State of mind in adolescents in Barcelona province (Spain): evolution, associated factors and impact of the pandemic

BACKGROUND: To analyse the evolution of state of mind in adolescents in the province of Barcelona for the last six years and the specific impact of the pandemic and its experience. Likewise, analyse the associated factors both in pre-pandemic period and during. METHODS: Since 2015/2016 a Questionnaire on health related habits was carried out among 4th year high school students to which a COVID-19 chapter was added in the 2020/2021 academic year. There was a representative provincial pre-pandemic sample (N=15,118) and a sample during the pandemic (N=4,966). The dichotomous aggregate variable of positive/negative state of mind was constructed with six specific items to which the bivariate analyses and a multivariate generalized mixed linear model were carried out for both periods. Analysis performed with SAS. RESULTS: The pandemic significantly intensified the trend of worsening the state of mind adolescents, and widened the gender gap. Boys went from 17.9% (pre-pandemic) to 25.7% (during pandemic) with a negative mood, while girls from 31.9% to 52.9%. In modelling during pandemic, socioeconomic and family factors appeared relevant and significant. Sex, perceived poor health, being victim of harassment, self-perception of weight, excessive use of the internet and a poor perception of the residential environment remained significant as in the pre-pandemic model. CONCLUSIONS: The specific negative impact of the pandemic on adolescents' mental well-being is perceived, but it is too early to tell whether it is reversible or not and to assess the effectiveness of interventions to tackle it.

Effective Screening and Texture Segmentation of Green Vegetation Cover Based on UAV Images

As an important part of the ecosystem, green vegetation coverage is crucial to people's sensory and mental health. Using reliable data sets to classify and identify the green vegetation cover on the land surface and explore its spatial distribution law can provide important reference for the work of regional ecosystem managers and urban planners. The optimization of effective screening methods for green vegetation coverage areas is an important requirement to measure the surface vegetation status. UAV aerial images feature high definition, large scale, small area and high up-to-dateness. However, at present, there are few studies based on the reliable UAV aerial image system to identify green vegetation cover and further explore its spatial changes. In this study, 701 residential neighborhoods in Beijing were taken as the research objects, and the green vegetation of 7,695 sample points was identified by UAV. The green vegetation coverage was measured, and the spatial distribution pattern of green vegetation in different land surface areas was quantitatively compared. The results show that the image processing method proposed in this paper can effectively detect the boundary of green vegetation cover area from UAV aerial images, the correlation of texture segmentation is good, and the segmentation performance is better than other methods. The distribution of green vegetation cover in the research target area is uneven, with 63.79% of the research area having relatively low (Level 2) and medium (Level 3) green vegetation coverage, which indicates that the green vegetation coverage area in the research area is insufficient to meet the needs of regional ecosystem development. The characteristics of green vegetation cover in 16 districts in the study area are different, showing different spatial distribution patterns;except Xicheng District, there are 211 points without landscape in the area covered by green vegetation in 15 districts. The results can provide support for urban land surface planning and management.

Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx (NOx = NO + NO2) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s-1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s-1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory.Weekly variations in NO2 emission are highly related to anthropogenic activities, such as the transport sector. The NO2 emissions were reduced by 16 % at weekends in Riyadh, and high reductions were found near the city center and in areas along the highway. An average weekend reduction estimate of 28 % was found in Madrid. The regions with dominant sources are located in the east of Madrid, where residential areas and the Madrid-Barajas airport are located. Additionally, due to the COVID-19 lockdowns, the NO2 emissions decreased by 21 % in March–June 2020 in Riyadh compared with the same period in 2019. A much higher reduction (62 %) is estimated for Madrid, where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas, and they cover smaller areas on weekdays compared with weekends. The spatial patterns of NO2 emission strengths during lockdown are similar to those observed at weekends in both cities. Although our analysis is limited to two cities as test examples, the method has proven to provide reliable and consistent results. It is expected to be suitable for other trace gases and other target regions. However, it might become challenging in some areas with complicated emission sources and topography, and specific NO2 decay times in different regions and seasons should be taken into account. These impacting factors should be considered in the future model to further reduce the uncertainty budget.

Effect of Replacing Feldspar by Philippine Black Cinder on the Development of Low-Porosity Red Stoneware

Stoneware is a ceramic material with low porosity and high mechanical properties, such as the modulus of rupture. It is essentially made of clay, feldspar and quartz and is sintered to create a mixture of glass and crystalline phases. With the projected growth rate of the global ceramics market size and the country's development plan for 2023–2028, it is imperative that alternative raw materials for the manufacture of ceramic products be sourced so that the importation of these materials, such as feldspar, be minimized, if not eliminated. Cinder in the Philippines is mainly used as a filling material in pavements and residential areas. In this study, this resource is utilized as partial and full replacement of feldspar in a typical ternary diagram for stoneware production. Bars were formed from different formulations by the slip casting method and were sintered at 1200 °C. Physical and mechanical properties of the bars, such as shrinkage, loss on ignition, water absorption, apparent porosity and modulus of rupture were determined. Thermo-physical analyses were also carried out on the raw materials and on formulated powders. Meeting the requirements of the various quality standards for ceramics, the partial replacement of feldspar with black cinder (LF, LFBQ and LFBH) is feasible for wall and roof applications while full replacement of feldspar with black cinder (LB) is suitable for wider use as wall, floor, vitrified, industrial and roof tiles.

Spatial Identification, Prevention and Control of Epidemics in High-Rise Residential Areas Based on Wind Environments

The wind environment in residential areas can exert a direct or indirect influence on the spread of epidemics, with some scholars paying particular attention to the epidemic prevention and control of residential areas from the perspective of wind environments. As a result, it is urgent to re-examine the epidemic prevention response of residential spaces. Taking high-rise residential areas in Xi'an as an example, the article defines the air flow field area based on on-site wind environment measurements, crowd behavior annotation, and CFD simulation. Using the double-effect superposition of crowd behavior and risk space, the paper undertook a multiple identification strategy of epidemic prevention space. The identification methods and management and control strategies of epidemic prevention in high-rise residential areas are proposed. Additionally, the living environment of residential areas is optimized, and a healthy residential space is created. The transformation from concept and calls for action to space implementation is made to provide a reference for improving the space management and control capabilities in high-rise residential areas in China. The results of this study can be used as a guideline for future residential planning and design from the perspective of preventing airborne diseases.

Effects of emission sources on the particle number size distribution of ambient air in the residential area

Particle size distribution is a major factor in the health and climate effects of ambient aerosols, and it shows a large variation depending on the prevailing atmospheric emission sources. In this work, the particle number size distributions of ambient air were investigated at a suburban detached housing area in northern Helsinki, Finland, during a half-year period from winter to summer of 2020. The measurements were conducted with a scanning mobility particle sizer (SMPS) with a particle size range of 16–698 nm (mobility diameter), and the events with a dominant particle source were identified systematically from the data based on the time of the day and different particle physical and chemical properties. During the measurement period, four different types of events with a dominant contribution from either wood-burning (WB), traffic (TRA), secondary biogenic (BIO), or long-range transported (LRT) aerosol were observed. The particle size was the largest for the LRT events followed by BIO, WB, and TRA events with the geometric mean diameters of 72, 62, 57, and 41 nm, respectively. BIO and LRT produced the largest particle mode sizes followed by WB, and TRA with the modes of 69, 69, 46, and 25 nm, respectively. Each event type had also a noticeably different shape of the average number size distribution (NSD). In addition to the evaluation of NSDs representing different particle sources, also the effects of COVID-19 lockdown on specific aerosol properties were studied as during the measurement period the COVID-19 restrictions took place greatly reducing the traffic volumes in the Helsinki area in the spring of 2020. These restrictions had a significant contribution to reducing the concentrations of NOx and black carbon originating from fossil fuel combustion concentration, but insignificant effects on other studied variables such as number concentration and size distribution or particle mass concentrations (PM1, PM2.5, or PM10). © 2022 The Authors

COVID-19 in full inpatient care facillities - a never ending story?

Since March 2020, the corona pandemic has consistently exposed the weaknesses of the inpatient care system at the expense of those in need of case. No population group in Germany died more frequently as a result of corona-related infections (outbreaks) than residents of inpatient care facilities. By the end of March 2022. nearly 60% of Munich nursing home residents had become nosocomially infected with COVID-19, of which 18% died COVID-19 associated. Inadequate hygiene measures in the facilities could not and still cannot prevent large outbreaks. Because nursing facilities were not previously required to have hygienic staff, the Munich Health Department conducted standardized inspections and consultations during outbreaks. In almost no facility was a professionally correct outbreak management implemented. In addition, numerous hygiene deficiencies were identified that favored the transmission of SARS-CoV-2 infections to third parties. Furthermore, it became apparent that despite years of professional advice to the nursing facilities, no lasting positive effect on their hygiene management could be achieved. There are several reasons for this: a very high staff turnover, a low ratio of skilled workers, and a lack of commitment on the part of the facilities to a structured hygiene management system. Due to the continuing risk to the vulnerable population group in full inpatient care facilities, there is a fundamental need for regulation of binding hygiene management in these facilities - also with regard to risks from outbreaks with other pathogens. This was met by the legislature in September 2022 with an amendment to the Infection Protection Act. However, the theory-practice transfer required for functioning hygiene management can only succeed if sufficient numbers of professionally qualified staff with knowledge of German are available in the facilities to care for those in need of care.

A machine learning approach to address air quality changes during the COVID-19 lockdown in Buenos Aires, Argentina

Having a prediction model for air quality at a low computational cost can be useful for research, forecasting, regulatory, and monitoring applications. This is of particular importance for Latin America, where rapid urbanization has imposed increasing stress on the air quality of almost all cities. In recent years, machine learning techniques have been increasingly accepted as a useful tool for air quality forecasting. Out of these, random forest has proven to be an approach that is both well-performing and computationally efficient while still providing key components reflecting the nonlinear relationships among emissions, chemical reactions, and meteorological effects. In this work, we employed the random forest methodology to build and test a forecasting model for the city of Buenos Aires. We used this model to study the deep decline in most pollutants during the lockdown imposed by the COVID-19 (COronaVIrus Disease 2019) pandemic by analyzing the effects of the change in emissions, while taking into account the changes in the meteorology, using two different approaches. First, we built random forest models trained with the data from before the beginning of the lockdown periods. We used the data to make predictions of the business-as-usual scenario during the lockdown periods and estimated the changes in concentrations by comparing the model results with the observations. This allowed us to assess the combined effects of the particular weather conditions and the reduction in emissions during the period when restrictions were in place. Second, we used random forest with meteorological normalization to compare the observational data from the lockdown periods with the data from the same dates in 2019, thus decoupling the effects of the meteorology from short-term emission changes. This allowed us to analyze the general effect that restrictions similar to those imposed during the pandemic could have on pollutant concentrations, and this information could be useful to design mitigation strategies.The results during testing showed that the model captured the observed hourly variations and the diurnal cycles of these pollutants with a normalized mean bias of less than 6 % and Pearson correlation coefficients of the diurnal variations between 0.64 and 0.91 for all the pollutants considered. Based on the random forest results, we estimated that the lockdown implied relative changes in concentration of up to -45% for CO, -75% for NO, -46% for NO2, -12% for SO2, and -33% for PM10 during the strictest mobility restrictions. O3 had a positive relative change in concentration (up to an 80 %) that is consistent with the response in a volatile-organic-compound-limited chemical regime to the decline in NOx emissions. The relative changes estimated using the meteorological normalization technique show mostly smaller changes than those obtained by the random forest predictive model. The relative changes were up to -26% for CO, up to -47% for NO, -36% for NO2, -20% for PM10, and up to 27 % for O3. SO2 is the only species that had a larger relative change when the meteorology was normalized (up to 20 %). This points out the need for accounting not only for differences in emissions but also in meteorological variables in order to evaluate the lockdown effects on air quality. The findings of this study may be valuable for formulating emission control strategies that do not disregard their implication on secondary pollutants. We believe that the model itself can also be a valuable contribution to a forecasting system in the city and that the general methodology could also be easily applied to other Latin American cities as well. We also provide the first O3 and SO2 observational dataset in more that a decade for a residential area in Buenos Aires, and it is openly available at 10.17632/h9y4hb8sf8.1 .

Rethinking the influence of the Intelligent Building Systems on productivity, health, and well-being for enhancing the quality of life during mandatory working from home: Lessons learned from the COVID-19 pandemic

In the light of the recent global phenomena of the COVID-19 pandemic, there become evident changes in the habits and digital services usage in daily life. At this juncture, working from home (WFH) which is highly in need of Information and Communication Technologies (ICT) support for work productivity and occupant well-being, has recently become a popular and almost mandatory way of working due to lockdowns all around the world. The fact remains that providing a better quality of working-life has a potential for using intelligent building technologies that lead to the rapid advancement in global information services when such crises arise. Buildings that integrated with the systems based on intelligent technologies aim to enhance the productivity and well-being flexibly to meet the changing requirements of occupants. Therefore, this study focuses on the mandatory WFH concept emerged during COVID-19 pandemic, and in this context the need for the intelligent building systems in residential buildings. The findings of this study would form a pathway for rethinking the influence of the intelligent building systems (IBSs) into the prevention of health issues that we faced during mandatory WFH.

Utilizing Google Street View for Rapid Seismic Vulnerability Assessment: Case Study in the City of Manila, Philippines

Earthquake Impact Reduction Study for Metro Manila (MMEIRS) estimated that around 40% of the total number of residential buildings within Metro Manila will either collapse or be affected by the M7.2 generated by the West Valley Fault. Need arises to evaluate the seismic vulnerability of structures in the area to enhance the city’s resilience to seismic hazards. Rapid seismic vulnerability assessments are typically conducted by means of sidewalk surveys. However, advances in digital technologies such as Google Street View (GSV) provide the potential to do remote assessments, particularly amid mobility restrictions brought about by the COVID-19 pandemic. This paper aims to demonstrate the usefulness of GSV in collecting data needed for rapid seismic vulnerability assessments through the case of buildings in the City of Manila. Six 300 m x 300 m blocks were evaluated using GSV for identifying seismic-related building parameters. Results show the ease of use of GSV in data collection on areas encompassing commercial and residential zones within the city and poses difficulty for blocks dominated by informal settlements. Among the challenges observed in formal zones include blockages in views due to fences, trees, and/or vehicles parked in front. For informal settlements, much of the buildings are not visible in GSV for evaluation thereby necessitating supplemental data collection. Overall, GSV demonstrates usefulness, and has the potential to speed up seismic vulnerability assessments in urban areas in conjunction with existing in situ assessments currently conducted.

Analysis on drinking water use change by COVID-19: a case study of residential area in S-city, South Korea

The COVID-19 started to spread at early 2020 in South Korea and has been threatening our life in many aspects. Countermeasures such as social distancing to prevent COVID-19 spread have brought many changes in our society an human life. In this study, as a part of the COVID-19 pandemic management, drinking water usage change is analyzed to evaluate potential risks on water supply service. We collected hourly water use data of residential area in S city, which is a mid-size city in South Korea, before and after the COVID-19 pandemic. The collected data were analyzed to reveal the changes in total water consumption, water usage weight, and hourly water-demand pattern caused by the COVID-19 pandemic. The case study revealed the noticeable changes in water consumption caused by the COVID-19 pandemic and required more secured and adaptive operation of drinking water system under the pandemic situation caused by infectious disease.

IMPACT OF LIFESTYLE CHANGES DURING COVID-19 PANDEMIC ON ELECTRICITY DEMAND IN DETACHED HOUSES (PART 2) : ANALYSIS BY HOUSEHOLD IN THE WINTER OF 2021 AND CONSIDERATION OF RENEWABLE ENERGY SELF-CONSUMPTION

This paper focused on the impact of lifestyle changes in response to the novel coronavirus infection (COVID-19) on the electricity demand of 1339 detached houses from October 2020 to March 2021. Analyzing with the lifestyle questionnaire survey, twelve months after the first state of emergency for COVID-19 at April 2020, “working from home” was the only factor that increased household power consumption for 11% and the other factors were gone. Space heating power consumption in this period did not increase significantly. Lifestyle changes have affected household timely electricity demand and increased self-consumption of renewable energy of photovoltaic power generation systems.

Urban Heat Island Mitigation Strategy based on Local Climate Zone Classification using Landsat 8 satellite imagery

Appropriate strategies on urban climate mitigation should be formulated by considering the physical morphology of the urban landscape. This study aimed to investigate, analyze, and promote possible strategies to mitigate Jakarta’s urban heat island (UHI) phenomena. Jakarta’s local climate zone (LCZ) was classified into 17 classes using Landsat 8 data and the random forest method. Land surface temperature (LST) characteristic in each LCZ class was analyzed from 2018, 2019 and 2020. The result revealed that most of the local climate zone in Jakarta is dominated by LCZ 6 (open low-rise) and LCZ 3 (compact low-rise), which is the typical residential area in Jakarta. However, the mean LST in 2018, 2019 and 2020 showed that LCZ 3 (compact low-rise) and LCZ 7 (lightweight low-rise) are the areas that were most likely causing high surface temperature with the highest UHI intensity. During the COVID-19 pandemic in 2020, LST in Jakarta decreased drastically in some parts of the area, especially in public facility such as airport. However, the LST value in low-rise areas (LCZ 3 and LCZ 7) remains higher than the other LCZ classes. Materials of the building and land cover play a significant role in raising the land surface temperature. Therefore, mitigation strategies for urban heat islands in Jakarta should be focused on such particular areas mentioned.

Residential Refrigeration MEPS in Colombia: A Review and a Comparative Analysis

This paper addresses the energy efficiency issue in household appliances, which has led to the establishment of policies at a global level in favor of setting minimum energy performance standards (MEPS), which guarantee end users are able to select more efficient equipment. The countries of the United States, Brazil, Mexico, Chile, and the Community of the European Union were taken as references to review their policies and implementation strategies, in order to be compared with the Colombian panorama (at the market, technical and political levels). This allows the establishment of common aspects and differences related to the determination of energy consumption, adjusted volume, and formalization of efficiency ranges, and in the specific case of domestic refrigeration. Managing to distinguish the most relevant aspects for the successful adoption of these policies in Colombia. It is evident that the implementation of these guidelines has a positive impact on the market of the countries and communities of reference. Similarly, the MEPS are shown as a mechanism to regulate energy consumption in the residential sector.

Methods of Construction to the Meet Housing Crisis in the UK Residential Sector: A Comparative Study between Timber Frame and Masonry Construction

Major efforts have been invested in the UK Residential sector to meet the increasing housing demands, deliver sustainability, and improve its resiliency against many uncertainties. While data/information within the UK residential sector relating to location, sizes and volumes are annually updated, there is limited emphasis on the methods of construction that support meeting housing demands. Over the years, it has been recognised that the UK residential sector has been dominated by two methods of construction: timber frame and masonry. This study aims to holistically compare timber frames with masonry as the two domineering construction methods for the UK residential sector. The comparison will be based on build costs, preference and drivers by construction professionals, longevity and consumer confidence, and sustainability. The research methodology was developed based on applying mixed methods of quantitative data analysis of build costs and qualitative data assessment of semi-structured interviews. The findings showed that, from a build cost perspective, masonry methods of construction are a more cost-effective choice with major variation in material cost. However, although the masonry method of construction was more favoured, in many respects, small-in-size developers show more tendency to timber frames, as this is being rationalised by meeting sustainability targets. Practical implications show that the future of the residential sector in meeting the housing demands would heavily depend on Modern Methods of Construction (MMC), as it offers a more optimised mechanism;however, the uptake of this is considerably low. Future studies will enquire into pillars to make MMC efficient in the UK residential sector.

Impacts of Air Pollution and Dampness on Occupant Respiratory Health in Unplanned Houses: A Case Study of Bandung, Indonesia

This paper presents the results from field measurements and household surveys on the severity of indoor mold risk and its impact on respiratory health in a typical unplanned neighborhood of kampungs in Bandung, Indonesia. Mold risk was investigated using fungal risk detectors (n = 102), while air pollution levels were established with total suspended particulate (TSP) and particulate matter (PM2.5) (n = 38). The self-reported prevalence of respiratory diseases was obtained using a questionnaire form (ATS-DLD-78) (n = 599). The results showed that respiratory health problems were higher in the rainy season, particularly among children. Most houses suffered from severe mold risk, primarily due to extreme humid weather conditions, especially during rainy season (97%) where water leakage was prevalent (60%). In addition, the TSP and PM2.5 concentrations exceeded the WHO standards in most kampung houses, where around 58% of the houses recorded higher outdoor mean PM2.5 concentrations than indoors. Further, the path analysis showed that allergies followed by humidity rate and smell, which were affected by window-opening duration, directly impacted children’s respiratory health. Smoking behavior and building-related health problems, due to exposure to outdoor air pollution, affected the respiratory health of those aged 15 years old and over.

A Sequential Multi-Staged Approach for Developing Digital One-Stop Shops to Support Energy Renovations of Residential Buildings

Buildings account for 40% of the European Union’s energy consumption. Deep energy renovation of residential buildings is key for decarbonization and energy poverty alleviation. However, renovation is occurring at far below the needed pace and depth. In this context, building renovation one-stop shops, which bring all project phases under one roof and provide advice, support, and finance to households, are highlighted as a promising solution. Nevertheless, this model is still absent or under-developed in most European countries and remains understudied in the scientific literature. Therefore, the present research goals are as follows: (i) to provide a critical review of emerging one-stop shop models;(ii) to streamline the deployment of building renovation digital one-stop shops by piloting a sequential multi-staged approach for Portuguese households and proposing it for replication elsewhere;and (iii) to compare case-study insights with other one-stop shops and discuss the notion in the context of the European Renovation Wave. In total, for the Portuguese case-study, five steps were conducted. The first three—stakeholder mapping, expert interviews, and customer journey—aimed to gather intel on the local energy renovation market. The results from these stages informed the design of the platform (fourth step). Finally, a post-launch market consultation survey gathered user feedback (fifth step). Insights from this study suggest that digital one-stop shops, while providing a helpful tool to close information gaps and activate specific audiences, may be insufficient on their own. As such, a more comprehensive set of instruments supporting households is needed to accelerate building renovation.

Optimum Trombe wall thickness in the Mediterranean Tunisian context: An energetic and economic study

Trombe walls figure among many passive devices used in the Mediterranean climate to minimize heating demands in residential buildings. The thickness of this massive wall is a critical parameter that influences the effectiveness of the system. Insufficient wall thickness conducts to an important interior temperature fluctuation, and huge wall thickness will increase costs and thermal resistance. In this paper, the optimum thickness of four different construction materials (concrete, stone, adobe, and brick), which can be used in the Trombe wall, was determined using an energetic and economic analysis. The energetic results with TRNSYS software show that the best materials, which can contribute to a reduction by 50% in heating loads of a single room, are stone and concrete. For the economic analysis, the life cycle cost and the payback period were calculated for each construction material. The results show that the optimum thickness for stone and concrete are, respectively, 34 and 32 cm with a payback period of 2.85 and 2.65 years.

Indoor air quality fuelling India's COVID-19 infection

Just as the smell gets diluted by ventilation, the dangerous concentration of the virus can also get reduced by ensuring appropriate amount of outdoor air flows in. In closed and stale space droplets and aerosol gets quickly concentrated and greatly increases the risk of transmission of virus in that area. Visit to any nearby shopping malls, newly furnished coaching classes, modern residential buildings, government offices, hotels, restaurants and even hospitals shows that they are nothing but an assortment of closed and unventilated spaces. These closed space acts as Super spreader of the virus. Peak test positive rate of 22.6% per hundred test is observed during the month of May, which is a result of high humidity particulate matter concentration temperature CO2 concentration.

Identification of Comfort Aspects of Architectural Students’ Residence for School from Home Activities

Covid 19 pandemic affected learning methods from offline to online. All parties involved in learning need to make various adaptations so that the learning process can run effectively. Students are required to focus on education at home (School from Home/SFH). The architectural learning method prioritizes practice in designing called Studio Class. It causes problems when it comes to changing the learning method online. Place of residence also plays an essential role. When they are SFH, the students live in private houses, rented houses, and boarding houses. The purpose of this study is to determine whether characteristics of the learning room environment (thermal, lighting, and audial) in the living space have a major impact on the success of SFH learning. This study employs quantitative research to ascertain the variables affecting environmental comfort through online questionnaire data. The thermal element is determined to have the greatest impact on overall comfort. Audial comfort is critical in breaking students’ concentration when performing studio exercises. In general, students who live in boarding houses do not feel disruption from surrounding noise, however students who live in private homes do.