Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

Quantifying the human health benefits of curbing air pollution in Shanghai

Urban development in the mega-cities of Asia has caused detrimental effects on the human health of its inhabitants through air pollution. However, averting these health damages by investing in clean energy and industrial technologies and measures can be expensive. Many cities do not have the capital to make such investments or may prefer to invest that capital elsewhere. In this article, we examine the city of Shanghai, China, and perform an illustrative cost/benefit analysis of air pollution control. Between 1995 and 2020 we expect that Shanghai will continue to grow rapidly. Increased demands for energy will cause increased use of fossil fuels and increased emissions of air pollutants. In this work, we examine emissions of particles smaller than 10 microm in diameter (PM10), which have been associated with inhalation health effects. We hypothesize the establishment of a new technology strategy for coal-fired power generation after 2010 and a new industrial coal-use policy. The health benefits of pollution reduction are compared with the investment costs for the new strategies. The study shows that the benefit-to-cost ratio is in the range of 1-5 for the power-sector initiative and 2-15 for the industrial-sector initiative. Thus, there appear to be considerable net benefits for these strategies, which could be very large depending on the valuation of health effects in China today and in the future. This study therefore provides economic grounds for supporting investments in air pollution control in developing cities like Shanghai.     

Green supply chain management in the chemical industry: structural framework of drivers

ABSTRACT

The main purpose of Green Supply Chain Management (GSCM) is to improve the quality of supply chain management strategies and environmental performance. As per current statistics, the chemical industry is growing fast in Bangladesh. In order to compete for global competition, GSCM is essential in this sector. This paper proposes a systematic approach of structural framework whose aim is to enhance the probability of constructive implementation of GSCM in the field chemical industry in Bangladesh. Therefore, this framework evaluates the appropriate interrelationship along with the drivers of GSCM in the chemical industry. In total, eight drivers were finalized from an associated literature review with the help of survey and by taking expert opinions via the Delphi methodology. In addition to MICMAC analysis, the driving and the dependence powers for all the drivers were determined. Moreover, the structural frameworks for the drivers were developed by means of total interpretive structural modeling (TISM) technique. As a result, the findings indicate that the most significant driver was supplier pressure and willingness and the most important barrier was high cost. Finally, the main objective of this research is expected to help industrial managers to evaluate and understand the critical areas where they should emphasize to implement GSCM in the chemical industry.