# RECORD aa81dc840f8ab6c12b272e830117706e34b5a89a # TITLE: Fresh air in the city: the impact of air pollution on the pricing of real estate # YEAR: 2024.0 VENUE: Environmental science and pollution research international DOI: 10.1007/s11356-023-31668-1 # AUTHORS: Oktawia Miłuch; K. Kopczewska # PAGES: 24 CANDIDATE TABLE PAGES (1-based): [14] # ABSTRACT: This study investigates the impact of ambient air pollution on housing prices in Warsaw, Poland, by examining spatial dependencies. The high concentration of particulate matter (PM_10, PM_2.5 and PM_1) is expected to reduce real estate values. Using a hedonic model with approximately 15,000 observations and a spatial error model, we did not find evidence of this impact. Standard and premium housing submarkets differ in price determinants, but both are insensitive to environmental issues. This could be explained by the lack of comprehensive intra-urban historical information on air pollution, which limits investors’ rationality and their ability to properly value real estate based on environmental issues. Additionally, measurement and aggregation issues, along with low pollution variability within the city, may contribute to the insignificance of this information in real estate sales prices. Our empirical research confirms a strong link between air pollution and weather conditions within the city, where low temperatures and low-speed southern winds worsen contamination levels, while high temperatures and westerly winds improve air quality. Furthermore, we find that incorporating pollution data using PM yearly mean concentration works better in modelling than the PCA-reduced air pollution index. ===== PAGE 1 (score 20, numeric-paren 0, table-words 1, var-words 18) ===== Vol:.(1234567890) Environmental Science and Pollution Research (2024) 31:7604–7627 https://doi.org/10.1007/s11356-023-31668-1 1 3 RESEARCH ARTICLE Fresh air in the city: the impact of air pollution on the pricing of real estate Oktawia Miłuch1 · Katarzyna Kopczewska1  Received: 8 September 2023 / Accepted: 18 December 2023 / Published online: 2 January 2024 © The Author(s) 2024 Abstract This study investigates the impact of ambient air pollution on housing prices in Warsaw, Poland, by examining spatial dependencies. The high concentration of particulate matter ­(PM10, ­PM2.5 and ­PM1) is expected to reduce real estate values. Using a hedonic model with approximately 15,000 observations and a spatial error model, we did not find evidence of this impact. Standard and premium housing submarkets differ in price determinants, but both are insensitive to environmental issues. This could be explained by the lack of comprehensive intra-urban historical information on air pollution, which limits investors’ rationality and their ability to properly value real estate based on environmental issues. Additionally, measure- ment and aggregation issues, along with low pollution variability within the city, may contribute to the insignificance of this information in real estate sales prices. Our empirical research confirms a strong link between air pollution and weather conditions within the city, where low temperatures and low-speed southern winds worsen contamination levels, while high temperatures and westerly winds improve air quality. Furthermore, we find that incorporating pollution data using PM yearly mean concentration works better in modelling than the PCA-reduced air pollution index. Keywords  Air pollution · Spatial econometrics · Real estate valuation JEL Classification  Q53 · R31 · C21 · O18 Introduction Despite the extensive research on air quality, the real estate value created by clean air in an urban environment is still unknown as the empirical studies are far from conclusive. There are three reasons for this. The first one, theoretical, lies in rationality assump- tion and the interaction of many factors impacting housing prices. Environmental characteristics are not market goods; thus to estimate the value of air quality, the most common approach in economic studies is to link it with real estate value from a given area. In a pioneering work, Ridker and Henning (1967) assumed that air quality was one of the variables explaining a potential home buyer’s utility func- tion. With the hedonic price theory development, the air pollution assessment was mainly based on housing prices. They assumed that when controlling structural attributes, the observed differences in real estate prices exhibit the site characteristics value, such as environmental amenities (see meta-analysis by Smith and Huang 1995). However, such a perspective implicitly assumes that investors1 can con- sciously choose (and valuate) at a given moment in time all of the features of real estate. This is mostly true in relation to the size, location, or interior features such as balcony, etc., but difficult in the case of air pollution. This is because the current measurements of air quality are usually well known, but the long-term historical and prospective information about the environmental conditions of a given location is Responsible Editor: Eyup Dogan * Katarzyna Kopczewska kkopczewska@wne.uw.edu.pl Oktawia Miłuch oktawiamiluch28@gmail.com 1 Faculty of Economic Sciences, University of Warsaw, Ul. Dluga 44/50, 00‑241 Warsaw, Poland 1  In our research, we use the word investors to refer to people will- ing to buy a property for their own use as well as developers building houses for sale. The two groups share the same goal — to maximise their utility/profits; therefore, clean air in the neighbourhood is advan- tageous for both. In the case of individuals, the theory explaining this approach is presented in the literature review. ===== PAGE 14 (score 81, numeric-paren 52, table-words 4, var-words 21) ===== 7617 Environmental Science and Pollution Research (2024) 31:7604–7627 1 3 line. As one could expect, properties situated closer to the city centre have a higher sqm price than those further apart, regardless of their total value. This relation is reflected by the significant and positive value of the coefficient specify- ing distance to the city centre; nevertheless, the effect is more visible for exclusive apartments, which is probably due to their concentration in central areas. Lastly, the impact of transit time by public transport varies between standard and luxury flats. The former ben- efits from a shorter commuting time, while the effect is the Table 3   Spatial error models for submarkets *p < 0.1; **p < 0.05; ***p < 0.01 Dependent variable: price of a square meter of a flat Standard flats Exclusive flats (1) (2) Internal features of the flat Surface area (sqm)  − 36.59*** 10.36***  Year of construction 29.02*** 36.24*** Number of rooms  − 270.41***  − 858.58*** Floor 21.19**  − 99.00 Floors in building  − 49.85***  − 78.01 Market type (secondary) 1120.63*** 1533.71*** Air conditioning 709.32*** 949.89** Garage 477.42***   − 181.82 Elevator 310.65*** 638.83* Balcony  − 221.80***  − 363.79 Garden 45.04 755.41 Terrace 99.67 777.06** Districts of Warsaw Bialoleka  − 943.59***  861.48 Bielany 735.38***  5973.90** Mokotow 1193.84*** 2934.15 Ochota 515.90**  − 123.84 Praga Polnoc 7.53 939.74 Praga Poludnie  − 289.42 3864.10 Rembertow  − 1547.48*** 2496.67 Srodmiescie 3224.36*** 6497.90*** Targowek  − 817.08***  − 1879.58 Ursus  − 914.99*** 3565.19 Ursynow 1651.40*** 5955.07** Wawer 95.25 7658.26** Wesola 1205.13*** 3483.14 Wilanow 2876.65*** 6459.78*** Wlochy  − 455.91** 1701.08 Wola 1162.64*** 2233.34 Zoliborz 2216.74*** 3782.91* Relative location Distance to city centre  − 366.55***  − 1641.29*** Transit time  − 14.63** 99.83**  Air quality Mean ­PM10  − 60.07***  − 89.05 Mean ­PM2.5 92.58**  − 421.30 Mean ­PM1  − 12.31 811.13** Constant  − 41,112.88***  − 49,346.83*** λ 0.485*** 0.382*** Observations 13,539 1399 Log Likelihood  − 122,031.70  − 13,918.14 σ2 3,815,348.00 24,991,628.00 Akaike Inf. Crit 244,137.50 27,906.28 Wald test (df = 1) 1939.54*** 111.83*** LR test (df = 1) 1545.56*** 92.71*** ===== PAGE 15 (score 27, numeric-paren 0, table-words 3, var-words 21) ===== 7618 Environmental Science and Pollution Research (2024) 31:7604–7627 1 3 opposite considering the latter. Little is known about the impact of real transit time using public transport. Most of the papers examine the influence of transportation infrastructure in the neighbourhood on real estate value, which may not fully reflect the real possibilities of using public transport. However, in our case, the opposite signs in the two models might be explained by homebuyers’ needs. While individu- als with lower budgets seeking to purchase a flat may use public transport on an everyday basis, people who can afford luxury apartments may ignore this factor. The environmental variables include the yearly mean concentration of particular matters: ­PM10, ­PM2.5 and ­PM1. The statistically significant coefficients of ­PM10 and ­PM2.5 in the model related to standard apartments indicate that their prices are associated with air pollution levels. However, while ­PM10 negatively impacts the house value (by 0.5%), according to our estimates, ­PM2.5 increases the sqm price (by 0.7%). Similar conclusions can be drawn for ­PM1 in the case of exclusive apartments (by 3.9%). The insignificant coefficients of ­PM10 and ­PM2.5 for luxury properties, as well as the estimates of ­PM1 for standard properties, evidence a lack of association between air pollution and housing prices. The results may be unexpected; however, there is some speculation about why this occurs. Fernández-Avilés et al. 2012 and Tang and Niemeier (2021), using differ- ent pollutants and techniques to measure air quality, have drawn similar conclusions on the influence of air pollution on real estate value. Among studies which have published insignificant results relating to air pollution impacting house prices, some authors have acknowledged that the irrelevant effect of environmental coefficients is because the given pol- lutant does not tend to exceed air quality standards (Kim et al. 2003). Examining the literature, the results of other research suggest that when, in general, ambient air pollu- tion is relatively low, the pollutants’ influence on property value is more likely to be insignificant. However, compared to other metropolitan cities in Europe, air quality in Warsaw is quite poor. Moreover, as explained in the section con- cerning air quality data analysis, during winter in the worst scenario, the number of days with exceeded norms of ­PM10 and ­PM2.5 exceeded the level of 20. Altogether, neither the insignificant coefficient of the ­PM1 in the model describ- ing standard properties nor estimates of ­PM10 and ­PM2.5 for luxury flats are, as suggested by other researchers, are related to superior air quality. The significant and negative impact of ­PM10 on the prices of standard flats, as suggested by Lu and Lee (2022), may be explained by the fact that particulate matter with the largest diameters is more percep- tible than other pollutants included in the study below. The positive sign displayed by the ­PM2.5 coefficient in the stand- ard real estate model, as well as ­PM1 increasing the value of exclusive properties, constitute counter-intuitive results. According to Fernández-Avilés et al. 2012, these unexpected conclusions may arise from the difference between the sub- jective environmental perception of homebuyers and objec- tive conditions. The rational consumer makes the decision which maximises utility based on all available information. However, the environmental condition of a given property may be out of the scope of a potential homebuyer. Unlike long-term air pollution data, information on the accessibil- ity of public services or transportation is readily available. Therefore, in the Polish context of high demand for real estate, purchasing a house might not depend on the air qual- ity in the area but on affordability and facilities available in the vicinity. Based on the analysis of the spatial distribu- tion of ­PM10, ­PM2.5 and ­PM1, it happens to be that, in most cases, the most polluted districts have the most developed commercial services, communication and leisure facilities, etc. For instance, Bielany and Śródmiescie in both models positively impact the sqm price of a dwelling. The former is the central district of Warsaw, while the latter is a former industrial area with a steel mill, which is today an attractive place to live. As the conclusions from the literature about the impact of air quality on housing prices are ambiguous, it seems that in general, nations around the globe differ in their attitude toward clean air value. In a significant number of the papers based on data from Asia, air pollution decreases real estate prices, while outcomes of studies referring to other parts of the world are not as straightforward, which is also the case in Warsaw. As one can observe, according to p-values, not all vari- ables in both models are significant. The main purpose of the research was to question whether air quality impacts real estate prices; thus, its foremost role is explanatory. As writ- ten by Shmueli (2010), “trimming potentially theoretically meaningful variables is not advisable unless one is quite certain that the coefficient for the variable is near zero, that the variable is inconsequential, and that trimming will not introduce misspecification error “. Hence, some insignificant variables, important from the theoretical point of view, are included in the final models. Policy implications The analysis of air quality data has highlighted the need for improvements in Warsaw’s air pollution policy as the ambi- ent air quality over the analysed time was unsatisfactory. Compared to other European cities, the capital of Poland experiences some of the most severe air pollution, mostly from fuel combustion from the residential sector and trans- port, which leads to comparatively high social costs per cap- ita. Therefore, municipal actions towards those two sources of pollution to improve air quality should be reconsidered. In the case of pollution from transportation, one of the most common approaches widely applied worldwide is the restric- tion of access to the city centre for the most polluting cars.