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Religious spaces are an integral part of Indian cities. Unique in their spatiality, they function as socio-cultural hubs drawing users from varied economic and social hierarchies. This study deals with physical and perceptional assessments of micrometeorological conditions in two religious squares namely Hanuman Mandir Square (HMS) and Gurudwara Bangla Sahib Square (GBS) located in New Delhi (28.6° N; 77.2° E), India. The study involved real-time physical measurement of environmental variables such as dry-bulb temperature (Ta, °C), globe temperature (Tg, °C), relative humidity (RH), and air velocity (Va). Variables such as physiological effective temperature (PET), universal thermal comfort index (UTCI), and mean radiant temperature (Tmrt, °C) were computed from measured variables. Concurrent thermal comfort surveys were carried out with 353 respondents in both the squares. The paper describes the thermal characteristics of the studied squares and presents the associated subjective thermal response and preferences of the users. PET was found to correlate well with the subjective responses. The neutral value of PET is found to be 24.7 °C. The neutral PET value of respondents visiting for non-worship purposes was found to be 2.7 °C lesser than those visiting for worship purposes. People visiting the squares for non-worship purpose however were found to be more tolerant of higher PET conditions as compared to others. Factors such as intent of visit, solar exposure, thermal history, and landscape elements were found to have a statistically significant influence on the thermal perception. The paper further summarizes the adaptive opportunities preferred by the users in order to improve thermal comfort in the studied squares. A weighted ranking of adaptive preferences reported by the respondents has also been presented. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents rigorous experimental outdoor performance of a 2.32kWP stand-alone photovoltaic (SAPV) system in New Delhi (India) for four weather types in each month such as clear, hazy, partially cloudy/foggy and fully cloudy/foggy weather conditions respectively. The daily power generated from the existing SAPV system was experimentally found in the range of 4–6kWh/day depending on the prevailing sky conditions. The number of days and daily power generated corresponding to four weather types in each month were used to determine monthly and subsequently annual power generation from the existing SAPV system. There are three daily load profiles with and without earth to air heat exchanger suitable for three seasons like summer (3.75–6.15kWh/day), winter (2.79–5.19kWh/day) and rainy (3.75kWh/day). The hourly efficiency of the SAPV system components are determined and presented in this paper. The life cycle cost (LCC) analysis for the existing typical SAPV system is carried out to determine unit cost of electricity. The effect of annual degradation rate of PV system efficiency is also presented in this paper. The energy production factor (EPF) and the energy payback time (EPBT) of the SAPV system was also determined and presented in this paper. [ABSTRACT FROM AUTHOR]

This Daylighting is one of the basic components of passive solar building design and its estimation is essential. In India there are a few available data of measured illuminance as in many regions of the world. The Indian climate is generally clear with overcast conditions prevailing through the months of July to September, which provides good potential to daylighting in buildings. Therefore, an analytical model that would encompass the weather conditions of New Delhi was selected. Hourly exterior horizontal and slope daylight availability has been estimated for New Delhi using daylight modeling techniques based on solar radiation data. A model to estimate interior illuminance was investigated and validated using experimental hourly inside illuminance data of an existing skylight integrated vault roof mud house in composite climate of New Delhi. The interior illuminance model was found in good agreement with experimental value of interior illuminance. [ABSTRACT FROM AUTHOR]

A comparative study was performed to evaluate the performance of the UK Met Office’s Global Seasonal (GloSea) prediction General Circulation Model (GCM) for the forecast of maximum surface air temperature (Tmax) over the Indian region using the model generated hindcast of 15-members ensemble for 16 years (1987–2002). Each hindcast starts from 1st January and extends for a period of six months in each year. The model hindcast Tmax is compared with Tmax obtained from verification analysis during the hot weather season on monthly and seasonal scales from March to June. The monthly and seasonal model hindcast climatology of Tmax from 240 members during March to June and the corresponding observed climatology show highly significant (above 99.9% level) correlation coefficients (CC) although the hindcast Tmax is over-estimated (warm bias) over most parts of the Indian region. At the station level over New Delhi, although the forecast error (forecast-observed) at the monthly scale gradually increases from March to June, the forecast error at the seasonal scale during March to May (MAM) is found to be just 1.67 °C. The GloSea model also simulates well Tmax anomalies on monthly and seasonal scales during March to June with the lower Root Mean Square Error (RMSE) of bias corrected forecast (less than 1.2 °C), which is much less than the corresponding RMSE of climatology (reference) forecast. The anomaly CCs (ACCs) over the station in New Delhi are also highly significant (above 95% level) on monthly to seasonal time scales from March to June, except for April. The skill of the GloSea model for the seasonal forecast of Tmax as measured from the ACC map and the bias corrected RMSE map is reasonably good during MAM and April to June (AMJ) with higher ACC (significant at 95% level) and lower RMSE (less than 1.5 °C) found over many parts of the Indian regions. [ABSTRACT FROM AUTHOR]