Physicochemical characteristics of PM2.5: Low, middle, and high– income group homes in Agra, India–a case study

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  The present study shows the current scenario of the aggregate relation between income and pollution at the household level. The indoor sampling of fine particulate matter was conducted in low– middle– and high–income group homes in Agra City, the
     Atmospheric   Pollution   Research   5   (2014)   352 ‐ 360   ©    Author(s)   2014.   This   work    is   distributed    under    the   Creative   Commons    Attribution   3.0   License.   AA tm spheric PP ollution   R R  esearch   w w w .at m o sp o lr m    Physicochemical characteristics of PM 2.5 : Low, middle, and high–income group homes in Agra, India–a case study  Pradyumn   Singh,   Renuka   Saini,   Ajay   Taneja   Department    of    Chemistry,   Dr.   Bhim   Rao    Ambedkar    University,    Agra,   India ABSTRACT   The   present   study   shows   the   current   scenario   of    the   aggregate   relation   between   income   and   pollution   at   the   household   level.   The   indoor   sampling   of    fine   particulate   matter   was   conducted   in   low–   middle–   and   high–income   group   homes   in   Agra   City,   the   North   Central   region   of    India.   The   mean   indoor   concentrations   of    PM 2.5   were   46.7   µg/m 3 ,   39.2   µg/m 3   and   25.6   µg/m 3   in   low–   middle–   and   high–income   group   homes   respectively.   The   full–day   variation   revealed   that   the   concentrations   of    fine   particles   were   higher   during   morning   and   evening   hours   in   all   the   three   income   group   homes.   The   indoor   meteorological   parameters   were   also   monitored.   Using   scanning   electron   microscopy   coupled   with   energy   dispersive   x–ray   spectrometer   (SEM–EDS)   chemical   and   elemental   analysis   of    fine   particles   and   their   probable   sources   has   been   conducted   in   low–   middle–   high–income   group   homes.   EDS   spectra   indicates   the   elemental   composition   of    PM 2.5   which   can   be   distributed   into   following   groups   of    particles   i.e.   C–O   rich   (54%),   F   rich   (42%)   and   other   (4%)   in   low–income   group   homes.   In   middle–   and   high–income   group   homes   F   rich   (59–65%),   C–O   rich   (32–37%)   and   other   (3–4%)   were   observed   in   PM 2.5 .   The   SEM   images   of    fine   particles   indicates   that   the   particles   are   clustered   into   following   groups   i.e.   aluminosilicates/silica   particles,   spherical   carbon   rich   particles,   nearly   spherical   fluorine   rich   particles,   Mg–Si   or   Mg–Si–Al   particles.   Keywords:   Indoor     Air    Quality    (IAQ),   Socioeconomic   Status   (SES),    fine    particulate   matter,    physical–chemical    characteristics,   meteorological     parameters   Corresponding    Author:   Ajay Taneja    :   +91 ‐ 989 ‐ 7476288      :    Article   History:   Received:   10   October    2013   Revised:   09    January    2014    Accepted:   01   February    2014   doi:   10.5094/APR.2014.041   1.   Introduction   In   urban   areas   industrialization   and   economic   growth   have   resulted   a   dramatic   increase   in   the   number   of    office   buildings,   manufacturing   units,   and   residences   simultaneously   with   the   rise   in   both   the   number   and   density   of    motor   vehicles.   This   has   resulted   in   a   profound   deterioration   of    air   quality   (Chan   and   Yao,   2008).   Increasing   anthropogenic   activities   linked   to   socioeconomic   status   have   significant   bearing   on   the   air   quality   scenarios   (Kim,   1992;   Mitra   and   Sharma,   2002;   Branis   and   Linhartova,   2012).   In   India,   air   pollution   has   turned   out   to   be   a   major   worry   in   recent   years.   The   huge   parts   of    the   Indian   urban   population   are   exposed   to   the   utmost   pollutant   levels   throughout   the   world   (Smith,   1993;   Schwela,   1999;   Yale   CELP,   2007).   Interest   in   indoor   air   quality   is   primarily   fueled   by   the   fact   that   individuals   spend   the   majority   of    their   time   indoors.   It   is   projected   that   people   spend   more   than   around   80–90%   of    their   time   indoors   (Branis   et   al.,   2005;   Schweizer   et   al.,   2007;   Taneja   et   al.,   2008).   During   this   period,   they   are   exposed   to   an   ample   range   of    pollutants   of    indoor   and   outdoor   srcin.   Indoor   emission   sources   and   formation   processes   consist   of    out   gassing   from   furniture,   textiles,   carpets,   building   materials,   processes   like   cooking,   heating,   smoking,   residues   from   personal   care,   pesticides   and   specific   indoor   physical   activities   such   as   cleaning,   and   walking   (Fan   et   al.,   2003;   Smolik   et   al.,   2005;   Morawska   and   Salthammer,   2006;   Zdimal   et   al.,   2011).   Outdoor   pollutants   also   infiltrate   readily   into   interior   spaces   through   open   windows,   doors,   and   ventilation   systems   of    the   buildings.   Pollutants   in   indoor   spaces   have   mixture   of    both   outdoor   and   indoor   sources   (Massey   et   al.,   2009;   Nasir   et   al.,   2013).   It   was   made   known   that   aerosols   are   common   class   of    indoor   air   pollutants,   and   that   they   represent   serious   health   risks   from   air   pollution   indoors   (Salma   et   al.,   2013).   Array   of    the   factors   affecting   the   physical–chemical   characteristics   of    indoor   fine   particles   have   also   caused   a   large   deviation   in   their   properties   and;   for   that   reason,   it   seems   to   be   more   useful   to   be   aware   of    the   nature   and   relative   significance   of    the   dominant   factors   and   their   implications   in   indoor   environment   (Lee   and   Chang,   2000;   Patterson   and   Eatough,   2000;   Lee   et   al.,   2002;   Guo   et   al.,   2010;   Branis   et   al.,   2011;   Hovorka   and   Branis,   2011;   Szoboszlai   et   al.,   2011;   Salma   et   al.,   2013).   In   India,   a   large   amount   of    effort   has   been   made   to   study   the   pollution   level   in   low   income   classes   (Kulshreshtha   and   Khare,   2011;   Singh   and   Jamal,   2012).   Though,   not   much   study   has   been   done   about   the   middle–   and   high–income   class,   who   can   actually   offer   the   necessary   resource   inputs   to   stimulate   economic   growth   and   pollution   level.   This   paper   intends   to   define   and   present   the   concentration   of    fine   particles   and   their   physical–chemical   characteristics   in   the   indoor   environment   of    low–   middle–   and   high–income   group   homes   in   Agra   City.   Our   key   objectives   were:      Determination   of    PM 2.5   mass   concentration,      Characterization   of    chemical   and   morphological   composition   of    fine   particles,      Evaluation   of    PM 2.5   concentration   together   with   indoor   meteorological   variables   in   order   to   identify   the   possible   sources   of    fine   particles,   as   well   as   the   effect   of    various   indoor   activities   on   their   properties.     Singh et al.  – Atmospheric Pollution Research (APR) 353   2.   Methods   2.1.   Site   description   Agra,   the   city   of    inimitable   Taj   Mahal,   is   situated   in   Uttar   Pradesh,   the   North   Central   part   of    India   (27°10’N,   78°20’E),   approximately   200   kilometers   of    south   of    New   Delhi.   The   city   lies   in   a   semi–arid   region,   on   the   south   and   west   neighboring   to   the   Thar   Desert   of    Rajasthan   with   a   tropical   climate   and   strongly   affected   by   the   Aeolian   dust   blown   from   the   Thar   Desert.   Mathura   is   situated   towards   the   north,   and   on   the   east   it   is   bounded   by   Firozabad   District,   which   is   famous   for   its   glass   manufacturing   industries.   Four   major   national   highways   namely   NH–2,   3,   11   and   93   are   passing   all   the   way   through   the   city   and   serving   very   serious   load   of    traffic   (10 5   vehicles   per   day)   (Saini   et   al.,   2009;   ADA,   2013).   Agra   is   generally   a   commercial   city,   known   for   carpets,   leather   goods,   handicrafts,   stone   carving,   zari   zardozi,   inlay   work,   and   sweets   (petha   and   gajak).   These   are   mostly   positioned   in   the   old   mogul   city,   particularly   Rakabganj,   Lohamandi,   Tajganj,   and   Kotwali   areas.   The   large–scale   industrial   units   are   located   near   to   Kanpur–Delhi   national   highway   (NH–2),   and   in   Chatta   and   Hariparvat   areas.   Agra   City   has   about   2   009   497   total   population,   and   the   population   density   is   about   1   084   persons/km 2   (Census,   2011).   2.2.   Socioeconomic   conditions   of    the   sampled   households   Socioeconomic   status   determines   man’s   way   of    living,   type   of    house,   location   of    residence,   and   access   to   various   services   and   facilities.   Using   the   income   limits   (Census,   2011),   the   low–   middle–   and   high–income   group   homes   were   chosen   in   Agra   City   (Figure   1)   in   which   indoor   sampling   was   done.   This   includes   two   high–income   group   homes   (earning     >INR   70   000      USD   1   100   per   month)   with   commercial   areas   and   big   industries   in   the   vicinity.   Most   of    the   members   of    this   category   had   professional   degrees   and   were   engaged   in   white   collar    jobs   or   were   industrialists.   They   owned   palatial   houses   and   had   almost   all   the   modern   household   appliances   like   color   televisions,   videos,   refrigerators,   liquid   petroleum   gas,   coolers,   washing   machines,   generators,   telephones   and   vehicles.   Two   middle–income   group   homes   (earning   <INR   60   000        USD   900–1   000   per   month)   with   a   heavy   traffic   density.   The   members   of    the   medium–income   households   were   also   educated   and   some   of    them   had   professional   degrees.   They   were   employed   as    junior   engineers   and   office   workers.   Two   low   income   group   homes   made   up   of    mud   and   grasses   with   little   traffic   but   high   population   density.   The   sampled   low–income   households   belong   to   the   lower   socioeconomic   strata   (earning   <INR   5   000      USD   90–100   per   month).   The   low–income   household   members   were   poorly   educated.   Most   of    them   were   employed   as   skilled   and   unskilled   laborers.   As   household   income   decreases,   there   is   a   decrease   in   the   number   of    household   appliances,   a   decrease   in   the   level   of    education   and   a   change   in   the    job   status.   2.3.   Questionnaire   survey   In   this   study,   survey   data   were   collected   from   50   houses   out   of    which   six   houses   were   selected   in   Agra   City   for   indoor   sampling.   Questionnaires   were   made   to   fill   by   the   occupants   to   know   the   daily   indoor   activity   pattern,   along   with   the   survey   of    the   houses   to   know   the   sources   responsible   for   the   particulate   emission.   The   questionnaire   included   daily   time/activity   diary   to   know   about   the   house   characteristics   and   different   activities   such   as   cooking,   cleaning,   heating,   the   number   of    occupants,   surroundings   of    homes,   other   activities   carried   in   the   indoor   environment   of    the   homes.   The   questionnaire   survey   filled   by   the   occupants   of    the   houses   is   provided   with   the   work   as   supplementary   information   for   better   understanding   of    the   data   collected.   This   sampling   time   covered   the   activities   for   the   entire   day   inside   the   houses,   such   as   prayer   time   (burning   candles   and   incense   sticks),   cleaning,   sweeping,   making   food.   It   also   accounted   for   the   times   when   the   traffic   was   low   and   high   and   also   for   the   use   of    generators   in   case   of    power   failures   (Table   1).   Figure   1.   Site   map   of     Agra   City    showing   sampling   sites.   Singh et al.  – Atmospheric Pollution Research (APR) 354   Table   1.   General    characteristic   of    the   residential    homes   Low–Income   Group   Middle–Income   Group   High–Income   Group   Area   of    Living   Room   (m 2 )   5–8   12–15   20–25   Surfaces   (A—m 2 )   24.8–39.7   54.1–67.5   82.4–103.0   Total   volume   (V—m 3 )   11.7–18.8   29.4–36.7   60.5–75.6   A/V   (1/m)   2.1   1.8   1.3   Home   Age   (Years)   10–15   5–6   6–7   Conditions   Highly   Populated,   Less   Cemented   Area,   Use   of    Mud   Stoves,   Coal   and   Biomass   Combustion   Less   Populated,   Marble   Flooring,   L.P.G.   Stoves   Less   Populated,   Tile   Flooring,   Microwave,   Modern   and   efficient   Hobs,   Close   to   a   major   traffic   route   2.4.   Sample   collection   In   the   month   of    July   2012,   from   6   low–   middle–   and   high–income   group   homes,   a   total   of    24   indoor   samples   (4   samples   from   each   house)   of    fine   particles   were   collected   for   24   h   on   PTFE   filters   by   a   medium–volume   sampler   (model:   APM   550,   Envirotech,   New   Delhi   flow   rate:   16.6   L/min).   Grimm   31–   Channel   Portable   Aerosol   Spectrometer   model   No.1.109   was   used   for   the   monitoring   of    particulate   mass   concentration,   which   runs   at   a   flow   rate   of    1.2   L/min   ±5%   constant   with   controller   for   continuous   measurement   during   the   sampling   period.   The   instrument   was   generally   positioned   in   a   living   room   area   where   occupants   of    the   homes   spend   most   of    their   time.   Living   rooms   are   equipped   with   amenities   for   sitting,   and   can   have   room   for   a   larger   number   of    people   for   a   substantial   time   interval.   Inlet   head   was   positioned   as   close   as   possible   to   the   breathing   zone   for   the   occupants.   The   air   exchange   rate   was   measured   on   sampling   site   by   using   (YES–206)   Falcon   indoor   air   quality   monitor   from   (Young   Environment   Systems,   Inc.,   Canada).   Sampling   of    fine   particles   with   medium   volume   sampler   and   sampling   with   Grimm   aerosol   spectrometer   were   compared.   Average   fine   particle   concentrations   recorded   by   Grimm   aerosol   spectrometer   were   found   to   be   1.2–1.4   times   higher   than   medium   volume   sampler   at   all   the   sampling   sites.   It   may   be   because   of    its   sensitivity   and   no   loss   in   PM   mass   due   to   loading   and   unloading   of    the   filter   papers   which   occurs   in   other   sampler.   To   compare   the   PM 2.5   mass   concentration   data   collected   by   two   instruments   (APM   550   and   Grimm),   concentrations   sampling   was   done   simultaneously   by   placing   the   two   instruments   together   at   each   sampling   house.   We   found   that   there   is   corre ‐ lation   of    R 2 =0.872   for   PM 2.5   between   medium   volume   sampler   and   Grimm   aerosol   spectrometer.   2.5.   Gravimetric   analysis   Filter   papers   were   weighed   thrice   before   and   after   sampling   using   four   digit   balance   (Wensar   model–   MABI   20)   with   sensitivity   of    ±0.2   mg.   Before   weighing   the   samples   were   equilibrated   in   desiccators   at   20–30   °C   and   relative   humidity   of    30–40%   in   humidity   controlled   room   for   24   h.   Field   blank   filters   were   collected   to   reduce   the   gravimetric   bias   due   to   filter   handling   during   and   after   sampling.   Filters   were   handled   only   with   tweezers   coated   with   Teflon   tape   to   reduce   the   possibility   of    contamination.   PM   mass   was   determined   gravimetrically   by   subtracting   the   initial   average   mass   of    the   blank   filter   from   the   final   average   of    the   sampled   filter   dividing   by   air   volume   passed.   2.6.   Quality   control   in   monitoring   (i)   The   sampler   is   designed   to   work   at   a   constant   flow   rate   of    16.67±0.83   L/min.   Daily   flow   rate   calculations   (gas   meter   reading   /   timer   reading)   was   made   to   make   sure   that   the   fluctuation   in   flow   rate   was   within   the   range.   (ii)   Filter   in   the   wins   impactor   needs   to   be   changed   after   72   h   of    sampling   (Chow   and   Watson,   1998)   or   when   the   filter   gets   clogged   as   per   the   operator ′ s    judgment.   (iii)   Periodic   cleaning   of    the   sampler   was   done   to   make   the   sampler   dust   free   so   that   the   dust   on   the   sampler   may   not   be   counted   with   the   mass   concentration   of    the   sample.   2.7.   Sample   analysis   The   characterization   of    particles   in   PM 2.5   samples   were   performed   using   electron   scanning   microscopy   (SEM,   JEOL   Model   JSM–6390LV)   coupled   with   energy   dispersive   spectrometer   (EDS,   JEOL   Model   JED–2300)   for   determination   of    morphology   (shapes   and   sizes)   and   chemical   composition   of    airborne   particles.   SEM   is   a   method   for   high   resolution   surface   imaging.   It   uses   an   electron   beam   for   surface   imaging.   Its   advantages   over   light   microscopy   are   greater   magnification   and   much   larger   depth   of    field.   Different   elements   with   different   surface   topographies   emit   different   quantity   of    electrons   due   to   which   the   contrast   in   a   SEM   micro ‐ graph   is   representative   of    the   surface   topography   and   distribution   of    elemental   composition   on   the   surface.   Approximately   one   fourth   filter   paper   of    PTFE   filter   paper   was   cut   and   coated   with   gold.   Gold    –   coated   SEM   stubs   were   prepared   for   each   sample.   Stubs   were   gold–   coated   to   a   thickness   of    20   nm   using   a   sputter   coater   and   then   put   into   the   SEM   chamber   for   obtaining   morphol ‐ ogies   of    individual   particles   (Pipal   et   al.,   2011).   Three   images   of    one   sample   were   taken   at   a   magnification   of    x250,   x500,   x2   000   and   EDS   spectra   of    individual   particles   were   obtained   after   scanning   an   electron   beam   with   an   accelerating   voltage   of    10–15   kV.   2.8.   Statistical   analysis   Using   the   IBM   SPSS   software   version   Portable   PASW   Statistics   18   and   some   statistical   tools   were   applied   to   support   the   results.   The   continuous   fine   particle   (PM 2.5 )   concentration   data   and   other   environmental   parameters   were   initially   investigated   by   descriptive   statistics.   Further,   the   elemental   composition   of    PM 2.5 ,   the   bivariate   Pearson   correlation   was   used   to   know   the   strength   of    linear   relationship   all   the   elements.   3.   Results   and   Discussion   3.1.   Indoor   characterizations   and   PM 2.5   concentrations   The   average   mass   concentration   of    PM 2.5   in   low–income   group   homes   was   46.7   µg/m 3   (C.I.=38.1–55.5)   which   was   19.3%   higher   than   middle–income   group   homes   [39.1   µg/m 3   (C.I.=31.1–47.3)]   and   82.6%   higher   than   high–income   group   homes   [25.6   µg/m 3   (C.I.=20.9–30.2)]   (Table   2).   In   low–income   group   homes,   the   highest   average   fine   particulate   matter   (PM 2.5 )   concentration   was   recorded   in   the   evening   hours   (18:00–21:00   hours)   (18.7%   higher   than   morning   hours)   followed   by   morning   hours   (07:00–10:00   hours),   this   may   be   attributed   to   activities   like   cooking,   cleaning   and   maximum   number   of    occupants   in   the   evening   and   morning   hours   (Taneja   et   al.,   2008).   In   middle–income   group   homes,   evening   concentration   was   46.2%   higher   than   morning   hours.   In   high–income   group   homes   the   evening   concentration   was   139.5%   higher   than   morning   hours   and   211.3%   higher   than   afternoon   hours   (12:00–14:00   hours).   In   low–   middle–   and   high–income   group   homes   cooking   may   be   the   major   contributing   factor   in   variation   of    PM 2.5   concentration   in   evening   and   morning   hours     Singh et al.  – Atmospheric Pollution Research (APR) 355   (Massey   et   al.,   2009).   The   maximum   values   for   PM 2.5 ,   exceeding   the   349.8   µg/m 3   for   low–income   group   homes,   204.9   µg/m 3   for   middle–income   group   homes,   and   145.1   µg/m 3   for   high–income   group   homes.   These   results   reveal   the   existence   of    peaks,   although   with   a   low   frequency.   Its   srcin   can   be   due   to   tobacco   smoking,   wood   burning,   resuspension   of    dust   and   occupant   activities   during   the   different   times   in   a   day   (Tuckett   et   al.,   1998;   Long   et   al.,   2000;   Tucker,   2000).   3.2.   Meteorological   parameters   Meteorological   conditions   have   also   been   identified   as   one   of    the   predominant   factors   responsible   for   variation   of    PM 2.5   concen ‐ tration   (Massey   et   al.,   2012).   Along   with   the   measurement   of    particulate   matter   concentration   during   sampling   days,   the   meteo ‐ rological   parameters   were   also   monitored   and   are   given   in   Table   3.   The   average   concentrations   of    CO 2   were   584.1   ppm,   569.7   ppm   and   555.1   ppm   in   low–   middle–   and   high–income   group   homes.   The   highest   CO 2   concentration   was   recorded   in   low–income   group   homes.   This   may   be   due   to   the   use   of    solid   fuels   as   a   primary   source   of    energy.   As   this   is   one   month   study,   the   average   temperatures   were   34.5   °C   in   low–   32.1   °C   in   middle–   and   31.3   °C   in   high–income   group   homes.   The   average   relative   humidity   were   found   to   be   55.1%   in   low–   66.1%   in   middle–   69.8%   in   high–income   group   homes,   and   average   ventilation   rate   were   29.7   L/s,   33.1   L/s   and   31.9   L/s   in   low–   middle–   and   high–income   group   homes   respectively.   3.3.   Elemental   and   morphological   analysis   PM 2.5   in   low–income   group   homes.   As   shown   in   the   SEM   micro ‐ graphs   and   EDS   spectrum   of    PM 2.5   (Figure   2),   the   particles   were   irregular,   spherical,   reticular,   cluster,   and   flaky   shaped   and   C,   F   and   O–rich   particles   dominate   over   other   elements.   Apart   from   C,   F,   and   O   rich   particles,   Na,   Al,   Mg,   and   Si   rich   particles   were   also   present   in   this   size   range,   which   follow   the   trend:   C>F>O>Na>Al>   Si>Mg.   The   morphology   of    carbonaceous   particle   varies   depending   on   the   fuels,   burning   conditions   and   atmospheric   processes   (Berube   et   al.,   1999;   Posfai   and   Buseck,   2010;   Tumolva   et   al.,   2010).   In   our   study,   we   find   branched   clusters   resulting   in   spheres   of    carbon   occurring   at   high–temperature   processes   like   combus ‐ tion   (Murr   and   Bang,   2003;   Cyrys   et   al.,   2004;   Gotschi   et   al.,   2005).   In   the   low–income   group   homes   incomplete   combustion   of    fossil   and   bio–fuels   by   cooking   on   unvented   mud   stoves   and   smoking   are   the   major   source   of    carbon   and   oxygen   (Hand   et   al.,   2005;   Alexander   et   al.,   2008;   Cong   et   al.,   2009).   Nearly   spherical   particles   of    F   were   also   observed.   People   living   in   low–income   group   communities   commonly   use   coal   as   the   primary   source   of    energy.   Coal   naturally   contains   F   as   impurity   during   combustion.   Other   than   coal   combustion,   some   other   sources   may   also   contribute   to   rise   up   the   F   in   the   air,   i.e.   incense   burning,   pesticides,   insecticides,   brick   kilns,   floor   polishes,   and   some   industrialization   processes   (Huynh   et   al.,   1991;   Schauer,   2003;   Lonati   and   Giugliano,   2006;   Ikezawa   et   al.,   2011).   While   soil   also   contains   F,   and   soil   resuspension   by   the   wind   also   play   an   important   role   to   the   atmospheric   burden   of    F   in   the   form   of    soil   minerals   (Dudragne   and   Amouroux,   1998).   The   major   type   of    chemical   compound   in   the   earth’s   crust   is   composed   of    about   72%   of    the   aluminosilicate   group   in   terms   of    weight   (Van   Malderen   et   al.,   1996;   Cong   et   al.,   2009).   In   low–income   group   homes   some   aluminosilicates   were   also   identified,   which   were   made   up   of    Al–Si–O   along   with   other   elements   like   Na   and   Mg.   Si   associated   with   O,   Al   and   Na   showed   the   presence   of    clay,   mineral,   and   feldspar   particles   (Shao   et   al.,   2007).   Si–Na   particles   could   be   the   mixture   of    sea   salt   and   mineral   dust.   Mineral   particles   have   irregular   shapes,   and   they   were   mainly   derived   from   natural   sources   such   as   soil   dust,   resuspension   of    dust   from   the   road   and   some   other   anthropogenic   activities   such   as   construction   and   vehicles   (Li   et   al.,   2010a).   The   presence   of    Mg–Si   or   Mg–Al–Si   in   indoor   environment   shows   talc   like   composition   (Conner   et   al.,   2001).   Some   particles   were   skin   flakes   shaped.   Based   on   these   results,   the   observations   suggest   powders   and   cosmetics   are   also   of    one   of    the   possible   indoor   sources   of    fine   particles.   Figures   2.   SEM   micrographs   and    EDS   spectrum   of    PM 2.5  collected     from   low–income   group   homes.     Singh et al.  – Atmospheric Pollution Research (APR) 356   Table   2.   Explorative   statistical     parameters   of    indoor    concentrations    for    PM 2.5   collected     from   Grimm   PAS   1.109   in   low–    middle–    and    high–income   group   homes   Variable   Parameter   Low–Income   GroupMiddle–Income   Group   High–Income   Group   PM 2.5   (µg/m 3 )   Mean   46.7   39.2   25.6   Median   32.9   25.0   21.8   Standard   Error   4.4   4.1   2.3   Skewness   3.3   2.6   3.1   95%   Confidence   Interval   38.1–55.5   31.1–47.3   20.9–30.2   Table   3.   Measurement    of    meteorological     parameters   measured    during   the   study     period    in   low–    middle–    and    high–income   group   homes   CO 2   Temp.   RH   VR   Low–Income   Group   Homes   M   584.1   34.5   55.1   29.7   S.E.   7.8   0.2   0.9   1.9   Skew   1.7   0.5    –0.3   0.4   Min   500.1   31.1   39.0   4.2   Max   827.3   39.4   70.0   62.7   Middle–Income   Group   Homes   M   569.7   32.1   66.1   33.1   S.E.   13.7   0.2   1.4   2.1   Skew   1.1   0.6   0.2   0.3   Min   453.1   29.1   49.0   10.9   Max   838.5   39.2   81.0   66.7   High–Income   Group   Homes   M   555.1   31.3   69.8   31.9   S.E.   10.2   0.1   1.2   1.7   Skew   1.7   0.3   0.1   0.7   Min   464.1   29.8   55.1   50.4   Max   818.1   33.6   81.1   61.8   CO 2 :   Carbon   dioxide   (ppm),   Temp.:   Temperature   (  o C),   RH:   Relative   Humidity    (%),   VR:   Ventilation   Rate   (Lps),   M:   Mean,   S.E.:   Standard    Error,   Skew:   Skewness,   Min:   Minimum,   Max:   Maximum.   PM 2.5   in   middle–income   group   homes.   In   middle–income   group   homes   the   SEM   micrographs   and   EDS   spectrum   of    PM 2.5   (Figure   3)   show   the   presence   of    spheres,   cluster,   plates   and   reticular   shaped   particles   of    F>C>O>Al>Si>Na.   In   the   present   study,   we   could   spot   the   branched   clusters   resulting   from   the   interconnection   of    often   hundred   of    carbonaceous   spherules,   which   stick   together   through   mingle   of    adhesive   surface   forces   and   partial   coalescence   occurring   at   high–temperature   common   during   combustion   (Murr   and   Bang,   2003).   A   blend   of    carbonaceous   particle   and   inorganic   with   varying   amount   of    soil–related   component   like   Na,   Si,   and   Al   are   forming   complex   aggregates   were   also   observed.   During   the   study   period   incense   burning   at   the   time   of    prayer   and   heavy   use   of    insecticides   like   mosquito   repellent   spray   or   coils   show   the   presence   of    nearly   spherical   shaped   particles   of    F   in   SEM   micrographs   of    middle–income   group   homes   (Lonati   and   Giugliano,   2006;   Ikezawa   et   al.,   2011).   Silica   particles   are   generally   characterized   by   the   presence   of    Si   and   O   particles.   Silica   particles   are   tubular   in   shape.   Generally,   these   particles   are   natural   and   anthropogenic   in   srcins   (Li   et   al.,   2010b).   This   is   the   most   abundant   chemical   constituent   of    the   earth’s   crust,   cement,   bricks,   glass,   ceramics,   and   clays,   etc.;   therefore,   these   particles   also   likely   to   be   srcinated   from   building   materials.   Other   major   contributors   of    the   earth’s   crust   are   aluminosilicates.   Most   of    the   particles   are   irregular   in   shape   (Cong   et   al.,   2009).   In   middle–income   group   homes   soil   delivered   aluminosilicates   particles   were   mainly   composed   of    oxides   of    Al   and   Si   with   varying   amounts   of    Na   like   Na–feldspar   (Pachauri   et   al.,   2013).   PM 2.5   in   high–income   group   homes.   The   SEM   micrographs   and   EDS   spectrum   of    PM 2.5   (Figure   4)   indicates   that   the   particles   are   flaky,   cluster,   reticular   and   irregular   shaped   in   high–income   group   homes.   Apart   from   the   dominancy   of    F,   C   and   O   rich   particles,   Al   and   Si   were   also   observed.   The   trend   of    these   elements   was   F>C>   O>Si>Al.   Agra   is   famous   for   “Petha”   (a   delicacy   prepared   from   a   vegetable   of    the   gourd   family).   There   are   approximately   400   petha   industry   units   in   Agra   City.   The   situation   is   worst   in   the   petha   industry   area,   as   the   petha   waste   attracts   flies,   mosquitoes   and   strays   too.   In   some   areas,   the   trash   waste   was   recklessly   burnt   in   open   dump   yards   positioned   on   the   major   national   highways   of    Agra   City   (Agra   Nagar   Nigam,   2006).   High–income   group   homes   of    the   Lawyer’s   colony   and   Lajpatkunj,   Khandari,   Agra   was   located   near   to   NH–2,   hence   garbage   and   coal   burning   due   to   petha   industry   units   of    Agra   City   and   use   of    heavy   diesel   generators   may   attribute   to   increase   in   the   percentage   of    F   in   high–income   group   homes   (Webber,   2009).   SEM   micrographs   show   the   presence   of    nearly   spherical   shaped   particles   of    F.   In   addition   presence   of    F   in   high–income   group   homes   may   also   be   due   to   the   pest   control   performed   few   days   before   the   study   and   regular   floor   polishing   done   during   the   study   period   (Safai   et   al.,   2005).   People   living   in   high–income   group   homes   do   not   use   solid   fuel   for   cooking   and   heating,   they   use   better   modes   of    cooking   like   cooking   on   modern   and   efficient   hobs,   use   of    microwave   oven,   use   of    electric   chimneys,   and   better   cooking   oil,   so   C   was   not   the   major   element   found   in   high–income   group   homes.   PM 2.5   particle   also   seems   to   be   constituted   by   aluminosilicates   having   oxides   of    Al   and   Si   as   its   contents.   These   particles   probably   srcinate   from   crustal   sources   (Slezakova   et   al.,   2008).   Besides   all   these   sources   in   all   the   three   income   group   homes   (i.e.,   low–   middle–   and   high–income   group   homes)   presence   of    large   concentration   of    carbon   and   fluorine   particles   may   be   attributed   to   matrix   effect   and   coming   from   PTFE   filter   paper   (Ikezawa   et   al.,   2011).   3.4.   Correlation   matrix   By   evaluating   the   bivariate   Pearson   correlation   coefficient   for   all   the   elements   present   in   PM 2.5   collected   in   low–   middle–   and   high–income   group   homes,   the   degree   of    linear   relationship   can   be   measured   between   two   variables.   The   r    value  ≥ 0.5   shows   the   strong   correlation.   Table   4   shows   the   correlation   coefficients   between   particulate   matter   and   elements   in   low–   middle–   and   high–income   group   homes.   Highly   significant   correlation   ( r  >0.9)   was   observed   between   Al–Si,   Mg–Al.   Moreover,   the   positive   corre ‐ lation   of    F,   Mg   and   Al   with   O;   Al   and   Si   with   Na   and   Na   with   PM 2.5   were   also   found   in   low–income   group   homes   ( r  >0.6–0.8).   In   middle–income   group   homes   the   highest   correlation   ( r  >0.9)   was   observed   between   Na   with   Al,   Si   with   Na   and   Al   and   O   with   Na,   Al   and   Si.   O,   Na,   Al   show   positive   correlation   with   C   ( r  >0.5–0.6)   and   Si   shows   positive   correlation   with   F   ( r  >0.8)   in   middle–income   group   homes.   Highly   significant   correlation   ( r  >0.9)   was   shown   between   Al–O,   Si–O   and   Al–Si   in   high–income   group   homes.   PM 2.5   concen ‐ tration   shows   positive   correlation   only   with   C   in   middle–income   group   ( r  >0.5)   and   high–income   group   homes   ( r  >0.6).  
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