Search

The online Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is used to simulate the effects of albedo enhancement on aerosol, radiation, and cloud interactions in the Greater Montreal Area during the 2011 heat wave period. We used a 2-way nested approach to capture the full impacts of meteorological and photochemical reactions in the urban atmosphere. We conducted four sets of simulations with and without aerosol estimations and convective parameterizations to explore the aerosol interactions with radiation and cloud in the urban atmosphere. The direct, semi-direct, and indirect effects of aerosols are analyzed. The meteorological performance of the model indicates that the model slightly underpredicts air temperature, overpredicts wind speed, and underpredicts relative humidity. The chemical component of the model indicates that the model tends to underpredict fine particulate matters and overpredict ozone and nitrogen dioxide concentrations. The surface reflectivity of roofs, walls, and grounds is increased from 0.2 to 0.65, 0.60, and 0.45, respectively. Albedo enhancement led to a net decrease in radiative balance at solar noon by 25 W/m2, a decrease in daily air temperature by 0.5 °C, a reduction in water mixing ratio to 0.5 g/kg, and a decline in cloud coverage by 3% in the center part of the domain. Increasing urban albedo caused a decrease in planetary boundary layer height by 25 m. Albedo enhancement affords a decrease in temperature-sensitive photochemical reaction rates and thus reduces daily ozone concentrations by 3 ppb across the entire domain. The concentration of daily fine particulate matters decreased by 3 μg/m3 in the center part of the GMA during the 2011 heat wave period.

In shared spaces, occupants may have varied thermal and visual preferences for the indoor environmental conditions. Moreover, an occupant's perception of the indoor environment, such as her thermal and visual sensations, depends on her position inside an enclosed space. There is a strong relationship between occupants’ comfort conditions and their level of productivity, hence, improving the productivity of occupants in offices offers significant economic benefits. The main interest of this research is to propose a Multi-Objective Optimization (MOOP) method for position-based energy and comfort management in offices. The proposed method accounts for personalized thermal and visual preferences of occupants and their positions within an office space, and simultaneously optimizes energy consumption costs and collective productivity of office workers, by proposing Pareto optimal solutions for the automated control of the indoor environment. Occupants’ thermal and visual preferences and positions, their productivity rates, thermal and visual behavior, Indoor Air Quality (IAQ) of the space, energy exchanges processes across the building, indoor and outdoor environmental parameters, and energy prices, are considered in this optimization. Application of the proposed method under varied occupancy scenarios is analyzed by energy performance simulation of a multi-zone office building, located in Montreal, Canada. The proposed method (1) has the flexibility to account for the diversity among occupants’ environmental preferences, (2) manages the indoor environmental conditions based on office workers’ positions and preferences, and (3) simultaneously optimizes energy costs and office workers’ productivity.

Heat-related mortality is increasing as the result of climate change, extreme heat events and higher ambient temperature because of urban heat island (UHI) phenomenon. We coupled the Weather Research and Forecasting model (WRFV3.6.1) with a multi-layer of the Urban Canopy Model (ML-UCM) to investigate the effects of UHI intensity during the 2005 and 2011 heat wave periods in Greater Montreal Area (GMA), Canada. Each day of simulation is categorized into an air mass type using the Spatial Synoptic Classification. Using the non-accidental mortality data during summer period, the number of deaths above the expected mean anomalous daily mortality is calculated for each air mass classification. Results indicate that moist tropical plus and dry tropical weather have the highest rank in heat-related death. We assessed the effects of increasing surface reflectivity (ISR) on four meteorological parameters: 2-m air temperature, 10-m wind speed, 2-m relative humidity, dew point temperature, and four heat stress indices: National Weather Service – Heat Index, Apparent Temperature, Canadian Humid Index, and Discomfort Index (DI). ISR decreased air temperature by 0.6 °C, increased relative humidity by 2%, increased dew point temperature by 0.4 °C. The DI improved by 3% and heat-related mortality decreased by nearly 3.2% during heat wave periods in GMA.

The extreme effects of urban heat island (UHI) on energy consumption, air quality, and human health are significantly detrimental. Increasing the albedo of urban surfaces has been proposed as a potentially efficient mitigation strategy. In this study the Weather Research and Forecasting (WRF) mesoscale model has been used to simulate the urban climate of Rome (Italy).Four different scenarios have been analyzed: the Base Scenario as control case; the Base-ALB Scenario, in which the albedo of roof, walls and road have been increased; the Morph Scenario in which the morphology of urban area has been parameterized more accurately; the Morph-ALB Scenario in which the urban albedo of the improved model has been increased. This study demonstrates that a more accurate parametrization of the urban morphology leads to a more accurate representation of UHI phenomenon. The simulation results show that albedo increase leads to the decrease of the 2-m air temperature at day-time and at night-time. Albedo increase offers very promising results in terms of UHI mitigation, reducing the temperature in the urban area by up to 4 °C at daytime and a little increased (up to 1 °C) in some locations at night time, compared to the control cases.

In mesoscale meteorological modeling, physical models (radiation, planetary boundary layer, microphysics, cumulus, and land-surface) are employed to calculate terms of governing equations. We evaluate the sensitivity of near surface air temperature, wind speed, relative humidity and precipitation to different physical models within Weather Research and Forecasting (WRFV3.6.1) model for urban climate simulations and heat island mitigation for Montreal, Canada for period 09–11 Aug-2009. A multi-layer urban canopy model is used to consider the turbulence between buildings in urban areas. The model ensemble with the least error is proposed as an appropriate platform for urban climate simulations to study Urban Heat Island (UHI) mitigation strategies. Increasing surface reflectivity was applied to mitigate the UHI intensity over the domain. The albedo of roofs, walls, and roads increased from 0.2 to 0.65, 0.6, and 0.45, respectively. The results of surface modification are presented. The averaged 2-m air temperature indicates a decrease by 0.2 °C. The 10-m wind speed is slightly increased over the domain. The relative humidity decreases as an average of 2.8% and the average precipitation reduced by 0.2 mm. An increase of albedo leads to a net decrease of radiative flux into the ground and therefore a decrease of convective cloud formation and precipitation.

The extraction of urban built-up areas is an important aspect of urban planning and understanding the complex drivers and biophysical mechanism of urban climate processes. However, built-up...

There is a strong relationship between occupants’ comfort and their productivity. Indoor environmental conditions have impacts on the mental and physical well-being of occupants that subsequently, influence their productivity. Generally, occupants in a shared space have varied preferences for the thermal conditions of the indoor environment. For energy management systems of office buildings, inability to acknowledge occupants’ thermal preferences may cause productivity losses. Salaries of office workers are many times higher than the costs of energy consumption, hence, improving the productivity of office workers can offer significant economic benefits. The main interest of this research is to propose a Multi-Objective Optimization (MOOP) method for personalized energy and comfort management in offices. The MOOP method simultaneously optimizes the energy costs and collective productivity of office workers, by proposing Pareto optimal solutions for the automated control of the indoor environment, based on occupants’ thermal preferences and Indoor Air Quality (IAQ). Alongside thermal preferences and IAQ, several continuously changing inputs are also considered including indoor and outdoor environmental parameters, energy exchange processes across the building zones, energy prices, occupants’ presence, productivity rates, and thermal behavior. Application of the proposed method for personalized energy and comfort management is analyzed by the annual energy performance simulation of an office building, located in Montreal, Canada. Based on the provided results, the proposed method has the flexibility to manage the diversity among the thermal preferences of occupants, and significantly improves the productivity of office workers while optimizing the energy consumption costs.

Observing the rapid urban expansions and numerous infrastructure developments in the East-Asian context, many cities are suffering the urban heat island (UHI) effect and its associated environmental and social challenges. Moreover, the lack of sufficient attention to the application of effective heat mitigation strategies in current urban development in these cities can drastically intensify the eventual impacts of UHI. Therefore, many governmental sectors and policy makers have been implementing operative solutions for cooling cities. Nevertheless, this study argues that in Kuala Lumpur, despite the growing attention to this matter, there is still a need for more rigorous consideration by the architecture, engineering and construction (AEC) professionals as well as more scholarly studies to reflect sustainable solutions to the UHI effect. As a result, today, some of the dense urban areas in Kuala Lumpur are characterized with the use of thermally massive building materials, urban surfaces with low albedo, complex urban morphology, waste heat, and low density of vegetation. On the other hand, recent studies demonstrate that there has been a rapidly increasing interest in studies related to UHI in other East Asian regions such as Singapore and Hong Kong. Hence, this study develops a comparative analysis to provide a state-of-the-art review of the recent attempts towards mitigating the UHI effect in Kuala Lumpur, Singapore, and Hong Kong. Among several available UHI mitigation strategies, this study is limited to the analysis of the environmental impacts of urban vegetation (green roofs, green facades, vertical greeneries and green pavements). Findings reveal that in general, urban greening can significantly mitigate the UHI intensity, both directly and indirectly, resulting in the decrease of global air temperature and mean radiant temperature up to 4 °C and 4.5 °C respectively. Overall, the study develops new practical guidelines, discusses the public benefits and elaborates on the future directions of UHI studies.

This paper intended to investigate spatio-temporal monotonic trend and shift in concentration of monsoon precipitation across West Bengal, India, by analysing the time series of monthly precipitation from 18 weather stations during the period from 1901 to 2002. In dealing with, the inhomogeneity in the precipitation series, RHtestsV4 software package is used to detect, and adjust for, multiple change points (shifts) that could exist in data series. Finally, the cumulative deviation test was applied at 5% significant level to check the homogeneity (presence of historic changes by cumulative deviations test). Afterward, non-parametric Mann-Kendall (MK) test and Theil-Sen estimator (TSE) was applied to detect of nature and slope of trends; and, Sequential Mann Kendall (SQMK) test was applied for detection of turning point and magnitude of change in trends. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation in precipitation data series. Four indices- precipitation concentration index (PCI), precipitation concentration degree (PCD), precipitation concentration period (PCP) and fulcrum (centre of gravity) were used to detect precipitation concentration and the spatial pattern in it. The application of the above-mentioned procedures has shown very notable statewide monotonic trend for monsoon precipitation time series. Regional cluster analysis by SQMK found increasing precipitation in mountain and coastal regions in general, except during the non- monsoon seasons. The results show that higher PCI values were mainly observed in South Bengal, whereas lower PCI values were mostly detected in North Bengal. The PCI values are noticeably larger in places where both monsoon total precipitation and span of rainy season are lower. The results of PCP reveal that precipitation in Gangetic Bengal mostly occurs in summer (monsoon season), and the rainy season arrives earlier in North Bengal than South Bengal, whereas the results of PCD also indicate that the precipitation in North Bengal was more dispersed within a year than that in South Bengal. The concentration characteristic of precipitation could be detected by fulcrum analysis, and significant concentration over most of West Bengal was obvious within July month band. Precipitation trend observed in West Bengal is compared with that in Central India (CI) region and comparison of precipitation departure with Indian monsoon and Gangetic Bengal can be explained by forecasting ensemble.

Although the urban heat island (UHI) phenomena phenomenon has was been documented over a century ago, the effect of the urban heat island on urban climate and environment during the summer have only been the focus of research over the last three decades. One main characteristics of the recent research has been to evaluate the summertime effects of UHI on energy use, air pollution, outdoor ambient temperature, and citizen health. The second aspect of the recent research has been the development and evaluation of materials to counter the effects of summertime UHI. This paper provides a selective representation (by topic) review of the research on the development and evaluation of mitigation measures, including: cool roofs, cool pavements, and urban vegetation.

Heat-related mortality (HRM) is increasing because of the climate change and urbanization leading to extreme heat events. This paper summarizes the results of the excess mortality attributed to excessive heat events in two largest cities in Canada, Toronto and Montreal, during three heat wave periods. We present an application of a fine-resolution, urban-mesoscale model to assess the impacts of heat and heat mitigation strategy on heat death. The Weather Research and Forecasting model (WRF) is coupled with a multi-layer of the Urban Canopy Model (ML-UCM) to assess the impacts of heat and heat mitigation strategy on heat -related death. The background albedo of 0.2 for urban surfaces are respectively increased to 0.65, 0.60, and 0.45 for roofs, walls, and grounds. The changes of the air mass category, ambient and apparent temperatures interpret the impacts of extreme heat and the potential of increasing surface albedo (ISA) on HRM. Here, the calculations and estimations of HRM is based on the data obtained from Canadian Environmental Health Atlas (CEHA) indicating an average of 120 heat-induced deaths in Toronto and Montreal. ISA affords a reduction in air temperature (1–2 °C), a decrease in dew point temperature (0.2–0.5 °C), and a slight increase in near-surface wind speed (−0.01 to −0.4 m/s). Increase in albedo shifts days into more benign conditions by nearly 60%. The HRM will lessen by 3–7%, pointing that seven to eighteen lives could be saved. Cooling the urban climate will improve discomfort index, lessen the impacts of elevated temperature, enhance human thermal comfort, and decrease HRM to some significant extent.

The effects of climate change and Urban Heat Island (UHI) phenomena have raised the attention for monitoring and evaluating the outdoor thermal comfort. The urban vegetation system is playing a significant role for UHI mitigation and adaption. The fraction of the ground covered by trees and other vegetation is smaller and contains less biomass than in nonurban areas. The absence of vegetation impacts the UHI in several ways, since vegetation, and in particular trees, intercept solar energy, and their shade reduces the temperature of surfaces below while increasing the latent heat exchange for the evapotranspiration process. In this paper, the common tree types and the size of trees in Montreal are investigated; and the effect of tree size and space between trees on outdoor comfort are compared by using environmental simulation. It’s demonstrated that, the correlation (R2) between tree cover (SVF) and urban Ta is about 0.64 at summer mid-night. In the daytime, tree cover could reduce air temperature at the tree level (4 °C at 20 m height from the ground), as well as higher level (2 °C at 60 m from the ground).

I ndoor E nvironment Q uality (IEQ) of an office has significant effects on the performance and productivity of its occupants. There are several factors that have positive or negative impacts on occupants’ overall satisfaction, including the level of thermal comfort, visual comfort, aural comfort and I ndoor A ir Q uality (IAQ). While keeping energy savings objectives, energy management system can provide acceptable thermal comfort, visual comfort, and IAQ levels, by taking energy-related decisions. Several inputs that are changing continuously, such as energy prices, sets of indoor and outdoor environment parameters, occupants’ presence, activities and preferences are required for timely energy-related decision-making. Therefore, there is a need for a well-structured method to reach optimum decisions for energy costs and occupants’ IEQ. The main interest of this research is to propose a M ulti- O bjective Op timization (MOOP) method for energy and comfort management in commercial buildings. The proposed method is capable of providing situation-specific economic optimum indoor conditions, based on the combination of thermal comfort, IAQ, and energy costs, as well as energy prices, occupancy information and types of occupants’ activities. Operation of the proposed method is analyzed by annual energy performance simulation of a commercial building in Montreal, Canada. Based on provided results, the proposed MOOP method is capable of improving productivity of occupants, by up to $1000 per year per person, while reaching energy savings objectives. It is observed that potential for productivity improvement is higher during the swing and warm seasons, compared to the cold season. Having ability of flexible decision-making, the proposed MOOP method is suitable for I ntelligent E nergy M anagement S ystems (IEMSs), with objectives of maximizing energy costs and comfort conditions.

Increasing albedo is an effective strategy to mitigate urban air temperature in different climates. Using reflective urban surfaces decreases the air temperature, which potentially reduces the rate of generation of smog. However, for implementing the albedo enhancement, complicated interactions between air, moisture, aerosols, and other gaseous contaminant in the atmosphere should be considered. We used WRF-CHEM to investigate the effect of increasing albedo in Montreal, Canada, during a heat wave period (July 10th through July 12th, 2005) on air quality and urban climate. The reflectivity of roofs, walls, and roads are increased from 0.2 to 0.65, 0.6, and 0.45, respectively. Air temperature at 2-m elevation is decreased during all hours in the simulation period and the maximum reduction is about 1 °C on each day (T max is reduced by about 0.7 °C) The concentration of two regulated pollutants −ozone (O 3 ) and fine particulate matters (PM 2.5 ) − is calculated at a height of 5-m above the ground. The maximum decrease in 8-h averaged ozone concentration is about 3% (∼0.2 ppbv). 24-h averaged PM 2.5 concentration decreases by 1.8 μg/m 3 . This relatively small change in concentration of pollutants is related to the decrease in planetary boundary layer height caused by increasing the albedo. Additionally, the combined effect of decreased solar heat gain by building surfaces and decreased air temperature reduces the energy consumption of HVAC systems by 2% (∼0.1 W/m 2 ), which exacerbates the positive effect of the albedo enhancement on the air quality.

Increasing awareness of the urban heat island (UHI) effect has raised attention about the outdoor thermal comfort in cities worldwide. Several studies in the last decades have revealed how critical the UHI effect can be in a cold climate, such as in Canadian cities. As a result, in Toronto, one of the cities experiencing the highest rate of building development in developed countries, UHI mitigation strategies are currently the object of extensive debates. This study evaluates different UHI mitigation strategies in different urban neighbors of Toronto, selected according to their building density. The effects of cool surfaces (on the roofs, on the street pavements or as vegetation areas) are evaluated through numerical simulations using the software ENVI-met. Having obtained the surface temperature, outdoor air temperature, mean radiant temperature, and physiologically equivalent temperature, this study compares the possible mitigation of net surface radiation and thermal radiative power. The results demonstrate that the duration of direct sun and the mean radiant temperature, which are strongly influenced by the urban form, play a significant role in urban thermal comfort. Finally, this research supports new policies for promoting sustainable urban development in Toronto, and suggests design strategies for a more resilient urban planning.

The Cool Roof Rating Council recommends applying the Monte Carlo (MC) method to ASTM standard C1549 to estimate the mean solar reflectance ( R ) of a variegated roofing sample. For samples with high degree of variation in the solar reflectance, the MC approach is slow in convergence. Applying proper set point of low-discrepancy sequences on the variegated roof sample can increase the convergence rate for about 40%. We measure solar reflectance of a variegated roofing sample (gridded to 1″ × 1″ cells) with C1549 and calculate R by averaging the measured solar reflectance. Then, we estimate R using MC and quasi-Monte Carlo (QMC) technique as a function of the number of random spots on the measured sample. To further investigate the performance of QMC, we analyze the sensitivity of the standard error of the mean reflectance of selected sample spots for a variety of simulated samples, where the range and distribution of the solar reflectance is varied. Based on the simulated and experimental results, we recommend using QMC for measuring the solar reflectance of variegated surfaces and propose an equation to estimate the required number of random spots as a function of the mix and the range of solar reflectance of samples.

We used DOE-2.1E to simulate energy consumption for several prototype office and retail buildings in four cold-climate cities in North America: Anchorage, Milwaukee, Montreal, and Toronto. To simulate the effect of snow on the roof, we defined a function calculating the daily U -value and absorptivity of the roof. Cool roofs for the simulated buildings resulted in annual energy expenditure savings in all cold climates. In Anchorage, the simulated annual heating energy consumptions of the old retail building with a dark versus a cool roof (without snow) are 123.5 and 125.8 GJ/100 m 2 , respectively (a 2.3 GJ/100 m 2 penalty for the cool roof). With snow, the heating penalties decreased to 1.2 GJ/100 m 2 , leading to an annual energy savings of 7 $/100 m 2 of roof area. For an old retail building in Montreal and Toronto, a cool roof can save up to 62 $/100 m 2 and 37 $/100 m 2 , respectively. For a new, medium-sized office building with natural gas heating fuel, a cool roof would save 4 $/100 m 2 in Montreal, 14 $/100 m 2 in Milwaukee and Anchorage, and 10 $/100 m 2 in Toronto. Cool roofs can reduce the peak electric demand of the retail buildings up to 1.9 and 5.4 W/m 2 in Toronto and Montreal, respectively.

The energy consumption of commercial buildings in Montreal (Canada) with absorptive and reflective skin materials is investigated. Four building prototypes (small office, medium office, large office, and retail store) with two types of heating systems (gas heating and heat pump) categorized based on vintage and HVAC system (old building with old HVAC, old building with new HVAC, and new building with new HVAC) are studied (total of 24 cases). For each case three simulations are performed using DOE-2 building energy model: (1) dark roof and walls with measured weather data: representing the actual case and the basis for comparing the effect on albedo enhancement, (2) cool roof and walls with measured weather data: determining the direct effect of increasing albedo of an individual building, and (3) cool roof and walls with modified weather data: predicting the effect of albedo enhancement in urban scale that contributes to weather condition. In all cases the effect of snow on the roof is considered and for modification of the weather data output of mesoscale meteorological simulation is used. Calculated energy consumption and energy expenditure showed that, in general, increasing the reflectivity of building skin saves energy and money. The surface modification is more beneficial for old vintage buildings. The maximum expenditure savings is about 11% for buildings with dark roof and walls, where the contribution of urban-scale increase in the surface albedo can be as high as 4% in the total energy expenditure savings.

In this paper, effect of increasing the urban albedo in Montreal (Canada), a cold climate region, on 2-m air temperature and energy consumption of HVAC systems is investigated. An algorithm is developed to select “monthly typical meteorological days” that represent the weather of each month in 2005. The Weather Research and Forecasting (WRF) model is coupled with a multi-layer urban canopy model and a building energy model to accurately simulate the urban climate. The albedo of roof, walls, and road is increased from 0.2 to 0.65, 0.6, and 0.45, respectively. The simulated 2-m air temperature is decreased in all months and the maximum decrease in daily-averaged air temperature is occurred in April (∼0.4 °C). Air temperature decrease is mainly observed during the morning. The annual average decrease of the 2-m air temperature in the urban area is about 0.2 °C (0.2 °C in summer and 0.1 °C in winter). Increasing the albedo in Montreal decreased the air temperature during summertime by as high as 4 °C. Increasing urban albedo showed a small effect on net annual cooling and heating energy expenditure. With the simplified building energy model used in WRF, the annual energy expenditure savings is about 1 $/100 m2.

The objective of this paper is to review the topics related to the optimized operation of intelligent buildings with respect to occupant comfort and energy consumption. To simultaneously optimize energy costs and indoor environmental quality, intelligent buildings should consider several continuously changing inputs including energy exchange processes across the building, sets of indoor and outdoor environmental parameters, energy prices, occupants’ presence, preferences, and behavior inside the building. Therefore, a well-structured framework supported by computational intelligence and optimization methods, environmental monitoring, and behavior modeling techniques, as well as comfort, productivity, and behavioral studies, are required to make optimal decisions for the indoor environment. In this paper, the main concepts, challenges, the latest studies, findings, and developments related to the six topics of (1) Occupant comfort conditions; (2) Occupant productivity; (3) Building control; (4) Computational optimization; (5) Occupant behavior modeling; (6) Environmental monitoring and analysis, in offices, commercial and residential buildings are reviewed. Moreover, future directions and challenges related to the optimized operation of intelligent buildings are discussed.

Tropical cities are more susceptible to the suggested fall outs from projected global warming scenarios as they are located in the Torrid Zone and growing at rapid rates. Therefore, research on the mitigation of urban heat island (UHI) effects in tropical cities has attained much significance and increased immensely over recent years. The UHI mitigation strategies commonly used for temperate cities need to be examined in the tropical context since the mechanism of attaining a surface energy balance in the tropics is quite different from that in the mid-latitudes. The present paper evaluates the performance of four different mitigation strategies to counterbalance the impact of UHI phenomena for climate resilient adaptation in the Kolkata Metropolitan Area (KMA), India. This has been achieved by reproducing the study sites, selected from three different urban morphologies of open low-rise, compact low-rise and mid-rise residential areas, using ENVI-met V 4.0 and simulating the effects of different mitigation strategies- cool pavement, cool roof, added urban vegetation and cool city (a combination of the three former strategies), in reducing the UHI intensity. Simulation results show that at a diurnal scale during summer, the green city model performed best at neighborhood level to reduce air temperature (Ta) by 0.7 °C, 0.8 °C and 1.1 °C, whereas the cool city model was the most effective strategy to reduce physiologically equivalent temperature (PET) by 2.8° – 3.1 °C, 2.2° – 2.8 °C and 2.8° – 2.9 °C in the mid-rise, compact low-rise and open low-rise residential areas, respectively. It was observed that (for all the built environment types) vegetation played the most significant role in determining surface energy balance in the study area, compared to cool roofs and cool pavements. This study also finds that irrespective of building environments, tropical cities are less sensitive to the selected strategies of UHI mitigation than their temperate counter parts, which can be attributed to the difference in magnitude of urbanness.

Increasing surface reflectivity in urban areas can decrease ambient temperature, resulting in reducing photochemical reaction rates, reducing cooling energy demands and thus improving air quality and human health. The weather research and forecasting model with chemistry (WRF-Chem) is coupled with the multi-layer of the urban canopy model (ML-UCM) to investigate the effects of surface modification on urban climate in a two-way nested approach over North America focusing on Sacramento, Houston, and Chicago during the 2011 heat wave period. This approach decreases the uncertainties associated with scale separation and grid resolution and equip us with an integrated simulation setup to capture the full impacts of meteorological and photochemical reactions. WRF-ChemV3.6.1 simulated the diurnal variation of air temperature reasonably well, overpredicted wind speed and dew point temperature, underpredicted relative humidity, overpredicted ozone and nitrogen dioxide concentrations, and underpredicted fine particular matters (PM2.5). The performance of PM2.5 is a combination of overprediction of particulate sulfate and underprediction of particulate nitrate and organic carbon. Increasing the surface albedo of roofs, walls, and pavements from 0.2 to 0.65, 0.60, and 0.45, respectively, resulted in a decrease in air temperature by 2.3 °C in urban areas and 0.7 °C in suburban areas; a slight increase in wind speed; an increase in relative humidity (3%) and dew point temperature (0.3 °C); a decrease of PM2.5 and O3 concentrations by 2.7 µg/m3 and 6.3 ppb in urban areas and 1.4 µg/m3 and 2.5 ppb in suburban areas, respectively; minimal changes in PM2.5 subspecies; and a decrease of nitrogen dioxide (1 ppb) in urban areas.

We have developed a new evaluation method of “thermal radiative power” (TRP) for investigating the impact of building surface material albedo on urban environment. The simulation system ENVI-met is used. This system is a 3D computer model which analyzes micro-scale thermal interactions within urban environments. It simulates urban-scale environmental conditions such as roofs, exterior wall, and ground surface temperatures. Focuses of this research are on the climate change in urban and community scale in cold climates. The urban environmental analysis is carried out in a typical residential area in the central city of Montreal. The model for simulation is based on the existing urban conditions (building layout, building volume and ground surface properties). The TRP with varied building roof materials is calculated and compared. The effect of building surface materials on local climate is analyzed. The selected simulation area in this research is 300 m by 300 m. Each urban surface (ground, walls, and roofs) is analyzed individually, in order to determine the urban environmental contribution. The interaction between reflective surfaces is discussed. Representing the environmental conditions by TRP could help to define the impact of urban surfaces on the macro-climate (urban level) and micro-climate (community level).

The increasing awareness of theurban heat island (UHI) effect has raised the attention for monitoring and evaluating the outdoor thermal comfort in cities worldwide. The urban microclimate is an important factor for pedestrians’ health, but it also affects the urban air quality, the energy use of buildings, citizen wellbeing, and urban sustainability. Issues related to the urban microclimate are becoming more acute in cities given the increasing rates of urban development and construction. In this paper, UHI mitigation strategies in the city of Toronto are assessed. This paper also compares different urban forms according to their orientations, height of wall enclosure, and use of vegetation. The effects of cool surfaces (on the roofs, on the street pavements, or by additional vegetation) are evaluated through numerical simulations using the software ENVI-met. After having obtained the surface temperature, outdoor air temperature, and mean radiant temperature, this study compares three urban areas according to the possible mitigation of net surface radiation and thermal radiative power. The results demonstrate that the duration of direct sun and the mean radiant temperature, which are strongly influenced by the urban form especially in denserareas of the city, play a significant role over the urban thermal comfort. This research supports a sustainable urban developmentin a cold climate, such as that of Toronto. The final scope of this paper isto suggest design strategies for a more resilient urban planning.

The thermal behavior of an external opaque building element depends on the combination of several physical characteristics related to insulation level, thermal inertia, external radiative properties. Concerning the insulation level, parameters like the R-value and its inverse, the U-value or thermal transmittance, are commonly considered in building codes, but they are defined with reference to steady-state conditions and cannot describe the behavior of the element when it is subjected to the cycle of solar radiation. On the other hand, parameters like periodic thermal transmittance, decrement factor and time shift represent the dynamic response of the element resulting from its thermal inertia, so they are often considered but do not include the capability of returning solar energy to the atmosphere. In this regard, a few additional parameters are relevant such as solar reflectance and thermal emittance of the external surface, which are unrelated to both insulation and inertia. In order to rate the overall dynamic behavior of an external opaque building element subjected to the cycle of solar radiation and constant indoor temperature, a “solar transmittance index” (STI) is proposed. STI includes in a single performance parameters the effects of both the radiative properties of the external surface and the thermo-physical properties of the materials under the surface. The utilization of such single performance parameter may be greatly helpful in defining requirements and policies to prevent building overheating, reduce cooling energy demand and mitigate the fallouts of the urban heat island effect.

Solar reflectance (R) of roofing materials is a function of irradiance magnitude and direction, and surface properties. Current methods of labeling the surface reflectance are applicable to homogeneous materials. However, reflectivity of recently developed directional reflective materials (DRM) has a strong dependence on the heterogeneity of the surface. We have developed a model to calculate the hourly reflectance of DRMs as a function of zenith and azimuth angles. We investigate options to represent the reflectance of DRMs. Two main options are proposed for labeling; (1) Option 1: using one reflectance for the whole year, and (2) Option 2: using seasonal reflectance (a number representing summer reflectance, a number representing winter reflectance, and the mean of the winter and summer reflectances for other months of a year). We propose a simple method based on Option 2 to label the solar reflectance of DRMs. The proposed option assigns the average reflectance of DRMs as the winter reflectance and the reflectance of the DRM according to a 20° zenith toward the reflective side as the summer reflectance. In summer, the selected metric estimates the mean hourly heat absorption and energy saving for building energy models accurately, and peak heat absorption of the surface by 8% (

We have developed an algorithm to optimise the fan flow rate by integrating DOE2 (building's energy simulation software) with MATLAB's genetic algorithm. In our developed algorithm, MATLAB can send desired values of optimisation variables for different hours to DOE2 to simulate building's energy use, and it can also receive building's energy consumption and other data from DOE2 for the optimisation. This powerful optimisation tool can be used for finding optimal solution of night-time ventilation fan flow rates and maximising energy savings. Results of optimisation are used to train a neural network to predict fan flow rates for different conditions. Night-time ventilation investigated in DOE2 considers parameters such as (1) night-time ventilation duration, (2) ventilation fan flow rate, (3) outdoor temperature, and (4) temperature difference between outdoor and indoor. Optimisation results show outdoor temperature between 10°C and 18°C and the temperature difference of more than 8°C are appropriate for ...

Highly reflective roofs can decrease the energy required for building air conditioning, help mitigate the urban heat island effect, and slow global warming. However, these benefits are diminished by soiling and weathering processes that reduce the solar reflectance of most roofing materials. Soiling results from the deposition of atmospheric particulate matter and the growth of microorganisms, each of which absorb sunlight. Weathering of materials occurs with exposure to water, sunlight, and high temperatures. This study developed an accelerated aging method that incorporates features of soiling and weathering. The method sprays a calibrated aqueous soiling mixture of dust minerals, black carbon, humic acid, and salts onto preconditioned coupons of roofing materials, then subjects the soiled coupons to cycles of ultraviolet radiation, heat and water in a commercial weatherometer. Three soiling mixtures were optimized to reproduce the site-specific solar spectral reflectance features of roofing products exposed for 3 years in a hot and humid climate (Miami, Florida); a hot and dry climate (Phoenix, Arizona); and a polluted atmosphere in a temperate climate (Cleveland, Ohio). A fourth mixture was designed to reproduce the three-site average values of solar reflectance and thermal emittance attained after 3 years of natural exposure, which the Cool Roof Rating Council (CRRC) uses to rate roofing products sold in the US. This accelerated aging method was applied to 25 products–single ply membranes, factory and field applied coatings, tiles, modified bitumen cap sheets, and asphalt shingles–and reproduced in 3 days the CRRC's 3-year aged values of solar reflectance. This accelerated aging method can be used to speed the evaluation and rating of new cool roofing materials.

Utilizing a cool roof is an efficient way to reduce the cooling energy use of a building. Cool roofs, however, may increase heating energy use in winter. In cold climates, during winter the sun angle is low, days are short, the sky is cloudy, and most the heating occurs early in the morning or in the evening hours when the solar intensity is low. In addition, the roof may be covered with snow for most of the heating season. All these lead to a lower (than what is commonly thought) winter time heating penalties for cool roofs. We used DOE-2.1E to simulate energy consumption in an office building in four cold climate cities in North America: Anchorage (AK), Milwaukee (WI), Montreal (QC), and Toronto (ON). The effect of the sun angle, clouds, daytime duration, and heating schedules can be modelled with existing capabilities of DOE-2. Snow on the roof provides an additional layer of insulation and increases the solar reflectance of the roof. To simulate the effect of snow, we defined a DOE-2 function consisti...

A validated computational fluid dynamics simulation tool is used to study the long-term performance of a centralized latent heat thermal energy storage system (LHTES). The LHTES system is integrated with a building mechanical ventilation system. Paraffin RT20 was used as a phase change material (PCM) and fins are used to enhance its performance. To reduce the computational time, artificial neural networks (ANN) was used to relate the relationships between the LHTES inputs and output parameters. Extensive CFD simulations were carried out to identify all the influential parameters for the development of ANN. They include phase change temperature range, air flow rate, the geometrical configuration of a LHTES system, fin size, and the unit's length. Further CFD simulations were carried out to provide sufficient data for proper training and testing of the ANN. The ANN model was used to predict the LHTES's outlet air-temperature. There was a good agreement between the ANN prediction and CFD model's prediction. The ANN model then was used to study the annual performance of a LHTES for application in Montreal. We found that the potential of use the centralized LHTES system to reduce the cooling load is high with a wider phase change temperature range. The centralized LHTES system contributes to reducing the cooling load from 21% to 36% when the length of the centralized LHTES system is increased from 500 to 650 mm at a flow rate of 1.5 m/s.

Centralized latent heat thermal energy storage (LHTES) system offers potential benefits in energy efficiency, in load shifting, and in emergency heating/cooling load systems. A three-dimensional heat transfer model of a LHTES is developed to investigate the quasi-steady state and transient heat transfer of phase change materials (PCMs). The prediction of model is in good agreement with the experimental data. The effect of convective heat transfer on the melting rate of PCM is assessed. Through a parametric study, the effect of the temperature, PCM phase change temperature range, and the temperature difference of the incoming air and PCM melting temperature on thermal performance of PCM is undertaken. The temperature difference between the air as a heat transfer fluid (HTF) and the PCM melting point has a significant effect on the performances of a LHTES system. The thermal energy retrieved from the centralized LHTES system is the highest when the inlet air temperature is about 10 K higher than the PCM mean melting temperature. Correlations are obtained for the distribution of melting front and solid fraction as a function of time during charging and discharging of LHTES. These correlations can be used for further component optimization and design of cooling and heating systems.

Urban heat island (UHI) phenomenon has been observed in many large cities located in cold regions (e.g. Montreal in Canada) during summer. One of the well-known strategies to mitigate the temperature rise of urban areas is increasing their albedo. Roofs cover about 25% of urban areas and increasing their reflectivity would have a significant effect on the total energy budget of a city. We have studied the effect of increasing the albedo of roofs on the air and skin temperature distributions of the Greater Montreal area. We performed simulations for one-day summer episode (12 July 2005) using the Weather Research and Forecasting (WRF) mesoscale model. The WRF solver (version 3.4.1) is coupled with three different urban canopy models (UCMs): slab, single-layer, and multi-layer. We used all three UCMs by increasing the roof albedo from 0.2 to 0.8 and compared the results. All models simulated a well-defined UHI over areas with high concentration of roofs. They predicted a maximum air temperature decrease of ...

Installing roofs with high solar reflectance and high thermal emittance, known as “Cool roofs,” are becoming increasingly popular because of their cooling energy saving potentials, cost effectiveness and sustainability. Lower surface temperature of cool roofs may affect the hygrothermal performance of roofing systems and hence their performance should be characterized in different climates. We simulated the performance of several roofing systems including: typical, smart, and self-drying roofs for residential and commercial buildings. In addition, we proposed vented roofs with smart vapor retarders in very cold climate regions across North America. We also developed an algorithm to investigate the effect of snow on hygrothermal behaviour of dark and white roofs. Results showed that office buildings never experience moisture accumulation problems during the simulation period (5 years). In residential buildings, white typical roofing compositions with conventional vapor retarders experienced moisture accumulation problems in very cold cities such as Anchorage, Edmonton and St. John's. Using smart vapor retarder (smart roofs) or self-drying roofs helped to decrease risk of moisture accumulation. In these climates, adding a ventilated air space along with using smart vapor retarder eliminated the risk of moisture accumulation and prevented excessive OSB (oriented strand board) moisture content. The risk of mold growth was significantly lowered in vented smart roofs. Simulating the effect of snow on the roofs for Anchorage, Montreal and Chicago showed that the hygrothermal performances of white roofs improved with snow accumulation on the roof.

Reflective roofs can reduce demand for air conditioning and warming of the atmosphere. Roofs can also host photovoltaic (PV) modules that convert sunlight to electricity. In this study we assess the effects of installing a building integrated photovoltaic (BIPV) roof on an office building in Yuma, AZ. The system consists of thin film PV laminated to a white membrane, which lies above a layer of insulation. The solar absorptance of the roof decreased to 0.38 from 0.75 after installation of the BIPV, lowering summertime daily mean roof upper surface temperatures by about 5 °C. Summertime daily heat influx through the roof deck fell to ±0.1 kWh/m 2 from 0.3–1.0 kWh/m 2 . However, summertime daily heat flux from the ventilated attic into the conditioned space was minimally affected by the BIPV, suggesting that the roof was decoupled from the conditioned space. Daily PV energy production was about 25% of building electrical energy use in the summer. For this building the primary benefit of the BIPV appeared to be its capacity to generate electricity and not its ability to reduce heat flows into the building. Building energy simulations were used to estimate the cooling energy savings and heating energy penalties for more typical buildings.

With increasing the solar reflectance of urban surfaces, the outflow of short-wave solar radiation increases, less solar heat energy is absorbed leading to lower surface temperatures and reduced outflow of thermal radiation into the atmosphere. This process of “negative radiative forcing” effectively counters global warming. Cool roofs also reduce cooling-energy use in air conditioned buildings and increase comfort in unconditioned buildings; and cool roofs and cool pavements mitigate summer urban heat islands, improving outdoor air quality and comfort. Installing cool roofs and cool pavements in cities worldwide is a compelling win–win–win activity that can be undertaken immediately, outside of international negotiations to cap CO2 emissions. We review the status of cool roof and cool pavements technologies, policies, and programs in the U.S., Europe, and Asia. We propose an international campaign to use solar reflective materials when roofs and pavements are built or resurfaced in temperate and tropical regions.

Summarization: Increase of the ambient air temperature in cities caused by the urban heat island phenomenon has a seri- ous impact on the economic and social system of cities. to counterbalance the consequences of the increased urban temperatures important research has been carried out resulting in the development of efficient mitigation technologies. the present paper aims to present the state of the art in terms of local climate change and urban heat island mitigation techniques. In particular, developments in the field on highly reflective materials, cool and green roofs, cool pavements, urban green and of other mitigation technologies are presented in detail, while examples of implemented projects are given. Presented on: Journal of Civil Engineering and Management

Many contaminants in the living space of a house, such as carbon monoxide, benzene, toluene, and ethylbenzene, originate from attached garage. As more airtight and energy-efficient houses are designed and constructed, these contaminants may be retained in indoor air for a longer period of time, jeopardizing the occupants' health. In this study, CONTAM, a multi-zone model, is employed to analyze the effect of garage-house interface on the contaminant transport from an attached garage to the living space. Parametric studies of two buildings are carried out to investigate the effect of ventilation on the transport of contaminant from the garage to living space, based on experimental data of five Effective Leakage Area (ELA) of a typical garage-house interface. The results show high concentration of indoor pollutants for typical leaky garage-house interface. Parametric simulations also indicate that the improper design of mechanical exhaust systems can cause higher infiltration of contaminants from the garage to the house, resulting in higher indoor air pollution concentration.

Exposed asphalt shingles undergo chemical and physical changes as they weather. Here we focus on the resulting changes in solar reflectance. Most roofing granules employing inorganic metal oxide pigments are very stable. Initial reflectance changes are therefore due to changes in the asphalt itself, and the loss of processing oils coating the granules. Ultraviolet-induced photo-oxidation of these oils and exposed asphalt produces dark hydrophilic substances that are removed by rain, or in dry climates, transported by dew. After six months, changes in solar reflectance are small and (in California) mainly due an annual cycle of accumulation of atmospheric dust and its removal by rain. In hot humid climates cyanobacteria grow rapidly on granule surfaces, creating dark stains that reduce reflectance by as much as 0.06 at 3 years. We show that in these types of climates (exemplified by Houston) biocide additives such as Cu2O can be employed to maintain solar reflectance. When cyanobacteria are absent, solar reflectance changes over the first three years are on the order of 0.02 or less, and may be either positive or negative.

Cool roofs, cool pavements, and urban vegetation reduce cooling energy use in buildings, lower local air pollution, and decrease greenhouse gas (GHG) emissions from urban areas. To promote widespread and large-scale implementation of cool roofs to moderate urban heat-island phenomenon, more awareness and understanding of cool roof benefits at the local level is needed. As part of an investigation of strategies to mitigate urban heat-island effects, field data gathered from a monitoring project on cool roofs in India were reviewed. An innovative field-based analytical method was developed to quantify cooling energy savings resulting from the installation of cool roofs on commercial buildings. For buildings monitored in the Metropolitan Hyderabad region, the measured annual energy savings from roof-whitening of previously black roofs ranged from 20 to 22 kWh/m2 of roof area, corresponding to a cooling energy use reduction of 14–26%. The application of white coatings to uncoated concrete roofs resulted in annual savings of 13–14 kWh/m2 of roof area, corresponding to cooling energy savings of 10–19%. The annual direct CO2 reductions associated with the reduced cooling energy use were estimated to be 11–12 kg CO2/m2 of flat roof area. Additional field work on various building types and locations will help to understand magnitudes of regional or global potential in energy savings and GHG emission reductions from applying cool roofs. Knowledge about quantified cool roof benefits at both the local and regional level may promote the formulation of new policies and programs throughout the world.