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Building occupancy is an important basic factor in building energy simulation but it is hard to represent due to its temporal and spatial stochastic nature. This paper presents a novel approach for building occupancy simulation based on the Markov chain. In this study, occupancy is handled as the straightforward result of occupant movement processes which occur among the spaces inside and outside a building. By using the Markov chain method to simulate this stochastic movement process, the model can generate the location for each occupant and the zone-level occupancy for the whole building. There is no explicit or implicit constraint to the number of occupants and the number of zones in the model while maintaining a simple and clear set of input parameters. From the case study of an office building, it can be seen that the model can produce realistic occupancy variations in the office building for a typical workday with key statistical properties of occupancy such as the time of morning arrival and night departure, lunch time, periods of intermediate walking-around, etc. Due to simplicity, accuracy and unrestraint, this model is sufficient and practical to simulate occupancy for building energy simulations and stochastic analysis of building heating, ventilation, and air conditioning (HVAC) systems.

Green finance (GF) regards social responsibility and environmental protection interests as the core of development and has become a new growth point and a new engine for promoting the development of the green economy (GE). To more accurately grasp the coordination between GF and the GE, the selection of appropriate indicators and feasible methods is worth exploring. Aiming at sustainable development by evaluating the coupling coordination between GF and the GE by means of a comprehensive index system and an integrated approach, this study establishes a coupling coordination degree model based on panel data of 30 Chinese provinces over the period 2007–2016. Furthermore, it evaluates the spatial distribution difference and dynamic evolution trend of the coordination by introducing global/local spatial autocorrelation, a space Markov chain, and a local indicators of spatial association (LISA) Markov chain. According to the research results, the coupling coordination degrees of the provinces exhibit gradual upward trends, and most regions in China are in a barely coordinated state at present. The coordination degree of GF and the GE shows strong spatial dependence overall, and partially presents the characteristics of “high-high (HH)” and “low-low (LL)” clustering patterns. The forecast results show that the future coordination of GF and the GE will remain stable and be affected by the coordinated development of surrounding areas.

Abstract Air pollutant emissions, fuel consumption, and household air pollution were investigated in rural Hubei, central China, as a revisited evaluation of an intervention program to replace coal use by wood in gasifier stoves. Measured emission factors were comparable to the results measured two years ago when the program was initiated. Coal combustion produced significantly higher emissions of CO2, CH4, and SO2 compared with wood combustion; however, wood combustion in gasifier stoves had higher emissions of primary PM2.5 (particles with diameter less than 2.5 μm), Elemental Carbon (EC) and Organic Carbon (OC). In terms of potential impacts on climate, although the use of wood in gasifier stoves produced more black carbon (6.37 vs 910 gCO2e per day per capita from coal and wood use) and less SO2 (-684 vs -312), obvious benefits could be obtained owing to greater OC emissions (-15.4 vs -431), fewer CH4 emissions (865 vs 409) and, moreover, a reduction of CO2 emissions. The total GWC100 (Global Warming Potential over a time horizon of 100 years) would decrease by approximately 90% if coal use were replaced with renewable wood burned in gasifier stoves. However, similar levels of ambient particles and higher indoor OC and EC were found at homes using wood gasifier stoves compared to the coal-use homes. This suggests critical investigations on potential health impacts from the carbon-reduction intervention program.

Digital financial inclusion (DFI) plays an increasingly important role in raising residents’ income levels and optimizing income structures. Using data from the 2015–2019 China Household Finance Survey (CHFS), this paper examines the impact of DFI on residents’ income and income structure from a microeconomic perspective using OLS fixed effects models and panel Tobit models. It was found that (1) DFI significantly raises residents’ income, increasing their total annual per capita household income by CNY4200, and increasing their annual per capita household wage income, business income and property income by CNY2430, CNY1030, and CNY450, respectively. In terms of different functions of DFI, the use of digital payment, digital lending and digital financing can raise the annual per capita household income of residents by CNY4250, CNY10,360 and CNY3050, respectively. (2) DFI increases wage income by enhancing residents’ household employment level, increases business income by promoting residents’ entrepreneurship, and increases property income by improving the financial market participation. (3) DFI has a more significant effect on increasing income for higher income groups as well as rural residents. The findings of this paper provide theoretical and practical support for optimizing the design of financial inclusion policies and exploring new drivers of income growth for residents.

Prefabricated construction (PC), with the characteristics of green, environmentally friendly, energy saving and high production efficiency, is attracting more and more attention from all over the world. Supply chain management is closely related to the application efficiency of PC, but only in the last three years has this interdisciplinary research received due attention. The prefabricated construction supply chain management (PCSCM) have not received enough attention. Especially recently, the related literature shows explosive growth. This paper adopted the method of systematic literature review through the tool of bibliometric statistics. And we reviewed 152 articles from 2001 to 2018, with the goal of understanding the current situation, trends, and gaps in PCSCM research, and a framework is proposed to promote its development. First, the study discussed the four themes of clustering, concentrating mainly on strategic research and project evaluation, PC supply chain process design and optimization, supply chain integration and management, and the application of advanced technology. Then, the research gaps and conceptual development framework to promote PCSCM were reported. Only through the coordinated development of technology, market circumstances, and decision-making level of participants, can the PCSC form an integrated whole, so as to optimize the efficiency and sustainability of prefabricated construction industry and improve its level.

AbstractDengue is hyperendemic in Brazil, with outbreaks affecting all regions. Previous studies identified geographical barriers to dengue transmission in Brazil, beyond which certain areas, such as South Brazil and the Amazon rainforest, were relatively protected from outbreaks. Recent data shows these barriers are being eroded. In this study, we explore the drivers of this expansion and identify the current limits to the dengue transmission zone. We used a spatio-temporal additive model to explore the associations between dengue outbreaks and temperature suitability, urbanisation, and connectivity to the Brazilian urban network. The model was applied to a binary outbreak indicator, assuming the official threshold value of 300 cases per 100,000 residents, for Brazil’s municipalities between 2001 and 2020. We found a nonlinear relationship between higher levels of connectivity to the Brazilian urban network and the odds of an outbreak, with lower odds in metropoles compared to regional capitals. The number of months per year with suitable temperature conditions for Aedes mosquitoes was positively associated with the dengue outbreak occurrence. Temperature suitability explained most interannual and spatial variation in South Brazil, confirming this geographical barrier is influenced by lower seasonal temperatures. Municipalities that had experienced an outbreak previously had double the odds of subsequent outbreaks, indicating that dengue tends to become established in areas after introduction. We identified geographical barriers to dengue transmission in South Brazil, western Amazon, and along the northern coast of Brazil. Although a southern barrier still exists, it has shifted south, and the Amazon no longer has a clear boundary. Few areas of Brazil remain protected from dengue outbreaks. Communities living on the edge of previous barriers are particularly susceptible to future outbreaks as they lack immunity. Control strategies should target regions at risk of future outbreaks as well as those currently within the dengue transmission zone.Author summaryDengue is a mosquito-borne disease that has expanded rapidly around the world due to increased urbanisation, global mobility and climate change. In Brazil, geographical barriers to dengue transmission exist, beyond which certain areas including South Brazil and the Amazon rainforest are relatively protected from outbreaks. However, we found that the previous barrier in South Brazil has shifted futher south as a result of increased temperature suitability. The previously identified barrier protecting the western Amazon no longer exists. This is particularly concerning as we found dengue outbreaks tend to become established in areas after introduction. Highly influential cities with many transport links had increased odds of an outbreak. However, the most influencial cities had lower odds of an outbreak than cities connected regionally. This study highlights the importance of monitoring the expansion of dengue outbreaks and designing disease prevention strategies for areas at risk of future outbreaks as well as areas in the established dengue transmission zone.

This paper explores to what extent moving towards the 30% GHG emission reductions by 2020 with respect to 1990 in the EU can be considered a transformative target. To do so, we first define the concept of transformative targets from a complex systems perspective and show a novel approach and original results using an extended application of the GEM-E3 model. Traditional macroeconomic models cannot easily handle key synergetic system effects derived from green growth and sustainability policies, and thus require additional features. We analyse the role of semi-endogenous growth driven by learning-by-doing and low-carbon investment expectations following a long-term transformative trajectory.