Cleaner air would enhance India’s annual solar energy production by 6–28 TWh

India has set a target of 100 GW solar installation capacity by the year 2022. However, the loss of solar energy due to environmental factors like air pollution is not properly considered in renewable energy resource assessments. Here we show that India lost 29% of its utilizable global horizontal irradiance potential due to air pollution between 2001 and 2018. The average loss in output incurred by solar power systems with horizontal, fixed-tilt, single-axis, and dual-axis trackers due to air pollution is estimated to be 12%, 26%, 33%, and 41%, respectively, equivalent to a loss of 245–835 million USD annually. The successful implementation of the National Clean Air Program and the complete mitigation of household emissions through the supply of cleaner fuel for domestic use and rural electrification would allow India to generate a surplus of 6–16 TWh of electricity per year from the existing installed solar power capacity in 2018. This translates to an economic benefit of 325–845 million USD annually, which is equivalent to the implementation costs of these social programs. Mitigating air pollution would therefore accelerate India’s progress towards achieving its solar energy target at a lesser installation capacity, avoiding additional expenditure for the expansion of the solar energy infrastructure.


Introduction
Transitioning to renewable energy is crucial to avoid catastrophic climate change and to achieve sustainable growth. India has committed to reducing the greenhouse gas emissions intensity of its GDP by 33%-35% by 2030 from 2005 levels, and increasing the share of non-fossil-fuel-based energy resources to 40% of the total power production by 2030 under the Paris agreement (UNFCC NDC Registry 2016). Among the renewables, solar energy in India has been growing prodigiously in recent years. According to the International Renewable Energy Agency report (IRENA 2019), India is ranked fifth in the world in overall solar power capacity (www.irena.org/Statistics/View-Data-by-Topic/ Capacity-and-Generation/Country-Rankings), and it has set an ambitious target of 100 GW of installations by 2022 (Niti Ayog 2015). The continuous decreasing trend in the levelized cost of energy, higher module efficiency, and strong support from the Government of India (GoI) has attracted huge investments in solar photovoltaic (PV) technology (Bhushan et al 2015, International Energy Agency (IEA) 2019). The deployment and planning of solar PV and concentrated solar plants (CSP) require appropriate site selection, accurate estimates of global horizontal irradiance (GHI), direct normal irradiance (DNI), and an assessment of the environmental factors that may affect the solar energy resource (Bhushan et al 2015, Jimenez et al 2016. Aerosols in the atmosphere attenuate incoming solar radiation through scattering and absorption. This is known as the 'atmospheric attenuation effect.' In addition to that, aerosols often get deposited over panel surfaces and affect their PV performances, which is termed the 'soiling effect.' Unlike a global transition from dimming to brightening due to a decrease in aerosol loading, air pollution in east and south Asia is on the rise (Wild et al 2005, Streets et al 2006, Soni et al 2012. Hence, the impacts of aerosols on solar energy potential need to be addressed while undertaking new solar expansion exercises over countries such as China and India. China has experienced a loss of 11%-15% in PV potential between 1960 and 2015, with a higher loss (21%-34%) in more recent years due to aerosols (Li et al 2017, Sweerts et al 2019. A city-based study on urban haze found an ∼11.5% loss in solar insolation over ideally tilted silicon (Si) modules in the megacity Delhi during the years 2016-17, causing a loss of ∼20 million USD (Peters et al 2018). Extrapolating the observations from an experimental setup over north-western India in a modeling framework, Bergin et al estimated a reduction of 17%-25% in solar power across India, China, and the Arabian Peninsula with almost equal contributions from the attenuation effect and the soiling effect on a monthly cleaning cycle (Bergin et al 2017). In the same context, a global study estimated a reduction of more than 50% in solar power by aerosols over highly polluted regions like northern India, northern China, and global desert regions (Li et al 2020). Although all these studies point towards a negative impact of air pollution on solar power resources, detailed economic quantitative estimates of the benefits of achieving clean air goals on solar power generation in India are not yet quantified.
Here, we report the impact of air pollution on the solar resources in India by considering both the 'atmospheric attenuation' and the 'soiling effect' over various panel configurations for the 18 years period (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018). Our 'soiling impact' considers the net accumulation of atmospheric aerosols on solar panels per day through dry deposition and the natural rain removal process (Bergin et al 2017, Li et al 2020. We analyze the radiation and aerosol data from Clouds and the Earth's Radiant Energy System (CERES) and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) for the study period. We further estimate the surplus solar energy that India would be able to generate and economic benefits it can reap if air pollution levels in the country are reduced successfully by strictly implementing some of the major mitigation policies announced by the GoI or by meeting the World Health Organization's (WHO's) previous annual air quality guideline (AQG) of 10 µg m −3 in the most ambitious clean air scenario. Finally, we provide a possible pathway based on our mitigation action plan, which can help India to achieve its 100 GW goal on time. All results are discussed, keeping in view the five regional power grids (north, south, west, east, and north-east) in India.

Solar radiation and other meteorological datasets
In this study, we process synoptic gridded (SYN1deg) version 4.1 data from NASA's CERES (CERES Science Team 2017) downward shortwave (0.3-5 µm) flux over the Indian region (6-38 • N, 65-98 • E) at its five regional power grids for the year 2001-18 (figure S1 and table S1 available online at stacks.iop.org/ERL/17/054007/mmedia). We use three ground-based datasets of varied temporal resolutions for evaluating the CERES data. This includes daily data from the India Meteorological Department (IMD) for the year 2016 at eight stations (Soni et al 2012, Riihela et al 2018, per minute interval data from the World Radiation Monitoring Center-Baseline Surface Radiation Network (WRMC-BSRN) from 2014 to 2018 at four stations (Driemel et al 2018), and monthly as well as yearly mean data from the Global Energy Balance Archive (GEBA) for 2001-09 at eleven stations (Wild et al 2017) (table  S2). Combining eight IMD station-days (N = 2281) shows a good agreement with CERES (R 2 of 0.79) with a mean absolute bias error (MABE) of 20.91 Wm −2, and a root mean square error (RMSE) of 28.03 W m −2 (figures S2(a) and (d)). Evaluation with the individual IMD station also shows strong consistency except at Shillong with complex terrain at the north-eastern power grid (with R 2 of 0.45) (figure S3). Analysis of four BSRN stations' data (3249 station days) also shows a good agreement (R 2 : 0.67, MABE: 24.36 W m −2 , RMSE: 39.36 W m −2 ) (figures S2(b) and (e)). Evaluation of 11 GEBA stations on a monthly and yearly mean scale shows strong consistency (R 2 : 0.89, MABE: 9.81 W m −2 , RMSE: 12.53 W m −2 ), as shown in figures S2(c) and (f). Our analysis is consistent with the earlier study with CERES and other ground station observations (Jia et al 2016). This extensive evaluation of CERES with the one regional (IMD) and two global (BSRN and GEBA) datasets, encompassing our entire study period over the Indian region, establishes the credibility of CERES SYN1deg data for further analysis.
Additionally, we use the daily aerosol optical depth (AOD) product (MCD19A2) at 1 km retrieved by a moderate resolution imaging spectroradiometer (MODIS) using the multi-angle implementation of atmospheric correction (MAIAC) algorithm (Lyapustin and Wang 2018). This product performs better than the previous MODIS products at a coarser resolution over India. We converted MAIAC AOD to PM 2.5 (fine particulate matter with an aerodynamic diameter of less than 2.5 µm) using a dynamic scaling factor derived from the MERRA-2 dataset that is calibrated against the Central Pollution Control Board (CPCB) of India reference-grade monitors across India. The instantaneous satellite-derived PM 2.5 was then converted to a 24 h average using the diurnal scaling factor from MERRA-2. The detailed algorithm and the evaluation have been reported recently (Dey et al 2020).
Further, to quantify the soiling effect, the dry deposition fluxes for the four aerosol species, namely dust, sulfate, black carbon, and organic carbon, and rain rate at an hourly scale from MERRA-2, are taken into consideration. The details of CERES, groundbased networks, and other meteorological data are depicted in SI-Datasets (section I).

Experiment design
To quantify the aerosol contributions to the available solar potential, we have performed a set of experiments. These experiments are based on radiation data with varied atmospheric conditions. The details of this experiment and the various data products based on different atmospheric conditions (aerosol and cloud presence) are depicted in table S3. Fundamentals of the solar radiation incident upon PV panels are documented in SI-methodology (section II.1). The impact of the 'atmospheric attenuation effect' of aerosols on solar radiation (R s ) is calculated by (R s,AS − R s,NA ); where R s,AS is all-sky radiation and R s,NA is all-sky with no aerosol. The percentage attribution of the 'atmospheric attenuation effect' of aerosol is obtained by dividing the individual impact with the solar radiation at all-sky conditions (R s,AS ).
Based on earlier studies, the soiling impact has been estimated by combining the effects of both accumulation and removal of particulate matter (PM) over the solar panel surface (Li et al 2020). For accumulation, we consider the dry deposition flux, and for removal, only natural rain-rate have been taken into account. The influence on incoming radiation due to the optical depth of the deposited PM has been estimated based on previous studies (Bergin et al 2015, Li et al 2020 and is given by: where, τ is the 'soiling optical depth' and R S,AS,OUT is the output irradiance from the panel. The 'soiling τ ' is calculated as follows: β i and PM i are the absorption coefficient, scattering coefficient, backscattering ratio, and mass accumulation per unit area, respectively. Here, 'i' represents the above-mentioned four aerosol species. The optical properties of the accumulated PM mass are documented in SI-Methodology (section II.6). Our percentage soiling loss is consistent with the observation (figure S4) at IITGN situated in the western Indian power grid zone on a daily scale (Valerino et al 2020).
Annually, India receives 2600-3200 h of bright sunshine and 300 clear sky days (Soni et al 2012). We consider an average of 7 h of daily bright sunshine across India and a monocrystalline Si module solar panel (panel material efficiency ∼20%). The 18 year average exposed radiation at a horizontal flat surface configuration over the Indian landmass is 4.86 kWh m −2 per day, and the loss in solar radiation due to the aerosol burden is 0.56 kWh m −2 (due to atmospheric attenuation) and 0.59 kWh m −2 (due to atmospheric attenuation and soiling effect) per day. The module output is calculated as 0.30 kWh m −2 per day (= 4.86 × ( 7 24 ) × 0.2) considering 7 h of bright sunshine (in a 24 h period). This is consistent with the average daily generation over the Indian region (https://globalsolaratlas.info/map). Similarly, we estimate the loss due to aerosol loading to be 0.04 Additionally, we also estimate the benefit of meeting the previous WHO-AQG (figures S5-S7, table S4). Systematic procedures are stated in SI-Methodology (section II.2). The gain in solar energy includes gain from the 'atmospheric attenuation' and the 'soiling effect' . To calculate the gain in 'atmospheric attenuation,' a nonlinear relationship between the clear-sky radiation and AOD by following Beer's laws has been considered ( figure S8). In addition to that, to estimate the gain in the 'soiling effect,' a linear relation with the 'soiling optical depth' and AOD on a yearly scale considering per day net accumulation (figure S9, SI-Methodology section II.3) has been considered.

Economic burden estimation
We convert the impact of aerosols (e.g. either loss or gain) on solar energy generation in terms of firsthand monetized values. We assume that the loss/gain in radiation is linearly proportional to the loss/gain of generation and ignore factors such as transmission loss, loss in power conversion, and loss due to other components' inherent complexity and inefficiency. Similarly, we estimate the benefit from the implementation of the three policy options discussed above. In all our calculations, we consider the latest FY 2018-19 cumulative solar installation capacity of 28 GW and 39 TWh yr −1 generation to preserve the consistency in first-hand monetized estimates. We also consider an average cost of 0.052 USD per unit (per kWh) consumption of electricity across the country (https://cercind.gov.in/2021/orders/01-SM-2021.pdf). Further, to examine the impact of aerosol-induced pollution on solar productions, we use installation-generation data from the Central Electricity Authority, Ministry of Power (figure S10,

Solar energy potential in India and its loss due to aerosols
India has been expanding its renewable solar energy goal under the Jawaharlal Nehru National Solar Mission (Jawaharlal Nehru National Solar Mission (JNNSM) 2010). However, the impact of aerosols (and other environmental factors) is not considered exhaustively in solar energy resource assessments for India. We show the 18 year mean annual GHI distribution (figure 2(a)) over five regional power grids in India (figure S1 and table S1), where 60% of the Indian landmass is exposed to more than 5 kWh m −2 per day of annual average global insolation over the period 2001-2018 (figure 2(d)). This is the minimum requirement for solar PV power generation and is consistent with the earlier estimate based on NASA surface meteorology and solar energy (SSE) data with the highest intensity over western and southern India and the lowest over north-eastern India (Ramachandra et al 2011). This abundant solar potential can be utilized in various applications such as solar thermal, GHI-based solar photovoltaic (SPV), and direct normal irradiancebased concentrated solar plants.
The annual average loss in solar resources (over horizontal flat surfaces) due to 'atmospheric attenuation' is −0.56 kWh m −2 and due to the combined effect of 'atmospheric attenuation' and 'soiling effect' is −0.59 kWh m −2 per day with considerable spatial heterogeneity across the grids (figures 3(a) and S11(a), (c) horizontal). The maximum loss in GHI is noted over the eastern power grid (−0.76 kWh m −2 per day, 16%), followed by the western and northern power grids (table 1), in conjunction with the observed spatial gradient in aerosol optical depth over India (Dey and Di Girolamo 2010). The seasonal pattern of this impact follows the seasonality of the GHI, the variation in aerosol-loading, and aerosol deposition fluxes (figures S12 and S13). The maximum impact of aerosols on GHI is noted during the premonsoon (March-May) and post-monsoon seasons (October-November). Compared to other seasons, the total GHI loss in absolute terms during the winter season (December-February) is not high as the overall availability of GHI itself is lowest during this season, but the relative loss of GHI is found to be the highest. In the monsoon (June-September) season, the loss in solar power due to aerosols is the lowest in India, as monsoon rain cleans the ambient atmosphere as well as aerosol loads on solar panel surfaces. Our estimates show that avoiding almost two decades of the per-day annual 'atmospheric attenuation' effect could add an additional 28% GHI potential across the Indian landmass. Along with the 'atmospheric attenuation,' precluding the per day 'soiling load' could brighten a further 1% of the Indian region (a total of 29% enhancement) with sufficient GHI for SPV generation (figures 2(b)-(d)).

The sensitivity of aerosol-driven solar power loss to solar panel settings
In addition to the horizontal flat surface configuration (horizontal), we also analyze the impact of aerosols on GHI for three other prominent solar panel configurations, namely: fixed-tilted flat surface at a latitudinal tilt (fix), single-axis vertical tracker at a latitudinal tilt (single), and dual-axis trackers (dual). These trackers in solar engineering have been designed to better utilize the direct component of the total radiation or GHI. In India, optimally tilted solar panels are widely used, and very few plants have trackers in operations (Bhushan et al 2015, TATA Solar Power 2017. The single-axis trackers follow the sun diurnally, and the dual-axis trackers follow the sun both diurnally and seasonally. Our analysis suggests that most of the northern grid and parts of the western grid experience considerable enhancement in energy utilization upon the implementation of trackers ( figure S14(a)). Relative to the horizontal flat surface solar panels, dual-axis configuration has the highest tracking advantage (92%), followed by the single-axis (80%) and fix-tilted setting (60%) in the northern grid. Overall, the northern grid experiences the highest tracking advantage, followed by the western, eastern, north-eastern, and southern grids (figure S15). Mainly, the latitude of the location and the fraction of direct radiation in the available GHI at that location are responsible for tracking advantages in various solar panel configurations. Over the Indian landmass (figure S14(b)), the regions closer to the equator (e.g. the southern grid) and areas where the percentage contribution of direct radiation in total irradiance is smaller than ∼40% (e.g. most parts of the eastern and north-eastern grids) experience relatively lesser energy enhancements through trackers (Li et al 2017).
Aerosols, by absorbing and scattering incoming solar radiation, reduce the direct radiation and enhance the diffuse radiation (figure S16). As different panel settings and trackers are designed for better utilization of direct radiation, the attenuation effect of aerosols is larger for more advanced trackers (dual > single > fix > horizontal). The highest attenuation due to aerosols are noted over highly polluted regions like the Indo-Gangetic plain and dust-dominated Thar desert, thereby covering large parts of the northern and eastern grids (figures S11(a) and (b)).
For the soiling effect, the aerosol deposition tends to be much more on a horizontal flat surface than optimally tilted fixed panels and a minimum for the most sophisticated trackers like dual trackers. This is because tracking panels frequently change their tilt angle and thus provide a smaller effective surface for aerosol deposition. In our calculations, we neglect the gravitational sedimentation for the trackers and fixed tilted panels but consider both sedimentation and turbulent deposition for horizontal flat surface panels. It is to be noted that the turbulent flux is uniform in all directions and is independent of the trackers' movement. Like the atmospheric attenuation effect, the soiling effect of aerosols is also pronounced over the highly polluted regions across India. The overall impact of the soiling effect depends on the available GHI, rain rate, and the aerosol dry deposition flux on solar panels (see section 2.2). Incorporating all these factors, just as in the case of the atmospheric attenuation effect, the impact of the soiling effect is higher on more sophisticated panel configurations (figures S11(c) and (d)).
On a daily scale, the total aerosol impact is mainly governed by the atmospheric attenuation effect rather than the soiling effect. As the regional power grids in India are commissioned based on the utilization, procurement, transmission, and demand for electricity, the impact in SPV generation due to aerosols is not uniform across the power grids. In the eastern grid, aerosols decrease the total radiation by 16% Table 1. Grid-level 'atmospheric attenuation' effect and 'total impact' of aerosol on exposed total radiation for all four-panel orientations. The percentage impact of only the 'atmospheric attenuation' effect and 'total impact' are shown in parenthesis. The negative sign signifies the reduction effect. in horizontal, 35% in fix-tilt, 42% in single-axis, and 52% in dual-axis panel settings. However, in absolute terms, the loss in total radiation due to aerosols is larger in the northern grid (having the highest tracking advantage) than in the eastern grid if we switch to advanced panel orientations or trackers (figures 3 and 4). The grid-wise power loss statistics are summarized in table 1.

Economic burden of solar energy loss due to aerosols
Considering 7 h of average daily sunshine and monocrystalline Si modules (20% efficiency), the 18-year average loss in solar radiation in terms of the module output is 0.04 kWh m −2 per day over a horizontal flat surface, to 0.21 kWh m −2 per day over a dual-axis tracker (table 1 and figure S17). We estimate that over the last two decades, aerosol in the atmosphere alone resulted in an average loss of 12% (horizontal) to 41% (dual) in solar energy potential across the country. This translates to a 245-835 million USD loss annually (CERC 2021). The GoI has launched several utility scales and off-grid solar energy schemes along with an attractive subsidy to exploit renewable solar installations (Ministry of New and Renewable Energy (MNRE) 2019) (table S6). India is also a founder member of a treaty-based International Solar Alliance (International Solar Alliance (ISA) 2015) with more than 120 countries pledging a mission of 'Every home no matter how far away, will have a light at home,' and therefore, promotes the capacity building, generation, and adaptation of solar energy nationwide. Our analysis suggests that the GoI should promote and implement air pollution mitigation plans with urgency to accelerate the growth of the renewable energy sector. Cleaner air would surely enhance solar energy production along with co-benefits opportunities for public health, climate, and economy.

Policy options for India
The GoI has introduced three major policies in recent times to reduce air pollution (Balakrishnan et al 2019). The PMUY was launched in 2016 to provide clean energy for cooking to 80 million households below the poverty level (MoPNG 2016). The DDUGJY was launched in 2014 to electrify 600 000 villages and eliminate kerosene lighting (MoP 2014). It has been shown that complete eradication of household emissions due to cooking and heating with dirty fuel and kerosene lighting could meet India's national ambient air quality standard in 2015 (Chowdhury et al 2019). The NCAP was launched in 2019 to reduce fine particulate matter (PM 2.5 ) concentration by 20%-30% in 122 nonattainment cities by 2024 relative to 2017 (MoEFCC 2019).
We estimate gain in solar energy from improved air quality through the successful implementation of Figure 4. Box plot of daily mean total aerosol impact across the regional power grids over various solar panel settings. Each box ranges from the first quartile (Q1) to the third quartile (Q3), with a median. The IQR is the interquartile range (Q3-Q1); the upper whisker and lower whisker extend to the last datum less than Q3 + 1.5 IQR, the first datum greater than Q1-1.5 IQR, respectively. Beyond the whiskers, data are considered as outliers and are plotted as individual red + points. Green circles represent mean values. Different solar panel settings like horizontal flat surface (Horz), fixed tilted panel (fix), single-axis tracker (single), and dual-axis trackers (dual) are also depicted above. these policies. Our analysis suggests that the complete transition of the household sector to clean energy use in India through the PMUY and DDUGJY would generate a surplus of 3 TWh yr −1 (over a horizontal flat surface) to 8 TWh yr −1 (over dual tracker) with respect to the existing solar power generation of 39 TWh yr −1 in FY 2018-19 from 28 GW of cumulative solar installation currently operational in India. This excess solar power is equivalent to a worth of 163-425 million USD annually (figure 5 and  table S4).
Meeting the NCAP target would also generate 3 TWh yr −1 (horizontal flat surface) to 8 TWh yr −1 (dual tracker) of solar power worth 162-420 million USD annually. This surplus of energy would be more pronounced over the eastern and north-eastern power grids as the population in these regions rely extensively on fossil fuel and biomass burning for their day-to-day activities (Balakrishnan et al 2019). The combined benefits from these current policies are worth 325-845 million USD with respect to the existing solar capacity of the nation and are equivalent to the budget allocation for the PMUY (1100 million USD, www.india.gov.in/spotlight/pradhanmantri-ujjwala-yojana#tab=tab-3) and NCAP (42.6 million USD for the first two years, www.nrdc.org/experts/anjali-jaiswal/india-launchesnational-clean-air-program). If India had met the previous WHO-AQG in 2018, this would offer a surplus of 10 TWh yr −1 (horizontal flat surface) to 28 TWh yr −1 (dual tracker) solar energy based on the present-day generation capacity of 39 TWh yr −1 , resulting in additional revenue of 505-1425 million USD annually.

Accelerated progress towards 100 GW target
The world has seen an exponential growth in solar renewables capacity building for the last two decades (IRENA 2019, REN21 2019). India has generated its solar power installation capacity from less than 3 GW in 2013-14 to 35 GW in 2019-20 (table S5). If the current trend continues, the exponential expansion will help India to achieve its 100 GW of installation targets by FY 2022-23 (figure S10). With the solar installed capacity of 28 GW (in FY 2018-19), India could have accomplished 98% of the solar generation in the next FY 2019-20 (i.e. 50 TWh yr −1 ) by simply avoiding almost two decades of particle-induced burden. In fact, imposing the integral benefits of the NCAP and eradication of household emissions by implementing the PMUY and DDUGJY (in FY 2018-19) could even have generated ∼1% more energy than the actual energy generation of the next FY 2019-20 (table S5). We further show that if India can completely avoid air pollution or strictly implement the PMUY and NCAP, then with a mere 76 GW installation (proposed in FY 2021-22), it can achieve 95% and 98% of the equivalent generation from 100 GW of installed capacity respectively ( figure 6 and table S5). Note that we consider fixed tilted panel configuration in our estimates as this setting is widely used in India either as roof-top or in-ground-mounted (Niti Ayog 2015, Bhushan et al 2015). Our results suggest that cleaning air will not only accelerate India's transition towards its renewable energy goals, but it would also save the additional revenues required for 24 GW of installation in the coming years due to the area involved balance-of infrastructural cost such as manpower, financial, and customer acquisition (Lewis 2016) to meet its 100 GW target.

Discussion and conclusions
Our analysis demonstrates that India's solar energy goal can be realized on time, even earlier, if the current installation trend is followed along with the air pollution mitigation plans. In this study, we consider only the direct impact of aerosols on solar energy. Climate studies have shown that cloud lifetime increases with an increase in aerosol loading (Twomey 1974, Christensen et al 2020. It implies that mitigating air pollution would also reduce cloudiness, which in turn would further enhance solar power production. In addition to that, precipitation is inhibited in polluted clouds. Thus, if pollution is reduced, it could be hypothesized that increased precipitation would lead to more wet scavenging and even further reduction in the aerosols present in the atmosphere and thus increase solar power generation. However, this aspect needs to be quantified in a modeling framework that can address aerosol-cloud interaction. Therefore, we conclude that the actual benefit of reducing air pollution could be much higher in India than what we report in this study.
We make a few assumptions firstly; we consider 7 h of daily sunshine across the Indian landmass.
We assume benefits in clear-sky radiation as the actual solar energy generation benefits by considering 300 clear-sky days annually over the Indian region. In our calculation of either loss or gain in solar energy generation due to air pollution, we assume the same base-year generation irrespective of panel configurations. In our economic burden analysis, we only convert solar PV output in terms of monetized value and do not consider the infrastructural cost for the setting up of various solar panel configurations. The temperature dependency of the solar panel efficiency has a minimal effect at near-standard temperature and hence is constant throughout our analysis (www.pveducation.org/pvcdrom/solar-celloperation/effect-of-temperature). To estimate soiling impact, we assume no multiple scattering between the aerosol species and the panel systems. Since aerosol single scattering albedo remains unchanged in the study period , the partitioning of direct and diffuse radiation is assumed to be unchanged (figure S18).
Our findings will help policymakers, planners, and investors to better assess the solar power resource and facilitate expansion of the solar infrastructure over India in the coming years. Since air pollution mitigation policies are expected to bring notable benefits to SPV generation, particularly in direct radiation-based CSP plants (figure S19), the GoI needs to invest more in the country's CSP installation facility. Our results show that the economic benefit of reducing air pollution in terms of excess solar power generation is equivalent to the current implementation cost of the major air pollution mitigation policies. This is in addition to the enormous health benefit expected due to the reduction in air pollution exposure (Balakrishnan et al 2019). Therefore, the assessment of solar resources should be incorporated while conducting the cost-benefit analysis of any air pollution mitigation plans in India.
The PMUY has been instrumental in increasing the accessibility of clean fuel in India, but various factors deter sustained usage of clean fuel (Mani et al 2020). Similarly, the clean air action plans proposed by various nonattainment cities under the NCAP lack prioritization based on cost-effectiveness and ease of implementation (Ganguly et al 2020). India must overcome these practical hurdles and ensure proper implementation of these important policies to extract maximum benefit.
Our analysis delineates that air pollution mitigation actions have prominent potential to reinforce solar energy generation in India. Therefore, the design of new policies targeting the control of individual aerosol species can be assessed in the future.
The penetration and adoption of solar renewables through increasing usage of different solar appliances such as solar lanterns, solar heaters, solar cookers, and other allied noncarbon products, and the enhanced production of solar energy, would reduce India's dependency on coal for power generation. This is likely to further accelerate the reduction in air pollution across the country.

Data availability statement
The data used in this paper can be made available from the corresponding authors upon reasonable request.

Code availability
The codes used to analyze the data and produce the results are available from the corresponding authors upon reasonable request.