Dataset Information

Socio-demographic predictors of health and environmental co-benefit behaviours for climate change mitigation in urban China.

ABSTRACT:

Objective

This study aims to examine the patterns and socio-demographic predictors of health and environmental co-benefit behaviours that support climate change mitigation in a densely populated Asian metropolis-Hong Kong.

Methods

A population-based, stratified and cross-sectional random digit dialling telephone survey study was conducted between January and February 2016, among the Cantonese-speaking population aged 15 and above in Hong Kong. Socio-demographic data and the self-reported practice of 10 different co-benefit behaviours were solicited. Ethics approval and participant's verbal consent were sought.

Findings

The study sample consisted of 1,017 respondents (response rate: 63.6%) were comparable to the age, gender and geographical distributions of the Hong Kong population found in the latest 2011 Hong Kong Population Census. Among the co-benefit behaviours, using less packaging and disposable shopping bags were practiced in the highest frequency (70.1%). However, four behaviours were found to have never been practiced by more than half of the respondents, including bringing personal eating utensils when dining in restaurants or small eateries, showering less than five minutes, having one vegetarian meal a week, and buying more organic food. Results of multivariable logistic regression showed that frequency of practicing co-benefit behaviours were consistently associated with gender and age.

Conclusion

Urban residents in Hong Kong do not engage in the practice of co-benefit behaviours in a uniform way. In general, females and older people are more likely to adopt co-benefit behaviours in their daily lives. Further research to assess the knowledge and attitudes of the population towards these co-benefit behaviours will provide support to relevant climate change mitigation policies and education programmes.

SUBMITTER: Chan EYY

PROVIDER: S-EPMC5703449 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Socio-demographic predictors of health and environmental co-benefit behaviours for climate change mitigation in urban China.

Chan Emily Ying Yang EYY Wang Susan Shuxin SS Ho Janice Ying-En JY Huang Zhe Z Liu Sida S Guo Chunlan C

PloS one 20171127 11

<h4>Objective</h4>This study aims to examine the patterns and socio-demographic predictors of health and environmental co-benefit behaviours that support climate change mitigation in a densely populated Asian metropolis-Hong Kong.<h4>Methods</h4>A population-based, stratified and cross-sectional random digit dialling telephone survey study was conducted between January and February 2016, among the Cantonese-speaking population aged 15 and above in Hong Kong. Socio-demographic data and the self-r ...[more]

PMID: 29176879

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Project description:Climate change mitigation benefits from the land sector are not being fully realised because of uncertainty and controversy about the role of native forest management. The dominant policy view, as stated in the IPCC's Fifth Assessment Report, is that sustainable forest harvesting yielding wood products, generates the largest mitigation benefit. We demonstrate that changing native forest management from commercial harvesting to conservation can make an important contribution to mitigation. Conservation of native forests results in an immediate and substantial reduction in net emissions relative to a reference case of commercial harvesting. We calibrated models to simulate scenarios of native forest management for two Australian case studies: mixed-eucalypt in New South Wales and Mountain Ash in Victoria. Carbon stocks in the harvested forest included forest biomass, wood and paper products, waste in landfill, and bioenergy that substituted for fossil fuel energy. The conservation forest included forest biomass, and subtracted stocks for the foregone products that were substituted by non-wood products or plantation products. Total carbon stocks were lower in harvested forest than in conservation forest in both case studies over the 100-year simulation period. We tested a range of potential parameter values reported in the literature: none could increase the combined carbon stock in products, slash, landfill and substitution sufficiently to exceed the increase in carbon stock due to changing management of native forest to conservation. The key parameters determining carbon stock change under different forest management scenarios are those affecting accumulation of carbon in forest biomass, rather than parameters affecting transfers among wood products. This analysis helps prioritise mitigation activities to focus on maximising forest biomass. International forest-related policies, including negotiations under the UNFCCC, have failed to recognize fully the mitigation value of native forest conservation. Our analyses provide evidence for decision-making about the circumstances under which forest management provides mitigation benefits.

Project description:BackgroundThe potential contributions from forest-based greenhouse gas (GHG) mitigation actions need to be quantified to develop pathways towards net negative emissions. Here we present results from a comparative analysis that examined mitigation options for British Columbia's forest sector. Mitigation scenarios were evaluated using a systems perspective that takes into account the changes in emissions and removals in forest ecosystems, in harvested wood product (HWP) carbon stocks, and in other sectors where wood products substitute for emission-intensive materials and fossil fuels. All mitigation activities were assessed relative to a forward-looking 'business as usual' baseline for three implementation levels. In addition to quantifying net GHG emission reductions, we assessed economic, and socio-economic impacts as well as other environmental indicators relating to forest species, age class, deadwood availability and future timber supply. We further considered risks of reversal for land-based scenarios, by assessing impacts of increasing future wildfires on stands that were not harvested.ResultsOur spatially explicit analyses of forest sector mitigation options demonstrated a cost-effective portfolio of regionally differentiated scenarios that directed more of the harvested wood to longer-lived wood products, stopped burning of harvest residues and instead produced bioenergy to displace fossil fuel burning, and reduced harvest levels in regions with low disturbance rates. Domestically, net GHG emissions were reduced by an average of -9 MtCO2e year-1 over 2020-2050 for a portfolio of mitigation activities at a default implementation level, with about 85% of the GHG emission reductions achieved below a cost of $50/tCO2e. Normalizing the net GHG reduction by changes in harvested wood levels permitted comparisons of the scenarios with different ambition levels, and showed that a 1 MtCO2 increase in cumulative harvested stemwood results in a 1 MtCO2e reduction in cumulative emissions, relative to the baseline, for the Higher Recovery scenario in 2070.ConclusionsThe analyses conducted in this study contribute to the global understanding of forest sector mitigation options by providing an integrated framework to synthesize the methods, assumptions, datasets and models needed to quantify mitigation activities using a systems approach. An understanding of economically feasible and socio-economically attractive mitigation scenarios along with trade offs for environmental indicators relating to species composition and age, helps decision makers with long-term planning for land sector contributions to GHG emission reduction efforts, and provides valuable information for stakeholder consultations.

Dataset Information

Socio-demographic predictors of health and environmental co-benefit behaviours for climate change mitigation in urban China.

Objective

Methods

Findings

Conclusion

Publications

Socio-demographic predictors of health and environmental co-benefit behaviours for climate change mitigation in urban China.

Similar Datasets

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