Nonlinear Impact of Air Quality on Tourist Arrivals: New Proposal and Evidence

2020 ◽  
Vol 60 (2) ◽  
pp. 434-445 ◽  
Author(s):  
Liang-Ju Wang ◽  
Ming-Hsiang Chen

This study makes a novel contribution to the tourism literature by proposing an inverted U–shaped impact of air quality on tourist arrivals and examining this relationship using 58 major tourist cities in China from 2004 to 2015. The estimation of linear and nonlinear dynamic panel regression tests is based on the system generalized method of moments. The linear test results show that air quality measured by the concentration of fine particulate matter (PM2.5) has a significantly negative impact on both inbound and domestic tourist arrivals. The nonlinear test results validate an inverted U–shaped link between air quality and both inbound and domestic tourist arrivals.

2020 ◽  
pp. 135481662097074
Author(s):  
Liang-Ju Wang ◽  
Ming-Hsiang Chen ◽  
Lu Lu

This article makes an original contribution to the hospitality research literature. It proposes a curvilinear impact of air quality (AQ) on hotel sales (HS) and then empirically tests this nonlinear effect using data from 26 major tourist cities in China from 2002 to 2016. The results of dynamic panel regression test based on estimations of the system generalized method of moments reveal an inverse U-shaped impact of AQ (measured by concentrations of the fine particulate matter, i.e. PM2.5) on HS and thus validate the proposal. Empirical findings offer valuable policy implications for hotel business owners and tourism authorities and policymakers.


2021 ◽  
pp. 135481662110224
Author(s):  
Liang-Ju Wang ◽  
Ming-Hsiang Chen ◽  
Zhandong Yang ◽  
Ching-Hui (Joan) Su

This study proposes and tests two hypotheses concerning the effects of hotel industry operations on air quality based on data of 26 major tourist cities in China from 2002 to 2017. The empirical analyses take two steps. In the first step, panel regression test results reveal that hotel industry operations (measured by hotel sales revenue) significantly raise the value of particulate matter (PM)2.5 (the key indicator of air quality), supporting the first hypothesis that hotel industry operations deteriorate air quality and providing empirical evidence of the adverse impact of the hotel industry on air quality. In the second step, subsample analyses support the second hypothesis that the impact of hotel sales revenue on air quality diminishes over time. The results from the rolling regression tests validate the existence of a diminishing effect of hotel industry operations on air quality.


Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 302
Author(s):  
Rajesh Kumar ◽  
Piyush Bhardwaj ◽  
Gabriele Pfister ◽  
Carl Drews ◽  
Shawn Honomichl ◽  
...  

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m−3. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications.


2017 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Melissa Anne Hart ◽  
Ningbo Jiang

Abstract. Internationally, severe wildfires are an escalating problem likely to worsen given projected changes to climate. Hazard reduction burns (HRB) are used to suppress wildfire occurrences, but they generate considerable emissions of atmospheric fine particulate matter, which depending upon prevailing atmospheric conditions, can degrade air quality. Our objectives are to improve understanding of the relationships between meteorological conditions and air quality during HRBs in Sydney, Australia. We identify the primary meteorological covariates linked to high PM2.5 pollution (particulates


2016 ◽  
Author(s):  
Yu Fu ◽  
Amos P. K. Tai ◽  
Hong Liao

Abstract. To examine the effects of changes in climate, land cover and land use (LCLU), and anthropogenic emissions on fine particulate matter (PM2.5) between the 5-year periods 1981–1985 and 2007–2011 in East Asia, we perform a series of simulations using a global chemical transport model (GEOS-Chem) driven by assimilated meteorological data and a suite of land cover and land use data. Our results indicate that climate change alone could lead to a decrease in wintertime PM2.5 concentration by 4.0–12.0 μg m−3 in northern China, but an increase in summertime PM2.5 by 6.0–8.0 μg m−3 in those regions. These changes are attributable to the changing chemistry and transport of all PM2.5 components driven by long-term trends in temperature, wind speed and mixing depth. The concentration of secondary organic aerosol (SOA) is simulated to increase by 0.2–0.8 μg m−3 in both summer and winter in most regions of East Asia due to climate change alone, mostly reflecting higher biogenic volatile organic compound (VOC) emissions under warming. The impacts of LCLU change alone on PM2.5 (−2.1 to +1.3 μg m−3) are smaller than that of climate change, but among the various components the sensitivity of SOA and thus organic carbon to LCLU change (−0.4 to +1.2 μg m−3) is quite significant especially in summer, which is driven mostly by changes in biogenic VOC emissions following cropland expansion and changing vegetation density. The combined impacts show that while the effect of climate change on PM2.5 air quality is more pronounced, LCLU change could offset part of the climate effect in some regions but exacerbate it in others. As a result of both climate and LCLU changes combined, PM2.5 levels are estimated to change by −12.0 to +12.0 μg m−3 across East Asia between the two periods. Changes in anthropogenic emissions remain the largest contributor to deteriorating PM2.5 air quality in East Asia during the study period, but climate and LCLU changes could lead to a substantial modification of PM2.5 levels.


2019 ◽  
Vol 12 (12) ◽  
pp. 6385-6399 ◽  
Author(s):  
Bonne Ford ◽  
Jeffrey R. Pierce ◽  
Eric Wendt ◽  
Marilee Long ◽  
Shantanu Jathar ◽  
...  

Abstract. A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of ratios of fine particulate matter (PM2.5) to AOD and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements, from which 109 successful PM2.5 : AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5 : AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future wider deployments of the CEAMS network.


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