Estimating the Impact of Air Pollution on Inbound Tourism in China: An Analysis Based on Regression Discontinuity Design

Prior studies have suggested the existence of a reverse causality relationship between air quality and tourism development: while air quality influences tourism, dynamic segments of the tourism industry (e.g., cruising, airline, foodservice) have impacts on air quality. This reverse causality hinders a precise estimate on the effect of air pollution on tourism development within a conventional econometric framework, since the variable of air pollution is endogenous. This study estimates the impact of air pollution on the inbound tourism industry in China, by controlling for endogeneity based on a regression discontinuity design (RDD). The estimate is derived from a quasi-experiment generated by China’s Huai River Policy, which subsidizes coal for winter heating in northern Chinese cities. By analyzing data from 274 Chinese cities during the period 2009–2012, it is found that air pollution significantly reduces the international inbound tourism: an increase of PM 10 (particulate matter smaller than 10 μ m) by 0.1 mg/m 3 will cause a decline in the tourism receipts-to-local gross domestic product (GDP) ratio by 0.45 percentage points. This study also highlights the importance of controlling for endogeneity, since the detrimental impact of air pollution would otherwise be considerably underestimated. This study further demonstrates that, although air pollution is positively correlated with the average expenditure of each tourist, it substantially depresses the number of inbound tourists. The results imply that air quality could potentially influence inbound tourists’ city destination choices. However, it is interesting to note that travelers in air polluted cities in China tend to spend more money.

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Examining the Potential Impacts of Air Pollution on China’s Inbound Tourism: The Case of Beijing and Shanghai

10.20944/preprints202103.0028.v1 ◽

2021 ◽

Author(s):

Xu Ni ◽

Hongqing Ma

Keyword(s):

Air Pollution ◽

Air Quality ◽

Economic Impact ◽

Potential Effect ◽

Tourism Industry ◽

Social Awareness ◽

Inbound Tourism ◽

Source Countries ◽

The Impact

Concerns about China’s air quality, and its impact on the important tourism industry have been on the debate in recent years. This article aims to investigate the potential effect of air pollution on direct economic impact of tourism, using the case of Beijing and Shanghai. The results indicate that air pollution negatively affects China's inbound tourism, resulting in huge loss of tourist arrivals and receipts, and Beijing suffers a greater loss in comparison with Shanghai, its loss in tourist number amounts to 1569,700 persons, equal to CNY 10264.268 million in tourism receipts, and the GDP losses ranges from CNY 20528.536 to 41057.072 across major source countries. This study provides a quantification of the impact helpful to generate a social awareness of air pollution detrimental impacts on inbound tourism and hence the economy.

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Evaluating the Impact of Air Pollution on China’s Inbound Tourism: A Gravity Model Approach

Sustainability ◽

10.3390/su12041456 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1456 ◽

Cited By ~ 1

Author(s):

Boyang Xu ◽

Daxin Dong

Keyword(s):

Air Pollution ◽

Air Quality ◽

Gravity Model ◽

Tourist Attractions ◽

Tourist Destinations ◽

Foreign Countries ◽

Inbound Tourism ◽

Clean Air ◽

Negative Impacts ◽

The Impact

China’s inbound tourism grew very slowly in recent years. This study modelled China’s inbound tourism based on a gravity model with province-level inbound tourist arrivals data from 13 countries of origin between 2010 and 2016. It was found that air pollution in tourist destinations and origin regions both had significant negative impacts on China’s inbound tourism. On average, if the concentration of particulate matter with a diameter of 2.5 micrometers or less (PM 2.5 ) in China and foreign countries increased by 1 μ g/m 3 , inbound tourist arrivals would decline by approximately 1.7% and 3.8%, respectively. The effect of pollution in destination regions is explained by the importance of clean air as a favored characteristic of tourist attractions. The effect of pollution in tourist origin countries is explained by more awareness of and concern about air pollution by potential tourists if they live in more polluted countries. Further analysis showed that the impact of air pollution in destination regions was larger for tourists coming from more polluted and Asian countries, and visiting less polluted and more popular destinations. This study has a clear policy implication: improving air quality can be considered as a straightforward and effective way to promote inbound tourism in China. If air quality in China can be substantially improved in the future, inbound tourist arrivals have the potential to rise by at least tens of millions of person-times.

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The Impact of Air Pollution on Domestic Tourism in China: A Spatial Econometric Analysis

Sustainability ◽

10.3390/su11154148 ◽

2019 ◽

Vol 11 (15) ◽

pp. 4148 ◽

Cited By ~ 6

Author(s):

Daxin Dong ◽

Xiaowei Xu ◽

Hong Yu ◽

Yanfang Zhao

Keyword(s):

Air Pollution ◽

Air Quality ◽

Local Governments ◽

Spillover Effects ◽

Tourism Industry ◽

Spatial Econometric ◽

Pm 2.5 ◽

Domestic Tourism ◽

The Impact ◽

Domestic Tourist

This study utilizes a spatial econometric model to analyze the impact of air pollution on domestic tourism in China. Based on a panel dataset covering 337 cities from 2004–2013, this study derives the following findings. (1) Air pollution significantly reduces domestic tourist arrivals in the local city. On average, if the concentration of PM 2.5 (particulate matter equal to or less than 2.5 micrometers in width) in one city increases by 1 μ g/m 3 , the number of domestic tourists to the city declines by 0.7%. (2) Air pollution demonstrates significant spatial spillover effects. If the PM 2.5 in other cities simultaneously increases by 1 μ g/m 3 , the number of domestic tourists traveling to the local city rises by 4.1%. (3) The magnitude of the spillover effects of air pollution is larger than the negative direct effects on local cities. This study suggests that enhancing air quality in the local area will effectively promote the domestic tourism industry in the local city. In addition, it is implied that a simultaneous improvement in the air quality in all cities might not lead to an increase in the number of domestic tourist arrivals. Thus, in order to deal with the spillover effects of air pollution on the domestic tourism industry, local governments should make efforts to develop cross-city or cross-region tourism.

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Evaluating the impact of partial driving restrictions on local air quality in Chongqing using regression discontinuity design

Environment and Planning B Urban Analytics and City Science ◽

10.1177/23998083211010801 ◽

2021 ◽

pp. 239980832110108

Author(s):

Xin Li ◽

Shuhan Jiang ◽

Tianqi Wang ◽

Jia Hu ◽

Yun Yuan

Keyword(s):

Air Quality ◽

Traffic Congestion ◽

Quality Index ◽

Regression Discontinuity ◽

Principal Component ◽

River System ◽

Air Quality Index ◽

Regression Discontinuity Design ◽

Driving Restrictions ◽

The Impact

Driving restriction is used to mitigate traffic congestion and improve air quality. A partial bridge restriction policy is created in Chongqing, China since the bridges are natural network bottlenecks due to the local river system. Is such a strategy really capable of reducing air pollution and further improving local air quality? Employing an integration of principal component analysis and a regression-discontinuity design approach, this study examines the short-run effect of the partial driving restrictions on the local air quality index in Chongqing, China. The examination is first conducted to the city level, and then its eight administrative districts are tested separately. The findings reveal that the air quality index of the whole city area has experienced deterioration after the introduction of restrictions in Chongqing. Among eight districts, Yuzhong is the only one experiencing an improvement of air quality index.

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Post-Industrial Tourism as a Driver of Sustainable Development

Sustainability ◽

10.3390/su13158145 ◽

2021 ◽

Vol 13 (15) ◽

pp. 8145

Author(s):

Aleksandra Kuzior ◽

Oleksii Lyulyov ◽

Tetyana Pimonenko ◽

Aleksy Kwilinski ◽

Dariusz Krawczyk

Keyword(s):

Sustainable Development ◽

Tourism Development ◽

Tourism Industry ◽

Digital Marketing ◽

Gender And Education ◽

Development Goals ◽

The Difference ◽

Post Industrial ◽

The Impact ◽

Industrial Tourism

The accepted Sustainable Development Goals aim at reorienting the tourism industry to sustainable tourism and enhancing post-industrial tourism. In this case, it is necessary to identify the statistically significant determinants which affect post-industrial tourism development. In this paper, we aim to analyse: (1) the impact of economic and environmental dimensions, and of digital marketing on supporting post-industrial tourism development and (2) the difference between attitude to post-industrial tourism on the gender, age, and education dimensions and digital channels on post-industrial tourism development. The data was collected from questioning 2334 respondents during April–November 2020. The study applied the following methods: frequencies, percentages, t-test, and one-way ANOVA and multiple regression analysis. The findings confirmed the statistically significant impact of the economic and environmental dimensions, as well as digital marketing on post-industrial tourism development. The results of the analysis justified that digital marketing was a catalysator of post-industrial tourism development. In addition, the findings confirmed that there is no difference in attitudes towards post-industrial tourism with respect to the dimensions of age, gender, and education.

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Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-021-02071-4 ◽

2021 ◽

Author(s):

Christian Acal ◽

Ana M. Aguilera ◽

Annalina Sarra ◽

Adelia Evangelista ◽

Tonio Di Battista ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Functional Data ◽

Central Italy ◽

Principal Component ◽

Functional Principal Component Analysis ◽

Area Of Interest ◽

Pm 10 ◽

The Impact ◽

Monitoring Stations

AbstractFaced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of $$\hbox {NO}_{{2}}$$ NO 2 , $$\hbox {PM}_{{10}}$$ PM 10 , $$\hbox {PM}_{2.5}$$ PM 2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the $$\hbox {PM}_{{10}}$$ PM 10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

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The interplay between environmental exposures and COVID-19 risks in the health of children

Environmental Health ◽

10.1186/s12940-021-00716-z ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Peter D. Sly ◽

Brittany A. Trottier ◽

Catherine M. Bulka ◽

Stephania A. Cormier ◽

Julius Fobil ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Disease Severity ◽

Research Effort ◽

Severe Disease ◽

Environmental Exposures ◽

Research Strategy ◽

Lessons Learned ◽

Research Questions ◽

The Impact

Abstract Background An unusual feature of SARS-Cov-2 infection and the COVID-19 pandemic is that children are less severely affected than adults. This is especially paradoxical given the epidemiological links between poor air quality and increased COVID-19 severity in adults and that children are generally more vulnerable than adults to the adverse consequences of air pollution. Objectives To identify gaps in knowledge about the factors that protect children from severe SARS-Cov-2 infection even in the face of air pollution, and to develop a transdisciplinary research strategy to address these gaps. Methods An international group of researchers interested in children’s environmental health was invited to identify knowledge gaps and to develop research questions to close these gaps. Discussion Key research questions identified include: what are the effects of SAR-Cov-2 infection during pregnancy on the developing fetus and child; what is the impact of age at infection and genetic susceptibility on disease severity; why do some children with COVID-19 infection develop toxic shock and Kawasaki-like symptoms; what are the impacts of toxic environmental exposures including poor air quality, chemical and metal exposures on innate immunity, especially in the respiratory epithelium; what is the possible role of a “dirty” environment in conveying protection – an example of the “hygiene hypothesis”; and what are the long term health effects of SARS-Cov-2 infection in early life. Conclusion A concerted research effort by a multidisciplinary team of scientists is needed to understand the links between environmental exposures, especially air pollution and COVID-19. We call for specific research funding to encourage basic and clinical research to understand if/why exposure to environmental factors is associated with more severe disease, why children appear to be protected, and how innate immune responses may be involved. Lessons learned about SARS-Cov-2 infection in our children will help us to understand and reduce disease severity in adults, the opposite of the usual scenario.

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Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

Complex & Intelligent Systems ◽

10.1007/s40747-021-00435-5 ◽

2021 ◽

Author(s):

Shwet Ketu ◽

Pramod Kumar Mishra

Keyword(s):

Air Pollution ◽

Air Quality ◽

Class Imbalance ◽

Imbalanced Data ◽

Classification Algorithm ◽

Quality Data ◽

Pollution Level ◽

Classification Problems ◽

Chi Square ◽

The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

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Gender Differences in Association between Air Pollution and Daily Mortality in the Capital of the Green Lungs of Poland–Population-Based Study with 2,953,000 Person-Years of Follow-Up

Journal of Clinical Medicine ◽

10.3390/jcm9082351 ◽

2020 ◽

Vol 9 (8) ◽

pp. 2351

Author(s):

Łukasz Kuźma ◽

Krzysztof Struniawski ◽

Szymon Pogorzelski ◽

Hanna Bachórzewska-Gajewska ◽

Sławomir Dobrzycki

Keyword(s):

Public Health ◽

Gender Differences ◽

Air Pollution ◽

Air Quality ◽

Air Pollutant ◽

World Health ◽

The European Union ◽

Daily Mortality ◽

Male Population ◽

The Impact

(1) Introduction: air pollution is considered to be one of the main risk factors for public health. According to the European Environment Agency (EEA), air pollution contributes to the premature deaths of approximately 500,000 citizens of the European Union (EU), including almost 5000 inhabitants of Poland every year. (2) Purpose: to assess the gender differences in the impact of air pollution on the mortality in the population of the city of Bialystok—the capital of the Green Lungs of Poland. (3) Materials and Methods: based on the data from the Central Statistical Office, the number—and causes of death—of Białystok residents in the period 2008–2017 were analyzed. The study utilized the data recorded by the Provincial Inspectorate for Environmental Protection station and the Institute of Meteorology and Water Management during the analysis period. Time series regression with Poisson distribution was used in statistical analysis. (4) Results: A total of 34,005 deaths had been recorded, in which women accounted for 47.5%. The proportion of cardiovascular-related deaths was 48% (n = 16,370). An increase of SO2 concentration by 1-µg/m3 (relative risk (RR) 1.07, 95% confidence interval (CI) 1.02–1.12; p = 0.005) and a 10 °C decrease of temperature (RR 1.03, 95% CI 1.01–1.05; p = 0.005) were related to an increase in the number of daily deaths. No gender differences in the impact of air pollution on mortality were observed. In the analysis of the subgroup of cardiovascular deaths, the main pollutant that was found to have an effect on daily mortality was particulate matter with a diameter of 2.5 μm or less (PM2.5); the RR for 10-µg/m3 increase of PM2.5 was 1.07 (95% CI 1.02–1.12; p = 0.01), and this effect was noted only in the male population. (5) Conclusions: air quality and atmospheric conditions had an impact on the mortality of Bialystok residents. The main air pollutant that influenced the mortality rate was SO2, and there were no gender differences in the impact of this pollutant. In the male population, an increased exposure to PM2.5 concentration was associated with significantly higher cardiovascular mortality. These findings suggest that improving air quality, in particular, even with lower SO2 levels than currently allowed by the World Health Organization (WHO) guidelines, may benefit public health. Further studies on this topic are needed, but our results bring questions whether the recommendations concerning acceptable concentrations of air pollutants should be stricter, or is there a safe concentration of SO2 in the air at all.

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Effectiveness of a Power Factor Correction Policy in Improving the Energy Efficiency of Large-Scale Electricity Users in Ghana

Energies ◽

10.3390/en12132582 ◽

2019 ◽

Vol 12 (13) ◽

pp. 2582 ◽

Cited By ~ 3

Author(s):

Samuel Lotsu ◽

Yuichiro Yoshida ◽

Katsufumi Fukuda ◽

Bing He

Keyword(s):

Energy Efficiency ◽

Power Factor ◽

Large Scale ◽

Regression Discontinuity ◽

Power Factor Correction ◽

Energy Crisis ◽

Regression Discontinuity Design ◽

The Government ◽

Power Factor Improvement ◽

The Impact

Confronting an energy crisis, the government of Ghana enacted a power factor correction policy in 1995. The policy imposes a penalty on large-scale electricity users, namely, special load tariff (SLT) customers of the Electricity Company of Ghana (ECG), whose power factor is below 90%. This paper investigates the impact of this policy on these firms’ power factor improvement by using panel data from 183 SLT customers from 1994 to 1997 and from 2012. To avoid potential endogeneity, this paper adopts a regression discontinuity design (RDD) with the power factor of the firms in the previous year as a running variable, with its cutoff set at the penalty threshold. The result shows that these large-scale electricity users who face the penalty because their power factor falls just short of the threshold are more likely to improve their power factor in the subsequent year, implying that the power factor correction policy implemented by Ghana’s government is effective.

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