Loss of Value in House Properties due to Air Pollution in Map Ta Phut Industrial Area of Thailand

Boonyanam, Nararuk

doi:10.35762/aer.2016.38.3.1

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…Although HPM has been applied in some real estate studies in Thailand, the focus is not on flood risks. They aim to assess the change in property prices because of public transportation systems such as the subway (Vichiensan et al, 2011;Chalermpong, 2007;Malaitham et al, 2020), pollution (Boonyanam, 2016;Rinchumphu, 2019) and local public goods (Rinchumphu et al, 2020;Suwanrada and Wagener, 2006). In addition, Aksorntueng and Sittikul (2006) use HPM to construct a housing price index, and Tochaiwat et al (2021) examine the factors that affect the prices of used condominiums.…”

Section: Literature Reviewmentioning

confidence: 99%

Flood hazards and housing prices: a spatial regression analysis for Hat Yai, Songkhla, Thailand

Chongwilaikasaem

Chalermyanont

2022

IJHMA

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Purpose Global warming exacerbates sea level rise and extreme weather events that cause severe flooding, resulting in lost productivity and property damage. To reduce the impact of flooding, residents are avoiding purchasing homes in high-risk areas. There are numerous studies on the relationship between flood hazards and housing prices in developed countries, but few in developing countries. Therefore, this study aims to investigate the relationship between flood hazards and housing prices in Hat Yai, Songkhla, Thailand. Design/methodology/approach This study uses spatial-lag, spatial error and spatial autoregressive lag and error (SARAR) models to analyze the effect of flood risk on property prices. The main analysis examines the degree of flood risk and housing rental prices from our survey of 380 residences. To test the robustness of the results, the authors examine a different data set of the same samples by using the official property valuation from the Ministry of Finance and the flood risk estimated by the Southern Natural Disaster Research Center. Findings The SARAR model was chosen for this study because of the occurrence of spatial dependence in both dependent variable and the error term. The authors find that flood risk has a negative impact on property prices in Hat Yai, which is consistent with both models. Originality/value This study is one of the first to use spatial econometrics to analyze the impact of flood risk on property prices in Thailand. The results of this study are valuable to policymakers for benefit assessment in cost–benefit analysis of flood risk avoidance or reduction strategies and to the insurance market for pricing flood risk insurance.

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Section: Literature Reviewmentioning

confidence: 99%

Flood hazards and housing prices: a spatial regression analysis for Hat Yai, Songkhla, Thailand

Chongwilaikasaem

Chalermyanont

2022

IJHMA

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Integrated assessment of inhalation health risk and economic benefit of improving ambient targeted VOCs in Petrochemical industrial area

Malakan,

Thepanondh,

Keawboonchu

et al. 2024

Air Qual Atmos Health

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The Maptaphut industrial area, one of the largest petrochemical complexes in Thailand, is the major cause of the various air pollutants. The larger concern is that a significant volume of air pollution is emitted and that air quality management needs to be improved. This is in part due to a lack of deeper understanding of how anthropogenic emissions are emitted from different sources in this area— especially volatile organic compounds (VOCs). Moreover, it has complicated relationship results of air pollution, disease mechanisms, and health effects. As a result, its available data can only give a rough indication of them. These factors are often assumed to be associated with economic consequences, but assessing the health-related economic losses caused by air pollution remains limited in many ways.Four targeted VOCs were analyzed, including benzene, 1,3-butadiene, 1,2-dichloroethane, and vinyl chloride from industrial and non-industrial sources, namely stacks, flares, storage tanks, wastewater treatment plants, transportation and marketing, fugitive losses, slurry/open equipment/vessel, and on-road mobile emissions. Source apportionment can be conducted using emissions inventory (EI) to establish pollution source databases, the dispersion model, and then imported on the risk model by determining receptors. The AERMOD dispersion model coupled with the IRAP-h view model was used to predict the spatial distribution of the ground-level concentration and analyze the inhalation health risk covering cancer and non-cancer risks— as well as the prioritization of pollutants.The risk assessment results indicated that the highest risk occurred most from 1,3-butadiene for cancer and chronic non-cancer risks contributed to fugitive sources, about 83% and 94%, and most benzenes for acute non-cancer risk contributed to on-road mobile sources, at about 56%.Consequently, the benzene classified as the most important priority depending on its risk results, comprehensive epidemiological studies, and discharge volumes.With the economic benefits assessment, BenMAP-CE was further utilized to estimate the health impacts and economic value of multiple scenarios to facilitate decision-making for benzene reduction. Overall, the 10% rollback policy for benzene concentration, monetized value of about 13.13 billion US dollars for all mortalities, gave the best practical scenario for the most economically viable option based on the B/C (benefit/cost) ratio results in Maptaphut. Ultimately, policymakers need to take additional measures to improve air quality and reduce health impacts while also considering economic benefits, especially benzene reduction.

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The Effect of Air Pollution on Real-Estate Price in Tehran

Bahadori¹,

Hoseini²

2022

JPBUD

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This paper investigates the effect of air pollution on real-estate price in Tehran for the period (2013-14) and (2018-19). By combining microdata of real-estate transactions for more than 50,000 units that are traded multiple times during the period of study, the pollution index is constructed for each house by using the air pollution index from various stations in Tehran. Using this dataset, the effect of different pollutants on house prices is estimated. The findings show that particulate matter (PM 2.5 index) decreases house prices in Tehran, such that one standard deviation increase in the PM 2.5 index reduces house price by 3.1 percent. Moreover, there is no significant effect of NO 2 and CO pollutants, which can be due to their unobservability in air, their trivial instant effect on health, and the insignificance of these pollutants in determining the final index.

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Loss of Value in House Properties due to Air Pollution in Map Ta Phut Industrial Area of Thailand

Cited by 3 publications

References 13 publications

Flood hazards and housing prices: a spatial regression analysis for Hat Yai, Songkhla, Thailand

Flood hazards and housing prices: a spatial regression analysis for Hat Yai, Songkhla, Thailand

Integrated assessment of inhalation health risk and economic benefit of improving ambient targeted VOCs in Petrochemical industrial area

The Effect of Air Pollution on Real-Estate Price in Tehran

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