• Energy Research
• other engineering and technologies close
• 15. Life on land close
• GB close

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H₁₀₀, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H₁₀₀ and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 10²-10⁶ plants/hectare and heights 6-49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H₁₀₀.

AbstractChina is under pressure to improve its agricultural productivity to keep up with the demands of a growing population with increasingly resource‐intensive diets. This productivity improvement must occur against a backdrop of carbon intensity reduction targets, and a highly fragmented, nutrient‐inefficient farming system. Moreover, the Chinese government increasingly recognizes the need to rationalize the management of the 800 million tonnes of agricultural crop straw that China produces each year, up to 40% of which is burned in‐field as a waste. Biochar produced from these residues and applied to land could contribute to China's agricultural productivity, resource use efficiency and carbon reduction goals. However competing uses for China's straw residues are rapidly emerging, particularly from bioenergy generation. Therefore it is important to understand the relative economic viability and carbon abatement potential of directing agricultural residues to biochar rather than bioenergy. Using cost‐benefit analysis (CBA) and life‐cycle analysis (LCA), this paper therefore compares the economic viability and carbon abatement potential of biochar production via pyrolysis, with that of bioenergy production via briquetting and gasification. Straw reincorporation and in‐field straw burning are used as baseline scenarios. We find that briquetting straw for heat energy is the most cost‐effective carbon abatement technology, requiring a subsidy of $7 MgCO2e−1 abated. However China's current bioelectricity subsidy scheme makes gasification (NPV $12.6 million) more financially attractive for investors than both briquetting (NPV $7.34 million), and pyrolysis ($−1.84 million). The direct carbon abatement potential of pyrolysis (1.06 MgCO2e per odt straw) is also lower than that of briquetting (1.35 MgCO2e per odt straw) and gasification (1.16 MgCO2e per odt straw). However indirect carbon abatement processes arising from biochar application could significantly improve the carbon abatement potential of the pyrolysis scenario. Likewise, increasing the agronomic value of biochar is essential for the pyrolysis scenario to compete as an economically viable, cost‐effective mitigation technology.

Resource-use efficiency and crop yield are significant factors in the management of agricultural greenhouse. Appropriate modeling methods effectively improve the control performance and efficiency of the greenhouse system and are conducive to the design of water and energy-saving strategies. Meanwhile, the extreme environment could be forecasted in advance, which reduces pests and diseases as well as provides high-quality food. Accordingly, the interest of the scientific community in greenhouse modeling and optimizing has grown considerably. The objective of this work is to provide guidance and insight into the topic by reviewing 73 representative articles and to further support cleaner and sustainable crop production. Compared to the existing literature review, this work details the approaches to improve the greenhouse model in the aspects of parameter identification, structure and process optimization, and multi-model integration to better model complex greenhouse system. Furthermore, a statistical study has been carried out to summarize popular technology and future trends. It was found that dynamic and neural network techniques are most commonly used to establish the greenhouse model and the heuristic algorithm is popular to improve the accuracy and generalization ability of the model. Notably, deep learning, the combination of “knowledge” and “data”, and coupling between the greenhouse system elements have been considered as future valuable development.

A focus on land-use and forests as a means to reduce carbon dioxide levels in the global atmosphere has been at the heart of the international climate change debate since the United Nations Kyoto Protocol was agreed in 1997. This environmental management practice is a process technically referred to as mitigation. These largely technical projects have aimed to provide sustainable development benefits to forest-dependent people, as well as to reduce greenhouse gas emissions. However, these projects have had limited success in achieving these local development objectives. This article argues that this is due in part to the patriarchal underpinnings of the sustainable development and climate-change policy agendas. The author explores this theory by considering how a climate mitigation project in Bolivia has resulted in different outcomes for women and men, and makes links between the global decision-making process and local effects.

Abstract Life cycle assessment (LCA) of slow pyrolysis biochar systems (PBS) in the UK for small, medium and large scale process chains and ten feedstocks was performed, assessing carbon abatement and electricity production. Pyrolysis biochar systems appear to offer greater carbon abatement than other bioenergy systems. Carbon abatement of 0.7–1.3 t CO2 equivalent per oven dry tonne of feedstock processed was found. In terms of delivered energy, medium to large scale PBS abates 1.4–1.9 t CO2e/MWh, which compares to average carbon emissions of 0.05–0.30 t CO2e/MWh for other bioenergy systems. The largest contribution to PBS carbon abatement is from the feedstock carbon stabilised in biochar (40–50%), followed by the less certain indirect effects of biochar in the soil (25–40%)—mainly due to increase in soil organic carbon levels. Change in soil organic carbon levels was found to be a key sensitivity. Electricity production off-setting emissions from fossil fuels accounted for 10–25% of carbon abatement. The LCA suggests that provided 43% of the carbon in the biochar remains stable, PBS will out-perform direct combustion of biomass at 33% efficiency in terms of carbon abatement, even if there is no beneficial effect upon soil organic carbon levels from biochar application.

The purpose of this paper is to provide a broad overview of the social and environmental costs and benefits of biofuels in Asia. The major factors that will determine the impacts of biofuels are: (1) their contribution to land-use change, (2) the feedstocks used, and (3) issues of technology and scale. Biofuels offer economic benefits, and in the right circumstances can reduce emissions and make a small contribution to energy security. Feedstocks that involve the conversion of agricultural land will affect food security and cause indirect land-use change, while those that replace forests, wetlands or natural grasslands will increase emissions and damage biodiversity. Biofuels from cellulose, algae or waste will avoid some of these problems, but come with their own set of uncertainties and risks. In order to ensure net societal benefits of biofuel production, governments, researchers, and companies will need to work together to carry out comprehensive assessments, map suitable and unsuitable areas, and define and apply standards relevant to the different circumstances of each country. The greatest benefits may come from feedstocks produced on a modest scale as co-products of smart technologies developed for phytoremediation, waste disposal and emissions reduction.

To increase the spatial resolution of Soil Moisture Active Passive (SMAP), this study modifies the downscaling factor model based on the Temperature Vegetation Drought Index (TVDI) using data from the Project for On-Board Autonomy (PROBA-V). In the modified model, TVDI parameters were derived from the temperature-vegetation space and the Enhanced Vegetation Index (EVI). This study was conducted in the north China region using SMAP, PROBA-V, and Moderate Resolution Imaging Spectroradiometer satellite images. The 9-km spatial resolution SMAP data was downscaled to 0.3-km spatial resolution soil moisture using a modified downscaling method. Downscaling accuracies from the original and modified downscaling factor models were compared based on field observations. The results show that both methods generated similar spatial distributions in which soil moisture estimates increased as vegetation coverage increased from built-up areas to forest. However, based on the root mean square error between observations and estimations, the modified model demonstrated an increased estimation accuracy of 4.2% for soil moisture compared to the original method. This study also implies that downscaled soil moisture shows promise as a data source for subsequent watershed scale studies.

Poor households in urban informal settlements face a big challenge in accessing clean energy for cooking, heating, and lighting. We use Kenya’s Mathare informal settlement as a landscape site to better understand how cross-sector collaboration can enhance access to sustainable energy in informal settlements. We also demonstrate that academics are well-placed in facilitating multi-stakeholder engagements between community members, experts, and policy actors. This is pursued by drawing on the results of two energy research projects (CoDEC and AfriCLP). We employ a landscape governance framework to re-conceptualise the findings from the CoDEC and AfriCLP projects. Specifically, we use the ecological, socio-cultural, and political dimensions of landscape governance to discuss the relationships between energy demands and other landscape issues in the case study. In conclusion, the paper recommends landscape governance as a promising approach for integrating energy issues with other competing landscape interests, while also encouraging cross-sector collaboration.