Introduction

Ground level atmospheric ozone (O3) is a criteria air pollutant and a major component of photochemical smog. Its formation depends on the chemistry of the precursors, viz., oxides of nitrogen (NOx = NO2 + NO), volatile organic compounds (VOC), and related species like carbon monoxide (CO), and prevailing meteorological conditions like solar radiation, air temperature, and wind (e.g., Allu et al., 2020; Geddes et al., 2009; Haagen-Smit, 1952; Khalil et al., 2018; Leighton, 1961; Paoletti et al., 2014; Singh et al., 2018; Wałaszek et al., 2018; Zhang et al., 2020). The VOC-NOx-O3 chemistry at the ground level atmosphere is well understood (e.g., Atkinson, 2000; Crutzen, 1974; Seinfeld & Pandis, 2016). NOx and VOC are primary species that originate from natural and anthropogenic sources such as vehicular traffic and industrial fossil fuel burning, and through episodic events like biomass burning and volcanoes (e.g., Barletta et al., 2002; Khillare et al., 2005, 2008a, 2008b; Hoque et al., 2008; Li et al., 2017; Ling et al., 2014; Sillman, 1999; Srivastava et al., 2006; Steinbrecher et al., 2009). Ozone is formed through the photolysis of NO2 and has a comparatively short lifetime in the air. However, its precursors can remain in the atmosphere for many days continuously forming ozone and resulting in long-range (often transboundary) transport (Wild et al., 2004; Young et al., 2013). Photochemical ozone production also occurs in rural and remote locations and in remote unpolluted areas (Crutzen, 1974).

Surface O3 shows explicit diel and seasonal variations, which are governed by the photochemistry of its production and removal (Debaje et al., 2003; Lal et al., 2000; Zhao et al., 2021). Highly reactive hydroxyl (•OH) and nitrate (NO3•) radicals are the important oxidative species in the troposphere during day and night, respectively. They are formed through reactions of O3 (e.g., Aschmann et al., 2002; Atkinson et al., 1995). The •OH radical is the key species which initiates reactions of hydrocarbons (HC) and CO during the day, and in the process highly oxidizing peroxy radicals like HOO•, alkyl peroxy radical (ROO•), and acyl peroxy radical (RC(O)OO•) are formed. These peroxy radicals compete with O3 to oxidize NO to NO2 leading to a situation where more O3 is formed than is consumed. This process leads to the built up of O3 during the day.

Two discrete regimes govern the ground level atmospheric ozone: (i) NOx-sensitive regime, when the production of O3 is sensitive to the concentration of NOx, and (ii) VOC-sensitive regime, when the increase in the concentration of O3 is a function of the concentration of VOC (Sillman, 1995; Finlayson-Pitts, 1999; Seinfeld & Pandis, 2016). If controls are applied to the wrong precursor, the O3 concentrations can rise as has been seen in many places around the world since the COVID-19 pandemic led to substantial reductions in NO emissions in VOC-limited regions (e.g., Sicard et al., 2020; Sulaymon et al., 2021; Torkmahalleh et al., 2021).

Ground level atmospheric O3 also affects carbon dynamics, ecological interconnections, and agricultural efficiency across the ecosphere (Schneider et al., 2017). High O3 levels can lead to the closure of stomata, thereby reducing the uptake of gases affecting photosynthesis (Karnosky et al., 2003). Later, Ghude et al. (2014) reported reductions of crop yield in India due to surface ozone and, therefore, an agricultural economy like India’s cannot ignore O3 pollution.

Surface ozone is also an important greenhouse gas contributing to global warming and climate change (IPCC, 2013; Kulkarni et al., 2011; Zhao et al., 2020). The concentration of O3 is changing in the global scale leading to an increase in the background concentrations, which influence the levels of local concentrations of O3 and NO2 (Clapp & Jenkin, 2001).There are reports of reduction of particulate pollution but O3 remained constant or increasing, indicating the complexities in the O3 pollution and, therefore, its control (e.g., Squizzato et al., 2018).

Ozone in the lower atmosphere is termed as “bad” O3 for its adverse effects on human health and the environment. It was termed as lung irritant soon after its discovery (Bates, 1989). Health effects of increased concentration of O3 include reduction of lung functions, increased respiratory problems, and inflammation. Long-term exposure of O3 ultimately leads to chronic damage of the lungs in vertebrates (Lippmann, 1991). Ozone exposure can decrease the variability in heart rate of human beings thereby deteriorating the cardiac autonomic nervous system (Jia et al., 2011). The cardiovascular effects of ambient O3 are found in animals, when exposed for a long duration, thereby altering their vascular tone (Chuang et al., 2009; Paffett et al., 2015; Robertson et al., 2013).

There has been limited literature addressing O3 from India. More so, the reported studies are generally from major metropolitan areas, at sites that are often heavily influenced by local sources like traffic (e.g., Badarinath et al., 2009a, 2009b; Beig et al., 2013; Ganguly & Tzanis, 2013; Lal et al., 2012; Singla et al., 2011). There are a few studies on the ground level atmospheric O3 from the Brahmaputra Valley region (e.g., Bharali et al., 2015; Bhuyan et al., 2014; Dumka et al., 2020; Pathak et al., 2016). Tyagi et al. (2020) examined the O3 concentrations of three stations in northeastern India (including Tezpur) as well as surface temperatures and other meteorological parameters. They concluded that there is significant transport of O3 to the region; however, they did not address the air mass trajectory pathways/regions that contributed to higher O3.

Therefore, this study was taken up to determine the variability of ground level O3 on a daily and seasonal basis in a relatively rural area of the mid-Brahmaputra Valley. Ozone has been assessed in terms of the NOx-O3 photostationary state to understand the processes that are driving the O3 concentration. Concentration-weighted trajectory (CWT) analysis was done to identify likely source regions from where air masses carrying precursors originated and were subsequently transported to the region contributing to the formation of O3.

Methodology

The site

Ozone, NO and NO2, and meteorological variables were measured on the Tezpur University campus (26° 37′ N and 92° 50′ E) under the MAPAN (monitoring of atmospheric pollution and networking) program. The location of the study area along with illustrative air mass back trajectories during winter is shown in Supplemental Fig. S1. The diel patterns’ atmospheric temperature through the year over the study area is shown in Fig. S2. The site is characterized as a rural residential/institutional area. The station is surrounded by villages and agricultural fields. Tezpur city had a population of about 2.0 million (Census of India, 2011). The moderately busy highways are at about 20 km and the eastern Himalayan ranges begin at 30 km on the north from the monitoring station. The region is still developing. Traditional biomass burning in homes, agriculture, and forest are seen in the surrounding areas of the study site previously reported by Bhuyan et al. (2018).

Methodology

Continuous hourly measurements of O3, NO, and NO2 and meteorological parameters for two consecutive years (2013–14 and 2014–15) were used for the study. The O3 measurements were made with a Serinus 10 ozone analyzer (Ecotech). This analyzer uses non-dispersive ultraviolet (UV) absorption technology to measure O3 with a sensitivity of 0.5 ppb and in the range of 0–20 ppm (Ecotech user manual, 2010; Dumka et al., 2020). The measurements of NO and NO2 were made with a Serinus 40 Oxides of Nitrogen analyzer (Ecotech) that uses gas phase chemiluminescence detection. The concentration of NOx is the sum of the concentrations of NO and NO2.This Serinus 40 analyzer measures with a sensitivity of 0.4 ppb with auto ranging of 0–20 ppm (Ecotech, 2011; Gilge, 2010; Yadav et al., 2014). Another important parameter estimated in this study was total oxidant (OX = O3 + NO2) that assists in understanding the O3 behavior. Hourly average measurements of meteorological variables were made at the same station. The four seasons considered in the study were as per the India Meteorological Department (Laskar et al., 2016.): pre-monsoon (March–May), monsoon (June–September), post-monsoon (October–December), and winter (January–February).

The R package, Openair (Carslaw, 2018; Carslaw & Ropkins, 2012) was used for analyses and illustrations and in computing the polar plots. The air mass back trajectories were computed using TrajStat software that applies NOAA/ARL HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model to calculate back trajectories. The NCEP/NCAR Reanalysis data (ftp://arlftp.arlhq.noaa.gov/pub/archives/reanalysis) were used to compute 72 h (3 days) back trajectories arriving at the site every hour (Draxler & Hess, 1998; Rolph et al., 2017; Stein et al., 2015). The time difference between UTC and local time was carefully adjusted so that the time of the measurement of concentration and the time of reaching the trajectory matched.

Concentration-weighted trajectory (CWT) analysis was applied where trajectories were weighted with associated concentrations. Each grid was assigned a residence-time-weighted concentration from the measured data associated with the trajectories that crossed that grid cell, as follows:

$${C}_{ij}=\frac{1}{{\sum }_{l=1}^{M }\tau ijl}\sum_{l=1}^{M}{c}_{l}{\tau }_{ijl}$$
(1)

where,

Cij — average weighted concentration in the ijth cell.

l — index of the trajectory.

M — total number of trajectories.

Cl — concentration observed on arrival of trajectory l.

τijl — time spent in the ijth cell by trajectory l.

In the cases of higher Cij, it could be inferred that air masses that passed over the ijth cell were transporting that species leading to high concentrations at the receptor site. To reduce the effect of a small number of polluted trajectories, a weighting function was multiplied with the CWT (Wang et al., 2009).

Results and discussion

Concentrations

The concentrations of hourly O3, maximum O3 of the day (O3 max), NO, NO2, NOx, and OX for the years 2013–14 and 2014–15 are shown in Fig. 1, and the descriptive statistics are given in Table S1. The 95th percentile O3 concentrations were 43 ppb during 2013–2014 and 41 ppb during 2014–2015. The minimum concentration was 1 ppb during both the years. The 95th percentile NOx concentrations were 15 ppb during 2013–2014 and 14 ppb during 2014–2015. Low NOx and comparatively high O3 are typical of remote locations where the production of O3 is mainly governed by the NOx concentration (Chameides et al., 1992). However, in a high NOx regime like an urban area, the production of O3 is controlled by NOx and VOC levels (Chameides et al., 1992; Sillman et al., 1990).

Fig. 1
figure 1

Box plot of measured concentrations for the years (a) 2013–2014 and (b) 2014–2015. The central solid lines inside the box represent median values of the respective species; the whiskers are maximum (95th percentile) and minimum values excluding the outliers

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A summary of O3 concentrations from the present study and related studies is provided in Table 1. Bhuyan et al. (2014) reported a maximum O3 concentration of 43 ppb from urban Dibrugarh in the upper Brahmaputra Valley that was comparable to the present study values. Tezpur experienced higher maximum concentrations of O3 compared to several regions of the Indian mainland, e.g., uplands of Udaipur (28 ppb; Yadav et al., 2014), city area of Ahmedabad (30 ppb; Lal et al., 2000), Coastal Tranquebar (37 ppb; Debaje et al., 2003), and semi-urban areas of Jodhpur (22 ppb; Pancholi et al., 2018). There are several reports of higher maximum concentrations of O3 compared to the present study form the mainland India (e.g., urban areas of Pune; 5 ppb; Beig et al., 2007), urban commercial areas of Agra (72 ppb; Satsangi et al., 2004), semi-arid rural continental location of Anantapur (72 ppb; Reddy et al., 2012), and urban high-altitude area of Ooty (62 ppb; Udayasoorian et al., 2013). There were reports where the O3 values were comparable to those in Tezpur. These locations include a rural mountain valley of Kannur (44 ppb; Nishanth et al., 2012), a busy urban industrial area of Lahore (41 ppb; Tabinda et al., 2016). Sarangi et al. (2014) reported average monthly O3 concentrations in a remote high-altitude location of central Himalayas (Nainital, India) where concentrations were in the upper range of values observed in the mid-Brahmaputra Valley. The proximity of Nainital to one of the most polluted regions of India, the Indo-Gangetic Plain (IGP) could have resulted in higher O3 values in the hills. In another study from the Nepalese Himalayas, a maximum O3 concentration of 60 ppb was reported that could have been an outcome of the valley effect. In neighboring Bangladesh, Sikder et al. (2013) reported a high maximum O3 concentration of 97 ppb in Dhaka. Therefore, it appears that the maximum ozone concentrations varied in different locations likely related to the land uses. Although the station at Tezpur is a rural location, the maximum O3 values were on higher compared to other similar locations of Indian subcontinent.

Table.1 Comparison of ground level atmospheric ozone concentrations over mid Brahmaputra Valley region with concentrations reported elsewhere
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Diel and seasonal variations of O3

The hour of the week of O3 concentrations in the year 2014 (January to December)) are shown in Fig. 2A. The hour of the week plot generally showed O3 trends with single peak (maximum ozone) during the afternoons. The diel pattern of O3 in 2014 is shown in Fig. 2B that shows a clear afternoon peak. This pattern is different from the trends of urban areas where the maximum ozone is experienced at midday (e.g., Dumka et al., 2020; Han et al., 2011; Reddy et al., 2012; Yadav et al., 2014). The diel O3 concentration variation followed the progression of temperature during the day shown in Fig. S2. Increased O3 concentrations have been reported to follow the increase in atmospheric temperature (AT) (e.g., Coates et al., 2016). Temperature affects the O3 formation by speeding up the rates of chemical reactions, e.g., O3 + NO + hv → NO2 + O is a function of temperature, which is the reaction that leads to the formation of O3 by reaction with O2. AT also increases the rate of emission of biogenic VOCs (Sillman & Samson, 1995) as well as the evaporative emission of VOCs (Rubin et al., 2006).

Fig. 2
figure 2

Variations in the concentrations of O3 (mean O3 and 95% confidence interval in mean): (a) variations in the hourly mean concentrations of O3 as the days progressed in a week of the year (Monday to Sunday); (b) variations of hourly mean concentrations of O3 as the day of the year progressed; (C) concentrations of mean O3 in weekdays (Monday to Sunday); and (d) monthly variations of mean O3 concentrations (January to December, 2014)

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The O3 distributions across the days of the week (Fig. 2C) showed a small rise in the concentrations during Monday, Thursday, and Friday with the concentrations decreasing only marginally on Tuesday, Wednesday, and during the weekends. Higher O3 is observed on weekends due to reduction of NOx emissions on weekends in a VOC-limited regime (Cleveland et al., 1974; Sicard et al., 2020; Wolff et al., 2013). The occurrence of higher levels of O3 is termed as the “weekend effect.” The •OH radical initiated reactions of VOC play a key role here and a significant lowering of NOx makes more •OH available to initiate the oxidation of VOCs leading to an increase in the ozone formation (Fujita et al., 2003). Also, the lack of titration of O3 and the ability of the peroxides and peroxy radicals to cycle the NO more rapidly to the NO2 to be photolyzed allows the formation of additional O3. Alternatively, lower weekend O3 concentrations could be the result of NOx reduction in a NOx-limited regime.

The month-to-month O3 pattern in 2014 is shown in Fig. 2D. It clearly shows pre-monsoon (April) O3 concentrations maxima at this site (e.g., Crutzen, 1988; Dumka et al., 2020; Gilge et al., 2010; Yadav et al., 2014). The monthly average AT in the study area has been presented in Fig. S2(b). The maximum average monthly AT across the study region was seen during July–August. However, the ozone maxima were found during April when the temperatures were warm (20 to 30 °C) and enhanced photochemical reactions. Although AT has a role in increasing the O3 formation through increasing the rate constants for important reaction, temperature also enhances the rates of biogenic emission of VOCs (e.g., Coates et al., 2016; Gu et al., 2020; Rubin et al., 2006; Sillman & Samson, 1995). The time series plots of the concentrations of O3, NOx, NO2, and NO of the study period are given in Fig. S3. The pre-monsoon maximum of O3 is clearly seen in these plots. However, maximum NOx concentration was observed in the winter months. The meteorological conditions during the pre-monsoon favored the rise of O3 concentration. The maximum concentration of O3 was seen in the month of April when plants start growing strongly and emit more reactive VOCs. In this region, March–April are the main foliating months in the forests and tea plantations, which would lead to elevated emission of biogenic VOCs (BVOC) and impacting the O3 formation (e.g., Wu et al., 2020). Also, there are controlled burning fires in the forests for management (Badarinath et al., 2009a). These fires emit large quantities of reactive organic compounds that also interact with the NOx chemistry and O3 formation (Singh et al., 1995). Previously, Tyagi et al. (2020) examined O3 with respect to AT of three stations in the northeastern India and did not find a dependency of O3 on temperature. They inferred this discrepancy to the transport of O3 into the region. However, the role of VOCs of both biogenic and anthropogenic origins cannot be overlooked in the present study.

Diel patterns of O3 and O3-NOx photostationary state

The O3–NOx relationship can be explained by the following reactions after Leighton (1961):

$${NO}_{2}hv(<424^\circ nm)\stackrel{{J}_{1}}{\to }NO+{O}^{\cdot }$$
(2)
$${O}^{\cdot }{+O}_{2}+M\stackrel{{k}_{2}}{\to }{O}_{3}+M$$
(3)
$${O}_{3}+NO+hv\stackrel{{k}_{3}}{\to }{NO}_{2}+{O}^{\cdot }$$
(4)

Daytime O3, NO2, and NO equilibrate on a timescale of a few minutes (Clapp & Jenkin, 2001) to reach a “dynamic” equilibrium called the “photostationary state” (PS), wherein d[O3] / dt = 0 (Seinfeld & Pandis, 2016). If J1 is the rate of the photodissociation of NO2 including the light intensity (Eq. 2) and k3 is the rate coefficient of the formation of NO2 (Eq. 4), then the PS can be explained by the ratio J1/k3 = [O3][NO] / [NO2], which will govern the concentrations of O3, NO2, and NO during the day. J1 is a function of solar intensity so it includes a diel variability whereas k3 is a function of temperature. The k3 varies with temperature as given by Seinfeld and Pandis (2016):

$${k}_{3}\left({ppm}^{-1}{ min}^{-1}\right)=3.23\times {10}^{3}\mathrm{exp}[-1430/T]$$
(5)

However, the accumulation of O3 in the lower atmosphere is more complicated, and reactions that convert NO to NO2 with no-or-less destruction of O3 are required for O3 to accumulate. Ozone reacts with olefins to form Criegee intermediates that can decompose to produce •OH and peroxy radicals. The •OH radicals oxidize other VOCs and CO to form additional oxidizing radicals like HOO• and ROO•. These oxidants convert NO to NO2 without the destruction of and O3 (Eq. 4) as outlined in (Eq. 6) to (Eq. 11) (Atkinson, 2000; Greiner, 1967; Stedman et al., 1970):

$$\mathrm{RH}\hspace{0.17em}+\hspace{0.17em}\mathrm{OH}\hspace{0.17em}\to \hspace{0.17em}\mathrm{R}\hspace{0.17em}+\hspace{0.17em}{H}_{2}O$$
(6)
$${R}^{\cdot }+{O}_{2}\to {ROO}^{\cdot }$$
(7)
$${ROO}^{\cdot }+NO\to {RO}^{\cdot }+{NO}_{2}$$
(8)
$${CO+}^{\cdot }OH\to {CO}_{2}+H$$
(9)
$${H}^{\cdot }+{O}_{2}\to {HOO}^{\cdot }$$
(10)
$${HOO}^{\cdot }+NO{\to }^{\cdot }OH+{NO}_{2}$$
(11)

There are external factors that can affect the PS including transport of O3, the nature and concentrations of VOCs, alternate generation of peroxy radicals such as photolysis of short-chin carbonyls, and local sources and transport of NOx (Khalil, 2018). Due to these complexities, a “true” PS is rarely attained in the ground level atmosphere.

Thus, the net O3 (measured O3 concentration) and J1/k3 were plotted against time of day for the different seasons to ascertain how the temporal variation of O3 behaved relative to J1/k3 (Fig. 3). The net O3 and J1/k3 attained a maximum during midday to the early afternoon hours, and then both parameters declined as the day progressed.

During the pre-monsoon and monsoon seasons (Fig. 3a, b), the net O3 and J1/k3 attained their maxima and were about equal during midday to afternoon (1130 h to 1530 h local time). In this period, much of the NO2 has photolyzed to give O3, and the net O3 was a function of NOx. These two seasons are much warmer seasons compared to the post-monsoon and winter periods, and the days are longer. Maximum sunshine and temperature occur during that time period (1130 h to 1530 h). It was also interesting to see that the maxima were attained long after the sunrise, which is the high traffic period of the morning hours.

During post-monsoon and winter seasons (Fig. 3c, d), the net O3 and J1/k3 peaked for a shorter duration at around 14:00 local time. During the post-monsoon net O3 and J1/k3 were nearly equal at ~ 1400 h local time. However, during the winter, net O3 and J1/k3 never became equal. During the peak hour, the levels of net O3 were much higher than the J1/k3 during the winter month.

Fig. 3
figure 3

net O3 (measured concentrations) and J1/k3 plotted against time of the day in different seasons: (a) pre-monsoon, (b) monsoon, and (c) post-monsoon, (d) winter.

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During all the seasons, the ratio (J1/k3) and net O3 fell after the peak. The slopes of net O3 and J1/k3 were not similar. The fall in the case of J1/k3 was much sharper than net O3 and the levels of net O3 remained higher than the ratio during the rest of the day. Also, net O3 was found to be higher than J1/k3 during the period preceding the peak period. During the winter season, the net O3 was always much higher than J1/k3 This discrepancy points at the factors that cause deviations of net O3 from the PS. Those factors include transport of O3 and the role of VOCs. The activity of VOC and involvement of OH are local (Khalil, 2018), and OH generation and reactions of VOC degradation and production of O3 in the process happens in situ. However, the VOCs and NOx could be from both local emission and long-range transport.

The local sources of elevated levels of VOCs were biomass burning and biogenic emissions. The long-range transport of peroxyacyl nitrate (PAN) and other PAN homologues from the IGP can add NOx and radicals in the region during the winter, which are important drivers of O3 production.

Though biomass burning is prevalent in the region (Deka & Hoque, 2015), during the winter months, there is escalation in the biomass burning which is a major source of VOCs in the atmosphere. A unique festive biomass burning, locally known as meji burning during mid-January each year is a major emitter of particulate matter and gases (Deka & Hoque, 2014; Hoque & Deka, 2010) that also have implications on the oxidative behavior of the regional atmosphere and O3 buildup in the winter period.

Biomass burning emits loads of oxygenated hydrocarbons like aldehydes, ketones, and alcohol which are important sources of free radicals linked with the reactivity of NOx and ozone formation. Acetone alone can provide a high production of HOx (•OH and HOO•) radicals thereby enhancing the production of O3 (Singh et al., 1995). The alcohols also further undergo oxidation giving rise more reactive aldehydes and radicals that would favor O3 formation explained by the following reaction (Singh et al., 1995):

$${CH}_{3}OH{+}^{\cdot }OH+{(O}_{2})\to {CH}_{2}O+{HOO}^{\cdot }+{H}_{2}O$$
(12)
$${C}_{2}{H}_{5}{OH}{+}^{\cdot }OH+\left({O}_{2}\right)\to {CH}_{3}CHO+HOO+{H}_{2}O$$
(13)

Another important source of VOC in the winter months is agriculture. The whole of the Brahmaputra Valley region is widely cultivated with crops from the Brassicaceae family that are known to emit volatile organics (Gan et al., 1998; Mead et al., 2008). Rapeseed, cabbage, and radish are principal winter crops of the Brahmaputra Valley. There is a large area (0.276 million ha) under rapeseed cultivation (Das, 2015). Even the fallow lands are used for rapeseed since it is a hardy crop and does not need irrigation and excessive manuring. Similarly, large areas are under cabbage (33.24 kha) and radish (21.17 kha) (Horticulture Statistics Division, 2018). The Brassicaceae family is known to emit large volumes of CH3Br and other organics (Gan et al., 1998; Mead et al., 2008). CH3Br is a reactive gas and provides a source of radicals that covert NO to NO2 and enhance the production of O3 (Orlando et al., 1996), shown in Eqs. 14-16:

$${CH}_{3}Br{+}^{\cdot }OH{\to }^{\cdot }{CH}_{2}Br+{H}_{2}O$$
(14)
$${\cdot \mathrm{CH}}_{2}Br+{O}_{2}+M\to {CH}_{2}{BrOO}^{\cdot }+M$$
(15)
$${CH}_{2}{BrOO}^{\cdot }+NO\to {CH}_{2}BrO+{NO}_{2}$$
(16)

PAN is a source of NOx and organic radicals in the remote atmosphere. The thermochemical stability of PAN depends on the temperature and is quite stable at low temperature. At 7 °C and NO2/NO ratio of 2–20, the lifetime of PAN (τPAN) is ~ 19 to 120 h, and at 27 °C, τPAN is ~ 0.75 h to 4.4 h (Altshuller, 1993). Other PANs have similar lifetimes. Therefore, at low temperatures, PAN can be transported long-range and pump in NOx and organic radicals to the remote regions. Analysis of the air mass back trajectories reaching the site during winter (Fig. S1) suggests that 28% of the trajectories traveled from the IGP region of India. The IGP is one of the most polluted regions of India from where aided by the low temperatures, there was likely transport to the study area of PAN. As the trajectories reached the site where the temperature is 10 °C to 24 °C in the winter, the PAN decomposed to NOx and organic radicals (Eq. 17):

$${CH}_{3}C\left(O\right){OONO}_{2}+M\to {CH}_{3}{C(O)OO}^{\cdot }+{NO}_{2}+M$$
(17)

The ventilation coefficients (VC) calculated for winter month (January) as mixed layer height (MLH) × wind speed (WS), as illustrated in Fig. 4 show that the maximum VC is experienced at ~ 9:00 the morning and that is, then, there was a steep rise in the winter period concentration of net O3.

Fig. 4
figure 4

Ventilation coefficient (VC) during winter period (January 2014). VC was calculated as VC = MH × WS; MH was calculated by HYSPLIT

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Transport of O3

Transport of O3 also has a greater implication in the deviation of PS as seen in the period before and after the peak O3 time of the day, wherein the O3 concentrations were always higher than the ratio (J1/k3). The transport of O3 to the station was examined by comparing (i) the polar plots of O3 and NO2 (for local transport) and (ii) the concentration-weighted trajectories (CWT) of O3 (for regional transport representing the precursors like PAN). The polar plots of NO2 were considered because O3 is ultimately produced (through all photochemical processes) from the photolysis of NO2. If O3 was to be produced only from the photolysis of NO2, the polar plots of O3 and NO2 would look similar. The polar plots of O3 and NO2 are given in Fig. 5, in which the concentrations are plotted against wind speed and wind direction.

Fig. 5
figure 5

Polar plots of O3 (a–d: pre-monsoon, monsoon, post-monsoon, winter), and (b) NO2 (e–h: pre-monsoon, monsoon, post-monsoon, winter): concentrations plotted against wind direction and wind speed during the study period

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Through the seasons, high O3 concentrations were found to accompany high wind speed that suggests transport of O3 to the site (Fig. 5a–d). However, stagnant conditions would also allow locally emitted NO to titrate the O3. Alternatively, higher concentrations of NO2 were observed under lower wind speeds (Fig. 5e–h). Only moderate and low levels of NO2 were associated with high wind speeds indicating that the NOx was locally emitted and dispersed under higher ventilation conditions. It is clear from the plots that higher O3 and higher NO2 were seen to be associated with winds from different directions. It was important to look at the polar plots of the winter season (Fig. 5d, h). As discussed in the previous section, in the winter season, O3 did not show a diel pattern corresponding to J1/k3 (PS), and the O3 concentration was much higher than J1/k3. The polar plot of O3 in winter shows that O3 was higher when the wind speeds were high, a pattern that is different from the polar plot of NO2. The wind directions with respect to high ozone and the direction with respect to high NO2 were found to be different, which may be inferred as transport of O3 to the site. There are previous reports that during the winter and pre-monsoon seasons, the region receives air mass trajectories that originated and/or passed over the IGP (Bhuyan et al., 2016; Deka et al., 2020) and bring high pollutant concentrations to the region (Ommi et al., 2017; Rahman et al., 2020).

The HYSPLIT air mass trajectories reaching the site were weighted with the concentrations of O3, and the CWTs were computed (Fig. 6). It was clear from the CWT plot that when the trajectories originated or passed over the IGP, the Indian Himalayan region including Nepal, Bangladesh, and the Bay of Bengal, the site experienced higher O3 concentrations (shown as colors above yellow). Moderate concentrations of O3 (color codes green to yellow) were observed when the trajectories originated or passed over Myanmar, the Shillong Plateau, and the western regions of China. These results suggest that the O3 concentrations are strongly affected when the trajectories originated or traveled over polluted regions transporting O3 precursors such as PAN to the area.

Fig. 6
figure 6

Concentration-weighted trajectories (CWT) computed from 3-day HYSPLIT back trajectories reaching the site every hour for O3; Tezpur station is shown as the black star

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Conclusions

Ambient O3 concentrations of mid-Brahmaputra Valley showed vivid diel, monthly, and seasonal variations, which is not unusual. Ozone concentrations through days and seasons do vary and should vary. However, the behavior of O3 against the PS varied among seasons and O3 of the days of the winter period deviated from the PS substantially. This deviation can be attributed to local emissions from biomass burning, VOCs from both biogenic and anthropogenic emissions, and long-range transport of O3 precursors in the form of PAN and PAN homologues.