• Energy Research
• 15. Life on land close
• IN close
• PK close
• SA close

Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.

Abstract The co-pyrolysis of Single-use low density polyethylene (LDPE) and Eucalyptus biomass (EuBm) can be considered as a sustainable waste management technique to produce viable byproducts. This study elucidates the effects of variable temperatures (300–600 °C), residence times (90–150 minutes), and proportions of LDPE (0.25, 0.33 (w/w)) on physicochemical characteristics of LDPE - EuBm char composites. The interference of liquified polymer coating on the surface with degradation of biomass could be the reason for low nutrient extractability of chars synthesized at 300 and 400 °C. These chars were rich in volatile matter (> 68 %) and their pores were filled with partially pyrolyzed products. Interestingly however, substantial changes in properties were observed at 500 °C due to the likely synergetic effect between the feeds. The highest plant-extractable concentrations of major nutrients (Na, K, Ca, Mg, NO3−, PO43-), electrical conductivity (4.73 mS/cm), and cation exchange capacity (50.5 Cmolc/kg) of char were observed at this temperature. The optimization through regression modeling identified 524 °C, 118 min, and 31 % (w/w) of LDPE as optimal process parameters to obtain char suitable for application in soil. Soil incubation test fortified the benefits of char to soil with 3.5 times improvement in soil fertility index at 5 % (w/w) rate of application.

Countries in Sub-Saharan Africa are particularly vulnerable to climate change, given dependence on agricultural production and limited adaptive capacity. Based on farm household and Participatory Rural Appraisal data collected from districts in various agroecological zones in Kenya, this paper examines farmers' perceptions of climate change, ongoing adaptation measures, and factors influencing farmers' decisions to adapt. The results show that households face considerable challenges in adapting to climate change. While many households have made small adjustments to their farming practices in response to climate change (in particular, changing planting decisions), few households are able to make more costly investments, for example in agroforestry or irrigation, although there is a desire to invest in such measures. This emphasizes the need for greater investments in rural and agricultural development to support the ability of households to make strategic, long-term decisions that affect their future well-being.

Coastal communities in the Coral Triangle are increasingly threatened by climate change. Sea-level rise (SLR) will result in biophysical and socioeconomic impacts that could increase the loss of livelihoods, cultural heritage and infrastructure. Effective adaptation requires a holistic approach that incorporates scientific knowledge together with local and traditional knowledge. Community-based adaptation built on local knowledge is of great value for environmental management, particularly when scientific data are lacking. This article reports a case study that integrated traditional and scientific knowledge using participatory three-dimensional modeling (P3DM) in BoeBoe village, Solomon Islands. P3DM is a process by which members of the local community build a physical terrain model and overlay it with the location of important resources such as protected areas or harvesting sites. Additionally, SLR inundation scenarios based on surveyed elevations were incorporated into a geographic information system (GIS), allowing for a real-time integration of science with local knowledge. Despite discrepancies in scales and accuracy, information from both the P3DM and GIS were complementary. The process, itself, provided a forum for discussion between many members of the village who would normally not be involved and highlighted the importance of community engagement when building capacity for adaptation to climate change.

The potential of different agro-wastes like green grass (Cynodon dactylon (L.)), bagasse, algae (Enteromorpha spp.), banana stem and water hyacinth (Eichhornia crassipes) in combination with cattle dung for methane production by anaerobic digestion have been evaluated. The results indicate that these wastes can be exploited for methane generation in combination with cattle dung. Best results were obtained with green grass when it was combined with cattle dung in the ratio of 1:4.

AbstractAgeratum conyzoides, an herb found throughout the year, is generally considered as a weed: it causes reduction in soil productivity and leads to health hazards for cattle and humans. However, its biomass can easily represent a cost‐effective source, which can be used for lignocellulosic biofuel production. The conversion of lignocellulosic biomass to ethanol has drawn much attention in recent times due to abundance of biomass. In the present study, the cellulose and hemicellulose biomass of the leaf and stem of A. conyzoides was converted to sugars using acid hydrolysis.146.01 ± 02 mg/g of fermentable sugar was obtained from A. conyzoides. The maximum ethanol concentration 11.89 g/L was obtained after 7 days. Scanning electron microscopy was used to characterize the surface morphology after acid hydrolysis of biomass. In the current study, the residues of acid hydrolysis and fermented wastewater was used for biogas production through anaerobic digestion. The yield of biogas from the residues of acid hydrolysis and fermented wastewater was 204 L kg−1VS. The results obtained indicate that A. conyzoides may be considered as a promising feedstock for bioethanol and biogas production.

The study reports estimates of above ground phytomass carbon pools in Indian forests for 1992 and 2002 using two different methodologies. The first estimate was derived from remote sensing based forest area and crown density estimates, and growing stock data for 1992 and 2002 and the estimated pool size was in the range 2,626–3,071 Tg C (41 to 48 Mg C ha-1) and 2,660–3,180 Tg C (39 to 47 Mg C ha-1) for 1992 and 2002, respectively. The second methodology followed IPCC 2006 guidelines and using an initial 1992 pool of carbon, the carbon pool for 2002 was estimated to be in the range of 2,668–3,112 Tg C (39 to 46 Mg C ha-1), accounting for biomass increment and removals for the period concerned. The estimated total biomass increment was about 458 Tg over the period 1992–2002. Removals from forests include mainly timber and fuel wood, whereby the latter includes large uncertainty as reported extraction is lower than actual consumption. For the purpose of this study, the annual extraction values of 23 million m3 for timber and 126 million m3 for fuel wood were used. Out of the total area, 10 million ha are plantation forests with an average productivity (3.2 Mg ha-1 year-1) that is higher than natural forests, a correction of 408 Tg C for the 10 year period was incorporated in total estimated phytomass carbon pool of Indian forests. This results in an estimate for the net sink of 4 Tg C year-1. Both approaches indicate Indian forests to be sequestering carbon and both the estimates are in agreement with recent studies. A major uncertainty in Indian phytomass carbon pool dynamics is associated with trees outside forests and with soil organic carbon dynamics. Using recent remote-sensing based estimates of

Asseng, S. et al. Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time. We thank the Agricultural Model Intercomparison and Improvement Project and its leaders C. Rosenzweig from NASA Goddard Institute for Space Studies and Columbia University (USA), J. Jones from University of Florida (USA), J. Hatfield from United States Department of Agriculture (USA) and J. Antle from Oregon State University (USA) for support. We also thank M. Lopez from CIMMYT (Turkey), M. Usman Bashir from University of Agriculture, Faisalabad (Pakistan), S. Soufizadeh from Shahid Beheshti University (Iran), and J. Lorgeou and J-C. Deswarte from ARVALIS—Institut du Végétal (France) for assistance with selecting key locations and quantifying regional crop cultivars, anthesis and maturity dates and R. Raymundo for assistance with GIS. S.A. and D.C. received financial support from the International Food Policy Research Institute (IFPRI). C.S. was funded through USDA National Institute for Food and Agriculture award 32011-68002-30191. C.M. received financial support from the KULUNDA project (01LL0905L) and the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (BMBF). F.E. received support from the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (2812ERA115) and E.E.R. was funded through the German Science Foundation (project EW 119/5-1). M.J. and J.E.O. were funded through the FACCE MACSUR project by the Danish Strategic Research Council. K.C.K. and C.N. were funded by the FACCE MACSUR project through the German Federal Ministry of Food and Agriculture (BMEL). F.T., T.P. and R.P.R. received financial support from FACCE MACSUR project funded through the Finnish Ministry of Agriculture and Forestry (MMM); F.T. was also funded through National Natural Science Foundation of China (No. 41071030). C.B. was funded through the Helmholtz project ‘REKLIM—Regional Climate Change: Causes and Effects’ Topic 9: ‘Climate Change and Air Quality’. M.P.R. and P.D.A. received funding from the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS). G.O’L. was funded through the Australian Grains Research and Development Corporation and the Department of Environment and Primary Industries Victoria, Australia. R.C.I. was funded by Texas AgriLife Research, Texas A&M University. E.W. and Z.Z. were funded by CSIRO and the Chinese Academy of Sciences (CAS) through the research project ‘Advancing crop yield while reducing the use of water and nitrogen’ and by the CSIRO-MoE PhD Research Program. Peer reviewed