Industrial SO2 emission monitoring through a portable multichannel gas analyzer with an optimized retrieval algorithm

SO2 variability over a large concentration range and interferences from other gases have been major limitations in industrial SO2 emission monitoring. This study demonstrates accurate industrial SO2 emission monitoring through a portable multichannel gas analyzer with an optimized retrieval algorithm. The proposed analyzer features a large dynamic measurement range and correction of interferences from other coexisting infrared absorbers such as NO, CO, CO2, NO2, CH4, HC, N2O, and H2O. The multichannel gas analyzer measures 11 different wavelength channels simultaneously to correct several major problems of an infrared gas analyzer including system drift, conflict of sensitivity, interferences among different infrared absorbers, and limitation of measurement range. The optimized algorithm uses a third polynomial instead of a constant factor to quantify gas-to-gas interference. Measurement results show good performance in the linear and nonlinear ranges, thereby solving the problem that the conventional interference correction is restricted by the linearity of the intended and interfering channels. The results imply that the measurement range of the developed multichannel analyzer can be extended to the nonlinear absorption region. The measurement range and accuracy are evaluated through experimental laboratory calibration. Excellent agreement was achieved, with a Pearson correlation coefficient (r(2)) of 0.99977 with a measurement range from approximately 5 to 10 000 ppmv and a measurement error of less than 2 %. The instrument was also deployed for field measurement. Emissions from three different factories were measured. The emissions of these factories have been characterized by different coexisting infrared absorbers, covering a wide range of concentration levels. We compared our measurements with commercial SO2 analyzers. Overall, good agreement was achieved

A New Control Interaction Phenomenon in Large-Scale Type-4 Wind Park

ABSTRACT: This paper demonstrates the risk of a new control interaction phenomenon between a large- scale type-4 wind park (WP) and a 500 kV transmission grid at super-synchronous frequency range. This study aims at (i) using the impedance-based stability assessment (IBSA) method to investigate this new interaction phenomenon; and (ii) analyzing the impact of various transmission grid topologies, WP operating conditions as well as wind turbine (WT) converter control parameters on the severity of the interaction. For ultimate accuracy, the frequency-dependent impedance characteristics of the WP are extracted using the electromagnetic transient (EMT)-type impedance scanning instead of simplified analytical model. The performed analyses demonstrate that the WP generation capacity, length of the transmission lines, applied series and shunt compensation levels, presence of parallel lines, and grid side converter (GSC) control parameters of the WT, can significantly affect the identified control interaction risk. The obtained results are validated through detailed EMT simulations. Although the type-4 WP is considered in this paper, the presented results can be generalized to any inverter-based resource (IBR) with full-size converter (FSC), such as photovoltaic (PV) power stations

Imperfect Information and Cross-Autocorrelation among Stock Prices.

The author develops a model to explain why stock returns are positively cross-autocorrelated. When marketmakers observe noisy signals about the value of their stocks but cannot instantaneously condition prices on the signals of other stocks, which contain marketwide information, the pricing error of one stock is correlated with the other signals. As marketmakers adjust prices after observing true values or previous price changes of other stocks, stock returns become positively cross-autocorrelated. If the signal quality differs among stocks, the cross-autocorrelation pattern is asymmetric. The author shows that both own- and cross-autocorrelations are higher when market movements are larger. Copyright 1993 by American Finance Association.

Trade size, order imbalance, and the volatility-volume relation

This paper examines the roles of the number of trades, size of trades, and order imbalance (buyer- versus seller-initiated trades) in explaining the volatility-volume relation for a sample of NYSE and Nasdaq stocks. Our results reconfirm the significance of the size of trades, beyond that of the number of trades, in the volatility-volume relation on both markets. After controlling for the return impact of order imbalance, the volatility-volume relation becomes much weaker. For NYSE stocks, the order imbalance in large trade size categories affects the return more than in smaller size categories. For Nasdaq stocks, the largest return impact comes from the order imbalance in maximum-sized Small Order Execution System (SOES) trades. (C) 2000 Elsevier Science S.A. All rights reserved. JEL classification. G10; G12; G13

Price informativeness and stock return synchronicity: Evidence from the pricing of seasoned equity offerings

We investigate what stock return synchronicity reflects in terms of price informativeness by examining its effect on the pricing of seasoned equity offerings (SEOs). Based on 5,087 SEOs from 1984 to 2007, we find a significantly negative relation between stock return synchronicity (estimated as the logit transformation of the R-squared statistic from a two-factor regression) and SEO discounts (the percentage differences between pre-offer day closing prices and offer prices). The negative relation is strongest when there is no analyst coverage, and it declines as analyst coverage increases. This shows that stock price is more informative when stock return synchronicity is higher and also that information asymmetry can be mitigated by analyst coverage. We further decompose stock return synchronicity into the market comovement and industry comovement components and find that both components are equally important in affecting SEO discounts. (C) 2014 Elsevier B.V. All rights reserved