How can vegetation protect us from air pollution? A critical review on green spaces' mitigation abilities for air-borne particles from a public health perspective - with implications for urban planning.

Air pollution causes the largest death toll among environmental risks globally, but interventions to purify ambient air remain inadequate. Vegetation and green spaces have shown reductive effects on air-borne pollutants concentrations, especially of particulate matter (PM). Guidance on green space utilisation for air quality control remains scarce, however, as does its application in practise. To strengthen the foundation for research and interventions, we undertook a critical review of the state of science from a public health perspective. We used inter-disciplinary search strategies for published reviews on green spaces and air pollution in key scientific databases. Using the PRISMA checklist, we systematically identified reviews with quantitative analyses. For each of the presented PM mitigation mechanisms, we conducted additional searches focused on the most recent articles published between 2016 and early 2021. The included reviews differentiate three mitigation mechanisms of green spaces for PM: deposition, dispersion and modification. The most studied mechanism is deposition, particularly measures of mass and settling velocity of PM on plant leaves. We consolidate how green space setups differ by scale and context in their potentials to reduce peak exposures, stationary (point) or mobile (line) pollution sources, and the potentially most harmful PM components. The assessed findings suggest diverse optimisation options for green space interventions, particularly concerning plant selection, spatial setup, ventilation and maintenance - all alongside the consideration of supplementary vegetation effects like on temperature or water. Green spaces' reductive effects on air-borne PM concentrations are considerable, multi-mechanistic and varied by scale, context and vegetation characteristics. Such effect-modifying factors must be considered when rethinking public space design, as accelerated by the COVID-19 pandemic. Weak linkages amid involved disciplines motivate the development of a research framework to strengthen health-oriented guidance. We conclude on an urgent need for an integrated and risk-based approach to PM mitigation through green space interventions.

Assessing Drinking Water Quality at the Point of Collection and within Household Storage Containers in the Hilly Rural Areas of Mid and Far-Western Nepal.

Accurate assessments of drinking water quality, household hygenic practices, and the mindset of the consumers are critical for developing effective water intervention strategies. This paper presents a microbial quality assessment of 512 samples from household water storage containers and 167 samples from points of collection (POC) in remote rural communities in the hilly area of western Nepal. We found that 81% of the stored drinking water samples (mean log10 of all samples = 1.16 colony-forming units (CFU)/100 mL, standard deviation (SD) = 0.84) and 68% of the POC samples (mean log10 of all samples = 0.57 CFU/100 mL, SD = 0.86) had detectable E. coli. The quality of stored water was significantly correlated with the quality at the POC, with the majority (63%) of paired samples showing a deterioration in quality post-collection. Locally applied household water treatment (HWT) methods did not effectively improve microbial water quality. Among all household sanitary inspection questions, only the presence of livestock near the water storage container was significantly correlated with its microbial contamination. Households' perceptions of their drinking water quality were mostly influenced by the water's visual appearance, and these perceptions in general motivated their use of HWT. Improving water quality within the distribution network and promoting safer water handling practices are proposed to reduce the health risk due to consumption of contaminated water in this setting.

Understanding the effect of socio-economic characteristics and psychosocial factors on household water treatment practices in rural Nepal using Bayesian Belief Networks.

About 20 Million (73%) people in Nepal still do not have access to safely managed drinking water service and 22 million (79%) do not treat their drinking water before consumption. Few studies have addressed the combination of socio-economic characteristics and psychosocial factors that explain such behaviour in a probabilistic manner. In this paper we present a novel approach to assess the usage of household water treatment (HWT), using data from 451 households in mid and far-western rural Nepal. We developed a Bayesian belief network model that integrates socio-economic characteristics and five psychosocial factors. The socio-economic characteristics of households included presence of young children, having been exposed to HWT promotion in the past, level of education, type of water source used, access to technology and wealth level. The five psychosocial factors capture households' perceptions of incidence and severity of water-borne infections, attitudes towards the impact of poor water quality on health, water treatment norms and the knowledge level for performing HWT. We found that the adoption of technology was influenced by the psychosocial factors norms, followed by the knowledge level for operating the technology. Education, wealth level, and being exposed to the promotion of HWT were the most influential socio-economic characteristics. Interestingly, households who were connected to a piped water scheme have a higher probability of HWT adoption compared to other types of water sources. The scenario analysis revealed that interventions that only target single socio-economic characteristics do not effectively boost the probability of HWT practice. However, interventions addressing several socio-economic characteristics increase the probability of HWT adoption among the target groups.