Wetlands with greater degree of urbanization improve PM2.5 removal efficiency

Residential green and blue spaces and working memory in children aged 6-12 years old. Results from the INMA cohort

Availability of green and blue spaces in the area of residence has been related to various health outcomes during childhood, including neurodevelopment. Some studies have shown that children living in greener and/or bluer areas score better on cognitive tasks although the evidence is inconsistent. These protective effects are hypothesized to occur in part through reductions in air pollution exposure and odds of attention-deficit/hyperactivity disorder (ADHD). This study analysed the effects of residential green and blue spaces on working memory of children in the Spanish INfancia y Medio Ambiente (INMA) birth cohort and the potential joint mediating role of air pollution and ADHD. The study samples were composed of 1738 six-to eight-year-olds (M = 7.53, SD = 0.68, 49% female) and 1449 ten-to twelve-year-olds (M = 11.18, SD = 0.69, 50% female) living in Asturias, Gipuzkoa, Sabadell or Valencia, Spain. Individual Normalized Difference Vegetation Index (NDVI) values in 100-, 300- and 500-m buffers and availability of green and blue spaces >5000 m2 in 300-m buffers were calculated using Geographic Information Systems software. Individual NO2 values for the home environment were estimated using ESCAPE's land use regression models. ADHD diagnosis was reported by participants' parents via a questionnaire. Working memory was measured with numbers and colours (in the younger group only) N-back tests (2- and 3-back d'). Mixed-effects models informed of the beneficial effects of NDVI in a 300-m buffer on numerical working memory in the younger sample although the results were not consistent for all d' scores considered and failed to detect significant effects through the candidate mediators. Availability of major blue spaces did not predict working memory performance. Provision of green spaces may play a role in children's working memory but further research is required.

Environmental management: a country-level evaluation of atmospheric particulate matter removal by the forests of India

Particulate matter (PM) is a critical air pollutant, responsible for an array of ailments leading to premature mortality worldwide. Nature-based solutions for mitigation of PM and especially role of forests in mitigating PM from an ecosystem perspective are less explored. Forests provide a natural pollution abatement strategy by providing a surface area for the deposition of PM. Depending on their structure and composition, forests have varying capacities for PM adsorption, which is again less explored. Hence, in the present study, we evaluate the removal capacity of PM by the forest-type groups of India. Deposition flux and total PM removal across sixteen forest types were estimated based on the 2019 dataset of PM using Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data. Externality values and PM removal costs by industrial equipment were used for associating an economic value to the air pollution abatement service by forests. The total PM2.5 removal by forests in 2019 was estimated to be 1361.28 tons and PM10 was estimated to be 303,658.27 tons. Deposition of PM was found to be high in littoral and swamp forests, tropical semi-evergreen forests, tropical moist deciduous forests, and sub-tropical pine forests. Tropical dry deciduous forests had the highest net weight % removal of PM with 39% removal for PM2.5 and 39% removal for PM10. The air pollution abatement service by forests for PM removal was 188 M US dollars (USD) with externality-based removal service by forests of 2009 M USD. The net PM removed by all forests of India was estimated to be approximately worth ₹ 470-648 Crore (59-81 million dollars) for PM2.5 and worth ₹56,746-1,22,617 Crore (7093-15,327 million dollars) for PM10 based on valuation using value transfer method. The study concludes that forests can be a significant contributor to PM reduction at a global level. Especially for India's National Clean Air Programme and further research and policy considerations, the findings would be extremely useful.

Haze pollution and urbanization promotion in China: How to understand their spatial interaction?

Can promoting urbanization and controlling haze pollution result in a win-win situation? Based on panel data from 287 prefecture-level cities in China, this paper uses the three-stage least-squares estimator method(3SLS) and generalized space three-stage least-squares estimator method (GS3SLS) to study the spatial interaction between haze pollution and urbanization. The results show the following: (1) There is a spatial interaction between haze pollution and urbanization. On the whole, haze pollution and urbanization have a typical inverted U-shaped relationship. (2) Haze and urbanization show different relationships in different regions. The haze pollution in the area left of the Hu Line has a linear relationship with urbanization. (3) In addition to haze, urbanization also has a spatial spillover effect. When the haze pollution in the surrounding areas increases, the haze pollution in the area will also increase, but the level of urbanization will increase. When the level of urbanization in the surrounding areas increases, it will promote the level of urbanization in the local area and alleviate the haze pollution in the local area. (4) Tertiary industry, greening, FDI and precipitation can help alleviate haze pollution. FDI and the level of urbanization have a U-shaped relationship. In addition, industry, transportation, population density, economic level and market scale can promote regional urbanization.

Associations between exposure to blue spaces and natural and cause-specific mortality in Greece: An ecological study

BACKGROUND

A growing body of evidence suggests that exposure to natural environments, such as green space, may have a beneficial role in health. However, there is limited evidence regarding the effects of exposure to blue spaces and mortality. We investigated the association of exposure to blue spaces with natural and cause-specific mortality in Greece using an ecological study design METHODS: Mortality and socioeconomic data were obtained from 1,035 municipal units (MUs) from the 2011 census data. To define exposure to "blue" we used a rate of the land cover categories related to blue space from the COoRdination and INformation on the Environmental (CORINE) 2012 map per 10,000 persons in the municipal unit. We further assessed the exposure to blue space in the MUs that are located in the coastline of Greece using the distance to the coast as a proxy for proximity to blue space. the Annual PM_2.5, NO₂, BC and O₃ concentrations for 2010 were predicted by land use regression models while the normalized difference vegetation index was used to assess greenness. We applied single and two exposure Poisson regression models accounting for spatial autocorrelation and adjusting for unemployment and lung cancer mortality rates, percentages of the population aged 25-64 with upper secondary or tertiary education attainment and of those born in Greece, and urbanicity. The analysis was conducted for the whole country and separately by varying geographical definitions.

RESULTS

An interquartile range (IQR) increase of blue space per 10,000 persons was associated with decreased risk in natural mortality (Relative Risk (RR): 0.98 (95% confidence interval (CI): 0.98, 0.99), as well as in mortality due to cardiovascular causes, respiratory causes and diseases of the nervous system 0.98 (95% CI: 0.97, 0.99); 0.97 (95% CI: 0.95, 0.99); 0.94 (95% CI: 0.88, 1.00) respectively). We estimated protective associations for ischemic heart disease (IHD) mortality (RR = 0.98, 95% CI: 0.97, 1.00 per IQR); COPD mortality (RR = 0.97, 95% CI: 0.93, 1.00 per IQR) and mortality from cerebrovascular disease (RR = 0.97 (95% CI: 0.96, 0.99 per IQR). We estimated protective associations for the distance from the coast and mortality from the diseases of the nervous system (RR = 0.75, 95% CI: 0.61, 0.92, ≤1 km from the coast versus >1 km). Our results were stronger for inhabitants of the islands, the coastline and in the rural areas of Greece while the estimates were robust to co-exposure adjustment.

CONCLUSIONS

We estimated statistically significant protective effects of exposure to blue space on mortality from natural, cardiovascular and respiratory causes, diseases of the nervous system, cerebrovascular and ischemic heart disease for in Greece with higher estimates in the coastline and the islands. Further research is needed to elaborate our findings.

Multidimensional effects of urbanization on PM2.5 concentration in China

Recently, the contradiction between urbanization and the air environment has gradually attracted attention. However, most existing studies have explored the impact of single urbanization factors, such as population, the economy, or land, on PM_2.5 and ignored the impact of multidimensional urbanization on PM_2.5 concentration. Moreover, the heterogeneity in the mechanisms responsible for the PM_2.5 concentration caused by multidimensional urbanization has not been thoroughly studied in different regions in China. Therefore, we investigate the spatial-temporal evolution characteristics of PM_2.5 concentration in China during 1998-2019 by spatial analysis and dynamic panel models based on the environmental Kuznets curve (EKC). Then, we study the effects of multidimensional urbanization on PM_2.5 concentration, and analyze the dominant factors in China's eight economic regions. During the study period, the PM_2.5 concentration in China fluctuated before 2013 and gradually decreased thereafter. The PM_2.5 concentration has significant regional differences in China. Spatially, the PM_2.5 concentration is higher in the north than in the south and higher in the east than in the west. Additionally, there is a significant spatial spillover effect. Both population urbanization and economic urbanization show an inverted U-shaped relationship with PM_2.5 concentration in China, which is consistent with the classical EKC theory. Due to other socioeconomic factors, the PM_2.5 concentration tends to decrease linearly with increasing land urbanization rate. The effects of urbanization on the PM_2.5 concentration in the eight economic regions in China show significant differences. The effect of land urbanization on the PM_2.5 concentration is dominant in the Middle Yangtze River region, that of economic urbanization is dominant in northwestern China, and that of population urbanization is dominant in the remaining regions in China.

The Threshold Effect of Urban Levels on Environmental Collaborative Governance: An Empirical Analysis from Chinese Cities

Taking 286 cities above the prefecture level in China as the research object and the research period from 2003 to 2019, through the two-way fixed effect model, this paper empirically analyzes the impact of the city level on environmental collaborative governance. The threshold regression model is used to reveal the nonlinear relationship between urban levels and environmental collaborative governance and to analyze the phase characteristics of different urban levels for environmental collaborative governance. The results show that: (1) The city level has a significant role in promoting collaborative environmental governance. (2) The regression results of the three major sections show that the urban level promotion in the eastern region has the strongest promoting effect on the coordinated environmental governance, and the western region is the weakest. (3) The impact of the city level on collaborative environmental governance is nonlinear. When the city scale reaches a certain critical point, its impact on the collaborative environmental governance tends to intensify.

Mechanisms of Impact of Blue Spaces on Human Health: A Systematic Literature Review and Meta-Analysis

Blue spaces have been found to have significant salutogenic effects. However, little is known about the mechanisms and pathways that link blue spaces and health. The purpose of this systematic review and meta-analysis is to summarise the evidence and quantify the effect of blue spaces on four hypothesised mediating pathways: physical activity, restoration, social interaction and environmental factors. Following the PRISMA guidelines, a literature search was conducted using six databases (PubMed, Scopus, PsycInfo, Web of Science, Cochrane Library, EBSCOHOST/CINAHL). Fifty studies were included in our systematic review. The overall quality of the included articles, evaluated with the Qualsyst tool, was judged to be very good, as no mediating pathway had an average article quality lower than 70%. Random-effects meta-analyses were conducted for physical activity, restoration and social interaction. Living closer to blue space was associated with statistically significantly higher physical activity levels (Cohen’s d = 0.122, 95% CI: 0.065, 0.179). Shorter distance to blue space was not associated with restoration (Cohen’s d = 0.123, 95% CI: −0.037, 0.284) or social interaction (Cohen’s d = −0.214, 95% CI: −0.55, 0.122). Larger amounts of blue space within a geographical area were significantly associated with higher physical activity levels (Cohen’s d = 0.144, 95% CI: 0.024, 0.264) and higher levels of restoration (Cohen’s d = 0.339, 95% CI: 0.072, 0.606). Being in more contact with blue space was significantly associated with higher levels of restoration (Cohen’s d = 0.191, 95% CI: 0.084, 0.298). There is also evidence that blue spaces improve environmental factors, but more studies are necessary for meta-analyses to be conducted. Evidence is conflicting on the mediating effects of social interaction and further research is required on this hypothesised pathway. Blue spaces may offer part of a solution to public health concerns faced by growing global urban populations.

The Impact of Regeneration and Climate Adaptations of Urban Green-Blue Assets on All-Cause Mortality: A 17-Year Longitudinal Study

Urban waterways are underutilised assets, which can provide benefits ranging from climate-change mitigation and adaptation (e.g., reducing flood risks) to promoting health and well-being in urban settings. Indeed, urban waterways provide green and blue spaces, which have increasingly been associated with health benefits. The present observational study used a unique 17-year longitudinal natural experiment of canal regeneration from complete closure and dereliction in North Glasgow in Scotland, U.K. to explore the impact of green and blue canal assets on all-cause mortality as a widely used indicator of general health and health inequalities. Official data on deaths and socioeconomic deprivation for small areas (data zones) for the period 2001–2017 were analysed. Distances between data zone population-weighted centroids to the canal were calculated to create three 500 m distance buffers. Spatiotemporal associations between proximity to the canal and mortality were estimated using linear mixed models, unadjusted and adjusted for small-area measures of deprivation. The results showed an overall decrease in mortality over time (β = −0.032, 95% confidence interval (CI) [−0.046, −0.017]) with a closing of the gap in mortality between less and more affluent areas. The annual rate of decrease in mortality rates was largest in the 0–500 m buffer zone closest to the canal (−3.12%, 95% CI [−4.50, −1.73]), with smaller decreases found in buffer zones further removed from the canal (500–1000 m: −3.01%, 95% CI [−6.52, 0.62]), and 1000–1500 m: −1.23%, 95% CI [−5.01, 2.71]). A similar pattern of results was found following adjustment for deprivation. The findings support the notion that regeneration of disused blue and green assets and climate adaptions can have a positive impact on health and health inequalities. Future studies are now needed using larger samples of individual-level data, including environmental, socioeconomic, and health variables to ascertain which specific elements of regeneration are the most effective in promoting health and health equity.

Corruption, Economic Development and Haze Pollution: Evidence from 139 Global Countries

Long-term exposure to haze pollution will not only affect citizens’ health and shorten their life expectancy, but also cause unpredictable economic losses. In addition, it has become the focus of worldwide concern whether and how institutional quality affects haze pollution. In this study, we explored the impacts of political corruption on haze pollution in 139 global countries. We employed a geographical detector model to identify the driving factors of spatial differentiation in global haze pollution. In addition, corruption degree and per capita gross domestic production (GDP) were used as threshold variables to analyze whether there is a nonlinear relationship between corruption and haze pollution. The main results are as follows. (1) The corruption perception index (CPI) was negatively correlated with haze pollution and had a strong and stable explanatory power for the heterogeneity of haze pollution. Besides, the degree of corruption had a significant triple threshold effect on haze pollution. When the CPI crossed the double threshold value, strengthening institutional quality could inhibit haze pollution. (2) Per capita GDP significantly determined how institutional quality exerted an effect on haze pollution, which was also a key factor affecting spatial heterogeneity of PM2.5 concentration. In high-income countries, choosing a more honest ruling party could substantially reduce haze pollution, while in low-income countries, an incompetent government could increase the degree of haze pollution. (3) The “Matthew effect” was manifested in our study. It indicated that the higher was the level of economic development, the lower was the severity of haze pollution. Based on these results, we state that policy makers cannot simply alleviate haze pollution through anti-corruption construction. For low-income countries, ensuring economic growth is the prerequisite for the substantial alleviation of haze pollution. On the contrary, high-income countries should pay more attention to the integrity of government institutions and strengthen the awareness of anti-corruption.

Reduced growth response of ornamental plant Nicotiana alata L. upon selected heavy metals uptake, with co-application of ethylenediaminetetraacetic acid

The use of ornamental plant will increase with the improvement in living standards in green and blue-green infrastructure of urban settings. Nicotiana alata is an ornamental plant, frequently grown as a model plant for horticulture, medicine, and scientific research studies throughout the world. Despite its popularity, little is known about the response of N. alata against heavy metals (HMs). This work is based on the hydroponic study to identify the impacts of selected HMs (Cd, Cr, Cu, Ni and Pb) on N. alata, at 0, 50 and 100 μM concentration, with the co-application of EDTA, at 0 and 2.5 mM in hydroponics system. The HMs uptake was found to be dose dependent, with significant higher uptake at 100 μM of respective HM. Highest cumulative uptake (mg kg-1 of HMs in root, shoot, and leaf dried weight) noted were 767.50 ± 50.83, 862.30 ± 23.83, 271.29 ± 18.68, 1117.49 ± 46.10 and 2166.81 ± 102.09, for Cd, Cr, Cu, Ni, and Pb at 100 μM, respectively. It was identified that EDTA co-application with HMs resulted in boosted HMs uptake, with cumulative uptake percentage increment of 41.62, 54.67, 53.98, 34.48 and 19.92% for 100 μM of Cd, Cr, Cu, Ni, and Pb, respectively. Higher uptake led to negative impact on plant physiology, photosynthetic pigments, and higher lipid peroxidation, H2O2 contents, and electrolyte leakage that increased the stress. Higher HMs uptake induced higher antioxidant enzymatic response. It is recommended to incorporate appropriate soil modification to grow N. alata in sustainable infrastructures.

Particle removal in polluted cities: Insights from the wash-off process dynamics for different wetland plants

Particulate matter (PM) in the atmosphere is a threat to human health. Wetland plants were confirmed to accumulate particles on the leaf surface; at the same time, rainfall could wash-off particles and accelerate the whole removal process, however, the dynamic processes occurring during rainfall events on wetland plants remain unclear. In order to provide sustainable strategies for authorities to take measures, we need to figure out how to reduce PM on leave surface by artificial rainfall efficiently. Four wetland species (Scirpus validus, Typha orientalis, Phragmites australis, and Iris wilsonii) were selected to examine for leave surface accumulation and simulate the experiment. We estimated the wash-off ability of rainfalls with three different intensities (15, 30, and 60 mm h^-1) and determined the proportions of different PM size-fractions washed by the rains. The results showed that particles accumulated on the surface could be washed off efficiently (78% ∼ 89%) by the simulated rainfalls. The removal rates were high in the first 30 min and large particles comprised a large proportion of the removed particles. The rainfall with the intensity of 30 mm h^-1 removed the most particles among three different rainfall intensities. When the rainfall intensity increased, fine particles (PM_2.5) could be washed off more easily. Moreover, with a thinner wax layer, fine particles on wetland plants' leaf surfaces might be more easily removed by the rains. While wash off the plants, spraying rains with the intensity of 30 mm h^-1 for about 30 min every time (high intensity with shorter time) may be particle removal efficiency.

The Concentrations and Removal Effects of PM10 and PM2.5 on a Wetland in Beijing

Particulate matter (PM) is an essential source of atmospheric pollution in metropolitan areas since it has adverse effects on human health. However, previous research suggested wetlands can remove particulate matter from the atmosphere to land surfaces. This study was conducted in the Hanshiqiao Wetland National Nature Reserve in Beijing during 2016. The concentrations of PM10 and PM2.5 on a wetland and bare land in the park, as well as metrological data, were collected during the whole year. Based on the observed data, removal efficiency of each land use type was calculated by empirical models and the relationships between concentrations and metrological factors were also analyzed. The results indicated that: (1) In general, the PM10 and PM2.5 concentrations on the bare land surface were higher than those on the wetland surface, in both of which the highest value appeared at night and evening, while the lowest value appeared near noon. In terms of season, the average concentration of PM10 was higher in winter (wetland: 137.48 μg·m−3; bare land: 164.75 μg·m−3) and spring (wetland: 205.18 μg·m−3; bare land: 244.85 μg·m−3) in general. The concentration of PM2.5 on the wetland surface showed the same pattern, while that on the bare land surface was higher in spring and summer. (2) Concentrations of PM10 and PM2.5 were significantly correlated with the relative humidity (p < 0.01) and inversely correlated with wind speed (p < 0.05). The relationship between PM10 and PM2.5 concentrations and temperature was more complicated—it showed a significantly negative correlation (p < 0.01) between them in winter and spring, however, the correlation was insignificant in autumn. In summer, only the correlation between PM10 concentration and temperature on the wetland surface was significant (p < 0.01). (3) The dry removal efficiency of PM10 was greater than that of PM2.5. The dry removal efficiencies of PM10 and PM2.5 followed the order of spring > winter > autumn > summer on the wetland. This study seeks to provide practical measures to improve air quality and facilitate sustainable development in Beijing.

Comparison of dry and wet deposition of particulate matter in near-surface waters during summer

Atmospheric particulate matter (PM) deposition which involves both dry and wet processes is an important means of controlling air pollution. To investigate the characteristics of dry and wet deposition in wetlands, PM concentrations and meteorological conditions were monitored during summer at heights of 1.5 m, 6 m and 10 m above ground level at Cuihu Wetland (Beijing, China) in order to assess the efficiency of PM2.5 (particles with an aerodynamic size of <2.5 μm) and PM10 (particles with an aerodynamic size of <10 μm) removal. The results showed: Daily concentrations of PM, dry deposition velocities and fluxes changed with the same variation trend. The daily average deposition velocity for PM10 (3.19 ± 1.18 cm·s-1) was almost 10 times that of PM2.5 (0.32 ± 0.33 cm·s-1). For PM2.5, the following dry deposition fluxes were recorded: 10 m (0.170 ± 0.463 μg·m-2·s-1) > 6 m (0.007 ± 0.003 μg·m-2·s-1) > 1.5 m (0.005 ± 0.002 μg·m-2·s-1). And the following deposition fluxes for PM10 were recorded: 10 m (2.163 ± 2.941 μg·m-2·s-1) > 1.5 m (1.565 ± 0.872 μg·m-2·s-1) > 6 m (0.987 ± 0.595 μg·m-2·s-1). In the case of wet deposition, the relative deposition fluxes for PM2.5 and PM10 were 1.5 m > 10 m > 6 m, i.e. there was very little difference between the fluxes for PM2.5 (0.688 ± 0.069 μg·m-2·s-1) and for PM10 (0.904 ± 0.103 μg·m-2·s-1). It was also noted that rainfall intensity and PM diameter influenced wet deposition efficiency. Dry deposition (63%) was more tilted towards removing PM10 than was the case for wet deposition (37%). In terms of PM2.5 removal, wet deposition (92%) was found to be more efficient.