Annual CO-emissions of combined pellet and solar heating systems

Emissions are an important aspect of a pellet heating system. High carbon monoxide emissions are often caused by unnecessary cycling of the burner when the burner is operated below the lowest combustion power. Combining pellet heating systems with a solar heating system can significantly reduce cycling of the pellet heater and avoid the inefficient summer operation of the pellet heater. The aim of this paper was to study CO-emissions of the different types of systems and to compare the yearly CO-emissions obtained from simulations with the yearly CO-emissions calculated based on the values that are obtained by the standard test methods. The results showed that the yearly CO-emissions obtained from the simulations are significant higher than the yearly CO-emissions calculated based on the standard test methods. It is also shown that for the studied systems the average emissions under these realistic annual conditions were greater than the limit values of two Eco-labels. Furthermore it could be seen that is possible to almost halve the CO-emission if the pellet heater is combined with a solar heating system.

Emissions Characterisation of residential pellet boilers during start-up and stop periods

In this study, gaseous emissions and particles are measured during start-up and stop periods for an over-fed boiler and an under-fed boiler. Both gaseous and particulate matter emissions are continuously measured in the laboratory. The measurement of gaseous emissions includes oxygen (O2), carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxide and (NO). The emissions rates are calculated from measured emissions concentrations and flue gas flow. The behaviours of the boilers during start-up and stop periods are analysed and the emissions are characterised in terms of CO, NO, TOC and particles (PM2.5 mass and number). The duration of the characterised periods vary between two boilers due to the difference in type of ignition and combustion control. The under-fed boiler B produces higher emissions during start-up periods than the over-fed boiler A. More hydrocarbon and particles are emitted by the under-fed boiler during stop periods. Accumulated mass of CO and TOC during start-up and stop periods contribute a major portion of the total mass emitted during whole operation. However, accumulated mass of NO and PM during start-up and stop periods are not significant as the duration of emission peak is relatively short.

EMISSIONS CHARACTERISTICS OF A RESIDENTIAL PELLET BOILER AND A STOVE

Gaseous and particulate emissions from a residential pellet boiler and a stove are measured at a realistic 6-day operation sequence and during steady state operation. The aim is to characterize the emissions during each phase in order to identify when the major part of the emissions occur to enable actions for emission reduction where the savings can be highest. The characterized emissions comprised carbon monoxide (CO), nitrogen oxide (NO), total organic carbon (TOC) and particulate matter (PM 2.5). In this study, emissions were characterised by mass concentration and emissions during start-up and stop phases were also presented in accumulated mass. The influence of start-up and stop phases on the emissions, average emission factors for the boiler and stove were analysed using the measured data from a six-days test. The share of start-up and stop emissions are significant for CO and TOC contributing 95% and 89% respectively at the 20kW boiler and 82% and 89% respectively at the 12 kW stove. NO and particles emissions are shown to dominate during stationary operation.

Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts

We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.