Abstract: Common knowledge states that prolonged exposure to air pollution negatively affects health. In the era of growing interest in air quality and widespread access to spatial data, there are increasingly more solutions in the field of maps and portals illustrating the concentration of air pollutants. They vary in detail, content, and analytical capabilities. Currently, there is no standardized cadastre of emissions and air quality that universally provides residents with information about air quality in selected places around the world. Therefore, the objective of this paper is to propose a model solution for the construction of the Emission and Air Quality Cadastre (EMAC). Business analysis methods were used in the research. To assess the macro-environment, i.e., external factors influencing the construction and development of EMAC, PESTEL analysis (identifies factors in six key areas: Political, Economic, Socio-cultural, Technological, Ecological, and Legal) and scenario analysis of environmental conditions were used. To assess existing map portals, the functionalities of which should appear in EMAC, the competitive profile assessment method was used. The implementation of the EMAC can contribute to increasing air quality awareness among residents of their area, encourage the implementation of actions to promote a healthy lifestyle, and help authorities take effective measures to protect the urban environment.
B I B L I O G R A F I AAgenda, 2015. Cf, O. D. D. S., 2015
Agenda, 2015. Cf, O. D. D. S.
Transforming our world: the 2030 Agenda for sustainable development
United Nations: New York, NY, USA
https://documents-dds-ny.un.org/doc/UNDOC/GEN/N15/291/89/PDF/N1529189.pdf?OpenElement (2015), Accessed 1st Oct 2023
Bao et al., 2023
F. Bao, Z. Zhao, L. Dong
Government land control approach, industrial agglomeration, and urban air quality: analysis based on spatial spillovers and threshold effects
J. Clean. Prod., 427 (2023), Article 139176, 10.1016/j.jclepro.2023.139176
BC Air Quality, 2023
BC Air Quality
https://www.env.gov.bc.ca/epd/bcairquality/readings/find-stations-map-NO2.html (2023), Accessed 20th Aug 2023
Beelen et al., 2009
R. Beelen, G. Hoek, E. Pebesma, D. Vienneau, K. de Hoogh, D.J. Briggs
Mapping of background air pollution at a fine spatial scale across the European Union
Sci. Total Environ., 407 (6) (2009), pp. 1852-1867, 10.1016/j.scitotenv.2008.11.048
Bhattacharjee and Dey, 2015
D. Bhattacharjee, M. Dey
Competitive profile matrix: a theoretical review
Abac J., 35 (2) (2015), pp. 61-70
http://www.assumptionjournal.au.edu/index.php/abacjournal/article/view/3022
Bieda and Cienciała, 2021
A. Bieda, A. Cienciała
Towards a renewable energy source cadastre - a review of examples from around the world
Energies, 14 (23) (2021), p. 8095, 10.3390/en14238095
Boddy, 2012
C. Boddy
The nominal group technique: an aid to brainstorming ideas in research
Qual. Mark. Res. Int. J., 15 (1) (2012), pp. 6-18, 10.1108/13522751211191964
Brody et al., 2004
S.D. Brody, B.M. Peck, W.E. Highfield
Examining localized patterns of air quality perception in Texas: a spatial and statistical analysis
Risk Anal., 24 (6) (2004), pp. 1561-1574, 10.1111/j.0272-4332.2004.00550
Brzozowska and Mazela, 2024
A. Brzozowska, K. Mazela
Spatial analyses as support for road real estate management processes – case study on the paid parking zone in krakow
GIS Odyssey J., 4 (2) (2024), pp. 27-50, 10.57599/gisoj.2024.4.2.27
Budkowski, 2023
S. Budkowski
The use of geodata in the process of the ventilation of the city of krakow
Geomat. Environ. Eng., 17 (4) (2023), 10.7494/geom.2023.17.4.53
Cadle et al., 2010
J. Cadle, D. Paul, P. Turner
Business Analysis Techniques: 72 Essential Tools for Success. BCS, the Chartered Institute
(2010)
Chief Inspectorate of Environmental Protection, 2023
Chief inspectorate of environmental protection
https://powietrze.gios.gov.pl/ (2023), Accessed 1st Aug 2023
Da Cunha et al., 2023
L. Da Cunha, M.S. Ferreira, R. Cerqueira, A.A. Namen
The effect of long-term climatic variability on wild mammal populations in a tropical forest hotspot: a business intelligence framework
Ecol. Inform., 73 (2023), Article 101924, 10.1016/j.ecoinf.2022.101924
Dawidowicz et al., 2020
A. Dawidowicz, M. Kulawiak, E. Zysk, K. Kocur-Bera
System architecture of an INSPIRE-compliant green cadastre system for the EU Member State of Poland
Remote. Sens. Appl. Soc. Environ., 20 (2020), Article 100362, 10.1016/j.rsase.2020.100362
Espinosa et al., 2021
R. Espinosa, J. Palma, F. Jiménez, J. Kamińska, G. Sciavicco, E. Lucena-Sánchez
A time series forecasting based multi-criteria methodology for air quality prediction
Appl. Soft Comput., 113 (2021), Article 107850, 10.1016/j.asoc.2021.107850
Goyal et al., 2022
P. Goyal, S. Gulia, S.K. Goyal
Development of strategic air quality improvement framework for urban hotspots
J. Clean. Prod., 380 (2022), Article 134886, 10.1016/j.jclepro.2022.134886
Hasenfratz et al., 2015
D. Hasenfratz, O. Saukh, Ch Walser, Ch Hueglin, M. Fierz, T. Arn, J. Beutel, L. Thiele
Deriving high-resolution urban air pollution maps using mobile sensor nodes
Pervasive Mob. Comput., 16 (2015), pp. 268-285, 10.1016/j.pmcj.2014.11.008
Janaszek et al., 2024
A. Janaszek, A.F.d. Silva, N. Jurišević, M. Kanuchova, Ľ. Kozáková, R. Kowalik
The assessment of sewage sludge utilization in closed-loop economy from an environmental perspective
Water, 16 (3) (2024), p. 383, 10.3390/w16030383
Jerrett et al., 2005
M. Jerrett, A. Arain, P. Kanaroglou, B. Beckerman, D. Potoglou, T. Sahsuvaroglu, J. Morrison, C. Giovis
A review and evaluation of intraurban air pollution exposure models
Exposure Sci. Environ. Epidemiol., 15 (2005), pp. 185-204, 10.1038/sj.jea.7500388
Kalogianni et al., 2021
E. Kalogianni, K. Janečka, M. Kalantari, E. Dimopoulou, J. Bydłosz, A. Radulović, P. Van Oosterom
Methodology for the development of LADM country profiles
Land Use Policy, 105 (2021), Article 105380, 10.1016/j.landusepol.2021.105380
Kshirsagar and Shah, 2022
A. Kshirsagar, M. Shah
Anatomization of air quality prediction using neural networks, regression and hybrid models
J. Clean. Prod., 369 (2022), Article 133383, 10.1016/j.jclepro.2022.133383
Li et al., 2014
J.J. Li, A. Jutzeler, B. Faltings
Estimating urban ultrafine particle distributions with Gaussian process models
S. Winter, C. Rizos (Eds.), Research@ Locate, vol. 14 (2014), pp. 145-153
https://users.cecs.anu.edu.au/∼jasonli/papers/2014-LiJutzelerFaltings-Locate.pdf
Li et al., 2023
Q. Li, T. Qian, J. Wang, R. Long, H. Chen, C. Sun
Social “win-win” promotion of green housing under the four-subject evolutionary game
Energy Econ., 127 (2023), Article 107117, 10.1016/j.eneco.2023.107117
London air quality map, 2023
London air quality map
https://www.london.gov.uk/what-we-do/environment/pollution-and-air-quality/london-air-quality-map (2023), Accessed 13th Aug 2023
Madsen, 2011
B. Madsen
Statistics for Non-statisticians
Springer, Heidelberg (2011)
Malik et al., 2022
S. Malik, M.Z. Arshad, Z. Amjad, A. Bokhari
An empirical estimation of determining factors influencing public willingness to pay for better air quality
J. Clean. Prod., 372 (2022), Article 133574, 10.1016/j.jclepro.2022.133574
Marans, 2003
R.W. Marans
Understanding environmental quality through quality of life studies: the 2001 DAS and its use of subjective and objective indicators
Landsc. Urban Plann., 65 (1–2) (2003), pp. 73-83, 10.1016/S0169-2046(02)00239-6
Matejicek, 2005
L. Matejicek
Spatial modelling of air pollution in urban areas with GIS: a case study on integrated database development
Adv. Geosci., 4 (2005), pp. 63-68, 10.5194/adgeo-4-63-2005
Nadj et al., 2020
M. Nadj, A. Maedche, C. Schieder
The effect of interactive analytical dashboard features on situation awareness and task performance
Decis. Support Syst., 135 (2020), Article 113322, 10.1016/j.dss.2020.113322
Nowak et al., 2020
M. Nowak, A. Dawidowicz, R. Źróbek, M.D.T. Tuyet
Identification of development determinants of green information systems for urban areas – Polish case study
Acta Sci. Pol. Adm. Locorum., 19 (2020), pp. 45-60, 10.31648/aspal.4456
NSW Government Australia, 2023
NSW Government Australia
https://www.airquality.nsw.gov.au/concentration-data (2023), Accessed 22nd Aug 2023
Oleniacz et al., 2023
R. Oleniacz, M. Bogacki, M. Rzeszutek, P. Bździuch
Air quality improvement in urban street canyons: an assessment of the effects of selected traffic management strategies using OSPM model
Appl. Sci., 13 (11) (2023), p. 6431, 10.3390/app13116431
Osička and Černoch, 2022
J. Osička, F. Černoch
European energy politics after Ukraine: the road ahead
Energy Res. Social Sci., 91 (2022), Article 102757, 10.1016/j.erss.2022.102757
Pattinson et al., 2014
W. Pattinson, I. Longley, S. Kingham
Using mobile monitoring to visualise diurnal variation of traffic pollutants across two near-highway neighbourhoods
Atmos. Environ., 94 (2014), pp. 782-792, 10.1016/j.atmosenv.2014.06.007
Paul et al., 2014
D. Paul, J. Cadle, D. Yeates (Eds.), Business Analysis. BCS, the Chartered Institute for IT (2014)
Payne and Moore, 2022
G.T. Payne, C. Moore
External corporate governance mechanisms: linking forces to behaviors
Oxford Research Encyclopedia of Business and Management (2022)
Santana et al., 2021
P. Santana, A. Almeida, P. Mariano, C. Correia, V. Martins, S.M. Almeida
Air quality mapping and visualisation: an affordable solution based on a vehicle-mounted sensor network
J. Clean. Prod., 315 (2021), Article 128194, 10.1016/j.jclepro.2021.128194
Schmitz et al., 2019
O. Schmitz, R. Beelen, M. Strak, et al.
High resolution annual average air pollution concentration maps for The Netherlands
Sci. Data, 6 (1) (2019), Article 190035, 10.1038/sdata.2019.35
Shahzad, 2021
F. Shahzad
Data redundancy management in connected environments. Networking and internet architecture [cs.NI]
Université de Pau et des Pays de l'Adour, 2021. English, NNT : 2021PAUU3034 (2021)
Showkat and Parveen, 2017
N. Showkat, H. Parveen
In-depth Interview. Quadrant-I (E-text)
(2017), pp. 1-9
Skrobacki et al., 2019
Z. Skrobacki, L.E. Dabek, P. Lagowski
Modelling and forecasting of SO2 concentration in atmospheric air–A case study of the city of krakow
IOP Conf. Ser. Mater. Sci. Eng., 471 (10) (2019), Article 102057, 10.1088/1757-899X/471/10/102057
IOP Publishing
Sohel et al., 2014
S.M. Sohel, A.M.A. Rahman, M.A. Uddin
Competitive profile matrix (CPM) as a competitors' analysis tool: a theoretical perspective
Int. J. Human Potent. Dev., 3 (3) (2014), pp. 40-47, 10.1007/s11301-019-00158-5
Sun and Min, 2024
C. Sun, J. Min
Dynamic trends and regional differences of economic effects of ultra-high-voltage transmission projects
Energy Econ., 138 (2024), Article 107871, 10.1016/j.eneco.2024.107871
Sun et al., 2024
C. Sun, M. Xu, B. Wang
Deep learning: spatiotemporal impact of digital economy on energy productivity
Renew. Sustain. Energy Rev., 199 (2024), Article 114501, 10.1016/j.rser.2024.114501
Szopińska et al., 2022
K. Szopińska, A. Cienciała, A. Bieda, J. Kwiecień, Ł. Kulesza, P. Parzych
Verification of the perception of the local community concerning air quality using ADMS-roads modeling
Int. J. Environ. Res. Publ. Health, 19 (17) (2022), Article 10908, 10.3390/ijerph191710908
Targino et al., 2016
A.C. Targino, M.D. Gibson, P. Krecl, M.V.C. Rodrigues, M.M. Dos Santos, M. de Paula Corrêa
Hotspots of black carbon and PM2.5 in an urban area and relationships to traffic characteristics
Environ. Pollut., 218 (2016), pp. 475-486, 10.1016/j.envpol.2016.07.027
UN DESA, 2023
UN DESA
The Sustainable Development Goals Report 2023: Special Edition - July 2023, UN DESA. © UN DESA, New York, USA (2023)
https://unstats.un.org/sdgs/report/2023/, Accessed 1st Oct 2003
Walter et al., 2022
L. Walter, N.M. Denter, J. Kebel
A review on digitalization trends in patent information databases and interrogation tools
World Pat. Inf., 69 (2022), Article 102107, 10.1016/j.wpi.2022.102107
Wang et al., 2019
S. Wang, Y. Zhong, E. Wang
An integrated GIS platform architecture for spatiotemporal big data
Future Gener. Comput. Syst., 94 (2019), pp. 160-172, 10.1016/j.future.2018.10.034
Warchoł et al., 2024
A. Warchoł, K. Pęzioł, M. Baścik
Energy-saving geospatial data storage—LiDAR point cloud compression
Energies, 17 (24) (2024), p. 6413, 10.3390/en17246413
WHO, 2021
WHO
World health organization global air quality guidelines: particulate matter (PM2.5 and PM10)
Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide, WHO, Geneva, Switzerland (2021)
2021
https://apps.who.int/iris/handle/10665/345329, Accessed 5th Oct 2023
World Air Quality Index Sitemap, 2023
World Air Quality Index Sitemap
https://aqicn.org/links (2023), Accessed 10th Aug 2023
Google Scholar
Xiaoyan Zhang et al., 2022
X. Xiaoyan Zhang, L. Han, H. Wei, X. Tan, W. Zhou, W. Li, Y. Qian
Linking urbanization and air quality together: a review and a perspective on the future sustainable urban development
J. Clean. Prod., 346 (2022), Article 130988, 10.1016/j.jclepro.2022.130988
Yin et al., 2023
G. Yin, Z. Huang, L. Yang, E. Ben-Elia, L. Xu, B. Scheuer, Y. Liu
How to quantify the travel ratio of urban public transport at a high spatial resolution? A novel computational framework with geospatial big data
Int. J. Appl. Earth Obs. Geoinf., 118 (2023), Article 103245, 10.1016/j.jag.2023.103245
Yin et al., 2021
J. Yin, J. Dong, N.A. Hamm, Z. Li, J. Wang, H. Xing, P. Fu
Integrating remote sensing and geospatial big data for urban land use mapping: a review
Int. J. Appl. Earth Obs. Geoinf., 103 (2021), Article 102514, 10.1016/j.jag.2021.102514
Zender-Świercz et al., 2019
E. Zender-Świercz, M. Telejko, M. Starzomska, A. Łubek
The microbiology contaminants and microclimate parameters in the nursery building
Int. J. Environ. Sci. Technol., 16 (2019), pp. 6699-6704, 10.1007/s13762-019-02284-9
Zheng et al., 2013
Y. Zheng, F. Liu, H.P. Hsieh
U-Air: when urban air quality inference meets big data
Proceedings of the 19th Int. Conference on Knowledge Discovery and Data Mining (SIGKDD), ACM (2013), pp. 1436-1444, 10.1145/2487575.2488188
Zheng et al., 2014
Y. Zheng, T. Liu, Y. Wang, Y. Zhu, E. Chang
Diagnosing New York City's noises with ubiquitous data
Proceedings of the 16th International Conference on Ubiquitous Computing (UbiComp), ACM (2014), pp. 715-725, 10.1145/2632048.2632102
Zysk et al., 2020
E. Zysk, A. Dawidowicz, M. Nowak, M. Figurska, S. Źróbek, R. Źróbek, J. Burandt
Organizational aspects of the concept of a green cadastre for rural areas
Land Use Policy, 91 (2020), Article 104373, 10.1016/j.landusepol.2019.104373 
Pełny tekst 
DOI