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Rural household income growth may have two counteracting effects on energy-related carbon emissions, by stimulating total energy consumption and by changing the energy structure towards low-carbon energy sources. This study aims to provide more insight into this relationship for the case of rural central China, a region where coal-fired electricity dominates modern energy consumption. Based on survey data collected in 2019, energy-related carbon emissions (ECE) and energy-related carbon intensity (ECI) per unit of energy are calculated. A mediation effect model is employed to distinguish between energy structure changes and total electricity consumption as mediating factors in the income growth – carbon emission relationship. We argue that whether biomass fuels are treated as either carbon-intensive or as carbon neutral has major consequences for the analysis. When biomass fuel is treated as carbon-intensive, income-related changes in energy structure and electricity consumption have opposite effects on ECE, but both are conducive to the reduction of ECI. When biomass fuel is treated as carbon-neutral, the positive effect of growth in coal-fired electricity consumption on ECE is much larger than the negative effect of the change in energy structure. Based on these findings, we present several recommendations for balancing two main targets of China's rural revitalization vitalization policy, i.e. rural household income growth and the transition towards low-carbon energy sources in China.

Rural household income growth may have two counteracting effects on energy-related carbon emissions, by stimulating total energy consumption and by changing the energy structure towards low-carbon energy sources. This study aims to provide more insight into this relationship for the case of rural central China, a region where coal-fired electricity dominates modern energy consumption. Based on survey data collected in 2019, energy-related carbon emissions (ECE) and energy-related carbon intensity (ECI) per unit of energy are calculated. A mediation effect model is employed to distinguish between energy structure changes and total electricity consumption as mediating factors in the income growth – carbon emission relationship. We argue that whether biomass fuels are treated as either carbon-intensive or as carbon neutral has major consequences for the analysis. When biomass fuel is treated as carbon-intensive, income-related changes in energy structure and electricity consumption have opposite effects on ECE, but both are conducive to the reduction of ECI. When biomass fuel is treated as carbon-neutral, the positive effect of growth in coal-fired electricity consumption on ECE is much larger than the negative effect of the change in energy structure. Based on these findings, we present several recommendations for balancing two main targets of China's rural revitalization vitalization policy, i.e. rural household income growth and the transition towards low-carbon energy sources in China.

Due to the high nitrogen and phosphorus content, source-separated urine can serve as a major nutrient source for microalgae production. The aim of this study was to evaluate the nutrient removal rate and the biomass production rate of Chlorella sorokiniana being grown continuously in urine employing a short light-path photobioreactor. The results demonstrated, for the first time, the possibility of continuous microalgae cultivation in human urine. The lowest dilution factor successfully employed was a factor of 2 (50% v/v urine). Microalgae dominated a smaller bacterial population and were responsible for more than 90% of total nitrogen and phosphorus removal. With a light-path of 10 mm, a maximum volumetric biomass productivity as high as 9.3 g L(-1) d(-1) was achieved. The co-existing bacterial population removed up to 70% of organic pollutants from the urine at a rate of 1300 mg COD L(-1) d(-1). Enriching the urine with magnesium, adjusting the N:P molar ratio, and shortening the reactor light-path further increased the volumetric biomass productivity to 14.8 g L(-1) d(-1). The corresponding nitrogen and phosphorus removal rates were 1300 and 150 mg L(-1) d(-1), respectively. The subsequently produced biomass contained 43-53% w/w proteins and 16-25% w/w total fatty acids.

Due to the high nitrogen and phosphorus content, source-separated urine can serve as a major nutrient source for microalgae production. The aim of this study was to evaluate the nutrient removal rate and the biomass production rate of Chlorella sorokiniana being grown continuously in urine employing a short light-path photobioreactor. The results demonstrated, for the first time, the possibility of continuous microalgae cultivation in human urine. The lowest dilution factor successfully employed was a factor of 2 (50% v/v urine). Microalgae dominated a smaller bacterial population and were responsible for more than 90% of total nitrogen and phosphorus removal. With a light-path of 10 mm, a maximum volumetric biomass productivity as high as 9.3 g L(-1) d(-1) was achieved. The co-existing bacterial population removed up to 70% of organic pollutants from the urine at a rate of 1300 mg COD L(-1) d(-1). Enriching the urine with magnesium, adjusting the N:P molar ratio, and shortening the reactor light-path further increased the volumetric biomass productivity to 14.8 g L(-1) d(-1). The corresponding nitrogen and phosphorus removal rates were 1300 and 150 mg L(-1) d(-1), respectively. The subsequently produced biomass contained 43-53% w/w proteins and 16-25% w/w total fatty acids.

Serengeti National Park is famed for its wildlife migration tourism for decades. The park contributes substantially to country’s revenue and is a major employment arena that is based on tourism activities. Wildlife migration is the major tourist attraction in Serengeti and climate-dependent. There is a growing concern that climate has changed significantly with potential influence on wildlife migration. However, the knowledge of the consequences of climate-change on Serengeti’s tourism are poorly known. This paper analyses the consequences of rainfall and temperature variability and change, and associated land-cover changes on major tourist attractions and tourism over the past four decades. The results show that natural climate is an important factor shaping tourism seasonality and tourist attractions in Serengeti. Key impacts of increasing rainfall and temperature variability, and associated land-cover change include disruption of tourism seasonality, wildebeest migration patterns, and reduced diversity of tourist attractions. Both negatively affect tourism by reducing the park’s attractiveness. Adapting tourism to climate-change impacts requires active and integrated management approaches that improve the park’s attractiveness. The results can be used to develop climate-change adaptation strategies and inform conservation and tourism planning.

Serengeti National Park is famed for its wildlife migration tourism for decades. The park contributes substantially to country’s revenue and is a major employment arena that is based on tourism activities. Wildlife migration is the major tourist attraction in Serengeti and climate-dependent. There is a growing concern that climate has changed significantly with potential influence on wildlife migration. However, the knowledge of the consequences of climate-change on Serengeti’s tourism are poorly known. This paper analyses the consequences of rainfall and temperature variability and change, and associated land-cover changes on major tourist attractions and tourism over the past four decades. The results show that natural climate is an important factor shaping tourism seasonality and tourist attractions in Serengeti. Key impacts of increasing rainfall and temperature variability, and associated land-cover change include disruption of tourism seasonality, wildebeest migration patterns, and reduced diversity of tourist attractions. Both negatively affect tourism by reducing the park’s attractiveness. Adapting tourism to climate-change impacts requires active and integrated management approaches that improve the park’s attractiveness. The results can be used to develop climate-change adaptation strategies and inform conservation and tourism planning.

The microbial electrolysis cell (MEC) is a promising system for H2 production, but little is known about the active microbial population in MEC systems. Therefore, the microbial community of five different MEC graphite felt anodes was analyzed using denaturing gradient gel electrophoresis (DGGE) profiling. The results showed that the bacterial population was very diverse and there were substantial differences between microorganisms in anolyte and anode samples. The archaeal population in the anolyte and at the anodes, and between the different MEC anodes, was very similar. SEM and FISH imaging showed that Archaea were mainly present in the spaces between the electrode fibers and Bacteria were present at the fiber surface, which suggested that Bacteria were the main microorganisms involved in MEC electrochemical activity. Redundancy analysis (RDA) and QR factorization-based estimation (QRE) were used to link the composition of the bacterial community to electrochemical performance of the MEC. The operational mode of the MECs and their consequent effects on current density and anode resistance on the populations were significant. The results showed that the community composition was most strongly correlated with current density. The DGGE band mostly correlated with current represented a Clostridium sticklandii strain, suggesting that this species had a major role in current from acetate generation at the MEC anodes. The combination of RDA and QRE seemed especially promising for obtaining an insight into the part of the microbial population actively involved in electrode interaction in the MEC.

The microbial electrolysis cell (MEC) is a promising system for H2 production, but little is known about the active microbial population in MEC systems. Therefore, the microbial community of five different MEC graphite felt anodes was analyzed using denaturing gradient gel electrophoresis (DGGE) profiling. The results showed that the bacterial population was very diverse and there were substantial differences between microorganisms in anolyte and anode samples. The archaeal population in the anolyte and at the anodes, and between the different MEC anodes, was very similar. SEM and FISH imaging showed that Archaea were mainly present in the spaces between the electrode fibers and Bacteria were present at the fiber surface, which suggested that Bacteria were the main microorganisms involved in MEC electrochemical activity. Redundancy analysis (RDA) and QR factorization-based estimation (QRE) were used to link the composition of the bacterial community to electrochemical performance of the MEC. The operational mode of the MECs and their consequent effects on current density and anode resistance on the populations were significant. The results showed that the community composition was most strongly correlated with current density. The DGGE band mostly correlated with current represented a Clostridium sticklandii strain, suggesting that this species had a major role in current from acetate generation at the MEC anodes. The combination of RDA and QRE seemed especially promising for obtaining an insight into the part of the microbial population actively involved in electrode interaction in the MEC.