Urban local air quality management framework for non-attainment areas in Indian cities

© 2017 Elsevier B.V. Increasing urban air pollution level in Indian cities is one of the major concerns for policy makers due to its impact on public health. The growth in population and increase in associated motorised road transport demand is one of the major causes of increasing air pollution in most urban areas along with other sources e.g., road dust, construction dust, biomass burning etc. The present study documents the development of an urban local air quality management (ULAQM) framework at urban hotspots (non-attainment area) and a pathway for the flow of information from goal setting to policy making. The ULAQM also includes assessment and management of air pollution episodic conditions at these hotspots, which currently available city/regional-scale air quality management plans do not address. The prediction of extreme pollutant concentrations using a hybrid model differentiates the ULAQM from other existing air quality management plans. The developed ULAQM framework has been applied and validated at one of the busiest traffic intersections in Delhi and Chennai cities. Various scenarios have been tested targeting the effective reductions in elevated levels of NOx and PM2.5 concentrations. The results indicate that a developed ULAQM framework is capable of providing an evidence-based graded action to reduce ambient pollution levels within the specified standard level at pre-identified locations. The ULAQM framework methodology is generalised and therefore can be applied to other non-attainment areas of the country

PM2.5-related health and economic loss assessment for 338 Chinese cities

China is in a critical stage of ambient air quality management after global attention on pollution in its cities. Industrial development and urbanization have led to alarming levels of air pollution with serious health hazards in densely populated cities. The quantification of cause-specific PM2.5-related health impacts and corresponding economic loss estimation is crucial for control policies on ambient PM2.5 levels. Based on ground-level direct measurements of PM2.5 concentrations in 338 Chinese cities for the year 2016, this study estimates cause-specific mortality using integrated exposure-response (IER) model, non-linear power law (NLP) model and log-linear (LL) model followed by morbidity assessment using log-linear model. The willingness to pay (WTP) and cost of illness (COI) methods have been used for PM2.5-attributed economic loss assessment. In 2016 in China, the annual PM2.5 concentration ranged between 10 and 157 μg/m3 and 78.79% of the total population was exposed to >35 μg/m3 PM2.5 concentration. Subsequently, the national PM2.5-attributable mortality was 0.964 (95% CI: 0.447, 1.355) million (LL: 1.258 million and NPL: 0.770 million), about 9.98% of total reported deaths in China. Additionally, the total respiratory disease and cardiovascular disease-specific hospital admission morbidity were 0.605 million and 0.364 million. Estimated chronic bronchitis, asthma and emergency hospital admission morbidity were 0.986, 1.0 and 0.117 million respectively. Simultaneously, the PM2.5 exposure caused the economic loss of 101.39 billion US$, which is 0.91% of the national GDP in 2016. This study, for the first time, highlights the discrepancies associated with the three commonly used methodologies applied for cause-specific mortality assessment. Mortality and morbidity results of this study would provide a measurable assessment of 338 cities to the provincial and national policymakers of China for intensifying their efforts on air quality improvement

Measuring perceived social sustainability of brands – A scale development

Consumer perceptions regarding a brand’s commitment to social sustainability is a crucial differentiator and contributes to brand equity. Despite the acknowledged importance, presently no measurement scale is available for measuring consumer Perceived Social Sustainability of Brands (PSSB). This study, therefore, attempts to develop and validate the PSSB scale. Results from two empirical studies were used to establish the psychometric properties of the PSSB scale. Findings reveal PSSB comprises of six underlying dimensions namely: supporting education, supporting community, supporting innovative growth, supporting poverty elimination, supporting healthy living, and supporting sustainable water management. Based on the empirical studies a final refined scale with 26 measurement items was developed after testing for reliability and validity. We also tested the predictive validity of the scale, which show that PSSB is a valid predictor of outcomes such as brand trust and brand image. PSSB scale is developed around SDGs (Sustainable Development Goals) to help managers measure, understand, and accordingly mainstream the brand’s social sustainability perceptions among their target consumers and potential markets

Analysis of various transport modes to evaluate personal exposure to PM2.5 pollution in Delhi

Access to detailed comparisons of the air quality variations encountered when commuting through a city offers the urban traveller more informed choice on how to minimise personal exposure to inhalable pollutants. In this study we report on an experiment designed to compare atmospheric contaminants, in this case, PM2.5 inhaled during rickshaw, bus, metro, non-air-conditioned car, air-conditioned (AC) car and walking journeys through the city of Delhi, India. The data collection was carried out using a portable TSI SidePak Aerosol Monitor AM520, during February 2018. The results demonstrate that rickshaws (266 ± 159 μg/m3) and walking (259 ± 102 μg/m3) modes were exposed to significantly higher mean PM2.5 levels, whereas AC cars (89 ± 30 μg/m3) and the metro (72 ± 11 μg/m3) had the lowest overall exposure rates. Buses (113 ± 14 μg/m3) and non-AC cars (149 ± 13 μg/m3) had average levels of exposure, but open windows and local factors caused surges in PM2.5 for both transport modes. Closed air-conditioned transport modes were shown to be the best modes for avoiding high concentrations of PM2.5, however other factors (e.g. time of the day, window open or closed in the vehicles) affected exposure levels significantly. Overall, the highest total respiratory deposition doses (RDDs) values were estimated as 84.7 ± 33.4 μg/km, 15.8 ± 9.5 μg/km and 9.7 ± 0.9 μg/km for walking, rickshaw and non-AC car transported mode of journey, respectively. Unless strong pollution control measures are taken, the high exposure to PM2.5 levels will continue causing serious short-term and long-term health concerns for the Delhi residents. Implementing integrated and intelligent transport systems and educating commuters on ways to reduce exposure levels and impacts on commuter's health are required

Design and preparation of a novel colon-targeted tablet of hydrocortisone

ABSTRACT The objective of this research was to design a new colon-targeted drug delivery system based on chitosan. The properties of the films were studied to obtain useful information about the possible applications of composite films. The composite films were used in a bilayer system to investigate their feasibility as coating materials. Tensile strength, swelling degree, solubility, biodegradation degree, Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC), Scanning Electron Microscope (SEM) investigations showed that the composite film was formed when chitosan and gelatin were reacted jointly. The results showed that a 6:4 blend ratio was the optimal chitosan/gelatin blend ratio. In vitro drug release results indicated that the Eudragit- and chitosan/gelatin-bilayer coating system prevented drug release in simulated intestinal fluid (SIF) and simulated gastric fluid (SGF). However, the drug release from a bilayer-coated tablet in SCF increased over time, and the drug was almost completely released after 24h. Overall, colon-targeted drug delivery was achieved by using a chitosan/gelatin complex film and a multilayer coating system

Identifying forest ecosystem regions for agricultural use and conservation

ABSTRACT Balancing agricultural needs with the need to protect biodiverse environments presents a challenge to forestry management. An imbalance in resource production and ecosystem regulation often leads to degradation or deforestation such as when excessive cultivation damages forest biodiversity. Lack of information on geospatial biodiversity may hamper forest ecosystems. In particular, this may be an issue in areas where there is a strong need to reassign land to food production. It is essential to identify and protect those parts of the forest that are key to its preservation. This paper presents a strategy for choosing suitable areas for agricultural management based on a geospatial variation of Shannon's vegetation diversity index (SHDI). This index offers a method for selecting areas with low levels of biodiversity and carbon stock accumulation ability, thereby reducing the negative environmental impact of converting forest land to agricultural use. The natural forest ecosystem of the controversial 1997 Ex-Mega Rice Project (EMRP) in Indonesia is used as an example. Results showed that the geospatial pattern of biodiversity can be accurately derived using kriging analysis and then effectively applied to the delineation of agricultural production areas using an ecological threshold of SHDI. A prediction model that integrates a number of species and families and average annual rainfall was developed by principal component regression (PCR) to obtain a geospatial distribution map of biodiversity. Species richness was found to be an appropriate indicator of SHDI and able to assist in the identification of areas for agricultural use and natural forest management

Active control of vibrations of a tall structure excited by external forces

This paper is concerned with active control of vibrations of tall structures subjected to strong wind or earth quake shocks using an active mass damper (AMD). A linear black box model of the systems is obtained from an experimental scale model of the structure. Two alternative control systems, and associated observers are designed and their performance assessed theoretically and experimentally

Personal exposure to fine particulate matter concentrations in central business district of a tropical coastal city

<p>In the present study, personal exposure to fine particulate matter (particulate matter with an aerodynamic diameter <2.5 μm [PM_2.5]) concentrations in an urban hotspot (central business district [CBD]) was investigated. The PM monitoring campaigns were carried out at an urban hotspot from June to October 2015. The personal exposure monitoring was performed during three different time periods, i.e., morning (8 a.m.−9 a.m.), afternoon (12.30 p.m.–1.30 p.m.), and evening (4 p.m.–5 p.m.), to cover both the peak and lean hour activities of the CBD. The median PM_2.5 concentrations were 38.1, 34.9, and 40.4 µg/m³ during the morning, afternoon, and evening hours on the weekends. During weekdays, the median PM_2.5 concentrations were 59.5, 29.6, and 36.6 µg/m³ in the morning, afternoon, and evening hours, respectively. It was observed that the combined effect of traffic emissions, complex land use, and micrometeorological conditions created localized air pollution hotspots. Furthermore, the total PM_2.5 lung dose levels for an exposure duration of 1 hr were 8.7 ± 5.7 and 12.3 ± 5.2 µg at CBD during weekends and weekdays, respectively, as compared with 2.5 ± 0.8 µg at the urban background (UB). This study emphasizes the need for mobile measurement for short-term personal exposure assessment complementing the fixed air quality monitoring.</p> <p><i>Implications</i>: Personal exposure monitoring at an urban hotspot indicated space and time variation in PM concentrations that is not captured by the fixed air quality monitoring networks. The short-term exposure to higher concentrations can have a significant impact on health that need to be considered for the health risk–based air quality management. The study emphasizes the need of hotspot-based monitoring complementing the already existing fixed air quality monitoring in urban areas. The personal exposure patterns at hotspots can provide additional insight into sustainable urban planning.</p

Impact of indoor heat load and natural ventilation on thermal comfort of radiant cooling system: An experimental study

Construction and operation of buildings are responsible for about 20% of the global energy consumption. The embodied energy of conventional buildings is high due to the utilization of energy-intensive construction materials and traditional construction methodology. Higher operational energy is attributed to the usage of power-consuming conventional air-conditioning systems. Therefore, moving to an energy-efficient cooling technology and eco-friendly building material can lead to significant energy savings and CO2 emission reduction. In the present study, an energy-efficient thermally activated building system (TABS) is integrated with glass fiber reinforced gypsum (GFRG), an eco-friendly building material. The proposed hybrid system is termed the thermally activated glass fiber reinforced gypsum (TAGFRG) system. This system is not only energy-efficient and eco-friendly but also provides better thermal comfort. An experimental room with a TAGFRG roof is constructed on the premises of the Indian Institute of Technology Madras (IITM), Chennai, located in a tropical wet and dry climate zone. The influence of indoor sensible heat load and the impact of natural ventilation on the thermal comfort of the TAGFRG system are investigated. An increase in internal heat load from 400 to 700 W deteriorates the thermal comfort of the indoor space. This is evident from the increases in operative temperatures from 29.8 to 31.5 °C and the predicted percentage of dissatisfaction from 44.5% to 80.9%. Natural ventilation increases the diurnal fluctuation of indoor air temperature by 1.6 and 1.9 °C for with and without cooling cases, respectively. It reduces the maximum indoor CO2 concentration from 912 to 393 ppm

Characteristics of tail pipe (Nitric oxide) and resuspended dust emissions from urban roads – A case study in Delhi city

Introduction: Personal exposure to elevated vehicle exhaust and non-exhaust emissions at urban roadside leads to carcinogenic health effects, respiratory illness and nervous system disorders. In this paper, an attempt has been made to investigate the exhaust and non-exhaust emissions emitted from selected roads in Delhi city. Methods: Based on the vehicular density per hour and speed, three categories of roads have been considered in the present study: (a) low density road (≤1000 vehicles/hour, V ≥ 10 m/s); (b) medium density road (>1000 vehicles/hour but ≤ 2000 vehicles/hour, V ≥ 7.5 m/s 2000 vehicles/hour, V < 7.5 m/s). At the selected roads, real-world exhaust emissions were measured using AVL DiTEST 1000 analyser. The silt load measurements were also carried out as per EPA AP-42 methodology at the selected roads. Results: Results indicated real-world NO exhaust emissions of 0.5 g/m3 (2.03 g/km) on high-density roads and 0.23 g/m3 (0.67 g/km) on low and medium density roads. These values were significantly higher than the Bharat Standard (BS) IV (0.25 g/km). The silt load on the different types of roads indicated 3, 25 and 44 g/m2 -day dust deposition on, low, medium and high-density road, respectively. PM2.5 and PM10 emission rates were measured using US-EPA AP-42 methodology and were found to be least at low-density roads with values of 0.54 and 2.22 g/VKT (VKT -Vehicle Kilometer Travelled) respectively, and highest for high density roads with values of 12.40 and 51.25 g/VKT respectively. Conclusion: The present study reveals that both tailpipe (exhaust) and resuspend able road dust (non-exhaust) emissions contributes significantly and deteriorates local air quality. Although there exists emission standards, but there are no enforced regulations for non-exhaust emissions (resuspension of road dust). Hence, there is need to regulate non-exhaust emissions on urban roads