Inequality in Beijing: A Spatial Multilevel Analysis of Perceived Environmental Hazard and Self-Rated Health

Environmental pollution is a major problem in China, subjecting people to significant health risk. However, surprisingly little is known about how these risks are distributed spatially or socially. Drawing upon a large-scale survey conducted in Beijing in 2013, we examine how environmental hazards and health, as perceived by residents, are distributed at fine (sub-district) scale in urban Beijing, and investigate association between hazards, health and geographical context. A Bayesian spatial multilevel logistic model is developed to account for spatial dependence in unobserved contextual influences (‘neighbourhood effects’) on health. Results reveal robust associations between exposure to environmental hazards and health. A unit decrease on a 5-point Likert scale in exposure is associated with increases of 15.2% (air pollution), 17.5% (noise) and 9.3% (landfills) in the odds of reporting good health, with marginal groups including migrant workers reporting greater exposure. Health inequality is also evident, and associated with age, income, educational attainment and housing characteristics. Geographical context (neighbourhood features like local amenity) also plays a role in shaping the social distribution of health inequality. Results are discussed in the context of developing environmental justice policy within a Chinese social market system that experiences tension between its egalitarian roots and its pragmatic approach to tackling grand public policy challenges

Cross-Sector Review of Drivers and Available 3Rs Approaches for Acute Systemic Toxicity Testing

Acute systemic toxicity studies are carried out in many sectors in which synthetic chemicals are manufactured or used and are among the most criticized of all toxicology tests on both scientific and ethical grounds. A review of the drivers for acute toxicity testing within the pharmaceutical industry led to a paradigm shift whereby in vivo acute toxicity data are no longer routinely required in advance of human clinical trials. Based on this experience, the following review was undertaken to identify (1) regulatory and scientific drivers for acute toxicity testing in other industrial sectors, (2) activities aimed at replacing, reducing, or refining the use of animals, and (3) recommendations for future work in this area

Modest amendment of sewage sludge biochar to reduce the accumulation of cadmium into rice (Oryza sativa L.): A field study

Much research has considered the influence of biochars on the availability and phytoaccumulation of potentially toxic elements (PTEs) from soil. However, the vast majority of these studies use, what are arguably, unrealistic and unpractical amounts of biochar (10, 50 and even up to 100 t/ha). To offer a more realistic insight into the influence of biochar on PTE partitioning and phytoaccumulation, a field study, using modest rates of biochar application (1.5, 3.0 t/ha), was undertaken. Specifically, the research investigated the influence of sewage sludge biochar (SSBC) on the accumulation of Cd into rice (Oryza sativa L.) grown in Cd contaminated (0.82 ± 0.07 mg/kg) paddy soil. Results indicated, Cd concentrations in rice grains to significantly (p < 0.05) decrease from 1.35 ± 0.09 mg/kg in the control to 0.82 ± 0.07 mg/kg and 0.80 ± 0.21 mg/kg in the 1.5 t/ha and 3.0 t/ha treatments, respectively. Accordingly, the hazardous quotient (HQ) indices for Cd, associated with rice grain consumption, were also reduced by ∼40%. SSBC amendment significantly (p < 0.05) increased grain yields from 1.90 ± 0.08 g/plant in the control to 2.17 ± 0.30 g/plant and 3.40 ± 0.27 g/plant in the 1.5 t/ha and 3.0 t/ha treatments, respectively. Thus, the amendment of SSBC to contaminated paddy soils, even at low application rates, could be an effective approach to mitigate Cd accumulation into rice plants, to improve rice grain yields, and to thereby improve food security and protect public health

Reconciling discrepancies in the source characterization of VOCs between emission inventories and receptor modeling

Emission inventory (EI) and receptor model (RM) are two of the three source apportionment (SA) methods recommended by Ministry of Environment of China and used widely to provide independent views on emission source identifications. How to interpret the mixed results they provide, however, were less studied. In this study, a cross-validation study was conducted in one of China's fast-developing and highly populated city cluster- the Pearl River Delta (PRD) region. By utilizing a highly resolved speciated regional EI and a region-wide gridded volatile organic compounds (VOCs) speciation measurement campaign, we elucidated underlying factors for discrepancies between EI and RM and proposed ways for their interpretations with the aim to achieve a scientifically plausible source identification. Results showed that numbers of species, temporal and spatial resolutions used for comparison, photochemical loss of reactive species, potential missing sources in EI and tracers used in RM were important factors contributed to the discrepancies. Ensuring the consensus of species used in EIs and RMs, utilizing a larger spatial coverage and longer time span, addressing the impacts of photochemical losses, and supplementing emissions from missing sources could help reconcile the discrepancies in VOC source characterizations acquired using both approaches. By leveraging the advantages and circumventing the disadvantages in both methods, the EI and RM could play synergistic roles to obtain robust SAs to improve air quality management practices