- 1 We want to thank the survey participants, SAQI volunteers, and anonymous reviewers for their vital (...)
1‘Datafication’ is generally understood simply as a process transforming subjects, objects and practices into digital data, enabling quantification and analysis of complex phenomena.1 Globally, data-centric approaches to policy have emerged, which can help understand and address persistent socio-environmental issues in greater detail and nuance, but these changes also raise questions, particularly in relation to democratization. There is an urgent need to understand datafication in more social terms to ensure that citizens are not excluded and marginalized in the process of standardizing information. Datafication draws its significance from the fact that it supports data-driven decision-making and supposedly effective problem-solving (Kitchin 2014; Lupton 2014; Naimi and Westreich 2014). However, a one-size-fits-all approach to datafication is limited by factors such as personal experiences, levels of exposure, sociopolitical contexts, and community participation and engagement, and these aspects are often ignored in policy formulation processes.
2In this paper, we consider how far the datafication of environmental policy can contribute to a shift from the technocratic scientism evident in the current datafication discourse to more citizen-science-oriented policies aimed at mitigating the air pollution crisis in Delhi and, more broadly, in the context of cities in the Global South that are witnessing a public health crisis due to pollution. In India, data-led environmental governance is a recent phenomenon. We witness the first traces of it, especially in relation to air pollution, in the National Air Quality Index (NAQI), launched by the Indian government in 2014, which provides real-time data on air quality in major cities across the country. Delhi, the capital city of India, is an important case in this change since data-driven governance using air-quality monitoring stations to calculate the AQI has led to several decision-making and policy-guiding interventions in the city (Gulia et al. 2021).
3According to Negi and Srigyan (2022), “Delhi’s toxic air has invited a technoscientific scramble to understand, interpret, and provide fixes” over the last decade (p. 1). However, it is also critical to comprehend how residents perceive air pollution, which may differ from the way scientific experts perceive it. Negi and Srigyan (2022) argue that engaging with residents’ daily experiences is crucial for forming effective collaborations and taking action to reduce air pollution. It is in this context that we consider ongoing efforts toward the datafication of air quality and explore how such change can be integrated in the socio-economic-spatial context. The paper aims to explore the potential role of community engagement in the production and use of data on air pollution at the neighborhood level. It is motivated by the current air-pollution data regime that is centralized and separated from local communities, rendering the latter mere consumers of the data produced by a technocratic logic that excludes concerns of equality and social justice. In this vision of data consumers, only citizens and communities with access to relevant knowledge get to use the data.
4Our methodology involved a yearlong mapping and monitoring of air pollution in six Delhi neighborhoods using a community-participation approach. We set out to demonstrate how new data epistemologies are needed to address knowledge barriers on the one hand and to help create community-level response mechanisms on the other. The project involved working with communities and engaging them in a participatory project to collect air-quality data through low-cost sensors (LCS), while also surveying the subjective responses of community members within six distinct locations in the Delhi neighborhoods of Okhla and Najafgarh. Through this participatory approach, the paper examines the limits of the existing model of air-quality data collection and explores whether claims of greater awareness are fulfilled across the various social groups inhabiting the neighborhood. A crucial objective was to understand the way in which low-cost sensor-based data practices help to bridge the gap between people’s awareness of pollution and their willingness to be involved in policy practices.
- 2 Air quality deteriorates during the winter months in Delhi, and this is also reflected in the growt (...)
5This section focuses on the debate that has emerged on scientism versus citizen science in relation to environmental problems. Scientism focuses on technological approaches to address environmental challenges, while citizen science involves the participation of non-scientists in scientific research to address environmental issues (Kimura and Kinchy 2019; Negi and Srigyan 2022). Our paper explores the potential of citizen science in addressing urban air pollution, and assesses the reach of AQI in a move toward a more inclusive and democratic approach to environmental policy. Datafication via standardization, and more specifically by indexing pollution levels, is a relatively recent phenomenon worldwide (Mejias and Couldry 2019; Thom and Ott 1976; Voelkl et al. 2021). However, it has spread incredibly fast because AQI appeals to database and application developers and to the management of air quality through market-based solutions (Booker et al. 2023). In Delhi, hundreds of products use the AQI label as a means to target elite customers2 (The Hindu 2020). Though AQI is also used by state and government agencies to advance public awareness and regulate emissions in urban areas, much of the recent impetus has come from private firms using AQI in an aggressive manner to market consumer products with the promise of an instant means of alleviating health problems that have emerged due to the rising levels of pollution in the capital.
6AQI was first used in industrialized economies, which relied on standardized data to mitigate the impact on the environment and public health. In the context of the United States of America, the problem of pollution of the environment and of the air at municipal and neighborhood levels became an opportunity to cultivate active citizen engagement within the broader politics of environmental and climate issues (Fisher, Svendsen, and Connolly 2015), while arguing that science “of the people, by the people, for the people” would improve “data democracy” (Kimura and Kinchy 2019:20). The rise and prominence of the Environmental Protection Agency in the USA led to the development of standards and databases against which scientists, citizens, and local leadership were able to compare levels of pollutants and their active outreach, with a view to prompting the groups of citizens concerned to undertake action. In this context, AQI and, more recently, similar air-quality indices and datasets have become a source of local and state-level action (Garnett 2017). Regarding these approaches, Booker et al. (2023) argue that “in the context of air quality science, the scientific gaze is referred to as a ‘metrological regime,’ which standardizes ways of knowing the air and determines what comes to count as air pollution and what concentrations are harmful” (p. 33). Furthermore, they argue that air pollution is a hybrid phenomenon, understood and produced through socio-economic and political practices and material environmental processes.
7Citizen sensing and participatory sensing are viewed as grassroots efforts that challenge traditional technoscience and governance alignments because “it is often difficult to reduce air pollution emissions through the conventional political channels” (Gabrys 2017:175). Low-cost sensors (LCSs) are widely used instruments when citizens actively engage in managing air pollution (Mahajan et al. 2020).
8Existing research on LCSs indicates that neighborhood-level air pollution is a long-standing issue. Community air-pollution mapping using LCSs is a worldwide approach that is expected to further develop (Varaden et al. 2021). Gabrys (2017) argues that using DIY air-monitoring devices, or LCSs, can create new forms of collective attachment, individual identity, and political engagement to address environmental problems.
- 3 Discussion on air pollution monitoring in India with CPCB scientist “C” on May 5, 2022, at IIITD.
9The government uses high-tech instruments in fixed monitoring stations, but these are sparsely located and require considerable investment that cannot be easily replicated. On the other hand, LCSs provide an opportunity to produce insightful data at a fine-grained level by increasing the density of the urban pollution monitoring network (Commodore et al. 2017; Kumar et al. 2015; Mahajan et al. 2020; Sahu et al. 2020). At present, the reliability of LCSs is neither scientifically proven nor certified by regulatory agencies. In our interactions with the scientific community, such as the pollution research scientists at India’s Central Pollution Control Board (CPCB), experts were concerned about the accuracy of data generated by low-cost sensors, as it could potentially undermine the enforcement of air pollution policies.3
10Nonetheless, proponents of citizen sensing emphasize the importance of involving citizens in the monitoring process, even if the data collected is not completely accurate. Furthermore, some contend that a greater number of monitoring sites and the ability to spot changes in data patterns are more important than precise numerical readings (Gabrys 2017). However, it is also argued that citizen science can be problematic if it is not carried out critically (Booker et al. 2023). Moreover, it is recommended that before deploying low-cost sensors for air pollution monitoring, one should compare their reliability with that of precise monitoring instruments in order to prove the credibility and validity of the data generated by LCSs. In this context, our social-AQI project was carried out in Delhi with the aim of focusing on the social dimensions of AQI and similar indices, and of identifying the ways in which communities’ social and spatial settings inform their awareness and interest in citizen-led pollution-data initiatives.
11As previously stated, central government agencies such as the CPCB already rely on AQI and other standardized indices to address environmental challenges. This is part of a wider push toward a data-driven economy, and the change has percolated into the social sector. The evolving political economy of digitalization generates empirical and normative tensions between the market-driven, scientific standards of the data-driven approach on the one hand and the governance framework on the other, because political scrutiny of decision-making is critical to democratic accountability in the emerging environmental policy regime.
12While its proponents argue that data-driven decision-making is more appropriate, especially in domains such as environmental regulation, it has been shown that datafication can also lead to less democratic decision-making because claims of science and objectivity make it difficult for citizens to contribute to and hold governments accountable for pollution regulation (Niemeijer 2002). Hence, datafication needs to be evaluated both normatively and empirically against the experience of citizens. As Merry (2016) pointed out, “the increasing importance of quantification in governance reflects the emergence of what might be called an ‘indicator culture’” (p. 9) that values numerical data as knowledge and a decision-making tool.
- 4 The odd-even scheme in Delhi is a traffic control policy that aims to reduce air pollution levels i (...)
13This mode of governance works through the collaborative production of standards and the evaluation of outcomes, including the use of self-assessment and ranking techniques (for example, the Gross Domestic Product and Human Development Index). Standardizing air quality through AQI is one form of this type of indicator. The Indian Central Pollution Control Board adopted AQI standards in 2014 to simplify pollution data for the general public. The main aim was to spread air-quality awareness using six bands classified as good, satisfactory, moderately polluted, poor, very poor, and severe. Each band has a color code to visually express the level of severity. It also promoted the development of public-health interventions: the government would issue health alerts in the city based on AQI. For example, the “Odd-Even Scheme”4 was launched in Delhi in 2016 to bring down AQI levels (Kar 2021).
- 5 This work, in collaboration with IIT Delhi, is part of an initiative by the government of India and (...)
14In somewhat of a contrast to the context of environmental politics in the Western world, in India the measures and the know-how to develop AQI and open datasets have had a slow start, and it is only in recent years that there has been a growing interest in standardizing air-quality monitoring in urban areas (Nasir, Goyal, and Prabhakar 2016). In the course of our research, we discovered that a number of public institutions dedicated to advancing scientific knowledge on air pollution increasingly rely on data-driven approaches to map air pollution. These include the CPCB, the Institute of Tropical Meteorology, the leading Indian Institutes of Technology (IITs), the Council of Scientific and Industrial Research, the Indian Council of Medical Research, and the National Environmental Engineering Research Institute. These institutions have developed initiatives such as the National Air Quality Index as well as the SAFAR web application, which aims to provide real-time air-quality information and forecasts. The IITs have also implemented measures such as the National Clean Air Program, while IIT Bombay’s Aerosol and Air Quality Research Facility is working towards effective solutions to address India’s air pollution problem.5
- 6 PM2.5 refers to small inhalable particles that measure 2.5 micrometers or less in diameter. These f (...)
15The policy focus in India has so far been on monitoring emissions rather than the impact of air quality on public health, especially in industrial zones and areas with large marginalized populations. In 2019, deaths attributable to PM2.56 pollution in India were found to have increased 2.5 times over the two previous decades, according to a report by the think-tank Centre for Science and Environment (CSE) (Outlook 2022). Moreover, monitoring is often undertaken by centralized boards that focus primarily on regional and large-scale emissions. The Central Pollution Control Board is the most prominent of these centralized monitoring agencies and has become the nodal authority for coordinating with state-level monitoring bodies since the late 1990s. In Delhi, there is also the Delhi Pollution Control Board, but we found the CPCB to have much more direct involvement in air-pollution policy, partly due to the fact that this agency is based in the National Capital Region, which receives an extraordinary amount of attention both in the national media as well as in policy debates.
- 7 The Supreme Court of India is the highest constitutional court with the power of judicial review an (...)
16The story of the shifting narrative of air pollution in Delhi needs to be read in the broader context of urban politics and the institutional dynamics of governance. Institutional dynamics shaped the response to the problem of air pollution (Bell et al. 2004; Rizwan, Nongkynrih, and Gupta 2013; Véron 2006). Although it was recognized that the roots of the air pollution problem lay in the extensive processes of industrialization, urban development, and human settlement, the response to the problem was framed as urban governance and planning failure (Véron 2006). In fact, the judiciary intervened in the matter, framing the problem as a governance failure; it perceived the problem in terms of the violation of rules and addressed it accordingly. The Supreme Court’s7 intervention proved to be a watershed moment in the datafication of air-quality governance. It was the beginning of a long process whereby the apex court tried to frame identifiable causes of air pollution and tangible criteria for air quality. The emphasis was on reducing vehicle emissions by transitioning to cleaner energy, and the case for transitioning to Compressed Natural Gas (CNG) as the only fuel for all public and commercial vehicles was premised on the argument that it was impossible to prevent the spurious mixing of lubricants and kerosene into vehicle fuels. The government’s inability to control violations provided the bedrock for the policy (Bell et al. 2010).
17The establishment of standards for industrial units was a relatively lesser challenge, especially hazardous ones in “nonconforming areas.” The Delhi Master Plan was premised on a single land-use policy that permitted only one land-use type in a particular zone. Industrial units in any area not categorically assigned for industrial use were considered a violation. The “sealing drive,” under which the court sanctioned the closure of industrial units in non-conforming zones and their transfer, was premised on this category of violation (Narayanan 2018).
- 8 Ontologies are used for creating knowledge graphs that represent and integrate heterogeneous inform (...)
- 9 SPARQL: Data stored in a knowledge graph is queried using SPARQL query language.
18The paper is centered around the Social-Air Quality Index (S-AQI) project, which was carried out by a team of social scientists, field workers, computer scientists, and computer engineers from the Indraprastha Institute of Information and Technology, Delhi (IIIT-D). The project aimed at understanding the gaps in centralized AQI-based air pollution governance and sought to come up with a spatially engaged and community-centric conception of air-quality management. The social scientists and the field workers in the team focused on the socio-spatial aspects of air pollution in selected unplanned neighborhoods of Delhi, while the computer science team worked on data processing, cleaning, integrating and structuring heterogeneous data from different sources. This was accomplished by describing the pollution, pollutants, air-pollution-sensor data and survey data in a machine-processable artifact named ontology.8 An app was developed by querying the integrated data using a query language called SPARQL9 to raise awareness among various social groups.
19The study was conducted using a mixed-methods approach that included three main components. First, interactive discussions with community members were held in order to encourage individual and community involvement. Second, in order to make the research more participatory, three workshops were organized, gathering together a variety of key stakeholders, including scientific experts and local communities. Through the use of low-cost sensors, the third component concentrated on engaging local communities and empowering them to understand and use AQI data to manage their daily activities.
20For this study, we focused on the unplanned localities of Delhi rather than the planned middle-class pockets. Our primary concern was to understand the air pollution issue beyond the privileged middle-class groups that have historically blown their own trumpets about the air pollution issue in the city. Since the aim of the research was to explore problems of democratic inclusion and participation of communities in the wake of datafication, it makes sense to address the air pollution problem in unplanned colonies. Bhan (2013) mentioned that only 23% of the city’s total population lives in planned urban colonies, while the rest of the population lives in unplanned neighborhoods. We selected two sites in Delhi (Okhla and Najafgarh) with six different sub-localities chosen because of their distinct social and spatial attributes concerning air pollution exposure and contribution. In Okhla, the three sites were Sanjay Colony, Tekhand, and Shaheen Bagh; in Najafgarh, the sites were Nangli Dairy, Najafgarh, and Jarodha Kalan. The sites comprise slums, unplanned and unauthorized colonies, an urban periphery, and an urban village. These locations are home to poor-to-middle-class populations and are distinct from well-planned areas. We consciously chose marginalized social groups located in these areas and, based on initial findings, further categorized the population into students, teachers, local shopkeepers and vendors, mothers of young children, social workers, and athletes with sporting aspirations. Social demographics in these localities show a mix of natives from local villages and migrants. The majority of natives and migrants come from marginalized socio-ethnic groups, which have historically suffered caste- and religion-based prejudices from the state as well as within society (Harriss 2005).
21The selection of sub-localities in each area was based on socio-spatial considerations, with a focus on unplanned localities. It is worth noting that Okhla and Najafgarh are both situated on the outskirts of Delhi (Map. 1), with different socioeconomic characteristics and land uses, as discussed later. Peri-urban areas are highly stressed and have numerous governance blind spots (Negi and Srigyan 2022).
Map 1
Map of Delhi with fieldwork sites
Source: created by the author using Quantum GIS (QGIS) and Open Street Map (OSM) as the data sources.
Map 2
Major sources of pollution in Okhla
Source: created by the author using Quantum GIS (QGIS) and Open Street Map (OSM) as the data sources.
22Okhla is situated in a planned industrial zone surrounded by opulent areas of south Delhi and shares boundaries with NOIDA, Faridabad and Badarpur. A power plant in Badarpur imported technology from the former Soviet Union, Czechoslovakia, and the United States during the 1970s. The plant’s operations are environmentally hazardous because a significant amount of the coal remains uncombusted, making it the country’s most toxic power plant (Negi and Srigyan 2022).
23However, the power plant is not Okhla’s only source of vulnerability. Tekhand (Map. 2), a tightly clustered, marginalized village in south Delhi located at the intersection between multiple sources of pollution, is among the most vulnerable sites we studied. Negi and Srigyan (2022) specify that these sources are primarily path-dependent and include the inland container depot and railway station, where approximately ten thousand diesel trucks that arrive at the depot each night emit significant amounts of pollution. The second concern is the proximity of one of the three municipal landfills in Delhi, which is officially closed but still accepts waste.
- 10 Similar patterns were observed during fieldwork and interviews (2021–2022).
24Sanjay Colony is located in Okhla Phase II and is a slum surrounded by two industrial areas. Most people here work in nearby industrial units and factories. The commonest occupation among the wage-earning population is contracted export jobs, scrap dealing, shopkeeping, tailoring and factory work (Dimri and Sharma 2006).10 During our field work, we learned that many children in the area suffer from tuberculosis, as reported by the Deepalaya Foundation, an NGO working in the area.
25In Shaheen Bagh, the Timarpur-Okhla waste-to-energy plant, which began operating in 2011, emits toxic fumes 24 hours a day, seven days a week. The presence of restaurants and informal businesses and ongoing construction activities contribute to worsening air quality. Our observations and interviews suggest that the area is inhabited by university students, small-scale businesses, service-based industry workers in Noida, etc.
Map 3
Major sources of pollution in Najafgarh
Source: created by the author using Quantum GIS (QGIS) and Open Street Map (OSM) as the data sources.
26On the other side of Delhi, Najafgarh is an area that is rarely studied (Map 3). It has a rural and urban economy and an unevenly distributed demography. It is an expanding peripheral town surrounded by farmland, has mixed land use, and appears to be deceptively less polluted. For Najafgarh, the surrounding areas are an additional source of pollution (Map 3). Indeed, the construction boom in the neighboring city of Gurugram has resulted in a concentration of brick kilns along the border between Najafgarh and Gurugram. Heavy-goods trucks carrying building materials drive through the area at night. It is worth noting that, despite the absence of significant sources of pollution in Najafgarh itself, the air quality remains alarmingly poor.
27In Najafgarh, we selected Nangli Sakrawati and Jharoda Kalan as sites for installing sensors. Nangli Sakrawati village, situated on the outskirts of Najafgarh, has undergone a complex urban transformation. The young generation from farming households has been converting land into warehouses and factories to rent them out to secure a fixed income. This is transforming this part of Najafgarh into an unregulated industrial area currently known as Nangli Sakrawati small-scale industrial area (NSSSIA). This is the Municipal Corporation of Delhi (MCD) dairy farm that was relocated to the area in 1976 because Delhi’s first master plan mandated that nuisances of a rural type, such as dairy farming, should be moved outside the city boundary. Jharoda Kalan is a village surrounded by other villages (Dhichon Kalan), unauthorized colonies, farmland and many government institutions, such as the Police Training College of the Department of Police, the Central Reserve Police Force (CRPF) camp, Government schools, and the dispensary.
28To conduct our research, we procured low-cost air-quality sensors from Aerogram, a Delhi start-up that develops air-pollution devices. The local sensors used in this study monitored the levels of particulate pollutants, specifically PM1.0, PM2.5, and PM10. In addition, the sensors recorded the relative humidity and temperature of the environment. These sensors functioned based on the principle of estimating the average particle density within a given volume by using lasers to count the number of particles of varying sizes. Subsequently, by combining this particle count with certain assumptions, the average density was estimated. Note that this estimation method is subject to several assumptions and presents a certain margin of error. However, it provides a reasonable estimation of PM concentrations.11 Six sensors were placed in places selected on the basis of factors such as dense population, local pollution sources, and proximity to markets. In terms of the precise location, we relied on support received from individual community members who showed an interest in learning more about the sensors and were willing to help us with day-to-day maintenance.
29Despite their limitations, the LCSs used in the course of this research were significantly less expensive than high-tech alternatives. As we sought to comprehend the implications of data affordability for low-income communities living on the outskirts of cities, cost concerns were a critical factor. The sensors’ limitations included the need for a continuous Wi-Fi connection and a power source. Furthermore, the sensors had to be placed in open areas, such as on balconies or rooftops, to ensure that the readings were representative of the local environment. To handle these issues, we chose cybercafes, non-profit organizations, shops, and other public places as sensor-installation sites and we worked alongside individuals with a keen interest in the project to ensure that the power supply was not disrupted. We also made routine field trips between October 2021 and March 2022 to ensure that the sensors were functioning properly.
30The project began on March 25, 2021, with the first week dedicated to delineating the boundaries of our research sites and understanding the social, cultural, and spatial phenomena in these areas through fieldwork. However, owing to COVID-19, the Delhi government declared a second lockdown from April 5 to June 15, 2021, which disrupted our fieldwork. As a result, we focused on secondary literature to further our study during this period. From July to September 2021, we resumed fieldwork and selected sensor deployment sites.
31The primary goal was to help communities understand their local AQI data. Our project’s slogan was “Aapka AQI data, aapke hath” (Your data is in your hands). We attempted to understand the utility of low-cost sensors and their ability to democratize AQI knowledge in the Delhi community through a neighborhood intervention-based approach that goes beyond scientific and technocratic decision-making, typically ignoring stakeholders in marginalized urban communities (Negi and Srigyan 2022). With our sensors, we carried out field visits to locations to perform ethnographic research and we regularly conferred with community members to discuss their ideas and interests in air-quality-related issues. In order to ensure uniformity across sites, we selected Social Air Quality Index (SAQI) volunteers (two from each location) to work alongside us and engage in conversations about air pollution in their communities. They also helped us identify respondents for fieldwork. The process proved beneficial for fostering dialogue and creating a platform for community engagement.
32During the installation of sensors, we encountered numerous obstacles in each of the six locations. However, it was interesting to see how individuals in both neighborhoods reacted differently to our intervention. Their interest in our intervention was linked to their socioeconomic status, literacy level, and political opinions. In Sanjay Colony, for example, it was easy to interact with the community and persuade them to install the sensor. Residents were interested in understanding their community because they lived in a notified slum in an industrial region lacking sanitation and essential amenities. They expected that, after these studies had been conducted in their community, the neighborhood could be improved and the government would hear their voices.
- 12 Local shopkeeper, Tekhand, September 25, 2021.
- 13 Local shopkeeper, Nangli Sakrawati, October 1, 2021.
33In Tekhand, on the other hand, there was a mixed response. As the village was so close to the huge Okhla landfill, it was easy to bring up the subject of air pollution. However, when it came to placing the sensor, the respondents asked how it would benefit them (isme mera kya fayda hai).12 They demanded payment in return for the installation of the device on their property. They contended that, as graduates of a government college, we should be provided with money to address these logistical issues. We were met with a similar reaction when a shopkeeper in Najafgarh inquired how much rent we would pay for this, asking us, “What company do you work for?”13
- 14 Narendra Modi has been India’s prime minister since 2014.
- 15 Student, Shaheen Bagh, August 26, 2021.
34As participation was central to our study, paying out money ran contrary to our methods. However, such encounters helped us comprehend the lack of political and civic engagement with regard to air pollution. Similarly, we learned how certain socioeconomic groups in Shaheen Bagh are wary of state and government interventions. People in this neighborhood, with a sizable Muslim population, were skeptical about our research and sensor device. We received remarks such as, “Has Modi14 sent you for surveillance? It’s a camera, isn’t it? And why is it making noise?”15
- 16 The anti-CAA protests were a series of nationwide demonstrations against the Citizenship Amendment (...)
- 17 The Khajuri Khas riot was a communal riot that broke out in northeast Delhi in February 2020.
- 18 Teacher, Shaheen Bagh, March 12, 2022.
35Another participant said, “I’d like to see what’s inside the sensor.” A teacher (about 50 years old) added, “We know you’re doing your research, and it’s a good thing for us, but as you know, what happened in Delhi in the last two years, the anti-CAA protests,16 the Khajuri Khas riot.17 As a result, people find it difficult to trust the state’s objectives and your project.”18
- 19 Arvind Kejriwal is an Indian political leader who currently serves as Chief Minister of Delhi.
- 20 Local political party activists, Najafgarh, October 3, 2021.
36Aside from a general defiance of the state, there were times when suspicion was founded on political affiliations. One of the most frequent comments we heard in Najafgarh (this time from one of the property dealers who also dabbles in local politics and supports the BJP) was, “Is Kejriwal19 planning to send this data to Pakistan? to detonate a weapon on us?” (Kejriwal, kya data Pakistan bheje ga isliye ye sensor lagwa raha hai, uske pass system nhi hai jo tumhe bheja hai… kahi hum par explosive gira de).20
37After successfully installing the sensors, often with the assistance of younger members of the community who operated cybercafes in the neighborhoods, the next significant challenge was data consistency. Electricity and internet connectivity were needed for the sensors to operate continuously. For example, there was a fire in a neighboring factory in Sanjay Colony, and an electricity outage lasted for a few days. As a consequence, the sensor was rendered inoperable for that period.
38Furthermore, these low-cost sensors contained a number of technological flaws. Due to dust, they would occasionally cease working all of a sudden or begin to make a strange noise. On occasion, the algorithm would produce an error. These occurrences occasionally irritated our project workers. To limit the number of errors, the sensors required frequent maintenance and monitoring. Other than learning about the AQI sensors’ technical flaws and obstacles, we discovered a broader picture of people’s general skepticism about the deployment of LCSs, knowledge of AQI data in these neighborhoods, and disparities across social groups.
Figure 1
Interactive offline quiz/workshop with students’ mothers (author, 2022)
39Between August 2021 and March 2022, we created two teams to perform additional ethnographic observations and a survey in two areas. We conducted 100 structured interviews using a questionnaire intended to detect social and institutional differences in AQI-data knowledge and use. An equal number of interviews were conducted across Okhla and Najafgarh. 50 interviews were conducted with males and 50 with females. Survey respondents were chosen using stratified sampling, with ten responses drawn from each major social cohort based on the research area attributes described above. We also held workshops with offline quizzes to evaluate people’s knowledge of air pollution in their area. In Figure 1, we are holding a workshop with mothers of young children at an NGO in Sanjay Colony, showing them how to use the sensor and app to check the quality of their air and to organize their daily routine.
40Key sections of the questionnaire dealt with the following themes:
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Institutional or organizational information
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Knowledge of air quality
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Perception of air quality
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The government’s action and responsibilities
41We discovered a dearth of awareness about the Air-Quality Index among the selected colonies during the initial part of our fieldwork, prior to the installation of the sensors. Despite being conscious of the air pollution issue, local communities—with the exception of a few students, teachers, and athletes—did not incorporate AQI into their everyday vocabulary. Our interactions with local council functionaries revealed that the lack of public engagement with AQI provided an opportunity for local government and elected representatives to present air pollution as a state- and central-level problem, leading to a democratic deficit in terms of community participation in local governance.
- 21 Sixty installations of the app were made to collect feedback.
42In order to increase awareness about AQI and suggest measures to mitigate the harmful impacts of air pollution within a particular locality, we developed a mobile and web-friendly application that is available in the local languages (Hindi and English). We modeled the sensor and survey data (collected by social scientists) using the SAQI ontology and integrated the data into a Knowledge Graph (KG) (Figure 3). We designed a neighborhood pollution dashboard, SAQI app (Figure 2), that leverages the KG to answer questions related to air pollution and to suggest measures that can be taken by different social cohorts such as students, teachers, mothers of young children, athletes, etc. The SAQI app creates awareness and encourages individuals to take steps towards mitigating the effects of air pollution in their locality.21 Our datasets aim to gain insights into the problem of air pollution in Delhi. They are available to the public at https://dx.doi.org/10.5281/zenodo.7448007.
Figure 2
The Social-AQI app
Figure 3
Schematic diagram of an integrated community-participation approach for air-quality awareness
- 22 Student’s mother, Najafgarh, September 9, 2021.
43As previously stated, the two sites, Okhla and Najafgarh, are significant in terms of social diversity and spatial position. Okhla, for example, is primarily an industrial region; the common perception is that it has higher levels of pollution than areas such as Najafgarh. Najafgarh was chosen as a study site because it has a rural and urban economy, as well as a population that is unevenly distributed. It is a complex neighborhood on the western periphery of Delhi where one can witness the process of urbanization, local politics, and conflicts. In terms of air pollution, several Najafgarh residents thought their neighborhood was cleaner than the rest of the city because it is on the outskirts and surrounded by open crop fields. We frequently heard, “There isn’t much pollution here; you should study in central Delhi; there are open fields here” (yahan itna pollution nahi hoga aap main Delhi study karo, yahan toh khula hain area or khet hain).22
44Because of the areas’ socio-spatial variation, we conducted an analysis to investigate how locals perceive the air pollution issue at the two sites, which adaptive mechanisms have evolved, and how AQI data is managed and regulated in these two distinct localities. The results were compared to highlight the levels of a) access to information and data barriers, knowledge of AQI data, b) perception of political responsibilities, c) coping mechanisms and local awareness at the six localities within the two study sites.
Figure 4.1
Figure 4.2
45Our findings revealed that there was limited access to information across all the study locations. However, the extent of this limitation differed among various social categories in Okhla and Najafgarh. In Okhla, teachers, students, social workers, mothers of young children, and local shopkeepers and vendors were interviewed, while in Najafgarh, interviews were conducted with teachers, students, athletes, mothers of young children, and local shopkeepers and vendors.
46The overarching pattern, however, was that a significant portion of the populace had little to no access to AQI data from both sites. More specifically, 29 of the 50 Okhla interviewees knew what the Air Quality Index (AQI) was, and 26 of those 29 had studied up to graduation and including post-graduation. On the other hand, 21 of the 50 respondents had no idea what AQI was, and 15 of those 21 had only completed high school or had never attended school. In Najafgarh, those with limited literacy proficiency had little or no understanding of the Air Quality Index (AQI) and associated issues, especially among mothers concerned about their children’s health. During peak pollution months, students and teachers were much more aware of the AQI and had access to AQI statistics via mobile phones, newspapers, and news agencies. Thirty-eight of the 50 respondents claimed to have been informed of the AQI. Several sports instructors mentioned during our conversations that they were concerned about air pollution because of recent occurrences of smog. When we interviewed mothers of younger children as well as local shopkeepers and vendors in Nangli Sakrawati, many of the mothers expressed deep concern about local air quality and their children’s health, but they were unfamiliar with the term AQI and unaware of the harmful effects of air pollution. Women also talked about their daily experience of physical discomfort due to exposure to air pollution, such as burning eyes, fatigue, and breathing problems, and about how this has evolved over the last few decades. During our interviews, some people stated that donning a mask during COVID-19 was no problem for them because they already had respiratory issues or allergies to dust and pollution. They said that they had been wearing masks to protect themselves from pollution prior to the pandemic.
47It is also worth noting that, when asked if they had seen the dashboard screens in Delhi that display the quality of the city’s air pollution, roughly half of those we met in our survey said they had but told us that they did not understand what the different colors meant regarding the quality of the ambient air. The general trend was for individuals to either receive AQI data or not have any access to it. This should be taken into account because some respondents stated that AQI data was more or less available. Interestingly, but perhaps predictably, Najafgarh Sports Academy athletes were more aware and conscious of the air-quality index. As they engage in outdoor activities, the majority of them check the AQI on a regular basis. The athletes showed significant knowledge of the location of the Delhi Pollution Control Committee monitoring station in Najafgarh. “Governments want to keep their report cards clean, as they have installed the Najafgarh sensor far from the highly polluted and populated city in the relatively clean rural Najafgarh area,” a few of them (Joginder and friends, cricket players of less than 35 years of age) remarked.
48In Okhla, field observations and contact with authorities and residents demonstrated minimal public involvement with AQI data. One such instance was a conversation with a ward councilor (incumbent) in Shaheen Bagh who expressed reluctance to participate in the project and said that there was no way to know for certain what questions he might have to face if pollution levels were found to be higher than the estimated standards. Local administration is fraught with a lack of accountability across all locations, which is exacerbated by a system defined by data-driven policy and decision-making. As a result of this, there is a major democratic deficit across the board; together, the local political representative, who evades accountability because of centralized AQI data on the one hand, and the lack of community awareness on the other hand, maintain the status quo. This is true at both municipal and higher levels. This led us to speculate that encouraging civic participation or making AQI data meaningful would help individuals connect with the numerical values produced by AQI.
49In Okhla, 40 of the 50 respondents reported that their workplaces seldom give any information about air pollution or organize seminars or awareness sessions. The responses from store owners, women, and social workers consistently followed this pattern. Most respondents said no well-established organization in the vicinity dealt with pollution-related problems. The majority of people were unaware of their existence.
50Data and participant observations from Najafgarh show that many social groups hold the state government and local municipal corporations directly responsible for regulating air pollution in their area. However, there were significant variations in their responses; for example, athletes said that they would prefer participation from all levels of government. For them, it is everyone’s responsibility: the state’s, the federal authority’s, or the citizens’. Local shopkeepers, on the other hand, felt that the issue should be politicized. Some even wanted air pollution to be an advocacy subject. Others grumbled about the government’s work not being satisfactory in their area, despite the fact that their area is considered marginalized or disadvantaged.
- 23 Swachh Bharat Abhiyan is a cleanliness and sanitation campaign that was launched by the Indian gove (...)
51They were referring to Connaught Place in central Delhi, where the Smog Tower was installed, claiming that “everything is already clean. Modi’s Swachh Bharat Abhiyan23 is limited to office buildings. What about our roads?” Furthermore, by not locating the sensor in a congested region of Najafgarh, the government is blowing its own trumpet, they said.
52It is also essential to understand that local and higher authorities attempt to sidestep responsibility for Delhi’s air pollution problem, blaming each other or neighboring states instead. This behavior leads to a lack of accountability and cooperation, thus limiting efforts to address the situation effectively. Local responses are therefore of significance for decentralized decision-making, community-level involvement, and resilience across locations. In Okhla, for example, despite the fact that a sizable majority thinks that air pollution problems should be politicized, at least at a local level, local elected officials do not want to address these issues in their election campaigns.
- 24 Former local councilor, Shaheen Bagh, March 2021.
53According to a former local councilor we met at his office, “the Delhi government is tackling the issue at a much larger level, and the state government has provided substantial funding to address the crisis.”24 In Okhla, local politicians were seen as reluctant to take up the issue because they felt that they could do very little about it. When asked why air pollution was not on the agenda of the upcoming municipal elections, they maintained that air pollution is a central or state issue and vast amounts of funds are required to tackle it. By contrast, when we asked citizens questions about the government’s responsibility in addressing crises, the majority of those polled concluded that while the government is eager to work toward solutions, there is an urgent need for more policy action. Indeed, a sizeable gap exists between the level of commitment among local elected officials and the growing expectations among citizens, who see much more room for improvement.
54A similar story emerged at the other Najafgarh sites. We discovered a predictable pattern in the opinions of party workers who vocally blamed opposing parties’ governments. For example, Mr. Satyapal Malik (BJP), ward councillor of the Roshan Pura neighborhood in Najafgarh, discussed that the primary cause of pollution in Delhi is road traffic and dust. Dust is the primary cause of pollution in Delhi, as there is minimal manufacturing activity in the city. Only our rural Najafgarh has 10–15 bus depots; the Delhi government should decentralize them. Not much attention is given to Delhi Dehat. No trees were planted here. He also brought up the installation of the “oxygen and smog towers,” indicating the politicization of this somewhat controversial scheme. We also interviewed the councilor and deputy chairperson of Najafgarh ward 43S, Meena Yadav, concerning the air pollution issue in her area; she was disconcerted and refused to proffer any kind of statement on the subject.
55As previously established, various subgroups of the population highly value different aspects of pollution-related concerns. While government policies need to be decentralized, efforts also have to come from the bottom up. To accomplish this, a thorough understanding of AQI-related programs has to be shared. People need to be educated about the complexities of data, local organizations have to be empowered, and a solid framework needs to be established to alleviate local crises. This is important because our study found that different communities reacted differently to different sources of air pollution.
56Residents’ reactions in Okhla were rather diverse; however, Sanjay colony was greatly impacted due to its proximity to factories, which was reflected in the area’s response. On the other hand, traffic and road congestion emerged as a recurring theme in residents’ responses about the causes of air pollution in the different regions, especially in the late afternoon and early evening. According to the results of our survey, 94 out of the 100 respondents believed that vehicle emissions were a significant source of air pollution in their area. Many respondents also stated that the number of vehicles on the road had increased dramatically, with people purchasing cars just to show off. Across all our research sites, however, most people did not perceive rising levels of air pollution as being a major issue, though this varied according to the location. Nonetheless, 42 of the 100 respondents judged that Delhi’s neighboring states, such as Punjab and Haryana, were to blame for the deteriorating air quality caused by burning stubble, brick kilns, and power plants.
57In Najafgarh, we discovered that athletes have the potential to bridge the AQI knowledge gap. In recent years, governing bodies for athletics have worked to empower athletes by installing a growing network of air-quality monitors in stadiums or near places where World Athletics events are hosted. The project Social-AQI will create a real-time global air-quality database, collecting data and information that will be crucial for identifying local air-pollution sources and determining the best solutions to combat them.
- 25 Delhi NCR, or Delhi National Capital Region, is a metropolitan area comprising Delhi and its surrou (...)
58The athletics sector can use this project to bring people together and contribute to overcoming the challenges created by social inequalities. This network of air-quality sensors will be used to create datasets that will enable World Athletics to advise on the best time to partake in sports in each location, in cooperation with the government and other existing monitoring networks. Vinod Yadav, a 36-year-old primary schoolteacher who practices archery, said that his breath-holding capacity is reduced during peak pollution days. In Najafgarh, he observed, air pollution also comes from nearby factories and brickworks located in the bordering state of Haryana, in places like Bhiwani. “We could also see a complete change in air quality when one moves towards Jaipur through Gurgaon, where the NCR region25 ends.”
59Our study resulted in an unconventional approach to the AQI issue. When we introduced the sensors to the neighborhoods, a number of SAQI volunteers suggested alternate strategies for installing these sensors in their respective areas. We explained that the issue is not just about how well they function as a source of data and information but also about the motivations the local populace may have for engaging with this data on their own terms. “You should conduct a workshop with the community,” one of the SAQI volunteers we spoke with at Nangli Dairy in Najafgarh suggested. “Air can be a huge political agenda in Delhi in the future; it is occurring gradually; you can see the banners and posters.” This also applies to Okhla, where pollution-related problems are becoming politicized, particularly in Shaheen Bagh. In a few locations, we saw banners and hoardings claiming that if political parties and municipal representatives were elected, they would reduce air pollution.
60The findings add to and validate the claims made in the citizen science debate. Decentralized data sources and governance mechanisms enable local marginalized communities to relate to AQI data more effectively than to standardized results from higher echelons. Even though we understood the challenge in terms of data literacy and accuracy, we were able to demonstrate on an experimental level that the datafication process itself includes a degree of scientific uncertainty in addition to the social constraints regarding how it is created, implemented and used on the ground.
61Low-cost citizen science techniques for monitoring air pollution have shown the benefits of taking steps at the local level to adapt to changing situations, including varying pollution levels in neighborhoods. While the CPCB’s current framework for data collection is beneficial for developing a national agenda, local sensors and datasets can be more in keeping with the capabilities and requirements of local people. Exposure to local pollution, for example, is influenced by resource availability in places like urban villages, slums, and peripheral agricultural regions. Furthermore, residents’ social background and institutional ties influence how they respond to pollution. According to our results, those associated with sports academies, schools, and other community-based organizations are more likely to be informed about AQI readings and thus in a better position to interact with the data on the ground.
62Decentralizing data systems and democratizing air-quality measurement and governance structures are essential for empowering communities to plan their daily activities around local air-quality conditions. Local institutions may not play a significant role in air pollution mitigation and improvement, but they do involve local communities and institutions in the datafication of governance and leverage local resources. They rally citizens behind them on critical public health and air pollution issues.
63According to our findings, a decentralizing policy mechanism is required to delegate control of air-quality monitoring from agencies such as the CPCB to local representatives and authorities. This shift would allow local actors to be more proactive in addressing the civic participation issue. Our findings show that local schoolchildren and teachers are more conscious of the AQI and its link to pollution, making them more likely to work with local environmental groups to address the issue. Furthermore, it would be worthwhile providing extra assistance to schools and neighborhood institutions to help them localize AQI sensors and develop data management capacity in their communities. It is important to note, however, that other social groups with which we have not yet had any contact may also be aware of AQI. As a result, future studies should seek to engage with these groups and examine their views on air-quality monitoring and control.
- 26 Carrington, Damian, and Damian Carrington, Environment Editor 2022 “‘Put Kids First’: India’s Warri (...)
- 27 Arriagada, Evelyn. 2020. “‘Las Madres Del Plomo’: Women’s Environmental Activism and Suffering in N (...)
64Setting up local organizations and empowering them to coordinate local air pollution problems has the potential to contribute to discussions on citizen science and the development of resilience mechanisms at the local level. These local institutions can help educate people and, in particular, support marginalized populations and foster commitment. For example, based on our survey, it has been found that mothers, as a social group, exhibit the highest level of concern regarding the health effects of pollution. However, they are currently unaware of effective means to channel their concerns into action. This observation is consistent with proven examples of mother-led mobilization around air pollution issues, such as Warrior Moms in India26 and Mothers Against Pollution in Chile.27 It illustrates the fact that when mothers are organized and empowered, they can play a significant role in driving change related to air pollution. Furthermore, many people are often hesitant to become involved in politics, with the exception of local shopkeepers who are more outspoken. Because most people do not associate blame and accountability with the government, formal institutional support can help bridge this political gap.
65Data and datafication have made substantial inroads into the policy landscape in general and particularly into decision-making regarding urban governance issues. Current trends suggest that in the coming years, high-quality, high-resolution data on air quality will become more readily accessible and commercially available. Nonetheless, unless social networks are created to embed this data in communities, this will result in a more centralized system of control and surveillance than a model for democratic governance. In order to understand the patterns of information exchange and explore how interactions with data shape social relations, we studied diverse locations in the two urban neighborhoods of Delhi. While the patterns of these interactions appear to differ depending on location and social group, what they all have in common is a general dearth of literacy in AQI data.
66This article has explored the role of citizen science and low-cost devices in standardizing air-quality data and promoting environmental justice at the local level. It argues that the decentralization of data governance and the promotion of local data are essential for effective policy formulation and adaptation at the local, neighborhood level. Our findings contribute to the growing corpus of knowledge about using technology to promote environmental justice and civic involvement. The paper argues that increased citizen participation and widespread knowledge would make AQI data more legible and meaningful to people. This, we contemplate, is critical if datafication is to serve a democratic purpose. A comparison across groups, as done in our findings above, indicates that the gaps in AQI awareness have a social basis; groups living in the most marginalized neighborhoods are not unconcerned, but the rise of an AQI-based governance regime has left them with little say in determining the path forward. The paper concludes that, though there is no universal means of ensuring that more data leads to greater awareness in urban neighborhoods, managing local data sources is vital for informed policy choices and local political action.
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