Suchergebnisse

Objective:Our purpose was to assess stigma toward schizophrenia in a representative sample of the Brazilian general population.Methods:The sample consisted of 1015 individuals interviewed by telephone. A vignette describing someone with schizophrenia was read, and four stigma aspects regarding this hypothetical individual were assessed: stereotypes, restrictions, perceived prejudice and social distance. Latent profile analysis searched for stigma profiles among the sample. Multinomial logistic regression was used to find correlates of each class.Results:Four stigma profiles were found; 'no stigma' individuals ( n = 251) mostly displayed positive opinions. 'Labelers' ( n = 222) scored high on social distance; they more often had familial contact with mental illness and more often labeled the vignette's disorder as schizophrenia. 'Discriminators', the group with the majority of individuals ( n = 302), showed high levels of stigmatizing beliefs in all dimensions; discriminators were significantly older. 'Unobtrusive stigma' individuals ( n = 240) seemed to demonstrate uncertainty or low commitment since they mostly answered items with the middle/impartial option.Conclusion:Some findings from the international literature were replicated; however, familial contact increased stigma, possibly denoting a locally modulated determinant. Hereby, our study also adds important cross-cultural data by showing that stigma toward schizophrenia is high in a Latin-American setting. We highlight the importance of analyzing the general population as a heterogeneous group, aiming to better elaborate anti-stigma campaigns.

Political-feasibility concerns are at the center of real-world air-pollution policymaking. Yet, these concerns are often not represented in leading decision-support tools that have been used for assessing policies' environmental impacts. Focusing on a wide range of clean-air policies in India, we assess their political-feasibility scores on the basis of public opinion, market, and institutional considerations and then incorporate these scores into the evaluation of environmental impacts by using an integrated assessment model (GAINS-South Asia). We demonstrate that although some policies with substantial potential to mitigate air pollution are also highly politically feasible (e.g., replacing solid fuels with cleaner fuels in households), others can be less politically feasible (e.g., banning agricultural waste burning). Because some clean-air policies co-reduce CO2 emissions and aerosols, considering varying degrees of political feasibility is particularly important in achieving air-pollution and climate objectives simultaneously because of its implications on the implementation scale and policy sequence.

Political-feasibility concerns are at the center of real-world air-pollution policymaking. Yet, these concerns are often not represented in leading decision-support tools that have been used for assessing policies' environmental impacts. Focusing on a wide range of clean-air policies in India, we assess their political-feasibility scores on the basis of public opinion, market, and institutional considerations and then incorporate these scores into the evaluation of environmental impacts by using an integrated assessment model (GAINS-South Asia). We demonstrate that although some policies with substantial potential to mitigate air pollution are also highly politically feasible (e.g., replacing solid fuels with cleaner fuels in households), others can be less politically feasible (e.g., banning agricultural waste burning). Because some clean-air policies co-reduce CO2 emissions and aerosols, considering varying degrees of political feasibility is particularly important in achieving air-pollution and climate objectives simultaneously because of its implications on the implementation scale and policy sequence.

Solar photovoltaic (PV) electricity generation can greatly reduce both air pollutant and greenhouse gas emissions compared to fossil fuel electricity generation. The Chinese government plans to greatly scale up solar PV installation between now and 2030. However, different PV development pathways will influence the range of air quality and climate benefits. Benefits depend on how much electricity generated from PV is integrated into power grids and the type of power plant displaced. Using a coal-intensive power sector projection as the base case, we estimate the climate, air quality, and related human health benefits of various 2030 PV deployment scenarios. We use the 2030 government goal of 400 GW installed capacity but vary the location of PV installation and the extent of inter-provincial PV electricity transmission. We find that deploying distributed PV in the east with inter-provincial transmission maximizes potential CO2 reductions and air quality-related health benefits (4.2% and 1.2% decrease in national total CO2 emissions and air pollution-related premature deaths compared to the base case, respectively). Deployment in the east with inter-provincial transmission results in the largest benefits because it maximizes displacement of the dirtiest coal-fired power plants and minimizes PV curtailment, which is more likely to occur without inter-provincial transmission. We further find that the maximum co-benefits achieved with deploying PV in the east and enabling inter-provincial transmission are robust under various maximum PV penetration levels in both provincial and regional grids. We find large potential benefits of policies that encourage distributed PV deployment and facilitate inter-provincial PV electricity transmission in China.

Solar photovoltaic (PV) electricity generation can greatly reduce both air pollutant and greenhouse gas emissions compared to fossil fuel electricity generation. The Chinese government plans to greatly scale up solar PV installation between now and 2030. However, different PV development pathways will influence the range of air quality and climate benefits. Benefits depend on how much electricity generated from PV is integrated into power grids and the type of power plant displaced. Using a coal-intensive power sector projection as the base case, we estimate the climate, air quality, and related human health benefits of various 2030 PV deployment scenarios. We use the 2030 government goal of 400 GW installed capacity but vary the location of PV installation and the extent of inter-provincial PV electricity transmission. We find that deploying distributed PV in the east with inter-provincial transmission maximizes potential CO2 reductions and air quality-related health benefits (4.2% and 1.2% decrease in national total CO2 emissions and air pollution-related premature deaths compared to the base case, respectively). Deployment in the east with inter-provincial transmission results in the largest benefits because it maximizes displacement of the dirtiest coal-fired power plants and minimizes PV curtailment, which is more likely to occur without inter-provincial transmission. We further find that the maximum co-benefits achieved with deploying PV in the east and enabling inter-provincial transmission are robust under various maximum PV penetration levels in both provincial and regional grids. We find large potential benefits of policies that encourage distributed PV deployment and facilitate inter-provincial PV electricity transmission in China.

This paper assesses the macroeconomic and sectoral impacts of the "Clean Air Policy Package" proposed by the European Commission in December 2013. The analysis incorporates both the expenditures necessary to implement the policy by 2030 and the resulting positive feedback effects on human health and crop production. A decomposition analysis identifies the important drivers of the macroeconomic impacts. We show that while expenditure on pollution abatement is a cost for the abating sectors, it also generates an increased demand for the sectors that produce the goods required for pollution abatement. Moreover, we find that positive feedback effects, particularly those related to health can offset the resource costs associated to the clean air policy and result in positive macroeconomic impacts for the economy of the European Union.

This paper assesses the macroeconomic and sectoral impacts of the "Clean Air Policy Package" proposed by the European Commission in December 2013. The analysis incorporates both the expenditures necessary to implement the policy by 2030 and the resulting positive feedback effects on human health and crop production. A decomposition analysis identifies the important drivers of the macroeconomic impacts. We show that while expenditure on pollution abatement is a cost for the abating sectors, it also generates an increased demand for the sectors that produce the goods required for pollution abatement. Moreover, we find that positive feedback effects, particularly those related to health can offset the resource costs associated to the clean air policy and result in positive macroeconomic impacts for the economy of the European Union.

In recent years several European air pollution policies have been based on a cost-effectiveness approach. In the European Union, the European Commission starts using the multi-pollutant, multi-effect GAINS (Greenhouse Gas Air Pollution Interactions and Synergies) model to identify cost-effective National Emission Ceilings and specific emission control measures for each Member State to reach these targets. In this paper, we apply the GAINS methodology to the case of Italy with 20 subnational regions. We present regional results for different approaches to environmental target setting for PM2.5 pollution in the year 2030. We have obtained these results using optimization techniques consistent with those of GAINS-Europe, but at a higher resolution. Our results show that an overall health-impact oriented approach is more cost-effective than setting a nation-wide limit value on ambient air quality, such as the one set for the year 2030 by the European Directive on ambient air quality and cleaner air for Europe. The health-impact oriented approach implies additional emission control costs of 153 million €/yr on top of the baseline costs, compared to 322 million €/yr for attaining the nation-wide air quality limit. We provide insights into the distribution of costs and benefits for regions within Italy and identify the main beneficiaries of a health-impact approach over a limit-value approach.

In recent years several European air pollution policies have been based on a cost-effectiveness approach. In the European Union, the European Commission starts using the multi-pollutant, multi-effect GAINS (Greenhouse Gas Air Pollution Interactions and Synergies) model to identify cost-effective National Emission Ceilings and specific emission control measures for each Member State to reach these targets. In this paper, we apply the GAINS methodology to the case of Italy with 20 subnational regions. We present regional results for different approaches to environmental target setting for PM2.5 pollution in the year 2030. We have obtained these results using optimization techniques consistent with those of GAINS-Europe, but at a higher resolution. Our results show that an overall health-impact oriented approach is more cost-effective than setting a nation-wide limit value on ambient air quality, such as the one set for the year 2030 by the European Directive on ambient air quality and cleaner air for Europe. The health-impact oriented approach implies additional emission control costs of 153 million €/yr on top of the baseline costs, compared to 322 million €/yr for attaining the nation-wide air quality limit. We provide insights into the distribution of costs and benefits for regions within Italy and identify the main beneficiaries of a health-impact approach over a limit-value approach.

The coal-dominated electricity system poses major challenges for India to tackle air pollution and climate change. Although the government has issued a series of clean air policies and low-carbon energy targets, a key barrier remains enforcement. Here, we quantify the importance of policy implementation in India's electricity sector using an integrated assessment method based on emissions scenarios, air quality simulations, and health impact assessments. We find that limited enforcement of air pollution control policies leads to worse future air quality and health damages (e.g., 14 200 to 59 000 more PM2.5-related deaths in 2040) than when energy policies are not fully enforced (5900 to 8700 more PM2.5-related deaths in 2040), since coal power plants with end-of-pipe controls already emit little air pollution. However, substantially more carbon dioxide will be emitted if low-carbon and clean coal policies are not successfully implemented (e.g., 400 to 800 million tons more CO2 in 2040). Thus, our results underscore the important role of effectively implementing existing air pollution and energy policy to simultaneously achieve air pollution, health, and carbon mitigation goals in India.

The coal-dominated electricity system poses major challenges for India to tackle air pollution and climate change. Although the government has issued a series of clean air policies and low-carbon energy targets, a key barrier remains enforcement. Here, we quantify the importance of policy implementation in India's electricity sector using an integrated assessment method based on emissions scenarios, air quality simulations, and health impact assessments. We find that limited enforcement of air pollution control policies leads to worse future air quality and health damages (e.g., 14 200 to 59 000 more PM2.5-related deaths in 2040) than when energy policies are not fully enforced (5900 to 8700 more PM2.5-related deaths in 2040), since coal power plants with end-of-pipe controls already emit little air pollution. However, substantially more carbon dioxide will be emitted if low-carbon and clean coal policies are not successfully implemented (e.g., 400 to 800 million tons more CO2 in 2040). Thus, our results underscore the important role of effectively implementing existing air pollution and energy policy to simultaneously achieve air pollution, health, and carbon mitigation goals in India.

Facing severe air pollution and growing dependence on natural gas imports, the Chinese government plans to increase coal-based synthetic natural gas (SNG) production. Although displacement of coal with SNG benefits air quality, it increases CO2 emissions. Due to variations in air pollutant and CO2 emission factors and energy efficiencies across sectors, coal replacement with SNG results in varying degrees of air quality benefits and climate penalties. We estimate air quality, human health, and climate impacts of SNG substitution strategies in 2020. Using all production of SNG in the residential sector results in an annual decrease of ∼32,000 (20,000 to 41,000) outdoor-air-pollution-associated premature deaths, with ranges determined by the low and high estimates of the health risks. If changes in indoor/household air pollution were also included, the decrease would be far larger. SNG deployment in the residential sector results in nearly 10 and 60 times greater reduction in premature mortality than if it is deployed in the industrial or power sectors, respectively. Due to inefficiencies in current household coal use, utilization of SNG in the residential sector results in only 20 to 30% of the carbon penalty compared with using it in the industrial or power sectors. Even if carbon capture and storage is used in SNG production with today's technology, SNG emits 22 to 40% more CO2 than the same amount of conventional gas. Among the SNG deployment strategies we evaluate, allocating currently planned SNG to households provides the largest air quality and health benefits with the smallest carbon penalties