The transport sector has been one of the largest source of carbon emission and urban air pollutants. The research on the coordinated development of pollutant and carbon emission reduction in transport industry is helpful to the realization of urban pollutant prevention and carbon emission reduction, especially in big cities. Thus, a multi-period bottom-up vehicle development mathematical model is proposed to analyze the technology development path, emission path and energy structure adjustment path, and the synergistic benefits of carbon dioxide (CO2) emission reduction under a expected air pollution emission standard. Four pollutants, carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and particulate matter (PM), generated from the vehicle are considered in this model. Then, the proposed model is used to analyze the related vehicle structure and energy consumption under the expected emission standards for Beijing during 2020 and 2035. The technology development path, emission path and energy structure adjustment path are examined, and the synergistic benefits of CO2 emission reduction are also studied. Some important implication are found as follows (1) Even with the goal of environmental pollution control only, new energy vehicles will have an explosive growth period, starting from about 2025. (2) Strict air pollution emission policies do not always lead to the rapid development of new energy vehicles before 2025. (3) The four main pollutants show different levels of synergistic effect among which CO on HC and NOx on PM are obvious, respectively. (4) Even under the control of the air pollution policy, the synergistic effect to CO2 emission reduction is also obvious. Compared to the baseline case, the reduction benefit from the MILD and STRICT environmental policies are 30 and 70 million yuan, respectively.Integrated agriculture and aquaculture systems (IAAS) allow nutrients, energy, and water to flow throughout the components of the system, increasing the efficiency with which inputs are converted to food. Yet effectively designing an IAAS requires understanding how nutrients accumulate and alter the system's productivity. Here we developed a mechanistic model for nitrogen transport and utilization and parameterized it using the IAAS in He'eia, Hawai'i. Of note, we modeled tidal influence, which extends existing IAAS models that often assume aquaculture in tank enclosures. We simulated the impact of nitrogen loading from three possible land use scenarios across agriculture and development priorities on the productivity of the fishpond downstream. We projected that organic nitrogen and nitrate concentrations parallel the successive increases in nitrogen loading across management strategies. Autotroph and fish densities were predicted to follow similar trends in response to increased nitrogen availability, causing fish harvests to increase from the current land use (25 kg/ha) to the restored agriculture (35 kg/ha) and urban (50 kg/ha) alternatives. While fish harvests were predicted to be highest in the urban scenario, modeled caloric production in the restored scenario from agriculture and aquaculture would sustain 235 people (4.3 people/ha) in the He'eia IAAS, 16 and 125 times more than the current or urban land uses, respectively. Restoring diversified agriculture was also predicted to retain a larger proportion of nitrogen inputs (0.43) than urbanizing the region (0.30), which would reduce nitrogen export to the adjacent Kāne'ohe Bay. Several state variables were notably sensitive to tidal flux rates, highlighting the importance of incorporating tidal dynamics into a coastal IAAS model. https://www.selleckchem.com/products/autophinib.html This model provides valuable insights for the management of existing coastal IAAS and design of new IAAS in coastal regions to improve the sustainability of future food systems.Manganese dioxide has been widely recognized as catalyst in catalytic ozonation for organic pollutants removal from wastewater in recent decades. However, few studies focus on the structure-activity relationship of MnO2 and catalytic ozonation mechanism in water. In the present study, the oxidative reactivity of three different crystal phases of MnO2 corresponding to α-MnO2, β-MnO2 and γ-MnO2 towards metoprolol (MET) and ibuprofen (IBU) were evaluated. α-MnO2 was found to contain the most abundant oxygen vacancy and readily reducible surface adsorbed oxygen (O2-, O-, OH-), which facilitated an increase of ozone utilization and the highest catalytic performance with 99% degradation efficiency for IBU and MET. α-MnO2 was then selected to investigate the optimum key operating parameters with a result of catalyst dosage 0.1 g/L, ozone dosage 1 mg/min and an initial pH 7. The introduction of α-MnO2 promoted reactive oxygen species (O2-, O-, OH-) generation which played significant roles in IBU degradation. Probable degradation pathways of MET and IBU were proposed according to the organic intermediates identified and the reaction sites based on density function theory (DFT) calculations. The present study deepened our understanding on the MnO2 catalyzed ozonation and provided reference to enhance the process efficiency.Wetting-drying cycles typically result in a wide range of soil moistures and redox potentials (Eh) that significantly affect the soil microbial community. Although numerous studies have addressed the effects of soil moisture on soil microbial community structure and composition, the response of active microbes to the fluctuation in soil Eh is still largely unknown; this is especially true for the ecological roles of abundant and rare taxa. To explore the dynamics of active and total microbial communities in response to wetting-drying cycles, we conducted a microcosm experiment based on three wetting-drying cycles and 16S rRNA transcript (active) and 16S rRNA gene (total) amplicon sequencing. We found that both active and total microbial communities during three wetting-drying cycles were clustered according to the number of wetting-drying cycles (temporal factor) rather than soil moisture or Eh. Dynamics of the active microbial community, however, were redox dependent during the first wetting-drying cycle. In addition, rare taxa in the active microbial community exhibited more obvious differences than abundant ones during three wetting-drying cycles.