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. Reference Le Quéré, Andrew, Friedlingstein, Sitch, Hauck, Pongratz and Pickers2018). 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 Reference Duren and Miller2012; Seto et al. Reference Seto, Dhakal, Bigio, Blanco, Delgado and Dewar2014). The primary reason for this increase in CO2 emissions is the burning of fossil fuels (Boden et al. Reference Boden, Marland and Andres2010). 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. Reference Ciais, Sabine, Bala, Bopp, Brovkin, Canadell, Stocker, Qin and Plattner2013; Turnbull et al. Reference Turnbull, Graven, Krakauer, Schuur, Druffel and Trumbore2016). As a result, understanding the contribution of fossil fuel CO2 (CO2ff) emissions from cities and urban areas is critical to develop an effective mitigation policy (Wang et al. Reference Wang, Zhou, Niu, Xiong, Wu, Cheng, Hou, Lu and Du2021). Typically, fossil fuel CO2 (CO2ff) emissions are calculated using fuel consumption data, but this method has large estimation errors at fine spatial resolutions (Marland et al. Reference Marland, Boden and Andres2003; Andres et al. Reference Andres, Boden, Bréon, Ciais, Davis, Erickson, Gregg, Jacobson, Marland, Miller, Oda, Olivier, Raupach, Rayner and Treanton2012). To overcome the shortcomings of this method, as an alternative, radiocarbon (14C) is used to trace the CO2ff because it is fully depleted in fossil fuels. Therefore, CO2ff can easily be identified from other sources based on its radiocarbon content (Levin et al. Reference Levin, Kromer, Schmidt and Sartorius2003).
14C content is generally measured in air samples collected in flask (Turnbull et al. Reference Turnbull, Miller, Lehman, Tans, Sparks and Southon2006) and air bags (Niu et al. Reference Niu, Zhou, Wu, Cheng, Lu, Xiong, Du, Fu and Wang2016a) or over sodium hydroxide solution (Levin et al. Reference Levin, Kromer, Schmidt and Sartorius2003; Turnbull et al. Reference Turnbull, Mikaloff Fletcher, Ansell, Brailsford, Moss, Norris and Steinkamp2017). 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. Reference Hsueh, Krakauer, Randerson, Xu, Trumbore and Southon2007; Riley et al. Reference Riley, Hsueh, Randerson, Fischer, Hatch, Pataki, Wang and Goulden2008; Bozhinova et al. Reference Bozhinova, Palstra, Van der Molen, Krol, Meijer and Peters2016; Niu et al. Reference Niu, Zhou, Zhang, Wang, Zhang, Lu, Cheng, Wu, Xiong, Du and Fu2016b; Varga et al. Reference Varga, Jull, Lisztes-Szabó and Molnár2020a). However, because crop plants are not found in cities, tree leaves and grasses are the best plant samples to study the spatial variation of CO2ff across cities and urban areas (Riley et al. Reference Riley, Hsueh, Randerson, Fischer, Hatch, Pataki, Wang and Goulden2008; Niu et al. Reference Niu, Zhou, Zhang, Wang, Zhang, Lu, Cheng, Wu, Xiong, Du and Fu2016b; Varga et al. Reference Varga, Barnucz, Major, Lisztes-Szabó, Jull, László, Pénzes and Molnár2019, Reference Varga, Jull, Lisztes-Szabó and Molnár2020a). Several radiocarbon-based studies have been carried out in various cities and urban areas around the world to quantify CO2ff contribution (Lichtfouse et al. Reference Lichtfouse, Lichtfouse, Kashgarian and Bol2005; Riley et al. Reference Riley, Hsueh, Randerson, Fischer, Hatch, Pataki, Wang and Goulden2008; Wang and Pataki Reference Wang and Pataki2010; Park et al. Reference Park, Hong, Park, Sung, Lee, Kim, Kim, Choi, Kim and Woo2013; Niu et al. Reference Niu, Zhou, Zhang, Wang, Zhang, Lu, Cheng, Wu, Xiong, Du and Fu2016b; Santos et al. Reference Santos, Oliveira, Park, Sena, Chiquetto, Macario and Grainger2019; Varga et al. Reference Varga, Jull, Lisztes-Szabó and Molnár2020a; Zhou et al. Reference Zhou, Niu, Wu, Xiong, Hou, Wang, Feng, Cheng, Du, Lu, An, Burr and Zhu2020).
India is the third largest CO2 emitter (Friedlingstein et. al. Reference Friedlingstein, O’Sullivan, Jones, Andrew and Hauck2020) 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. Reference Ahmad, Baiocchi and Creutzig2015). 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. Reference Ahmad, Baiocchi and Creutzig2015). 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. Reference Tiwari, Revadekar and Ravi2013, Reference Tiwari, Vellore, Ravi, van der Schoot and Cho2014; Lal et al. Reference Lal, Chandra and Venkataramani2015; Lin et al. Reference Lin, Indira, Ramonet, Delmotte, Ciais and Bhatt2015; Chandra et. al. Reference Chandra, Lal, Venkataramani, Patra and Sheel2016; Sharma et al. Reference Sharma, Dadhwal, Kant, Mahesh, Mallikarjun, Gadavi, Sharma and Ali2014; Sreenivas et. al. Reference Sreenivas, Mahesh, Subin, Kanchana, Rao and Dadhwal2016; Jain et al. Reference Jain, Singh, Akhil Raj, Madhavan and Ratnam2021; Metya et. al. Reference Metya, Datye, Chakraborty, Tiwari, Sarma, Bora and Gogoi2021). A recent study of fossil fuel CO2 estimation based on radiocarbon measurements in crop plants across India has also been reported (Sharma et al. Reference Sharma, Kunchala, Ojha, Kumar, Gargari and Chopra2023). However, to the best of our knowledge, no 14C-based CO2ff 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 CO2ff 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. Reference Mahato, Pal and Ghosh2020) and the world’s second most populous megacity (UN 2018; Mahato et al. Reference Mahato, Pal and Ghosh2020). 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. Reference Masood and Ahmad2023) 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. Reference Kumar, Gulia, Harrison and Khare2017). 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. Reference Mahato, Pal and Ghosh2020). 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 CO2ff 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 CO2ff 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. Reference Sharma, Umapathy, Kumar, Ojha, Gargari, Joshi, Chopra and Kanjilal2019). 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. Reference Sharma, Umapathy, Kumar, Ojha, Gargari, Joshi, Chopra and Kanjilal2019). 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 CO2ff
Radiocarbon content is expressed in terms of Δ14C that is defined as follows:
$${\Delta ^{14}}C = \left[ {{{{{({^{14}C \over {{^{12}}C}})}_{SN}}} \over {{{({{{^{14}}C} \over {^{12}C}})}_{abs}}}} - 1} \right] \times 1000 $$
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 Reference Stuiver and Polach1977).
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, CO2ff is calculated using following formulation described in Turnbull et al. (Reference Turnbull, Rayner, Miller, Naegler, Ciais and Cozic2009):
$${\rm{C}}{{\rm{O}}_{2{\rm{ff}}}} = \;{{{\rm{C}}{{\rm{O}}_{2{\rm{bg}}}}\;\left( {{\Delta ^{14}}{{\rm{C}}_{{\rm{mes}}}} - \;{\Delta ^{14}}{{\rm{C}}_{{\rm{bg}}}}} \right)} \over {{\Delta ^{14}}{{\rm{C}}_{{\rm{ff}}}} - \;{\Delta ^{14}}{{\rm{C}}_{{\rm{mes}}}}}} - \;{{{\rm{C}}{{\rm{O}}_{2{\rm{oth}}}}\;\left( {{\Delta ^{14}}{{\rm{C}}_{{\rm{oth}}}} - \;{\Delta ^{14}}{{\rm{C}}_{{\rm{mes}}}}} \right)} \over {{\Delta ^{14}}{{\rm{C}}_{{\rm{ff}}}} - \;{\Delta ^{14}}{{\rm{C}}_{{\rm{mes}}}}}}$$
where Δ14Cmes = Δ14C measured in the Peepal tree leaves in this study
Δ14Cbg = Δ14C measured at clean air background site
Δ14Cff = –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
Δ14Cff = –1000‰)
CO2bg = CO2 from a clean air background site
CO2oth and Δ14Coth = 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 CO2ff 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. Reference Varga, Orsovszki, Major, Veres, Bujtás, Végh, Manga, Jull, Palcsu and Molnár2020b, Reference Varga, Major, Gergely, Lencsés, Bujtás, Jull, Veres and Molnár2021). 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. Reference Wenger, Pugsley, O’Doherty, Rigby, Manning, Lunt and White2019). 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 CO2ff values. However, as per previous studies, ignoring this correction will produce 0.2–0.5 ppm of bias in our CO2ff values as estimated for mid-latitude Northern Hemisphere (Turnbull et al. Reference Turnbull, Graven, Krakauer, Schuur, Druffel and Trumbore2016).
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. (Reference Hua, Turnbull, Santos, Rakowski, Ancapichún, De Pol-Holz, Hammer, Lehman, Levin, Miller, Palmer and Turney2022). 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. Reference Hua, Turnbull, Santos, Rakowski, Ancapichún, De Pol-Holz, Hammer, Lehman, Levin, Miller, Palmer and Turney2022). 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 CO2ff 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. (Reference Hua, Turnbull, Santos, Rakowski, Ancapichún, De Pol-Holz, Hammer, Lehman, Levin, Miller, Palmer and Turney2022). The present study region, Delhi, lies in the NH zone 3 as per the zones defined in Hua et al. (Reference Hua, Turnbull, Santos, Rakowski, Ancapichún, De Pol-Holz, Hammer, Lehman, Levin, Miller, Palmer and Turney2022). 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 CO2bg 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. Reference Nomura, Naja, Ahmed, Mukai, Terao, Machida, Sasakawa and Patra2021). 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. Reference Nomura, Naja, Ahmed, Mukai, Terao, Machida, Sasakawa and Patra2021).
Spatial Distribution of CO2ff across Megacity Delhi
Using the Equation (2), the CO2ff values calculated for all collected samples across Delhi are given in Table 1, and spatial distribution map of CO2ff is presented in Figure 2. A maximum uncertainty of 1.18 ppm in CO2ff values of all samples can be derived from the corresponding external uncertainty of 2.51‰ in 14C measurements.
The CO2ff 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. CO2ff 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 CO2ff 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). CO2ff 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 CO2ff 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 CO2ff (33.34 ppm) observed in our study is higher than the maximum value observed in Rio de Janeiro state in Brazil (Santos et al. Reference Santos, Oliveira, Park, Sena, Chiquetto, Macario and Grainger2019) and Mexico City (Vay et al. Reference Vay, Tyler, Choi, Blake, Blake, Sachse, Diskin and Singh2009) but lower than the maximum value observed in Xi’an city (Zhou et al. Reference Zhou, Wu, Huo, Xiong, Cheng, Lu and Niu2014) as listed in Table 2. The CO2ff values in this study reflect the daytime fossil fuel CO2 signal because photosynthesis occurs in the daytime only. CO2ff values may be higher during nighttime because of stable atmospheric conditions (Wang and Pataki Reference Wang and Pataki2010).
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 CO2ff over different parts of the megacity Delhi region.
The main findings emerged from this study are as follows:
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We found that the spatial distribution of fossil fuel emissions is heterogeneous across megacity Delhi.
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Δ14C values are varying between –67.78‰ to 5.61‰.
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CO2ff values are varying between 1.63 ppm to 33.34 ppm.
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Sampling sites located in the parks have larger CO2ff 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 CO2ff in megacity Delhi that can be utilized for the mitigation policies.
ACKNOWLEDGMENTS
Authors are thankful to IUAC for extending AMS facility for 14C funded by Ministry of Earth Science (MoES), Govt. of India with reference numbers MoES/16/07/11(i)-RDEAS and MoES/P.O.(Seismic)8(09)-Geochron/2012. The authors would like to acknowledge the support of colleagues, collaborators, and friends for help with collection of samples.
