The article investigates the interaction between the sea-breeze circulation and the urban heat island effect in Houston, Texas, located on the Gulf of Mexico coast. The analysis focuses on the summer period in 2022 during the Convective-cloud Urban Boundary-layer Experiment and the Tracking Aerosol Cloud Convection Interactions Experiment. The work, which exclusively used ground-based observations, found a high degree of intra-urban variability in both the temperature and the humidity field during the sea-breeze days. Near-surface virtual potential temperature during the sea-breeze episodes in the metropolitan area varied by almost 10 K, with urban regions near the coast experiencing lower temperature than the inland region. The urban heat island effect was strong enough to create persistent hot spots even during the sea-breeze episodes. On land-breeze days, both the temperature and the humidity fields were more uniform with little spatial variability. The depth of the sea-breeze circulation was captured using X-band radar and radiosondes; it averaged around 1500-2000 m above ground level. The thermal gradient due to the interaction between the sea-breeze circulation and the urban heat island effect led to secondary flows that influenced local convective activity.This article is part of the theme issue 'Urban heat spreading above and below ground'.

Urban extreme precipitation is a crucial study topic due to its growing societal impact and limited understanding of its processes. This study examines the extreme summer precipitation event that occurred in coastal New York City (NYC) on July 17, 2018, using observations and simulations. Severe flooding was caused throughout the City by the thunderstorm event, which had a maximum rainfall of 44 mm and an Urban Heat Island (UHI) intensity of 8 degrees C. The study employs two high-resolution weather model simulations: one uses the Building Effect Parameterization (BEP), while the other incorporates with the BEP, Building Energy Model (BEM), an anthropogenic heat source, and a variable building drag coefficient. Forensics of the event show that increasing temperatures, and a strong UHI ahead of an approaching storm in the northwest initiated an urban storm cell near Bronx borough. The northwest-moving thunderstorm merged with the active urban cell and intensified the precipitation. Surface data indicates classic UHI signatures, such as pre-storm City-warming and poststorm cooling. The BEP + BEM model performed better than the BEP-only model by better simulating anthropogenic heat flux and projecting a greater UHI effect (3.8 vs. 2 degrees C). This improved simulation of anthropogenic heat produced high surface temperatures that strengthened low-level moisture convergence with the City, enhancing precipitation. The results highlight the key role played by anthropogenic heat in altering mesoscale atmospheric phenomena, strengthening storm intensity in coastal-urban environments. The findings of urban and anthropogenic processes on precipitation are transferable for improved urban-weather forecast and for planning resiliency of cities.

Cities are transitioning to a decarbonized energy state to contribute to global warming reduction and for energy security. As cities evolve into this future energy state the compounding effect of a changing local and global climate plays a major background. Key energy sectors to be transitioned are the transportation (EV) and the buildings. In Mega-Cities buildings represent the largest energy demand and atmospheric carbon sources mostly due to the energy required for cooling and heating the spaces. For cold climate cities this transition represents major a major shift to evolve from carbon based space heating into electrification prompting new winter peaks never envisioned with direct implications on the local climate by reduction of the winter Urban Heat Island and potential improvement of the air quality. This work presents a framework to project new energy demands for New York Metro Region under a transition to full electrification and a changing climate towards 2050. For this region, buildings account for 70% of the total energy consumed and carbon emissions. We focus on an electrified winter for buildings and EV by evaluating the energy infrastructure and environmental impacts of such major shifts. For future climate forcing two Socio-Economic Pathways (SSPs) climate scenarios are used of the Sixth Assessment of the Coupled Model Intercomparison Project (CMIP6), 245 and 585. The future climate ensemble used is the downscaled 12 km resolution for the Continental US from the IM3/HyperFACETS Thermodynamic Global Warming Simulation Dataset. The Weather Research and Forecasting model coupled with a multi-layer building environment parameterization and building energy model, is used to perform the analysis. Results indicate a new winter energy peak increase of two fold factor (from 8GW to 16 GW). The presentation will outline context, methods, results, and challenges to meet these goals.

The main goal of our effort is to analyze, design, develop prototype and test electrical air source heat pumps (ASHPs) for hot water, space heating and cooling for multi-family buildings. Focusing on implementing the use of low Global Warming Potential refrigerants (e.g. TR-CO2) system to provide a cleaner and more sustainable alternative to society's heating and cooling needs. This specific research is focused on the heating mode. A key challenge of TR-CO2 systems is the heat rejection which occurs in the gas cooler as a single gas phase. Identification of the pinch point is essential to avoid occurring within the gas cooler; leading to increases in efficiency. We present here system performance of a TR-CO2 air source heat pump system using a customized python computer model coupled to commercial software for whole building analysis. This coupling enables variable heating load conditions for a mid-size multi-family building in New York City. The heat pump system is being modeled using proprietary code for the heat pump system coupled to EnergyPlusT software with different gas cooler variations for constant and then variable loads. The TR-CO2 system is benchmarked against R410A with very optimistic results.

The summer of 2023 in Puerto Rico and US Virgin Islands witnessed an unprecedented surge in extreme heat, surpassing historical norms prompting the analysis of the broader implications for the Caribbean region. This study presents the initial analysis of this remarkable heatwave, the broader context of global climate change, and its potential impacts on people's well-being and energy demand. Historical and 2023 summer daily maximum heat index (HI) are calculated using local stations and regional gridded data. The results show that summer 2023 exhibited a significant departure from the historical climate. For about 70% of summer days, HI values above 100 degrees F were recorded. It was found that the extreme summer is part of a broader regional pattern. The summer of 2023 recorded higher sea surface temperatures with anomalies above 2.07 degrees C and the weakening of the Azores High resulting in reduced wind speed in the region. This diminished the cooling effect associated with cooler maritime air aiding the stagnation of air masses over the region. The analysis sets a threshold of HI of 103 degrees F to assess human exposure. A significant portion of the region's population, especially in urban areas, was exposed to HI above this threshold. Concurrently, the intense heat led to increased energy demands, with about a 25% increase in peak energy demand in buildings. Per capita consumption exceeded 200 kWh/month for cooling and human comfort and anomalies adding around 15 kWh/month. The study is a step forward in developing adaptive strategies to safeguard vulnerable communities due to global warming-induced extreme events.

This work in progress (WIP) paper shares experiences and lessons learned from the first three years in the development and implementation of a model to improve the preparation and transition of Hispanic STEM doctoral students into community college (CC) faculty positions by the Hispanic Alliance for the Graduate Education and the Professoriate (H-AGEP). This is a collaborative effort between the City College of New York (CCNY) and The University of Texas at El Paso (UTEP) in partnership with El Paso CC (EPCC), LaGuardia CC (LaCC), and Queensborough CC (QCC). The proposed model addresses the important need of recruiting more Hispanic faculty at CC who can serve as outstanding teachers, mentors and role models to students at CC. Over 50% of Hispanics start their college journey at a community college while less than 5% of faculty in higher education is from Hispanic backgrounds. Increasing the can increase the number of Hispanic who receive degrees from community college and who transfer to 4 year institutions to obtain degrees in STEM. Higher representation of faculty from Hispanic and other racial/ethnic groups on campus have a positive impact on underrepresented minority student's success when measured in grades and course completions as well as retention and degree completion. The lessons learned came from a Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis performed as part of a self-study conducted in December 2020. The study included H-AGEP fellows, CCNY and UTEP participant faculty, dissertation advisors, and CC faculty mentors. The lessons learned provide important feedback for program improvement as well as information to teams who may be interested in developing alliances and collaborations with similar goals. A key result of the assessment is the value that CC partners bring in supporting teaching training and in providing a positive perspective on careers at community college to the participating doctoral students. The paper presents a brief summary of the H-AGEP model. Then it summarizes the findings from the self-study and concludes with the lessons learned from the process.

The power transmission infrastructure is vulnerable to extreme weather events, particularly hurricanes and tropical storms. A recent example is the damage caused by Hurricane Maria (H-Maria) in the archipelago of Puerto Rico in September 2017, where major failures in the transmission infrastructure led to a total blackout. Numerous studies have been conducted to examine strategies to strengthen the transmission system, including burying the power lines underground or increasing the frequency of tree trimming. However, few studies focus on the direct hardening of the transmission towers to accomplish an increase in resiliency. This machine learning-based study fills this need by analyzing three direct hardening scenarios and determining the effectiveness of these changes in the context of H-Maria. A methodology for estimating transmission tower damage is presented here as well as an analysis of impact of replacing structures with a high failure rate with more resilient ones. We found the steel self-support-pole to be the best replacement option for the towers with high failure rate. Furthermore, the third hardening scenario, where all wooden poles were replaced, exhibited a maximum reduction in damaged towers in a single line of 66% while lowering the mean number of damaged towers per line by 10%.

Qatar Environment and Energy Research Institute (QEERI) hosted a workshop entitled “Impact of Sustainable Buildings in Arid Environment on the Indoor and Outdoor Air Quality,” held in Doha, Qatar, on May 17–19, 2022, co-funded by the Qatar National Research Fund (QNRF), and co-organized by City College of New York (CCNY). The workshop provided a premier interdisciplinary platform for local researchers and enablers to engage and exchange knowledge and experiences with international leading practitioners and subject matter experts in the fields of sustainable buildings, indoor and outdoor air quality, and the urban heat island phenomena. A diverse number of regional partners and stakeholders were represented. The workshop benefitted from a pool of invited international subject experts from various universities and entities. The outcome-driven workshop included breakout sessions where participants actively engaged in brainstorming discussions guided by facilitators. The discussions focused on driving impact in Qatar and beyond by examining the current research landscape and identifying collaborative opportunities. The short-term and long-term outcomes of potential initiatives and project proposals are outlined in this summary. An example of a short-term outcome is the proposed collaborative project to investigate the impact of almost doubling the state of Qatar’s population (over 1.5 million fans are expected to visit the country during the World Cup causing a shock to the system) on vital elements in the city, such as mobility, telecommunication services, and the local environment. In addition, multiple potential research proposals with international collaborations were proposed. A special issue on the subject in the Journal of Engineering for Sustainable Buildings and Cities was recommended as an immediate actionable outcome.

During hurricanes, power transmission and distribution systems are highly susceptible to structural failures due to constant exposure to strong winds. This article focuses on the impacts of Hurricane Maria (H-Maria) in Puerto Rico (PR) as an exceptional case study. The storm caused extensive damage to the power infrastructure, including transmission lines, distribution lines, and substations. The study highlights the importance of accurately representing the turbulent hurricane boundary layer (HBL) in simulations, particularly in areas with complex terrain. The research employs a Large Eddy Simulation (LES) approach within the Weather Research and Forecasting model (WRF) to recreate H-Maria's winds. The simulation demonstrates improved accuracy in representing the HBL, showcasing stronger wind velocities in mountainous areas where the power towers are situated. Further analysis reveals significant downward motion and turbulence intensity within the HBL at the location of the transmission line. These findings highlight the heightened risk of structural failure and damage due to fluctuating wind directions and the complex terrain's amplifying effect.

Cities are accelerating policies to electrify their energy sectors as a key strategy for reducing greenhouse gas emissions. In densely populated cities with cold climates, the building sector often accounts for over 70% of total energy consumption during winter seasons. In such cold climate megacities, the common practice for heating building spaces involves burning oil or gas. A major shift from this conventional approach toward electric-based heating technologies could have far-reaching implications. In this work, we focus on New York City (NYC), where buildings account for over 75% of the total energy consumption used during winter seasons. The city has adopted policies aimed at achieving deep decarbonization by targeting buildings as a primary source of emissions. We evaluate the potential energy infrastructure and environmental impacts of such major shifts by focusing on the adoption of air-source heat pumps from natural gas boilers. The Weather Research and Forecasting model, coupled with a multilayer building environment parameterization and building energy model, is used to perform this analysis. A city-scale case study was performed over the winter month of January 2021. Simulation results show good agreement with surface weather stations. We show that a shift of heating systems from gas to electricity results in an equivalent peak energy demand from 21,500 MW to 5800 MW, while reducing the peak urban heat island (UHI) by 2.5-3 degrees C. Results highlight potential trade-offs in adaptation strategies for cities, which may be necessary in the context of increasing decarbonization policies.

The main objective of this work is to develop a commercially feasible R744 HP system for the multi-family building sector for cold climates. The motivation behind this effort is the urgent need to bring into the markets, an efficient, low global warming potential air source heat pump system for cold-climates. It will aid in electrifying space heating, an essential strategy to decarbonize our society. We plan to address the efficiency of space heating for colder climates like the Northeast while being affordable and attractive to customers with existing gas or oil-powered systems. Our strategy aims to focus on optimizing the system using transcritical R744, this primarily means a revamp of various components, particularly the gas cooler. Gas coolers have been a challenge in terms of optimization with lower COPs than that of the more commonly used refrigerants. We have conducted an assessment of the viability of a staggered tubes design which allows for more efficient heat transfer between the R744 and air. This is quite important as the refrigerant operates at a much higher temperature (about 220–250°F) than seen in hydrofluorocarbon systems. Lowering the outlet temperature on the gas cooler side is a major step in providing a suitable design to be used in both residential and commercial buildings. A Blackbox model has been designed, which allows for the simulation of different design options for optimization of the gas cooler design. A 3.5-ton capacity gas cooler with a COP above 2.5 has been designed to be built for lab testing conditions under simulated outdoor winter conditions.

Prathap Ramamurthy1,∗, Jorge González, Luis Ortiz, Mark Arend and Fred Moshary 1 Department of Mechanical Engineering, City College of New York, New York, NY, United States of America 2 Department of Atmospheric and Environmental Sciences, University of Albany, Albany, NY, United States of America 3 Department of Atmospheric, Oceanic, and Earth Sciences, George Mason University, Fairfax, VA, United States of America 4 Department of Electrical Engineering, City College of New York, New York, NY, United States of America ∗ Author to whom any correspondence should be addressed.

As cities are increasing technological efficacy on greenhouse gas (GH) emission reduction efforts, the surrounding urban ecosystems and natural resources may be affected by these measures. In this research, climate indicators such as heat index, extreme heat events, intensified urban heat islands (UHIs), and sea breeze are projected for the middle and end of the 21st century to understand the climate change signal on these variables with and without building energy mitigation measures. Cities amplify extreme heat and UHI impacts by concentrating large populations and critical infrastructure in relatively small areas. Here, we evaluate the combined climate and building energy mitigation impacts on localized climate metrics throughout the 21st century across extreme emission scenarios (RCP8.5) for the tropical coastal city of San Juan. The analysis of statistically downscaled global circulation model outputs shows underestimation for uncorrected summer daily maximum temperatures, leading to lower extreme heat intensity and duration projections from the present time which are corrected using bias-corrected techniques. High-resolution dynamic downscaling simulations reveal a strong dependency of changes in extreme heat events in urban settings, however, the intensities shift to lower-level grasslands and croplands with energy mitigation measures (combination of white roof, tilted photovoltaic roof, and efficient heating ventilation and air conditioning systems). The building energy mitigation measures have the potential of reducing the UHI intensities to 1 °C and 0.5 °C for the 2050 and 2100 climate periods, respectively.

As climate change continues to evolve with alarming increases in extreme weather conditions, its impact on building cooling and heating energy needs, in order to maintain acceptable occupant comfort becomes increasingly beyond the design constraints. To reduce such mismatch, it is important to improve the accuracy of weather files used for building energy simulations (BES). The widely used simulation software, EnergyPlus (EP) provides Typical Meteorological Year (TMY) weather data, which are not designed to detect extreme conditions and have limited data locations. There is a greater number of Microclimate (MC) stations that can be incorporated into BES for higher resolution data. The challenge is the time-consuming data preparation process to match the EP format. To address this issue, the co-authors developed a program, Virtual Information Fabric Infrastructure (VIFI), which automatically prepares MC data for more accurate BES. To demonstrate the need for higher resolution data, this study analyzed locations in the Great Lakes region and found that July's cooling demand for Rogers City MI and Alpena MI, which are located 35 mi (56 km) apart, differed by 19%. The results emphasize the importance of considering MC data in BES and provide a solution for their efficient integration into BES.

Datasets generated during and/or analyzed during the Socio-Technical Approach for the Assessment of Critical Infrastructure Systems Resiliency in Extreme Weather Events.

Sea surface temperatures and vertical wind shear are essential to tropical cyclone formation. TCs need warm SSTs and low shear for genesis. Increasing SSTs and decreasing VWS influences storm development. This work analyzes SST and VWS trends for the Caribbean, surrounding region, and the Atlantic hurricane main developing region from 1982–2020. Storm intensity increases significantly during this period. Annual and seasonal trends show that regional SSTs in the MDR are warming annually at 0.0219 °C yr−1 and, per season, 0.0280 °C yr−1. Simultaneously, VWS decreases during the late rainfall season, at 0.056 m/s yr−1 in the MDR and 0.0167 m/s yr−1 in the Caribbean and surrounding area. The Atlantic Warm Pool is expanding at 0.51 km2 per decade, increasing upper atmospheric winds and driving VWS changes. Correlations of large-area averages do not show significant relationships between TC intensity, frequency, and SSTs/VWS during the LRS. The observed changes appear to be associated with regional warming SSTs impacting TC changes. Plain Language Abstract: Tropical cyclone (TC) formation requires warm ocean waters and low wind shear. Changes to sea surface anomalies and wind shear influences are essential to understanding storm development and intensification. The ability to forecast storm changes is vital to human lives and livelihoods. This work analyzes sea surface temperatures (SSTs) and vertical wind shear (VWS) trends in the Caribbean, surrounding areas, and the Atlantic main developing region (MDR). We found increasing SSTs, decreasing wind shears, an expanding Atlantic Warm Pool (AWP), and increased storm intensity during the Atlantic hurricane season.

Tropical environments cover a large part of the Earth: almost all the portion of the planetary surface included between latitudes 23.43 North (Tropic of Cancer) and 23.43 South (Tropic of Capricorn) [1]. Tropical climates can be divided in three sub-climates: rainforest, monsoon and savannah [2]. All these climates imply high humidity values and average temperatures of the coldest month greater to 18 °C [3]. In such environments, buildings and cities must face overheating for large periods of the year. Moreover, almost the 40% of humanity is living in these environments [4], and the number is expected to grow to the 50% by the 2050 [5]. Many megalopolises with more than 10.000.000 of inhabitants are placed there: Calcutta (India), Lagos (Nigeria), Rio de Janeiro (Brazil), Canton (China), Manila (Philippines) are just a few examples.

Abstract Tropical environments cover a large part of the Earth: almost all the portion of the planetary surface included between latitudes 23.43 North (Tropic of Cancer) and 23.43 South (Tropic of Capricorn) [1]. Tropical climates can be divided in three sub-climates: rainforest, monsoon and savannah [2]. All these climates imply high humidity values and average temperatures of the coldest month greater to 18 °C [3]. In such environments, buildings and cities must face overheating for large periods of the year. Moreover, almost the 40% of humanity is living in these environments [4], and the number is expected to grow to the 50% by the 2050 [5]. Many megalopolises with more than 10.000.000 of inhabitants are placed there: Calcutta (India), Lagos (Nigeria), Rio de Janeiro (Brazil), Canton (China), Manila (Philippines) are just a few examples.

Global climate change has increased the need for cooling indoor spaces, leading to a rise in adoption of air conditioning. This adoption, while decreasing health risks, can increase energy use and pose economic burdens in low income households. Here, we estimate the burden associated with cooling, as well as potential extreme heat exposure without it in the largest city in the US, New York using a coupled weather and building energy model, utility pay scales, and household income data from the US Census.Results show uneven distribution of AC economic burden, with lower income neighborhoods experiencing the largest relative costs. High-burden neighborhoods see the largest climate-driven increases in spite of lower enthalpy increases. These neighborhoods also have the most exposure to indoor extreme heat, which may triple by end of century. Energy burden may pose a barrier to AC operation, with estimated cost in the lowest income households reaching up to 6.1% of income for a 100 m(2) dwelling, which could increase to 8% by end of century. We also explore adaptation strategies and quantify their impacts, finding that modifying traditional set points and reflective roofs can reduce energy burden significantly, by up to 20% in the highest burden neighborhoods.

Hurricanes are a dominant disaster in the Caribbean, always causing serious power outages throughout the islands. Hurricane Maria was a prime example, causing unimaginable destruction of the power infrastructure of Puerto Rico (PR). Consequently, one month after the hurricane landfall, approximately 80% of the population was still without power. After an event of such massive destruction, the electric power restoration process progresses very slowly. This timeline can be improved using power outage (PO) forecast models that help identify the vulnerable places before the hurricane landfall. Generally, these models are trained with historical power outages records, associated data on weather conditions, and additional information about the natural and built environments. However, PO records are often difficult to acquire, and, in many instances, the power utility companies may not record them. This study utilizes a satellite-based Visible Infrared Imaging Radiometer Suite (VIIRS) night light data product as a surrogate for the power delivery to predict hurricane-induced PO in areas having limited to nonexistent historical data records. The processed satellite data is then used along with geographic variables, and simulated weather data to formulate machine learning-based algorithms to predict PO for future hurricane events. These models are applied and validated in the context of the PR catastrophic storm, Hurricane Maria.