The impact of air quality and meteorological conditions including visibility on tourism: the case of Zakopane (Poland)

• Autorzy: Anioł Ewa , Szeląg Bartosz , Kula Dorota , Ignar Stefan , Majewski Grzegorz

Identyfikatory

DOI

10.5604/01.3001.0016.1800

Warianty tytułu

PL

Wpływ jakości powietrza i warunków meteorologicznych, w tym widoczności, na turystykę: przypadek Zakopanego (Polska)

• Języki publikacji: EN

Abstrakty

EN

The aim of the study was to investigate the impact of air pollution and meteorological conditions on visibility in Zakopane, the most popular tourist destination in southern Poland. To achieve this objective, correlation analysis, multiple linear regression analysis and random forests were used. In addition, an analysis was performed of the occurrence of episodes of elevated pollutant concentrations and basic statistical characteristics of visibility, meteorological conditions and air pollution. Meteorological parameters (air temperature, relative humidity, total precipitation, wind speed, atmospheric pressure and visibility) and concentrations of air pollutants; particulate matter (PM₁₀) and gaseous pollutants (SO₂, NO₂) were recorded from 2010 to 2019. The data came from a monitoring station located in Zakopane-MpZakopaSien. It was found that high concentrations of air pollutants SO₂ and PM₁₀, along with relative humidity (RH), were the most important parameters affecting visibility limitation in Zakopane. Concentrations and indirectly also visibility were largely influenced by increased automobile traffic due to tourist activity, as well as emissions from apartment/building heating (combustion of various fuels). Understanding the relationship between air pollutant concentrations, meteorological conditions and visibility is a prerequisite and the basis for the scientific formulation of air pollution prevention and control policies in places where monitoring is particularly important.

PL

Celem pracy było zbadanie wpływu zanieczyszczeń powietrza i warunków meteorologicznych na widoczność w Zakopanem, najpopularniejszej miejscowości turystycznej w południowej Polsce. Do realizacji tego celu wykorzystano analizę korelacji, analizę regresji liniowej wielokrotnej oraz lasy losowe. Ponadto przeprowadzono analizę występowania epizodów podwyższonych stężeń zanieczyszczeń oraz podstawowych charakterystyk statystycznych widoczności, warunków meteorologicznych i zanieczyszczenia powietrza. Parametry meteorologiczne (temperatura powietrza, wilgotność względna, suma opadów, prędkość wiatru, ciśnienie atmosferyczne i widzialność) oraz stężenia zanieczyszczeń powietrza; pyłu zawieszonego (PM₁₀) i zanieczyszczeń gazowych (SO₂, NO₂) rejestrowano od 2010 do 2019 r. Dane pochodziły ze stacji monitoringu zlokalizowanej w Zakopanem – Mp Zakopane. Wykazano, że wysokie stężenia zanieczyszczeń powietrza SO₂ i PM₁₀ wraz z wilgotnością względną (RH) były najważniejszymi parametrami wpływającymi na ograniczenie widzialności w Zakopanem. Na stężenia i pośrednio na widoczność duży wpływ miał wzmożony ruch samochodowy związany z działalnością turystyczną, a także emisja z ogrzewania mieszkań/budynków (spalanie różnych paliw). Zrozumienie zależności pomiędzy stężeniami zanieczyszczeń powietrza, warunkami meteorologicznymi i widocznością jest warunkiem wstępnym i podstawą do naukowego formułowania polityki zapobiegania i kontroli zanieczyszczeń powietrza w miejscach, gdzie monitoring jest szczególnie ważny.

Słowa kluczowe

EN

visibility; air pollution; meteorological parameters; tourism

PL

widoczność; zanieczyszczenie powietrza; parametry meteorologiczne; turystyka

• Wydawca: Szkoła Główna Służby Pożarniczej
• Czasopismo: Zeszyty Naukowe SGSP / Szkoła Główna Służby Pożarniczej
• Rocznik: 2022
• Tom: Nr 84
• Strony: 31--53
• Opis fizyczny: Bibliogr. 70 poz., rys., tab.

Twórcy

autor

Anioł Ewa

• Warsaw University of Life Sciences

• https://orcid.org/0000-0002-5903-0592

autor

Szeląg Bartosz

• Kielce University of Technology

• https://orcid.org/0000-0002-0559-5475

autor

Kula Dorota

• Warsaw University of Life Sciences

• https://orcid.org/0000-0002-7445-2822

autor

Ignar Stefan

• Warsaw University of Life Sciences

• https://orcid.org/0000-0002-5080-8695

autor

Majewski Grzegorz

• Warsaw University of Life Sciences

• https://orcid.org/0000-0002-0122-1409

Bibliografia

• [1] Łapko A., Strulak-Wójcikiewicz R., Panasiuk A., Źródła informacji o zanieczyszczeniach powietrza jako narzędzie planowania wyjazdów turystycznych, 2020.
• [2] Majewski G., Szeląg B., Mach T., Rogula-Kozłowska W., Anioł E., Bihałowicz J., Dmochowska A., Bihałowicz J.S., Predicting the number of days with visibility in a specific range in Warsaw (Poland) based on meteorological and air quality data, “Frontiers in Environmental Science” 2021, 9, 623094.
• [3] Seinfeld J.H., Pandis S.N., From air pollution to climate change, “Atmospheric Chemistry and Physics” 1998, 1326.
• [4] Watson J.G., Visibility: Science and regulation, “Journal of the Air & Waste Management Association” 2002, 52, 628–713.
• [5] Anaman K.A., Looi C.N., Economic impact of haze-related air pollution on the tourism industry in Brunei Darussalam, “Economic Analysis and Policy” 2000, 30, 133–144.
• [6] Brimblecombe P., Visibility Driven Perception and Regulation of Air Pollution in Hong Kong, 1968–2020, “Environments” 2021, 8, 51.
• [7] Zhou X., Santana Jimenez Y., Pérez Rodríguez J.V., Hernández J.M., Air pollution and tourism demand: A case study of Beijing, China, “International Journal of Tourism Research” 2019, 21, 747–757.
• [8] Chen C.-M., Lin Y.-L., Hsu C.-L., Does air pollution drive away tourists? A case study of the Sun Moon Lake National Scenic Area, Taiwan, “Transportation Research Part D: Transport and Environment” 2017, 53, 398–402.
• [9] Guindi M.N., Flaherty G.T., Byrne M., Every breath you take: how does air pollution affect the international traveller?, “Journal of Travel Medicine” 2018, 25, tay021.
• [10] Becken S., Jin X., Zhang C., Gao J., Urban air pollution in China: Destination image and risk perceptions, “Journal of Sustainable Tourism” 2017, 25, 130–147.
• [11] Rataj M., Holewa-Rataj J., Analiza zmian jakości powietrza Małopolski w latach 2012– 2020, „Nafta-Gaz” 2020, 76.
• [12] Anioł E., Suder J., Bihałowicz J.S., Majewski G., The Quality of Air in Polish Health Resorts with an Emphasis on Health on the Effects of Benzo(a)pyrene in 2015–2019, “Climate” 2021, 9, 74.
• [13] McKercher B., Shoval N., Park E., Kahani A., The [limited] impact of weather on tourist behavior in an urban destination, “Journal of Travel Research” 2015, 54, 442–455.
• [14] Gładka A., Rymaszewska J., Zatoński T., Impact of air pollution on depression and suicide, “Int J Occup Med Environ Health” 2018, 31, 711–721.
• [15] Jhun I., Coull B.A., Schwartz J., Hubbell B., Koutrakis P., The impact of weather changes on air quality and health in the United States in 1994–2012, “Environmental Research Letters” 2015, 10, 084009.
• [16] Poole J.A., Barnes C.S., Demain J.G., Bernstein J.A., Padukudru M.A., Sheehan W.J., Fogelbach G.G., Wedner J., Codina R., Levetin E., Impact of weather and climate change with indoor and outdoor air quality in asthma: A Work Group Report of the AAAAI Environmental Exposure and Respiratory Health Committee, “Journal of Allergy and Clinical Immunology” 2019, 143, 1702–1710.
• [17] Environment M.o., REGULATION OF THE MINISTER OF ENVIRONMENT of 24 August 2012 on the levels of certain substances in the air.
• [18] Myers R.H., Myers R.H., Classical and modern regression with applications; Duxbury press Belmont, CA 1990; Volume 2.
• [19] Breiman L., Random forests, “Machine Learning” 2001, 45, 5–32.
• [20] Lai C., Reinders M.J., Wessels L., Random subspace method for multivariate feature selection, “Pattern Recognition Letters” 2006, 27, 1067–1076.
• [21] Shawabkeh A., Al-Beqain F., Redan A., Salem M., Benzene Air Pollution Monitoring Model using ANN and SVM. In Proceedings of the 2018 Fifth HCT Information Technology Trends (ITT), 2018, pp. 197–204.
• [22] James G., Witten D., Hastie T., Tibshirani R., Statistical learning. In “An introduction to statistical learning”, Springer: 2021, pp. 15–57.
• [23] Zhang C., Liu C., Zhang X., Almpanidis G., An up-to-date comparison of state-of-the- -art classification algorithms, “Expert Systems with Applications” 2017, 82, 128–150.
• [24] Szeląg B., Modelowanie matematyczne, optymalizacja i sterowanie pracą przepływowych oczyszczalni ścieków, “Badania Systemowe” 2019, 76.
• [25] Brokamp C., Jandarov R., Hossain M., Ryan P., Predicting daily urban fine particulate matter concentrations using a random forest model, “Environmental Science & Technology” 2018, 52, 4173–4179.
• [26] Huang K., Xiao Q., Meng X., Geng G., Wang Y., Lyapustin A., Gu D., Liu Y., Predicting monthly high-resolution PM2.5 concentrations with random forest model in the North China Plain, “Environmental Pollution” 2018, 242, 675–683.
• [27] Grange S.K., Carslaw D.C., Using meteorological normalisation to detect interventions in air quality time series, “Science of the Total Environment” 2019, 653, 578–588.
• [28] Pucer J.F., Štrumbelj E., Impact of changes in climate on air pollution in Slovenia between 2002 and 2017, “Environmental Pollution” 2018, 242, 398–406.
• [29] Kumar D., Evolving Differential evolution method with random forest for prediction of Air Pollution, “Procedia computer science” 2018, 132, 824–833.
• [30] Yi H., Xiong Q., Zou Q., Xu R., Wang K., Gao M., A novel random forest and its application on classification of air quality, In Proceedings of the 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI), 2019; pp. 35–38.
• [31] Kusiak A., Zeng Y., Zhang Z., Modelling and analysis of pumps in a wastewater treatment plant: A data-mining approach, “Engineering Applications of Artificial Intelligence” 2013, 26(7), 1643–1651.
• [32] Jacob D.J., Winner D.A., Effect of climate change on air quality, “Atmospheric Environment” 2009, 43, 51–63.
• [33] Druet P., Wiśniewski P., Foehn wind as a factor affecting the air quality in the town of Zakopane, 2020.
• [34] Kaewrat J., Janta R., Health risk assessment of residents in a tourist city: A case study of nakhon si thammarat province, “Walailak Journal of Science and Technology (WJST)” 2021, 18, 11510 (11512 pages) –11510 (11512 pages).
• [35] Kayes I., Shahriar S.A., Hasan K., Akhter M., Kabir M., Salam M., The relationships between meteorological parameters and air pollutants in an urban environment, “Global Journal of Environmental Science and Management” 2019, 5, 265–278.
• [36] Li R., Wang Z., Cui L., Fu H., Zhang L., Kong L., Chen W., Chen J., Air pollution characteristics in China during 2015–2016: Spatiotemporal variations and key meteorological factors, “Science of the Total Environment” 2019, 648, 902–915.
• [37] Majewski G., Rogula-Kozlowska W., Rozbicka K., Rogula-Kopiec P., Mathews B., Brandyk A., Concentration, chemical composition and origin of PM1: Results from the first long-term measurement campaign in Warsaw (Poland), “Aerosol and Air Quality Research” 2018, 18, 636–654.
• [38] Rehan M., Munir S., Analysis and Modeling of Air Pollution in Extreme Meteorological Conditions: A Case Study of Jeddah, the Kingdom of Saudi Arabia, “Toxics” 2022, 10, 376.
• [39] Krakow, P.I.f.E.P.i. Report on the state of the environment in the małopolskie voivodship in 2010, 2011.
• [40] Majewski G., Szeląg B., Białek A., Stachura M., Wodecka B., Anioł E., Wdowiak T., Brandyk A., Rogula-Kozłowska W., Łagód G., Relationship between Visibility, Air Pollution Index and Annual Mortality Rate in Association with the Occurrence of Rainfall- —A Probabilistic Approach. “Energies” 2021, 14, 8397.
• [41] Liu Y., Zhou Y., Lu J., Exploring the relationship between air pollution and meteorological conditions in China under environmental governance. Scientific reports 2020, 10, 1–11.
• [42] Fu X., Wang X., Hu Q., Li G., Ding X., Zhang Y., He Q., Liu T., Zhang Z., Yu Q., Changes in visibility with PM2.5 composition and relative humidity at a background site in the Pearl River Delta region, “Journal of Environmental Sciences” 2016, 40, 10–19.
• [43] Liu F., Tan Q., Jiang X., Yang F., Jiang W., Effects of relative humidity and PM2.5 chemical compositions on visibility impairment in Chengdu, China, “Journal of Environmental Sciences” 2019, 86, 15–23.
• [44] Wang X., Zhang R., Yu W., The effects of PM2. 5 concentrations and relative humidity on atmospheric visibility in Beijing, “Journal of Geophysical Research: Atmospheres” 2019, 124, 2235–2259.
• [45] Lo W.L., Zhu M., Fu H., Meteorology visibility estimation by using multi-support vector regression method. “Journal of Advances in Information Technology” 2020, 11, 40–47.
• [46] Liu X., Zhang Y., Cheng Y., Hu M., Han T., Aerosol hygroscopicity and its impact on atmospheric visibility and radiative forcing in Guangzhou during the 2006 PRIDE-PRD campaign, “Atmospheric Environment” 2012, 60, 59–67.
• [47] Yan P., Pan X., Tang J., Zhou X., Zhang R., Zeng L., Hygroscopic growth of aerosol scattering coefficient: A comparative analysis between urban and suburban sites at cold in Beijing, “Particuology” 2009, 7, 52–60.
• [48] Deng J., Wang T., Jiang Z., Xie M., Zhang R., Huang X., Zhu J., Characterization of visibility and its affecting factors over Nanjing, China, “Atmospheric Research” 2011, 101, 681–691.
• [49] Fang G., Yang J., Chen Y., Zammit C., Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China, “Hydrology and Earth System Sciences” 2015, 19, 2547–2559.
• [50] Environment M.o., Regulation of the Minister of Environment of October 8, 2019, amending the Regulation on levels of certain substances in the air. 2019.
• [51] Łukaszczyk Z., Węgiel tak, smog nie – świadomość i odpowiedzialność, “Systemy Wspomagania w Inżynierii Produkcji” 2018, 7.
• [52] Ośródka L., Ośródka K., Święch-Skiba J., Smog zimowy w Górnośląskim Okręgu Przemysłowym jako jeden ze skutków antropogenicznych zmian klimatu lokalnego, 1999.
• [53] Wielgosiński G., Czerwińska J., Smog episodes in Poland, “Atmosphere” 2020, 11, 277.
• [54] Majewski G., Rogula-Kozłowska W., Czechowski P.O., Badyda A., Brandyk A., The impact of selected parameters on visibility: First results from a long-term campaign in Warsaw, Poland, “Atmosphere” 2015, 6, 1154–1174.
• [55] Maji K.J., Dikshit A.K., Deshpande A., Disability-adjusted life years and economic cost assessment of the health effects related to PM2.5 and PM10 pollution in Mumbai and Delhi, in India from 1991 to 2015, “Environmental Science and Pollution Research” 2017, 24, 4709–4730.
• [56] Zhao P., Zhang X., Xu X., Zhao X., Long-term visibility trends and characteristics in the region of Beijing, Tianjin, and Hebei, China, “Atmospheric Research” 2011, 101, 711–718.
• [57] Clancy L., Goodman P., Sinclair H., Dockery D.W., Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study, “The Lancet” 2002, 360, 1210–1214.
• [58] Kim Y.J., Kim K.W., Kim S.D., Lee B.K., Han J.S., Fine particulate matter characteristics and its impact on visibility impairment at two urban sites in Korea: Seoul and Incheon, “Atmospheric Environment” 2006, 40, 593–605.
• [59] Chen Y., Xie S.-d., Long-term trends and characteristics of visibility in two megacities in southwest China: Chengdu and Chongqing, “Journal of the Air & Waste Management Association” 2013, 63, 1058–1069.
• [60] Fu G., Xu W., Yang R., Li J., Zhao C., The distribution and trends of fog and haze in the North China Plain over the past 30 years, “Atmospheric Chemistry and Physics” 2014, 14, 11949–11958.
• [61] Singh A., Avis W.R., Pope F.D., Visibility as a proxy for air quality in East Africa, “Environmental Research Letters” 2020, 15, 084002.
• [62] Li Y., Lau A., Wong A., Fung J., Decomposition of the wind and nonwind effects on observed year‐to‐year air quality variation, “Journal of Geophysical Research: Atmospheres” 2014, 119, 6207–6220.
• [63] Singh A., Bloss W.J., Pope F.D., 60 years of UK visibility measurements: impact of meteorology and atmospheric pollutants on visibility, “Atmospheric Chemistry and Physics” 2017, 17, 2085–2101.
• [64] Tsai Y.I., Kuo S.-C., Lee W.-J., Chen C.-L., Chen P.-T., Long-term visibility trends in one highly urbanized, one highly industrialized and two rural areas of Taiwan, “Science of the Total Environment” 2007, 382, 324–341.
• [65] Fu Q., Zhuang G., Wang J., Xu C., Huang K., Li J., ... & Streets D.G., Mechanism of formation of the heaviest pollution episode ever recorded in the Yangtze River Delta, China, “Atmospheric Environment” 2008, 42(9), 2023–2036.
• [66] Kim B.-Y., Cha J.W., Chang K.-H., Lee C., Visibility Prediction over South Korea Based on Random Forest, “Atmosphere” 2021, 12, 552.
• [67] Sekula P., Ustrnul Z., Bokwa A., Bochenek B., Zimnoch M., Random Forests Assessment of the Role of Atmospheric Circulation in PM10 in an Urban Area with Complex Topography, “Sustainability” 2022, 14, 3388.
• [68] Anioł E., Majewski G., Long-term trends in visibility and its characteristics in selected regions of Poland, “Scientific Review Engineering and Environmental Sciences” 2019, 2019, 594–609.
• [69] Lizak M., Moszczyńska N., Musmanow M., Prawne instrumenty ochrony powietrza, Problematyka nauk przyrodniczych i technicznych – Vol. 3, 50.
• [70] Jęczmyk A., Uglis J., Kasprzak K., Zanieczyszczenie powietrza a turystyka, 2019.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu „Społeczna odpowiedzialność nauki” - moduł: Popularyzacja nauki i promocja sportu (2022-2023).