SPATIAL DISTRIBUTION OF FOSSIL FUEL CO₂ IN MEGACITY DELHI DETERMINED USING RADIOCARBON MEASUREMENTS IN PEEPAL (FICUS RELIGIOSA) TREE LEAVES

Abstract

The quantification of fossil-fuel derived carbon dioxide (CO_2ff) emissions is critical for regional carbon budgets. Radiocarbon (¹⁴C) is an effective tool to estimate the contribution of CO_2ff to the total atmospheric CO₂. In the present study, we have determined the spatial distribution of fossil fuel derived CO₂ across Delhi using ¹⁴C measurements in Peepal tree leaves from April 2016 to March 2017 at city scale. Our analysis results show that the Δ¹⁴C values vary between –67.78‰ to 5.61‰ and corresponding CO_2ff values are varying from 1.63 ppm to 33.34 ppm. CO_2ff values from campus sites vary between 6.99 ppm to 16.38 ppm with an average value of 10.22 ± 3.20 ppm, while CO_2ff values vary from 2.41 ppm to 33.34 ppm with an average value of 13.32 ± 9.40 ppm for sites located in the parks. Further, we observed the higher contributions of fossil fuels in the CO₂ from northwest Delhi, central Delhi, and some parts of east and southwest Delhi. In the absence of real-time CO₂ monitoring, the results of this study provide a potential method for analyzing the contribution of CO_2ff values over the urban landscape to total CO₂ over the study region.

INTRODUCTION

The rising levels of carbon dioxide (CO₂) in the atmosphere due to an increase in the anthropogenic fossil fuel burning activities are leading to climate change (IPCC 2014; Le Quéré et al. 2018). CO₂ mole fractions in the atmosphere have increased from 280 parts per million (ppm) before the industrial revolution to 415.7 ppm in 2021, which is approximately 49% higher than preindustrial CO₂ concentrations (WMO 2022). Further, cities and urban areas are responsible for 70% of this increase (Duren and Miller 2012; Seto et al. 2014). The primary reason for this increase in CO₂ emissions is the burning of fossil fuels (Boden et al. 2010). CO₂ emitted by combustion of fossil fuels is an additional flux in the atmosphere that perturbs the natural flux of CO₂ and leads to increase the CO₂ levels in the atmosphere (Ciais et al. 2013; Turnbull et al. 2016). As a result, understanding the contribution of fossil fuel CO₂ (CO_2ff) emissions from cities and urban areas is critical to develop an effective mitigation policy (Wang et al. 2021). Typically, fossil fuel CO₂ (CO_2ff) emissions are calculated using fuel consumption data, but this method has large estimation errors at fine spatial resolutions (Marland et al. 2003; Andres et al. 2012). To overcome the shortcomings of this method, as an alternative, radiocarbon (¹⁴C) is used to trace the CO_2ff because it is fully depleted in fossil fuels. Therefore, CO_2ff can easily be identified from other sources based on its radiocarbon content (Levin et al. 2003).

¹⁴C content is generally measured in air samples collected in flask (Turnbull et al. 2006) and air bags (Niu et al. 2016a) or over sodium hydroxide solution (Levin et al. 2003; Turnbull et al. 2017). Annual crop plants, grasses and tree leaves also provide a radiocarbon signal of their growing period because they absorb atmospheric CO₂ by photosynthesis processes (Hsueh et al. 2007; Riley et al. 2008; Bozhinova et al. 2016; Niu et al. 2016b; Varga et al. 2020a). However, because crop plants are not found in cities, tree leaves and grasses are the best plant samples to study the spatial variation of CO_2ff across cities and urban areas (Riley et al. 2008; Niu et al. 2016b; Varga et al. 2019, 2020a). Several radiocarbon-based studies have been carried out in various cities and urban areas around the world to quantify CO_2ff contribution (Lichtfouse et al. 2005; Riley et al. 2008; Wang and Pataki 2010; Park et al. 2013; Niu et al. 2016b; Santos et al. 2019; Varga et al. 2020a; Zhou et al. 2020).

India is the third largest CO₂ emitter (Friedlingstein et. al. 2020) and home to the second largest urban population in the world (UN 2014). In 2011, 32% of the population of India is living in the urban areas, and it is further expected to grow up to 50% by 2050 (UN 2014; Ahmed et al. 2015). Furthermore, India’s current urban population is 10.5 percent of the global urban population, with a projected increase to 12.8 percent by 2050 (UN 2014; Ahmed et al. 2015). Therefore, study of CO₂ emissions from Indian cities and urban areas is not only useful to make mitigation policies for India but also for its global implications.

Several studies based on atmospheric CO₂ observations have been documented over the Indian region, including Indian cities, urban and semi-urban areas (Tiwari et al. 2013, 2014; Lal et al. 2015; Lin et al. 2015; Chandra et. al. 2016; Sharma et al. 2014; Sreenivas et. al. 2016; Jain et al. 2021; Metya et. al. 2021). A recent study of fossil fuel CO₂ estimation based on radiocarbon measurements in crop plants across India has also been reported (Sharma et al. 2023). However, to the best of our knowledge, no ¹⁴C-based CO_2ff measurements have been reported from any Indian city. Therefore, in this study, we used ¹⁴C measurements from Peepal tree leaves to determine spatial variations of CO_2ff in the megacity of Delhi.

MATERIAL AND METHODS

Study Area

Delhi is India’s capital city and is governed as a national capital territory (NCT). Delhi is also one of the most polluted cities in the world (WHO 2016; Mahato et al. 2020) and the world’s second most populous megacity (UN 2018; Mahato et al. 2020). The megacity Delhi (28°22′N to 28°54′N latitude and 76°50′E to 77°20′E longitude) covers an area of 1483 km² geographically. Haryana and Uttar Pradesh states are neighboring states of megacity Delhi surrounding it from three sides (north, east, south) and one side (west), respectively. The topography of megacity Delhi can be divided into three major zones: the Yamuna floodplains, the Aravalli Ridge, and the great Gangetic plains (isfr vol. 2, 2019). However, the main portion of the megacity is covered by the Gangetic plain, having an elevation in the range of 180–316 m above mean sea level (isfr vol. 2, 2019). It is also reported that the population of Delhi is 16.8 million with a density of 11,320 per square km and 97.5% urban and 2.5% rural population as per the 2011 census (Census 2011; http://census2011.co.in). Delhi’s climate is semi-arid with an annual average temperature of 31.5°C (Masood et. al. 2023) and rainfall ranging from 400 mm to 600 mm (isfr vol. 2, 2019), and the prevailing wind direction is northwest. The total number of registered vehicles in Delhi was 12.25 million by 2021 (Delhi Economic Survey 2021–2022), and this number is expected to increase up to 25.6 million by 2030 (Kumar et al. 2017). The national capital region (NCR) includes the megacity of Delhi as well as its neighboring cities of Gurgaon, Faridabad, Noida, Ghaziabad, Sonipat, and Bahadurgarh (Mahato et al. 2020). As shown in Figure 1, Delhi city is also home to several industrial units, two coal-fired thermal power plants, and three gas-fired power plants.

Figure 1 Study area and sampling locations.

Sampling Sites and Sample Collection

For the present study, we collected and analyzed a total of 27 Peepal tree (Ficus religiosa) leave samples from 23 locations across megacity Delhi and four locations from adjacent cities i.e., Ghaziabad, Noida, Faridabad, and Gurugram (one sample from each city). Fifteen samples were collected in the year 2017, 10 samples were collected in 2018, and 2 samples were collected in 2020. The Peepal tree was chosen for this study because it is the fourth most abundant tree species in Delhi’s National Capital Territory (isfr vol. 2, 2019) and is found in the majority of the megacity and surrounding cities. It is a deciduous tree that sheds its leaves only once a year in March and April and new leaves start growing after 1–2 weeks and fully grown within a ∼10-day period. Newly grown leaves are pink in color when they first emerge and convert into a dark green color after maturity. We collected mature leaves in the month of March. They represent the CO_2ff signal for their growing period from April to March. The height of a Peepal tree can reach up to 30 m. We sampled leaves from 2 m above the ground. At this sampling height, leaves will be less influenced by soil respiration. From one sampling location, two–three leaves per tree were collected. Six of the 27 sampling sites are educational/research institute campuses, and 10 are parks in various areas of Delhi. Markets, metro station parking areas, roadside, suburban, and residential areas are among the remaining sampling locations. All the details of sampling sites including the collection time periods are given in Table 1, and sampling sites are shown in Figure 1.

Table 1 List of locations of samples with sampling year, latitude, longitude, measured Δ¹⁴C values, associated uncertainty, adjusted Δ¹⁴C values to 2017, and calculated CO_2ff values.

Sample Pretreatment, Graphitization, and ¹⁴C Measurements

Sample pretreatment, graphitization, and ¹⁴C measurements were performed at the accelerator mass spectrometry (AMS) facility of Inter University Accelerator Centre (IUAC), New Delhi (Sharma et al. 2019). Peepal tree leaves from one sampling location were dried and ground together. The mixture of tree leaves was pretreated using an acid-base-acid (ABA) protocol. In the first step, samples were treated with 0.5M HCl and then treated with 0.1M NaOH. In the final step, samples were again pretreated with 0.5 M HCl. In all the steps, samples were kept at 60°C temperature for 1-hr duration and rinsed with deionized water after each step. The pretreated samples were dried in a freeze dryer for 8–10 hr. 2.5–3 mg of each dried sample was packed into tin boats and combusted in an elemental analyzer at 920°C. The carbon dioxide produced was graphitized using automated graphitization equipment (AGE) (Sharma et al. 2019). ¹⁴C in the graphite produced after graphitization was measured using a 500 kV Pelletron based accelerator mass spectrometer XCAMS (the ¹⁴C accelerator mass spectrometer eXtended for ¹⁰Be and ²⁶Al) with a precision around 2‰. The ¹⁴C/¹²C ratio measured by XCAMS was normalized to the Oxalic Acid II standard sample, and AMS online δ¹³C values were used for the isotopic fractionation correction. An external uncertainty of 2.51‰ was determined in radiocarbon measurements using 18 IAEA C3 secondary standard samples measured during the same period.

Calculation of Δ¹⁴C and CO_2ff

Radiocarbon content is expressed in terms of Δ¹⁴C that is defined as follows:

(1) $${\Delta ^{14}}C = \left[ {{{{{({^{14}C \over {{^{12}}C}})}_{SN}}} \over {{{({{{^{14}}C} \over {^{12}C}})}_{abs}}}} - 1} \right] \times 1000 $$

where (¹⁴C/¹²C)_SN is the measured ¹⁴C/¹²C ratio in the samples normalized with δ¹³C value of –25‰ and (¹⁴C/¹²C)_abs is the absolute ratio of ¹⁴C standard sample corrected for fractionation and ¹⁴C decay (Stuiver and Polach 1977).

The AMS system provides the ¹⁴C/¹²C ratio of the sample, and this ratio is converted into Δ¹⁴C as per Equation (1). Using Δ¹⁴C values, CO_2ff is calculated using following formulation described in Turnbull et al. (2009):

(2) $${\rm{C}}{{\rm{O}}_{2{\rm{ff}}}} = \;{{{\rm{C}}{{\rm{O}}_{2{\rm{bg}}}}\;\left( {{\Delta ^{14}}{{\rm{C}}_{{\rm{mes}}}} - \;{\Delta ^{14}}{{\rm{C}}_{{\rm{bg}}}}} \right)} \over {{\Delta ^{14}}{{\rm{C}}_{{\rm{ff}}}} - \;{\Delta ^{14}}{{\rm{C}}_{{\rm{mes}}}}}} - \;{{{\rm{C}}{{\rm{O}}_{2{\rm{oth}}}}\;\left( {{\Delta ^{14}}{{\rm{C}}_{{\rm{oth}}}} - \;{\Delta ^{14}}{{\rm{C}}_{{\rm{mes}}}}} \right)} \over {{\Delta ^{14}}{{\rm{C}}_{{\rm{ff}}}} - \;{\Delta ^{14}}{{\rm{C}}_{{\rm{mes}}}}}}$$

where Δ¹⁴C_mes = Δ¹⁴C measured in the Peepal tree leaves in this study

Δ¹⁴C_bg = Δ¹⁴C measured at clean air background site

Δ¹⁴C_ff = –1000‰ (Δ¹⁴C value of fossil fuels. Since ¹⁴C is absent in the fossil

fuels, therefore, putting ¹⁴C values as zero in Equation (1) will give

Δ¹⁴C_ff = –1000‰)

CO_2bg = CO₂ from a clean air background site

CO_2oth and Δ¹⁴C_oth = CO₂ and Δ¹⁴C from other sources such as heterotopic

respiration, nuclear reactors, ocean exchange.

The second term in Equation (2) is considered as a correction or bias from other sources in CO_2ff value. For continental sites, corrections for CO₂ from ocean can be ignored. There are two nuclear reactors at the distance of 150 km and 580 km from Delhi and both are pressurized heavy water reactors (PHWR). Pressurized water reactors emit ¹⁴C dominantly in the form of ¹⁴CH₄ (Varga et al. 2020b, 2021). Both of these reactors are also not in the upwind direction of Delhi and this correction can also be ignored. Another source of ¹⁴C is respiration, and it can be divided into autotrophic and heterotrophic respiration. CO₂ emitted during autotrophic respiration is generally absorbed from recent atmosphere (< 1 yr old; Wenger et al. 2019). However, CO₂ emitted by heterotopic respiration may have carbon from older materials such as decaying biomass from the bomb ¹⁴C period. This CO₂ may have large amount of ¹⁴C in comparison of current atmosphere and may produce a bias in the CO_2ff values. However, as per previous studies, ignoring this correction will produce 0.2–0.5 ppm of bias in our CO_2ff values as estimated for mid-latitude Northern Hemisphere (Turnbull et al. 2016).

RESULTS AND DISCUSSION

Spatial Distribution of Δ¹⁴C across Megacity Delhi

We have presented the distribution of Δ¹⁴C values for all the samples collected across Delhi in Figure 2(a) and values are given in Table 1. In order to prepare a spatial distribution map of Δ¹⁴C, we have scaled down all Δ¹⁴C values to the year 2017 because most of the samples were collected in this year. For the scaling factor, we have used decreasing rate of background Δ¹⁴C data for NH zone 3 as suggested in Hua et al. (2022). Background Δ¹⁴C data for NH zone 3 is decreasing at the rate of 2.5‰ and 3.4‰ from April 2017 to March 2018 and from April 2018 to March 2019, respectively. We have assumed the same rate of decrease of 3.4‰ from April 2019 to March 2020, since this background data is available up to 2019 only (Hua et al. 2022). Samples collected in 2018 are scale down by 2.5‰ while two samples collected in the first week of March 2020 are scale down by 9.3‰ for the year 2017.

Figure 2 Spatial distribution of Δ¹⁴C and CO_2ff across megacity Delhi. Other legends of this figure are same as Figure 1.

Δ¹⁴C values are varying from –67.78‰ to 5.61‰ in the megacity Delhi where highest value belongs to a site from Anand Vihar while lowest value belongs to a site from a public park from Geeta colony in East Delhi district. East Delhi district is densely populated area having the third largest population density (22,639 persons/km²) of eleven districts of Delhi city as per 2011 census. Δ¹⁴C values for six campus sites are varying between –7.59‰ to 29.90‰. Δ¹⁴C values are varying from 3.66‰ to –67.78‰ for the sampling sites located in the parks. As shown in Figure 2, we have observed depleted Δ¹⁴C values from the sampling locations from Central Delhi (–47.17‰), the parking area of Tees Hazari Metro station (–51.93‰), Narela (34.14‰) and Sarojani nagar market (–27.01‰). Observed Δ¹⁴C values in the four nearest cities in the NCR region (Ghaziabad, Gurugram, Noida, and Faridabad) were found to be –69.62‰, 11.64‰, –18.14‰, and –46.84‰, and the Δ¹⁴C values from nearest cities are not shown in Figure 2. They are given in Table 1.

Selection of Background Site

We do not have Δ¹⁴C values from a clean air background site in India. Therefore, we have utilized background values for Northern Hemisphere (NH) zone 3 reported in Hua et al. (2022). The present study region, Delhi, lies in the NH zone 3 as per the zones defined in Hua et al. (2022). We have taken average of ∆¹⁴C values from April 2016 to March 2017 from this record for our study, and this average value is 9.7‰. For the CO_2bg value, we used the average CO₂ value (401.12 ppm) from the observational station Nainital, India, from April 2016 to March 2017 (Nomura et al. 2021). Nainital (29.36ºN, 79.46ºE; 1940 m asl) is located at the bottom side of the Himalaya mountains and considered a background site for northern Indian air (Nomura et al. 2021).

Spatial Distribution of CO_2ff across Megacity Delhi

Using the Equation (2), the CO_2ff values calculated for all collected samples across Delhi are given in Table 1, and spatial distribution map of CO_2ff is presented in Figure 2. A maximum uncertainty of 1.18 ppm in CO_2ff values of all samples can be derived from the corresponding external uncertainty of 2.51‰ in ¹⁴C measurements.

The CO_2ff values vary from 1.63 ppm to 33.34 ppm across megacity Delhi, and the highest value belongs to a site from a public park from Geeta colony in East Delhi district. CO_2ff values for six campus sites vary between 6.99 ppm to 16.38 ppm with an average value of 10.22 ± 3.20 ppm (average value ± standard deviation). On the other hand, for the sampling sites located in the parks, the CO_2ff values vary from 2.41 ppm to 33.34 ppm, with an average value of 13.32 ± 9.40 ppm. We have found campus sites to be more consistent than park sites, as seen from their standard deviation. This is because some parks sites are located in the densely populated areas (like Bhagat Singh park in East Delhi) and some parks are located with busy roads (e.g., sampling site in Connaught Place). CO_2ff values for the four nearest cities in the NCR region (Ghaziabad, Gurugram, Noida, and Faridabad) are found to be 35.37 ppm, 0.22 ppm, 12.43 ppm, and 24.91 ppm, respectively. Figure 2 shows high CO_2ff values in northwest Delhi, central Delhi, and parts of eastern Delhi and southwest Delhi. We also note that most of the industrial areas and four out of five thermal power plants are also situated in these parts of Delhi, as shown in Figures 1 and 2. Both thermal power plants and industrial areas are considered to be potential emission sources for fossil fuel CO₂.

The maximum value of CO_2ff (33.34 ppm) observed in our study is higher than the maximum value observed in Rio de Janeiro state in Brazil (Santos et al. 2019) and Mexico City (Vay et al. 2009) but lower than the maximum value observed in Xi’an city (Zhou et al. 2014) as listed in Table 2. The CO_2ff values in this study reflect the daytime fossil fuel CO₂ signal because photosynthesis occurs in the daytime only. CO_2ff values may be higher during nighttime because of stable atmospheric conditions (Wang and Pataki 2010).

Table 2 Comparisons from similar studies.

SUMMARY AND CONCLUSIONS

Identifying the contribution of CO₂ emitted by fossil fuels would enable us to understand regional CO₂ budgets, particularly in urban areas, for any country. For the first time, we used radiocarbon measurements at the city/urban scale to address the spatial distribution and quantify the contributions of CO_2ff over different parts of the megacity Delhi region.

The main findings emerged from this study are as follows:

• We found that the spatial distribution of fossil fuel emissions is heterogeneous across megacity Delhi.

• Δ¹⁴C values are varying between –67.78‰ to 5.61‰.

• CO_2ff values are varying between 1.63 ppm to 33.34 ppm.

• Sampling sites located in the parks have larger CO_2ff values (13.32 ± 9.40 ppm) than the sites located in the campuses (10.22 ± 3.20 ppm).

The present study emphasizes that Peepal tree leaves can be used to monitor fossil fuel CO₂ values in the absence of real-time monitoring of CO₂ values and can also aid in the establishment of future CO₂ monitoring stations in the Delhi region. Furthermore, this study provides the database for CO_2ff in megacity Delhi that can be utilized for the mitigation policies.