Real-world tailpipe emissions from autorickshaws (3-wheelers) under heterogeneous traffic conditions.

The current study aimed to measure real-world emissions of three-wheeled autorickshaws powered by CNG and parameters (such as speed, acceleration, air-fuel (A/F) ratio, and rpm) influencing 3-wheeler emission rates. Test vehicles manufactured under Bharat Standards BS-III and BS-IV were monitored for exhaust emissions in Delhi city using a portable exhaust emission measurement system (AVL Ditest Gas 1000). The average emission rates of CO, HC, and NO gases for on-road autorickshaws were found to be 0.015 ± 0.017, 0.003 ± 0.0017, and 0.007 ± 0.005 g/s, respectively. Further, the highest emission factor values of 3.98 g/km and 3.93 g/km were estimated for CO and HC+NO gases, respectively. These values were found to be 1.4-3.2 times higher than the respective BS emission norms (BS III-CO =1.25 g/km, HC+NO = 1.25 g/km; BS-IV-CO = 0.94 g/km and HC+NO = 0.94 g/km). In this study, it was observed that the driving pattern and emissions were affected by traffic characteristics, driver behavior (constant acceleration and deceleration), and vehicle characteristics. The air-fuel ratio (A/F) was found to correlate highly with emission rates, followed by acceleration/deceleration and speed. Further analysis found that more than 70% of the aggregated emissions were due to acceleration and deceleration, which contributed to nearly 70% of the travel time. This was followed by the breakdown of speed and emissions into different bins, which found that 20-30 kmph has a higher emission rate and 40-50 kmph bin has a lower emission rate.

Health risk assessment of workers' exposure to BTEX and PM during refueling in an urban fuel station.

The proximity of fuel stations to the roads and the activities inside the station can contribute to PM and VOCs and impose health risks on station workers. The study presents the exposure and health risk assessment of the fuel station personnel to total volatile organic compounds (TVOCs) and particulate matter (PM) during refueling operations. TVOCs and PM monitoring were carried out at a fuel station in Chennai, India, for 1 week in March 2021, covering both weekdays and weekends. The health risks were assessed using EPA's health impact assessment methodology. Exposure to TVOCs (3177.39 ± 5450.32 µg/m3) exceeded the EPA standard of 5 µg/m3, by more than 500 times, peaking during refueling operations. The average concentrations of PM10, PM2.5, and PM1 were 76.55 ± 23.08 µg/m3, 41.81 ± 9 µg/m3, and 30.38 ± 7.56 µg/m3, respectively. The concentrations were observed to be high during morning and evening hours due to the increased traffic on the adjacent road and inside the fuel station. The synergistic health risks linked with long-term exposure to high concentrations of BTEX and PM were also estimated. At the fuel station, a significant contribution to the SOA formation potential was shown by toluene, followed by m-xylene, p-xylene, o-xylene, ethylbenzene, and benzene. Furthermore, the deposition of airborne particles in the workers' respiratory tract was calculated using the Multiple Path Particle Dosimetry model while considering the daily average exposure duration of 12 h. The results showed that 59% of PM10 particles were deposited in the head region, whereas 11% and 10% of PM2.5 and PM1 particles were deposited in the pulmonary region. Hence, the health risk assessment indicated no non-cancer risk of exposure to PM (hazard quotient = 0.13) to station personnel exposed regularly for 1 year. However, prolonged exposure to VOCs for more than 1 year can result in both carcinogenic and non-carcinogenic risk (hazard quotient = 0.045 and cancer risk > 10-6) in workers.

Trends, Extreme Events and Long-term Health Impacts of Particulate Matter in a Southern Indian Industrial Area.

The present study uses various statistical tools to understand the behaviour of PM2.5 and PM10 in the Kanjikode industrial area of Southern India. Annual PM2.5 and PM10 average concentrations in 2018-2020 were three times more than the World Health Organization-specified standards (5 and 15 µg m-3). The statistical distribution analysis suggested well-fitted lognormal and gamma distributions of 24-h average PM2.5 concentrations and gamma distributions of 24-h average PM10 concentrations. Trend analysis observed a notable monotonic increasing trend for 24-h average PM2.5 concentrations with an increasing magnitude of 0.43 µg m-3 per annum. A downward trend was found for 24-h average PM10 concentrations, with a decreasing magnitude of 0.2 µg m-3 per year. Extreme event analysis of PM2.5 and PM10 has provided the highest concentration levels expected in the coming 10 years, 193 and 165 µg m-3, respectively, higher than the Indian National Ambient Air Quality Standards and considered a public health threat. The health risk assessment by AirQ + emphasized that more than 15, 34, and 27 premature deaths caused by total mortality in 2018, 2019, and 2020 could have been prevented if PM2.5 concentrations in the Kanjikode industrial area did not exceed 10 µg m-3. Statistical analysis and health risk assessment suggested adopting various constructive and multipronged approaches to reduce pollution levels and develop a health risk management plan in the industrial region. Supplementary Information: The online version contains supplementary material available at 10.1007/s11270-023-06302-y.

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM2.5: 67 µg m-3 (lockdown) versus 81 µg m-3 (pre-lockdown); PM10: 171 µg m-3 versus 235 µg m-3; CO: 0.9 mg m-3 versus 1.1 mg m-3) except ozone which increased during the lockdown period (57 µg m-3 versus 39 µg m-3). The variation in pollutant concentrations revealed that PM2.5, PM10 and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

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 (PM2.5 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 âˆ¼ 68% of time spent boiling/stewing in Cairo, Sulaymaniyah and Akure. The highest average PM2.5 (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 PM2.5 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 PM2.5 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.

Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art.

Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.

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; PM2.5) 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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 exposure highlights the importance of implementing plausible solutions to make a positive impact on peoples' lives in these cities.

Dynamics of PM2.5 pollution in the vicinity of the old municipal solid waste dumpsite.

The present study explored the effect of local meteorology on the dispersion of PM2.5 from a 30-year open municipal solid waste (MSW) dumpsite in Chennai, India. The spatial monitoring was conducted in and around the dumpsite to understand the impacts of dumpsite activities on the nearby residential area. Results showed that dumpsite activities are responsible for deteriorating local air quality. The 24-h average PM2.5 concentrations were 50, 43.7, and 34 µg m-3 during stagnation, recirculation, and ventilation events, respectively. Spearman's correlation showed an inverse relationship between PM2.5 and temperature; wind speed indicated dispersion of fine aerosols. The observed inverse relationship between PM2.5 and relative humidity indicated the hygroscopic growth of fine aerosols in the study area. We used AERMOD to simulate the dispersion of 1-h, 8-h, and 24-h PM2.5 emissions from open waste burning in the dumpsite. The 1-h, 8-h, and 24-h simulated results showed the maximum concentration of 247, 136, and 53.4 µg m-3 in the dumpsite, and concentration levels ranged between 50-60, 30-50, and 10-20 µg m-3 were observed in the nearby residential area. The AERMOD predictions indicated that open waste burning could be a significant contributor to high PM2.5 concentration in an adjacent residential area of the dumpsite.

Unprecedented reduction in air pollution and corresponding short-term premature mortality associated with COVID-19 lockdown in Delhi, India.

Countries around the world introduced strict restrictions on movement and activities known as 'lockdowns' to restrict the spread of the novel coronavirus disease (COVID-19) from the end of 2019. A sudden improvement in air quality was observed globally as a result of these lockdowns. To provide insight into the changes in air pollution levels in response to the COVID-19 restrictions we have compared surface air quality data in Delhi during four phases of lockdown and the first phase of the restriction easing period (25 March to 30 June 2020) with data from a baseline period (2018-2019). Simultaneously, short-term exposure of PM2.5 and O3 attributed premature mortality were calculated to understand the health benefit of the change in air quality. Ground-level observations in Delhi showed that concentrations of PM10, PM2.5 and NO2 dropped substantially in 2020 during the overall study period compared with the same period in previous years, with average reductions of ~49%, ~39%, and ~39%, respectively. An overall lower reduction in O3 of ~19% was observed for Delhi. A slight increase in O3 was found in Delhi's industrial and traffic regions. The highest peak of the diurnal variation decreased substantially for all the pollutants at every phase. The decrease in PM2.5 and O3 concentrations in 2020, prevented 904 total premature deaths, a 60% improvement when compared to the figures for 2018-2019. The restrictions on human activities during the lockdown have reduced anthropogenic emissions and subsequently improved air quality and human health in one of the most polluted cities in the world.Implications: I am submitting herewith the manuscript entitled "Unprecedented Reduction in Air Pollution and Corresponding Short-term Premature Mortality Associated with COVID-19 Forced Confinement in Delhi, India" for potential publishing in your journal.The novelty of this research lies in: (1) we utilized ground-level air quality data in Delhi during four phases of lockdown and the first phase of unlocking period (25th March to 30th June) for 2020 as well as data from the baseline period (2018-2019) to provide an early insight into the changes in air pollution levels in response to the COVID-19 pandemic, (2) Chatarize the change of diurnal variation of the pollutants and (3) we assess the health risk due to PM2.5 and O3. Results from ground-level observations in Delhi showed that concentrations of PM10, PM2.5 and NO2 substantially dropped in 2020 during the overall study period compared to the similar period in previous years, with an average reduction of ~49%, ~39%, and ~39%, respectively. In the case of O3, the overall reduction was observed as ~19% in Delhi, while a slight increase was found in industrial and traffic regions. And consequently, the highest peak of the diurnal variation decreased substantially for all the pollutants. The health impact assessment of the changes in air quality indicated that 904 short-term premature deaths (~60%) were prevented due to the decline in PM2.5 and O3 concentrations in the study period. The restrictions on human activities during the lockdown have reduced the anthropogenic emissions and subsequently improved air quality and human health in one of the most polluted cities in the world.

Association of air pollution and meteorological variables with COVID-19 incidence: Evidence from five megacities in India.

Although lockdown of the industrial and transport sector and stay at home advisories to counter the COVID-19 pandemic have shown that the air quality has improved during this time, very little is known about the role of ambient air pollutants and meteorology in facilitating its transmission. This paper presents the findings from a study that was conducted to evaluate whether air quality index (AQI), three primary pollutants (PM2.5, PM10 and CO), Ground level ozone (O3) and three meteorological variables (temperature, relative humidity, wind speed) have promoted the COVID-19 transmission in five megacities of India. The results show significant correlation of PM2.5, PM10, CO, O3 concentrations, AQI and meteorological parameters with the confirmed cases and deaths during the lockdown period. Among the meteorological variables considered, temperature strongly correlated with the COVID-19 cases and deaths during the lockdown (r=0.54;0.25) and unlock period (r=0.66;0.25). Among the pollutants, ozone, and among the meteorological variables, temperature, explained the highest variability, up to 34% and 30% respectively, for COVID-19 confirmed cases and deaths. AQI was not a significant parameter for explaining the variations in confirmed and death cases. WS and RH could explain 10-11% and 4-6% variations of COVID-19 cases. A GLM model could explain 74% and 35% variability for confirmed cases and deaths during the lockdown and 66% and 19% variability during the unlock period. The results suggest that meteorological parameters may have promoted the COVID-19 incidences, especially the confirmed cases. Our findings may encourage future studies to explore more about the role of ambient air pollutants and meteorology on transmission of COVID-19 and similar infectious diseases.

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 (PM2.5; fine fraction) and ≤10 µm (PM2.5-10; 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, PM2.5 and PM10 concentrations were highest during windows-open, followed by fan-on and recirculation. Compared with recirculation, PM2.5 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. PM2.5 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 PM2.5 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.

Impact of urban heat island on meteorology and air quality at microenvironments.

This study analyzes the air pollution characteristics and their relation to meteorological conditions in Chennai, India. Meteorological conditions were the primary factor determining variations in daily average pollutant concentrations. The influence of urban infrastructure on meteorology is an important prediction on air quality. Understanding of the seasonal and diurnal secondary pollutant concentrations as a function of local meteorological conditions is necessary for urban air quality management. Micro-scale models for analyzing the surface layer interactions with the surrounding environment have recently gained attention. An attempt has been made to understand the effect of meteorology on air quality. This comprehensive study aims to assess the influence of local meteorology on urban air quality. The correlation was established between the change in meteorological parameters and mixing height on air quality at selected locations in a tropical urban environment. Results indicated the significant impact of land use patterns on the dispersion of air quality at study locations. Seasonal variations of ambient air temperatures at study locations were found to be more than 3°C in summer. Average mixing height variation among the study locations was observed to be more than 200 meters in summer. Results indicated the importance of wind velocity on the mixing height at study locations. The average concentrations of air quality parameters showed significant variation among the study locations. The maximum ozone (O3) concentration was recorded at the Central Business District (CBD) during the afternoon, i.e., around 38.3 ppb, whereas it was 26.8 and 14.6 ppb at the Residential Area (RA) and Urban Baseline (UBL), respectively. A strong correlation was observed between ambient temperature and O3 concentration during summer. In the winter, the average O3 concentration in all three-study locations increased to 45.3 ppb, 45.8 ppb, and 58.5 ppb at UBL, RA, and CBD sites, respectively. The study reveals the impact of microenvironments on air quality. Implications: An attempt has been made to study the seasonal and diurnal variation of air quality levels in selected study regions with land cover change. This article focuses mainly on the surface temperature intensity variations with respect to the percentage of land use pattern change in Chennai city, India, and the subsequent effect on meteorology of dispersion conditions and air quality parameters has been studied. The relationship between local meteorology and air quality has been established.

Advances in Mid-Infrared Spectroscopy-Based Sensing Techniques for Exhaled Breath Diagnostics.

Human exhaled breath consists of more than 3000 volatile organic compounds, many of which are relevant biomarkers for various diseases. Although gas chromatography has been the gold standard for volatile organic compound (VOC) detection in exhaled breath, recent developments in mid-infrared (MIR) laser spectroscopy have led to the promise of compact point-of-care (POC) optical instruments enabling even single breath diagnostics. In this review, we discuss the evolution of MIR sensing technologies with a special focus on photoacoustic spectroscopy, and its application in exhaled breath biomarker detection. While mid-infrared point-of-care instrumentation promises high sensitivity and inherent molecular selectivity, the lack of standardization of the various techniques has to be overcome for translating these techniques into more widespread real-time clinical use.

Off-Resonance Photoacoustic Spectroscopy Technique for Multi-Gas Sensing in Biogas Plants.

An off-resonance broadband photoacoustic spectroscopy (PAS) technique with a supercontinuum laser (SCL) in the near-infrared range is demonstrated for biogas measurements with different biomass matrices. The PAS sensor system has been calibrated with known concentrations of methane (CH4), carbon dioxide (CO2), water vapor (H2O vapor), and hydrogen sulfide (H2S). A laboratory-scale bioreactor was set up to monitor CH4 and CO2 generation using the SCL-PA sensor system. The obtained results show the suitability of the PAS sensor to be employed in a fully operational large scale biogas plant for online monitoring. The periodic variations in concentration for CH4, CO2, and H2O vapor were monitored in a large scale cattle dung based biogas plant in real-time, and the operating ranges were measured to be around 50-65%, 34-48%, and 0-1%, respectively. The SCL-PA sensor was also employed at two different Sewage Treatment Plants in Chennai, Tamilnadu, India, where along with CH4 (60-63%), CO2 (34-38%), and H2O vapor (0.8-1%), trace concentration levels of H2S were found to be around 0.04-1%.

Characterization and health risk assessment of indoor dust in biomass and LPG-based households of rural Telangana, India.

Indoor dust is one of the key sources contributing to indoor air pollution (IAP) in rural households. It acts as a media for various toxicants like heavy metal depositions and causes severe health risks. The present study deals with investigation of metal concentrations and morphological characteristics of indoor dust generated in varied fuel types followed by estimation of health risks for women and children in rural households in Telangana, India. Indoor floor dust samples were collected from households using biomass and liquefied petroleum gas (LPG) as their cooking energy during winter to evaluate the morphological and chemical characteristics in the aforementioned dust samples. A morphological (SEM-EDX) analysis revealed the presence of carbonaceous particles in biomass-based households and mineral-rich crustal sources in LPG-based households. As observed from ICP-OES analysis, there is a significant difference in mean concentrations of Al, Co, Cr, Fe, Zn, and Ni based on fuel type, except for Mn and Pb. From Pearson's correlation analysis and principal component analysis, it was observed that the biomass households were dominated by Zn, Al, Mn, Cr, and Pb, which could have been contributed from biomass burning deposits, crustal sources, and unpaved roads, while Cr, Pb, Fe, and Mn dominated in LPG households, indicating their origin from leaded paints (Pb and Cr) and crustal sources. The health risks associated with these heavy metals to women and children were investigated using an EPA health risk model. The values from the model indicated that both non-carcinogenic and carcinogenic risks were within the safe levels for both subjects. This study not only establishes chemical and morphological characteristics of indoor dust, but also quantifies the role of fuel type.Implications: The present study provides the latest geographical evidence of chemical and morphological characterization of indoor dust particles in varied fuels; i.e, biomass- and LPG-based households and associated health risk assessment in a sub-tropical rural site in Telangana, India. Nevertheless, further research is essential from various regions across the country for more heavy metal analysis and factors impacting these levels. One of the major limitations of the present study is the analysis of few metals and measurements in only living area locations. Future studies can include soil and road dust, as well as kitchens and bedrooms, to provide more comprehensive analysis of dust compositions in varied environments.

Off-resonant photoacoustic spectroscopy for analysis of multicomponent gas mixtures at high concentrations using broadband vibrational overtones of individual gas species.

The broadband photoacoustic spectroscopy (PAS) technique is proposed and demonstrated for measurement of CH4, CO2, and H2O vapor in the 1.6 to 2.0 µm wavelength region. The wide spectrum of a supercontinuum light source is used to cover broadband absorption bands of multiple gas species. This sensor works in the off-resonant frequency of the designed photoacoustic cell and exhibits a wide concentration measurement range of parts per billion by volume (ppb-v) to 100%. The PAS sensor is further tested in real time by measuring the concentration of CO2, CH4, and H2O vapor in biogas plants.

Environmental burden by an open dumpsite in urban India.

Open municipal solid waste (MSW) dumpsites are nowadays looming hotspots for water, air, and land pollution. Fresh and old MSW samples collected from a dumpsite in the coastal city of India were analyzed for moisture content, volatile content, energy content, elements, and toxic heavy metals. The compositional analysis results showed that fresh MSW consisted of 36% by weight bio-waste (food waste, yard waste, coconut waste) and around 30% recyclable materials (plastics, paper, cardboard, and metals). Approximately, 62% of the total fresh MSW was found to be combustible materials (plastics, paper, textile, rubber, cardboard, yard waste, and coconut husks). The analysis of old MSW samples collected from different depths (3-4 m and 6-7 m) showed the dominance of plastics (25-33%) and mixed residue (28-55%) having high energy content. Measurements of gaseous emission below 6-7 m from the surface indicated a higher concentration of methane (CH4:5.85 ±â€¯0.12%) and lower concentration of carbon monoxide (CO: 3.82 ±â€¯1.3 ppm), and hydrogen sulfide (H2S:10.15 ±â€¯2.2 ppm). Haphazard dumping, waste characteristics, waste pile compaction processes and heat propagation due to deliberate fire may stimulate spontaneous fires.

Ozone pollution in Chinese cities: Assessment of seasonal variation, health effects and economic burden.

The ground-level ozone (O3) concentration in the urban regions of China has become an increasingly noticeable environmental problem in recent years. Many epidemiological studies have reported the association between O3 pollution and mortality, only a few studies have focused on the O3-related mortality and corresponding economic effects at the Chinese city and province level. This study reports the seasonal variation of ground-level O3 in 338 cities of China during the year 2016 and evaluates its effect on premature mortality and economic loss. It further illustrates the differences in cause-specific mortality outcomes of the log-linear and linear model, two of the prominently used methods for estimating health effects. In 2016, the annual average daily maximum 8-h O3 concentration in China ranged between 74 and 201 µg/m3 (138 ±â€¯24.7 µg/m3). 30% of the total population was exposed to >160 µg/m3 O3 concentration (Chinese national ambient air quality standard) and about 67.2% urban population lived in exposure above the WHO recommended O3 concentrations (100 µg/m3). The estimated national O3-attributable mortality was 74.2 × 103 (95% CI: 16.7×103-127×103) in the log-linear model, whereas, the total O3-related mortality using the linear model was 69.6 × 103 (95% CI: 16.2 × 103-115 × 103). The exposure to O3 caused a nationwide economic loss of about 7.6 billion US$ (range: 1.7-12.9) in 2016. This study uniquely provides most comprehensive coverage of the Chinese cities for O3 associated mortality utilizing ground level measurement data for 2016 and presents a measurable assessment to the policymakers of China for streamlining their efforts on air quality improvement and O3 containment.

Characteristics of indoor air pollution and estimation of respiratory dosage under varied fuel-type and kitchen-type in the rural areas of Telangana state in India.

Indoor Air Pollution (IAP) is one of the top environmental risks in developing countries including India, with more than a million deaths annually, predominantly through Particulate Matter (PM) exposure. The current study deals with the measurement of PM concentrations in rural households under varied fuel and kitchen-types, evaluation of the indoor air pollution (IAP) characteristics and estimation of respiratory dosage for the different subjects (women, young children and the elderly). Monitoring of particulate matter (PM) was carried out during summer, monsoon and winter season with biomass, LPG and combine of biomass and LPG being used as fuel for cooking. Furthermore, different types of indoor kitchens (with partition and without partition) and outdoor kitchens (separate enclose kitchen and open kitchen) were also considered as kitchen type along with fuel are two crucial factors contributing to IAP. Deposition fractions were calculated using Multiple Particle Path Dosimetry (MPPD) to study the deposition patterns in different parts of the human respiratory tract (HRT) - head, tracheobronchial and pulmonary for women, young children and the elderly people. Dosage of particulate matter was calculated by inputting the recorded PM measurements, a comparison made for biomass-LPG and dosage intensification due to the kitchen-type presented. While the biomass households exhibited high levels of dosage (1181.4 to 5891.7 µg) against the LPG households (89.9 to 811.2 µg), the indoor kitchen types exhibited a maximum intensification of 10.6 times than outdoor kitchens with the same fuel. This study not only establishes the IAP characteristics but also quantifies the role of fuel-type and kitchen-type in IAP. The study also indicates various measures that could be deployed to reduce dosage and thus minimize the health risks.

Application of multiple-path particle dosimetry model for quantifying age specified deposition of particulate matter in human airway.

Particulate matter (PM) is crucial among six criteria air pollutants, and it is frequently associated with human morbidity and mortality. According to the aerodynamic diameter, PM is classified as coarse (PM10) and fine (PM2.5). PM with these smaller sizes can easily enter and get deposited in the human airways. This deposited PM fraction commences the development of respiratory diseases such as asthma, chronic obstructive pulmonary disease, and even cancer. Thus, the quantification of PM deposition and its clearance in the human airway are essential for evaluating health risks. This study aims to investigate the size-segregated PM (PM10, PM2.5, and PM1) deposition in human lungs. Size-segregated PM is collected using the Grimm portable environmental dust monitor during winter season near an arterial road located in Chennai city of Tamil Nadu state, India. Multiple-Path Particle Dosimetry (MPPD) Model version 3.04 is utilized for quantifying PM deposition. In MPPD, airway structures of infants (3 and 28 months), children (3, 8, 9 and 14 years) and adults (18 and 21 years) are considered for the study. The values of PM concentration, body orientation, breathing scenario, tidal volume, pause fraction, inspiration fraction, and breathing frequency are specified in the MPPD for quantifying PM depositions. Results showed that 8-year children and 28 months infant groups are recorded with maximum and minimum size-segregated PM deposition respectively. The coarse particles (PM10) are primarily deposited in the head (55-95%) and tracheobronchial (3-44%) regions whereas fine particles (PM2.5 and PM1) depositions are observed maximum in the head (36-63%) and pulmonary (28.2-52.7%) regions. Except for the adult age group, PM2.5 has the maximum deposition percentage in tracheobronchial and pulmonary regions. In the case of lobar depositions, lower lobes receive maximum deposition (66.4%) than the upper (27.2%) and middle lobes (6.4%). PM2.5 dominated the deposition in all five lobes of infant, children, and adults. The clearance rate of deposited PM is high in the tracheobronchial region whereas it is low in the pulmonary region. This study also concludes that PM2.5 is the important size fraction in lung deposition. Further, the study results can be used for human health risk assessments such as oxidative potential and toxicity of deposited PM.