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The Nigerian government is committed to sustaining rice production to meet national demand. Nevertheless, political tension and climate-induced stressors remain crucial constraints in achieving policy targets. This study examines whether climate change and political instability significantly threaten rice production in Nigeria. First, we employed nonparametric methods to estimate the country's rainfall and temperature trends between 1980Q1 and 2015Q4. Second, we employed the autoregressive distributed lag (ARDL) technique to examine the effects of climate change and political instability on rice production. The results show that while temperature has an increasing pattern, rainfall exhibits no significant trend. The findings from the ARDL estimate reveal that rice production responds negatively to temperature changes but is less sensitive to changes in rainfall. In addition, political instability adversely affects rice production in Nigeria. We argue that Nigeria's slow growth in rice production can be traced back to the impact of climate change and political tension in rice farming areas. As a result, reducing the overall degree of conflict to ensure political stability is critical to boosting the country's self-sufficiency in rice production. We also recommend that farmers be supported and trained to adopt improved rice varieties less prone to extreme climate events while supporting them with irrigation facilities to facilitate rice production.

• Premise of the study: Climate change is associated with phenological shifts in an increasing number of organisms worldwide. However, accurate estimates of these shifts are dependent on long‐term data sets that include phenological observations from before annual average temperatures began to rise.• Methods: We compared the first flowering times of native prairie plants between 2007 and 2010 with historical data recorded by O. A. Stevens from 1910 to 1961. By merging climate variable data from the same time period, it also was possible to correlate first flowering dates with associated climate variables.• Key results: Over the past 100 years, spring temperatures in the Red River Valley near Fargo, North Dakota, USA, have increased, and growing seasons have lengthened significantly. Seventy‐five percent of the 178 species observed by Stevens had flowering times that were sensitive to at least one variable related to temperature or precipitation. Over the past 4 yr, 5% to 17% of the species observed have significantly shifted their first flowering time either earlier or later relative to the previous century.• Conclusions: The results of this study indicate that as spring temperatures in the northern Great Plains have increased and the growing season has lengthened, some spring flowering species have advanced their first flowering time, some fall species have delayed their first flowering, and some species have not changed. Given the importance of flowering timing for reproductive success, the changing climate in the Great Plains is expected to have long‐term ecological and evolutionary consequences for native plant species.

Abstract Kenya has made considerable policy efforts to expand its renewable energy portfolio to meet energy demand and mitigate greenhouse gas (GHG) emissions. Development of proper policies requires a robust framework for analyzing the benefits of renewable energy investments. Towards this end, this study applied a choice experiment analysis to determine how attributes (type of energy, ownership, impact on environment, distance and visibility, community job creation, and yearly renewable energy tax) impact the public willingness to pay for renewable energy development in Kenya. A nationwide survey of 1020 households was conducted in nine counties using conditional logit (MNL) and random parameter logit (RPL) frameworks. The results reveal that the Kenyan public places a high value on environmental impact, followed by type of renewable energy and community job creation, respectively. On the other hand, respondents do not place much emphasis on ownership or distance and visibility. Policy simulation suggests that while renewable energy adoption is highly valued by households, the total willingness to pay is not enough to cover the higher capital cost for the development of various renewable energy technologies.

Integrated assessment models (IAMs) are playing an increasingly important role in long-run sustainability analysis. At their core is a set of global economic and environmental accounts which capture a complete set of inter-industry and inter-regional relationships in the global economy in a consistent manner. While much attention is focused on the raw data and parameterization required to expand or add sectoral detail to IAMs, only rarely is there discussion of how different matrix balancing methods (i.e. translating disparate raw data sources into the consistent database) affect modeling results. This article offers an in-depth look into the database–modeling nexus in IAMs, focusing on the electric power sector which is both a major source of CO2 emissions and a critical vehicle for climate change mitigation. Comparisons of the prevailing matrix balancing algorithms show how the choice of database reconciliation methodology affects modeling results using policy-relevant simulations in the context of the electric power sector. The resulting insights can be applied to the disaggregation of other, technology rich sectors in the economy. We conclude that appropriate selection of database reconciliation methodologies can reduce the deviation between bottom-up and top-down modeling.

The paper proposes a critical assessment of municipal solid waste gasification today, starting from basic aspects of the process (process types and steps, operating and performance parameters) and arriving to a comparative analysis of the reactors (fixed bed, fluidized bed, entrained bed, vertical shaft, moving grate furnace, rotary kiln, plasma reactor) as well as of the possible plant configurations (heat gasifier and power gasifier) and the environmental performances of the main commercially available gasifiers for municipal solid wastes. The analysis indicates that gasification is a technically viable option for the solid waste conversion, including residual waste from separate collection of municipal solid waste. It is able to meet existing emission limits and can have a remarkable effect on reduction of landfill disposal option.

Microbial production of ethanol might be a potential route to replace oil and chemical feedstocks. Bioethanol is by far the most common biofuel in use worldwide. Lignocellulosic biomass is the most promising renewable resource for fuel bioethanol production. Bioconversion of lignocellulosics to ethanol consists of four major unit operations: pretreatment, hydrolysis, fermentation, and product separation/distillation. Conventional bioethanol processes for lignocellulosics apply commercial fungal cellulase enzymes for biomass hydrolysis, followed by yeast fermentation of resulting glucose to ethanol. The fungus Neurospora crassa has been used extensively for genetic, biochemical, and molecular studies as a model organism. However, the strain's potential in biotechnological applications has not been widely investigated and discussed. The fungus N. crassa has the ability to synthesize and secrete all three enzyme types involved in cellulose hydrolysis as well as various enzymes for hemicellulose degradation. In addition, N. crassa has been reported to convert to ethanol hexose and pentose sugars, cellulose polymers, and agro-industrial residues. The combination of these characteristics makes N. crassa a promising alternative candidate for biotechnological production of ethanol from renewable resources. This review consists of an overview of the ethanol process from lignocellulosic biomass, followed by cellulases and hemicellulases production, ethanol fermentations of sugars and lignocellulosics, and industrial application potential of N. crassa.

This paper examines methods of extending the edible quality of food products by modified atmosphere packaging. Also discussed are developments giving improvements in product handling flexibility, output, reliability and hygiene.

The Keelung port, which is located on the northern tip of Taiwan, right next to the Taipei metropolitan area, is an important international harbor. However, any air pollutants generated from the Keelung port region, immediately travel to the neighboring Keelung city, and greatly impact the residents' daily life and the quality of their environment. This study has investigated and quantified pollution emissions, from the Keelung port region, between 1997 and 2002. Emissions from major air pollution sources were estimated. The estimated results indicated that total TSP (total suspended particles) emissions had significantly increased, from 5221 ton/yr in 1997 to 262 687 ton/yr in 2002, due to the greatly increased volume of sand imported into Keelung Harbor. Quantities of other emissions, such as SO(2), NO(2), CO and HC remained stable and were 440, 207, 78 and 25 ton/yr, respectively, on average, with variations within 7% over the previous six-year period. By examining the emissions from pollution sources, it was found that TSP emissions mainly originated from re-suspension of dust, due to both vehicle movement and the sand unloading process; this accounted for over 99% of the total TSP emissions produced in the port region. About 80% of the total SO(2) emissions originated from the main ships' engines within the Keelung port region, due to the use of fuel with a high sulfur content. In addition, loading/unloading machines within the port region were the major sources of NO(2), CO and HC pollution emissions, which comprised 54, 58 and 66% of the total emissions of these pollutants, respectively. TSP emissions from Keelung port were much higher than from the neighboring Keelung city; hence, alleviating TSP emissions should be the first priority for air pollution reduction within both the port of Keelung and Keelung city.

Along with the growth and globalization of the whole world economy since the First Industrial Revolution, the production and use of fossil fuels have led to increased CO2 emissions and, ultimately, significant environmental degradation. The impact of globalization, economic growth, and renewable energy sources on CO2 may show trends with different turning points in developing countries, and estimations may need to follow Fourier-type functions to capture the frequency domain. Therefore, the aim of this study is to examine the effects of renewable energy production, economic globalization, and economic growth on CO2 emissions for Turkey in the period 1971-2006 with Fourier autoregressive distribution lag (ADL) cointegration, DOLS, and Fourier-Granger causality tests. The originality of this study is the estimation of a model of CO2 emissions with a Fourier-type function for the first time. The findings indicate a negative relationship between renewable energy production and CO2 emissions and a positive relationship between economic globalization and economic growth and CO2 emissions. In addition, according to the empirical results, there exists a one-way causality relationship between economic globalization to CO2 and economic globalization to renewable energy production, and there is evidence of a bidirectional causality relationship between economic globalization and economic growth in this study.