Estimation of greenhouse gas emissions from industrial wastewater treatment plants

The outcome of Kyoto protocol and other National and International agreements influence the design and operation of wastewater treatment facilities by restricting their greenhouse gas (GHG) emissions. Wastewater treatment plants (WWTPs) are recognized as one of the larger minor sources of GHG emissions that produce CO 2 , CH 4 , and N 2 O during the treatment processes. The overall on-site and off-site greenhouse gas (GHG) emissions by WWTPs of food processing industry were estimated by using an elaborate mathematical model. Three different types of treatment systems were examined in this study which included aerobic, anaerobic, and hybrid anaerobic/aerobic processes. The overall on-site emissions were 1952, 1992, and 2435 kg CO 2 e/d while the off-site emissions were 1313, 4631, and 5205 kg CO 2 e/d for the aerobic, anaerobic and hybrid treatment systems respectively. The on-site biological processes made the highest contribution to GHG emissions in the aerobic treatment system while the highest emissions in anaerobic and hybrid treatment systems were obtained by off-site GHG emissions due to on-site material usage. Biogas recovery and reuse as fuel were shown to cover the total energy needs of the treatment plants for aeration, heating and electricity for all three types of operations, and considerably reduced GHG emissions by 512, 673, and 988 kg CO 2 e/d from a total of 3265, 6623, and 7640 kg CO 2 e/d for aerobic, anaerobic, and hybrid treatment systems, respectively. In the end, recommendations were given on feasible approaches to reduce GHG emissions from WWTPs

Logarithmic radiative effect of water vapor and spectral kernels

Radiative kernels have become a useful tool in climate analysis. A set of spectral kernels is calculated using a moderate resolution atmospheric transmission code MODTRAN and implemented in diagnosing spectrally decomposed global outgoing longwave radiation (OLR) changes. It is found that the effect of water vapor on the OLR is in proportion to the logarithm of its concentration. Spectral analysis discloses that this logarithmic dependency mainly results from water vapor absorption bands (0–560 cm−1 and 1250–1850 cm−1), while in the window region (800–1250 cm−1), the effect scales more linearly to its concentration. The logarithmic and linear effects in the respective spectral regions are validated by the calculations of a benchmark line‐by‐line radiative transfer model LBLRTM. The analysis based on LBLRTM‐calculated second‐order kernels shows that the nonlinear (logarithmic) effect results from the damping of the OLR sensitivity to layer‐wise water vapor perturbation by both intra‐ and inter‐layer effects. Given that different scaling approaches suit different spectral regions, it is advisable to apply the kernels in a hybrid manner in diagnosing the water vapor radiative effect. Applying logarithmic scaling in the water vapor absorption bands where absorption is strong and linear scaling in the window region where absorption is weak can generally constrain the error to within 10% of the overall OLR change for up to eightfold water vapor perturbations

Validation of a weather forecast model at radiance level against satellite observations allowing quantification of temperature, humidity and cloud related biases.

An established radiative transfer model (RTM) is adapted for simulating all-sky infrared radiancespectra from the Canadian Global Environmental Multiscale (GEM) model in order to validate its forecasts atthe radiance level against Atmospheric InfraRed Sounder (AIRS) observations. Synthetic spectra aregenerated for 2 months from short-term (3–9 h) GEM forecasts