atmosphere

Communication Can We Vacuum Our Air Problem Using Towers?

Sarath Guttikunda * and Puja Jawahar Urban Emissions, New 110019, ; [email protected] * Correspondence: [email protected]

 Received: 29 July 2020; Accepted: 28 August 2020; Published: 29 August 2020 

Abstract: In November 2019, the Supreme Court of India issued a notification to all the states in the National Capital Region of Delhi to install smog towers for clean air and allocated INR 36 crores (~USD 5.2 million) for a pilot. Can we vacuum our problem using smog towers? The short answer is “no”. Atmospheric science defines the air pollution problem as (a) a dynamic situation where the air is moving at various speeds with no boundaries and (b) a complex mixture of chemical compounds constantly forming and transforming into other compounds. With no boundaries, it is unscientific to assume that one can trap air, clean it, and release into the same atmosphere simultaneously. In this paper, we outline the basics of atmospheric science to describe why the idea of vacuuming outdoor air pollution is unrealistic, and the long view on air quality management in Indian .

Keywords: India; Delhi; air quality; controls; smog towers; filtration systems

1. Introduction

Air pollution is a major health risk worldwide—outdoor PM2.5 (particulate matter) and pollution accounted for an estimated 3 million and 0.5 million premature deaths, respectively, and household (indoor) air pollution for an additional 1.6 million premature deaths [1]. Corresponding numbers for India are 680,000 for outdoor PM2.5, 145,000 for outdoor ozone, and 480,000 for household pollution. Similar estimates were presented by researchers and scientists from the Indian institutes [2–6]. In all the studies, the very young and the old are particularly vulnerable. The year 2020 is an aberration in the pollution trends, with the COVID-19 lockdowns and a range of restrictions for all the sectors [7]. Across India, ambient air pollution levels improved as much as 50% compared to the annual trends for the same period in the previous year [8]. A summary of the data from all the cities with at least one continuous air monitoring station is included in the Supplementary Materials. Following the pandemic, epidemiological work on COVID-19 patients suggests that the risk of mortality is higher among the population exposed to chronic PM2.5 and NO2 pollution [9,10]. One key lesson from the COVID-19 lockdowns worldwide, is that air pollution can be reduced locally and globally by reducing the emissions at the sources. This was witnessed in the data from the ground-based monitors worldwide and retrievals over India, , Italy, and the United States [11–13]. The measures enacted during the lockdowns are unprecedented, but the results are evidence that we eventually need to control the emissions at the sources for “clean air”. While the messages are clear that high air pollution is the leading cause of health impacts and “clean air” is only possible by addressing the emissions at the sources, in November 2019, the Supreme Court of India issued a notification to all the states in the National Capital Region of Delhi (NCR) to install smog towers. These giant filtering systems are being pursued as a control mechanism only in the absence of real action to control the emissions at the sources and the continuing incidence of high air pollution levels in Delhi and other major cities. Examples discussed in the notification for replication

Atmosphere 2020, 11, 922; doi:10.3390/atmos11090922 www.mdpi.com/journal/atmosphere Atmosphere 2020, 11, x FOR PEER REVIEW 2 of 13

While the messages are clear that high air pollution is the leading cause of health impacts and “clean air” is only possible by addressing the emissions at the sources, in November 2019, the Supreme Court of India issued a notification to all the states in the National Capital Region of Delhi (NCR) to install smog towers. These giant filtering systems are being pursued as a control mechanism Atmosphereonly in the2020 absence, 11, 922 of real action to control the emissions at the sources and the continuing incidence2 of 11 of high air pollution levels in Delhi and other major cities. Examples discussed in the notification for replication are (a) a 100 m high purification tower in Xi’an, China [14] and (b) experimental large are (a) a 100 m high purification tower in Xi’an, China [14] and (b) experimental large vacuum cleaners vacuum cleaners called Wind Augmentation and Air Purifying Units (WAYU) were deployed in the called Wind Augmentation and Air Purifying Units (WAYU) were deployed in the cities of Delhi, cities of Delhi, Mumbai, and Bengaluru, with no operational details, and (c) a smaller version of the Mumbai, and Bengaluru, with no operational details, and (c) a smaller version of the Xi’an smog tower Xi’an smog tower in Delhi (Figure 1). The latter designs also include “mist makers” to initiate in Delhi (Figure1). The latter designs also include “mist makers” to initiate coagulation and induce wet coagulation and induce wet scavenging of the . The units installed in Delhi and Mumbai scavenging of the particles. The units installed in Delhi and Mumbai were designed by the National were designed by the National Environmental Engineering Research Institute (NEERI) and Indian Environmental Engineering Research Institute (NEERI) and Indian Institute of Technology (Mumbai) Institute of Technology (Mumbai) and inaugurated by the then Minister of Environment [15]. and inaugurated by the then Minister of Environment [15].

(a) (b) (c)

Figure 1. Examples of ambient filtering systems: (a) a smog tower from Xi’an, China, (Image edited Figure 1. Examples of ambient filtering systems: (a) a smog tower from Xi’an, China, (Image edited from South China Morning Post), (b) a Wind Augmentation and Air Purifying Unit (WAYU) in Delhi, from South China Morning Post), (b) a Wind Augmentation and Air Purifying Unit (WAYU) in Delhi, and (c) a smaller version of Xi’an’s filtering system in Delhi. and (c) a smaller version of Xi’an’s filtering system in Delhi. A fundamental question remains, “can we vacuum our air pollution problem using smog towers and mistA fundamental makers”? question The short remains, answer “can is “no”. we vacuum The idea our of air removing pollution what problem is already using smog in the towers air is unrealistic,and mist makers”? given the The dynamic short natureanswer ofis air“no”. pollution, The idea which of removing moves and what transforms is already simultaneously. in the air is Inunrealistic, this paper, given we outlinethe dynamic the basics of of atmospheric air pollution, science which to moves describe and why transforms the idea simultaneously. of vacuuming outdoorIn this paper, air pollution we outline is unscientific, the basics of and atmosphe the longric view science on airto describe quality management why the idea in of Indian vacuuming cities. outdoor air pollution is unscientific, and the long view on air quality management in Indian cities. In In India, PM2.5 is considered the main criteria for environmental compliance and public health,India, PM and2.5 allis considered of the discussion the main in thiscriteria paper pollutant is about for PM. environmental compliance and public health, and all of the discussion in this paper is about PM. 2. The Sciences 2. The Sciences The definition of atmospheric science can be explained via the three basic sciences—Mathematics, Physics,The anddefinition Chemistry. of atmospheric science can be explained via the three basic sciences— Mathematics, Physics, and Chemistry. 2.1. Mathematics 2.1. Mathematics Mathematics relates to the “quantification” of the problem. In a box model version of a (FigureMathematics2), the size ofrelates the city to the and “quantification” the height of the of the problem. layer willIn a determinebox model the version amount of ofa city air present(Figure 2), at anythe size given of instance.the city and The the inversion height of layer the isinversion an invisible layer layer will ofdetermine air, which the determines amount of theair totalpresent volume at any of given air available instance. for The horizontal inversion and layer vertical is an mixing. invisible This layer height of isair, determined which determines by prevalent the surfacetotal volume temperature, of air airavailable temperature for horizontal at the ground and andvertical upper mixing. layers, humidityThis height levels, is determined and land cover, by allprevalent varying surface in time temperature, and space. There air temperature is seasonality at associatedthe ground with and the upper inversion layers, layer—highest humidity levels, during and theland summer cover, all months varying and in lowest time and during space. the winterThere is months. seasonality This isassociated a typical trendwith the for mostinversion of the layer— inland cities in India [16]. The coastal cities like Chennai and Mumbai experience lesser variation across the seasons due to the constant presence of land–sea breeze. Atmosphere 2020, 11, x FOR PEER REVIEW 3 of 13

highest during the summer months and lowest during the months. This is a typical trend for most of the inland cities in India [16]. The coastal cities like Chennai and Mumbai experience lesser Atmospherevariation2020 across, 11, 922the seasons due to the constant presence of land–sea breeze. 3 of 11

(a) (b)

Figure 2. Depiction of a box model pollution calculation with varying inversion heights (a) for summer Figure 2. Depiction of a box model pollution calculation with varying inversion heights (a) for months and (b) for winter months. summer months and (b) for winter months. Pollution (in the units of µg/m3) is defined as mass over volume, where mass is the emission load 3 and volumePollution is the(in amountthe units of of air μ present.g/m ) is Indefined the summer as mass months, over volume, a higher where volume mass of airis meansthe emission more roomload and for lateralvolume and is the vertical amount mixing, of air and present. vice versaIn the for summer the winter months, months. a high Forer thevolume same of amount air means of emissionsmore room in for all lateral the months, and vertical concentrations mixing, and are vice bound versa to for be the higher winter inthe months. winter For months the same and amount lower inof theemissions summer in months.all the months, For “clean concentrations air” and lower are bo concentrations,und to be higher the in requirementthe winter months is either and higher lower inversionin the summer layer heightmonths. or For lower “clean emissions. air” and It lower is next concentrations, to impossible the to alterrequirement meteorology; is either however, higher reducinginversion emissions layer height should or lower be relatively emissions. easy. It is next to impossible to alter meteorology; however, reducingIn the emissions box model, should we assumedbe relatively that easy. emissions remain constant over months. This is not true. EmissionsIn the are box also model, seasonal, we assumed which in that the caseemissions of India rema arein higher constant in theover winter months. months This fromis not space true. heatingEmissions needs are [also17] alongseasonal, with which a lowering in the incase mixing of India height, are higher further in compounding the winter months the air from pollution space problem.heating needs A hypothetical [17] along casewith isa illustratedlowering in in mixi Tableng1 height,for what further could compounding be the changes the in air the pollution overall pollutionproblem. whenA hypothetical the city size case expands, is illustrated emissions in Table halve 1 or for double, what orcould for changesbe the changes in the meteorological in the overall conditions.pollution when All the the calculations city size expands, assume emissions a steady statehalve condition. or double, The or for worst-case changes in scenario the meteorological is when the emissionsconditions. double All the and calculations the mixing assume height dropsa steady to astate quarter condition. of the norm,The worst-case resulting inscenario a 700% is increase when the in theemissions overall double pollution. and Duringthe mixing the winterheight hazedrops episodes, to a quarter areas of betweenthe norm, , resulting , in a 700% and increase Delhi experiencein the overall these pollution. conditions During [18,19 the]—emissions winter nearly episodes, double areas compared between toPunjab, summer Haryana, months and with Delhi the additionexperience of agriculturalthese conditions residue [18,19]—emissions burning and the near onsetly ofdouble winter compared season requiring to summer more months biomass with and the coaladdition combustion of agricultural to support residue space burning heating, withand the a simultaneous onset of winter drop season in the surfacerequiring and more air temperatures. biomass and Typicalcoal combustion day-time mixing to support layer heightsspace heating, are 1000–2000 with ma insimultaneous the summer drop months in andthe 100–200surface mand in theair wintertemperatures. months. Typical Typical day-time night-time mixing heights layer are halfheights of this. are 1000–2000 m in the summer months and 100–200 m in the winter months. Typical night-time heights are half of this. Table 1. A hypothetical pollution calculation for a city using a steady state box model method. W = width of the city; L = length of the city; H = mixing height; E = emissions. Table 1. A hypothetical pollution calculation for a city using a steady state box model method. W = width of Studythe city; and L = Institution length of the city; H = mixing W height; L E = emissions. H E Pollution %Change BaseStudy case, and all as Institution usual 1.0 W 1.0 L 1.0 H 1.0 E Pollution 1.0 %Change 0% City size doubles in width and length and no Base case, all as usual 2.0 1.0 2.0 1.0 1.0 1.0 1.0 1.0 0.25 1.0 75% 0% change in the emissions − EmissionCity size doubles, doubles everything in width else and is length the same and no1.0 1.0 1.0 2.0 2.0 +100% 2.0 2.0 1.0 1.0 0.25 −75% Mixing heightchange doubles, in the everything emissions else is 1.0 1.0 2.0 1.0 0.5 50% the same − Emission doubles, everything else is the same 1.0 1.0 1.0 2.0 2.0 +100% Mixing height halves, everything else is 1.0 1.0 0.5 1.0 2.0 +100% the same Mixing height doubles, everything else is the same 1.0 1.0 2.0 1.0 0.5 −50% Emission doubles and mixing height halves 1.0 1.0 0.5 2.0 4.0 +300% MixingEmission height doubles halves, and everything mixing height else is is the same 1.0 1.0 0.5 1.0 2.0 +100% 1.0 1.0 0.25 2.0 8.0 +700% one quarter

Emission halves and everything else is 1.0 1.0 1.0 0.5 0.5 50% the same − Atmosphere 2020, 11, 922 4 of 11

Mathematically, for a given set of seasonal patterns in meteorology, especially over the Indo-Gangetic plain, the best option is to cut the emissions at the sources and disperse the emissions to Atmosphere 2020, 11, x FOR PEER REVIEW 5 of 13 farther distances via better urban planning. 2.2. Physics 2.2. Physics Physics relates to the “movement” of the problem. A popular saying is that “pollution knows no Physics relates to the “movement” of the problem. A popular saying is that “pollution knows boundaries”. The box model assuming closed walls in Figure 2 and Table 1 is good to illustrate the no boundaries”. The box model assuming closed walls in Figure2 and Table1 is good to illustrate point that emissions are key for any increase and decrease in pollution levels. Simultaneously, the point that emissions are key for any increase and decrease in pollution levels. Simultaneously, meteorology plays an important role in determining how much of those emissions stay in the box, meteorology plays an important role in determining how much of those emissions stay in the box, determined by the horizontal wind components (U and V), or how much of those emissions will stay determined by the horizontal wind components (U and V), or how much of those emissions will stay close to the surface, determined by the vertical wind component (W) (Figure 3). close to the surface, determined by the vertical wind component (W) (Figure3).

Figure 3. Three-dimensional motion of air through a city. Figure 3. Three-dimensional motion of air through a city. This adds two new dimensions to the air pollution problem: (a) the air is not static over the This adds two new dimensions to the air pollution problem: (a) the air is not static over the city— city—between wind speeds of 1 m/s and 2 m/s, the latter is pushing twice the amount of air through the between wind speeds of 1 m/s and 2 m/s, the latter is pushing twice the amount of air through the city boundaries; (b) the air from outside the boundary carries outside emissions, which add to the total city boundaries; (b) the air from outside the boundary carries outside emissions, which add to the emissions inside the city. Similarly, emissions from inside the city will be carried to a city downwind. total emissions inside the city. Similarly, emissions from inside the city will be carried to a city This is called “long-range ” of pollution—sometimes this is an exchange of pollution between downwind. This is called “long-range transport” of pollution—sometimes this is an exchange of the cities and sometimes between the states. For example, a city like Delhi is surrounded by satellite pollution between the cities and sometimes between the states. For example, a city like Delhi is cities Gurugram (from the state of Haryana) in the West and Noida (from the state of Uttar Pradesh) surrounded by satellite cities Gurugram (from the state of Haryana) in the West and Noida (from the in the East. There is constant movement of vehicles between these cities and in a map of urban state of Uttar Pradesh) in the East. There is constant movement of vehicles between these cities and built-up area, it is difficult to draw a closed box [20]. In this case, depending on the wind direction, in a map of urban built-up area, it is difficult to draw a closed box [20]. In this case, depending on the emissions from each of these cities are affecting the others downwind. wind direction, emissions from each of these cities are affecting the others downwind. The effect of long-range transport is also prominent during the seasonal dust storms (May–June) originatingThe effect from of thelong-range Middle transport East or the is Tharalso promin desertent in the during state the of seasonal Rajasthan dust [21 ],storms and agricultural (May–June) residueoriginating burning from (April–May the Middle and East October–November) or the Thar desert originating in the state mostly of Rajasthan from the [21], states and of agricultural Punjab and Haryanaresidue burning [22]. In both(April–May cases, seasonal and October–November) wind speeds are high originating enough to mostly pick up from and the push states the emissionsof Punjab intoand theHaryana higher [22]. altitudes, In both support cases, seasonal inter-state wind transport, speeds andare high affect enough the pollution to pick levels up and downwind. push the Theemissions overall into known the horizontal higher altitudes, advection support and vertical inter- mixingstate transport, schemes are and more affect complex the pollution than described levels indownwind. this paper. The overall known horizontal advection and vertical mixing schemes are more complex thanGuttikunda described in et this al. (2019)paper. [ 16] presents an analysis for 20 Indian cities, documenting contributions of emissions inside and outside the city airsheds. On average, 30% of the pollution observed in these cities originatesGuttikunda outside et the al. city(2019) limits. [16] pres For citiesents an in analysis North India for 20 like Indian Ludhiana, cities, Amritsar,documenting and contributions Chandigarh, theof emissions long-range inside transport and outside contribution the city is moreairsheds. than On 50% average, on an annual 30% of basis.the pollution observed in these citiesThe originates movement outside of the the pollution city limits. also includesFor cities scavenging—dry in North India deposition like Ludhiana, when theAmritsar, and areChandigarh, in contact the with long-range a surface transport and wet contribution deposition duringis more thethan rains. 50% on The an dryannual deposition basis. rates for variousThe pollutants movement are of determined the pollution by al theso surfaceincludes roughness, scavenging—dry soil moisture deposition content, when and the wind pollutants speeds. are in contact with a surface and wet deposition during the rains. The dry deposition rates for various pollutants are determined by the surface roughness, soil moisture content, and wind speeds. Under windy conditions and over dry surfaces, we have lesser deposition of the , and vice versa on the trees with enough moisture on the leaves.

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Under windy conditions and over dry surfaces, we have lesser deposition of the particulates, and vice Atmosphere 2020, 11, x FOR PEER REVIEW 6 of 13 versa on the trees with enough moisture on the leaves.

2.3.2.3. Chemistry Chemistry Chemistry relates to the “composition” of the problem—the critical one of the three sciences, as Chemistry relates to the “composition” of the problem—the critical one of the three sciences, it links PM2.5, PM10, SO2, NO2, CO and ozone directly to all known health impacts. Of the six as it links PM2.5, PM10, SO2, NO2, CO and ozone directly to all known health impacts. Of the six pollutants, the most critical is PM2.5, and its chemical composition is different in space and time pollutants, the most critical is PM2.5, and its chemical composition is different in space and time [23,24]. [23,24]. While the first five pollutants are part of direct emissions, ozone is a secondary compound While the first five pollutants are part of direct emissions, ozone is a secondary compound formed in formed in the atmosphere in the presence of NOx and hydrocarbons. the atmosphere in the presence of NOx and hydrocarbons.

AA sample sample of of PM PM2.52.5 cancan provide provide information information not not only only on on how how much much pollution pollution there there is, but is,but also also on theon thefuel fuel origins origins of the of the mass mass on onthe the filter. filter. Figure Figure 4 4presents presents a a summary summary of of the the key key marker metals, elements,elements, and and compounds compounds associated associated with with major major so sources.urces. There There are are overlaps overlaps between between the the sources sources andand the the ratio ratio of of the the markers markers also also vary vary significantly, significantly, which which allows allows for for statistically statistically apportioning apportioning source source contributions.contributions. These These markers markers range range fr fromom metals metals from from direct direct combustion combustion of of fuels, fuels, like like coal coal and and diesel, diesel, toto contributionscontributions fromfrom other other gases, gases, like like SO 2 SOforming2 forming sulphate sulphate aerosols (in a series (in a of series reactions of involvingreactions involvingozone and ozone some and intermediate some intermediate radicals), radicals), NOx forming NOx nitrateforming aerosols nitrate aerosols and hydrocarbons and hydrocarbons forming formingsecondary secondary organic aerosolsorganic aerosols (via 500 +(viaknown 500+ known reactions reactions with ozone withand ozone intermediate and intermediate radicals) radicals) [25,26]. [25,26].Ozone isOzone a by-product is a by-product of these of 500 these+ reactions. 500+ reacti Mostons. ofMost the of chemical the chemical transformation transformation between between gases gasesand aerosols and aerosols takes takes place place during during the long-rangethe long-range transport—in transport—in other other words, words, a significant a significant portion portion of ofthe the PM PM2.52.5samples samples collected collected in in the the city cityare are therethere becausebecause ofof thethe emissionsemissions originating outside the the citycity [16]. [16]. The The secondary secondary nature nature of of the the PM PM2.52.5 originatingoriginating from from sources sources not not likely likely within within a acity city boundary, boundary, complicatescomplicates the the overall overall pollution pollution control control strategy.

Figure 4. Key metal and ion markers of various sources contributing to PM2.5. Figure 4. Key metal and ion markers of various sources contributing to PM2.5.

3.3. Do Do Smog Smog Towers Towers Work? Work? ForFor managing managing outdoor outdoor air air pollution, pollution, the the answer answer is isstill still “no”. “no”. Atmospheric Atmospheric science science defines defines the theair pollutionair pollution problem problem as (a) as (a)a dynamic a dynamic situation situation where where the the air air is ismoving moving at at various various speeds speeds with with no no boundaries,boundaries, and and (b) (b) a a complex complex mixture mixture of of chemical chemical compounds compounds constantly constantly forming forming and and transforming transforming intointo other other compounds. compounds. With With no no boundaries, boundaries, it it is is unscientific unscientific to to assume assume that that one one can can trap trap air, air, clean clean it, it, andand release release into the same atmosphere simultaneously. Expecting Expecting filtering filtering units units to to provide provide any any noticeablenoticeable results results at at the the community level level is unrealis unrealistic.tic. This This is is illustrated in in a back-of-the-envelope calculationcalculation for for Delhi Delhi (Table (Table 22)) usingusing twotwo pilotspilots underunder consideration,consideration, (a)(a) T1:T1: aa smogsmog towertower inin Xi’anXi’an (China) designed to filter 10 million m3 of air every day; (b) T2: a smaller version of T1 piloted in Delhi’s Lajpat number market in January 2020, with a capacity of 600,000 m3/day.

For these calculations, we considered Delhi’s airshed, including its satellite cities Gurugram, Noida, Greater Noida, Ghaziabad, Faridabad, and Rohtak, covering an area of 7000 sq.km (~84 km ×

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(China) designed to filter 10 million m3 of air every day; (b) T2: a smaller version of T1 piloted in Delhi’s Lajpat number market in January 2020, with a capacity of 600,000 m3/day.

Table 2. Outdoor air pollution filtering efficiency of the smog towers in Delhi’s airshed.

Variable Delhi’s Airshed T1: Xi’an Smog Tower T2: Delhi’s 2020 Pilot Filtering capacity under full 400,000 25,000 implementation (m3/h) Average airshed volume (m3/h), 1,209,600 million in the calculated using inputs from summer 120,960 million Table3 in the winter 0.000033% in the summer 0.000002% in the summer Filtering efficiency as the amount and 0.00033% in the and 0.00002% in the of air filtered in one hour winter winter 3,024,000 units in the 50,000,000 units in the Number of towers required at summer and 302,400 summer and 5,000,000 full capacity units in the winter units in the winter The Supreme Court of INR 700,000 (~USD India allocated INR 36 Unknown; reported pilot Unit cost 10,000) + operations and crores (~USD 5.2 million) cost is USD 10 million maintenance for replication of T1 Required capital cost for full USD 15,725 billion USD 500 billion implementation in Delhi Required operations and maintenance costs for full HIGH HIGH implementation in Delhi

Table 3. Summary of all day (AD), daytime (DT), and nighttime (NT) averages ( standard deviations) ± of mixing heights (MH in m), near surface temperature (T in ◦C), and near surface wind speeds (WS in m/s) by month. Data is extracted from Weather Research Forecasting (WRF) model simulations using the National Centers for Environmental Prediction (NCEP) reanalysis fields for the year 2018.

Variable January February March April May June July August September October November December MH–AD 298 58 516 94 926 198 1075 254 1243 307 1054 244 573 240 505 152 462 123 501 91 350 73 286 71 ± ± ± ± ± ± ± ± ± ± ± ± MH–DT 557 118 974 187 1801 393 2066 501 2377 640 1855 485 994 450 906 269 827 239 959 184 651 129 534 140 ± ± ± ± ± ± ± ± ± ± ± ± MH–NT 39 8 57 56 51 18 84 45 109 60 254 124 153 85 104 58 97 105 43 13 50 33 38 8 ± ± ± ± ± ± ± ± ± ± ± ± T–DT 18.9 1.8 24.2 2.8 30.5 2.6 35.5 2.4 39.4 2.7 39.0 3.2 33.9 2.9 33.0 2.1 31.4 2.2 30.0 1.6 25.3 1.5 18.8 2.2 ± ± ± ± ± ± ± ± ± ± ± ± T–NT 9.9 1.5 15.3 2.5 19.6 1.8 26.3 2.2 31.1 1.8 34.0 2.3 30.6 2.1 29.3 1.3 26.5 1.1 21.8 1.8 17.5 1.9 11.1 2.8 ± ± ± ± ± ± ± ± ± ± ± ± WS–AD 2.7 0.7 2.8 0.9 3.1 0.6 3.8 0.8 3.7 0.9 4.5 1.2 3.1 0.7 2.7 0.7 2.8 0.9 2.5 0.5 2.7 0.7 2.4 0.6 ± ± ± ± ± ± ± ± ± ± ± ±

For these calculations, we considered Delhi’s airshed, including its satellite cities Gurugram, Noida, Greater Noida, Ghaziabad, Faridabad, and Rohtak, covering an area of 7000 sq.km (~84 km 84 km). × Table3 presents a summary of mixing heights, near surface temperature, and wind speeds for the year 2018. The average wind speed in the domain is 4 m/s (=14.4 km/h) in the summer months and 2 m/s (=7.2 km/h) in the winter months. Similarly, the average mixing heights are 1000 m and 200 m, respectively. This translates to an average exchange of 1,209,600 million m3/h and 120,960 million m3/h of air in the summer and winter months, respectively (city side * speed * mixing height)—this calculation assumes a steady state with constant flow of air and no vertical mixing. The concept of vacuum cleaning has worked in closed environments. For example, (a) in a closed room, if the doors and windows remain shut, then an air purifier is an efficient way to clean the air [27]. This emulates a box model containing a constant amount of air with limited movement. When purifying the closed room, all the dust is collected on a filter, which requires either cleaning or replacement after some time, and a clean disposal of the dust collected. During high pollution days, the frequency of cleaning and replacement is more (b) at the end of a combustion unit, with flue gas moving at a constant flow rate in one direction, like a power plant boiler with a chimney. The system will include an inlet for polluted air and an outlet for cleaned air. This system is designed to trap Atmosphere 2020, 11, 922 7 of 11 emissions at the source, before entering the atmosphere at the top of the chimney. In this case, all the dust (fly ash) from the cyclone bags or electrostatic precipitators or filters also need clean collection and disposal [28]. (c) In a subway tunnel, where the air flow is limited and prone to increased exposure levels, a purifier will induce an artificial air flow, diluting the incoming air, and thus reducing the overall exposure levels. None of these examples present the use of filtering systems to clean the air permanently. In an outdoor environment, at best these systems are a demonstration of a filtering system with negligible efficiencies (Table2), whose performance at a power plant, or at any of the end of the pipe applications where the emissions originate, is the most efficient.

4. Taking a Long View on Air Quality Management The air pollution problem in India is year-round [29,30]. The winter months (November, December, January, and February) are the worst, with stagnant meteorology stifling the lateral and vertical movement of pollution, low temperatures pushing the need for space heating, which is mostly met using biomass [17], and some seasonal emissions from agricultural residue burning [22]. These are in addition to the all-year combustion of petrol, diesel, gas, coal, and waste in the transport, industrial, and domestic sectors, and resuspended from the construction activities and traffic on the roads. The monsoon months (June, July, and August) are the best, with enhanced wet scavenging across the country. The air pollution problem in India is not limited to the cities. An analysis of annual average PM2.5 concentrations, using a combination of satellite retrievals and global emission inventories for the period of 1998–2018, suggests that 60% of the districts do not meet the national ambient standard of 40 µg/m3 and 98% do not meet the WHO guideline of 10 µg/m3 [31]. Typically, North Indian districts are more adversely affected from chronic air pollution. The judicial system played a central role in several air pollution decisions in India: In 1998, the Supreme Court ruled to convert public transport buses and para-transit vehicles to • run on (CNG). This was a public interest litigation, which also led to other emission control measures in Delhi [32,33]. CNG conversion was the most successful for the transport sector and, in the early 2000s, the city of Delhi witnessed a reduction in emissions and pollution. However, the scale of replacement has not been replicated in any other Indian city since, and the overall bus fleet composition in Delhi has remained the same irrespective of the growing demand [34]. In 2015, three toddlers filed a public interest ligation in the Supreme Court of India, to request • a full ban on the sale of fireworks. In an apparent victory for cleaner air, in November 2016, the Court ordered a complete ban on the sale of firecrackers in the NCR. What seemed to be a progressive measure was, however, annulled by a ‘temporary’ ruling, when the ban was lifted with the caveat that the ban will be reinstituted if there is evidence that fireworks are a major pollutant during the festive season. In 2018, the Supreme Court ruled in favour of the introduction of BS-VI standard vehicles • nationwide, starting 1 April 2020, instead of the original plan for 2025 under the auto fuel policy. In 2019, the Supreme Court ruled in favour of an immediate ban on the use of pet (with high • sulphur content) in all industries in the NCR by June 2019. Time and again, judicial interventions have resulted in putting pressure on the respective agencies to implement long-term measures for long-term benefits. Non-judicial interventions proposed and implemented for improving air quality and health are: In 2015, the Government of India launched the smart cities program for 100 cities. While air • quality was not explicitly mentioned as the environment indicator, the proposed activities were designed to benefit overall air quality. These included a ranking system to evaluate the programs, road cleaning, and street greening in the cities. Atmosphere 2020, 11, 922 8 of 11

In December 2016, Delhi proposed the Graded Responsibility Action Plan (GRAP), a series • of measures to enforce under poor, very poor, severe and emergency levels of pollution [35]. These decisions are made based on a 48-h running average of the , calculated using hourly PM2.5 and PM10 levels. This plan is now an example for other cities in the Indo-Gangetic Plain to replicate. A missing link in the program is an independent body with teeth to clamp down on offending polluters across states. The Ministry of and Natural Gas took an important first step with the Pradhan Mantri • Ujjwala Yojana (PMUY) in 2016, providing liquified petroleum gas (LPG) connections to the poorest households. As of September 2019, the PMUY has connected 80 million beneficiaries by directly transferring subsidies to the bank accounts of women in these households and improving indoor and outdoor health [36]. While the number of connections is on the rise, there are barriers to LPG uptake, which need to be addressed [37]. In April 2015, a parliamentary standing committee proposed new emission standards for all the • coal-fired thermal power plants. These standards were ratified in December 2015, tightening the standards for PM and introducing standards for SO2, NOx, and for the first time. If implemented in full, these standards are expected to yield a 50% drop in the PM2.5 (primary and secondary) pollution from these plants [38,39]. All the power plants are expected to comply in 2022. Financial support from the Government of India for the Faster Adoption and Manufacturing • of Electric Vehicles (FAME) program, made electric vehicles (EVs) a new policy and economic choice for small- and large-scale applications. The program now includes subsides for two-, three-, and four-wheelers and the introduction of EV buses into the public transportation system. The Delhi transport corporation is expected to receive its first 1000 buses in 2021–2022 and the Delhi government is promoting EVs to account for 25% of new registrations by 2024. In 2019, the Ministry of Environment, Forest and Climate Change (MoEFCC) announced the National Clean Air Programme (NCAP) for 122 non-attainment cities from 20 states and three union territories [40]. Under the NCAP, every city is required to prepare a list of actions necessary to reduce their PM2.5 levels by 20–30%, compared to 2017, by 2024. The authors of [41] present a review of these action plans, summarizing the key action points that all the cities want to implement as: (a) augmenting public transport, (b) eradicating road and construction dust, (c) abolishing open waste burning, (d) promoting clean cooking, (e) implementing industrial emission standards, (f) increasing ambient monitoring capacity, and (g) raising public awareness. While improving ambient monitoring capacity and raising public awareness are short-term activities (with long-term maintenance), all others are part of long-term planning, designed to reduce emissions at the sources. Following the approval of the 102 NCAP city action plans by MoEFCC, the prevalence of pollution episodes in October–November 2019, and limited action in the cities to counter air pollution, the Supreme Court bench again intervened to demand the installation of smog towers and allocated INR 36 crores (~USD 5.2 million) for the replication of the Xi’an’s smog tower design in Delhi. In August 2020, a memorandum of understanding was signed by the Indian Institute of Technology (Bombay) to design and construct the system. Wasting the judicial power by implementing band aid measures is not only unscientific, but also a waste of limited financial and technical resources. We cannot vacuum our way to “clean air”.

5. Conclusions The city clean air action plans provide proof that there is enough technical know-how on how much air pollution there is, the key sectors that need attention, the institutional requirements to implement long-term strategies, and the ways in which they can be addressed [40,41]. These action plans need institutional and financial support. At the institutional level, there are three tasks that need immediate attention, where the judiciary can help to move the strategies forward: (1) Personnel and Capacity— CPCB and the state pollution control boards are too understaffed to perform auditory Atmosphere 2020, 11, 922 9 of 11 and scientific operations. (2) Monitoring infrastructure—as of June 2020, there are 230 continuous monitoring stations operated and maintained by CPCB in 124 (of 715) districts. More than half of these districts have only one station and 70 monitors are in the vicinity of the NCR, which demonstrates the bias in measuring and managing air pollution outside the big cities like Delhi. To spatially and temporally represent the air pollution problem, India requires at least 4000 continuous air quality monitoring systems (2800 in the urban areas and 1200 in the rural areas). (3) Information support—air quality management requires information on emission loads, source contributions, costs and benefits of interventions, and a way to prioritize actions. The funds allocated by the Supreme Court for temporary interventions like testing smog towers are most useful for implementing these permanent solutions.

Supplementary Materials: The following are available online at http://www.mdpi.com/2073-4433/11/9/922/s1, Table S1: Summary of air quality in 124 cities in India for the periods before and during the 4 COVID-19 lockdowns. Author Contributions: Conceptualization, writing, and editing—S.G. and P.J.; Methodology, resources, and visualization—S.G. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Conflicts of Interest: The authors declare no conflict of interest.

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