Over the last decades, the development of the Klang Valley (Malaysia), as an urban commercial and industrial area, has elevated the risk of atmospheric pollutions. There are several significant sources of air pollutants which vary depending on the background of the location they originate from. The aim of this study is to determine the trend and status of air quality and their correlation with the meteorological factors at different air quality monitoring stations in the Klang Valley. The data of five major air pollutants (PM(10), CO, SO(2), O(3), NO(2)) were recorded at the Alam Sekitar Sdn Bhd (ASMA) monitoring stations in the Klang Valley, namely Petaling Jaya (S1), Shah Alam (S2) and Gombak (S3). The data from these three stations were compared with the data recorded at Jerantut, Pahang (B), a background station established by the Malaysian Department of Environment. Results show that the concentrations of CO, NO(2) and SO(2) are higher at Petaling Jaya (S1) which is due to influence of heavy traffic. The concentrations of PM(10) and O(3,) however, are predominantly related to regional tropical factors, such as the influence of biomass burning and of ultra violet radiation from sunlight. They can, though, also be influenced by local sources. There are relatively stronger inter-pollutant correlations at the stations of Gombak and Shah Alam, and the results also suggest that heavy traffic flow induces high concentrations of PM(10), CO, NO(2) and SO(2) at the three sampling stations. Additionally, meteorological factors, particularly the ambient temperature and wind speed, may influence the concentration of PM(10) in the atmosphere.
This study is an attempt to explain the nexus between health expenditures, GDP, human development index (HDI), CO2 emissions (COEM), renewable energy (RENE), financial development (FD) and electricity consumption (EC) using data from 2000Q1 to 2014Q4 for Brazil, India, China and South Africa. The study applies CIPS and CADF to determine the integration order. The tests confirmed the unique order of integration. The study further uses the Westerlund panel cointegration, which suggests the existence of a long-run relationship. Moreover, the panels dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) are applied to ascertain the long-run elasticity. The health expenditure and electricity consumption affect the COEM positively. Moreover, HDI and RE affect COEM negatively. The study further confirms the existence of an N-shaped EKC in the long run. The pairwise Dumitrescu and Hurlin, Econ Model 29:1450-1460, (2012) test is used to uncover the direction of the association between the variables. The findings obtained from DH confirm a bidirectional causality between HDI and FD. Likewise, another bidirectional causal relationship has also been found between FD and EC. The findings of our study advocate policies in the direction of HDI and health expenditure by adopting RENE. This study highlights the importance of RENE, which can facilitate a reduction in carbon emissions and decreasing health expenditures. Moreover, the financial sector needs to be improved to create entrepreneurship opportunities for the public in improving the HDI in ensuring sustainable development.