| 摘要: |
| 在过去的几十年中，美国通过联邦
的环境保护署致力于改良城市空气质量，在
大范围上取得了相当优异的成绩。然而，在
一些重要的工业大都会，空气污染依旧比较
严重。工业排放和依赖传统化石能源的交通
工具被普遍认为是城市空气污染的两个主要
来源。在国外城市规划的相关研究中，经常
探讨污染对居民住房选择的影响，评价社区
发展的公平性与正义性，并提出相应的环境
污染管理政策。然而，很少有研究对环境政
策的效果进行量化评价。本文选择美国德克
萨斯州休斯顿地区作为研究对象，分析研究
空气污染和住房价格之间的潜在联系，回答
空气污染是否对住房价格具有显著影响的
问题。同时，探讨空气污染对不同种族聚居
的社区的影响，以及区域性环境保护政策的效果，特别是对空气质量和住房价格的关系所产生的影响。本研究采用享乐价格模型（hedonic
price model），利用休斯顿地区哈里斯县的住房价格来量化城市臭氧污染对社区和人口的影
响，以及房价对当地区域性环境政策的反馈。研究发现哈里斯县的房价符合一般市场规律，即
房价与房龄成负相关，与建筑面积，学区质量，交通可达性和家庭收入等变量成正相关。其次，
可达性等交通分析显示出房价与到城市中心商业区的距离成负相关，这体现出美国城市发展的
模式。另外，通过分析发现，空气污染对城市少数族裔聚集的社区具有不平衡的影响。最后，通
过对联邦环境署在该地区颁布的三个年份（1997年、2008年和2015年）的环境标准进行评估，
显示出环境政策对房价的影响：第一，政策带来的效果具有滞后性；第二，新的环境政策实施
以后，普遍对当地房价具有积极的意义。该研究首次分析了休斯顿地区的空气污染与住房市场
之间的关系，深入地探讨了当地的环境政策，同时以此为实例解释了美国城市发展与环境之间
的联系。 |
| 关键词: 空气污染 房价 环境政策 人口分布 城市中心 |
| DOI：10.13791/j.cnki.hsfwest.20210401 |
| 分类号: |
| 基金项目: |
|
| Impacts of Air Pollution on Housing Prices and Related Policy Discussions: A Case Studyof Houston, Texas |
|
JIN Zhonghua,PAN Qisheng
|
| Abstract: |
| For several decades, the United States has been committing to improving air quality
by empowering its Environmental Protection Agency (EPA) and has achieved excellent results
on a large scale. However, EPA has reported that, there were still a large number of population,
over 81 million in 2019, living in counties with air quality concentrations above one or more
National Ambient Air Quality standards (NAAQs) in the US. Currently, in some major intensive
manufacturing cities, air pollution still presents at relatively high levels, such as Los Angeles, New
York, Chicago, Dallas, and Houston. In relevant environmental studies, environmental justice is
often highlighted that disadvantaged populations are often observed experiencing higher level of
air pollutions, but fewer studies have adopted quantitative methods to assess the effectiveness of
environmental policies. Taking the Houston area as an empirical case, this study explores the impact
of air pollution on local housing prices and racial distributions, and examines the impact of regional
environmental policies on housing prices. As the most populous city in southern US, Houston is
famous of its energy industry and the majority working class population own at least one vehicle.
Industrial production and traffic emission are the two primary sources of air pollution in the urban
area. Additionally, high temperature stimulates the creation of smog and ozone, causing public
health concerns to the local communities. Even though that the overall air quality is good in this
area, there are still many days in a year when the air pollution levels exceed the limit, especially the ground level ozone. This study employs the Hedonic price model to quantify the impact of urban ozone pollution on local communities and residents, as
well as to test the responses of housing prices to environmental policies. The Hedonic price model recognizes the housing prices as a bundle of prices of
many different characteristics, often referring as the implicit prices. To evaluate the impact of air pollution, ground level ozone is considered as one of
many explanatory variables that affect housing prices. Ozone data is obtained from Texas Commission on Environmental Quality (TCEQ), which is the
state environment agency monitoring daily air quality. In geographic information system (GIS), inverse distance weighted (IDW) method is applied to
interpolate site observed ozone data to the entire study area, and then each housing unit is assigned with an estimated ozone value by their location. The
other explanatory variables in the model include housing structure variables, neighborhood quality variables, and demographic variables. To identify
city centers, Census Transportation Planning Products (CTPP) data is obtained to identify major Transportation Analysis Zones (TAZs) that have the
highest job densities as city centers. Moreover, EPA has passed three ozone standards, 1997 standard, 2008 standard, and 2015 standard, based on which
metropolitan areas are being identified as attainment or nonattainment areas. Four dummy variables are included to represent four periods of time
before and after governmental regulations became effective on air quality. There are several interesting and important findings. First, this study finds
that housing prices follow the general market trend. Housing prices are negatively correlated with home age, distance to central business districts, and
distance to nearest highway, but positively correlated with floor area, school district quality, and median area incomes. Second, accessibility analysis
shows that housing prices decrease with the increasing distance from the urban centers, which reflects the special pattern of urban development in the
US. Housing units locate close to city centers are generally older, and most of the newer housing units are built in the suburbs. Housing units with high
accessibility to city centers and transportation facilities tend to have higher transaction prices as land value is relatively higher within the city than in the
suburbs. In addition, this study finds that air pollution has an unbalanced impact on housing prices. The regression results indicate that the ozone levels
positively correlate with median housing value. Areas close to city centers tend to experience higher level of ozone. Percentages of Asian population,
Hispanic population, and African American population are used to estimate the impact of demographics on housing prices. The regression also shows
that minority populations are negatively correlated with housing prices. The evaluation of the environmental standards shows that environmental policies
have two major effects. One is that the policies have lagged effects on housing prices. The other one is that those policies, in general, have positively
significant impacts on local housing prices. As air pollution standards become more and more strict, air quality could be potentially improved over time.
In future research, improvements can be made by incorporating more explanatory variables and by collecting more air monitoring data. Additional
site monitoring air quality data could improve the accuracy of interpolation method. This study is among one the few studies exploring the relationship
between air pollution and the housing market in the Houston area, and it discusses the effectiveness of local environmental policies in-depth. |
| Key words: Air Pollution Housing Price Environmental Policy Demographics Urban Centers |
