Mass emission

Design nd Operation. The destruction efficiency of a catalytic oxidation system is determined by the system design. It is impossible to predict a priori the temperature and residence time needed to obtain a given level of conversion of a mixture in a catalytic oxidation system. Control efficiency is determined by process characteristics such as concentration of VOCs emitted, flow rate, process fluctuations that may occur in flow rate, temperature, concentrations of other materials in the process stream, and the governing permit regulation, such as the mass-emission limit. Design and operational characteristics that can affect the destmction efficiency include inlet temperature to the catalyst bed, volume of catalyst, and quantity and type of noble metal or metal oxide used. 

For determination of the total mass-emission rate of SO9, the moisture content and the volumetric flow rate of the exhaust gas stream must also be measured. 

A samphng probe is placed at any location in the stack, and a grab sample is collected in an evacuated flask. This flask contains a solution of siilfiiric acid and hydrogen peroxide, which reacts with the NO. The volume and moisture content of the exhaust-gas stream must be determined for calculation of the total mass-emission rate. The sample is sent to a laboratoiy, where the concentration of nitrogen oxides, except nitrons oxide, is determined colorimetrically. 

The three coefficients relating to x-rays in Equation 4-13 may conveniently be combined into a mass emission coefficient, k - If this is done, the equation becomes... 

Mass Emissions of Pollutants from E-Waste Processed in China and Human Exposure Assessment... 

Keywords China, Electronic waste (e-waste), Human exposure, Mass emission, Pollutant... 

Mass Emissions of Organic Pollutants from E-Waste in China. 295... 

To obtain the mass emissions of pollutants from e-waste recycling processes, it is essential that the inputs of pollutants are truly e-waste related. To fulfill this requirement, a causal analysis is desirable. However, the concept of causation is rather problematic because causal mechanisms are complex [26]. Nonetheless, we are compelled to identify causes, in an attempt to minimize the uncertainties associated with our estimates. In this chapter, the strict empiricist, David Hume s empirical criterion, was adopted. This approach requires only a combination of (1) e-waste processing and environmental pollution are associated in space and time (contiguity) (2) e-waste processing precede to environmental pollution (temporal succession) and (3) e-waste processing is always conjoined with environmental pollution (consistent conjunction). These are always the cases judged from a number of previous studies [6, 27-35]. 

Based on the values of Cpcdd/fs [46], Ccipahs [38], and CBfrs in e-waste, the annual mass emissions of selected PCDD/F and C1PAH congeners and BFRs from e-waste are estimated (Table 3). The lowest annual mass emission of PBDEs is about 82,207 tons/year, with 70,607 tons/year from importation and 11,600 tons/ year from domestic generation (Table 3). Nona- and deca-BDEs are the most important congeners as they are the major constituents of BRFs in electronic equipment [77]. In addition, the annual mass emissions of PBBs, TBBPA, and PBPs are also estimated with the same procedure (Table 3). Obviously, importation is responsible for the majority of annual mass emissions of e-waste-derived organic pollutants in China (Table 3). 

---