A spatial assessment of the forest carbon budget for Ukraine

Mitigation and Adaptation Strategies for Global Change - The spatial representation of forest cover and forest parameters is a prerequisite for undertaking a systems approach to the full and...     

High-resolution spatial distribution of greenhouse gas emissions in the residential sector

The development of high-resolution greenhouse gas (GHG) inventories is an important step towards emission reduction in different sectors. However, most of the spatially explicit approaches that have been developed to date produce outputs at a coarse resolution or do not disaggregate the data by sector. In this study, we present a methodology for assessing GHG emissions from the residential sector by settlements at a fine spatial resolution. In many countries, statistical data about fossil fuel consumption is only available at the regional or country levels. For this reason, we assess energy demand for cooking and water and space heating for each settlement, which we use as a proxy to disaggregate regional fossil fuel consumption data. As energy demand for space heating depends heavily on climatic conditions, we use the heating degree day method to account for this phenomenon. We also take the availability of energy sources and differences in consumption patterns between urban and rural areas into account. Based on the disaggregated data, we assess GHG emissions at the settlement level using country and regional specific coefficients for Poland and Ukraine, two neighboring countries with different energy usage patterns. In addition, we estimate uncertainties in the results using a Monte Carlo method, which takes uncertainties in the statistical data, calorific values, and emission factors into account. We use detailed data on natural gas consumption in Poland and biomass consumption for several regions in Ukraine to validate our approach. We also compare our results to data from the EDGAR (Emissions Database for Global Atmospheric Research), which shows high agreement in places but also demonstrates the advantage of a higher resolution GHG inventory. Overall, the results show that the approach developed here is universal and can be applied to other countries using their statistical information.

     

Simulating the spatial distribution of pollutant loads from pig farming using an agent-based modeling approach

Environmental Science and Pollution Research - This research developed an agent-based model (ABM) for simulating pollutant loads from pig farming. The behavior of farmer agents was captured using...     

Health risk assessment of occupational exposure to particulate-phase polycyclic aromatic hydrocarbons associated with Chinese, Malay and Indian cooking

Food cooking using liquefied petroleum gas (LPG) has received considerable attention in recent years since it is an important source of particulate air pollution in indoor environments for non-smokers. Exposure to organic compounds such as polycyclic aromatic hydrocarbons (PAHs) contained in particles is of particular health concern since some of these compounds are suspected carcinogens. It is therefore necessary to chemically characterize the airborne particles emitted from gas cooking to assess their possible health impacts. In this work, the levels of fine particulate matter (PM(2.5)) and 16 priority PAHs were determined in three different ethnic commercial kitchens, specifically Chinese, Malay and Indian food stalls, where distinctive cooking methods were employed. The mass concentrations of PM(2.5) and PAHs, and the fraction of PAHs in PM(2.5) were the highest at the Malay stall (245.3 microg m(-3), 609.0 ng m(-3), and 0.25%, respectively), followed by the Chinese stall (201.6 microg m(-3), 141.0 ng m(-3), and 0.07%), and the Indian stall (186.9 microg m(-3), 37.9 ng m(-3), and 0.02%). This difference in the levels of particulate pollution among the three stalls may be attributed to the different cooking methods employed at the food stalls, the amount of food cooked, and the cooking time, although the most sensitive parameter appears to be the predominant cooking method used. Frying processes, especially deep-frying, produce more air pollutants, possibly due to the high oil temperatures used in such operations. Furthermore, it is found that frying, be it deep-frying at the Malay stall or stir-frying at the Chinese stall, gave rise to an abundance of higher molecular weight PAHs such as benzo[b]fluoranthene, indeno[1,2,3-cd]pyrene and benzo[g,h,i]perylene whereas low-temperature cooking, such as simmering at the Indian stall, has a higher concentration of lower molecular weight PAHs. In addition, the correlation matrices and diagnostic ratios of PAHs were calculated to determine the markers of gas cooking. To evaluate the potential health threat due to inhalation exposure from the indoor particulate pollution, excess lifetime cancer risk (ELCR) was also calculated for an exposed individual. The findings suggest that cooking fumes in the three commercial kitchens pose adverse health effects.     

GIS-ASSISTED REGRESSION ANALYSIS TO IDENTIFY SOURCES OF SELENIUM IN STREAMS1

ABSTRACT: Using a geographic information system, a regression model has been developed to identify and to assess potential sources of selenium in the Kendrick Reclamation Project Area, Wyoming. A variety of spatially distributed factors was examined to determine which factors are most likely to affect selenium discharge in tributaries to the North Platte River. Areas of Upper Cretaceous Cody Shale and Quaternary alluvial deposits and irrigated land, length of irrigation canals, and boundaries of hydrologic subbasins of the major tributaries to the North Platte River were digitized and stored in a geographic information system. Selenium concentrations in samples of soil, plant material, ground water, and surface water were determined and evaluated. The location of all sampling sites was digitized and stored in the geographic information system, together with the selenium concentrations in samples. A regression model was developed using stepwise multiple regression of median selenium discharges on the physical and chemical characteristics of hydrologic subbasins. Results indicate that the intensity of irrigation in a hydrologic subbasin, as determined by area of irrigated land and length of irrigation delivery canals, accounts for the largest variation in median selenium discharges among subbasins. Tributaries draining hydrologic subbasins with greater intensity of irrigation result in greater selenium discharges to the North Platte River than do tributaries draining subbasins with lesser intensity of irrigation.     

Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

Greenhouse gas (GHG) inventories at national or provincial levels include the total emissions as well as the emissions for many categories of human activity, but there is a need for spatially explicit GHG emission inventories. Hence, the aim of this research was to outline a methodology for producing a high-resolution spatially explicit emission inventory, demonstrated for Poland. GHG emission sources were classified into point, line, and area types and then combined to calculate the total emissions. We created vector maps of all sources for all categories of economic activity covered by the IPCC guidelines, using official information about companies, the administrative maps, Corine Land Cover, and other available data. We created the algorithms for the disaggregation of these data to the level of elementary objects such as emission sources. The algorithms used depend on the categories of economic activity under investigation. We calculated the emissions of carbon, nitrogen sulfure and other GHG compounds (e.g., CO₂, CH₄, N₂O, SO₂, NMVOC) as well as total emissions in the CO₂-equivalent. Gridded data were only created in the final stage to present the summarized emissions of very diverse sources from all categories. In our approach, information on the administrative assignment of corresponding emission sources is retained, which makes it possible to aggregate the final results to different administrative levels including municipalities, which is not possible using a traditional gridded emission approach. We demonstrate that any grid size can be chosen to match the aim of the spatial inventory, but not less than 100 m in this example, which corresponds to the coarsest resolution of the input datasets. We then considered the uncertainties in the statistical data, the calorific values, and the emission factors, with symmetric and asymmetric (lognormal) distributions. Using the Monte Carlo method, uncertainties, expressed using 95% confidence intervals, were estimated for high point-type emission sources, the provinces, and the subsectors. Such an approach is flexible, provided the data are available, and can be applied to other countries.

     

Synthesis of butyl butyrate in 93 % yield by <Emphasis Type="Italic">Thermomyces lanuginosus</Emphasis> lipase on waste eggshells

There is a high demand for immobilized enzymes in the industry because it is a green technology, it improves the efficiency of the crude enzyme and it minimizes the step of product recovery. Selection of a suitable carrier for enzyme immobilization is crucial. Eggshells are abundantly available as an organic waste. Here, lipase from Thermomyces lanuginosus was immobilized on eggshell to produce butyl butyrate. We evaluated the effect of lipase loading, from 0.5 to 3.0 %, size of eggshells, lower than 1, 1–2 and 2–4 mm, and temperature, from 30 to 50 °C. Results show that the optimum conditions calculated by response surface methodology analysis for butyl butyrate synthesis were 40 % w/v of immobilized lipase loading and 0.2 M of substrate concentration at 38 °C during 24 h. The predicted yield was 92.78 %, and the yield obtained during synthesis was 93.48 %.