality assessment is demonstrated using hourly PM10 observations throughout the year. Peak hourly mean PM10 concentrations for winter (autumn) PTI events were underestimated by 13 µg m−3 (11 µg m−3) by the TGM compared with the RBM. Only the RBM indicated that nocturnal hourly mean PM10 values in winter PTI events can exceed 100 µg m−3, the upper threshold of low-level short-term PM10 exposure according to World Health Organisation guidelines. The efficacy, simplicity and cost effectiveness of the RBM for identifying PTI events has the potential to make it a powerful tool for urban air quality management in complex terrain regions; for which it adds an additional dimension to contemporary atmospheric stability classification tools. Furthermore, the long-term consistency of the radon source function will enable the RBM to be used in the same way in future studies, enabling the relative magnitude of PTI events to be gauged, which is expected to assist with the assessment of public health risks.

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Rapid improvement in air quality due to aerosol-pollution control during 2012–2018: An evidence observed in Kunshan in the Yangtze River Delta, China

Wu¹,

Zhang

Wang³

et al. 2020

Atmospheric Pollution Research

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Characterizing the State of the Urban Surface Layer Using Radon‐222

Cited by 33 publications

References 72 publications

Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

Identifying ‘persistent temperature inversion’ events in a Subalpine Basin using Radon-222

Rapid improvement in air quality due to aerosol-pollution control during 2012–2018: An evidence observed in Kunshan in the Yangtze River Delta, China

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