Ecological model analysis of respiratory health risk factors by ambient air pollution in Lucknow,the capital City of Uttar Pradesh,India

Ambient air pollution, particularly in the urban environment of developing countries, has turned out to be a major health risk factor. We explore the compounded impact of age sensitivity, exposure, poverty, co-morbidity, etc., along with composite air pollution in determining morbidity and health burden of people in Lucknow, India. This cross-sectional study is confined to analyse respiratory health status across different socio-economic and geographic locations using n = 140 in-depth questionnaire method. We used mean daily ambient air pollution data of PM₁₀, PM_2.5, SO_2, and NO₂ for the 2008–2018 period. We used the ecological model framework to assess the risk at different hierarchical levels and compounded severity on a spatial scale. We also used Logistic regression model with log odds and odds ratio to analyze the association of risks outcomes with composite air pollution scores calculated using the principal component analysis method. There is a strong association of location-specific respiratory disease prevalence with an overall 32 percent prevalence. The prevalence of ecological model 1 (individual domain) is 4.3 percent, while ecological model 2 (community domain) has the highest prevalence at 32.4 percent. The logistic regression model shows that respiratory disease load is positively associated with age sensitivity (P < .001) and composite pollution level (P < .001). For another model with suffocation as the outcome variable, composite pollution level (P < .001) and exposure (P < .001) are positively associated. Optimum interventions are required at Ecological models 1, 2, and 3 levels for better respiratory health outcomes.

     

Research Progress on the Impact of Urbanization on Climate Change

The world has been undergoing a remarkable process of urbanization, especially in developing countries in recent years. The urbanization process has brought about great urban development and large population agglomeration, changes in production and lifestyle, and man-made disturbances such as greenhouse gas and pollution emissions. As the global urbanization process continues to advance, its impact on climate change continues to strengthen significantly. This paper mainly reviewed and summarized relevant researches from two aspects: the influence of urbanization on climate change and the mechanism of influence of urbanization on climate change. Urbanization causes regional warming and urban heat island effect, extreme events such as high temperature, heat wave and heavy rainfall increase in frequency, and also leads to increased urban flood risk. The increase of pollutant emission in the process of urbanization is the main cause of air quality deterioration. Urbanization also has an indirect impact on air quality by changing urban climate. Urbanization has an important impact on climatic factors such as relative humidity, wind speed, sunshine and cloud cover. The impacts of urbanization on climate change are mainly realized through underlying surface changes, greenhouse gas and pollution emissions, anthropogenic heat emissions and urban high heat capacity. Urbanization not only directly affects the regional/local climate, but also indirectly affects the regional/local climate by promoting global climate change. Therefore, the impact of urbanization on climate change has a global and regional multi-scale superposition effect.     

Tree-ring growth recovers,but δ13C and δ15N do not change,after the removal of point-source air pollution: a case study for poplar (Populus cathayana) in northwestern China

Pollution from urban centers and fossil fuel combustion can decrease forest growth and interfere with physiological processes. To evaluate whether tree growth and the carbon isotope ratio (δ¹³C) and nitrogen isotope ratio (δ¹⁵N) in tree rings can serve as proxies for air pollution, this study compared these indices for poplar (Populus cathayana) growing at urban and suburban locations in Lanzhou, in northwestern China. Basal area increment values were much lower at the urban site than in the suburbs from 1985 to 2009, were negatively correlated with NO₂ (r = ?0.56, p < 0.01) and SO₂ (r = ?0.52, p < 0.05) emissions from 1990 to 2009, and increased abruptly after the Lanzhou urban steel factory closed. Urban tree-ring δ¹³C values were not significantly correlated with NO₂ and SO₂ concentrations, and did not differ significantly between the two sites, indicating that other environmental effects (such as precipitation) masked the pollution effects. Tree-ring δ¹⁵N values in the urban samples were much higher than the suburban values. Such differences may be attributable to uptake of ¹⁵N-enriched compounds caused by a higher urban N deposition rate. Tree growth is a promising tool for detecting ecophysiological responses of trees to both diffuse and point-source air pollution, but δ¹³C and δ¹⁵N in poplar were not sensitive to point-source air pollution in a heavily polluted environment.     

Application of GAINS model for assessing selected air pollutants in Khyber Pakhtunkhwa and Balochistan,Pakistan

Pakistan is a developing country existing geographically at a pivoted location between two of the world’s largest pollution emitting countries (China and India) which adds to the severity of environmental issues faced by the country. These concerns include air pollution, climate change, and extreme weather situations prevailing in Pakistan. This increasing air pollution is deteriorating the health, threatening the food security and adding up its share to the already existing global warming. The initial step in devising a wide ranging, multifaceted, economically feasible, and sustainable solution to deal with the severity of this issue is the quantification of the air pollution and greenhouse gas emission in Pakistan. The GAINS model is one of the most comprehensive tools, dealing with the air pollutants and greenhouse gases covered by the Kyoto Protocol. This study has utilized this model to analyze the source-based anthropogenic emissions of air pollutants (NH₃ and SO₂), volatile organic compounds (VOCs), and greenhouse gases (CH₄ and CO₂), their impacts and abatement cost, for the duration of 1990–2030, in the Khyber Pakhtunkhwa and Balochistan regions of Pakistan. An overall increasing trend was observed during 1990–2030 for (a) air pollutants: NH₃ (223.52–568.87kT/Y); SO₂ (50.52–332.95kT/Y), (b) VOCs (121.76–246.81kT/Y), and (c) greenhouse gases: CO₂ (7.83–62.45MT/Y) and CH₄ (1120-2314kT/Y). The emission inventories created for all greenhouse gases together estimated the increase of 42.37 to 138.57 MTCO₂eq. for greenhouse gases over the time duration of 1990–2030.     

Present environment and historic changes from the record of lake sediments, Dhaka City, Bangladesh

Changes in the urban environment of Dhaka City have been evaluated from the geochemical compositions of bottom sediments from two lakes, Gulshan-1 and –2. Abundances of Pb, Zn, Fe₂O₃ and total sulfur in a Gulshan-1 core gradually increase toward the sediment–water interface. Three stages of condition change can be recognized in Gulshan-1, based on trace metal concentration patterns. The basal Stage I corresponds to background Dhaka sedimentation, whereas gradual increase in Stage II represents the beginning of pollution. Marked increases in Pb and Zn in Stage III reflect rapid urban development and increased emissions to the atmosphere. The condition of the Dhaka environment is compared to that of Japan based on Zn–Fe₂O₃ and Pb–Fe₂O₃ relations. Zn–Fe₂O₃ ratios in Stage I Dhaka sediments are similar to normal Japanese sediments, whereas Stage II data lie on the same trend as Japan urban sediments. Dhaka Stage III samples have greater Zn:Fe₂O₃ ratios than Japanese urban sediments, suggesting Zn pollution from poorly-controlled industrial sources. In contrast, the Dhaka Pb–Fe₂O₃ trend lies between normal and urban Japanese sediments. Although vehicle emissions in Dhaka are now significant, the data suggest that Pb pollution from this source remains in its early stages.     

Stress of urban energy consumption on air environment

With rapid urbanization and heavy industrialization as well as the rapid increase of cars in China, the effect of energy consumption on urban air environment is increasingly becoming serious, and has become a hot topic for both scholars and decision-makers. This paper explores the effect mechanism and regulation of urban energy consumption on the air environment, and summarizes the framework of the stress effect relationship and the evolutionary process. In accordance with the effect relationship of the internal factors between the two, analytic approaches studying the stress effect of urban energy consumption on air environment are proposed, including the analysis of air environment effects caused by urban energy consumption structure change, and the analysis of air environment effects caused by urban energy economic efficiency change, as well as a decomposition analysis of air pollutant emission caused by urban energy consumption. Applying the above-mentioned approaches into a case study on Beijing City, this paper analyzes the effect relationship among urban energy consumption structure improvement, energy economic efficiency increase and air quality change since the period when Beijing City officially proposed to bid for the 2008 Olympic Games in 1998. In addition, it further analyzes the effect and contribution of urban industrial activity level, industrial economic structure, industrial energy intensity, and industrial energy structure as well as emission coefficients on the change in industrial SO₂ emission, which can provide valuable information to the government for making comprehensive environmental policies, with the use of the logarithmic mean Divisia index (LMDI) method. It is shown that under the precondition that the industrial economy maintain a continuous and rapid increase, improvements in energy intensity and a decline in emission coefficients are the main means for reducing Beijing’s industrial SO₂ emissions.     

Transboundary air pollution and environmental justice: Vancouver and Seattle compared

This paper comparatively analyzes the association between urban neighborhood socioeconomic markers and ambient air pollution in Vancouver and Seattle, the two largest urban regions in the Georgia Basin-Puget Sound (GB-PS) international airshed. Given their similarities and common airshed, Vancouver and Seattle are useful comparators addressing not only whether socioeconomic gradients exist in urban environmental quality but also identifying clues to differences in these gradients between Canadian and American cities. Large air quality sampling campaigns and pollution regression mapping provide the pollution data, in this case nitrogen dioxide—a marker of traffic emissions considered the most important air pollutant for human health in the typical North American city. Pollution data are combined with neighborhood census data for regression and spatial analyses. Median household income is the most consistent correlate of air pollution in both cities, including their most polluted neighborhoods, although neighborhoods marked by immigrant populations do not correlate with high pollution levels in Vancouver as they do in Seattle.     

GIS-based DRASTIC model for groundwater vulnerability and pollution risk assessment in the Peshawar District,Pakistan

Groundwater is the most economic natural source of drinking in urban and rural areas which are degraded due to high population growth and increased industrial development. We applied a GIS-based DRASTIC model in a populated urban area of Pakistan (Peshawar) to assess groundwater vulnerability to pollution. Six input parameters—depth to phreatic/groundwater level, groundwater recharge, aquifer material, soil type, slope, and hydraulic conductivity—were used in the model to generate the groundwater vulnerable zones. Each parameter was divided into different ranges or media types, and ratings R?=?1?–?10 were assigned to each factor where 1 represented the very low impact on pollution potential and 10 represented very high impact. Weight multipliers W?=?1?–?5 were also used to balance and enhance the importance of each factor. The DRASTIC model scores obtained varied from 47 to 147, which were divided into three different zones: low, moderate, and high vulnerability to pollution. The final results indicate that about 31.22, 39.50, and 29.27% of the total area are under low, moderate, and high vulnerable zones, respectively. Our method presents a very simple and robust way to assess groundwater vulnerability to pollution and helps the decision-makers to select appropriate landfill sites for waste disposals, and manage groundwater pollution problems efficiently.     

Estimation of number of deaths associated with exposure to excess ambient PM10 air pollution

The respirable particle matter (PM₁₀) concentration in urban areas has been a chronic cause concern and principal reason for increased morbidity rate among resident population. The present study aimed at estimating a discrete event like mortality rate associated and attributable to excess particulate matter pollution in the Kathmandu Valley area. The Government of Nepal conducts air monitoring of particulates at its air monitoring site network covering valley area. Adopting the data available with respect to PM₁₀ and with several other considerations like cutoff value for PM₁₀, mean annual concentration, demographic data of valley, exceedance to the reference cutoff value, attributable fraction evolution and computation relative risk attributable to PM₁₀ was computed. Assumption was made about the relative risk of long-term average PM₁₀ exposure on natural mortality estimated and reported from a previous study. The estimation or mortality rate in our case was 0.95% after all these considerations and computation. This implies that 95 deaths out of 10,000 deaths are due to particulate pollution existing in the Kathmandu Valley Area.     

Lockdown during COVID-19 pandemic: A case study from Indian cities shows insignificant effects on persistent property of urban air quality

The influence of reduction in emissions on the inherent temporal characteristics of PM_2.5 and NO₂ concentration time series in six urban cities of India is assessed by computing the Hurst exponent using Detrended Fluctuation Analysis (DFA) during the lockdown period (March 24–April 20, 2020) and the corresponding period during the previous two years (i.e., 2018 and 2019). The analysis suggests the anticipated impact of confinement on the PM_2.5 and NO₂ concentration in urban cities, causing low concentrations. It is observed that the original PM_2.5 and NO₂ concentration time series is persistent but filtering the time series by fitting the autoregressive process of order 1 on the actual time series and subtracting it changes the persistence property significantly. It indicates the presence of linear correlations in the PM_2.5 and NO₂ concentrations. Hurst exponent of the PM_2.5 and NO₂ concentration during the lockdown period and previous two years shows that the inherent temporal characteristics of the short-term air pollutant concentrations (APCs) time series do not change even after withholding the emissions. The meteorological variations also do not change over the three time periods. The finding helps in developing the prediction models for future policy decisions to improve urban air quality across cities.     

基于STIRPAT模型的甘肃省交通碳排放测算及影响因素分析

依据IPCC清单指南的数据, 采用"自上而下"的碳排放计算方法, 对2000-2013年甘肃省交通碳排放进行测算, 对交通碳排放总量、人均量、交通能源碳排放结构及碳排放强度进行动态分析. 基于STIRPAT模型, 运用岭回归统计方法对甘肃省交通碳排放影响因素进行定量分析. 结果表明: 甘肃省交通碳排放总量和人均碳排放量都呈逐年上升的趋势; 煤炭、汽油、柴油、电力四种能源消费的碳排放量占交通碳排放量的绝大部分; 交通碳排放强度呈下降趋势; 城镇化水平、客运周转量、货运周转量、人均GDP每增长1%, 导致交通碳排放分别增长0.221%、0.137%、0.174%和0.125%. 建设低碳交通体系将成为甘肃省交通部门减碳的有效途径.     

The impact of model resolution on simulated ambient air quality and associated human exposure

A simple numerical experiment to evaluate the influence of model resolution on estimates of ambient air quality and associated human exposure is presented. This is done based on annual mean NO₂ concentration fields for the agglomeration of Brussels and surroundings, simulated by the deterministic urban/regional-scale AURORA model at a resolution of 1 km. These NO₂ concentration fields were used to calculate domain-wide exposure, which is defined here as the population density-weighted concentration. It was found that exposure decreased by 38% when degrading the resolution of the model from 1 to 64 km. A straightforward analysis revealed that this exposure reduction could be explained by the covariance between the concentration and population density patterns.     

Estimation of N2O emission from tea garden soils, their adjacent vegetable garden and forest soils in eastern China

The objective of this study was to investigate nitrous oxide (N₂O) emissions from different land-use types in eastern China. The dynamic changes of N₂O emissions were investigated in tea gardens with different nitrogen application rates, their adjacent vegetable garden and forest soils from June 2009 to May 2010. The results showed that high nitrogen application in a tea garden significantly increased soil N₂O emissions. Lower N₂O emission and percentage of N₂O–N to the applied N were observed in a tea garden with low N application than that from vegetable garden, indicating reasonable control of N application can efficiently decrease N₂O pollution in tea gardens. Both air and soil temperature had significant and positive impact on N₂O emissions, but little effect of precipitation was observed. Therefore, N application rate and environmental temperature are the most essential factors in influencing N₂O emission and should be taken into consideration in the field management of tea production.     

The nexus between income inequality,economic growth and environmental degradation in Pakistan

This study examines the impact of income inequality and economic growth on environmental degradation in Pakistan using ARDL bounds testing approach for the period 1966–2011. Empirical results for the aggregate CO₂ emissions and its four sources such as CO₂ emissions from solid fuel, liquid fuel and gaseous fuel consumption as well as electricity and heat production confirm the existence of long run co-integrated relationship between income inequality, economic growth and environment degradation. The estimated results indicate that carbon emissions increase as the income gap expands in Pakistan. Besides the negative impact of industrial share and population density on CO₂ emissions, we also confirm that economic growth in Pakistan comes up with higher emissions. Hence, the hypothesis of EKC is not valid for Pakistan during the study period. Our empirical findings are robust as evidenced by dynamic ordinary least squared and the U-tests. Overall, this study suggests that the distribution of income matters to aggregate carbon emissions and focus should be made on sustained economic growth to reduce pollutants and hence CO₂ emission in the study area.     

Impact of household expenditures on CO2 emissions in China: Income-determined or lifestyle-driven?

The aim of this paper is to analyze the relationship between household expenditure and CO₂ emissions among different income groups of urban and rural households in China. Having employed the 2007 Social Accounting Matrix of China, this study examines the direct and indirect CO₂ emissions caused by household demand. The results show that within both urban and rural households, the higher the income level is, the higher the per capita emissions are; the CO₂ emissions per unit expenditure due to savings and taxes are generally much larger than those from consumption of goods and services; and these emissions per unit consumption expenditures mainly come from indirect emissions. To deeply explore the relationships between consumption patterns and CO₂ emissions, two scenarios are established to eliminate the differences in income level and consumption propensity among different groups step by step. Main results indicate that (1) the income gap is the primary cause of the significant differences in emission levels among each group; (2) the difference in consumption propensity is also a notable reason; and (3) the rural higher income groups spend a larger share of their income on those carbon-intensive goods (e.g., electricity, transportation, energy products), thus making their consumption patterns more carbon-intensive, while for the urban, the consumption patterns of lower income groups are more carbon-intensive. Finally, policy recommendations on the reduction of household emissions are also made.

     

Assessment of ambient air quality in Bishnumati corridor, Kathmandu metropolis

The Kathmandu valley urban area is growing as a metropolis. Bishnumati corridor in Kathmandu valley is is a target of increased pollution. The unabated solid waste land-filling on either side of the river-bank and animal slaughter houses and biological waste arising from these activities, busy commercial and high residential density characterize the corridor. Six areas, namely Teku Dovan, Kalimati Bridge, Kankeswori, Shova Bhagwati, Balaju and New Bus Park areas, all areas falling within the Bishnumati corridor were selected to measure air quality representing corridor. The pollutants quantified were respirable particulate matter — PM₁₀, sulphur dioxide and oxides of nitrogen. The air-borne microbial flora and fungi load quantification were also carried out. Teku Dovan (918.92 μg/m³) and Shovabhagavati areas (847.45 μg/m³) showed higher levels of particulates. Kankeswori area showed highest levels of aerial bacterial (3.7×10⁷ cfu/m³) and fungal load (4.8×10⁸ cfu/m³). The PM₁₀ levels at all the sites are substantial and fall in the categories of ’Harmful’ and ’Hazardous’ quality of air suggesting that the corridor needing intervention to minimize the risk from air pollution. Non-judicious open-air combustion of the solid waste contributes to air pollution. Heavy traffic and few roads not clad with asphalt; perceivable mal-odor and persistent stench emanating from the indiscriminate disposal and consequent putrefaction processes, dense population and increased commercial activities are other principal contributing sources to the resulting pollution of the corridor. In view of this status, mitigating measures to minimize exposure to the toxicants in the corridor is a necessity.     

Traffic-related immissions and their impact on historic buildings: implications from a pilot study at two German cities

Besides the enormous improvement of air quality in Germany due to the reduction of sulphur dioxide emissions in the last decades, high immissions of nitrogen oxides and fine particulate matter are frequently observed at traffic-rich urban sites. The changed chemical composition of air pollution requires a new investigation of its impact on historic buildings constructed of natural stone. In a pilot study a multi-disciplinary approach was chosen to obtain information on the actual pollution situation of historic buildings and monuments at traffic hotspots in Germany. The study concentrated on the two German cities of Munich and Mainz of different size, traffic volume and stone inventory. Dose–response functions were calculated to demonstrate the change of impact of different pollutants over the last three decades, and for comparison of traffic hotspots and housing areas of both cities. Numeric modelling on a city-scale was used to identify the historic buildings and monuments affected by elevated traffic immissions. Because a relevant part of these pollutants is dominated by short-range transport, the differences of wind speed and deposition rates were calculated using a street-scale 3D flow and dispersion model regarding traffic volume, wind regime and adjacent buildings. Finally, particulate matter was sampled at different positions of two buildings heavily exposed to traffic emissions. Individual particles were investigated by environmental scanning electron microscopy. After classification of the particles into different chemical groups, the fraction of traffic-induced particulate matter was quantified. Summarizing the results, it must be stated that soiling by traffic-related particulate matter, deposition of nitrates deriving from exhaust emission and other diffusely emitted components bear a severe damage potential for natural building stone at least locally at traffic-rich urban sites.     

Contamination and potential mobility assessment of heavy metals in urban soils of Hangzhou,China: relationship with different land uses

Concentration and distribution of heavy metals (Cd, Cu, Pb and Zn) in urban soils of Hangzhou, China, were measured based on different land uses. The contamination degree of heavy metals was assessed on the basis of pollution index (PI), integrated pollution index (IPI) and geoaccumulation index (I _geo). The 0.1 mol l⁻¹ HCl extraction procedure and gastric juice simulation test (GJST) were used to evaluate the potential mobility and environmental risk of heavy metals in urban soils. The average concentration of Cd, Cu, Pb and Zn in urban soils was measured at 1.2 (with a range of 0.7–4.6), 52.0 (7.4–177.3), 88.2 (15.0–492.1) and 206.9 (19.3–1,249.2) mg kg⁻¹, respectively. The degree of contamination increased in the order of industrial area (IA) > roadside (RS) > residential and commercial areas (RC) > public park and green areas (PG). The PIs for heavy metals indicated that there is a considerable Cd, Cu, Pb and Zn pollution, which originate from traffic and industrial activities. The IPI of these four metals ranged from 1.6 to 11.8 with a mean of 3.5, with the highest IPI in the industrial area. The assessment results of I _geo also supported that urban soil were moderately contaminated with Cd and to a lesser extent also with Cu, Pb and Zn. The IP and I _geo values reveal the pollution degree of heavy metal was the order of Cd > Pb > Zn ≈ Cu. It was shown that mobility and bioavailability of the heavy metals in urban soils increased in the order of Cd > Cu > Zn ≈ Pb. Owing to high mobility of Cd and Cu in the urban soils, further investigations are needed to understand their effect on the urban environment and human health. It is concluded that industrial activities and emissions from vehicles may be the major source of heavy metals in urban contamination. Results of this study present a rough guide about the distribution and potential environmental and health risk of heavy metals in the urban soils.     

Detection of a sulfur dioxide signal in a tree-ring record: a case study from Trail,British Columbia,Canada

Dendroecological analysis of tree-ring chronologies was used to determine radial growth responses of a western larch (Larix occidentalis Nutt.) stand to climate and ambient SO₂ exposure. A unique, 32-year long record of ambient SO₂ concentrations was exploited to estimate annual SO₂ dose with a 0.25 ppm threshold. Tree-ring data were a subset from a previous study including three control sites and one polluted site that was near the location of the SO₂ monitor. An autoregression model was employed in a stagewise procedure that first removed climate effects by autoregression on the average of the controls and then estimated a dose-response relationship by autoregression of the residuals from the first stage on SO₂ exposure. Significant growth losses from air pollution were demonstrated that were approximately equal in magnitude to the variation explained by annual fluctuations of climate.     

The characteristics of air pollutants during different seasons in the urban area of Lanzhou,Northwest China

Based on data from ground-based air quality stations, space–time variations of six principal atmospheric pollutants, such as particulate matter (PM_2.5 and PM₁₀) and gas pollutants (SO₂, NO₂, СО, and O₃), obtained from January 1, 2014 to December 31, 2017 in the city of Lanzhou, have been studied. Average total concentrations of PM_2.5 and PM₁₀ were 53.2?±?26.91 and 124.54?±?82.33 µg/m³, respectively; however, the results showed that in 75.53% and 84.85% days, concentrations of these pollutants exceeded Chinese National Ambient Air Quality Standard and in 100% days exceeded World Health Organization guidelines standards. Daily mean values of aerosol optical depth and Ångström exponent based on data, received by satellite Moderate Resolution Imaging Spectroradiometer, show a broad range of values for aerosol optical depth (from 0.018 to 1.954) and Ångström exponent (from 0.003 to 1.8). Results of principal components analysis revealed three factor loadings. Thus, Factor 1 has the relevant loadings for PM_2.5, PM₁₀, CO, SO₂, and NO₂ (36%) and closely associated with transport emissions and industrial sources, which contribute to air pollution in Lanzhou. Factor 2 was heavily loaded with temperature and visibility (16.94%). Factor 3 consisted of relative humidity (14.11%). Cluster analysis revealed four subgroups: cluster 1 (PM_2.5, NO₂, SO₂), cluster 2 (CO), cluster 3 (PM₁₀) and cluster 4 (relative humidity, visibility, temperature, O₃, wind speed), which were compliant with results, obtained from principal components analysis. Positive correlation was found among all pollutants, other than O₃. According to processed backward trajectories obtained by Hybrid Single-Particle Lagrangian Integrated Trajectory model, it was found that movement of air masses occur from north, northwest, and west directions—the location of principal natural sources of aerosols.