To demonstrate the atmospheric emission characteristics of cadmium (Cd), which is considered an important contaminant to human health and environment, a comprehensive emission inventory of Cd has been established by applying the best available emission factors and activity data for the first time. This inventory covers major anthropogenic sources in China and a bottom-up approach is adopted to compile the inventory for the sources where possible. The total emissions of Cd are estimated at about 743.77 metric tons for the year 2009, of which the contributions of industrial processes and combustion sources are approximately 56.6 and 43.4%, respectively. Nonferrous metals smelting including copper, lead, and zinc, ranks as the leading source accounting for about 40.6% of the total. The high contribution results from the rapid growth of nonferrous metallurgical industry that reflects a new focus of Cd emission pollution in China. Cd emissions from coal combustion are estimated at approximately 273.69 metric tons, with a share of 36.8%, in which industrial coal-burning sector is thought to be the primary source. Moreover, Cd emissions are spatially allocated onto grid cells with a resolution of 0.5o×0.5o, indicating that the emissions are mainly distributed among the regions of eastern, central and southern China. In addition, the uncertainties in the inventory are quantified by using a Monte Carlo simulation, and the overall uncertainty falls within a range of −15 to 48%. It implies that more field tests for industrial coal combustion and metals smelting process are very necessary.

The South Pars zone in Iran encompasses the largest gas refineries and petrochemical complexes in the world. In the South Pars zone, elevated concentrations of reactive hydrocarbons co-emitted with nitrogen oxides from industrial facilities lead to substantial ozone production downwind. To understand the role of these emissions on the ozone formation and, to formulate appropriate control strategies in this zone, emissions of precursors of ozone were quantified, and compounds that deserve relatively more attention were determined. To do this, first, a fully-speciated ozone precursors emission inventory was prepared to provide necessary input data for air quality simulation models. Then, the emission inventory was weighted by emitted mass and incremental reactivity scales to determine which compounds deserve relatively more detailed representation in the modeling. Afterward, a photochemical model was applied to determine the ozone sensitivity to its precursors. Finally, source apportionment was done for the most important compounds. Additionally, the reactivity-based inventory was compared with other regions. Results show that nitrogen oxides-sensitive chemistry is dominant in the zone thus the most effective control strategy is the mitigation of the nitrogen oxides emissions. Gas refinery plants have a larger share than petrochemical plants in the nitrogen oxides emission and, the gas turbines are the main sources of nitrogen oxides emission in this region. Emitted volatile organic compounds contain more highly reactive species in comparison with the ambient air composition of typical urban areas and areas with gas production industries. Propylene and ethylene have the most contribution to the ozone formation in comparison with other volatile organic compounds. The major sources of their emissions are the olefin processes and polymer production plants.

Estimation of coal power plant emissions is a vital step to visualise emission trends with respect to specific policy implementations and technological interventions so that their effectiveness in terms of emission reductions and ambient air quality improvement can be quantitatively assessed. However, research work concerning stack emission estimations specifically for coal power plants in India is limited. To bridge the present gap, we present a plant-specific multi-year and multi-parameter Coal Power Stack Emission Model. This model has been developed to explore current and historical annual stack emissions from a coal-based thermal power plant taking into account essential variables such as coal characteristics, process attributes and control equipment aspects, which can significantly influence the stack emissions. This study concentrates on development of Coal Power Stack Emission model and its application for the estimation of plant and year-specific emission factors and stack emissions for a coal-based power plant at Badarpur, New Delhi, for the period of 2000–2008. The validation of Coal Power Stack Emission model has also been successfully carried out by comparing the trends of percentage change in annual emission estimates and observed ambient air concentrations of total suspended particles, PM10 and sulphur dioxide at two nearby air quality monitoring stations, namely Siri Fort and Nizamuddin.