Household solid waste combustion with wood increases particulate trace metal and lung deposited surface area emissions.

In households, municipal solid waste (MSW) is often burned along with wood to get rid of waste, to help in ignition or simply to reduce fuel costs. The aim of this study was to characterize the influence of household waste combustion, along with wood, on the physical and chemical properties of particulate emissions in a flue gas of a masonry heater. The MSW burning alongside wood increased average particulate matter (PM) mass (65%), lung deposited surface areas (LDSA, 15%), black carbon (BC, 65%) concentrations and the average particle size in the flue gas. The influence of MSW was smaller during ignition and burning phases, but especially during fuel additions, the mass, number, and LDSA concentrations increased significantly and their size distributions moved towards larger particles. For wood burning the trace metal emissions were relatively low, but significant increase (3.3-179 -fold increase over cycle) was seen when MSW was burned along the wood. High ratios were observed especially during fuel addition phases but, depending on compounds, also during ignition and burning end phases. The highest ratios were observed for chloride compounds (HCl, KCl, NaCl). The observed increase in light-absorbing particle, trace metal and BC concentrations in flue gas when adding wood with MSW are likely to have negative impacts on air quality, visibility, human health and climate. Furthermore, metals may also affect the condition and lifetime of the burning device due to corrosion.

Effect of the 2018 European drought on methane and carbon dioxide exchange of northern mire ecosystems.

We analysed the effect of the 2018 European drought on greenhouse gas (GHG) exchange of five North European mire ecosystems. The low precipitation and high summer temperatures in Fennoscandia led to a lowered water table in the majority of these mires. This lowered both carbon dioxide (CO2) uptake and methane (CH4) emission during 2018, turning three out of the five mires from CO2 sinks to sources. The calculated radiative forcing showed that the drought-induced changes in GHG fluxes first resulted in a cooling effect lasting 15-50 years, due to the lowered CH4 emission, which was followed by warming due to the lower CO2 uptake. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Contributions of climate, leaf area index and leaf physiology to variation in gross primary production of six coniferous forests across Europe: a model-based analysis.

Gross primary production (GPP) is the primary source of all carbon fluxes in the ecosystem. Understanding variation in this flux is vital to understanding variation in the carbon sink of forest ecosystems, and this would serve as input to forest production models. Using GPP derived from eddy-covariance (EC) measurements, it is now possible to determine the most important factor to scale GPP across sites. We use long-term EC measurements for six coniferous forest stands in Europe, for a total of 25 site-years, located on a gradient between southern France and northern Finland. Eddy-derived GPP varied threefold across the six sites, peak ecosystem leaf area index (LAI) (all-sided) varied from 4 to 22 m(2) m(-2) and mean annual temperature varied from -1 to 13 degrees C. A process-based model operating at a half-hourly time-step was parameterized with available information for each site, and explained 71-96% in variation between daily totals of GPP within site-years and 62% of annual total GPP across site-years. Using the parameterized model, we performed two simulation experiments: weather datasets were interchanged between sites, so that the model was used to predict GPP at some site using data from either a different year or a different site. The resulting bias in GPP prediction was related to several aggregated weather variables and was found to be closely related to the change in the effective temperature sum or mean annual temperature. High R(2)s resulted even when using weather datasets from unrelated sites, providing a cautionary note on the interpretation of R(2) in model comparisons. A second experiment interchanged stand-structure information between sites, and the resulting bias was strongly related to the difference in LAI, or the difference in integrated absorbed light. Across the six sites, variation in mean annual temperature had more effect on simulated GPP than the variation in LAI, but both were important determinants of GPP. A sensitivity analysis of leaf physiology parameters showed that the quantum yield was the most influential parameter on annual GPP, followed by a parameter controlling the seasonality of photosynthesis and photosynthetic capacity. Overall, the results are promising for the development of a parsimonious model of GPP.