Keywords

1 Introduction

Today, more than half of humanity lives in urban environments, and about 80 percent of energy consumption occurs within city boundaries, a figure that is rising with the development of the global economy. With the continuous growth of urban energy demand, the environmental problems caused by urban energy supply and energy consumption become more and more serious. With the continuous intensification of climate change, its consequences have brought impacts on human beings, especially the production and life of urban residents, and also put forward higher requirements for urban energy supply and maintenance system. Facing the urban energy dilemma, scholars have carried out corresponding research from different fields. Johari Fatemeh [1] designed and validated a more accurate urban building energy model by improving data quality); At the level of smart power grid, Zhang et al. [2] and Souabi Sonia [3] respectively studied the intelligent scheduling mode of urban EV charging stations and home photovoltaic power generation through LSTM algorithm. Vakili Seyedvahid [4] proposed a hybrid and coding design model applied to smart grid wireless communication to improve the capacity and security of smart grid communication systems. At present, the research on urban energy saving effect focuses more on power, resource allocation model and policy research, and less on improving the capacity and stability of urban energy system through building renovation represented by roof greening. By planting plants on the roof of the building and changing the thermodynamic properties of the underlying surface under the urban microclimate, green roof can significantly improve the urban green area, offset the ecological environment problems in the city caused by the separation of man and nature, and effectively improve the redundancy of energy supply and the stability of the energy system in the city. To a certain extent, the impact of the deterioration of the ecological environment and the change of climate conditions on the city will be weakened [5]. The effect of building energy saving and urban climate improvement brought by green roofs is significant. The research results of Mickovski et al. [6], Bates et al. [7] Kazemi et al. [8] show that the use of urban waste in green roof matrix can reduce the overall carbon emission of the city through the use of construction waste. It can also support green roof plants to improve urban microclimates. In terms of climate regulation, Andrew [9], Wong [10], Elnabawi [11] and Pragati [12] respectively explored the positive significance of green roofs for urban microclimate regulation from field records, model analysis, theoretical research and energy consumption simulation. The degree of adjustment is affected by the form of green roof, green roof plants, urban geographical location and so on.

Under the premise that extreme weather events in the world are becoming more and more serious and frequent, it is an effective means to improve the degree of climate change to improve the stability of urban energy system and reduce the overall urban energy consumption through multidisciplinary joint efforts. However, there are few studies on the effect of green roofs using construction waste substrate on the regulation of urban ecosystem and the contribution level of urban energy conservation under different summer weather events. This experiment simulates the contribution degree of green roofs using construction waste substrate to urban climate and building energy efficiency under the background of extreme meteorological events, in order to provide theoretical basis for the comprehensive development of urban energy conservation technology.

2 Simulation Result Analysis

Envi-met is a commonly used medium and small-scale climate simulation software, which can accurately simulate the influence of architecture, terrain, vegetation and other factors on medium and small-scale climate, and can generate intuitive and accurate simulation maps. Envi-met is one of the preferred software for medium and small-scale climate simulation in the world. In this paper, Envi-met 5.1.1 was used to conduct a simplified modeling of the experimental building and its surrounding environment to analyse the difference in microclimate effects of green roofs under extreme and typical summer weather conditions.

In order to provide more accurate experimental data for the simulation experiment, a long-term green roof temperature monitoring experiment was carried out in Henan Province, China from June to September 2022. The volume ratio of each component of the experimental substrate is peat soil: crushed brick (≤3 mm) = 1:1. The green roof type is mixed type, The vegetation was Osmanthus fragrans (20%), Camellia sasanqua (30%) and Sedum lineare (50%). A small weather station with FT BQX9 was set up in the central open space of the test plot to record meteorological information. The sampling interval was 300 s, and the GIS500 handheld temperature sensor was used to record the temperature of the exposed roof in the experiment site every 15 min as the control group. In order to fully study the energy-saving effect of green roofs in different summer weather events, three typical weather days are set, namely, typical summer day: August 2, 2022, and extreme high temperature day: August 12, 2022. The Person correlation analysis shows that the correlation of meteorological indicators on each meteorological day is ≥ 95%. The meteorological data that passed the correlation test were taken as model data to participate in the simulation experiment, and all the meteorological indicators were shown in Table 1. In order to ensure the accuracy of the model simulation results, the Settings of the building and underlying surface in this experiment are the same as the actual situation. All the indicators set are shown in Table 2, and the default values of the system are adopted for the indicators not mentioned.

2.1 Comparative Analysis of Simulated Measurement

Figure 1 shows the measured and simulated temperatures with and without green roofs for each weather event. On the whole, the simulated temperature and the real temperature show the same daily variation law, the measured temperature in the period with solar radiation is slightly higher than the simulated temperature, while the measured temperature in the period without solar radiation is slightly lower than the simulated temperature.

Table 1. Main meteorological data for each meteorological day
Full size table

Figure 2 shows the measured and simulated wind speeds with and without green roofs for each weather event. In the simulation of wind speed, because the model itself has blurred the contingency of some environmental impacts, compared with the complex urban environment, the simulation of wind environment is more difficult. In the process of measurement, wind speed is affected by a variety of external conditions, and its instantaneous change is large and the contingency is large, so ENVI-met cannot simulate the time-by-time dynamic wind speed. Therefore, the simulation of wind speed is not enough to reflect the chance, the wind speed reflects the characteristics of a more gentle, can only reflect the overall change. The difference between the measured wind speed and simulated wind speed on green roof under four simulated conditions is 0.03, 0.07, 0.02 and 0.04 m/s, respectively, which can indicate that the wind speed simulation can reflect the measured situation well to a certain extent.

Table 2. Building setting indicators and values
Full size table

2.2 Accuracy Analysis of Simulation Results

In order to evaluate the accuracy of microclimate simulation intuitively and scientifically, Root mean square error (RMSE) and Mean absolute percentage error (Mean absolute percentage error) are introduced here. As a quantitative evaluation index for the accuracy of green roof meteorological simulation, MAPE is calculated as follows.

$$ RSME = \sqrt {\frac{1}{n}\sum\nolimits_{i = 1}^{n} {\left( {y^{\prime}_{i} - y_{i} } \right)} } $$
(1)
$$ MAPE = \frac{1}{n}\mathop \sum \limits_{{i = 1}}^{n} \frac{{\left| {y^{\prime}_{i} - y_{i} } \right|}}{{y^{\prime}_{i} }} \times 100{{\% }} $$
(2)
Fig. 1.
figure 1

Measured and simulated temperature values of different weather events

Full size image

In the formula, \(y^{\prime}_{i}\) is the simulated value, \({y}_{i}\) is the corresponding point value measured by experiment, and \(n\) is the measured temperature count. According to the studies of Willmott [13] and Salata et al. [14], when RSME value is 0.52 ℃–4.30 ℃ and MAPE value is less than 10%, the accuracy of the model is relatively ideal. The MAPE and RSME values of the four simulated weather events in this paper are shown in Table 3. All calculated values meet the accuracy requirements.

Table 3. MAPE and RSME values for simulated weather events
Full size table

3 Simulated Temperature Field Analysis

This section sets four kinds of urban microclimate temperature simulation scenarios for whether there is roof greening when two different weather events occur. The type of roof greening set is composite roof greening, and the surface vegetation is set according to the actual situation. Figure 3–Fig. 4 shows the temperature field distribution of two time nodes at 2:00 and 13:00 respectively under four simulated conditions.

Fig. 2.
figure 2

Measured and simulated wind speed of different weather events

Full size image

Figure 3 shows the temperature distribution of the green roof at 1.4m altitude during different weather events in the late night. This simulation result can more intuitively and clearly represent the impact of the green roof on the urban microclimate. In the late night, regardless of whether there is a green roof in the building under extreme weather conditions, there are high temperature zones in the building impact zone in the north-south corridor between the buildings. Roof greening is difficult to eliminate the high temperature zone between buildings, but it can significantly reduce the temperature difference between the high temperature zone and the outer area in different weather events. The layout of roof greening in extreme high temperature weather events and typical summer has a cooling range of about 0.8 ℃ and 1.2 ℃, respectively. At the same time, it should be noted that in the case of roof greening, the overall temperature of the environment when extreme high temperature weather events occur and when typical summer meteorological events occur is lower than that in the case of no green roof at the same time, 0.6 ℃ and 1.0 ℃, respectively, and the overall temperature distribution is more average.

Figure 4 shows the temperature distribution at 1.4m altitude of the green roof at noon when different weather events occur. This simulation result shows that the urban microclimate changes completely opposite to that at night when different weather events occur. At noon, no matter whether there is a green roof in the building under extreme weather conditions, there will be a relatively significant low temperature zone on the north, south and east sides, among which the low temperature area on the west side of the building is the largest. Roof greening can significantly improve the range and temperature difference of low temperature zones between buildings, and the arrangement of roof greening in extreme high temperature weather events and typical summer has a cooling range of about 0.9 ℃ and 1.5 ℃, respectively. At the same time, it should be noted that in the case of roof greening, the overall ambient temperature at noon when extreme high temperature weather events occur and when typical summer meteorological events occur is lower than 1.1 ℃ and 1.3 ℃ respectively in the same period without green roofs, and the overall temperature distribution is not very average. It should be noted that when typical summer weather events occur, no matter whether roof greening is arranged or not, there will be a significant high temperature range on the south side of the building, and this high temperature area is the highest temperature value in the simulated environment at this time. The temperature in this high temperature area with roof greening and without roof greening is 33.21 ℃ and 34.90 ℃, respectively. However, this high temperature region does not appear when extreme hot weather events occur. The reason for this situation is that the temperature increased by 5 ℃ when extreme hot weather events occurred compared with the typical summer weather events, and the overall increase of ambient temperature led to the disappearance of this high temperature region.

Fig. 3.
figure 3figure 3

Temperature distribution of 1.4 m at night with four simulated results

Full size image

4 Evaluation of Overall Building Energy Saving Effect Caused by Roof Greening

In order to clarify the impact of the existence of green roofs on the overall energy consumption of buildings and quantitatively demonstrate the contribution of green roofs to the energy conservation of urban energy consumption systems, this paper uses energy plus software to conduct a comparative analysis of the energy consumption of building HVAC systems. The model setting and parameter design of EnergyPlus software are arranged strictly in accordance with the actual situation. The model has seven floors on the ground, with four Windows open on all sides and no shade for the Windows. In the simulation software, the interior and exterior walls of the building are differentiated from the internal and external Windows. The Settings of related parameters are shown in Table 2.

Fig. 4.
figure 4figure 4

Temperature distribution of 1.4 m at noon with four simulated results

Full size image

The test results are shown in Table 4. When different weather events occur, green roof has a relatively similar reduction effect on building energy consumption. In both extreme high temperature weather events and typical summer weather events, the reduction effect of green roof on building energy consumption is 3 W/m2/h, and the energy saving effect in extreme high temperature weather events is 0.32 W/m2/h higher than that in typical summer. This has a very positive effect on the supply and stability of urban power energy system. Based on the typical air conditioning habits of residential users and the 180-day cooling period, each building in the simulation scenario can reduce the electricity consumption of 21,772.8 KWH during a cooling period.

5 Conclusion

In this experiment, the method of model simulation was used to select the extreme hot weather and typical summer weather during the experiment for accurate environmental data sampling, and the microclimate characteristics of temperature and wind speed at the 1.4m altitude layer of the community were studied. Based on the premise that the evaluation of the model is in good agreement with the actual measurement, the micro-climate effects of different preset greening schemes in the study area are simulated and analyzed, and the following conclusions are obtained. Combined with the actual measurement values, the quantitative evaluation indexes RSME and MAPE for the accuracy of green roof weather simulation were used to evaluate the model fitting and forecasting ability. The results show that the model can better reflect the changes of temperature, wind speed and wind direction in the simulated area, and the evaluation results of the indicators are within the accurate range proposed by previous studies, indicating that it is feasible and scientific to analyze the actual microclimate change through model fitting data. Through the analysis of the measured data and simulated microclimate environmental characteristics, it can be seen that roof greening and weather events have significant effects on the microclimate environmental temperature in this region. There is an east-west high temperature zone between buildings at night, and the arrangement of roof greening in extreme high temperature weather events and typical summer can reduce the temperature in this high temperature zone by 0.8 ℃ and 1.2 ℃, respectively. Under the influence of roof greening, the temperature in extreme hot weather events and typical summer can be reduced by 0.6 ℃ and 1.0 ℃ respectively, and the overall temperature distribution is more average. The reason for the high temperature zone is that due to the direction of the building and the installation of surface vegetation, the north-south air circulation is not smooth, and the east and west sides of the building are respectively formed a quiet wind zone. At noon, a low temperature zone appeared on the east and west sides of the building respectively. During extreme high temperature meteorological events and typical summer meteorological events, the temperature decreased by 0.9 ℃ and 1.5 ℃, respectively, compared with the temperature around the building, and the overall ambient temperature decreased by 1.1 ℃ and 1.3 ℃. The main reasons for this are the arrangement of green roofs and the shading effect of buildings and surface plants. When extreme hot weather events occur, due to the comprehensive influence of solar radiation and air temperature, the ambient climate temperature of extreme hot weather in the experimental model is more average, and the cooling effect of roof greening is suppressed to a certain extent. It also causes the high temperature area on the south side of the building formed by the radiation of the building in typical summer days to disappear during the extreme high temperature summer days. The above results show that green roof can change the urban microclimate to some extent by reducing the maximum daily building temperature, increasing the minimum daily building temperature and smoothing the daily building temperature change process, which has a very positive significance for the supply and stability of urban energy system.

Table 4. Formatting sections, subsections and subsubsections.
Full size table

In the simulation experiment of building energy consumption, the significance of roof greening on urban energy consumption is further highlighted. The average energy-saving effect of roof greening in summer can reach 3W/m2/h, and this energy-saving effect will be improved in extreme high temperature meteorological events. On the whole, the summer energy saving effect of roof greening on a single building in the test site can reach 21772.8 KWH. For the city, its summer energy saving effect and value are very significant. This indicates that in the future urban renewal process, large-scale roof greening can have a very important positive significance for the stability of urban energy supply system and the promotion of low-carbon society.