Climate Of City Research Articles

Urbanization exacerbates climate sensitivity of eastern United States broadleaf trees.

Tree growth is a key mechanism driving carbon sequestration in forest ecosystems. Environmental conditions are important regulators of tree growth that can vary considerably between nearby urban and rural forests. For example, trees growing in cities often experience hotter and drier conditions than their rural counterparts while also being exposed to higher levels of light, pollution, and nutrient inputs. However, the extent to which these intrinsic differences in the growing conditions of trees in urban versus rural forests influence tree growth response to climate is not well known. In this study, we tested for differences in the climate sensitivity of tree growth between urban and rural forests along a latitudinal transect in the eastern United States that included Boston, Massachusetts, New York City, New York, and Baltimore, Maryland. Using dendrochronology analyses of tree cores from 55 white oak trees (Quercus alba), 55 red maple trees (Acer rubrum), and 41 red oak trees (Quercus rubra) we investigated the impacts of heat stress and water stress on the radial growth of individual trees. Across our three-city study, we found that tree growth was more closely correlated with climate stress in the cooler climate cities of Boston and New York than in Baltimore. Furthermore, heat stress was a significant hindrance to tree growth in higher latitudes while the impacts of water stress appeared to be more evenly distributed across latitudes. We also found that the growth of oak trees, but not red maple trees, in the urban sites of Boston and New York City was more adversely impacted by heat stress than their rural counterparts, but we did not see these urban-rural differences in Maryland. Trees provide a wide range of important ecosystem services and increasing tree canopy cover was typically an important component of urban sustainability strategies. In light of our findings that urbanization can influence how tree growth responds to a warming climate, we suggest that municipalities consider these interactions when developing their tree-planting palettes and when estimating the capacity of urban forests to contribute to broader sustainability goals in the future.

Episodic populist backlashes against urban climate actions

Populism is multilayered and involves two main dimensions – ideology and strategy – which are employed within and beyond political parties. These dimensions can result in sometimes overlapping but generally divergent backlashes, targeting specific climate and sustainability interventions in cities. This critical commentary presents episodic populist backlashes against urban climate actions by exploring how they create their own political landscapes across the political spectrum in cities against progressive urban climate agendas. Specifically, the article examines how episodic populist backlashes manifest on an urban scale and highlights the need for urban scholars to pay more attention to the phenomenon. The article proposes two complementary explanations for why populism precedes urban climate actions in episodic and thematic ways. These explanations include policy backlashes against diffused global climate norms in cities, and counter-movements and rhetoric against climate justice and what it entails, such as inclusion in decision-making and intersectionality. The article then concludes by offering a research agenda on the episodic populist backlashes against urban climate actions, which highlights the need for a better understanding of how episodic populist movements might emerge into global climate policy diffusion, and climate justice coupled with intersectionality in cities of the Global North and Global South.

Research on energy saving potentials using pure and zeotropic refrigerants in data center cooling systems

Zeotropic refrigerants possess the characteristic of temperature glide during phase-change process, making them suitable for temperature matching between cold and hot sources and reducing total temperature differences. In this manuscript, the applicability of two commonly used refrigerants, zeotropic refrigerant R407C and pure refrigerant R134a in data center cooling systems are investigated. Firstly, the heat transfer and flow characteristics of R407C and R134a are studied to obtain boiling heat transfer empirical correlations. Secondly, a data center cooling model is established, and modeling calculations are conducted based on experimental results. Finally, the influence of refrigerants on the energy saving effect are calculated based on the model. Experimental results demonstrate that R134a exhibits a 48.3% higher boiling heat transfer coefficient compared to R407C at heat flux 16500 W/m2. However, when considering a data center cooling system, using R407C as working fluid shows the advantage of temperature matching as heat transfer area increases. Based on modeling results, at large heat transfer area, the annual cooling load factor using R407C at low mass flow rate is 0.5% lower than that of using R134a at low mass flow rate, and 22.5% lower than that of using R134a at large mass flow rate for typical climate city Harbin.

Early engagement and co-benefits strengthen cities’ climate commitments

Cities can lead the way in tackling climate change through robust climate actions (that is, measures taken to limit climate change or its impacts). However, escalating crises due to pandemics, conflict and climate change pose challenges to ambitious and sustained city climate action. Here we use global data on 793 cities from the Carbon Disclosure Project 2021 platform to assess how the COVID-19 crisis has affected cities’ reported climate commitments and actions and the factors associated with these impacts. We find climate actions persist despite funding shortfalls; yet only 43% of cities have implemented green recovery interventions. Co-benefits of climate action (for example, health outcomes) and early engagement on sustainability issues (for example, via climate networks) are associated with sustained climate action and finance during COVID-19 and green recovery interventions. Cities should strengthen sustainability co-benefits and relationships with coalitions of actors to support durable climate commitments during crises.

Innovative continuous heating-enhance solar still farm- A case study for irrigation in a pistachio orchard

Water scarcity is a global concern that has become one of the main problems for agricultural activities, especially in countries with arid and semi-arid climates like Iran. Sirjan city, a sweltering and arid city in Iran, is one of the locations where its economy mainly relies on pistachio orchards and other agricultural activities, which are highly affected by poor water quality and high TDS of wells. This city's climate, high solar irradiation, sunny sky, and the high requirement for distilled water for irrigation make utilizing solar power and solar-still desalination systems a reasonable choice. However, the low water production rate of conventional solar still systems prevents the use of this technology in field-scale projects and real agricultural activities. Therefore, we mixed solar still and solar power, to enhance the water production rate and provide water with proper TDS for a pistachio orchard in Sirjan City. In comparison to conventional solar still, the proposed continuous heating-enhanced solar still benefits from several improvements, including passing water through the grooved glass that leads to lowering the glass temperature, increasing water basing temperature by a heating element, polyurethane isolation of basin and capability of working during day and night. The mentioned improvements will lead to an increase in daily water production by 21% from 5.5 to 6.6, 24% from 5.5 to 6.8, 31% from 5.5 to 7.2, and 44% from 5.5 to 7.92 respectively. Therefore, utilizing all the mentioned approaches leads to a 120% increase in daily water production from 5.5 to 12.17 L and in comparison, to the conventional mechanisms, significantly reduces the required area for the system. The results showed that the proposed method is highly effective and could be used in real agricultural activities in arid and semi-arid climates.

Chasing Comfort in the Chill: Simulating the Impact of Opened Streamlines on Microclimatic Conditions, Thermal Comfort and Building Facades in Cold Climate Cities

This project aims to evaluate the impact of water surfaces on urban microclimate change and the presence of water in dense urban areas on the heating and cooling loads of buildings by proposing the rehabilitation of urban water resources. It mainly questions whether favorable outcomes for urban microclimate may be expected at the local level with the rehabilitation of water bodies and the contribution of repaired water lines to energy savings in nearby buildings. The analyses are made for Erzurum, the coldest climate city in Türkiye, by using the ENVI-met program, a dynamic simulation tool widely used for microclimate analysis. The analyses use the meteorological data recorded on the site during the same years’ summer and winter periods. The microclimate change caused by the green areas, which involve the opening of covered streamlines, was estimated, and the change in the energy load of buildings was quantitatively analyzed. The findings show that rehabilitation of water lines in urban areas improved microclimate conditions and provided energy-saving opportunities for buildings. Thus, policy-makers should produce more green spaces, including water surfaces, in urban areas to improve the adaptation capacity of cities and mitigate the negative effects of climate change.

Spatial pattern of urban forest diversity and its potential drivers in a snow climate city, Northeast China

Urban forest diversity is the cornerstone of providing ecosystem services and improving urban environment. However, the spatial pattern of urban forest (UF) diversity and its driving mechanisms are still not well understood. In our study, using 330 UF sample plots and the corresponding plot-based standard deviation values of remote sensing parameters with different spatial resolutions, we developed prediction models for the spatial pattern of UF diversity, and the driving factors of UF diversity were further explored in our study. Our findings indicated that the 3-m spatial resolution of remote sensing was optimal for predicting UF diversity. Both excessively high and excessively low resolutions can increase misclassification errors. In addition, among the three prediction models, the boosted regression trees (BRT) model exhibited greater robustness than the support vector machine (SVM) and random forest (RF) models for predicting UF diversity. UF species were abundant, with 112 tree species in Changchun City. Spatially, the UF diversity showed a significant gradient decreasing trend from suburban areas (outer rings) to downtown areas. We also observed higher diversity in the older communities with high housing prices, supporting the “legacy effect and luxury effect”. Additionally, our research revealed that socioeconomic factors, landscape cover, and patterns collectively explained 41.25% of the UF diversity variation, wherein socioeconomic factors contributed the most variation (17.33%). We further found that UF diversity does not increase more with increasing house prices when the house prices are higher than ¥ 12,000/m2. The higher patch density reduced UF diversity, while a higher UF landscape shape index (LSI) promoted diversity. The LSI threshold, which significantly impacted UF diversity, was about 12. Our research showed that high-resolution remote sensing offers a rapid, cost-effective approach to acquire UF diversity patterns, which could enhance urban forest diversity and contribute to sustainable urban development.

Performance Evaluation of Single Stage Flash Evaporation Desalination Unit Integrated with a Parabolic Trough Solar Collector for Basrah City Climate, Iraq

Solar energy is the most suitable among all renewable energy options for competing with fossil fuels in desalination due to its ability to utilize both heat and power for the process. In this study, the Parabolic Trough Solar Collector (PTSC) for powering a Single Stage Flash (SSF) desalination unit was proposed for Basrah city climate, Iraq. The desalination system comprises two directly coupled sub-systems: the PTSC and the SSF desalination unit. The preheated feed brine water coming from condenser was used as a Heat Transfer Fluid (HTF) for PTSC, which gets heated to a desired temperature referred to as the Top Brine Temperature (TBT). The numerical simulations were performed via EBSILON professional 16.02 (2022) software. The effects of TBT, mass flowrate of feed brine water to get the desired TBT, solar collector area, and vacuum pressure inside flash chamber on the performance of the desalination system was studied. A major finding of the current study can be summarized as follows: The collector efficiency is enhanced eventually as TBT increases. The maximum values of distillate water in June are around 5.5, 4.56, 3.69, 2.75 and 1.85 kg/h for 12.408, 10.434, 8.3472, 6.26, and 4.1736 m² collector area respectively, when TBT 107 °C and vacuum pressure 40 kPa. For 1.598 m² collector area, the total distillate in the 1st of June amounted to 7.9 kg, with an average production rate of around 0.7 kg/h. The solar SSF system's productivity per solar collector unit area at 20 kPa, 15 kPa, and 10 kPa vacuum pressures was 4.7 kg/day/m², 5.3 kg/day/m², and 6.25 kg/day/m², respectively. The average Performance Ratio (PR) values are determined to be 0.694, 0.577, and 0.491 for 10 kPa, 15 kPa, and 20 kPa, respectively. These results are very acceptable when compared with an existing literature.

Exploring the Effect of Aspect Ratio (H/W) on Thermal Environment in Multiple Climate Zones with Open-Source Data

For a country with multiple climate zones, analyzing the impacts of urban design in different climate zones is a prerequisite to climate adaptation policies. However, countries advanced in climate adaptation strategies are mostly located in a single climate zone, leading to a lack of research on climate adaptation policies for multiple climate countries. As China is launching the urban zoning management policy, this research takes China as an example to explore a technique to quickly distinguish the impact of urban design in multiple climate zones by combing the open-source data with the Envi-met tool, where the open-source data indicate the data that can be obtained from public platforms such as the internet and Envi-met is a microclimate simulation tool. First, the open street map tool, one of the open-source data, was used to abstract the typical models of each climate city. Then, open-source meteorological data were employed as the boundary conditions for Envi-met simulation. Lastly, after the Envi-met simulation, the impacts of aspect ratio (H/W) on multiple climate indicators in seven climate cities were analyzed with the meteorological interpolation method. The analytical results show that H/W has a stronger ability to regulate the thermal comfort of high latitude cities. In Guangzhou and Changsha, the maximum differences of PET caused by H/W are only 0.61 °C (Changsha) and 0.63 °C (Guangzhou). H/W has the strongest regulating effect on the thermal comfort in Harbin, with the highest value of 8.62 °C. The regulating effects of H/W on outdoor PET in other 4 cities are 4.37 °C in Urumqi, 3.29 °C in Xining, 1.29 °C in Xi’an, and 0.76 °C in Kunming. In addition, H/W mainly affects PET by modifying the radiant temperature. Compared with mean radiant temperature, the effects of H/W on air temperature, relative humidity, and wind speed are negligible. Longitude regulates the occurrence time of the coldest and hottest thermal environments. Among the seven climate zones in China, the difference in appearance time between the coldest and hottest reaches up to 2 h. For the implementation of urban zoning management policy, in China, high latitude cities are encouraged to high H/W to create a comfortable city. Cities whose latitude is less than 30° may not consider the impacts of H/W on thermal comfort. This method of combining open-source data with Envi-met can serve as a reference for other countries that span multiple climate zones. In addition, these results provide a decision-making basis for the management of H/W in different climate cities of China.

The role of City Climate Networks in Promoting Citizen Participation in Municipalities: A Critical Multi-Case Analysis

BackgroundAt the COP21, cities were recognised as key actors in combatting climate change. In supporting cities, climate city networks such as transnational climate networks (TCNs) and national climate networks (NCNs) have emerged to enable cities in building capacities and formulating climate policy whilst also encouraging citizen engagement and participation in public decision-making. This paper addresses the question whether and how TCN or NCN membership enables municipalities to implement citizen participation in public decision-making. Six propositions are presented addressing: presumed influence of TCN membership on citizen participation, organization of citizen participation, initiator capacity, goal setting, involvement of stakeholders, participatory methods used, and planning processes. A multi-case study research design is used to verify these propositions, comprising of four medium-sized cities in the Netherlands and three in Belgium.ResultsResults of the analysis of four cities in The Netherlands show that municipalities having membership to climate city networks only to a low extent empower citizen participation via local climate agendas. Citizen participation emerges rather bottom-up via local initiatives or capacity building via EU framework programs—outside TCNs or NCNs—that better suit financial needs and provide more immediate benefits to municipalities. None of the six propositions were confirmed. A more positive image resulted from the Belgian cases that moderately confirmed four out of six propositions (i.e., organizing citizen participation, goal setting, selection of methods, and planning), and featured indirect empowerment via externally funded implementation projects following firm integration of participation in local climate policy through TCN influence.ConclusionsIn terms of citizen participation selected municipalities in the Netherlands having TCN and/or NCN membership only to a small extent differ from those not having membership. This is partly due to poor implementation of TCNs and NCNs—with Covenant of Mayors and ‘Klimaatverbond’ lacking support structure and capacity—having lost importance during the past years. However, there is reason to believe that context makes a difference as revealed by the cases from Belgium, which revealed more positive results.

Effect of sunlight on vitamin D and hemoglobin levels among the residents of Ningbo, China.

Objective: this study investigated the effect of sunlight on vitamin D and hemoglobin levels among the residents of Ningbo, China. The impact of gender, age, and season on vitamin D and hemoglobin levels was also explored. Methods: a total of 8,481 research subjects, including 5,146 men and 3,335 women, who were permanent residents of Ningbo and received health checkups at Ningbo Second Hospital, were included in the study. Ningbo City climate bulletin data from 2019 to 2022 was also included. Results: the study subjects received an average of 132.20 ± 40.05 h of sunlight exposure per month and had average vitamin D levels of 19.63 ± 6.61 ng/ml. Hemoglobin levels were adequate in 85.4 % of the participants and deficient in 14.6 %. Sunlight exposure correlated positively with vitamin D and negatively with hemoglobin levels. Regression analysis indicated that gender, age, and season affected vitamin D and hemoglobin levels to different degrees. Conclusion: in Ningbo, vitamin D deficiency was common in adults while hemoglobin levels were mostly normal. The amount of sunlight exposure had a significant effect on vitamin D and hemoglobin levels and this relationship was impacted by gender, age, and season.

Evaluation of the GRAMM/GRAL model for high-resolution wind fields in Heidelberg, Germany

Independent verification of mitigation efforts for climate and air quality action in cities relies on inferring emissions from atmospheric concentration measurements. As emissions are dispersed in the atmosphere before they reach an instrument, the quantitative estimation of emissions requires an understanding of the atmospheric transport and associated uncertainties. In this study, we analyse the catalogue of steady-state flow fields generated by the Graz Mesoscale Model (GRAMM) coupled to the Graz Lagrangian Model (GRAL) for an entire year in Heidelberg, Germany. We use a loss function for the wind field selection, which assigns a best-matching catalogue entry to any given hour by exploiting observation data. We introduce a new loss function which finds an optimal balance between differences in wind speed and wind direction. We evaluate the performance of the model based on 15 meteorological measurement sites, of which 14 are in the inner high-resolution and building-resolving GRAL domain (12.5 km × 12.5 km, 10 m resolution). Performance metrics include mean bias (MB) and root mean square errors (RMSEs) of simulated and observed wind speed and wind direction for all individual stations. On average, we find a mean underestimation of wind speed of 0.14 ms−1 corresponding to about 7 % of the mean wind speed and a mean RMSE of 1.03 ms−1. For wind direction, a mean overall bias smaller than 1° is achieved, but individual stations show larger biases (mean absolute bias: 37°), especially at stations where wind speeds are low on average. Evaluation benchmarks for mean biases of wind direction and wind speed of mesoscale models provided by the European Environmental Agency (EEA) are met at 11 and 14 out of 15 stations at low measurement heights, respectively. Recently suggested extended benchmarks for complex terrain are met at almost all stations. Additionally, for the first time, we analyse the model's ability to simulate the vertical wind profile and we analyse the benefit of implementing a wind profile measurement into the process. We find that the model does not fully capture the vertical profile in our setting. We further study the required measurement network size and find that a high number (> 6) of meteorological stations improves the selection of flow fields over the entire GRAL domain substantially. The conducted comprehensive analysis of the wind fields in the GRAL domain are the basis for detailed quantitative analysis of greenhouse gas and air pollutant emissions using the GRAMM/GRAL modelling framework.

INFLUENCE OF TRANSPORT OPERATIONS ON THE CHANGING LOCAL CLIMATE IN NIGERIA’S SOUTHWESTERN CITIES

The activities of transport operations exhibit both positive and negative outcomes. Its negative effects on human health and the sustainability of the environment are of interest in this study. As a result, the study investigated the influence of transport operations on the changing local climate in Nigeria's southwestern cities. It investigated motorists' socioeconomic status (SES) and travel characteristics; the salient components of transport operations contributing to greenhouse gas emissions (GHG emissions); the effect of GHG emissions from transport operations on the local climate; transport externalities contributing to local temperature changes; and the effect of GHG emissions from transport operations on human health in the research location. This study employed a cross-sectional research design, utilizing systematic sampling to collect 580 copies of questionnaires administered to commercial motorists found in queues across two randomly selected parks in each capital city within the region. Both descriptive and inferential statistics (ANOVA and Linear Regression) were used to analyze the data. The study found that 60% of the motorists were middle-aged (aged between 36 and 45). The majority (70%) drive an average of 100 to 150 km, and premium motor spirit (PMS) is the primary source of energy for 95% of them. The nature and condition of the fuel in use are the top-ranked components of transport operations contributing to GHG emissions. The result of the ANOVA revealed a significant variation among the components of transport operations contributing to GHG emissions (F = 28.302, p = 0.000<0.05). Meanwhile, the linear regression results indicate that vehicular GHG emissions have a significant impact on the local climate (F1⁄578=30.091, p=0.000<0.05). Traffic congestion and bad road conditions were the top-ranked transport externalities contributing to the changing local climate. The most common effects of GHG emissions on human health were headaches and difficulty breathing. Considering these findings, this study suggests the best tactics to lessen the effects of GHG emissions from transport operations, which adversely affect the local climate and human health in the study area.

Cooling wisdom of ‘water towns’: How urban river networks can shape city climate?

‘Water town’, a city design idea featuring buildings sitting along rivers and their associated riparian vegetation, serves as natural refuges for citizens to escape the dual challenges of heatwaves and urban heat islands. We investigated the multi-scale cooling effect of river networks in Shanghai, a typical modern city widely known as an assemblage of water towns. At the neighborhood scale, we conducted a series of field experiments along various rivers with different characteristics during the 2022 heatwave periods in central Shanghai. At the city scale, we first quantified the cooling impact of urban river networks by integrating remotely sensed data and fine-resolution urban river network maps. We found that the width of rivers, coverage ratio, density, and morphology of river networks are the key factors affecting the cooling potential. The confluence or proximity of river tributaries can also bring an enhanced cooling effect than standalone ones. Rivers were found to be all-day cool spots compared to adjacent city streets, with greater daytime cooling intensity (1–3 °C) than at night (0–0.6 °C). Compared to vegetation which has more spatial coverage within the city, rivers are constrained by a linear shape along certain paths but possess the ability to flow, which is beneficial for cooling by carrying cool water from upstream parks and offering wind corridors. The atmospheric cooling capability of 20% of river coverage is equivalent to 30% of tree canopy coverage in a neighborhood. The city-scale cooling effect yields a 36.9% cooling area with a maximum cooling extent of 5.5 °C. The disparities in cooling effect between river networks and standalone rivers primarily manifest in confluence areas and the reinforced cooling within dense river networks. Each additional confluence in local river networks leads to a mean increase of 3% in cooling area and 0.01 °C cooling intensity. Our study implies that urban watercourses cannot be neglected in urban climatic studies and should be incorporated into a new conceptualization of water-included urban local climate zone classifications in the world urban database.

Cool walkability planning: Providing pedestrian thermal comfort in hot climate cities

Global warming and urbanization are increasing the number of people living in cities that experience extreme heat. This makes walking uncomfortable, unattractive, and unhealthy and causes travelers to drive for trips that could be made on foot. To address these problems hot-climate cities can create networks of shadeways (shaded sidewalks) and pedways (enclosed, climate-controlled walkways). This article introduces the Cool Walkshed Index (CWI) which rates pedestrian thermal protection from A (best) to F (worst). Currently, most urban neighborhoods have CWI E (incomplete sidewalk networks) or D (complete sidewalk networks). Moderate-heat cities should aspire to CWI C (shaded sidewalks on busy routes); high-heat cities, with temperatures that frequently exceed 38 °C (100 °F) should aspire to CWI B (most buildings located within 300 m of enclosed, climate-controlled pedways); and extreme-heat cities, with temperatures that frequently exceed 43 °C (110° F) should aspire to CWI A (most buildings are located less than 100 m of enclosed, climate-controlled pedways). Analysis in this study indicates that the additional costs of these facilities can be repaid many times over through road, parking, and vehicle savings, and increased local property values.

Reconsidering Seasonality, Weather, and Road Safety in Non-temperate Areas: the Case of Kaohsiung, Taiwan

Various weather conditions, ranging from heavy rain, and gusts, to extreme heat, can influence road injury frequency through impacting driver behavior, with potentially increasing impacts in the context of a changing climate. Existing studies often used traditional season categories (e.g., four seasons) to stratify regression models, isolating certain weather effects on road injury frequency. However, this approach falls short in characterizing non-temperate climate regions, where traditional seasons may not apply. For instance, tropical summers often involve rainfall and carry different meteorological implications than the traditional definition of summer, which can have unique effects on road injury frequency. To this end, this study aims to investigate the varying levels and directions of weather effects on road injury frequency given different prevailing climatic conditions, with a particular geographic emphasis on non-temperate areas by using Kaohsiung, a tropical monsoon climate city, as the study area. This study first employed principal component analysis and cluster analysis to reveal the underlying climatic patterns unique to Kaohsiung in a data-driven manner. Subsequently, this study analyzed and compared the weather effects on road injury frequency across different climatic patterns. The findings show that adverse weather conditions, including heavy rainfall, sub-optimal temperatures, and strong wind, contribute to increased road injury frequency, especially in congested weekday traffic. Moreover, these weather effects on road injury frequency can vary in both magnitude and direction depending on the prevailing seasonal conditions. This echoes previous research findings regarding the effects of rainfall and temperatures while also shedding light on the understudied impact of wind. Based on these findings, this study confirms the effectiveness of integrating data-driven techniques and highlights practical policy implications concerning weather effects on road injury frequency. Further work should delve deeper into specific behavioral mechanisms through which weather factors influence road injury frequency given certain climatic conditions.

Applications of the Digital Mapping System (DMS) and the Influence on Climate Change

Recent years have seen a rapid change in climate, which has led to an increase in the number of severe weather-related disasters. The management, on the other hand, has not provided a solution that is adequate to the question of how to avert similar calamities. Because planners, designers, and those in charge of making decisions lack essential meteorological expertise and data, there is currently insufficient consideration given to the influence that DMS will have on the climate. As a direct result of increasing urbanisation, the rate at which climate change is occurring is accelerating, which means that the significance of this problem is growing. The city virtual map system has the potential to serve as a convergence point for virtual and climate systems, which will make it easier to find solutions to problems. The significance of DMS is analysed, and data-driven recommendations are offered based on the obtained meteorological data and after taking into consideration the effects of climate, population, and greening. This article starts with a brief overview of how the city's climate has changed recently. Next, the purpose of the urban climate map is explained, followed by a list of relevant pros and cons based on the relevant characteristics and a discussion of how DMS could be used in real-world situations.

An Artificial Intelligence‐Based Framework to Accelerate Data‐Driven Policies to Promote Solar Photovoltaics in Lisbon

Due to the unavailability of up‐to‐date and georeferenced information about Lisbon's existing solar energy systems, tracking the progress of solar energy in relation to the city's Climate Action Plans 2030 is a complex task, thus hindering the potential of data‐driven decision‐making for a targeted implementation of photovoltaics (PV) in buildings and urban infrastructure. To overcome the challenges posed, an integrated approach to accelerate policy‐making based on artificial intelligence (AI) resources and local citizens' and stakeholders' participation is developed and piloted in Lisbon. Recurring to a two‐step AI model setup to identify and geolocate PV systems, key policy indicators are calculated to inform policy‐makers about the evolution of PV deployment in the city and contribute to tailor future incentives to more depressed or energy poor districts. The AI model based on open data orthophotos from 2016 allowed estimates for the installed peak power at the city level, in that year, to be delivered in a few minutes, whereas manual inspection of aerial images will have taken several months. Although the PV capacity determined is 30% lower than the historical official numbers, the proof of concept for the proposed framework is achieved and validated by local stakeholders.

Machine Learning Techniques for Prediction of Climate Change in Nagpur using various Optimized Models

The Global temperatures are being affected by climate change. Nagpur's climate is a mix of wet and dry conditions. In the summer, the city experiences the driest weather. Because the city is approaching the extreme situation of climate change, it is vital to check the city's climate change parameters. In this study, we look at machine learning methods for predicting the climate, specifically the temperature factor for Nagpur. Three algorithms are discussed ,compare and contrast the Logistic Regression model, the Random Forest Classifier model, and the Auto Regressive approach model to find the optimum model for our prediction needs.

Long-term performance of roof-top GCPV systems in central Viet Nam

In pursuit of the objective of achieving "net zero emissions," many countries worldwide, including Viet Nam, have prioritized the utilization of photovoltaic technology for energy conversion. Specifically, the implementation of roof-top grid-connected photovoltaic systems (GCPV) has emerged as a highly efficient solution in urban areas. These systems offer several advantages, such as minimizing land usage, lowering monthly electricity expenses, preventing building heat, generating income for households, and reducing transmission and distribution costs. This article focuses on a comprehensive long-term analysis conducted on 51 roof-top GCPV systems in the tropical monsoon climate of Hue City, Viet Nam, during the period from 2019 to 2023. The analysis findings reveal that roof-top GCPV systems with a capacity of 3-6 kW are well-suited for households in the central region of Viet Nam, characterized by a tropical monsoon climate. These systems exhibit an average sizing ratio of 1.03. The annual average daily final yield peaked at 3.28 kWh/kWp/day in 2021 and reached its lowest point at 2.97 kWh/kWp/day in 2022. Notably, the typical slope of the yield gradually increases with the installed capacity and the studied year. Furthermore, the monthly average daily final yield demonstrates a seasonal pattern, with higher yields observed from March to August and lower yields from September to January, aligning with the climate of the study area. As the years progress, the capacity factor and performance ratio of roof-top GCPV systems display a declining trend. Throughout the entire study period, these systems successfully mitigated 664 metric tons of CO2 emissions. The evaluation of long-term yield data offers valuable insights for photovoltaic installers, operators, and system owners, aiding in system maintenance and optimizing load utilization across different time periods. Long-term performance can be used by energy managers and owners of roof-top GCPV systems to identify supply shortfalls and initiate countermeasures.