Lockdown Effects on Air Quality in Megacities During the First and Second Waves of COVID-19 Pandemic

Air pollution is among the highest contributors to mortality worldwide, especially in urban areas. During spring 2020, many countries enacted social distancing measures in order to slow down the ongoing COVID-19 pandemic. A particularly drastic measure, the “lockdown”, urged people to stay at home and thereby prevent new COVID-19 infections during the first (2020) and second wave (2021) of the pandemic. In turn, it also reduced traffic and industrial activities. But how much did these lockdown measures improve air quality in large cities, and are there differences in how air quality was affected? Here, we analyse data from two megacities: London as an example for Europe and Delhi as an example for Asia. We consider data during first and second-wave lockdowns and compare them to 2019 values. Overall, we find a reduction in almost all air pollutants with intriguing differences between the two cities except Delhi in 2021. In London, despite smaller average concentrations, we still observe high-pollutant states and an increased tendency towards extreme events (a higher kurtosis of the probability density during lockdown) during 2020 and low pollution levels during 2021. For Delhi, we observe a much stronger decrease in pollution concentrations, including high pollution states during 2020 and higher pollution levels in 2021. These results could help to design policies to improve long-term air quality in megacities.

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_2.5 and PM₁₀) 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. Different cuisines resulted in varying cooking durations and disproportional exposures. Occupants in Dhaka, Nanjing, Dar-es-Salaam and Nairobi spent > 40% of their cooking time frying (the highest particle emitting cooking activity) compared with ∼ 68% of time spent boiling/stewing in Cairo, Sulaymaniyah and Akure. The highest average PM_2.5 (PM₁₀) concentrations were in Dhaka 185 ± 48 (220 ± 58) μg m^-3 owing to small kitchen volume, extensive frying and prolonged cooking compared with the lowest in Medellín 10 ± 3 (14 ± 2) μg m^-3. Dual ventilation (mechanical and natural) in Chennai, Cairo and Sulaymaniyah reduced average in-kitchen PM_2.5 and PM₁₀ by 2.3- and 1.8-times compared with natural ventilation (open doors) in Addis Ababa, Dar-es-Salam and Nairobi. Using charcoal during cooking (Addis Ababa, Blantyre and Nairobi) increased PM_2.5 levels by 1.3- and 3.1-times compared with using natural gas (Nanjing, Medellin and Cairo) and LPG (Chennai, Sao Paulo and Sulaymaniyah), respectively. Smaller-volume kitchens (<15 m³; Dhaka and Nanjing) increased cooking exposure compared with their larger-volume counterparts (Medellin, Cairo and Sulaymaniyah). Potential exposure doses were highest for Asian, followed by African, Middle-eastern and South American homes. We recommend increased cooking exhaust extraction, cleaner fuels, awareness on improved cooking practices and minimising passive occupancy in kitchens to mitigate harmful cooking emissions.

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_2.5) 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). Data collected by portable laser particle counters were used to develop a proxy of car-user exposure profiles. Hotspots on all city routes displayed higher PM_2.5 concentrations and disproportionately high inhaled doses. For instance, the time spent at the hotspots in Guangzhou and Addis Ababa was 26% and 28% of total trip time, but corresponded to 54% and 56%, respectively, of the total PM_2.5 inhaled dose. With the exception of Guangzhou, all the cities showed a decrease in per cent length of hotspots with an increase in GDP and VSL. Exposure levels were independent of fuel prices in most cities. The largest health burden related to in-car PM_2.5 exposure was estimated for Dar-es-Salam (81.6 ± 39.3 μg m^-3), Blantyre (82.9 ± 44.0) and Dhaka (62.3 ± 32.0) with deaths per 100,000 of the car commuting population per year of 2.46 (2.28-2.63), 1.11 (0.97-1.26) and 1.10 (1.05-1.15), respectively. However, the modest health burden of 0.07 (0.06-0.08), 0.10 (0.09-0.12) and 0.02 (0.02-0.03) deaths per 100,000 of the car commuting population per year were estimated for Medellin (23 ± 13.7 μg m^-3), São Paulo (25.6 ± 11.7) and Sulaymaniyah (22.4 ± 15.0), respectively. Lower GDP was found to be associated with higher economic losses due to health burdens caused by air pollution in most cities, indicating a socioeconomic discrepancy. This assessment of health and socioeconomic parameters associated with in-car PM_2.5 exposure highlights the importance of implementing plausible solutions to make a positive impact on peoples' lives in these cities.

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_2.5) over many Indian cities. Analyses of their chemical profiles are important for receptor models to accurately estimate the contributions from different sources. We have developed chemical source profiles for five important pollutant sources - construction (CON), paved road dust (PRD), roadside biomass burning (RBB), solid waste burning (SWB), and crop residue burning (CPB) - during three intensive campaigns (winter, summer and post-monsoon) in and around Delhi. We obtained chemical characterisations of source profiles incorporating carbonaceous material such as organic carbon (OC) and elemental carbon (EC), water-soluble ions (F^-, Cl^-, NO₂^-, NO₃^-, SO₄^2-, PO₄^3-, Na⁺ and NH₄⁺), and elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Br, Rb, Sr, Ba, and Pb). CON was dominated by the most abundant elements, K, Si, Fe, Al, and Ca. PRD was also dominated by crustal elements, accounting for 91% of the total analysed elements. RBB, SWB and CPB profiles were dominated by organic matter, which accounted for 94%, 86.2% and 86% of the total PM_2.5, respectively. The database of PM emission profiles developed from the sources investigated can be used to assist source apportionment studies for accurate quantification of the causes of air pollution and hence assist governmental bodies in formulating relevant countermeasures.

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

Modelling photochemical pollutants, such as ground level ozone (O₃), nitric oxide (NO) and nitrogen dioxide (NO₂), 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 O₃, NO and NO₂ 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. Both models were aided with machine learning, to reduce their time-intensity compared to models built over high-performance computing. O₃ prediction performance of linear regression model at the city level, under both cases of meteorological consideration, was found to be significantly poor. However, the site-specific model with meteorology performed satisfactorily (r = 0.87; RK Puram site). Further, during testing, linear regression models (site-specific and combined) for NO and NO₂ with meteorology, show a slight improvement in their prediction accuracies when compared to the corresponding equivalent linear models without meteorology. Random forest regression with meteorology performed satisfactorily for indicative city-level NO (r = 0.90), NO₂ (r = 0.89) and O₃ (r = 0.85). In both regression techniques, increased uncertainty in modelling O₃ is attributed to it being a secondary pollutant, non-linear dependency on NO_x, VOCs, CO, radicals, and micro-climatic meteorological parameters. Analysis of importance among various precursors and meteorology have also been computed. The study holistically concludes that site-specific models with meteorology perform satisfactorily for both linear regression and random forest regression.

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 ≤2.5 μm (PM_2.5; fine fraction) and ≤10 μm (PM_2.5-10; coarse fraction). Measurements were carried out during morning, off- and evening-peak hours under windows-open and windows-closed (fan-on and recirculation) conditions on predefined routes. For all cities, PM_2.5 and PM₁₀ concentrations were highest during windows-open, followed by fan-on and recirculation. Compared with recirculation, PM_2.5 and PM₁₀ were higher by up to 589% (Blantyre) and 1020% (São Paulo), during windows-open and higher by up to 385% (São Paulo) and 390% (São Paulo) during fan-on, respectively. Coarse particles dominated the PM fraction during windows-open while fine particles dominated during fan-on and recirculation, indicating filter effectiveness in removing coarse particles and a need for filters that limit the ingress of fine particles. Spatial variation analysis during windows-open showed that pollution hotspots make up to a third of the total route-length. PM_2.5 exposure for windows-open during off-peak hours was 91% and 40% less than morning and evening peak hours, respectively. Across cities, determinants of relatively high personal exposure doses included lower car speeds, temporally longer journeys, and higher in-car concentrations. It was also concluded that car-users in the least affluent cities experienced disproportionately higher in-car PM_2.5 exposures. Cities were classified into three groups according to low, intermediate and high levels of PM exposure to car commuters, allowing to draw similarities and highlight best practices.

Health and economic impact of air pollution in the states of India: the Global Burden of Disease Study 2019

BACKGROUND

The association of air pollution with multiple adverse health outcomes is becoming well established, but its negative economic impact is less well appreciated. It is important to elucidate this impact for the states of India.

METHODS

We estimated exposure to ambient particulate matter pollution, household air pollution, and ambient ozone pollution, and their attributable deaths and disability-adjusted life-years in every state of India as part of the Global Burden of Disease Study (GBD) 2019. We estimated the economic impact of air pollution as the cost of lost output due to premature deaths and morbidity attributable to air pollution for every state of India, using the cost-of-illness method.

FINDINGS

1·67 million (95% uncertainty interval 1·42-1·92) deaths were attributable to air pollution in India in 2019, accounting for 17·8% (15·8-19·5) of the total deaths in the country. The majority of these deaths were from ambient particulate matter pollution (0·98 million [0·77-1·19]) and household air pollution (0·61 million [0·39-0·86]). The death rate due to household air pollution decreased by 64·2% (52·2-74·2) from 1990 to 2019, while that due to ambient particulate matter pollution increased by 115·3% (28·3-344·4) and that due to ambient ozone pollution increased by 139·2% (96·5-195·8). Lost output from premature deaths and morbidity attributable to air pollution accounted for economic losses of US$28·8 billion (21·4-37·4) and $8·0 billion (5·9-10·3), respectively, in India in 2019. This total loss of $36·8 billion (27·4-47·7) was 1·36% of India's gross domestic product (GDP). The economic loss as a proportion of the state GDP varied 3·2 times between the states, ranging from 0·67% (0·47-0·91) to 2·15% (1·60-2·77), and was highest in the low per-capita GDP states of Uttar Pradesh, Bihar, Rajasthan, Madhya Pradesh, and Chhattisgarh. Delhi had the highest per-capita economic loss due to air pollution, followed by Haryana in 2019, with 5·4 times variation across all states.

INTERPRETATION

The high burden of death and disease due to air pollution and its associated substantial adverse economic impact from loss of output could impede India's aspiration to be a $5 trillion economy by 2024. Successful reduction of air pollution in India through state-specific strategies would lead to substantial benefits for both the health of the population and the economy.

FUNDING

UN Environment Programme; Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.

Effect of PM2.5 chemical constituents on atmospheric visibility impairment

PM_2.5 sampling was conducted at a curbside location in Delhi city for summer and winter seasons, to evaluate the effect of PM_2.5 and its chemical components on the visibility impairment. The PM_2.5 concentrations were observed to be higher than the National Ambient Air Quality Standards (NAAQS), indicating poor air quality. The chemical constituents of PM_2.5 (the water-soluble ionic species SO₄^2-, NO₃^-, Cl^-, and NH₄⁺, and carbonaceous species: organic carbon, elemental carbon) were analyzed to study their impact on visibility impairment by reconstructing the light extinction coefficient, b_ext. The visibility was found to be negatively correlated with PM_2.5 and its components. The reconstructed b_ext showed that organic matter was the largest contributor to b_ext in both the seasons which may be attributed to combustion sources. In summer season, it was followed by elemental carbon and ammonium sulfate; however, in winter, major contributions were from ammonium nitrate and elemental carbon. Higher elemental carbon in both seasons may be attributed to traffic sources, while lower concentrations of nitrate during summer, may be attributed to volatility because of higher atmospheric temperatures.

IMPLICATIONS

The chemical constituents of PM_2.5 that majorly effect the visibility impairment are organic matter and elemental carbon, both of which are products of combustion processes. Secondary formations that lead to ammonium sulfate and ammonium nitrate production also impair the visibility.

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., 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 NO_x and PM_2.5 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.

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). The daily average PM_2.5 and PM₁₀ exceeded national standards, with highest concentrations (313 μg m^-3 and 639 μg m^-3, respectively) during winter and lowest (53 μg m^-3 and 130 μg m^-3) during the monsoon (June-August). PM concentrations during the trials can be interpreted either as reduced or increased, depending on the periods used for comparison purposes. For example, hourly average net PM_2.5 and PM₁₀ (after subtracting the baseline concentrations) reduced by up to 74% during the majority (after 1100 h) of trial hours compared with the corresponding hours during the previous year. Conversely, daily average PM_2.5 and PM₁₀ were higher by up to 3-times during the trial periods when compared with the pre-trial days. A careful analysis of the data shows that the trials generated cleaner air for certain hours of the day but the persistence of overnight emissions from heavy goods vehicles into the morning odd-even hours (0800-1100 h) made them probably ineffective at this time. Any further trial will need to be planned very carefully if an effect due to traffic alone is to be differentiated from the larger effect caused by changes in meteorology and especially wind direction.

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. These beam lines are pink (BL-8), white (BL-11) and monochromatic (BL-12), which are housed in specially designed shielded hutches. In order to ensure safety of users and other working personnel from ionizing radiations present in these beam lines, several safety systems are incorporated and safety procedures are followed. The paper describes the radiological safety aspects of the three beam lines during its initial commissioning trials and also the measurements on radiation levels carried out in and around the beam line hutches.

Prospect of brain-machine interface in motor disabilities: the future support for multiple sclerosis patient to improve quality of life

Multiple sclerosis (MS) is an autoimmune neurological disorder, which has impacted health related quality of life (HRQoL) more intensively than any other neurological disorder. The approaches to improve the health standard in MS patient are still a subject of primary importance in medical practice and seek a lot of experimental exploration. The present review briefly explains the anomaly in neuron anatomy and dysfunction in signal transmission arising in the context with the chronic cerebrospinal venous insufficiency (CCSVI), a recent hypothesis related with MS pathophysiology. Subsequently, it insights brain-machine interface (BMI) as an alternative approach to improve the HRQoL of MS subjects. Information sources were searched from peer-reviewed data bases (Medline, BioMed Central, PubMed) and grey-literature databases for data published in 2000 or later. We also did systemic search in edited books, articles in seminar papers, reports extracted from newspapers and scientific magazines, articles accessed from internet; mostly using PubMed, Google search engine and Wikipedia. Out of approximately 178, 240 research articles obtained using selected keywords, those articles were included in the present study which addresses the latest definitions of HRQol and latest scientific and ethical developments in the research of MS and BMI. The article presented a brief survey of CCSVI mediated MS and BMI-approach as a treatment to serve the patients suffering from disabilities as a result of MS, followed by successful precedence of BMI approach. Apart from these, the major findings of selected research articles including the development of parameters to define HRQoL, types and development of BMIs and its role in interconnecting brain with actuators, along with CCSVI being a possible cause of MS have formed the foundations to conclude the findings of the present review article. We propose a perspective BMI approach and promises it holds for future research to improve HRQoL in MS patients. In addition, we propose that brain-computer interfaces will be the core of new treatment modalities in the future for MS disabilities.

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. The OM content, potassium, calcium, sulfate, and nitrate concentrations of street dust in Delhi, India is measured to understand the spatial variation. Correlation analysis, analysis of variance, and factor analysis were performed to define the sources. The dust OM level ranges from 2.63 to 10.22 %. It is found through correlation and factor analysis that OM is primarily contributed from secondary aerosol and vehicular exhaust. The OM levels suggest that the use of a residential-commercial site for commercial purposes is polluting the street dust and creating the environmental and human health problems.

Genotype-phenotype studies of VCP-associated inclusion body myopathy with Paget disease of bone and/or frontotemporal dementia

Valosin containing protein (VCP) disease associated with inclusion body myopathy, Paget disease of the bone and frontotemporal dementia is a progressive autosomal dominant disorder caused by mutations in Valosin containing protein gene. To establish genotype-phenotype correlations we analyzed clinical and biochemical markers from a database of 190 members in 27 families harboring 10 missense mutations. Individuals were grouped into three categories: symptomatic, presymptomatic carriers and noncarriers. The symptomatic families were further divided into ten groups based on their VCP mutations. There was marked intra and inter-familial variation; and significant genotype-phenotype correlations were difficult to establish because of small numbers. Nevertheless when comparing the two most common mutations, R155C mutation was found to be more severe, with an earlier onset of myopathy and Paget (p = 0.03). Survival analysis of all subjects revealed an average life span after diagnosis of myopathy and Paget of 18 and 19 years respectively, and after dementia only 6 years. R155C had a reduced survival compared to the R155H mutation (p = 0.03).We identified amyotrophic lateral sclerosis (ALS) was diagnosed in 13 individuals (8.9%) and Parkinson's disease in five individuals (3%); however, there was no genotypic correlation. This study represents the largest dataset of patients with VCP disease and expands our understanding of the natural history and provides genotype-phenotype correlations in this unique disease.

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. The objectives of the present study are twofold, one, to measure the concentrations of PM(10) (<10 microm), PM(2.5) (<2.5 microm), and PM(1.0) (<1.0 microm) in naturally ventilated classrooms of a school building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM(10) (NVIAQM(pm10)), PM(2.5) (NVIAQM(pm2.5)), and PM(1.0) (NVIAQM(pm1.0)) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO(2) concentrations have also been monitored during school hours. Predicted indoor PM(10) concentrations show poor correlations with observed indoor PM(10) concentrations (R (2) = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM(pm2.5) and NVIAQM(pm1.0) results show good correlations with observed concentrations of PM(2.5) (R(2) = 0.87 for weekdays and 0.9 for weekends) and PM(1.0) (R(2) = 0.86 for weekdays and 0.87 for weekends). NVIAQM(pm10) shows the tendency to underpredict indoor PM(10) concentrations during weekdays as it does not take into account the occupant's activities and its effects on the indoor concentrations during the class hours. Intense occupant's activities cause resuspension or delayed deposition of PM(10). The model results further suggests conductance of experimental and physical simulation studies on dispersion of particulates indoors to investigate their resuspension and settling behavior due to occupant's activities/movements. The models have been validated at three different classroom locations of the school site. Sensitivity analysis of the models has been performed by varying the values of mixing factor (k) and newly introduced parameter R(c). The results indicate that the change in values of k (0.33 to 1.00) does not significantly affect the model performance. However, change in value of R(c) (0.001 to 0.500) significantly affects the model performance.

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. In the absence of data, the mechanism can be intuitively manipulated by the user to construct MFs with the desired shape. MFs have been developed using the proposed mechanism for urban vehicular exhaust emission modeling. It has been observed that all meteorological and vehicular parameters have either S-shaped MFs or Z-shaped MFs. Gaussian MF has been mostly applied for modeling air quality. The present study explored the application of fuzzy MF to analyze air pollution data from vehicular emission. The study reveals that S-shaped and Z-shaped MF can be used in addition to Gaussian MF.

Placental histomorphology in unexplained foetal loss with thrombophilia

BACKGROUND & OBJECTIVES

Acquired and genetic thrombotic conditions, both organ and non organ specific, are associated with increased foetal wastage. This study was carried out to examine the placenta from women with abnormal pregnancies and a history of unexplained foetal loss, and to associate with maternal thrombophilia status.

METHODS

Placentas from eight women with history of unexplained foetal loss were analyzed for histopathological characteristics. All the women were simultaneously screened for the common acquired and genetic thrombophilia markers i.e., lupus anticoagulants ( LA), IgG / IgM antibodies for anticardiolipin (ACA), beta2 glycoprotein 1 (beta2GPI) and annexin V, protein C (PC), protein S (PS), antithrombin III (AT III), factor V Leiden ( FVL) mutation, prothrombin (PT) gene G20210A, methylene tetrahydrofolate reductase (MTHFR) C 677T, endothelial protein C receptor (EPCR) 23 bp insertion and plasminogen activator inhibitor ( PAI-1 4G/5G) polymorphisms

RESULTS

Six of eight women were positive for one or more thrombophilia markers. The placenta in all the cases except one, showed the characteristic features of infarct fibrin deposition and calcification. Among two women who were negative for thrombophilia, one showed clear evidence of thrombus in the placental sections while the other did not show any characteristic infarcts in the placental sections.

INTERPRETATION & CONCLUSION

Our findings showed that the histopathological examination of the placentas confirmed thrombophilia as the aetiological cause of thrombosis in 6 of the 8 women. The presence of thrombus in a negative thrombophilia woman suggests yet unidentified thrombophilia markers or probably non-haemostatic factors causing thrombosis.

Indoor air quality assessment in and around urban slums of Delhi city, India

The present study aims at investigating the indoor air quality (IAQ) in selected households in one of the urban slums i.e. the Nizamuddin slums in Delhi, the capital city of India. The study includes investigations and assessments on associated health effects on the occupants living in inefficiently designed houses having poor ventilation. The monitoring of indoor air pollutants e.g. the respirable suspended particulate matter (RSPM), the carbon dioxide (CO2), the carbon monoxide (CO), the sulphur dioxide (SO2) and the nitrogen dioxide (NO2) for all three seasons i.e. summer (April-June 2004), rainy (July-September 2004) and winter (December 2004-February 2005) have been conducted. In addition, the spirometry tests on the occupants, particularly the womenfolk and children have been performed to determine the incidence of acute respiratory infections (ARI). Questionnaire survey has also been conducted in the households during the study period to investigate the sick building syndrome (SBS). The study reveals maximum concentration of indoor air pollutants in households during winters (December 2004-February 2005) associated with aggravated respiratory problems like cough, phlegm, wheezing, and breathlessness among occupants particularly the women occupants. Besides, decrement in lung function indices (i.e. FVC and/or FEV1) due to increased concentrations of RSPM and CO2 indoors during winter period has also been observed in the women respondents. The study concludes that women and children indoors are most vulnerable to respiratory problems compared to other sexes. A high SBS score is observed in these 'urban poor' households because of inadequate ventilation.

PRACTICAL IMPLICATIONS

'High indoor airborne pollutants during winter are associated with respiratory problems for women and children in houses in urban slum in Delhi. The work demonstrated the need of further studies of indoor air quality for the 'urban poor' in developing countries.'

Indoor air quality assessment in and around urban slums of Delhi city, India

The present study aims at investigating the indoor air quality (IAQ) in selected households in one of the urban slums i.e. the Nizamuddin slums in Delhi, the capital city of India. The study includes investigations and assessments on associated health effects on the occupants living in inefficiently designed houses having poor ventilation. The monitoring of indoor air pollutants e.g. the respirable suspended particulate matter (RSPM), the carbon dioxide (CO2), the carbon monoxide (CO), the sulphur dioxide (SO2) and the nitrogen dioxide (NO2) for all three seasons i.e. summer (April-June 2004), rainy (July-September 2004) and winter (December 2004-February 2005) have been conducted. In addition, the spirometry tests on the occupants, particularly the womenfolk and children have been performed to determine the incidence of acute respiratory infections (ARI). Questionnaire survey has also been conducted in the households during the study period to investigate the sick building syndrome (SBS). The study reveals maximum concentration of indoor air pollutants in households during winters (December 2004-February 2005) associated with aggravated respiratory problems like cough, phlegm, wheezing, and breathlessness among occupants particularly the women occupants. Besides, decrement in lung function indices (i.e. FVC and/or FEV1) due to increased concentrations of RSPM and CO2 indoors during winter period has also been observed in the women respondents. The study concludes that women and children indoors are most vulnerable to respiratory problems compared to other sexes. A high SBS score is observed in these 'urban poor' households because of inadequate ventilation.

PRACTICAL IMPLICATIONS

'High indoor airborne pollutants during winter are associated with respiratory problems for women and children in houses in urban slum in Delhi. The work demonstrated the need of further studies of indoor air quality for the 'urban poor' in developing countries.'

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. to 6 A.M., 6 A.M., to 2 P.M. and 2-10 P.M., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2-10 PM is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68-71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.

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.' The AQMP formulation methodology is based on past studies of Longhurst et al., (Atmospheric Environment, 30, 3975-3985, 1996); Longhurst & Elsom, ((1997). Air Pollution-II, Vol. 2 (pp. 525-532)) and Beatti et al., (Atmospheric Environment, 35, 1479-1490, 2001). Further, the vulnerability analysis (VA) has been carried out to evaluate the stresses due to air pollution in the study area. The VA has given the vulnerability index (VI) of 'medium to high' and 'low' at urban roadways/intersections and residential areas, respectively.

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. PM2.5, PM10, and total suspended particulates (TSP) concentrations at Satna were 20.5 +/- 6.0, 102.1 +/- 41.1, and 387.6 +/- 222.4 microg m(-3) and at Delhi were 126.7 +/- 28.6, 268.6 +/- 39.1, and 687.7 +/- 117.4 microg m(-3). Values at Delhi were well above the standard limit for 24-h PM2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 microg m(-3)), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM2.5 standards. The position of PM10 in Delhi is drastic and needs an immediate attention. PM10 levels at Delhi were also well above the standard limit for 24-h PM10 National Ambient Air Quality Standards (NAAQS; 150 microg m(-3)), while levels at Satna remained under the standard limit. PM2.5/PM10 values were also calculated to determine PM2.5 contribution. At Satna, PM2.5 contribution to PM10 was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 microg m(-3)). At Satna, the PM10 contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM10, PM2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.

Compensating for provider nonresponse using response propensities to form adjustment cells: the National Immunization Survey

OBJECTIVES

The National Immunization Survey (NIS) uses two phases of data collection to obtain vaccination information from a sample of young children: a random-digit-dialing (RDD) survey for identifying households with children 19-35 months of age, followed by a mail survey for obtaining provider-reported vaccination histories about these children. Provider-reported vaccination histories are used to estimate vaccination coverage rates. In 1998, provider-reported vaccination histories were not obtained for 32.9% of children with a completed RDD interview. This report describes the statistical methods adopted in 1998 to reduce the bias in vaccination coverage estimates that could result from "vaccination history nonresponse," that is, differences between children for whom provider data was obtained and those for whom it was not obtained.

METHODS

In the methods adopted in 1998, children with completed NIS RDD interviews are grouped into adjustment cells defined by their propensity to have adequate provider data. Sampling weights of children with adequate provider data are divided by the cell-specific weighted response rate to allow these children to represent all children in the cell.

RESULTS

Using an "optimal" number of cells, the overall extent of bias reduction was 0.5%, suggesting that provider nonresponse bias was small. Authoritative literature suggests using five cells. No statistically significant differences were observed in vaccination coverage estimates when comparing estimates based on the "optimal" number of cells with five cells. Thus, five adjustment cells are used to reduce provider nonresponse bias in the NIS vaccination coverage estimates. No substantively important differences were observed between estimates based on the methodology used prior to 1998 and the methodology adopted in 1998.

The role of ultrasound in the expectant management of early pregnancy loss

OBJECTIVE

To define the sonographic criteria which best determine the likelihood of successful expectant management of early pregnancy failure (EPF).

METHODS

Women with an ultrasound diagnosis of EPF at 7-14 weeks' gestation were offered the option of expectant management or surgical evacuation.

RESULTS

Five hundred and forty-five women had a diagnosis of EPF; 298 with incomplete miscarriage and 247 with missed miscarriage or an embryonic pregnancy. A total of 305 women opted for expectant management, with an overall success rate of 86%. The success rate for incomplete miscarriage (96%) was significantly better than that for missed miscarriage (62%).

CONCLUSION

This study demonstrates that EPF can be safely managed expectantly. Ultrasound has an invaluable role in predicting the likelihood of successful expectant management enabling patients to make an informed choice about their medical care.

Overview of the sampling design and statistical methods used in the National Immunization Survey

Abstract: The National Immunization Survey (NIS) is a large federally funded survey designed to estimate vaccination coverage rates for children residing in the United States aged 19 to 35 months. In 1999, over 8 million telephone call attempts were made to obtain provider-reported vaccination histories on 22,521 children in the age range of interest.

Food intake patterns and gallbladder disease in Mexican Americans

OBJECTIVE

Results of previous studies on diet and gallbladder disease (GBD), defined as having gallstones or having had surgery for gallstones, have been inconsistent. This research examined patterns of food intake in Mexican Americans and their associations with GBD.

DESIGN

Cross-sectional.

SUBJECTS

The study population included 4641 Mexican Americans aged 20-74 years who participated in the 1988-94 third National Health and Nutrition Examination Survey (NHANES III). GBD was diagnosed by ultrasound. Food intake patterns were identified by principal components analysis based on food frequency questionnaire responses. Component scores representing the level of intake of each pattern were categorized into quartiles, and prevalence odds ratios (POR) were estimated relative to the lowest quartile along with 95% confidence intervals (CI).

RESULTS

There were four distinct patterns in women (vegetable, high calorie, traditional, fruit) and three in men (vegetable, high calorie, traditional). After age adjustment, none were associated with GBD in women. However, men in the third (POR = 0.42, 95%CI 0.21-0.85) and fourth (POR = 0.53, 95%CI 0.28-1.01) quartiles of the traditional intake pattern were half as likely to have GBD as those in the lowest quartile.

CONCLUSIONS

These findings add to a growing literature suggesting dietary intake patterns can provide potentially useful and relevant information on diet-disease associations. Nevertheless, methods to do so require further development and validation.

Country of birth and prevalence of gallbladder disease in Mexican Americans

OBJECTIVES

This research sought to describe the association between country of birth and gallbladder disease (GBD) in Mexican Americans, identify subgroups at especially high risk, and identify risk factors that may mediate a birthplace-GBD association.

DESIGN

Cross-sectional.

METHODS

Our study population included 4157 Mexican Americans aged 20-74 who participated in the 1988-94 third National Health and Nutrition Examination Survey. GBD was diagnosed by ultrasound. Information on country of birth, education, income, and selected GBD risk factors was obtained from interviews. Prevalence odds ratios (POR) for GBD in Mexico- vs. US-born Mexican Americans were estimated by unconditional logistic regression, along with 95% confidence intervals (CI). To evaluate the extent to which GBD risk factors mediated the birthplace-GBD association, PORs for country of birth were compared in models with and without additional covariates.

RESULTS

Age-adjusted GBD prevalence was lower in Mexico- than in US-born Mexican-American women (POR = 0.70, 95% CI 0.50, 0.98) and men (POR = 0.63, 95% CI 0.40, 0.97). The difference was especially pronounced among subjects of lower socioeconomic status. Despite substantial differences in GBD risk factor distributions by birthplace, none could completely explain the prevalence difference.

CONCLUSIONS

The observation that GBD prevalence is higher among US-born Mexican Americans is consistent with research showing poorer health in this group. Further research is needed to identify strategies for reducing morbidity from GBD in Mexican Americans.

Prevalence and ethnic differences in gallbladder disease in the United States

BACKGROUND & AIMS

Gallbladder disease is one of the most common conditions in the United States, but its true prevalence is unknown. A national population-based survey was performed to determine the age, sex, and ethnic distribution of gallbladder disease in the United States.

METHODS

The third National Health and Nutrition Examination Survey (NHANES III) conducted gallbladder ultrasonography among a representative U.S. sample of more than 14, 000 persons. The diagnosis of gallbladder disease by detection of gallstones or cholecystectomy was made with excellent reproducibility.

RESULTS

An estimated 6.3 million men and 14.2 million women aged 20-74 years had gallbladder disease. Age-standardized prevalence was similar for non-Hispanic white (8. 6%) and Mexican American (8.9%) men, and both were higher than non-Hispanic black men (5.3%). These relationships persisted with multivariate adjustment. Among women, age-adjusted prevalence was highest for Mexican Americans (26.7%) followed by non-Hispanic whites (16.6%) and non-Hispanic blacks (13.9%). Among women, multivariate adjustment reduced the risk of gallbladder disease for both Mexican Americans and non-Hispanic blacks compared with non-Hispanic whites.

CONCLUSIONS

More than 20 million persons have gallbladder disease in the United States. Ethnic differences in gallbladder disease prevalence differed according to sex and were only partly explained by known risk factors.

Influence of ethnic origin on nuchal translucency screening for Down's syndrome

OBJECTIVE

To determine the influence of ethnic origin on access to and equity of nuchal translucency screening for Down's syndrome in a multiethnic population.

DESIGN

An observational study in a district general hospital with a large multiethnic population.

SUBJECTS

1944 women attending at a hospital antenatal clinic.

MAIN OUTCOME MEASURES

First-trimester fetal nuchal translucency measurements at 10-14 weeks in women from different ethnic groups.

RESULTS

The racial origin of the screened population was not significantly different from that of the population attending for initial antenatal examination. Multiple regression analysis showed a small but significant difference in nuchal translucency measurement between fetuses of different ethnic origin.

CONCLUSION

Nuchal translucency screening can be effectively and equitably delivered to a multiethnic population. Although there are significant differences in nuchal translucency measurement between ethnic groups, these differences are too small to require correction when nuchal translucency is used to screen for Down's syndrome.

The current status of methods for estimating the prevalence of human immunodeficiency virus in the United States of America

The prevalence of human immunodeficiency virus (HIV) infection can be estimated by two distinct methods. One method, back-calculation, is a complex statistical procedure that estimates the HIV epidemic curve. The second method is based on data from population-based surveys, which provide estimates of the proportion of persons infected with HIV within subgroups, and on the known or estimated population totals for these subgroups. Estimates from these methods are subject to substantial uncertainty and bias, both of which are difficult to quantify. We review recent use of these procedures to estimate HIV prevalence in the United States of America. We also summarize new data on the uncertainty and the bias in these estimates. Reliable estimates of HIV prevalence can be made only by synthesizing estimates from several procedures and by a comprehensive evaluation of relevant data. Future estimates of HIV prevalence will require modifications of these methods or the development of new methods.

Internalization of dengue virus-induced suppressor cytokine during transmission of the suppressor signal via macrophage

In dengue type 2 virus (DV)-induced suppressor T cell cascade TS1 cells secrete a suppressor cytokine (SF) which acts via syngeneic macrophages (M phi) to recruit TS2 cells. SF binds to both high and low affinity receptors (SF-R) on M phi. In the present study the fate of SF in M phi during transmission of suppressor signal is investigated. It was observed that SF bound to high affinity receptors internalized through receptor mediated endocytosis. This was inhibited by pretreatment of M phi with anti-SF-R-antiserum and didansylcadaverine, a potent inhibitor of endocytosis. Internalized SF was degraded by lysosomal activity as shown by inhibition of suppressor activity by pretreatment of M phi with monensin and NH4Cl. Degraded SF was transported to a site other than SF-R on M phi membrane for recruitment of TS2 cells. This was inhibited by anti-SF-antiserum. Transmission of suppressor signal is inhibited if M phi are treated first with H-2K-mAb and then with SF (shown earlier) but when M phi were treated first with SF and after 1 hr with H-2K-monoclonal antibody, the inhibition did not occur. As SF requires binding to H-2K and SF-R for mediation of suppression, the binding of H-2K occurred with degraded SF within the cell. Thus SF is internalized, degraded and binds to H-2K antigen before its recognition by native T cells.

Role of nitric oxide in transmission of dengue virus specific suppressor signal

Production of NO2- was maximum when peritoneal M phi was incubated with SF (40 mg) for 45 min. Pretreatment of M phi with anti-SF-antisera inhibited production of NO2- Pretreatment of M phi with NG monomethyl L-arginine (L-NMA) or arginase, an inhibitor of L-arginine dependent pathway, inhibited production of NO2- and transmission of suppressor signal in a dose-dependent manner. This indicates that NO and Ca2+ serve as intracellular signal in transmission of DV-induced suppressor signal.

Update on the seroepidemiology of human immunodeficiency virus in the United States household population: NHANES III, 1988-1994

To update the estimate of seroprevalence of HIV from the third National Health and Nutrition Examination Survey (NHANES III), data from the second phase of the survey were combined with previously published data to produce a more precise estimate. The testing was performed anonymously on 11,203 individuals 18-59 years of age examined from 1988 to 1994. Fifty-nine individuals were HIV positive, for an overall prevalence of 0.32%. The number of individuals living in households with HIV infection based on this estimate was 461,000, with a 95% confidence interval of 290,000-733,000. Analysis of nonresponse demonstrated that white and black men 40-59 years of age were least likely to participate in the survey. A sensitivity analysis demonstrated that this nonresponse may have biased the NHANES III estimate downward by 190,000 persons. Data from the second phase of the survey were used to analyze the association between drug use and HIV infection. Black women who used cocaine were 12 times more likely to be HIV positive compared with all tested black women (6.5% vs. 0.55%). This survey provides an estimate of HIV prevalence for individuals who reside in households but excludes some persons who are at higher risk for HIV infection, including prisoners and the homeless not residing in shelters.