Status of the Southern Carpathian forests in the long-term ecological research network

Air pollution, bulk precipitation, throughfall, soil condition, foliar nutrients, as well as forest health and growth were studied in 2006–2009 in a long-term ecological research (LTER) network in the Bucegi Mountains, Romania. Ozone (O₃) was high indicating a potential for phytotoxicity. Ammonia (NH₃) concentrations rose to levels that could contribute to deposition of nutritional nitrogen (N) and could affect biodiversity changes. Higher that 50% contribution of acidic rain (pH?<?5.5) contributed to increased acidity of forest soils. Foliar N concentrations for Norway spruce (Picea abies), Silver fir (Abies alba), Scots pine (Pinus sylvestris), and European beech (Fagus sylvatica) were normal, phosphorus (P) was high, while those of potassium (K), magnesium (Mg), and especially of manganese (Mn) were significantly below the typical European or Carpathian region levels. The observed nutritional imbalance could have negative effects on forest trees. Health of forests was moderately affected, with damaged trees (crown defoliation >25%) higher than 30%. The observed crown damage was accompanied by the annual volume losses for the entire research forest area up to 25.4%. High diversity and evenness specific to the stand type’s structures and local climate conditions were observed within the herbaceous layer, indicating that biodiversity of the vascular plant communities was not compromised.     

Mean Vehicle Speed Distributions for the Spatiotemporal Estimation of Exhaust Emissions

Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality.