Demonstrating PM<Subscript>2.5</Subscript> and road-side dust pollution by heavy metals along Thika superhighway in Kenya,sub-Saharan Africa

This study assessed the level of heavy metal in roadside dust and PM_2.5 mass concentrations along Thika superhighway in Kenya. Thika superhighway is one of the busiest roads in Kenya, linking Thika town with Nairobi. Triplicate road dust samples collected from 12 locations were analysed for lead (Pb), chromium (Cr), cadmium (Cd), nickel (Ni), zinc (Zn), and copper (Cu) using atomic absorption spectrophotometry (AAS). PM_2.5 samples were collected on pre-weighed Teflon filters using a BGI personal sampler and the filters were then reweighed. The ranges of metal concentrations were 39–101 μg/g for Cu, 95–262 μg/g for Zn, 9–28 μg/g for Cd, 14–24 μg/g for Ni, 13–30 μg/g for Cr, and 20–80 μg/g for Pb. The concentrations of heavy metals were generally highly correlated, indicating a common anthropogenic source of the pollutants. The results showed that the majority of the measured heavy metals were above the background concentration, and in particular, Cd, Pb, and Zn levels indicated moderate to high contamination. Though not directly comparable due to different sampling timeframes (8 h in this study and 24 h for guideline values), PM_2.5 for all sites exceeds the daily WHO PM_2.5 guidelines of 25 μg/m³. This poses a health risk to people using and working close to Thika superhighway, for example, local residents, traffic police, street vendors, and people operating small businesses. PM_2.5 levels were higher for sites closer to Nairobi which could be attributed to increased vehicular traffic towards Nairobi from Thika. This study provides some evidence of the air pollution problem arising from vehicular traffic in developing parts of the world and gives an indication of the potential health impacts. It also highlights the need for source apportionment studies to determine contributions of anthropogenic emissions to air pollution, as well as long-term sampling studies that can be used to fully understand spatiotemporal patterns in air pollution within developing regions.     

Characterization of particulate matter and its related metal toxicity in an urban location in South West India

This study reports the quantification of the toxicity of particulate matter (PM)-bound metals and their possible associated risks to human health. For assessment of PM, 24-h samples of PM₁₀ and PM_2.5 were collected by Mini Vol-TAS sampler at an urban site of Pune. Samples were sequentially extracted with ultrapure water and concentrated HNO₃ and analyzed for “soluble” and “total” metals. Factor analysis identified the resuspension of road dust due to traffic, biomass burning, construction activities, and wind-blown dust as possible sources that played an important role for overall pollution throughout the year. Water-soluble proportion was found to be ≤20 % for Cr, Co, Fe, and Al; ≥50 % for Sr, Cd, Ca, and Zn; and a substantial proportion (～25–45 %) for Mn, Ba, K, Na, Ni, Mg, Cu, and Pb metals in PM₁₀. For PM_2.5, the water-soluble proportion was ≤20 % for Fe, Co, Ni, Cr, and Al, while Sr, K, and Cd were mostly soluble (>50 %) and Cu, Ba, Mn, Ca, Zn, Pb, Na, and Mg were substantially soluble (～25–45 %). In the present study, among the toxic metals, Cd and Pb show higher concentration in the soluble fraction and thus represent the higher bioavailability index and especially are harmful to the environment and exposed person. Risk calculations with a simple exposure assessment method showed that the cancer risks of the bioavailable fractions of Cr, Cd and Ni were greater than the standard goal.     

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao,Peru

The temporal and spatial trends in the variability of PM₁₀ and PM_2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM₁₀ and PM_2.5 have ranges (averages) of 133–45 μg m^?3 (84 μg m^?3) and 35–16 μg m^?3 (26 μg m^?3) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM_2.5 value is approximately 40% of the PM₁₀ value. This proportion can be explained by PM₁₀ re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM₁₀ concentrations on the order of ?4.3 and ?5.3% year^?1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM₁₀ and PM_2.5, respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount.     

Seasonal variation in ambient PM mass and number concentrations (case study: Tehran, Iran)

Tehran, the capital city of Iran, is an important industrial and commercial center. This city is one of the worst cities in the world in terms of air pollution, which is mostly due to mobile sources rather than stationary sources. Particulate matter (PM), which is a complex mixture of extremely small particles and liquid droplets, is considered as an important source of air pollution in Tehran. In this study, our objective was to study PM₁₀, PM_2.5, and PM_1.0 mass and number concentrations and find the correlations of these two parameters in the west-central parts of Tehran during two consecutive warm and cold seasons. The particles collected from five stations were analyzed for their mass and number simultaneously by a laser-based Grimm dust monitor. In general, it was found that the accumulation of the PM in this region is more in the cold season. PM₁₀ mass concentration increases almost twofold and PM_2.5 and PM_1.0 almost three times in this season. The mean number concentration of the particles (0.3–20 μm) was found to be almost 4.8 times in the cold season. It was also noticed that the average dimensions of the particles decrease in that season.     

Study of the PM<Subscript>10</Subscript> concentration variations along two intra-urban roads within a compact city

Eighty-five measurement campaigns were performed repeatedly to compare the concentration variation profiles along two intra-urban roads—one with open configuration and the other with street canyon effect. Fixed-effects panel data analysis was applied for formulating a model to express the PM₁₀ concentrations along intra-urban roads in terms of parameters like nearby central monitoring data, traffic counts and meteorological conditions with an objective to analyze the PM₁₀ concentration variation patterns along the two roads. Our findings reveal that traffic intensity and metrological conditions exert influence on concentration variation for both types of road configurations while wind velocity only affect the pollutants removal effectiveness of open road configuration. Further analysis unveils that the PM₁₀ concentration distribution profiles within a compact city environment are not always uniform and are dependent on the road configuration. Considerable PM₁₀ concentration differences were observed along the street canyon, and 70% of their variations are attributed to variations in their road aspect ratios. By contrast, no significant concentration difference is observed at open road configurations.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

Characteristics of ambient 1-min PM2.5 variation in Beijing

One-minute PM_2.5 concentration was obtained with LD-5C pocket microcomputer laser dust instrument from Dec. 15th, 2005 to Jan. 16th, 2006 and Mar. 17th to Apr. 28th, 2006 in Beijing. The concentration of SO₂, NO₂, O₃, CO, and PM₁₀ from Jan. 1st, 2001 to Dec. 31st, 2004 were obtained from the conversion of air pollution index. Results showed that all the pollutants showed cyclic characteristics. The longer yearly cycles was shown from SO₂, NO₂, O₃, CO, and PM₁₀, as the sampling time was 4-year long and daily collected. The shorter hourly and daily cycle was shown from 1-min PM_2.5, as the sampling time was about 1-month long and one collected at 1 min. The spectral density analysis confirmed this from the periodogram graphs. The longer yearly cycle (365, 180 days), the seasonal cycle (120, 60–90 days), and monthly cycle (21, 23, 27 days) of SO₂, NO₂, CO, O₃, and PM₁₀ were obviously shown. In addition, the shorter weekly cycle of 5–7 days is obviously shown, too. The shorter hourly cycle (8–12, 4–6, 3, 1–2 h, 20 min) of 1-min PM_2.5 was also indicated from spectral density analysis. Two major factors contribute the 1-min PM_2.5 cycles, i.e., the meteorological factors and source effects. Both the relative humidity and dew point showed consistent variation with PM_2.5, but the wind speed showed inverse variations with PM_2.5. Furthermore, the spectral density analysis of the meteorological factors (4–5, 2–2.5, 1–1.5 days, 12, 6–8, 3 h) may partially explain the cycles of PM_2.5. As for the sources effects, it can be shown from the strong dust storm of April 16–18th, 2006. PM_2.5 constantly increased tens and even hundreds of times high concentration within a few minutes due to the intensity of the dust sources.     

Assessment of indoor and outdoor particulate air pollution at an urban background site in Iran

The relationship between indoor and outdoor particulate air pollution was investigated at an urban background site on the Payambar Azam Campus of Mazandaran University of Medical Sciences in Sari, Northern Iran. The concentration of particulate matter sized with a diameter less than 1 μm (PM_1.0), 2.5 μm (PM_2.5), and 10 μm (PM₁₀) was evaluated at 5 outdoor and 12 indoor locations. Indoor sites included classrooms, corridors, and office sites in four university buildings. Outdoor PM concentrations were characterized at five locations around the university campus. Indoor and outdoor PM measurements (1-min resolution) were conducted in parallel during weekday mornings and afternoons. No difference found between indoor PM₁₀ (50.1 ± 32.1 μg/m³) and outdoor PM₁₀ concentrations (46.5 ± 26.0 μg/m³), indoor PM_2.5 (22.6 ± 17.4 μg/m³) and outdoor PM_2.5 concentration (22.2 ± 15.4 μg/m³), or indoor PM_1.0 (14.5 ± 13.4 μg/m³) and outdoor mean PM_1.0 concentrations (14.2 ± 12.3 μg/m³). Despite these similar concentrations, no correlations were found between outdoor and indoor PM levels. The present findings are not only of importance for the potential health effects of particulate air pollution on people who spend their daytime over a period of several hours in closed and confined spaces located at a university campus but also can inform regulatory about the improvement of indoor air quality, especially in developing countries.     

Seasonal variations and source profile of <Emphasis Type="Italic">n</Emphasis>-alkanes in particulate matter (PM<Subscript>10</Subscript>) at a heavy traffic site,Delhi

Delhi is one of the most polluted cities in the world. The generation of aerosols in the lower atmosphere of the city is mainly due to a large amount of natural dust advection and sizable anthropogenic activities. The compositions of organic compounds in aerosols are highly variable in this region and need to be investigated thoroughly. Twenty-four-hour sampling to assess concentrations of n-alkanes (ng/m³) in PM₁₀ was carried out during January 2015 to June 2015 at Indira Gandhi Delhi Technical University for Women (IGDTUW) Campus, Delhi, India. The total average concentration of n-alkanes, 243.7 ± 5.5 ng/m³, along with the diagnostic tools has been calculated. The values of CPI₁, CPI₂, and CPI₃ for the whole range of n-alkanes series, petrogenic n-alkanes, and biogenic n-alkanes were 1.00, 1.02, and 1.04, respectively, and C _max were at C₂₅ and C₂₇. Diagnostic indices and curves indicated that the dominant inputs of n-alkanes are from petrogenic emissions, with lower contribution from biogenic emissions. Significant seasonal variations were observed in average concentrations of n-alkanes, which is comparatively higher in winter (187.4 ± 4.3 ng/m³) than during the summer season (56.3 ± 1.1 ng/m³).     

Particulate matter concentration levels during intense haze event in an urban environment

This study assessed concentration levels of particulate matter (PM) in the ambient environment of Ilorin metropolis, Nigeria, during haze episodes. Meteorological data (wind speed and direction, rainfall data, sunshine data, relative humidity and temperature) were obtained. Aerocet 531S particle counter (MetOne Instruments, USA) was used to measure four mass concentration ranges of PM (PM_1.0, PM_2.5, PM₁₀ and the total suspended particles (TSP)) in 10 locations taking into consideration land use patterns. Surfer® version 8 (Golden Software LLC, USA) was used to model the spatial variation of particulate matter concentration levels using kriging interpolation griding method. Human exposure assessment was done using the total respiratory deposition dose (TRDD) estimates and statutory limit breach (SLB) approaches. The appearance of dominating weak southern atmospheric wind flow was observed as wind speed ranged from 0 to 6.811 m/s while solar radiation periods ranged from 0.3 to 3.5 h/day. The relative humidity of the metropolis ranged between 28 and 57%, while daily temperature was 15 to 36 °C. Highest concentration levels of PM measured were 73.4, 562.7, 7066.3 and 9907.8 μg/m³ for PM_1.0, PM_2.5, PM₁₀ and TSP, respectively. Very strong negative correlations existed between the PM concentration levels and microclimatic parameters. Spatial variation of the concentration level as modelled using Surfer® version 8 indicated that particulate concentration level increases from south to north. Concentration levels of PM for the 24-h averaging period were generally above the 24-h threshold limit value set by the regulatory agencies for all the locations.     

Influence of burning of fireworks on particle size distribution of PM<Subscript>10</Subscript> and associated Barium at Nagpur

Influence of burning of fireworks on particle size distribution of PM₁₀ and associated barium (Ba) were studied at a congested residential cum commercial area of Nagpur city, India. Sampling was carried out by cascade impactor having 50% cut-off aerodynamic diameters of <10, 9, 5.8, 4.7, 3.3, 2.1, 1.1, 0.7, and <0.4 μm, 2 days before diwali, during diwali, celebrations of marriage functions, and New Year’s Eve. Noticeably, increased levels of PM₁₀ and Ba were observed during diwali as compared to days before diwali and other activities. PM₁₀ levels were increased by four to nine times whereas Ba levels were increased by eight to 20 times higher in alveolar region, when compared with the levels observed before diwali. Probability of deposition of Ba mass in alveolar region varied between 14 and 27 ng/h with higher deposition when the burning of fireworks activity was lower near the site. Trimodal distribution of Ba was observed on the first 2 days of diwali at 0.4–2.1, 2.1–4.7, and 4.7 to less than PM₁₀ micrometer range. While on the third day, it appeared bimodal with 70% contribution in coarse fraction whereas on the fourth day, distribution appeared unimodal with 66% contribution in alveolar region (<0.4–1.1 μm). Distribution of Ba varied with respect to particle size, in accordance with the intensity of the fireworks used on different days and distance between the burning of firecrackers from the monitoring site.     

Aerosol characteristics of different types of episode

Daily and hourly average data from nine air-quality monitoring stations distributed across central Taiwan, which include ten items (i.e., PM₁₀, PM_2.5, wind direction, wind speed, temperature, relative humidity, SO₂, NO₂, NO, and CO), were collected from 2005 to 2009. Four episode types: long-range transport with dust storms (DS), long-range transport with frontal pollution (FP), river dust (RD), and stagnant weather (SW), and one mixed type of episode were identified. Of these four episode types, the SW was the dominant type, averaging about 70 %. The mean ratio of PM_2.5/PM₁₀ was the lowest during the RD episodes (0.42), while the mean ratio of PM_2.5/PM₁₀ was the highest during the SW episodes (0.64). Fine aerosol (PM_2.5) and coarse aerosol (PM_10–2.5) samples were collected by high-volume samplers for chemical composition analysis, from only three stations (Douliou, Lunbei, and Siansi) during the days of SW, RD, DS, and FP. The concentrations of PM_2.5 and three ionic species (NH₄ ⁺, NO₃ ^?, and SO₄ ^2?) all showed significant differences among the four episode types. The highest levels of NO₃ ^? (12.1 μg/m³) and SO₄ ^2? (20.5 μg/m³) were found during the SW and FP episodes, respectively. A comparison on the spatial similarity of aerosol compositions among the episodes and/or non-episodes (control) was characterized by the coefficient of divergence (CD). The results showed higher CD values in PM_10–2.5 than in PM_2.5, and the CD values between RD episodes and the other three episodes were higher than those between two types of episode for the other three episodes. The ratios of SOR (sulfur oxidation ratio), SO₄ ^2?/EC (elemental carbon), NOR (nitrogen oxidation ratio), and NO₃ ^?/EC showed that sulfate formation was most rapid during the FP, while nitrate formation was most rapid during the SW.     

Acidic and basic properties and buffer capacity of airborne particulate matter in an urban area of Beijing

Particles with aerodynamic diameters <10  $\upmu $ m (PM₁₀) and particles with aerodynamic diameters <2.5  $\upmu $ m (PM_2.5) were sampled during summer 2006 in Beijing and mass concentrations, water-soluble ionic compounds concentrations, and acidic buffer capacity were analyzed. Results show that the mass concentration ranges of PM₁₀ and PM_2.5 were from 56.4 to 226.6  $\upmu $ g/m³ and from 31.3 to 200.7  $\upmu $ g/m³ during sampling days, respectively. Concentrations of F^???, Cl^???, NO $_{3}^{\,\,-}$ , NO $_{2}^{\,\,-}$ , SO $_{4}^{\,\,2-}$ , Ac^???, Ca^2?+?, Na^?+?, K^?+?, Mg^2?+?, and NH $_{4}^{\,\,+}$ in particles were analyzed by ion chromatography. Microtitration was adapted to determine the acidic?Cbasic property and the change of the buffering systems in different pH of the aqueous solution in which the PM is suspended. The major alkalinity and buffer capacity of particles were analyzed and calculated. The average carbonate buffer capacity was 0.3 mmol/g in PM_2.5 and 0.7 mmol/g in PM₁₀. The average acetic acid buffer capacity was 0.1 mmol/g in PM_2.5 and 0.3 mmol/g in PM₁₀. Carbonate and acetic acid are the main species for the buffer capacity in the particle phase. The average mass of carbonate was 71.0 mg/g in PM₁₀ and 46.7 mg/g in PM_2.5. The average mass of acetic acid was 11.2 mg/g in PM_2.5 and 20.0 mg/g in PM₁₀.     

Particulate matter concentration in ambient air and its effects on lung functions among residents in the National Capital Region, India

The World Health Organization has estimated that air pollution is responsible for 1.4 % of all deaths and 0.8 % of disability-adjusted life years. NOIDA, located at the National Capital Region, India, was declared as one of the critically air-polluted areas by the Central Pollution Control Board of the Government of India. Studies on the relationship of reduction in lung functions of residents living in areas with higher concentrations of particulate matter (PM) in ambient air were inconclusive since the subjects of most of the studies are hospital admission cases. Very few studies, including one from India, have shown the relationship of PM concentration and its effects of lung functions in the same location. Hence, a cross-sectional study was undertaken to study the effect of particulate matter concentration in ambient air on the lung functions of residents living in a critically air-polluted area in India. PM concentrations in ambient air (PM_1, PM_2.5) were monitored at residential locations and identified locations with higher (NOIDA) and lower concentrations (Gurgaon). Lung function tests (FEV₁, PEFR) were conducted using a spirometer in 757 residents. Both air monitoring and lung function tests were conducted on the same day. Significant negative linear relationship exists between higher concentrations of PM₁ with reduced FEV₁ and increased concentrations of PM_2.5 with reduced PEFR and FEV₁. The study shows that reductions in lung functions (PEFR and FEV₁) can be attributed to higher particulate matter concentrations in ambient air. Decline in airflow obstruction in subjects exposed to high PM concentrations can be attributed to the fibrogenic response and associated airway wall remodeling. The study suggests the intervention of policy makers and stake holders to take necessary steps to reduce the emissions of PM concentrations, especially PM_1, PM_2.5, which can lead to serious respiratory health concerns in residents.     

Atmospheric aerosols at a regional background Himalayan site—Mukteshwar, India

Continuous aerosol measurements were made at a regional background station (Mukteshwar) located in a rural Himalayan mountain terrain from December 2005 to December 2008 for a period of 3 years. The average concentrations of particulate matter less than or equal to 10 μm (PM₁₀), particulate matter less than or equal to 2.5 μm (PM_2.5) and black carbon (BC) are 46.0, 26.6 and 0.85 μg/m³ during the study period. Majority of the PM₁₀ values lie below 100 μg/m³ while majority of the PM_2.5 values lie below 30 μg/m³. It is further seen that during the monsoon months, especially July and August, the average values are comparatively low. It is also noted that the PM_2.5/PM₁₀ ratios between 0.50 and 0.75 have the maximum frequency distribution in the data set. Furthermore, the monthly mean ratio of BC to PM_2.5 mass lies between 3.0 and 7.5 % during the study period. Though the average PM₁₀ and PM_2.5 concentrations during the study period are less than the respective Indian ambient air quality standards, however, they are still above the WHO guidelines and would have adverse health impacts. This shows that even in rural/background regions that are far away from major pollution sources or urban areas, the aerosol concentrations are significant and require long-term monitoring, source quantification and aerosol model simulations.     

Chemical composition of ambient particulate matter and redox activity

Exposure to ambient particulate matter (PM) has been associated with a number of adverse health effects. Increasing studies have suggested that such adverse health effects may derive from oxidative stress, initiated by the formation of reactive oxygen species (ROS) within affected cells. The study aimed to assess physical characteristics and chemical compositions of PM and to correlate the results to their redox activity. PM_2.5 (mass aerodynamic diameter ≤2.5 μm) and ultrafine particles (UFPs, mass media aerodynamic diameter <0.1 μm) were collected in an urban area, which had heavy traffic and represented ambient air pollution associated with vehicle exhaust. Background samples were collected in a rural area, with low traffic flow. Organic carbon (OC), elemental carbon (EC), polycyclic aromatic hydrocarbons (PAHs), and metals were analyzed. The dithiothreitol activity assay was used to measure the redox activity of PM. Results showed that UFPs have higher concentrations of OC, EC, and PAHs than those of PM_2.5. Several metals, including Fe, Cu, Zn, Ti, Pb, and Mn, were detected. Among them, Cu had the highest concentrations, followed by Fe and Zn. Organic carbon constituted 22.8% to 59.7% of the content on the surface of PM_2.5 and UFPs. Our results showed higher redox activity on a per PM mass basis for UFPs as compared to PM_2.5. Linear multivariable regression analyses showed that redox activity highly correlated with PAH concentrations and organic compounds, and insignificantly correlated with EC and metals, except soluble Fe, which increased redox activity in particle suspension due to the presence of ROS.     

Inter-seasonal and spatial distribution of ground-level greenhouse gases (CO<Subscript>2</Subscript>, CH<Subscript>4</Subscript>, N<Subscript>2</Subscript>O) over Nagpur in India and their management roadmap

Ground-level concentrations of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) were monitored over three seasons, i.e., post-monsoon (September–October), winter (January–February), and summer (May–June) for 1 year during 2013–2014 in Nagpur City in India. The selected gases had moderate to high variation both spatially (residential, commercial, traffic intersections, residential cum commercial sites) and temporally (at 7:00, 13:00, 18:00, and 23:00 hours in all three seasons). Concentrations of gases were randomly distributed diurnally over city in all seasons, and there was no specific increasing or decreasing trend with time in a day. Average CO₂ and N₂O concentrations in winter were higher over post-monsoon and summer while CH₄ had highest average concentration in summer. Observed concentrations of CO₂ were predominantly above global average of 400 ppmv while N₂O and CH₄ concentrations frequently dropped down below global average of 327 ppbv and 1.8 ppmv, respectively. Two-tailed Student’s t test indicated that post-monsoon CO₂ concentrations were statistically different from summer but not so from winter, while difference between summer and winter concentrations was statistically significant (P < 0.05). CH₄ concentrations in all seasons were statistically at par to each other. In case of N₂O, concentrations in post-monsoon were statistically different from summer but not so from winter, while difference between summer and winter concentrations was statistically significant (P < 0.05). Average ground-level concentrations of the gases calculated for three seasons together were higher in commercial areas. Environmental management priorities vis a vis greenhouse gas emissions in the city are also discussed.     

基于不同时间尺度综合指数贡献率的攀枝花市大气污染特征分析

选取2016—2022年攀枝花市环境空气质量监测数据，基于年度、季度、月度、小时时间尺度评价环境空气质量综合指数贡献率。结果表明，攀枝花市污染类型已由传统的单一工业型污染转变为复合型污染，且污染物在不同时间尺度下的分布特征明显。从季度尺度来看，第一季度细颗粒物(PM_2.5)综合指数贡献率较大，第二和第三季度臭氧(O₃)综合指数贡献率较大，第四季度二氧化氮(NO₂)及PM_2.5综合指数贡献率较大。从月度尺度来看，O₃在3—8月的贡献较大，PM_2.5、NO₂、可吸入颗粒物(PM₁₀)、一氧化碳(CO)、二氧化硫(SO₂)在1—2月及11—12月的贡献较大。从小时尺度来看，O₃在13—19点贡献较大，PM₁₀、PM_2.5、CO在8—13点贡献较大，SO₂在9—13点贡献较大，NO₂在8—1...     

空气自动监测中PM2.5与PM10 “倒挂”现象特征及原因

采用不同原理的自动监测仪器在不同季节同时测定PM2.5与PM10,对所得数据中的PM2.5与PM10"倒挂"现象进行分析。结果表明,当PM10采用振荡天平法时,PM2.5与PM10的"倒挂"率较高;冬季和夏季"倒挂"现象发生率明显高于其他季节;造成PM2.5与PM10"倒挂"的原因主要有监测过程中的随机误差,PM2.5与PM10的监测方法原理不同,监测方法之间存在显著差异等。     

Distribution of PM2.5 and PM10-2.5 in PM10 Fraction in Ambient Air Due to Vehicular Pollution in Kolkata Megacity

This research paper aims at establishing baseline PM₁₀ and PM_2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM_2.5) and coarser fractions (PM_10-2.5) to PM₁₀ fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM₁₀ concentration was 304 μg/m³, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM₁₀ concentration was due to fine fraction (PM_2.5) released by vehicular exhaust. The 24h average PM_2.5 concentration was found 179 μg/m³, which is exceeded USEPA and EU standards of 65 and 50 μg/m³ respectively for the winter. India does not have any PM_2.5 standards. The 24 h average PM_10-2.5 concentrations were found 126 μg/m³. The PM_2.5 constituted more than 59% of PM₁₀ and whereas PM₁₀-PM_2.5 fractions constituted 41% of PM₁₀. The correlation between PM₁₀ and PM_2.5 was found higher as PM_2.5 comprised major proportion of PM₁₀ fractions contributed by vehicular emissions.