Nanomaterials pollutant's emission influencing outdoor recreation in China: Analytical strategies proceeding to sustainable environment

Abstract

The global demand for bioenergy and nanomaterial utilization has significantly contributed to their source depletion. The impact of outdoor pollutant emissions on residents' health, behavior, physical activity, and sleeping behavior is much less explored. Producing biofuels from organic waste has the potential to unite budget-friendliness and long-term sustainability. Primary biofuels are produced specifically to mitigate environmental problems, and secondary biofuels are produced specifically to mitigate other environmental problems. The high level of pollutants ina certain area can severely restrict human activities and ultimately influence their whole life. The study aims to empirically evaluate the influence of nanomaterials pollutants emissions influencing outdoor recreation in China because its economy is based on fast-paced industrialization and urbanization. Various datasets were collected, including domestic and international tourists from the annual statistics for 2011-2020 from the National Bureau of Statistics of China. Ten years of annual METAR data of visibility (VR), temperature (T), relative humidity (Demirhan), and wind speed (WS) from 30 metrological stations at international airports. Annual average AOD (Aerosol's Optical Depth), O₃ (Ozone), CO (Carbon Monoxide), SO₄ (Sulphate), and PM_2.5 (Particulate Matter) satellite imageries from 2011 to 2020 were obtained from NASA's official portal. The overall picture of satellite observations of pollutants over China describes that the highest level of AOD was observed in regions with greater population concentration than in other areas. We computed a statistical summary, correlation matrix, and Autoregressive Distributed Lag (ARDL) approach. Certain analyses were performed, like Unrestricted Error Correction Models (UECM) and Restricted Error Correction Model (RECM)), bound tests for cointegration, and multiplier estimations for short-term and long-term impacts. UECM and RECM models produced R² > 0.90 with good F statistics and a p-value of <0.05. A bounds F-test for no cointegration on the ARDL model was performed, and the results show that the p-value = 1e-06 and F = 8.516 with alternative hypothesis = Possible cointegration. Bounds t-test for no cointegration was also performed on UECM model and the results show that t = -2.9066, Lower-bound I(0) = -3.43, Upper-bound I(1) = -5.37, p-value = 0.6138 and alternative hypothesis = Possible cointegration. The study's findings may help Chinese policymakers and stakeholders design effective information strategies to combat air pollution. Effective measures can help alleviate this devastating air quality factor, thus benefiting the tourism industry and enhancing the local inhabitants' welfare.

Keywords: Autoregressive distributed lag; Bioenergy; Biofuels; Emission; Nanomaterial; Restrictederror correction model; Sustainability; Unrestricted error correction model.