Multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations of formaldehyde and nitrogen dioxide at three sites in Asia and comparison with the global chemistry transport model CHASER

Abstract

Abstract. Formaldehyde (HCHO) and nitrogen dioxide (NO2) concentrations and profiles were retrieved from ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations during January 2017–December 2018 at three sites in Asia: (1) Phimai (15.18∘ N, 102.5∘ E), Thailand; (2) Pantnagar (29∘ N, 78.90∘ E) in the Indo-Gangetic Plain (IGP), India; and (3) Chiba (35.62∘ N, 140.10∘ E), Japan. Retrievals were performed using the Japanese MAX-DOAS profile retrieval algorithm ver. 2 (JM2). The observations were used to evaluate the NO2 and HCHO partial columns and profiles (0–4 km) simulated using the global chemistry transport model (CTM) CHASER (Chemical Atmospheric General Circulation Model for Study of Atmospheric Environment and Radiative Forcing). The NO2 and HCHO concentrations at all three sites showed consistent seasonal variation throughout the investigated period. Biomass burning affected the HCHO and NO2 variations at Phimai during the dry season and at Pantnagar during spring (March–May) and post-monsoon (September–November). Results found for the HCHO-to-NO2 ratio (RFN), an indicator of high ozone sensitivity, indicate that the transition region (i.e., 1 < RFN < 2) changes regionally, echoing the recent finding for RFN effectiveness. Moreover, reasonable estimates of transition regions can be derived, accounting for the NO2–HCHO chemical feedback. The model was evaluated against global NO2 and HCHO columns data retrieved from Ozone Monitoring Instrument (OMI) observations before comparison with ground-based datasets. Despite underestimation, the model well simulated the satellite-observed global spatial distribution of NO2 and HCHO, with respective spatial correlations (r) of 0.73 and 0.74. CHASER demonstrated good performance, reproducing the MAX-DOAS-retrieved HCHO and NO2 abundances at Phimai, mainly above 500 m from the surface. Model results agree with the measured variations within the 1-sigma (1σ) standard deviation of the observations. Simulations at higher resolution improved the modeled NO2 estimates for Chiba, reducing the mean bias error (MBE) for the 0–2 km height by 35 %, but resolution-based improvements were limited to surface layers. Sensitivity studies show that at Phimai, pyrogenic emissions contribute up to 50 % and 35 % to HCHO and NO2 concentrations, respectively.

Air quality and urban climate improvements in the world’s most populated region during the COVID-19 pandemic

“…Studies based on satellite and ground observations showed that NO 2 levels in Tokyo decreased during the state of emergency (Ito et al 2021, Damiani et al 2022 but the changes that occurred on a daily scale were not examined. Figures 2(a) and (b) shows the time series of daily observations of surface NO 2 (red line) and partial column NO 2 (green line) and the respective meteorology-driven BAU scenarios during the first half of 2020, when mobility was strongly reduced (see supporting information for details of the datasets and ML approach).…”

“…While the COVID-19 pandemic was a worldwide tragedy, it also created a global natural experiment enabling an evaluation of the impact of reduced anthropogenic emissions in urbanized areas, and thus the possibility of a 'green' future (e.g. Shakil et al 2020, Zheng et al 2020, Gkatzelis et al 2021, Laughner et al 2021, Cooper et al 2022, Damiani et al 2022. The mobility restrictions imposed by most governments reduced urban traffic (Yabe et al 2020) and improved AQ worldwide (Venter et al 2020).…”

“…The mobility restrictions imposed by most governments reduced urban traffic (Yabe et al 2020) and improved AQ worldwide (Venter et al 2020). However, in many studies of the COVID-19-AQ connection, the focus was on reactive pollutants, such as nitrogen dioxide (NO 2 ), as their short lifetimes and predominantly anthropogenic origin make them good proxies of anthropogenic emissions (Bauwens et al 2020, Petetin et al 2020, Venter et al 2020, Cooper et al 2022, Damiani et al 2022. Yet, in contrast to the reported reductions in the emissions of those indicators, the levels of other pollutants, such as O 3 , formaldehyde (HCHO), and carbon monoxide (CO), as well as aerosols (e.g.…”

“…To limit the spread of COVID-19, this region was under a state of emergency between 7 April and 25 May 2020, when authorities requested citizen self-restraint. A recent study (Damiani et al 2022) provided a first look at the changes in the levels of trace gases and lightabsorbing aerosols that occurred during this period, mainly focusing on satellite data. A modulation of Tokyo's urban heat island, potentially associated with the reduced mobility during the pandemic, has also been reported (Fujibe 2020).…”

Evaluation of Aeris MIRA, Picarro CRDS G2307, and DNPH-based sampling for long-term formaldehyde monitoring efforts

“…However, the method has known interferences from NO2 and O3 (Karst et al, 1993;Achatz et al, 1999;Tang et al, 2004), is not suitable for sampling in conditions with low relative humidities (Wisthaler et al, 2008;Uchiyama et al, 2009), and has had mixed results in comparison to research-grade observations (Hak et al, 2005;Dunne et al, 2018), making the accuracy of these inferred diel cycles difficult to determine. While other studies have demonstrated the feasibility for continuous measurements via various 55 spectroscopy-based methods (Yokelson et al, 1999;Cardenas et al, 2000;Dasgupta et al, 2005;Hak et al, 2005;Spinei et al, 2018;St Clair et al, 2019;Dugheri et al, 2021), the number of long-term (longer than 1 month), groundbased, continuous HCHO measurements is limited to a handful of studies, all of which employ either the multi-axial differential optical absorption spectroscopy measurement technique (Tian et al, 2018;Kumar et al, 2020;Hoque et al, 2022) or a proton-transfer-reaction mass spectrometer, for which HCHO measurements are sensitive to humidity 60 fluctuations (Warneke et al, 2013;Hansen et al, 2014).…”