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• A simple, large-scale fabrication of cooling paper via pulping and papermaking technology. • The cooling paper is facilely deconstructed and regenerated to architect the secondary cooler. • The cooling paper features a high solar reflectance of 94% and emissivity of 0.95. • The cooling paper shows the sub-ambient temperature drop of 6 ∼ 8.8 °C under directly solar radiation at daytime. Passive radiative cooling materials provide coldness without energy consumption for all-day thermal comfort by reflecting solar irradiation and emitting heat into the 3 K universe. However, the conventional radiative cooling materials involve complex multilayer structures and unsustainable polymers, showing the non-recyclable disadvantage, which induces resource waste and environmental issues. Herein, we reported a low-cost, scalable, and eco-friendly radiative cooling material (namely cooling paper), consisting of the delignified, fibrillated cellulose fibers and nano-sized hydroxyapatite (HA) via the mature pulping and papermaking process. The resulting cooled paper can be recycled, and it can be easily deconstructed to harvest cellulose fibers and HA, individually. The recovered source materials can be reused to prepare secondary products that show comparable performance to the original cooling paper, including a high solar reflectance of ∼94% and an infrared emissivity of ∼0.95 in the atmospheric transparency window. Such cooling paper enables superior cooling performance with the temperature drop of 6 ∼ 8.8 °C under directly solar radiation. Based on the EnergyPlus simulation, our cooling paper shows a average cooling energy saving of ∼29 % in buildings across China. The recyclable cooling paper with high cooling capability and scalability, as well as environmental friendliness, shows promising potential for sustainable energy-efficient buildings. [ABSTRACT FROM AUTHOR]

The world's largest macroalgae bloom (also known as green tide) has been reported since the 29th Olympic Games in 2008, which is verified as the fast reproduction of floating green macroalgae (Ulva prolifera). It is helpful to assess the biomass of macroalgae for the government of marine environment protection. In this study, the synchronization cruise experiment was firstly introduced, which aimed to investigate the biomass evaluation of Ulva prolifera in the Yellow Sea of China. The Floating Algae Index by Polarimetric SAR image (FAIPS) was then proposed. Finally, the floating algae biomass evaluation model was demonstrated and verified, which showed an exponential relationship between FAIPS and wet biomass per area (kg/m2) of macroalgae. The model proposed in this paper can be used in the biomass assessment of floating algae in the presence of polarimetric SAR images, regardless of daylight and cloud coverage over the sea surface. [ABSTRACT FROM AUTHOR]

Recycling spent lithium-ion batteries has received wide attention because the spent batteries are hazardous and contain high-grade and catalytic active heavy metals. Reductive roasting is an effective pretreatment method to recover valuable metals from the used batteries. In this paper, Crofton weed, which has been defined as an invasive plant in China, was suggested as a biomass pyrolysis additive for the reducing pretreatment of spent lithium-ion batteries powder (LiNi 0.6 Co 0.2 Mn 0.2 O 2). The process can reduce carbon consumption for the spent battery recycling industry. Meanwhile, the Ni, Co, and other metals in the cathode powder could catalyze biomass pyrolysis, reducing the reaction's activation energy. The effects of temperature, biomass ratio, heating rate, and roasting retention time on the reduction were studied. TG-DSC, XRD, and SEM were used to characterize the experimental results, and the pyrolysis reduction mechanism was analyzed. Under the optimum roasting conditions: temperature 800 °C, biomass ratio 30%, heating rate 5 °C/min, without retention time, Li in the powder is converted into Li 2 CO 3 , and the high valence Ni, Co, Mn are reduced to low valence and easily soluble Ni, Co, and MnO, respectively. This method provided an alternative technology solution for both spent lithium-ion battery treatment and controlling invasive plants in China, namely Crofton weed. [ABSTRACT FROM AUTHOR]

Accurate carbon (C) stock estimation is crucial for C sequestration research, environmental protection, and policy formulation related to C management. Although research on C stock in forests, oceans, soil, and desert has received increasing attention, relatively few studies have focused on urban C stock. Moreover, the current mainstream methods for C stock assessment, including field surveys and satellite mapping, are characterised by notable limitations, including being labour-intensive and having limited real-time data acquisition capabilities. Therefore, this paper aims to assess urban C stock and proposes a novel two-stage estimation model based on deep learning and unmanned aerial vehicle (UAV) remote sensing. The first stage is that tree areas recognition via YOLOv5 and achieved 0.792 precision, 0.814 recall, and 0.805 mAP scores, respectively. In the second stage, a grid generation strategy and a Convolutional Neural Network (CNN) regression model were developed to estimate C stock based on recognised tree areas (R² = 0.711, RMSE = 26.08 kg). Three regions with a minimum of 300 trees in each area were selected as validation sets. The experimental results, in terms of R² and RMSE in kg, were (0.717, 0.711, 0.686) and (27.263, 27.857, 28.945), respectively. [ABSTRACT FROM AUTHOR]

In this paper, field spectroradiometer and aboveground biomass (AGB) data were acquired at the harvest stage at two sites in semiarid grasslands in Inner Mongolia, China. Four forms of commonly used vegetation indices (VIs) using all possible combinations of narrow-band first derivative (FDR) and raw reflectance (RR) were calculated, and the best FDR-VIs and RR-VIs were chosen by a linear regression analysis against AGB. The stepwise multiple linear regression (SMLR) models using the optimal FDR-VIs, RR-VIs, and both FDR-VIs and RR-VIs as input variables were developed for estimating the AGB. Results demonstrated that the estimation performance using the best FDR-VIs were comparable with the best RR-VIs, while the accuracy has been further improved by combining the best FDR-VIs and RR-VIs (maximum decrease in RMSE of 44% and minimum RMAE of 4.7%). The approach was found to be an important step for more accurate and effective grassland AGB estimation. [ABSTRACT FROM AUTHOR]

Understanding how a plant allocates biomass for reproduction and the effect of location position on twigs' biomass partitioning provides essential information on how to maximise fruit yields through pruning. Fengdan (Paeonia ostii) is a variety of oil Peony newly developed in China. In this paper, the pattern of biomass allocation and allometric growth of the modules within twig (fruit twigs) of five populations of Fengdan were investigated by using standardised major axis (SMA) analyses. The ANOVA results showed that the biomass of stem, seed, husk and fruit per twig significantly varied among populations and among twigs growing at different positions within an individual plant. The top twig had the largest stem and fruit biomass. Twig showed an allometric growth relationship between reproduction and growth (SMA slope b ≠ 1). An obvious trade‐off was found between seed number and 100‐seed weight in fruits. These findings demonstrate that the seated position of the Fengdan twig significantly influences its resource allocation pattern and fruit (seed) yield, implying the efficiency of creating a suitable growth environment and optimising tree architecture in increasing oil Peony yield. [ABSTRACT FROM AUTHOR]

Distributed energy systems are becoming increasingly popular worldwide. The 100% renewable energy system can be an important energy supply alternative to reduce the carbon emissions and address energy shortage, especially for remote areas. However, the performance of 100% renewable energy system (RES) at community level needs further detailed analysis, which is affected by the climates, availability of renewable energy and local energy markets. This paper proposes a design optimization framework of 100% renewable energy systems for low-density communities and investigates the system performance. To investigate the integration and performance of 100% RES, thirty typical cities located in different regions of China were chosen considering different climates, geographical features, and renewable energy distributions. By taking the economic performance as the optimization objective, the optimal design for the 100% RES is obtained, and the energy and economic performance is analyzed. Results show that, under the current energy market conditions, the 100% RES is feasible for low-density communities in most regions of China. The payback periods of the systems in most cities are less than six years. When the cost of PV is reduced by half considering future technological developments, the payback period of a 100% RES can be reduced by 30%–60%. This paper would provide design suggestions and application recommendations in regard to promoting 100% RES in China. • Application of 100% renewable energy system at community level is studied. • 30 zones are selected considering climates, renewable energy sources and markets. • Solar energy and biomass can contribute to over 90% of the total energy supply. • Investment of 100% RES can be paid back in 6 years for most regions. • Payback periods can be reduced by 30%–60% when PV technology is further developed. [ABSTRACT FROM AUTHOR]

Biomass energy can alleviate global warming and solve energy depletion, which is increasingly concerned by the world. Due to the different emission reduction benefits and growth potential of different regions and biomass power generation technologies, analyzing the suitability of these technologies combined with regional conditions can more accurately guide the long- and short-term development of biomass power industry. However, there is no comprehensive evaluation of the benefits and potential of several biomass power generation technologies in different regions. Therefore, this paper introduces development suitability indexes and constructs life-cycle environmental impact and time-value economic impact assessment models, and a growth potential dynamic assessment model based on Gaussian process and particle swarm optimization to illustrate the greenhouse gas emission reduction benefits and growth potential of biomass power generation technologies. The empirical research of China shows that biomass gasification and direct combustion power generation can bring the best environmental benefits, and biogas power generation can bring the best economic benefits. For regions with abundant biomass resources and bad air condition, it is more suitable to develop gasification and direct combustion power generation technology, while mixed-combustion and biogas power generation technology are more suitable in regions with high electricity consumption. [ABSTRACT FROM AUTHOR]

The composite fuel of coal gangue and biomass is expected to increase the utilization rate of solid waste and compensate for the disadvantages of separate fuels. However, the NO and SO2 emissions from this composite fuel during the combustion process are a concern, but there are few studies on it. In this paper, corn cobs and wheat straws, typical agricultural biomass discarded in North China, and coal gangue from the mine in Xilingol, China, were selected for co-combustion in a fluidized bed. The emission characteristics of NO and SO2 were studied by changing the ratio of biomass to coal gangue and the combustion temperature. Studies had shown that: to a certain extent, mixing biomass, and coal gangue can reduce the NO and SO2 emissions, and mixing 20% of biomasses had the best effect on NO and SO2 emissions reduction. The SO2 emission reduction effect of wheat straws was better than that of corn cobs, and the NO emission reduction effect of corn cobs was better than that of wheat straws. The NO emissions of wheat straws and corn cobs added to the coal gangue were 6.45% and 7.93% less than those of coal gangue alone. The SO2 emissions of wheat straws and corn cobs added to the coal gangue were 27.45% and 25.94% less than those of coal gangue alone. Both NO and SO2 emissions decreased with the growth of the biomass rate; NO and SO2 emissions increased with the growth of the combustion temperature. [ABSTRACT FROM AUTHOR]

Pennisetum hydridum has several beneficial characteristics, including the ability to grow quickly, a highly developed root system, the ability to produce high yields, strong resistance to environmental stressors, and the ability to adapt to different growth environments. Recent studies have shown that Pennisetum hydridum has the potential to play an important role in the sectors of bioenergy, environmental remediation, and livestock fodder. The objective of this paper is to review the current research on Pennisetum hydridum in China and discuss its potential for phytoremediation, biofuel development, and feed utilization. Pennisetum hydridum is resistant to a variety of stressors and can adapt to different growth environments. It can be used for the remediation of heavy metal-contaminated land, restoration of saline-alkali land, and nutrient removal of constructed wetlands, as well as soil and water conservation. Pennisetum hydridum exhibits a higher biomass yield, caloric value, and cellulose content than other bioenergy crops, suggesting it has superior potential as a second-generation biofuel resource. As a type of forage grass, Pennisetum hydridum also has an appealing taste and high feeding value, in addition to its high nutrition value. A comprehensive utilization framework for Pennisetum hydridum has been proposed in order to promote high-efficiency utilization of this multipurpose crop and fully realize its maximum potential. Research on Pennisetum hydridum as a bioenergy resource, however, is still in its infancy. Additional work is needed to better understand its breeding and genetic transformation processes, its energy conversion mechanism, and the biological pathways that support its growth and adaptability, so that this valuable resource may be utilized in the most productive way possible. [ABSTRACT FROM AUTHOR]

Biomass is one of the important growth indicators of summer maize (Zea mays). Timely and accurate acquisition of field summer maize biomass data and its dynamic changes is conducive to county agricultural management departments to rationally adjust field production management measures, which is of great significance for increasing maize yield based on the establishment of a simulation model of summer maize biomass process.In this paper, we analyzed above ground biomass and its variation characteristics of summer maize at different growth stages and discussed the feasibility of adjusting parameters of biomass simulation modelusing measured leaf area index and biomass datain Dafengdistrict ofYanchengcity, Jiangsu province, along the east coast of China. The simulation model of biomass process of summer maize could estimate the dynamic changes of aboveground biomass of summer maize at different growth stages from emergence to grain filling.Firstly, the simulation model can predict above ground biomass effectively because of biomass accumulation mainly coming from leaf formation from seedling emergence to pre-jointing growth stage, the root mean square difference (RMSE) of which was 18.31 kg/hm2. During the growth stage from jointing to tasseling stage, the biomass accumulation accelerate due to the elongation of stem nodes and the increase of number of nodes, and the difference between the predicted and measured values waslarge and RMSE was825.92 kg/hm2. For example, the predicted value of biomass at early jointing stage was 535.5 kg/hm2, and the measured value was 480 kg/hm2, with a difference of 10.36%. Another example, the predicted value of biomass beforetasseling stage was 7036.46 kg/hm2, and the measured value was 5794 kg hm-2, the difference was 17.66%. Then, adjusting the parameters of the model, the predicted biomasswas6014 kg/hm2, which was close to the measured biomasswithRMSE 219.43 kg/hm2.Finally, by using the simulation model adjusted by the parameters, we predictedbiomass during the growth period from tasseling to grain filling that predicted values were in good agreement with the measured values, and the determinant coefficient between them was 0.978 and RMSE was 182.95 kg/hm2. For example, the predicted biomass at grain filling stage before parameter adjustment was12 492 kg/hm2, the measured biomass was 10 785 kg/hm2, the relative error was15.83%, and the predicted biomass after parameter adjustment was 11 156 kg/hm2with the relative error of 3.44%.This study provided an effective informatics method for forecasting the aboveground biomass and its dynamic changes of summer maize at different growth stages, and could assist the county agricultural management departments to adjust production measurestimely. Combining remote sensing data with crop process simulation model to estimate regional crop biomass or yield was a hot topic in the remote sensing application in agriculture. In this paper, crop process simulation model was used to analyze the trend of biomass change at three growth stages of summer maize, namely, emergence to jointing, jointing to tasseling, tasseling to filling, and to clarify the law of biomass accumulation and nutrient uptake characteristics at corresponding growth stages. In the follow-up study, LAI and biomass inversion using remote sensing data will be further considered, and assimilation and application of remote sensing data and crop process simulation model will be studied to enhance the universality and effectiveness of maize biomass process simulation model in maize planting areas along the East coast in China. [ABSTRACT FROM AUTHOR]

The Chinese government has made significant effort to promote biomass based electricity generation in recent years. Yet, little is known about consumers’ preferences for biomass electricity and associated environmental impacts. This paper uses discrete choice experiments (DCE) to investigate Chinese consumers’ preference for electricity generated from various biomass sources. Based on 548 responses, the paper finds that Chinese households are willing to pay a premium of around 27 Yuan per month or 0.20 Yuan per kilowatt hour (kWh) to replace coal-fired electricity. Among the various biomass sources, electricity generated from agricultural and forestry biomass is most preferred, followed by biogas electricity and waste-to-energy. It is also found that respondents have a significant willingness to pay for reducing haze. Consumers’ household structure and environmental awareness also affect their preference for biomass electricity. These results have significant implications for the prioritization, design and communication of biomass promoting schemes. [ABSTRACT FROM AUTHOR]

Soil desertification affects the service functions of the ecosystem. In severe cases, it even causes a decline in agricultural productivity and shrinkage of animal husbandry, posing a threat to regional eco-environment and economic sustainability. The previous research on soil remediation research mainly concentrates on heavy metal degradation, saline soil improvement, and eroded and degraded soil improvement. There is little report on the biomass improvement and restoration of sandy soil. Therefore, this paper explores the remediation effect of biomass amendment on the physical-chemical performance and sustainable utilization of sandy soil in Huangyangtan, the largest sandy land in northern China's Hebei Province. Specifically, the authors detailed the strategies to measure the physical-chemical indices and microbial diversity of Huangyangtan sandy soil, and introduced the materials and mode of the biomass amendment test on Huangyangtan sandy soil, followed by an elaboration on the test results. The influence of different test fertilizers on the soil was analyzed in four dimensions, namely, physical performance, chemical performance, biological performance, and crop yield. The results show that biomass amendment can effectively remediate sandy soil, and promote its sustainable utilization. [ABSTRACT FROM AUTHOR]

【Objective】This paper aims to select turf grass cultivars suitable for vegetation restoration in Guizhou mercury mine wasteland and mercury pollution environment.【Method】Four turfgrass cultivars suiting southern China, including Motor, Feast, Pernille, and Legend, were selected as the experimental materials. The seed germination test and soil culture test under different concentration of Hg2+ stress were conducted to explore the seed germination and seedling growth of four cultivars.【Result】With Hg2+concentration increasing, the germination rate,germination potential,germination index and vigor index of the four cultivars were obviously inhibited. The tolerance limit of Feast and Motor was 120 mg/L; In the range of experimental treatment, the seed germination rate of the four cultivars was Pernille>Legend>Feast>Motor. The growth of the four cultivars was inhibited by high Hg2+ concentration, and the survival rate of the four cultivars decreased with the Hg2+ increasing. When the concentration of Hg2+ reached 100 mg/kg,the survival rate of the four cultivars was Feast>Pernille>Legend >Motor.【Conclusion】In the range of experiment,the comprehensive growth of Feast under Hg2+stress was the best. However, Feast showed stronger enrichment ability in mercury-containing 25 mg/kg soil, which was suitable for restoration of low-mercury soil and establishment of lawn, Legend had the strongest ability to enrich mercury in mercury-containing 50 and 100 mg/kg soil, which was suitable for restoration of high-mercury soil and establishment of lawn. [ABSTRACT FROM AUTHOR]

There are abundant crop straws in Chinese rural areas, but they are loose structure, low energy density and scattered distribution. Biomass densification technology is one of the effective ways to solve these problems. So the paper proposes a novel distributed heating/centralized monitoring mode of the biomass briquette fuel for rural areas. The mode includes the energy service station, the internet platform and the farmer households. A bidirectional C2S (Customer to Supplier) relationship between the energy service station and the farmer households is formed. The biomass briquette fuels are bartered using the crop straws instead of using money between the farmer households and the energy service station. The optimal service radius is calculated in different climate rons. The results are 4.75 km in extremely cold ron, 1.71 km in cold plain ron, 2.36 km in cold mountain ron. The use-scale of 1000 households is regarded as the standard for the promotion and application of the mode. The sensitivity analysis is that briquetting cost is the peak. At last, some suggestions are proposed, which will promote the future development of the briquette heating in China. • A mode of distributed heating/centralized monitoring is proposed in China. • A bidirectional C2S (Customer to Supplier) relationship is formed. • The optimal use-scale and optimal radius of the mode are calculated. • The "Internet + biomass energy network" is builds in rural area. • Some policies are suggested for the further development of biomass heating. [ABSTRACT FROM AUTHOR]

Biomass is an important indicator for monitoring vegetation degradation and productivity. This study tests the applicability of Hyperspectral Remote-Sensing in situ measurements for high-precision estimation aboveground biomass (AGB) on regional scales of Khorchin grassland in Inner Mongolia, China. In order to improve prediction accuracy of AGB which is frequently used as an indicator of aboveground net primary productivity (ANPP), this paper combined ground measurement with remote sensing inversion to build the spectral model. The ground normalized difference vegetation index (SOC_NDVI) calculated from ground spectral of grassland vegetation which was measured by a portable visible/NIR hyperspectral spectrometer (SOC 710). Meanwhile, the remote normalized difference vegetation index (TM_NDVI) calculated from remote spectral of grassland vegetation which was measured by Thematic Mapper (TM) from Landsat 8 which launched by National Aeronautics and Space Administration (NASA). According to regression analysis for the relationship between AGB and SOC_NDVI, SOC_NDVI and TM_NDVI, the evaluation model for aboveground biomass was developed (AGB = 12.523×e3.370×(0.462×TM_NDVI+0.413), standard error = 24.74 g m-2, R2 = 0.636, p < 0.001). The model accuracy verification results show that the correlation between the measured value and the predicted value of biomass was better with low model standard error. The model could make up for the lack of timeliness and comprehensiveness of conventional ground biomass survey, and provide technical support for high-precision large-area productivity estimation and ecological degradation diagnosis of regional scale grassland. [ABSTRACT FROM AUTHOR]

Traditional remote sensing observation can only derive chlorophyll-a concentration in surface water (Chlasurf), which is insufficient for water quality monitoring or biogeochemical applications. In this paper, a column-integrated biomass (CIB) estimation algorithm was established in Lake Dianchi, China, and the CIB was estimated by Ocean and Land Color Instrument (OLCI) data from 2016 to 2018. First, the results show that the method is applicable to CIB estimation in nonbloom conditions [mean absolute percentage error (MAPE) = 10.55%, mean ratio (MR) = 0.996]. On the one hand, Chlasurf could be estimated using a universal model of Chla (UMOC) estimation for case-II waters; on the other hand, CIB could be obtained from Chlasurf according to the linear relationship between the Chlasurf and CIB. Second, both the spatial and temporal variabilities of Chlasurf are larger than those of CIB, which indicates that the biomass of the whole lake is relatively stable from day to day. During algal bloom periods, the CIB at nonbloom areas tends to decrease, suggesting that algae from nonbloom regions have migrated to bloom regions. Third, wind speed (WS) is the most critical meteorological factor affecting the water surface biomass, compared with other parameters. The average percentage of surface-to-total biomass in nonbloom conditions is about 7% when the WS is less than 2 m/s. [ABSTRACT FROM AUTHOR]

Aboveground forest biomass (Bagf) and height of forest canopy (Hfc) are of great significance for the determination of carbon sources and sinks, carbon cycling and global change research. In this paper, Bagf of coniferous and broadleaf forest in the Chinese Three Gorges region is estimated by integrating light detection and ranging (LiDAR) and Landsat derived data. For a better Bagf estimation, a synergetic extrapolation method for regional Hfc is explored based on a specific relationship between LiDAR footprint Hfc and optical data such as vegetation index (VI), leaf area index (LAI) and forest vegetation cover (FVC). Then, an ordinary least squares regression (OLSR) and a back propagation neural network (BP-NN) model for regional Bagf estimation from synergetic LiDAR and optical data are developed and compared. Validation results show that the OLSR can achieve higher accuracy of Hfc estimation for all forest types (R2 = 0.751, Root mean square error (RMSE) = 5.74 m). The OLSR estimated Bagf shows a good agreement with field measurements. The accuracy of regional Bagf estimated by the BP-NN model (RMSE = 12.23 t ha–1) is superior to that estimated by the OLSR method (RMSE = 17.77 t ha–1) especially in areas with complex topography. [ABSTRACT FROM AUTHOR]

• Machine learning was applied to quantify the effects of stand, climate and soil on biomass of mixed forests with good accuracy. • Quantifying the importance of various environmental attribute factor to forest biomass depends on the combination of environmental variables and modeling methods. • Environmental variables including degree-days above 18 °C, bulk density and soil pH were most important predictors. Forest biomass is influenced by multiple environmental factors. Multi-source data on site-specific soil, climate, and stand factors are essential for stand biomass prediction. While previous studies concerning planted forest biomass at stand level highlighted the importance of environmental factors, few have been conducted on the effects of climate and soil on stand biomass estimation, especially for natural mixed forest with complicated stand structure. Machine learning (ML) algorithms provide new tools for examining the effects, but the applications are still limited. Therefore, the objectives of this paper were to develop ML models for stand biomass estimation with stand and multiple environmental predictors, and quantify the relative importance of environmental variables. Tree above- and below-ground biomass at stand level was set as output variable with the random forest (RF) and boosted regression tree (BRT) regression methods. The data were from 286 sample plots from the National Forest Inventory (NFI) in Jilin Province, northeast China. The results showed that models with the inclusion of stand, soil, and climate variables explained > 89% of forest biomass variations. BA (stand basal area) and H (stand average height) were the most important stand variables, DD18 (degree-days above 18 °C) was the most important climate variable, and bdod (bulk density) and pH were the most important soil variables. Relative importance of climate and soil factors was 0.5% to 5.1% and 1.2% to 4.1%, respectively, which were weak but important predictors of stand biomass. In the RF model, climate variables were more important than soil variables, but the opposite in the BRT models. We concluded that above forest stand, climate and soil factors were significant input variables for regional forest biomass mapping using ML. [ABSTRACT FROM AUTHOR]

Since the typical destructive methods for measuring aboveground biomass (AGB) have many limitations, a variety of non-destructive techniques have been developed. In this paper, the potential of ground-based hyperspectral remote-sensed data for non-destructive assessment of semi-arid pasture AGB at the peak productive period was investigated. The reflectance spectrometric and AGB data were sampled at the end of the growing season (almost peak biomass) over two locations at pastures in the southern Horqin sandy land, eastern Inner Mongolia, China. All combinations (two-band and three-band) of narrow bands in the forms of simple ratio vegetation index (SRVI), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI) and enhanced vegetation index (EVI) were used in a linear regression analysis against AGB. The predictive performance of the stepwise multiple linear regression (SMLR) using 4 best VIs as input variables was compared with the performance of multivariate partial least squares regression (PLSR) using all reflectance bands as input variables to estimate AGB. It was observed that the relationship between AGB and single band spectral reflectance was low, while the estimation performance of the best VIs based on all available wavebands was improved considerably. In addition, the best VIs based on all available wavebands had considerably better fitting performance than those based on traditionally used wavebands for estimating AGB. In comparison to PLSR using the full individual reflectance as input variables, SMLR using the best VIs as input variables performed much better, with the maximum decrease in RMSECV of 37% and the relative mean absolute errors always below 12.5%. The study demonstrated the high potential to estimate pasture AGB, which is a proxy for pasture forage yield, at the peak productive period using a hyperspectral technique. [ABSTRACT FROM AUTHOR]

Forest is a major carbon pool for terrestrial ecosystems, and it plays a very important role in global carbon cycle. Forest biomass is a key factor in estimating forest carbon storage, and its magnitude and spatial distribution are important parameters for assessing carbon sequestration potential of forest ecosystems. Scholars in the field have used different methods to study many aspects of forest biomass in China. Due to the spatial heterogeneity of forest biomass and differences in research methods and data, different scholars got different results. Three traditional methods have been used in biomass research: on- the- spot sampling, model method and remote sensing. Currently, statistical downscaling technique is a statistical method widely used in the study of ecosystem carbon cycle which transforms large- scale, lowresolution information into regional-scale, high-resolution information. This paper is based on the eighth China forest inventory data set, along with the impact factors of forest biomass, including the vegetation factor (NDVI), climatic factors (temperature, precipitation), and terrain factors (elevation, slope). We quantitatively estimate the forest biomass (1 km resolution) using the spatial downscaling technique, and the results of the study are verified on multiple scales. The results of this study are as follows: 1) The total stock of forest biomass is 13.56 Pg in China, with an average biomass of 65.3 t/hm2. The total amount of forest biomass is quite different in different provinces. The provinces with higher volume are concentrated in the southwest and the northeast, and the maximum biomass is 4.5 Pg in the southwest, accounting for 33% of the total biomass in China. The forest biomass is 3.58 Pg in the northeast, accounting for 26% of the total biomass in China. 2) The regression relationship between forest biomass and related factors at the provincial scale can be used for the estimation of forest biomass at the grid scale by downscaling technique, and the multi- scale verification analysis shows that the estimation results are reasonable. 3) The spatial pattern of forest biomass is consistent with the spatial distribution of hydrothermal condition. Taking the line from the northeast to the southwest as the boundary, China's biomass is primarily in the Da Xing'an Mountains, Xiao Xing'an Mountains and Changbai Mountain in the Northeast China, the Hengduan Mountains in the Southwest China, the Qinling Mountains, and the Wuyi Mountains in the Southeast China. [ABSTRACT FROM AUTHOR]

Energy and resource consumption has been expanding quickly with the rapid growth of Asian cities, which has resulted in increased greenhouse gas emission and waste generation. The promotion of low-carbon industries is an urgent global issue that extends to Asia as well. To reduce carbon dioxide emission substantially, industries must not only introduce energy-saving technologies but also use low-carbon raw materials and fuel, such as recyclable wastes and carbon-neutral biomass. This paper presents the concept of a “hybrid industry,” that is, an industry whose processes utilize not only fossil resources but also recycled and renewable resources as much as possible. This study examines the feasibility of hybrid industries through the promotion of urban symbiosis in cities in three Asian countries with different circumstances: Kawasaki in Japan, Ulsan in Korea, and Shenyang in China. Asian cities are in the midst of shifting from dumping wastes to incineration. However, in view of the carbon reduction effect of recycling as well as the cost for recycling and appropriate treatment of wastes, the potential of hybrid industries that use combustible municipal wastes as input should be considered. In this study, the potential for carbon dioxide reduction as well as the costs of promoting hybrid industries are evaluated. The results highlight that promoting hybrid industries generates significant environmental benefits for the three cities, and there are important factors that affect the cost-effectiveness of hybrid industries, including the spatial density of waste generation, composition of wastes, relative labor cost for collection and pre-treatment of wastes compared with construction cost of an incinerator and avoided costs through product and fossil resource substitution, and the willingness of citizens to separate wastes. Finally, key drivers for promoting hybrid industries through urban symbiosis in Asian cities are discussed. [ABSTRACT FROM AUTHOR]

Initiatives to mitigate climate change have recently aroused great interest in the role of natural carbon sinks in coastal ecosystems. Seaweeds are widely distributed in the world and represent a large biomass. Since they are part of the global carbon reserves, they remove carbon dioxide and influence climate change. Using the recent 20 years of seaweed mariculture in China's coastal areas as a case, this paper quantifies the carbon storage in cultivated seaweed biomass, and evaluates the carbon sink potential, the remediation ability of nitrogen and phosphorus and other environmental benefits. The carbon sink potential of cultivated seaweeds exhibits a rising trend from 2000 to 2019. The total carbon, nitrogen, and phosphorus removal amount of seaweed were 3,551,754.9 ± 177,587.75, 297,772.25 ± 14,888.61, 39,967.15 ± 1998.36 tons according to the seaweed cultivation yield in China coast. The total benefit of carbon sequestration was 22,405.67 ± 259.59 million CNY, and the average benefit was 1120.28 ± 263.27 million CNY, with the average annual growth rate of 4.00%. The total environmental benefit was 1,962,020.88 ± 22,747.42 million CNY, and the average benefit was 98,103.04 ± 23,073.08 million CNY, with the average annual growth rate of 4.00%. The present study illustrates distinctly the ecological value of large-scale cultivated seaweeds in increasing marine carbon sequestration and resolving offshore environmental issues, which is an efficient approach and comparable to other key marine ecosystems. Based on the carbon sink role of seaweed mariculture, and with the goal of global carbon neutrality, more attention should be paid to the carbon sink capacity of large-scale seaweed cultivation industry and be vigorously developed worldwide. • Seaweed has an active effect in N, P remediation and quantities of CO 2 accumulation. • Seaweed has a strong carbon sequestration capacity and is a key part of carbon sink. • Carbon sequestration benefit of seaweed cultivation is 22,405.67 ± 259.59 millions CNY. • Suggesting to pay more attention to the seaweed carbon sink on a global scale. • Suggesting to vigorously develop and promote seaweed cultivation industry worldwide. [ABSTRACT FROM AUTHOR]

Due to the shortage of fossil energy, pyrolysis has become a promising way for the thermal utilization of biomass resources, so as to partly replace fossil energy as well as achieve efficient resource usage. The site selection of the biomass pyrolysis (BP) project is an important task in the preliminary planning stage of the project. Moreover, since low-carbon development has become a common global goal at present, this paper proposes a decision-making framework from the low-carbon point of view for BP project site selection. Firstly, a complete site selection decision-making criteria system embracing the novel concept of low-carbon development is established for the first time, and the subjective and objective weighting method is integrated into the comprehensive integrated weighting method based on game theory. More importantly, a brand-new distance formula for the probabilistic linguistic term set is defined to measure the deviation between information, which uses expectation, variance and scale function to make the measurement more reasonable. Based on this, an improved TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method is proposed to more accurately determine the best option. Finally, taking Guangdong Province as an example, the best choice for site selection is obtained. This work can provide insightful theoretical basis for the site selection of BP projects. • A criteria system is established for site selection from the low-carbon perspective. • Subjective and objective weighting models are used to determine the weights. • A new formula based on expectation, variance and scale functions is defined. • A site selection framework is proposed based on a mixed method. [ABSTRACT FROM AUTHOR]

This paper analyzes the rural Chinese biomass supply system and models supply chain operations according to U.S. concepts of logistical unit operations: harvest and collection, storage, transportation, preprocessing, and handling and queuing. In this paper, we quantify the logistics cost of corn stover and sweet sorghum in China under different scenarios. We analyze three scenarios of corn stover logistics from northeast China and three scenarios of sweet sorghum stalks logistics from Inner Mongolia in China. The case study estimates that the logistics cost of corn stover and sweet sorghum stalk to be $52.95/dry metric ton and $52.64/dry metric ton, respectively, for the current labor-based biomass logistics system. However, if the feedstock logistics operation is mechanized, the cost of corn stover and sweet sorghum stalk decreases to $36.01/dry metric ton and $35.76/dry metric ton, respectively. The study also includes a sensitivity analysis to identify the cost factors that cause logistics cost variation. Results of the sensitivity analysis show that labor price has the most influence on the logistics cost of corn stover and sweet sorghum stalk, with a variation of $6 to $12/dry metric ton. [ABSTRACT FROM AUTHOR]

Bioenergy can be a promising solution to the energy, food and environment trilemma in China. Currently this coal-dependent nation is in urgent need of alternative fuels to secure its future energy and improve the environment. Biofuels derived from crop residues and bioenergy crops emerge as a great addition to renewable energy in China without compromising food production. This paper reviews bioenergy resources from existing conventional crop (e.g., corn, wheat and rice) residues and energy crops (e.g., Miscanthus ) produced on marginal lands. The impacts of biofuel production on ecosystem services are also discussed in the context of biofuel's life cycle. It is estimated that about 280 million metric tons (Mt) of crop residue-based biomass (or 65 Mt of ethanol) and over 150 Mt of energy crop-based ethanol can become available each year, which far exceeds current national fuel ethanol production (< 2 Mt year −1 ) and the 2020 national target of 10 Mt year −1 . Review on environmental impacts suggested that substituting fossil fuels with biofuels could significantly reduce greenhouse gas emissions and air pollution (e.g., particulate matter). However, the impacts of biofuel production on biodiversity, water quantity and quality vary greatly among biomass types, land sources and management practices. Improved agricultural management and landscape planning can be beneficial to ecosystem services. A national investigation is desirable in China to inventory technical and economic potential of biomass feedstocks and evaluate the impacts of biofuel production on ecosystem services and the environment. [ABSTRACT FROM AUTHOR]

Taiwan is an island in East Asia that strongly depends on imported fossil fuels. To reduce emissions and pollutants, there is interest in wind and solar energy. The current solar energy systems convert solar energy into electricity with high capital cost because of their low efficiency and high operational costs. This paper presents the position of renewable energy methods in Taiwan and the benefits of its expansion. This research suggests that the use of Photovoltaic/thermal (PV/T) collectors and wind turbines can provide appropriate solutions for electricity production due to the benefits of the long duration of insolation of solar collectors and the energy density of wind turbines. However, there are several challenges and problems that must be solved (land conditions and geographical positions are not appropriate for PV/T installation and wind energy system, respectively). Finally, a series of suggestions is presented to solve the economic problems associated with wind and solar energy systems. [ABSTRACT FROM AUTHOR]

The main strategies for biomass utilization are the development of biomass-fired power plants, which can minimize the emissions and pollutants from fossil fuels combustion, the improvement of energy density from biomass materials, and the economic development, especially in the rural areas. In the present paper, an economic study of catalytic biomass combustion was carried out to determine the potential of catalysts for CO2capture. The effects of catalyst type and feed input (Mfeed(kg/h)) on CO2concentration and total plant cost (TPC) were studied. Results were showed that on increasing Mfeedfrom 500 kg/h to 2500 kg/h, TPC increases from 2125 kEuro2014to 6428 kEuro2014for CaCO3, from 2270 kEuro2014to 7734 kEuro2014for MgCO3, and from 2410 kEuro2014to 7927 kEuro2014for CaCO3-MgCO3, due to an enhancement in the size of burner with increasing Mfeed. [ABSTRACT FROM PUBLISHER]

In this paper, a collaborative power dispatching system (CPDS) was developed to maximize the profit of a regional biomass power system consisting of an independent power grid. A power generating, dispatching and carbon emissions trading system (CETS) could be engaged in joint strategic planning and operational execution. The principal of CPDS is interactive planning of generating units in power generation and carbon emissions trading. An efficient carbon emissions trading plan for a CPDS would lead to optimized power generation levels under available power production capacities and carbon emissions. In a case study, four generator policies are proposed by considering basic CETSs to comparatively analyze the function of each generator in the CPDS. Results of four scenarios are compared, showing that biomass energy could replace thermal units to a certain extent, the carbon emissions and coal consumption of the CPDS would lie at a lower level, and a pumped storage unit could adjust the load fluctuations. The results of a carbon trading analysis show that the CETS has no significant impact on the CPDS, but along with the increase in trading price or the decrease in the free quota, the economic interests of power plants will be reduced accordingly. This may lead to carrying out low-carbon projects and reducing carbon emissions. Therefore, it is imperative to reduce carbon emissions by replacing power units with high energy consumption, and improve the consumption capacity of renewable energy. [ABSTRACT FROM AUTHOR]

To fulfill the target of emissions reduction, the Chinese government has made many efforts to develop renewable energy. Biomass power can provide stable power supply, avoid wasting straw resources and protect rural environment at the same time. However, the development of renewable power requires subsidies from the government, but increased subsidies placed heavy burden on the governments, whereas these governments want to develop renewable energy with minimum costs. This paper attempts to answer the question that whether the development of biomass power is a good choice for local governments in China. For this purpose, the goal of emissions reduction and subsidies of renewable energy powers were discussed. The main conclusion is that although the subsidies for biomass power were slightly higher than those for wind power, biomass power is a good choice for governments considering other benefits, especially for regions with rich agricultural and forest residues. In the future, regional and local conditions should be considered in the planning of biomass power development. [ABSTRACT FROM AUTHOR]

Burning agricultural straw before and/or after harvest is a common farming practice. Regional and extensive agricultural open field straw burning can cause serious air pollution events. This paper looks at the effects of biomass burning emission on regional haze that should be considered in the forecasting of regional haze. It describes the current state of crop residue burning in China and analyzes the relationship between biomass burning and regional haze in terms of temporal/spatial patterns and chemical composition. Finally, some suggestions/recommendations are proposed for the recycling of agricultural straw to reduce the impact of biomass burning on regional haze and air quality. We suggest that prescribed open burning would be a more suitable solution in China. We hope that this report about biomass burning and regional haze will bring the issue to the attention of governments and other researchers. [ABSTRACT FROM AUTHOR]

This paper presents an initial inquiry into model-based numeric nitrogen and phosphorus criteria for estuaries based on stressor-response models between nutrients and algal biomass (Chl- a concentration) and further studies the effect of salinity ( S ) on nutrient criteria. Field data collection and associated indoor modeling were conducted in Daliaohe Estuary. Dissolved inorganic nitrogen (DIN), total nitrogen (TN), phosphate ( P O 4 3 − ) and total phosphorus (TP) eco-criteria of Daliaohe Estuary in China were calculated at salinities of 15, 25 and 31. The results suggested that the variation in S had significant influence on the DIN and TN eco-criteria and no obvious effect on the P O 4 3 − and TP eco-criteria. The values of DIN and TN eco-criteria increased with either higher or lower salinity concentrations, and were strongly linked to the effects of salinity on algal nutrient absorption and utilization, growth, metabolism, and osmotic pressure. [ABSTRACT FROM AUTHOR]

Wetlands are important ecosystems as they are known as the "kidney of the earth". Particularly, urban wetlands play an important role in providing both natural and social beneficial services. However, urban wetlands are suffering from various human impacts, such as excessive land use conversion, air and water pollution, especially those in developing countries undergoing rapid industrialization and urbanization. Therefore, it is of great necessity to derive timely biomass information for optimal design, management and protection of urban wetlands. In this paper, we develop a set of models for estimating above ground biomass (AGB) in Xixi National Wetland Park in Hangzhou, China by using optical images and Synthetic Aperture Radar (SAR) images. A series of vegetation indices (VIs) derived from optical data is introduced along with spectral data. The modeling methods consist of (1) curve estimation; (2) linear regression for multivariable model; (3) Back Propagation Neural Network (BPNN) modeling. Curve estimation is a combination of linear and nonlinear regressions. It is applied to generate AGB models from a single variable including Normalized Difference Vegetation Index (NDVI) and radar backscatter coefficient. The models are then compared via three accuracy metrics. According to the results, SAR models generally show better accuracy than optical models and BPNN models show the greatest accuracy among all the models. The BPNN model from the combination of Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and European Remote-Sensing Satellite-2 (ERS-2) SAR (Synthetic Aperture Radar) image has the least root mean square (RMSE, 0.396 kg/m2), least mean absolute error (MAE, 0.256 kg/m2) and the greatest correlation coefficient (0.974). The results indicate that AGB can be estimated by integrating optical and SAR imagery. Four maps of AGB are derived to illustrate the distribution of AGB in the study area. The total AGB in the study area is estimated to be between 165,000 and 210,000 kg/m2. [ABSTRACT FROM AUTHOR]

Nowdays, coal and biomass are the most widely used hydrocarbon solid fuels in the world. The utilization of hydrocarbon solid fuels in China mainly depends on thermal conversion, the most representative of which is thermal power generation. In addition, thermal conversion utilization also includes pyrolysis, gasification, and liquefaction produces chemical products and liquid fuels. Pretreatments are important ways to improve thermal conversion efficiency, especially the most economical and widely used hydrothermal pretreatment. This paper reviews the effects of hydrothermal pretreatment on coal and biomass structure and examines the matching relationship between hydrothermal pretreatment and the thermal conversion process. The relationships between hydrothermal pretreatment and pyrolysis, gasification, liquefaction, and combustion of coal/biomass are discussed. Future studies on HTP should focus on environmentally friendly, high-efficiency, and low-energy consumption technology for coal/biomass thermal conversion. The treatment and utilization of effluents from the HTP systems, catalysis technologies and preparing high-quality materials by HTP are meaningful. [Display omitted] • HTP removes oxygenate groups and increases aromatization degree and porosity. • HTP increases crystalline structure order and decreases alkali metal content. • HTP improves coal conversion and tar yield by destroying cross-linked structure. • HTP reduces pollution, corrosion, ash slagging of conversion by demineralizing. [ABSTRACT FROM AUTHOR]

Abstract: The fast-growing Chinese economy will inevitably need more and more energy. This not only makes China''s energy shortage situation severer, but also causes more and more worries from the countries all over the world, especially those developed countries. In this paper, China''s energy state is analyzed and the influences of promoting new socialist countryside construction on China''s energy source problem and its energy strategy making are discussed. It is stressed in this paper that in drawing the national energy development plan, it is of vital importance to take the impacts of new socialist countryside construction on energy production, supply and consumption into consideration. Traditional mineral energy supply that has been used for towns and cities should not be simply copied to solve the energy problem in countryside construction. The best choice for combating the huge energy increase resulted from speeding up the countryside construction is promoting utilization of biomass and solar energy and various advanced energy technologies. To make the utilization of biomass and solar energy and various advanced energy technologies in countryside, the government should give necessary technical and financial supports. [Copyright &y& Elsevier]

In order to understand the basic character and development tendency of China’s rural household energy consumption, we present the total rural household energy consumption of 1998 in China, which was 340.97 million tce (tons of standard coal equivalent, 1 tce=7×106 kcal), according to statistics gathered from 30 provinces and 40.14% of which was commercial energy. This paper shows the correlation coefficients of the data, such as per-capita energy consumption of standard coal equivalent (PCEC), effective heat consumption for livelihood per capita per day (EHC), the proportion of commercial energy in EHC (PCE), annual electricity consumption for livelihood per capita (AEC) and so on. The paper suggests using EHC, PCE and AEC as the character indices to further reveal the correlation of per-capita income (PCI) and average annual temperature (AAT). [Copyright &y& Elsevier]

Taking natural grassland on the northern slope of the Qilian Mountain for example, this paper investigated and compared above-ground and bclowground biomass of grassland in multi-year enclosure (20 years), one-year enclosure, control areas (natural grazing areas). The results showed that coverage and height of the enclosure sample plots were significantly higher than that of natural grazing area (P<0.05); mean aboveground biomass of grassland: multi-year enclosure (316.58 g/m2) > one-year enclosure area (299.07 g/m2) > multi-year enclosure control area (254.39 g/m2) > one-year enclosure control area (187.37 g/m2); bclowground biomass: multi-year enclosure (2,906.90 g/m2) > one-year enclosure area (2,587.26 g/m2) > multi-year enclosure control area (2,378.93 g/m") > one-year enclosure control area (2,029.17 g/m"); mean aboveground biomass of natural grassland was 263.60 g/m2, mean belowground biomass 2,225.56 g/m2; ratio of belowground biomass to aboveground biomass varied between 6.79 and 12.90, distribution of bclowground biomass and aboveground biomass in each plot showed significant differences (P <0.05). Enclosure was favorable for improving the coverage and biomass of natural grassland plant communities in the Qilian Mountains. [ABSTRACT FROM AUTHOR]

In the rural area of northern China, residents often use a traditional stove-Kang system to heat their homes, which is an effective way of using locally-produced biomass to solve the energy and environment problems. However, many of these homes are not heated sufficiently during the winter months. The current system is inefficient and requires high levels of fuel consumption. This paper researches the Kang system by creating a simplified and modular system modeling program with the aim to assist in accurate real-time design and optimization of the domestic Kang heating system. This part-1 introduces the structure, principles and the underlying equations of the modular simulation system. A variety of improvement measures were modeled and tested, upon the base model, including the use of a water heat exchanger and radiator system to the existing Kang set up, solar hot water system, bathing system, and the use of phase change material at the surface of the Kang. The program demonstrates good flexibility of implementing different technical solutions as well as fast simulation capability. [ABSTRACT FROM AUTHOR]

The part-2 provides the calibration and validation of the model backbone against the field experimental data. The paper evaluates the simulation results from a myriad of scenarios on their technical ability to increase domestic comfort. Additionally, input from local communities was used to assess rural residents' heating needs and their acceptability of possible solutions. An economic analysis was further used to evaluate the long term feasibility of possible optimized improvements. It was determined that the addition of a room radiator system, consisting of a heat exchanger, water tank, thermostat controls and a panel radiator, delivered the most economical solution in regards to the increasing the resident's comfort per dollar invested. [ABSTRACT FROM AUTHOR]

China 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. [ABSTRACT FROM AUTHOR]

Biomass is widely used by households for cooking and heating in rural China. Along with rapid economic growth over the last three decades, increasing rural households tend to use less biomass and more commercial energy such as coal and electricity. In this paper, we analyzed the key drivers behind energy consumption and switching by rural households based on survey data of energy consumption by rural households in ten villages of Shanxi province in China. Our econometric results show that income growth can induce less use of biomass and more use of coal and modern fuels. However, no evidence shows that even wealthy households has abandoned biomass use in Shanxi, mainly due to the "free" access to land and agricultural resources in these villages. Previous wealth of a household represented by house value can lead to more time spent on biomass collection. Access to land resources has positive effects on biomass use and collection. Other key variables include education, household size, the number of elderly members, and coal price. We also find huge differences between villages, indicating the importance of access to agricultural resources and markets. [ABSTRACT FROM AUTHOR]

The spatial distribution of biomass resources is not uniform. At present, the zoning of biomass energy development suitability is primarily based on resource potential, whereas energy demand is ignored as an important factor affecting the degree of local energy self-sufficiency. Under the constraints of high transportation costs, solar energy with low geographical constraints can be a supplementary energy source for biomass despite its instability. Based on the energy utilization potential of solar energy and biomass resources, this paper evaluates the energy surplus factor (ratio of renewable resource potential to energy demand) of each city in the study area, takes meeting the specific energy surplus factor as the construction prerequisites of biomass combined heat and power (CHP) plants, calculates the biomass resource utilization rate and energy surplus factor in the study area under different conditions, and provides zoning suggestions and data reference for the unified planning of biomass CHP plants. The minimum energy surplus factor that is suitable for the development of biomass energy is set as the construction threshold of biomass CHP plants (The construction threshold is the minimum condition for the construction of biomass CHP plants. Only areas where the energy surplus factor reaches the preset construction threshold are allowed to build biomass CHP plants). The results show that the construction threshold is negatively correlated with the utilization rate of biomass resources. When the construction threshold is less than 1.4, the utilization rate of biomass resources decreases rapidly with the increase of the construction threshold; when the construction threshold is greater than 1.4, the utilization rate of biomass resources decreases slowly and tends to be flat. It is suggested that biomass resources should be developed in different regions and in stages, and priority should be given to developing areas with an energy surplus factor greater than 1.4. Areas with an energy surplus factor of 0.3–1.4 are considered secondary development areas, and areas with an energy surplus factor of less than 0.3 are not recommended for development; these can meet 31% and 59% of the total energy demand and reduce 50319380 tons and 180524400 tons carbon emissions so that the limited construction cost can meet higher energy demand and biomass resource utilization. • Priority development areas are identified based on solar and biomass potential. • Energy surplus factor is calculated to determine the development suitability. • Strategies for zoning and phased planning of biomass resources are proposed. [ABSTRACT FROM AUTHOR]

Densified Biomass Solid Fuel (DBSF) is a typical solid form of biomass, using agricultural and forestry residues as raw materials. DBSF utilization is considered to be an alternative to fossil energy, like coal in China, associated with a reduction of environmental pollution. China has abundant biomass resources and is suitable to develop DBSF. Until now, a number of policies aimed at fostering DBSF industry have been proliferated by policy makers in China. However, considering the seasonality and instability of biomass resources, these inefficiencies could trigger future scarcities of biomass feedstocks, baffling the resilience of biomass supply chains. Therefore, this review paper focuses on DBSF policies and strategies in China, based on the supply chain framework. We analyzed the current developing situation of DBSF industry in China and developed a framework for policy instruments based on the supply chain steps, which can be used to identify and assess the deficiencies of current DBSF industry policies, and we proposed some suggestions. These findings may inform policy development and identify synergies at different steps in the supply chain to enhance the development of DBSF industry. [ABSTRACT FROM AUTHOR]

This paper reviews developments in the direct-fired biomass power sector and provides an up to date investment outlook by calculating the Net Present Value of new investments, and the appropriate level of Feed-in-Tariff needed to stimulate future investment. An overview is provided of support policies, historical growth in installations, and main market players. A number of data sources is combined to build a database with detailed information of individual biopower projects. This data is used to describe technological and market trends, which are used in a cash flow model to calculate the NPV of a typical project. The NPV for new projects is estimated to be negative, and investment should be expected to stall without proper policy intervention. Increasing fuel prices, local competition over biomass fuel resources, lower than expected operational performance and a downturn in carbon markets have deteriorated the investment outlook. In order to ensure reasonable profitability, the Feed-In-Tariff should be increased, from the current level of 90.9 € MWh −1 , to between 97 and 105 € MWh −1 . Where possible, government organizations should help organize demand for the supply of heat. Local rural energy bureaus may help organize supply networks for biomass fuels throughout the country, in order to reduce seasonal and local fuel scarcity and price fluctuations. [ABSTRACT FROM AUTHOR]

Testing ecological models involves using independent data on model performance, which can be difficult or practically impossible to obtain. Individual based models of forest dynamics, or gap models, simulate the change of forests by computing the annual growth, birth and death of each tree at a location in a forest. The models are relatively simple and simulate results that can be translated to multiple response scales: Individual plant growth, population birth-death processes, stand environmental dynamics ( e.g ., evapotranspiration, element cycling, heat flux, etc .), landscape processes, and regional and global change. This paper reviews some of the approaches applied to testing gap models. Then, it demonstrates the testing of the performance of an individual-based gap model of forest dynamics, FAREAST, through comparison against independent data from China and across Russia. As part of this model testing, biomass simulation output for 93 locations is compared to independent field-collected inventory-data from 44 Russian forests, which span a broad range of forest types across Russia. FAREAST captures biomass dynamics and stabilization at specific locations bracketing the measured values. At Changbai Mountain, the model accurately predicts the community dynamics of complex mixed forest types present along an elevational gradient, as well as the broad regional compositional patterns across China and Russia. Validation of regional detailed landscape dynamics shows the model performs with fidelity with an average R2 value of 0.74 for 87 comparisons and an average root mean square error of 10.8 tC ha −1. Performance of the model for historical conditions implies the model's applicability across a broad region and suggests the usefulness of a detailed model for evaluating forest change to management and changing climate. [ABSTRACT FROM AUTHOR]

Three-North Shelterbelt Forest (TSF) program, is one of six key forestry programs and has a 73-year construction period, from 1978 to 2050. Quantitative analysis of the carbon sequestration of shrubs in this region is important for understanding the overall function of carbon sequestration of the forest and other terrestrial ecosystems in China. This study investigated the distribution area of shrubland in the TSF region based on remote sensing images in 1978 and 2008, and calculated the carbon density of shrubland in combination with the field investigation and previous data from published papers. The carbon sequestration quantity and rate from 1978 to 2008 was analyzed for four sub-regions and different types of shrubs in the TSF region. The results revealed that: 1) The area of shrubland in the study area and its four sub-regions increased during the past thirty years. The area of shrubland for the whole region in 2008 was 1.2 × 10 ha, 72.8% larger than that in 1978. The Inner Mongolia-Xinjiang Sub-region was the largest shrubland distribution area, while the highest coverage rate was found in the North China Sub-region. 2) In decreasing order of their carbon sequestration, the four types of shrubs considered in this study were Hippophae rhamnoides, Caragana spp., Haloxylon ammodendron and Vitex negundo var. heterophylla. The carbon sequestration of H. rhamnoides, with a maximum mean carbon density of 16.5 Mg C/ha, was significantly higher than that of the other three species. 3) The total carbon sequestration of shrubland in the study region was 4.5 × 10 Mg C with a mean annual carbon sequestration of 1.5 × 10 Mg C. The carbon density in the four sub-regions decreased in the following order: the Loess Plateau Sub-region, the North China Sub-region, the Northeast China Sub-region and the Inner Mongolia-Xinjiang Sub-region. The paucity of studies and data availability on the large-scale carbon sequestration of shrub species suggests this study provides a baseline reference for future research in this area. [ABSTRACT FROM AUTHOR]

As a major technical route to utilize biomass energy, biomass combustion power generation (BCPG) has been shown to be of environmental and economic significance. According to the operating experience, the installed capacity has a decisive impact on the operation and economic return of BCPG projects. In China, an installed capacity of either 30 MW or 12 MW is often chosen for constructing a BCPG project. To explore which one is more suitable for China, this paper uses actual operating data to compare the operation performance and techno-economics of two representative BCPG projects with an installed capacity of 30 MW and 12 MW. The results show that the operation situation and electricity production of the 30 MW project are better than those of the 12 MW project. The 30 MW project has a lower biomass consumption than the 12 MW project to produce per unit of electricity. The Internal Rate of Return (IRR) of the 30 MW project is greater than the industry benchmark in China and is almost three times the IRR of the 12 MW project. Therefore, it is recommended to construct BCPG projects with installed capacity of 30 MW in China. [ABSTRACT FROM AUTHOR]

Abstract: Biogas technology has brought benefits to health, the environment, the economy and energy conservation. Vast biomass resources, including organic waste, have the potential for use as feedstock for biogas production in China. This paper presents the development status of biogas application in China. The goal was to provide quantitative information about biogas use, from villages to large cities, to assess the major characteristics of biogas application. Analysis of the opportunities and constraints of the different biogas applications provided the basis for policies for the development of biogas plants and for the adjustment of the scale of biogas development to match local requirements. Based on the characteristics of different biogas plants and geographic regions, a fuzzy analytic hierarchy process model was used to provide a suitability evaluation for development of the regional biogas industry. Results from this model could provide decision support for development strategies for regional distribution plans and the scale of biogas system construction. The findings can also aid further research on balancing energy supply and demand, energy policy formation, and the regional eco-environment development in China. [Copyright &y& Elsevier]

Urban forest has undergone rapid development in China over the last three decades because of the acceleration of urbanization. Urban forest thus plays an increasingly important role in carbon sequestration at a regional and national scale. As one of the most urbanized cities in China, Shanghai showed an increase of forest coverage from 3% in the 1990s to 13% in 2009. Based on CITY-green model and the second soil survey of Shanghai, the forest biomass carbon (FBC) was estimated to be 0.48 Tg in the urban area and, forest soil organic carbon (SOC) (0-100 cm soil depth) is 2.48 Tg in the urban and suburban areas, respectively. These values are relatively within the median and lower level compared with other Chinese megacities, with the FBC of 0.02 Tg in Harbin to 47.29 Tg in Chongqing and the forest SOC of 1.74 Tg in Nanjing to 418.67 Tg in Chongqing. For the different land-use types in Shanghai, the SOC density ranges from 13.8 (tidal field) to 38.6 t ha (agricultural land). On average, the forest SOC density (31.5 t ha) in Shanghai is lower than that in agricultural lands (38.6 t ha) and higher than that in lawns (26.5 t ha) and gardens (21.3 t ha). In Shanghai, the SOC density in newly established urban parks is generally lower than that in older parks. In the northern and southeastern suburban areas (e.g., Baoshan, Yangpu, and Nanhui districts), greenspace SOC density is higher than that in the central commercial areas (Hongkou, Putuo, Changning, and Zhabei districts) and in newly developed district (Pudong District). Uncertainties still exist in the estimation of urban forest carbon in Shanghai, as well as in other Chinese cities. Thus, future research directions are also discussed in this paper. [ABSTRACT FROM AUTHOR]