In-kitchen aerosol exposure in twelve cities across the globe.

Poor ventilation and polluting cooking fuels in low-income homes cause high exposure, yet relevant global studies are limited. We assessed exposure to in-kitchen particulate matter (PM and PM) employing similar instrumentation in 60 low-income homes across 12 cities: Dhaka (Bangladesh); Chennai (India); Nanjing (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Akure (Nigeria); Blantyre (Malawi); Dar-es-Salaam (Tanzania) and Nairobi (Kenya). Exposure profiles of kitchen occupants showed that fuel, kitchen volume, cooking type and ventilation were the most prominent factors affecting in-kitchen exposure.

Potential health risks due to in-car aerosol exposure across ten global cities.

Car microenvironments significantly contribute to the daily pollution exposure of commuters, yet health and socioeconomic studies focused on in-car exposure are rare. This study aims to assess the relationship between air pollution levels and socioeconomic indicators (fuel prices, city-specific GDP, road density, the value of statistical life (VSL), health burden and economic losses resulting from exposure to fine particulate matter ≤2.5 µm; PM) during car journeys in ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania).

Chemical source profiles of fine particles for five different sources in Delhi.

Increasing emissions from sources such as construction and burning of biomass from crop residues, roadside and municipal solid waste have led to a rapid increase in the atmospheric concentrations of fine particulate matter (≤2.5 μm; PM) over many Indian cities. Analyses of their chemical profiles are important for receptor models to accurately estimate the contributions from different sources.

Regression-based flexible models for photochemical air pollutants in the national capital territory of megacity Delhi.

Modelling photochemical pollutants, such as ground level ozone (O), nitric oxide (NO) and nitrogen dioxide (NO), in urban terrain was proven to be cardinal, chronophagous and complex. We built linear regression and random forest regression models using 4-years (2015-2018; hourly-averaged) observations for forecasting O, NO and NO levels for two scenarios (1-month prediction (for January 2019) and 1-year prediction (for 2019)) - with and without the impact of meteorology. These flexible models have been developed for, both, localised (site-specific models) and combined (indicative of city-level) cases.

In-car particulate matter exposure across ten global cities.

Cars are a commuting lifeline worldwide, despite contributing significantly to air pollution. This is the first global assessment on air pollution exposure in cars across ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania). Portable laser particle counters were used to develop a proxy of car-user exposure profiles and analyse the factors affecting particulate matter ≤2.

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

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.

Effect of PM chemical constituents on atmospheric visibility impairment.

Unlabelled: PM sampling was conducted at a curbside location in Delhi city for summer and winter seasons, to evaluate the effect of PM and its chemical components on the visibility impairment. The PM concentrations were observed to be higher than the National Ambient Air Quality Standards (NAAQS), indicating poor air quality. The chemical constituents of PM (the water-soluble ionic species SO, NO, Cl, and NH, and carbonaceous species: organic carbon, elemental carbon) were analyzed to study their impact on visibility impairment by reconstructing the light extinction coefficient, b.

The influence of odd-even car trial on fine and coarse particles in Delhi.

The odd-even car trial scheme, which reduced car traffic between 08.00 and 20.00 h daily, was applied from 1 to 15 January 2016 (winter scheme, WS) and 15-30 April 2016 (summer scheme, SS).

Radiation safety aspects of the operation of first three synchrotron beam lines of Indus-2.

Five synchrotron radiation beam lines are commissioned and now under regular operation at the Synchrotron Radiation Source, Indus-2 at Raja Ramanna Centre For Advanced Technology (RRCAT), Indore, India. Nine beam lines are under trial operation, and six beam lines are in the installation stage. In the early phase of installation of beam lines on Indus-2, three bending magnet beam lines, Extended X-ray Absorption Fine Structure (EXAFS, BL-8), Energy Dispersive X-ray Diffraction (EDXRD, BL-11) and Angle Dispersive X-ray Diffraction (ADXRD, BL-12), were installed and commissioned, after approval from Atomic Energy Regulatory Board (AERB), India.

Organic matter determination for street dust in Delhi.

The organic matter of street dust is considered as one of the causes for high human mortality rate. To understand the association, the street dust samples were collected from four different localities (industrial, residential, residential-commercial, and commercial) situated in the greater Delhi area of India. The loss-on-ignition method was used to determine the organic matter (OM) content in street dust.

Indoor air quality modeling for PM 10, PM 2.5, and PM 1.0 in naturally ventilated classrooms of an urban Indian school building.

Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student's health and performance as they spend a substantial amount of their time (6-7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants' health.

Construction of fuzzy membership functions for urban vehicular exhaust emissions modeling.

This paper presents a method for constructing a membership function (MF) for the fuzzy sets that expert systems deal with. This paper introduces a Bezier curve-based mechanism for constructing MFs of convex normal fuzzy sets. The mechanism can fit any given data set with a minimum level of discrepancy.

Artificial neural network based carbon monoxide persistence models for episodic urban air quality management.

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November-March). The models have been developed for three 8-h groupings of 10 P.M.

Urban air quality in mega cities: a case study of Delhi City using vulnerability analysis.

Air pollution is one of the major environmental problems in India, affecting health of thousands of 'urban' residents residing in mega cities. The need of the day is to evolve an 'effective' and 'efficient' air quality management plan (AQMP) encompassing the essential 'key players' and 'stakeholders.' This paper describes the formulation of an AQMP for mega cities like Delhi in India taking into account the aforementioned key 'inputs.

Suspended particulate matter distribution in rural-industrial Satna and in urban-industrial South Delhi.

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM10), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns.