Government incentive policies play an important role in the promotion of distributed photovoltaic power. However, which policy is more effective for the diffusion of distributed photovoltaic power? This is a question that needs to be answered. Based on this, we combined the two-factor learning curve and system dynamics model to study the dynamic diffusion process of China’s distributed photovoltaic power (DSP). The results show that (1) the coefficients of learning by doing and learning by researching for DSP are 0.0435 and 0.2971 respectively. This indicates that technological innovation caused by R&D expenditures in the DSP is the driving force for cost reduction. (2) Both demand-pull and technology-push policies contribute to the diffusion of DSP; (3) the effect of FIT policy on the diffusion of distributed photovoltaic technology is more significant than that of R&D policy; and the reduction of production cost of photovoltaic power industry by R&D policy is more significant than FIT policy.

The following work provides a perspective on the potential application of solar heterogeneous photocatalysis, which is a nonselective advanced oxidation process considered as a sustainable technology, to assist in arsenic removal from water, which is a global threat to human health. Heterogeneous photocatalysis can oxidize trivalent arsenic to pentavalent arsenic, decreasing its toxicity and easing its removal with other technologies, such as chemical precipitation and adsorption. Several lab-scale arsenic photocatalytic oxidation and diverse solar heterogeneous photocatalytic operations carried out in different reactor designs are analyzed. It was found out that this technology has not been translated to operational pilot plant scale prototypes. General research on reactors is scarce, comprising a small percentage of the photocatalysis related scientific literature. It was possible to elucidate some operational parameters that a reactor must comply to operate efficiently. Reports on small-scale application shed light that in areas where other water purification technologies are economically and/or technically not suitable, and the solar energy is available, shed light on the fact that solar heterogeneous photocatalysis is highly promissory within a water purification process for removal of arsenic from water.

Climate change and increased greenhouse gas emissions boost the global average temperature to less than 2°C, which is the estimated breakeven point. The globe is moving into blue pollution economies as the environmental sustainability objective becomes more distorted. The study looked at three United Nations Sustainable Development Goals, namely (i) affordable and clean energy; (ii) industry, innovation, and infrastructure; and (iii) climate change, to see how far the Chinese economy has progressed toward green and clean development strategy. In the context of China, the “pollution damage function” was intended to refer to carbon damages related to carbon pricing, technological variables, sustained economic growth, incoming foreign investment, and green energy. The data was collected between 1975 and 2019 and analyzed using various statistical approaches. The results of the autoregressive distributed lag model suggest that carbon taxes on industrial emissions reduce carbon damages in the short and long run. Furthermore, a rise in inbound foreign investment and renewable energy demand reduces carbon damages in the short term, proving the “pollution halo” and “green energy” hypotheses; nonetheless, the results are insufficient to explain the stated results in the long run. In the long run, technology transfers and continued economic growth are beneficial in reducing carbon damages and confirming the potential of cleaner solutions in pollution mitigation. The causal inferences show the one-way relationship running from carbon pricing and technology transfer to carbon damages, and green energy to high-technology exports in a country. The impulse response estimates suggested that carbon tax, inbound foreign investment, and technology transfers likely decrease carbon damages for the next 10 years. On the other hand, continued economic growth and inadequate green energy sources are likely to increase carbon pollution in a country. The variance decomposition analysis suggested that carbon pricing and information and communication technology exports would likely significantly influence carbon damages over time. To keep the earth’s temperature within the set threshold, the true motivation to shift from a blue to a green economy required strict environmental legislation, the use of green energy sources, and the export of cleaner technologies. Source: Authors’ self-extract

This study aims to showcase the adaptability evaluation of human settlements in Chengdu with the use of 3S technology. Chengdu was selected as the research object; natural eco-environmental factors such as terrain fluctuations, temperature and humidity, vegetation type, land use, and vegetation cover were analyzed, together with human disturbance factors such as traffic and gross domestic product (GDP); and the index weights were calculated by analytic hierarchy process (AHP). The evaluation model of Chengdu’s residential environment adaptability was constructed based on the analysis carried out by the 3S technology: projection transformation, remote sensing interpretation, information extraction, and analysis. The results of the analysis reflected the zoning and spatial distribution characteristics of Chengdu’s residential environment adaptability, and show that (1) the adaptability index of Chengdu’s human settlement environment is between 15.98 and 76.75, and the suitability of human settlement environment is seen gradually decreasing from the middle, where it is the highest, when moving to the west and to the east of Chengdu; (2) according to the present situation, the suitability index can be divided into high-grade suitable areas, relatively high-grade suitable areas, moderately suitable areas, and low suitable areas; (3) the correlation between the spatial distribution of Chengdu population and each index factor is as follows: per capita GDP > topographic relief > temperature and humidity > vegetation coverage > traffic network density > land use > hydrological factors; (4) there is a good correlation between Chengdu’s human settlements suitability index and the present population density grid layer, and its correlation coefficient is 0.7326; and (5) the leading impact indicators of human settlements are different in different regions. The results show that the natural environmental conditions in Chengdu are superior and that the ecological environmental quality is relatively stable, but the human settlement suitability index is relatively low in the southeast and Longmenshan areas of Chengdu.

The pollution of wastewater with dyes has become a serious environmental problem around the world. In this context, the work aims to synthesize and characterize a supported nanocatalyst (NZ-180) from rice husk (RH) and alum sludge (AS) incorporating silver (AgNPs@NZ-180) and titanium nanoparticles (TiNPs@NZ-180) for Rhodamine B (RhB) dye degradation, under UV and visible irradiation. Central rotatable composite design (CRCD) was used to determine ideal conditions, using nanocatalyst and dye concentration such as input variables and degradation percentage like response variable. Samples were characterized by XRD, SEM-EDS, N₂ porosimetry, DLS, and zeta potential analyses. TiNPs@NZ-180 showed the best photocatalytic activity (62.62 and 50.82% under UV and visible irradiation, respectively). Specific surface area has increased from 35.90 to 418.90 m² g⁻¹ for NZ-180 and TiNPs@NZ-180, respectively. Photocatalytic performance of TiNPs@NZ-180 has reduced to 8 and 10% after 5 cycles under UV and visible light irradiation. Ideal conditions found by CRCD were 2.75 g L⁻¹ and 20 mg L⁻¹ for nanocatalyst and RhB concentrations, respectively. Therefore, (agro)industrial waste present such an alternative material for application in the removal of wastewater with dyes, which helps in the reduction of the impact of chemicals/pollutants on human and animal health.

The physiological impacts and interactions of antibiotic resistance gene (ARG) abundance, microcystin synthetase gene expression, graphene oxide (GO), and Microcystis aeruginosa in synthetic wastewater were investigated. The results demonstrated that the absolute abundance of sul1, sul2, tetW, and tetM in synthetic wastewater dramatically increased to 365.2%, 427.1%, 375.2%, and 231.7%, respectively, when the GO concentration was 0.01 mg/L. Even more interesting is that the sum gene copy numbers of mcyA-J also increased to 243.2%. The appearance of GO made the significant correlation exist between ARGs abundance and mcyA-J expression. Furthermore, M. aeruginosa displayed better photosynthetic performance and more MCs production at 0.01 mg/L GO. There were 65 pairs of positive correlations between the intracellular differential metabolites of M. aeruginosa and the abundance of sul1, sul2, tetM, and tetW with various GO concentrations. The GO will impact the metabolites and metabolic pathway in M. aeruginosa. The metabolic changes impacted the ARGs, microcystin synthetase genes, and physiological characters in algal cells. Furthermore, there were complex correlations among sul1, sul2, tetM, tetW, mcyA-J, MCs, photosynthetic performance parameters, and ROS. The different concentration of GO will aggravate the hazards of M. aeruginosa by promoting the expression of mcyA-J, producing more MCs; simultaneously, it may cause the spread of ARGs.

People’s sentiments and perceptions of greenhouse gas emission and renewable energy are important information to understand their reaction to the planned mitigation policy. Therefore, this research analyzes people’s perceptions of greenhouse gas emissions and their preferences for renewable energy resources using a sample of Twitter data. We first identify themes of discussion using semantic text similarity and network analysis. Next, we measure people’s interest in renewable energy resources based on the mentioned rate in Twitter and search interest in Google trends. Then, we measure people’s sentiment toward these resources and compare the interest with sentiments to identify opportunities for policy improvement. The results indicate a minor influence of governmental assemblies on Twitter discourses compared to a very high influence of two renewable energy providers amounts to more than 40% of the tweeting activities related to renewable energy. The search interest analysis shows a slight shift in people’s interest in favor of renewable energy. The interest in geothermal energy is decreasing while interest in biomass energy is increasing. The sentiment analysis shows that biomass energy has the highest positive sentiments while solar and wind energy have higher interest. Solar and wind energy are found to be the two most promising sources for the future energy transition. Our study implies that governments should practice a higher influence on promoting awareness of the environment and converging between people’s interests and feasible energy solutions. We also advocate Twitter as a source for collecting real-time data about social preferences for environmental policy input.

A massive bird dropping (BD) deposition on the common rectangular flat plate (RFP) of photovoltaic (PV) module is a matter of great concern in Western Rajasthan (WR) that diminish the overall energy production capacity of the system remarkably. In this research article, a prototype novel flat plate (NFP) design of a front glass cover of PV module is proposed to prevent the impact of BD settlement by the restriction of bird’s sitting/movement on the front glass cover. In this regard, the performance analysis of PV module with common RFP and newly designed NFP glass covers has been assessed at the different inclination β° (0–90). The BD accumulation onto the both glass covers was explored by the optical transmittance profiles at the different tilt angles, i.e., explained by bird movement on each flat glass surfaces. Consequently, a significant amount of output electric energy has been gained in NFP design rather than RFP corresponding to particular tilt regions TR I (0° ≤ β ≤ 25°), TR II (25° ≤ β ≤ 60°), and TR III (60° ≤ β ≤ 90°). According to the results achieved, an excellent level of improvement in average power loss, ~ 97.85%, corresponding to optimal TR (III) has been detected by employing NFP glass collector.

Combining the multi-regional input–output model with complex network technology, based on the provincial scale, this paper systematically describes the characteristics of the spatial network flow and its changing track of embodied carbon emissions among provinces in China from three dimensions of network structure, flow distribution characteristics, and spatial flow characteristics. Furthermore, the maximum spanning tree method is used to identify the spatial flow path of embodied carbon emissions between provinces and to distinguish the hierarchical status and roles of different provinces on the path. The research results show that the embodied carbon emission flow network among provinces has obvious small-world characteristics during the study, and the roles of different provinces in the network have significant heterogeneity. In general, Hebei and Inner Mongolia mainly act the role of suppliers of embodied carbon emissions, Guangdong and Zhejiang mainly act the role of consumers of embodied carbon emissions, while Zhejiang and Jiangsu mainly act as the media in the network. The spatial distribution characteristics of embodied carbon emission flow have a significant long tail effect; about 6% of the embodied carbon emission flow relationship among provinces accounts for 30% of that on the country level. The spatial flow direction of embodied carbon emissions was mainly concentrated in north China, central China, and southeast coastal region in the early stage and gradually shifted to inter-regional flows, presenting a divergent state of multiple regions and multiple centers. According to the flow path identification, it is found that Jiangsu, Guangdong, Hebei, Zhejiang, and other provinces are the key nodes on the spatial flow path of embodied carbon emissions in China, and the local center in a space is prominent. Based on the analysis and conclusions, the paper finally puts forward the corresponding countermeasures and suggestions in carbon reduction.

The Ghanaian economy relies heavily on maize and soybean production. The entire maize and soybean production system is low-tech, making it extremely susceptible to environmental factors. As a result, climate change and variability have an influence on agricultural production, such as maize and soybean yields. Therefore, the study’s ultimate purpose was to analyze the influence of CO₂ emissions, precipitation, domestic credit, and fertilizer consumption on maize and soybean productivity in Ghana by utilizing the newly constructed dynamic simulated autoregressive distributed lag (ARDL) model for the period 1990 to 2020. The findings indicated that climate change enhances maize and soybean yields in Ghana in both the short run and long run. Also, the results from the frequency domain causality showed that climate change causes maize and soybean yield in the long-run. These outcomes were robust to the use of the ordinary least squares estimator and the impulse response technique. The findings show that crop and water management strategies, as well as information availability, should be considered in food production to improve resistance to climate change and adverse climatic circumstances.