Impacts of Trans-Provincial Thermal Power Transmission on Air-Quality Recovery and Related Health Outcomes in China.

Trans-provincial thermal power transmission has become an important measure for optimizing power allocation and alleviating the mismatch between regional power production and consumption in China, however, leading to inter-regional redistribution of air pollution. Here, we investigated the impacts of thermal power transmission on air-quality recovery and related health outcomes in China. The results showed that the redistribution of air pollutant emissions contributed to air-quality improvements and health benefits in the eastern regions but to the opposite side in the western regions. On a national scale, trans-provincial thermal power transmission contributed to a change in air quality from slightly polluted to good conditions for a period of 9 days under the standard of 75 µg m-3, accounting for 1.8% of the total number of polluted days in 4 months of 2017 and promoting air-quality recovery in China. Furthermore, the recovery totally reduced the number of premature deaths (exposed to fine particulate matter, PM2.5) by 2392 persons (95% confidence interval: 1495-3124) in 2017. Owing to thermal power retrofits and stable power transmission structure, transmission network expansion during the last decade has not brought significant changes in its impacts on air pollution. However, the environmental inequity caused by thermal power transmission stimulates further attention on coordinating regional interests in air pollution control through various production-side and consumption-side measures.

Profiling the variability and inequity in the residential environment in Cyprus according to citizens' ratings: a cross-sectional internet-based "Place Standard" survey.

BACKGROUND: The "Place Standard Tool" (PST) offers a practical framework for structuring conversations about physical and social dimensions of Place which impact on health and well-being. The aim of this study was to survey citizens' perceptions of Place across diverse settings in Cyprus. While the PST has been extensively used in the context of community engagement, its properties as a measurement tool haven't been explored. METHODS: An open call was addressed to citizens to rate their neighbourhood environment across the 14 PST items (1: large to 7: little room for improvement). Exploratory factor, cluster and regression analyses were used to explore the dimensionality of the scale, depict neighbourhood profiles and explore differences in ratings according to socio-demographic characteristics, area-level census indicators and residents' assessment of neighbourhood social position (10-step ladder). RESULTS: With the exception of safety (M = 4.4, SD = 1.7), 492 participants (mean age 42, 50% residents for > 10 years) from 254 postcodes (21.7% islandwide) did not rate other features favourably, with lowest scores for "influence and sense of control" and "public transport". A stepwise pattern of dissatisfaction was observed along the social position continuum both for features rated less as well as more favourably (e.g. social contact). For instance, among participants who placed their neighbourhood at the three top steps of the ladder, 48.8% gave a low rating for "influence and sense of control", while the equivalent figure was 81.0% at the bottom three steps (OR = 4.5, 95% CI 2.3, 8.6). A clear dimensionality of Built (6 items, Cronbach's α = 0.798), Physical (3 items, α = 0.765), Social (2 items, α = 0.749) and Service (3 items, α = 0.58) environment was identified. A social gradient was evident according to census measures of socio-economic disadvantage (e.g. pre-1980 housing, single-parent households) with larger differences in terms of the built than the social environment. CONCLUSIONS: The study profiled the variability and documented the inequity in the health-related neighbourhood environment across Cypriot communities. The readily interpretable dimensionality of the scale supports its construct validity, allowing calculation of composite scores. The PST can be used as measurement tool in research as well as public health practice to advocate for neighbourhood initiatives which support and enhance citizens' participation.

The relationship between urban forests and income: A meta-analysis.

Urban trees provide substantial public health and public environmental benefits. However, scholarly works suggest that urban trees may be unequally distributed among poor and minority urban communities, meaning that these communities are potentially being deprived of public environmental benefits, a form of environmental injustice. The evidence of this problem is not uniform however, and evidence of inequity varies in size and significance across studies. This variation in results suggests the need for a research synthesis and meta-analysis. We employed a systematic literature search to identify original studies which examined the relationship between urban forest cover and income (n=61) and coded each effect size (n=332). We used meta-analytic techniques to estimate the average (unconditional) relationship between urban forest cover and income and to estimate the impact that methodological choices, measurement, publication characteristics, and study site characteristics had on the magnitude of that relationship. We leveraged variation in study methodology to evaluate the extent to which results were sensitive to methodological choices often debated in the geographic and environmental justice literature but not yet evaluated in environmental amenities research. We found evidence of income-based inequity in urban forest cover (unconditional mean effect size = 0.098; s.e. = .017) that was robust across most measurement and methodological strategies in original studies and results did not differ systematically with study site characteristics. Studies that controlled for spatial autocorrelation, a violation of independent errors, found evidence of substantially less urban forest inequity; future research in this area should test and correct for spatial autocorrelation.

Environmental and Socioeconomic Health Inequalities: a Review and an Example of the Industrial Ostrava Region.

BACKGROUND AND AIM: According to the World Health Organization (WHO) more than 2 million premature deaths and 7 million of total deaths each year can be attributed to the effects of air pollution. The contribution of air pollution to the health status of population is estimated to be about 20%. Health is largely determined by factors outside the reach of healthcare sector, including low income, unemployment, poor environment, poor education, and substandard housing. The aim of the paper was to review a current knowledge of relationships among air pollution, socioeconomic health inequalities, socio-spatial differentiation, and environmental inequity. The relationships were demonstrated on an example of the Ostrava region. Also basic approaches to health valuation were reviewed. RESULTS: Social differences are reasons both for health inequalities and spatial patterns of unprivileged area housing. In urban environments with poor air quality there is also a large concentration of low income residents. Less affluent population groups are more often affected by inadequate housing conditions including second-hand smoking and higher environmental burden in their residential neighbourhoods. Environmental injustice is highly correlated with other factors that link poverty with poor health, including inadequate access to medical and preventive care, lack of availability of healthful food, lack of safe play spaces for children, absence of good jobs, crime, and violence. CONCLUSIONS: The theoretical background and also results of the studies brought evidence that population health is affected by both socioeconomic and environmental inequalities. Air pollution is unevenly distributed in Ostrava and is related to distribution of socially disadvantaged environment and social exclusion as well.

Developing a composite indicator to prioritize tree planting and protection locations.

Trees provide numerous ecosystem services to benefit human health, and many cities have launched tree planting and management programs to increase tree populations and optimize tree locations through diverse tree priority schemes. Existing tree priority schemes are typically local-specific, expert-driven, and tree-planting-focused. In this study, a framework that captures interactions among the environment, tree and human demographic information is built. This framework provides a composite indicator, namely a tree priority planting or priority protection index (PPI), that can be integrated within a decision support system such as i-Tree Landscape to provide nationally consistent and locally relevant ways to strategically optimize tree planting and management locations across the entire United States. Three scenarios with the human health concerns are tested in a case study of New York City. The analyses are conducted at the census block group scale that is the finest-level scale available at i-Tree Landscape. The resulting PPI maps are analyzed using spatial statistics and compared against each other to investigate the impacts of alternative investments of limited public resources. The results show that: (1) tree priority patterns change greatly with alternative objectives; (2) adding more indicators to build PPIs lead to more diverse tree priority patterns as high (or low) values of different indicators are often not geographically coincident; (3) incorporating more indicators may not necessarily provide more useful information because the influences of individual indicators may be reduced and diluted by a higher level of aggregation; and (4) disaggregating PPIs may reveal corresponding contributions of individual indicators. Applying the proposed framework to build PPIs has important implications for tree priority effort, scientific exploration, education, and public engagement.

Spatially Analyzing the Inequity of the Hong Kong Urban Heat Island by Socio-Demographic Characteristics.

Recent studies have suggested that some disadvantaged socio-demographic groups face serious environmental-related inequities in Hong Kong due to the rising ambient urban temperatures. Identifying heat-vulnerable groups and locating areas of Surface Urban Heat Island (SUHI) inequities is thus important for prioritizing interventions to mitigate death/illness rates from heat. This study addresses this problem by integrating methods of remote sensing retrieval, logistic regression modelling, and spatial autocorrelation. In this process, the SUHI effect was first estimated from the Land Surface Temperature (LST) derived from a Landsat image. With the scale assimilated to the SUHI and socio-demographic data, a logistic regression model was consequently adopted to ascertain their relationships based on Hong Kong Tertiary Planning Units (TPUs). Lastly, inequity "hotspots" were derived using spatial autocorrelation methods. Results show that disadvantaged socio-demographic groups were significantly more prone to be exposed to an intense SUHI effect: over half of 287 TPUs characterized by age groups of 60+ years, secondary and matriculation education attainment, widowed, divorced and separated, low and middle incomes, and certain occupation groups of workers, have significant Odds Ratios (ORs) larger than 1.2. It can be concluded that a clustering analysis stratified by age, income, educational attainment, marital status, and occupation is an effective way to detect the inequity hotspots of SUHI exposure. Additionally, inequities explored using income, marital status and occupation factors were more significant than the age and educational attainment in these areas. The derived maps and model can be further analyzed in urban/city planning, in order to mitigate the physical and social causes of the SUHI effect.