Escape or stay? Effects of haze pollution on domestic travel: Comparative analysis of different regions in China

Sun, Jiancheng; Zhang, Jinhe; Wang, Chang; Duan, Xiaofang; Wang, Yaru

doi:10.1016/j.scitotenv.2019.06.415

Cited by 37 publications

(22 citation statements)

References 37 publications

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“…The study was based on a city-level sample with panel data structure, consisting of both temporal and spatial dimensions. Following the previous studies investigating the pollution-tourism nexus (e.g., [12,31,32,39]), it was assumed that the impacts of air pollution and other explanatory variables on tourism could be captured by a linear econometric regression model. To be precise, in this study the following panel data econometric model was used:…”

Section: Modelmentioning

confidence: 99%

“…Although there were uncertainties associated with the remote sensing measurements (for example, affected by weather and the precision of the electrical instruments), the accuracy and reliability of the PM 2.5 grids data have been highly appreciated. In fact, both data sources have been widely utilized in previous research (e.g., [8,9,11,12,42]). The data from the two data sources were highly correlated.…”

Section: Datamentioning

confidence: 99%

“…They further discovered that leisure-related activities were much more sensitive to air pollution than work-related activities. To examine the impact of air pollution on the tourism industry, a number of studies have used PM 2.5 , PM 10 , or AQI as indicative measures of air quality (e.g., [9][10][11][12]). However, how other major air pollutants (e.g., NO 2 , SO 2 ) influence the tourism industry in China has seldom been explored.…”

Section: Introductionmentioning

confidence: 99%

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The Impacts of Different Air Pollutants on Domestic and Inbound Tourism in China

Dong

Wang

et al. 2019

IJERPH

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Previous studies have reported that air pollution negatively affects the tourism industry. This paper attempted to answer the following question: among different air pollutants, which one acts as the most adverse factor? The study was based on a sample of panel data covering 337 Chinese cities for the period between 2007 and 2016. Four pollutant indicators were inspected: PM 2 . 5 (particulate matter 2.5 micrometers or less in size), PM 10 (particulate matter 10 micrometers or less in size), SO 2 (sulfur dioxide), and NO 2 (nitrogen dioxide). It was found that PM 2 . 5 had a significantly negative impact on both domestic and inbound tourist arrivals. Regarding the other three pollutant indicators, except for the negative influence of NO 2 on inbound tourist arrivals, no statistically significant impact was found. This study suggests that tourism policy makers should primarily focus on PM 2 . 5 , when considering the nexus between air quality and tourism development. According to our estimates, the negative impact of PM 2 . 5 on tourism is substantial. If the PM 2 . 5 concentration in the ambient air increases by 1 μ g/m 3 (= 0.001 mg/m 3 ), domestic and inbound tourist arrivals will decline by 0.482% and 1.227%, respectively. These numbers imply an average reduction of 81,855 person-times in annual domestic tourist arrivals and 12,269 in inbound tourist arrivals in each city.

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Section: Modelmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Impacts of Different Air Pollutants on Domestic and Inbound Tourism in China

Dong

Wang

et al. 2019

IJERPH

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“…The influence of unpredictable monsoon rain and El-Nino phenomenon both worsens the transboundary haze due to the prolonged and drier weather conditions, especially during the southwest monsoon season [3][4][5][6][7][8]. These conditions increase the severity of air quality due to it containing a noxious mix of air pollutants, such as particulate matter and noxious gases, which are collectively influenced by meteorological factors like ambient temperature, relative humidity, and wind speed [9,10]. Malaysia has been facing this awful phenomenon for almost over a decade, which started in the 1980s up until recent years [5,11,12].…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, huge losses occur when the atmospheric visibility decreases; many flights are cancelled due to unsafe conditions to fly, which decreases the number of tourism activities. Furthermore, the number of extinct plants, animals, and biodiversity will increase due to extreme environmental events, while the circumstances can also change tourism moods due to unsatisfactory environmental conditions and lead to a refusal to revisit [5,10,21,22].…”

Section: Introductionmentioning

confidence: 99%

Development of Multiple Linear Regression for Particulate Matter (PM10) Forecasting during Episodic Transboundary Haze Event in Malaysia

et al. 2020

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Malaysia has been facing transboundary haze events every year in which the air contains particulate matter, particularly PM10, which affects human health and the environment. Therefore, it is crucial to develop a PM10 forecasting model for early information and warning alerts to the responsible parties in order for them to mitigate and plan precautionary measures during such events. Therefore, this study aimed to develop and compare the best-fitted model for PM10 prediction from the first hour until the next three hours during transboundary haze events. The air pollution data acquired from the Malaysian Department of Environment spanned from the years 2005 until 2014 (excluding years 2007–2009), which included particulate matter (PM10), ozone (O3), nitrogen oxide (NO), nitrogen dioxide (NO), carbon monoxide (CO), sulfur dioxide (SO2), wind speed (WS), ambient temperature (T), and relative humidity (RH) on an hourly basis. Three different stepwise Multiple Linear Regression (MLR) models for predicting the PM10 concentration were then developed based on three different prediction hours, namely t+1, t+2, and t+3. The PM10, t+1 model was the best MLR model to predict PM10 during transboundary haze events compared to PM10,.t+2 and PM10,t+3 models, having the lowest percentage of total error (28%) and the highest accuracy of 46%. A better prediction and explanation of PM10 concentration will help the authorities in getting early information for preserving the air quality, especially during transboundary haze episodes.

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2022

A Back and Forth Between Tourism and Health

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Escape or stay? Effects of haze pollution on domestic travel: Comparative analysis of different regions in China

Cited by 37 publications

References 37 publications

The Impacts of Different Air Pollutants on Domestic and Inbound Tourism in China

The Impacts of Different Air Pollutants on Domestic and Inbound Tourism in China

Development of Multiple Linear Regression for Particulate Matter (PM10) Forecasting during Episodic Transboundary Haze Event in Malaysia

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