Impact of simulation-based traffic noise on rent prices

Kuehnel, Nico; Moeckel, Rolf

doi:10.1016/j.trd.2019.11.020

Cited by 27 publications

(14 citation statements)

References 22 publications

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“…e real estate market would then react to the lower demand of noisy dwellings and reduce their prices. In a previous study, the relationship between the simulated noise immission values and their impact on residential rent prices has been confirmed for this modeling suite using hedonic pricing (Kuehnel and Moeckel 2020). It was shown that dwellings with an L DEN level between 55 dB(A) and 65 dB(A) are rented for 5.8% less.…”

Section: Modeling Suitesupporting

confidence: 59%

“…In this study, the integrated land use/ transport modeling suite FABILUT (flexible, agent-based integrated land use/transport, Kuehnel et al 2020;Ziemke et al 2020) is used to implement the environmental feedback. It consists of the land use model SILO (Simple, Integrated Land-use Orchestrator, Moeckel 2016) and the transport simulation model MATSim (Multi-Agent Transport Simulation, Horni et al 2016).…”

Section: Modeling Suitementioning

confidence: 99%

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Traffic noise feedback in agent-based Integrated Land-Use/Transport Models

Kuehnel

Ziemke

Moeckel

2021

JTLU

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Road traffic is a common source of negative environmental externalities such as noise and air pollution. While existing transport models are capable of accurately representing environmental stressors of road traffic, this is less true for integrated land-use/transport models. So-called land-use-transport-environment models aim to integrate environmental impacts. However, the environmental implications are often analyzed as an output of the model only, even though research suggests that the environment itself can have an impact on land use. The few existing models that actually introduce a feedback between land-use and environment fall back on aggregated zonal values. This paper presents a proof of concept for an integrated, microscopic and agent-based approach for a feedback loop between transport-related noise emissions and land-use. The results show that the microscopic link between the submodels is operational and fine-grained analysis by different types of agents is possible. It is shown that high-income households react differently to noise exposure when compared low-income households. The presented approach opens new possibilities for analyzing and understanding noise abatement policies as well as issues of environmental equity. The methodology can be transferred to include air pollutant emissions in the future.

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Section: Modeling Suitesupporting

confidence: 59%

Section: Modeling Suitementioning

confidence: 99%

Traffic noise feedback in agent-based Integrated Land-Use/Transport Models

Kuehnel

Ziemke

Moeckel

2021

JTLU

Self Cite

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“…The impact of traffic networks and their components on real estate prices has been studied extensively by many authors, and the reported results confirm the present findings. Noise influences the real estate market, in particular the apartment market [22,23,[37][38][39][40][41][42][43]. Buyers search for apartments in quiet areas that are located far from major sources of noise.…”

Section: Discussionmentioning

confidence: 99%

The Influence of Traffic Noise on Apartment Prices on the Example of a European Urban Agglomeration

Szczepańska

Senetra

Wasilewicz-Pszczółkowska

2020

Sustainability

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Traffic noise is one of the key determinants of apartment prices. The real estate market is highly sensitive to adverse environmental factors, which explains significant variations in apartment prices. The aim of this study was to identify the correlations between traffic noise levels and the prices of apartments traded on a local real estate market. The study analyzed three residential districts in the city of Olsztyn in north-eastern Poland. The database covered 5259 transactions concluded in 2005–2018. The collected data were standardized in terms of technical and functional parameters, and noise was the key factor differentiating the evaluated property. The relationships between the explained variable (apartment price) and the explanatory variable (traffic noise) were determined by linear correlation analysis. A negative correlation was noted, which confirms that a building’s location relative to the road network and, consequently, the level of traffic noise, is one of the factors that play a role in the potential buyers’ choice of property. The results of the study also indicate that the impact of traffic noise on the decisions made by real estate buyers continued to decrease in the analyzed period. Infrastructure projects in the city (construction of tramway lines and a ring road) have visibly reversed the previously observed trends and have decreased the strength of the above correlations in the evaluated residential districts. The values of the correlation coefficient were stabilized below the level noted in earlier stages of the analysis after the completion of the major infrastructure projects.

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“…The functional link between rental prices and noise levels in the city of Munich (Germany) was determined with the implementation of the hedonic price regression model in the studies of Kuehnel and Moeckel [45]. In particular, the output indicated a rental price discount equal to 0.4% per dB(A), on average.…”

Section: Reference Literaturementioning

confidence: 99%

Economic Evaluation of the Indoor Environmental Quality of Buildings: The Noise Pollution Effects on Housing Prices in the City of Bari (Italy)

et al. 2021

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Among environmental factors, noise represents one of the most relevant determinants on human health and on the urban quality level and, consequently, on real estate values. Thus, the noise pollution issue plays a significant role in public urban policies aimed at increasing the acoustic comfort level and creating more sustainable and comfortable cities. The real estate market is highly sensitive to noise factor and the residential prices can be strongly influenced by a high acoustic pollution rate. The present research aims to analyze the functional relationships between noise pollution and selling prices in four municipal areas of the city of Bari (Southern Italy). For each area, a study sample constituted by two hundred residential properties sold in 2017–2019 was detected for the identification of the main influential factors on prices and the investigation of the contribution of noise on them. The implementation of an econometric technique was used to obtain four different models (one for each municipal area of the city of Bari) able to explain the specific impact of noise pollution level on selling prices. From the comparison of the results obtained for each area, the outputs confirm the expected phenomena in terms of a decrease of noise component influence on residential prices from the central area to the peripheral. For the suburban area of the city of Bari, the model obtained does not include the noise pollution factor, showing a lower (scarce) importance of the environmental factor among the buyer and seller bargaining phases.

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Impact of simulation-based traffic noise on rent prices

Cited by 27 publications

References 22 publications

Traffic noise feedback in agent-based Integrated Land-Use/Transport Models

Traffic noise feedback in agent-based Integrated Land-Use/Transport Models

The Influence of Traffic Noise on Apartment Prices on the Example of a European Urban Agglomeration

Economic Evaluation of the Indoor Environmental Quality of Buildings: The Noise Pollution Effects on Housing Prices in the City of Bari (Italy)

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