Abstract:Abstract. Analysis of gaseous criteria pollutants in Bangkok Metropolitangood to moderate. Unhealthy O3 categories were observed during episode conditions in the region.
“…The traffic is congested during these periods due to the higher number of vehicles on the road [62]. The second peaks occurred ∼3 hours after the evening traffic rush hour indicated to a combination of pollutants emissions and a more stable plenatary boundary layer which is characterized by weak turbulence and diffusion, allowing pollutants to accumulate in the layer [63, 64, 65]. Fig.…”
This study aims to evaluate the air quality on Langkawi Island, a famous tourist destination in Malaysia, using 13 years of data (1999–2011) recorded by the Malaysian Department of Environment. Variations of seven air pollutants (O3, CO, NO, NO2, NOx, SO2 and PM10) and three meteorological factors (temperature, humidity and wind speed) were analysed. Statistical methods used to analyse the data included principal component regression (PCR) and sensitivity analysis. The results showed PM10 was the dominant air pollutant in Langkawi and values ranged between 5.0 μg m−3 and 183.2 μg m−3. The patterns of monthly values showed that the concentrations of measured air pollutants on Langkawi were higher during the south-west monsoon (June–September) due to seasonal biomass burning activities. High CO/NOx ratio values (between 28.3 and 43.6), low SO2/NOx ratio values (between 0.04 and 0.12) and NO/NO2 ratio values exceeding 2.2 indicate the source of air pollutants in this area was motor vehicles. PCR analysis grouped the seven variables into two factor components: the F1 component consisted of SO2, NO and NOx and the F2 component consisted of PM10. The F1 component (R2 = 0.931) indicated a stronger standardized coefficient value for meteorological variables compared to the F2 component (R2 = 0.059). The meteorological variables were statistically significant (p < 0.05) in influencing the distribution of the air pollutants. The status of air quality on the island could be improved through control on motor vehicle emissions as well as collaborative efforts to reduce regional air pollution, especially from biomass burning.
“…The traffic is congested during these periods due to the higher number of vehicles on the road [62]. The second peaks occurred ∼3 hours after the evening traffic rush hour indicated to a combination of pollutants emissions and a more stable plenatary boundary layer which is characterized by weak turbulence and diffusion, allowing pollutants to accumulate in the layer [63, 64, 65]. Fig.…”
This study aims to evaluate the air quality on Langkawi Island, a famous tourist destination in Malaysia, using 13 years of data (1999–2011) recorded by the Malaysian Department of Environment. Variations of seven air pollutants (O3, CO, NO, NO2, NOx, SO2 and PM10) and three meteorological factors (temperature, humidity and wind speed) were analysed. Statistical methods used to analyse the data included principal component regression (PCR) and sensitivity analysis. The results showed PM10 was the dominant air pollutant in Langkawi and values ranged between 5.0 μg m−3 and 183.2 μg m−3. The patterns of monthly values showed that the concentrations of measured air pollutants on Langkawi were higher during the south-west monsoon (June–September) due to seasonal biomass burning activities. High CO/NOx ratio values (between 28.3 and 43.6), low SO2/NOx ratio values (between 0.04 and 0.12) and NO/NO2 ratio values exceeding 2.2 indicate the source of air pollutants in this area was motor vehicles. PCR analysis grouped the seven variables into two factor components: the F1 component consisted of SO2, NO and NOx and the F2 component consisted of PM10. The F1 component (R2 = 0.931) indicated a stronger standardized coefficient value for meteorological variables compared to the F2 component (R2 = 0.059). The meteorological variables were statistically significant (p < 0.05) in influencing the distribution of the air pollutants. The status of air quality on the island could be improved through control on motor vehicle emissions as well as collaborative efforts to reduce regional air pollution, especially from biomass burning.
“…The rapidly expanding fleet of motor vehicles has worsened the city's traffic conditions and air quality and has raised the urban temperature by contributing to the heat island effect (Attavanich, 2017;Khamchiangta and Dhakal, 2019). Motor vehicles thus damage public health, human welfare, and the economy (Uttamang et al, 2017). Indeed, the impacts of air pollution on health and life satisfaction have been estimated to cost around $6.17 billion annually during the first wave of car purchasing (Attavanich, 2017).…”
Section: Background Of Bangkok's Mobilitymentioning
Consumption of raw materials, energy, manufactured goods, and services is increasingly concentrated in cities, as urbanization accelerates globally. Such consumption is influenced by complex interactions arising between the various socio-technical and natural systems that make up cities. To improve understanding of the interlinked factors that can perpetuate—or “lock-in”—unsustainable consumption, we build an explanatory framework that conceptually joins the literature on socio-technical systems and on urban consumption. Two questions guide our study: (1) What are the principal socio-technical systems in cities that influence consumption behavior? (2) How do these systems interact to lock urban dwellers into unsustainable consumption behavior? The resulting framework incorporates theories of socio-technical lock-in with factors relating to both “structure” and “agency” in consumption literature. Specifically, it describes the influence and interactions of physical, non-physical, and human systems on two interlinked scales: macro-scale (structure and collectively shared conditions) and micro-scale (agency and individually shaped conditions). To demonstrate the practical value of this framework, we apply it to a case study on mobility in Bangkok, Thailand. This allows us to systematically identify the interlinked mechanisms contributing to the growing dependence on and lock-in to individually owned passenger vehicles. Our study thus provides a comprehensive understanding of the multiplex drivers of consumption behavior, taking into account both structure and agency. The framework also provides a tool for other scholars to empirically identify lock-in mechanisms that hamper the adoption of more sustainable consumption behavior in other sectors and geographies.
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