Current Science

Open Access Open Access  Restricted Access Subscription Access

Assessment of Particulate Matter in a University Campus during Spring Season


Affiliations
1 Department of Civil Engineering, Indian Institute of Technology (BHU), Varanasi 221 005, India
 

We aim to study particulate matter (PM) exposure at university campuses. The campus of Banaras Hindu University in the city of Varanasi was taken as a case study. PM concentrations were recorded using a portable aerosol monitor during peak hours for 45 days (February–March 2021) at several intersections inside the campus. PM exposure was substantially higher during the weekdays than on weekends. Due to higher humidity conditions, PM2.5 (fine particles) exposure was higher during February than during March. March witnessed an increased PM10 (coarse particles) exposure because of higher atmospheric temperature, which caused greater resuspension of the coarse particles. PM concentration inside the campus was affected by traffic volume, the number of intersections, and the presence of speed breakers. PM2.5 (54 µg m–3) was lower than the limits set by the National Ambient Air Quality Standards in India (60 µg m–3). In contrast, PM10 (115 µg m–3 ) exceeded the standard limits (100 µg m–3). Both PM2.5 and PM10 surpassed the daily limit (PM2.5: 15 µg m–3 and PM10: 45 µg m–3 ) set by the World Health Organization (WHO). Fine particulate matter (PM2.5) is more hazardous to health than coarse particulate matter (PM10). Consequently, the air quality on the campus was moderate as per the national norms.

Keywords

Air Pollution, Human Exposure, Particulate Matter, Spring Season, University Campus.
User
Notifications
Font Size

  • WHO, Ambient (outdoor) air pollution: key facts. World Health Organization, Geneva, Switzerland, 2022, pp. 1–9.

  • Mohanraj, R. and Azeez, P. A., Health effects of airborne particulate matter and the Indian scenario. Curr. Sci., 2004, 87, 741–748.

  • Gaur, M., Bhandari, K. and Shukla, A., Monitoring of total volatile organic compounds and particulate matter in an indoor environment. Curr. Sci., 2018, 115, 1787.

  • CPCB, National air quality standards, Central Pollution Control Board, New Delhi, India. Government Gazette, 2009, vol. 534, pp. 6–9.

  • CPCB, National air quality index, Central Pollution Control Board, New Delhi, India, 2014, pp. 1–44.

  • The Texas Guide to Accepted Mobile Source Emission Reduction Strategies, Texas Transportation Institute, 2007.

  • Li, X., Jin, L. and Kan, H., Air pollution: a global problem needs local fixes. Nature, 2019, 570, 437–439.

  • Li, H. et al., Particulate matter exposure and stress hormone levels: a randomized, double-blind, crossover trial of air purification. Circulation, 2017, 136, 618–627.

  • Kuo, C. Y., Hsieh, C. Y., Hu, C. W., Chen, S. C. and Yang, H. J., PM10 concentration in relation to clinic visits for anxiety disorders: a population-based study of a high river- dust episode region in Taiwan. Air Qual. Atmos. Health, 2018, 11, 221–227.

  • Azhdari, S. S. et al., Associations of combined short-term exposures to ambient PM2.5 air pollution and noise annoyance on mental health disorders: a panel study of healthy college students in Tehran. Air Qual. Atmos. Health, 2022, 15, 1497–1505.

  • Raz-Maman, C., Carel, R. S., Borochov-Greenberg, N., Zack, O. and Portnov, B. A., The exposure assessment period to air pollutants which affects lung function: analysis of recent studies and an explanatory model. Air Qual. Atmos. Health, 2022, 15, 393–402.

  • Zhang, Y. et al., Short-term effects of fine particulate matter and temperature on lung function among healthy college students in Wuhan, China. Int. J. Environ. Res. Public Health, 2015, 12, 7777–7793.

  • Jin, L. et al., The short-term effects of air pollutants on pneumonia hospital admissions in Lanzhou, China, 2014–2019: evidence of ecological time-series study. Air Qual. Atmos. Health, 2022, 2014–2019.

  • Li, C., Elemental composition of residential indoor PM10 in the urban atmosphere of Taipei. Atmos. Environ., 1994, 28, 3139–3144.

  • Osimobi, O. J. and Nwankwo, C. A., Assessment of particulate matter concentrations in a university campus in Nigeria. J. Environ. Stud., 2018, 4, 1–4.

  • Majd, E. et al., Indoor air quality in inner-city schools and its associations with building characteristics and environmental factors. Environ. Res., 2019, 170, 83–91.

  • Tung, T. C. W., Chao, C. Y. H., Burnett, J., Pang, S. W. and Lee, R. Y. M., A territory wide survey on indoor particulate level in Hong Kong. Build. Environ., 1998, 34, 213–220.

  • Adgate, J. L., Ramachandran, G., Pratt, G. C., Waller, L. A. and Sexton, K., Spatial and temporal variability in outdoor, indoor and personal PM2.5 exposure. Atmos. Environ., 2002, 36, 3255–3265.

  • Chao, C. Y. and Wong, K. K., Residential indoor PM10 and PM2.5 in Hong Kong and the elemental composition. Atmos. Environ., 2002, 36, 265–277.

  • Ramachandran, G., Adgate, J. L., Pratt, G. C. and Sexton, K., Characterizing indoor and outdoor 15 minute average PM2.5 concentrations in urban neighborhoods. Aerosol Sci. Technol., 2003, 37, 33–45.

  • Diapouli, E., Chaloulakou, A. and Spyrellis, N., Indoor and outdoor particulate matter concentrations at schools in the Athens area. Indoor Built Environ., 2007, 16, 55–61.

  • Pekey, B. et al., Indoor/outdoor concentrations and elemental composition of PM10/PM2.5 in urban/industrial areas of Kocaeli City, Turkey. Indoor Air, 2010, 20, 112–125.

  • Massey, D., Kulshrestha, A., Masih, J. and Taneja, A., Seasonal trends of PM10, PM5.0, PM2.5 and PM1.0 in indoor and outdoor environments of residential homes located in North-Central India. Build. Environ., 2012, 47, 223–231.

  • Elbayoumi, M. et al., Multivariate methods for indoor PM10 and PM2.5 modelling in naturally ventilated schools buildings. Atmos. Environ., 2014, 94, 11–21.

  • Pant, P., Habib, G., Marshall, J. D. and Peltier, R. E., PM2.5 exposure in highly polluted cities: a case study from New Delhi, India. Environ. Res., 2017, 156, 167–174.

  • WHO, Ambient (outdoor) air quality database, by country and city. World Health Organization, Geneva, Switzerland, 2022.

  • Pandey, J., Agrawal, M., Khanam, N., Narayan, D. and Rao, D. N., Air pollutant concentrations in Varanasi, India. Atmos. Environ. Part B, 1992, 26, 91–98.

  • Murari, V., Kumar, M., Mhawish, A., Barman, S. C. and Banerjee, T., Airborne particulate in Varanasi over middle Indo-Gangetic Plain: variation in particulate types and meteorological influences. Environ. Monit. Assess., 2017, 189.

  • Chen, M., Dai, F., Yang, B. and Zhu, S., Effects of neighborhood green space on PM2.5 mitigation: evidence from five megacities in China. Build. Environ., 2019, 156, 33–45.

  • Coutts, A. M., White, E. C., Tapper, N. J., Beringer, J. and Livesley, S. J., Temperature and human thermal comfort effects of street trees across three contrasting street canyon environments. Theor. Appl. Climatol., 2016, 124, 55–68.

  • Kumar, P. and Goel, A., Concentration dynamics of coarse and fine particulate matter at and around signalised traffic intersections. Environ. Sci. Process. Impacts, 2016, 18, 1220–1235.

  • Polednik, B., COVID-19 lockdown and particle exposure of road users. J. Transp. Health, 2021, 22, 101233.

  • Han, J., Liu, X., Chen, D. and Jiang, M., Influence of relative humidity on real-time measurements of particulate matter concentration via light scattering. J. Aerosol Sci., 2020, 139, 105462.

  • Laulainen, N. S., Summary of conclusions and recommendations from a visibility science workshop no. PNL-8606. Pacific North-west Lab., Richland, WA (United States), 1993.

  • Apte, J. S. et al., Concentrations of fine, ultrafine, and black carbon particles in auto-rickshaws in New Delhi, India. Atmos. Environ., 2011, 45, 4470–4480.

  • Goel, R., Gani, S., Guttikunda, S. K., Wilson, D. and Tiwari, G., On-road PM2.5 pollution exposure in multiple transport microenvironments in Delhi. Atmos. Environ., 2015, 123, 129–138.

  • Kim, T. Y. and Lee, S. H., Combustion and emission characteristics of wood pyrolysis oil–butanol blended fuels in a DI diesel engine. Int. J. Automat. Technol., 2015, 16, 903–912.

  • Panko, J. M., Hitchcock, K. M., Fuller, G. W. and Green, D., Evaluation of tire wear contribution to PM2.5 in urban environments. Atmosphere (Basel), 2019, 10, 1–14.

  • Sinha, D. and Dammani, J., Seasonal variations in mass concentrations of PM10 and PM2.5 at traffic intersection and residential sites in Raipur city. Res. J. Chem. Environ., 2018, 22, 25–31.

  • Huang, H. et al., Characterization of short- and medium-chain chlorinated paraffins in outdoor/indoor PM10/PM2.5/PM1.0 in Beijing, China. Environ. Pollut., 2017, 225, 674–680.

  • Wang, Z., Zhong, S., He, H. di, Peng, Z. R. and Cai, M., Fine-scale variations in PM2.5 and black carbon concentrations and corresponding influential factors at an urban road intersection. Build. Environ., 2018, 141, 215–225.

  • Coskuner, G., Jassim, M. S. and Munir, S., Characterizing temporal variability of PM2.5/PM10 ratio and its relationship with meteorological parameters in Bahrain. Environ. Forensics, 2018, 19, 315–326.

  • Yuval, F. B. and Broday, D. M., The impact of a forced reduction in traffic volumes on urban air pollution. Atmos. Environ., 2008, 42, 428–440.

  • Gopalaswami, R., A study on effects of weather, vehicular traffic and other sources of particulate air pollution on the city of Delhi for the year 2015. J. Environ. Pollut. Hum. Health, 2016, 4, 24–41.

  • Lonati, G., Giugliano, M. and Cernuschi, S., The role of traffic emissions from weekends’ and weekdays’ fine PM data in Milan. Atmos. Environ., 2006, 40, 5998–6011.

  • Song, J., Qiu, Z., Ren, G. and Li, X., Prediction of pedestrian exposure to traffic particulate matters (PMs) at urban signalized intersection. Sustain. Cities Soc., 2020, 60, 102153.

  • Sulaiman, N., Abdullah, M. and Chieu, P. L. P., Concentration and composition of PM10 in outdoor and indoor air in industrial area of Balakong Selangor, Malaysia. Sains Malays., 2005, 34, 43–47.

  • Cichowicz, R. and Dobrzański, M., Spatial analysis (measurements at heights of 10 m and 20 m above ground level) of the concentrations of particulate matter (PM10, PM2.5 and PM1.0) and gaseous pollutants (H2S) on the university campus: a case study. Atmosphere (Basel), 2021, 12, 1–14.


Abstract Views: 91

PDF Views: 51




  • Assessment of Particulate Matter in a University Campus during Spring Season

Abstract Views: 91  |  PDF Views: 51

Authors

Saroj Kanta Behera
Department of Civil Engineering, Indian Institute of Technology (BHU), Varanasi 221 005, India
Abhisek Mudgal
Department of Civil Engineering, Indian Institute of Technology (BHU), Varanasi 221 005, India

Abstract


We aim to study particulate matter (PM) exposure at university campuses. The campus of Banaras Hindu University in the city of Varanasi was taken as a case study. PM concentrations were recorded using a portable aerosol monitor during peak hours for 45 days (February–March 2021) at several intersections inside the campus. PM exposure was substantially higher during the weekdays than on weekends. Due to higher humidity conditions, PM2.5 (fine particles) exposure was higher during February than during March. March witnessed an increased PM10 (coarse particles) exposure because of higher atmospheric temperature, which caused greater resuspension of the coarse particles. PM concentration inside the campus was affected by traffic volume, the number of intersections, and the presence of speed breakers. PM2.5 (54 µg m–3) was lower than the limits set by the National Ambient Air Quality Standards in India (60 µg m–3). In contrast, PM10 (115 µg m–3 ) exceeded the standard limits (100 µg m–3). Both PM2.5 and PM10 surpassed the daily limit (PM2.5: 15 µg m–3 and PM10: 45 µg m–3 ) set by the World Health Organization (WHO). Fine particulate matter (PM2.5) is more hazardous to health than coarse particulate matter (PM10). Consequently, the air quality on the campus was moderate as per the national norms.

Keywords


Air Pollution, Human Exposure, Particulate Matter, Spring Season, University Campus.

References





DOI: https://doi.org/10.18520/cs%2Fv125%2Fi1%2F26-33