Vietnam is one of the countries suffering from the most serious adverse effects due to climate change and sea level rise. The main cause of climate change is the increased activities generating greenhouse gases. Organic waste is the main source of carbon dioxide emission, which has the largest concentration among different kinds of greenhouse gases in the earth’s atmosphere. The conversion of organic waste and biomass into energy contributes not only to supply cleaner energy but also to reduce emissions of greenhouse gases. Vietnam has a large potential of biomass and agricultural by-products. The technologies to turn biomass into different kinds of bio-energies were developed and applied all over the world. Biogas was called as "brown revolution" in the field of new energy. Biogas production technology now has been studied and applied widely in the world, particularly in developing countries with warm climate that is suitable for anaerobic fermentation of organic waste. The biogas digester can be built with any capacity, needs small investment and the input materials are widely available. The biogas energy is used for many purposes such as cooking, lighting, running engines, etc. It is a production technology quite consistent with the economy of developing countries and really brings to life more civilized and convenient to rural areas. / Việt Nam là một trong những quốc gia bị tác động nghiêm trọng nhất do biến đổi khí hậu và nước biển dâng cao. Nguyên nhân chính của biến đổi khí hậu là các hoạt động gia tăng tạo ra các khí gây hiệu ứng nhà kính. Chất thải hữu cơ là nguồn chính phát thải khí carbon dioxide có nồng độ lớn nhất trong số các loại khí gây hiệu ứng nhà kính khác nhau trong bầu khí quyển của trái đất. Việc chuyển đổi chất thải hữu cơ và sinh khối thành năng lượng góp phần không chỉ cung cấp năng lượng sạch hơn mà còn giảm phát thải khí gây hiệu ứng nhà kính. Việt Nam có một tiềm năng lớn về sinh khối và phụ phẩm nông nghiệp. Các công nghệ biến sinh khối thành các loại năng lượng sinh học khác nhau đã được phát triển và áp dụng rộng rãi trên thế giới. Khí sinh học được gọi là "cuộc cách mạng màu nâu" trong lĩnh vực năng lượng mới. Công nghệ sản xuất khí sinh học đã được nghiên cứu và áp dụng rộng rãi trên thế giới, đặc biệt là ở các nước đang phát triển với nhiệt độ khí hậu nhiệt đới phù hợp cho quá trình lên men kỵ khí các chất thải hữu cơ để sản xuất khí sinh học. Bình phản ứng tạo khí sinh học có thể được xây dựng với công suất bất kỳ, nhu cầu đầu tư nhỏ, các nguyên liệu đầu vào sẵn có. Năng lượng khí sinh học đã được sử dụng cho nhiều mục đích như thắp sáng, nấu ăn, chạy động cơ, v.v... Đây là hoạt động sản xuất khá phù hợp với nền kinh tế của các nước đang phát triển và thực sự đem lại cuộc sống văn minh hơn và tiện lợi đến các khu vực nông thôn.

Die Arbeit befasst sich mit der Anwendung der dielektrischen Erwärmung mittels Radiowellen auf unterschiedlichen Gebieten der Umwelttechnik. Im Mittelpunkt stehen die Aufheizung von Schüttbetten aus Adsorbenzien und Katalysatoren sowie die thermisch unterstützte Reinigung kontaminierter Böden und Feststoffe, insbesondere unter dem Gesichtspunkt des Einsatzes bei in-situ-Sanierungsvorhaben. Aus stofflicher Sicht wurde die Erwärmung technisch relevanter Feststoffe wie Aktivkohlen, Molekularsieben (Zeolithen) und anderer Katalysatoren ebenso wie die Behandlung von Modellböden und realen Bodenproben untersucht. Die durchgeführten physikalisch-chemischen Grundlagenuntersuchungen bezogen sich vor allem auf die Fragen, inwiefern sich die Radiowellen-Erwärmung von konventionellen Heizmethoden unterscheidet, ob und unter welchen Bedingungen eine selektive Erwärmung einzelner Feststoffkomponenten (z.B. Katalysatorkomponenten oder Partikel) möglich ist und welchen Einfluss der Wassergehalt und die Temperatur auf den Energieeintrag, den Schadstofftransport sowie den Prozess der Schadstoffdesorption besitzen. Der verfahrenstechnische Aspekt der Arbeit umfasst die Entwicklung der Methode der Radiowellen-Erwärmung vom Labor- bis in den Feldmaßstab, die Entwicklung und den Test eines praxistauglichen und automatisierten Systems zur Feststofferwärmung, die simultane Anwendung mehrerer Frequenzen elektromagnetischer Felder zur optimierten Erwärmung mit größerer Temperaturhomogenität, die Erprobung unterschiedlicher Elektrodengeometrien sowie die Durchführung von Sanierungsvorhaben mit Modellcharakter.

Der vorliegende Begleitbericht dokumentiert die Fortschreibung der Sächsischen Sortierrichtlinie 1998 in der Form, dass neben der neuen Sächsischen Sortierrichtlinie 2014 auch Gründe und Aspekte der Überarbeitung dargestellt werden. Außerdem sollen den Anwendern der Sächsischen Sortierrichtlinie 2014 weiterführende Informationen, wie beispielsweise modellhafte Berechnungen bei einzelnen Fragestellungen, vorgestellt wer-den.

The construction of Baku-Tbilisi-Ceyhan (BTC) Oil and South Caucasus Gas (SCP) pipelines was completed in 2005. The Azerbaijan section of BTC Oil and SCP Gas pipelines is 442 km long and 44 m wide corridor named as the Right-of-Way. BTC and SCP pipelines are aligned parallel to each other within the same 44m corridor. The construction process of the pipelines significantly disturbed vegetation and soil cover along Right-of-Way of pipelines. The revegetation and erosion control measures were conducted after the completion of construction to restore the disturbed footprints of construction activities. The general goals of the present studies, dedicated to the environmental monitoring of revegetation and planning of erosion control measures were: to evaluate the status of the revegetation in 2007 since the completion of the construction activities in 2005, to determine the climate and ground factors controlling the vegetation regrowth and to predict erosion-prone areas along Right-of-Way of pipelines. Regression and root mean square error analysis between the Normalized Difference Vegetation Index (NDVI) of IKONOS images acquired in 2007 and in-situ estimations of vegetation cover percentage revealed R2 equal to 0.80 and RMSE equal to 6% which were optimal for the normalization of NDVI to vegetation cover. The total area of restored vegetation cover between 2005 and 2007 was 8.9 million sq. m. An area of 10.7 million sq. m. of ground vegetation needed restoration in order to comply with the environmental acceptance criteria. Based on the Global Spatial Regression Model, precipitation, land surface temperature and evapotranspiration were determined as the main climate factors controlling NDVI of grasslands along Right-of-Way of pipelines. In case of croplands, precipitation, evapotranspiration and annual minimum temperature were determined as the main factors controlling NDVI of croplands. The regression models predicting NDVI for grasslands and croplands were also formulated. The Geographically Weighted Regression analyses in comparison with the global regression models results clearly revealed that the relationship between NDVI of grasslands and croplands and the predictor variables was spatially non-stationary along the corridor of pipelines. Even though the observed R2 value between elevation and NDVI of grasslands was low (R2= 0.14), the accumulation of the largest NDVI patterns was observed higher than 150m elevation. This revealed that elevation has non-direct control of NDVI of grasslands through its control of precipitation and temperature along the grasslands of Right-of-Way. The spatial distribution percentage of NDVI classes within slope aspect categories was decreasing in the southern directions of slope faces. Land surface temperature was decreasing with elevation but no particular patterns of land surface temperature in the relationship with NDVI accumulation within the aspect categories were observed. Aspect categories have non-direct control of NDVI and there are some other factors apart from land surface temperature which require further investigations. Precipitation was determined to be controlling the formation of topsoil depth and the topsoil obviously controls the VC growth of grasslands as one of the main ground factors. The regression analysis between NDVI of grasslands and croplands with groundwater depth showed very low correlation. But the clustered patterns of vegetation cover were observed in the relationship with groundwater depth and soil moisture for both grasslands and croplands. The modeling of groundwater depth relative to soil moisture and MODIS NDVI of grasslands determined that the threshold of groundwater depth for vegetation growth is in the range of 1-5 m. MODIS NDVI and soil moisture did not reveal a significant correlation. Soil moisture revealed R2 equal to 0.34 with elevation, R2 equal to 0.23 with evapotranspiration, R2 equal to 0.57 with groundwater depth and R2 equal to 0.02 with precipitation. This allowed to suspect that precipitation is not the main factor controlling soil moisture whereas elevation, evapotranspiration and groundwater depth have non-direct control of soil moisture. Therefore, soil moisture has also non-direct control of vegetation cover growth along the corridor of pipelines. The variations of soil moisture in the 1-3 m soil depth range may have the threshold of depth controlling vegetation cover regrowth and this requires more detailed soil moisture data for further investigations. The reliability of the Global Spatial Regression Model and Geographically Weighted Regression predictions is limited by the MODIS images spatial resolution equal to 250 m and spectral characteristics. The Morgan-Morgan-Finney (MMF) and Universal Soil Loss Equation (USLE) predictions revealed non-similarity in the spatial distribution of soil loss rates along Right-of-Way. MMF model revealed more clustered patterns of predicted critical erosion classes with soil loss more than 10 ton/ha/year in particular ranges of pipelines rather than Universal Soil Loss Equation model with the widespread spatial distribution. Paired-Samples T-Test with p-value less than 0.05 and Bivariate correlation with the Pearson\'s correlation coefficient equal to 0.23 showed that the predictions of these two models were significantly different. Verification of USLE- and MMF- predicted erosion classes against in-situ 316 collected erosion occurrences collected in the period of 2005-2012 revealed that USLE performed better than MMF model along pipeline by identifying of 192 erosion occurrences out of 316, whereas MMF identified 117 erosion sites. USLE revealed higher ratio of frequencies of erosion occurrences within the critical erosion classes (Soil Loss > 10 t/ha), what also showed higher reliability of soil loss predictions by USLE. The validation of quantitative soil loss predictions using the measurements from 48 field erosion plots revealed higher R2 equal to 0.67 by USLE model than by MMF. This proved that USLE-predicted soil loss rates were more reliable than MMF not only in terms of spatial distributions of critical erosion classes but also in the quantitative terms of soil loss rates. The total number of erosion-prone pipeline segments with the identified erosion occurrences was 316 out of 38376. The number of erosion-prone pipeline segments realistically predicted by USLE model e.g. soil loss more than 10 t/ha was 97 whereas MMF predicted only 70 erosion-prone pipeline segments. The regression analysis between 354 USLE and MMF erosion-prone segments revealed R2 equal to 0.36 what means that the predictions by USLE and MMF erosion models are significantly different on the level of pipeline segments. The average coefficients of variation of predicted soil loss rates by USLE and MMF models and the number of accurately predicted erosion occurrences within the geomorphometric elements of terrain, vegetation cover and landuse categories were larger in the USLE model. This supported the hypothesis that larger spatial variations of erosion prediction models can contribute to the better soil loss prediction performance and reliability of erosion prediction models. This also supported the hypothesis that better understanding of spatial variations within geomorphometric elements of terrain, land-use and vegetation cover percentage classes can support in the selection of the appropriate erosion models with better performance in the particular areas of pipelines. Qualitative multi-criteria assessment for the determination of erosion-prone areas revealed stronger relations with the USLE predictions rather than with MMF. Multi-criteria assessment identified 35 of erosion occurrences but revealed more reliable predictions on the level of terrain units. Predicted erosion-prone areas by USLE revealed higher correlation coefficient with erosion occurrences than MMF model within terrain units what proved higher reliability of the USLE predictions and its stronger relation with the multi-criteria assessment.