雾霾天气的成因及其法律层面应对状况与操作层面政策建议

雾与霾都是可以使能见度降低的天气现象,但是其组成成份不同,雾是由悬浮在空气中的水滴或冰晶所组成,是一种自然现象,而霾的本质则是人类活动造成的细颗粒物污染。细颗粒物的来源复杂,在长期暴露的情况下对人体健康产生严重影响。对于近期频繁发生的雾霾天气,其产生的外因是特殊的气象条件,而其内因则是严重的空气污染问题。纵观全球,发达国家在环境与发展的历程中都不约而同的走过了一条先污染后治理的道路。美国、英国、日本,均在发生严重的空气污染事件后颁布了的空气污染防治法律,从而逐步解决了空气污染的问题。我国《大气污染防治法》自1987年以来的几经修改,体现了我国着力解决大气污染问题的决心。为了进一步防治空气污染,更加积极的应对雾霾天气,建议从优化能源结构、实施联防联控着手,严格行业准入制度、加大对开放源与移动源污染的控制力度,加强组织领导努力提高公众环境意识,全面开展对空气污染的防治工作。     

Effects of construction activities on residential electricity consumption: Evidence from Singapore's public housing estates

This study aims to empirically test the effects of negative environmental externalities (i.e. noise pollution) due to construction activities within half to one kilometer (km) radius and how households react to such externalities by increasing the use of air-conditioners to mitigate noise from the construction work. We use a unique dataset of electricity consumption by public housing residents in Singapore measured at the building level and merge it with the dataset of construction sites for the periods from 2009 to 2011. Using a difference-in-differences approach, we find that electricity consumption by the households living close to the construction sites increases by 6% compared to the households who are not affected by noises from construction sites during the construction periods, after controlling for building and month of the year fixed effects. The results remain robust after controlling for spatial autocorrelated lag and error terms. The economic cost of the construction externalities for each household amounts to approximately S$98 per annum. We also find that the increases in electricity consumption of the affected households were persistent, and the electricity consumption of the affected households did not revert to the pre-construction levels, after the removal of the negative externality.     

Unintended outcomes of electricity smart-metering: trading-off consumption and investment behaviour

Smart-metering allows electricity utilities to provide consumers with better information on their energy usage and to apply time-of-use pricing. These measures have been shown to reduce electricity consumption and induce time-shifting of demand. Less is known about how they affect residential energy efficiency investment behaviour. We use data from a randomised-controlled trial on a sample of almost 2500 Irish consumers, conducted over a 12-month period to investigate the effect of smart-metering and residential feedback on household investment behaviour. The results show that exposure to time-of-use pricing and information stimuli, while reducing overall and peak usage, can also have the unintended effect of reducing investment in energy efficiency measures within the home. Our findings indicate that households exposed to treatment were less likely to adopt any energy saving measure (23–28 % on average), and those households adopted less energy saving features than those in the control group (15–21 % on average). This result highlights the potential for behavioural interventions to have unintended consequences on behaviours other than those specifically targeted. Furthermore, it underlines the importance of examining a wider range of outcomes and allowing longer time-scales when evaluating this type of experiment.     

Disentangling household and individual actors in explaining private electricity consumption

Previous research often regard household and individual as synonymous actors, although the overall household electricity consumption is the aggregate of diverging actions by individual household members. We disentangle the impact of actor-specific predictors on household and individual electricity consumption, employing regression models to data of 204 Austrian multi-person households. Predictors add more to the explained variance of household and individual electricity consumption if they are located at the same actor level as the dependent variable. While household electricity consumption is best predicted by the household context and value/knowledge factors, individual electricity consumption depends foremost on habit and whether a person stays at home during the day. The study exemplifies that future research and interventions need to decompose actor levels to better understand and target the drivers of private electricity consumption. Methodological challenges in measuring individual and household consumption behaviour are discussed.     

How do household characteristics affect appliance usage? Application of conditional demand analysis to Japanese household data

Although both appliance ownership and usage patterns determine residential electricity consumption, it is less known how households actually use their appliances. In this study, we conduct conditional demand analyses to break down total household electricity consumption into a set of demand functions for electricity usage, across 12 appliance categories. We then examine how the socioeconomic characteristics of the households explain their appliance usage. Analysis of micro-level data from the Nation Survey of Family and Expenditure in Japan reveals that the family and income structure of households affect appliance usage. Specifically, we find that the presence of teenagers increases both air conditioner and dishwasher use, labor income and nonlabor income affect microwave usage in different ways, air conditioner usage decreases as the wife's income increases, and microwave usage decreases as the husband's income increases. Furthermore, we find that households use more electricity with new personal computers than old ones; this implies that the replacement of old personal computers increases electricity consumption.     

Electricity and water consumption for laundry washing by washing machine worldwide

Washing laundry is one of the most widespread housework in the world. Today, washing machines do this work in many private households, using water, electricity, chemical substances, and process time. Although energy efficiency is in the focus of many regulations which have already achieved significant improvements, the question remains, how relevant these processes are in terms of the absolute impact on resources and whether there are possibilities to improve even further by looking abroad. This survey, which is based on published data, compares the energy and water consumption for automatic laundry washing in an average private household with the total energy and water consumption of private households. Only little data are available on resource consumption for laundry washing and reliable figures based on in-use measurements are hard to obtain. But although some of the data in this report are poor, this is the first work that tries to elucidate the contribution of automatic laundry washing to the total electricity and water consumption of households in selected countries worldwide. The report estimates the resource consumption of roughly 590,000,000 washing machines in 38 countries with about 2.3 billion people, which is about one third of the world population. The results of this work show that laundry washing in private households is done with quite different amounts of electricity and water in different parts of the world both in absolute and relative comparison to the overall household consumption. But due to different consumer habits in dealing with the achieved washing performance in the different global regions, the best practice in washing laundry in a most sustainable way cannot be determined yet. Further research is needed to form a basis for a most sustainable development of resource consumption in private households.     

Social habits and energy consumption in single-family homes

Personal interviews (response rate = 96.1%) were made with both men and women in an area of 76 similar, all-electric single-family houses (November 15 to December 1, 1981). The total variation in energy consumption in the area is explained by differences in social habits (water consumption, about 50%; ventilation habits, about 35%; indoor temperature, about 15%) among the households. The consumer sociological variables chosen for this study statistically explain more than 60% of total variation in household energy consumption. A relation has been found between attitude to energy consumption and household energy consumption with r = 0.48. The households display no knowledge that they themselves consume about one third of total energy used. When major energy saving activities are undertaken by the households, the motive is often energy consciousness. When minor energy-saving activities are taken, the motive is an economic one. The male energy-related role is of greater importance for the variation in household energy consumption than the female role.In a discussion, the importance of distinguishing between household energy consumption and household energy use in order not to affect the welfare of the households when energy saving actions are undertaken, is maintained.     

Responsiveness of low-income households to hybrid price/non-price policies in the presence of energy shortages: evidence from Colombia

At the beginning of 2016, Colombia was experiencing an energy shortage, and in order to avoid mandatory power cuts, the government launched an unexpected hybrid price/non-price energy-saving policy. In this paper, I evaluate how low-income households in a major Colombian city respond to this policy. Using hourly household electricity consumption data, I find that, on average, households reduce electricity consumption by 4.5% as a result of the policy. It is striking that even low-income households, who consume relatively small amounts of electricity, respond to energy-saving policies and engage in conservation behaviors in the short term. In my analysis, I also find that the effect is stronger the higher the household pre-treatment electricity consumption levels and smaller among poorer households. However, the heterogeneity in terms of income level vanishes once I control for household pre-program electricity consumption levels. Finally, my point estimates are comparable to the impact estimates of policies that are similar to the one I analyze in this paper.     

Haze,health, and income: An integrated model for willingness to pay for haze mitigation in Shanghai,China

Most existing studies indicate that residentsö willingness to pay (WTP) for environmental protection mainly depends on income and the degree of environmental pollution. However, owing to lack of suitable data, less research has focused on why people have higher or lower WTP for environmental protection, and many questions about their reasons remain unanswered. Based on contingent valuation questionnaires in 16 districts of Shanghai, this study investigates the influencing factors of residentsö WTP for haze mitigation. To avoid a multicollinearity problem, we integrate principal component analysis and the probit model to examine the determinants of WTP. Results show that residentsö WTP for haze mitigation ranges from 343.31 to 359.48 USD. The major influencing factors of residentsö WTP include subjective knowledge of haze impacts, understanding of the frequency and severity of haze, and social trust in haze data published by the government. In particular, we find that owing to anti-haze household expenditure on mitigating the effects of haze pollution on health, residents who considered that the areas they lived in were more influenced by haze pollution do not always have higher WTP for haze mitigation. Results of this study have policy implications for haze mitigation regarding the effect of anti-haze household expenditure.     

Determination of household energy using ‘fingerprints’ from energy billing data

Electric and gas utilities (in the U.S.A.) bill their customers on a regular basis, usually monthly or bimonthly. These data provide a truly valuable information resource for energy conservation programme analysts and evaluators. This paper discusses ways to analyse such billing data. The starting point is the Princeton University score-keeping model, which permits decomposition of total household energy use into its weather-and non-weather-sensitive elements; the weather-sensitive portion is assumed to be proportional to heating degree days. The score-keeping model also allows one to compute weather-adjusted energy consumption for each household based on its billing data and model parameters; this is the model's estimate of annual consumption under long-run weather conditions. The methods discussed here extend the score-keeping results to identify additional characteristics of household energy use. The methods classify households in terms of the intensity with which the particular fuel is used for space heating (primary heating fuel vs. supplemental heating fuel vs. no heating at all with the fuel). In addition, households that use the particular fuel for air conditioning are identified. In essence, the billing data and model results define household energy use ‘fingerprints’. The billing data and model results can also be used to identify and correct anomalous bills. Finally, the methods permit careful examination and analysis of changes in energy use from one year to another. They help explain why some households show anomalously large energy savings (e.g. they began using wood as a heating fuel during the second year) or negative energy savings (e.g. very high air conditioning energy use during the second year).     

Evidence of an indirect rebound effect with reversible heat pumps: having air conditioning but not using it?

Regional energy efficiency programmes are of particular interest as they tackle local constraints which are not always targeted by national energy policy. Within this framework, an energy efficiency programme for existing dwellings has been implemented in a southern European region, providing financial incentives for a combination of energy efficiency actions (heat pump combined with insulation and/or solar water heater). Ex-post evaluation results of this pilot programme are reported in this study. More than 200 households were surveyed regarding their individual energy consumption as well as house and household characteristics. Likewise, the survey highlights household behaviours concerning both space heating and air conditioning, before and after refurbishment. A 3-year billing analysis is used to calculate the energy savings attributed to the operation. Evaluations are carried out taking into account critical parameters like climate differences between years or direct (enhanced space heating comfort) and indirect (use of air conditioning) rebound effects via a statistical model. Moreover, an uncertainty assessment of energy savings was realized on the basis of three scenarios (low, median and high). This study is particularly focused on the use of air conditioning by households, data rarely found in the literature, whereas the consumption linked to air conditioning should increase in the residential sector especially in southern regions. These results help in answering questions about the installation of heat pumps in existing single-family houses with respect to energy savings as well as direct and indirect rebound effects.     

Household consumption of electricity in Brazil between 1985 and 2013

This article describes the electricity consumption in Brazilian residences between 1985 and 2013 through linear regressions. The explanatory variables considered were the number of households, effective consumption of families as a proxy for family income, and electricity tariff for households. To deal with the power generation crisis of 2001 we have introduced a dummy variable in the form of a step function. With such explanatory variables, we were able to account for the reduction of household electricity consumption caused by the policies conducted in 2001 and their permanent consequences. The regression presented coefficient of determination of 0.9892, and the several statistic tests conducted assured the existence of long-term relation between the electricity consumption in residences and the explanatory variables. The obtained elasticities for the household consumption of electricity with respect to number of residences, family income and residential tariff of electricity were 1.534±0.095, 0.189±0.049, and −0.230±0.060, respectively. These results allowed understanding the evolution over time of the household consumption of electricity in Brazil. They suggest that the electric sector in Brazil should pursue an active policy to manage demand of residential electricity using tariffs as a means to control it.     

An analysis of the welfare and distributive implications of factors influencing household electricity consumption

The deep economic crisis and the sharp rise in electricity prices have reduced electricity demand by Spanish households. This paper aims to analyse the responsiveness of household electricity demand and the welfare effects related to both factors in the 2006–2012 period by applying a demand model estimated with the quantile regression method. The results show that the electricity consumption of medium-high income households is particularly responsive to price increases, whereas that of medium-low income households is more responsive to changes in income. The retail electricity price increases and the economic crisis have led to lower and steeper U-shape price elasticities of demand and higher and steeper N-shape income elasticities of demand. The joint impact of those two factors on the welfare of lower-income households is higher in relative terms (i.e., as a share of household income) than for other income groups. These results suggest that the economic crisis and increases in retail electricity prices have had detrimental welfare effects, especially on the lower-income segment of the population. They should be considered when financing climate and energy policies through the electricity bill and provide a rationale to take such support, which pushes the retail electricity price upwards, out of the electricity bill.     

Can pecuniary and environmental incentives via SMS messaging make households adjust their electricity demand to a fluctuating production?

The increasing deployment of renewables introduces substantial variability into the production of electricity, requiring demand to be more movable across time. We analyze data from a large Danish field experiment (2015–2016) to investigate whether households can be prompted, via SMS messages, to move electricity consumption, and if so, whether these are motivated by pecuniary or environmental motives. The analysis has two steps: As a novel approach, we first use automatic model selection, which allows a different time-series regression for each of the 1488 households studied. From this, we obtain a cross-section of estimated SMS effects, which we then regress on the motive type. Since households can opt out there is a risk of self-selection. We therefore control for the size, income and average consumption of the household, and the age, educational- and labor market status of the SMS recipient. The results suggest that SMS messages can to some extent motivate households to move consumption. Although a stronger financial motive seems more effective, mixing financial and environmental motives seems the most effective. Finally, women and elderly people are more inclined to move consumption.     

上海某高校研究生宿舍空调电耗特性研究

以上海某高校研究生宿舍空调电耗作为研究对象,统计分析了所有抽样房间(共12间,每间4人)全年空调电耗使用规律,并总结出典型日、典型月空调电耗指标以及与室外温度之间的关系.夏季空调电耗集中于7、8、9月,冬季空调电耗集中于12、1、3月(2月寒假放假).全年男、女生宿舍单位面积空调电耗差异不大,但与夏季相比,冬季单位面积...     

Applying models for ordinal logistic regression to the analysis of household electricity consumption classes in Rio de Janeiro, Brazil

This study applies the proportional odds and partial proportional odds models for ordinal logistic regression to analyze household electricity consumption classes. Micro-data from households situated in the state of Rio de Janeiro during 2004 was used to measure the performance of the models in correctly classifying household electricity consumption classes via sociodemographic, electricity usage and dwelling characteristics. The strategy of using binary logistic regressions to test the main hypothesis of the proportional odds model, suggested by Bender and Grouven, was successful in identifying which of the independent variables could be estimated via the proportional odds assumption. Results indicate that the partial proportional odds models is slightly superior to the more restrictive approach. The study includes probabilistic examples to describe how changes in the independent variables affect the probability of a household belonging to specific classes of electricity consumption. Projections using the final model indicated that the approach may be useful for estimating aggregate household electricity consumption.     

Trade-linked Canada–United States household environmental impact analysis of energy use and greenhouse gas emissions

We compare energy use and greenhouse gas (GHG) emissions associated with total household expenditures and activities in Canada and US in 1997, the first detailed estimate of environmental burdens for Canadian households. We estimate direct burdens from published government data and indirect burdens using an industry-by-commodity, bi-national economic input–output life cycle assessment model developed in this study. Comparing 30 expenditure and two activity categories, per capita US household expenditures were 70% higher, while per capita household energy use and GHG emissions were only 10% and 44% higher, respectively. Energy use/dollar of expenditure was higher in most Canadian categories, while the average ratio of GHG emissions/energy use was higher in the US (65 vs 50 kg Eq. CO₂/GJ) due largely to a higher proportion of electricity from nonrenewable sources. Indirect environmental burdens represented 63–69% of total burdens and 62–70% of total burdens were associated with household operation and transportation. Key drivers of differences between energy profiles were: higher per capita electricity use by Canadian households, and higher US household private health care expenditures and motor fuel use. Energy-intensive production for export represented a higher proportion of Canadian production, resulting in less agreement between consumption and production-based analyses for Canada than US.     

Pricing electricity from residential photovoltaic systems: A comparison of feed-in tariffs,net metering,and net purchase and sale

Three mechanisms are commonly employed to enable households to sell electricity from grid-connected residential solar photovoltaic (PV) systems to utilities or grid companies: feed-in tariffs (FIT), net metering, and net purchase and sale. This study aims to compare these mechanisms with respect to social welfare and to retail electricity rates that include the cost to electric utilities of purchasing residential PV-generated electricity. The study presents a simple microeconomic model that shows, first, that the mechanism that produces the most social welfare is different depending on the amount of reduction in electricity consumption achievable under net metering or net purchase and sale (which are shown to be essentially similar). If the reduction is relatively small, FIT is likely to produce more social welfare than net metering/net purchase and sale; if the reduction is large, the opposite is the case. Second, the model shows that the mechanism that yields the lowest electricity rate is not definite, and differs depending on the homogeneity of households: when households are more homogeneous, the electricity rate under net metering/net purchase and sale is more likely to be higher than that under FIT.     

Demographics,energy and our homes

The projected growth in households in the UK is a key factor in future domestic energy consumption, particularly electricity consumption. While every household needs a home and its heating, lighting and appliances, increasing incomes have historically led to significantly higher appliance ownership, higher expectations of levels of energy service and greater usage. In the past this trend was combined with increasing household numbers to drive growth in domestic electricity demand. Official projections for population growth and household composition indicate significant drivers for future growth in energy demand. Curbing this will require policies to reverse the tendency for energy–efficiency improvements to be overwhelmed by growing numbers of households, more widespread appliance ownership and increased service expectations.     

Determinants of electricity use for residential water heating: The hood river conservation project

Because 85% of the homes in the Pacific Northwest have electric water heaters, water heating is the second most important residential electricity end-use in the region (second to space heating). This paper analyses the determinants of water-heating electricity use, using end-use load data and responses to a detailed home interview. These data are available for 142 homes in Hood River, Oregon.On average, these homes used 5000 kWh/yr for water heating. Almost 60% of the household-to-household variation in electricity use was explained with eight variables in a simple regression model. The number and ages of household members are the strongest determinants of electricity use: use increases by roughly 1000 kWh/yr with each additional household member. Other statistically significant determinants of water-heating electricity use are hot-water temperature, water-heater location, number of showers in the home and house type.Electricity use varies considerably throughout the year (as well as across households). Weekly usage was 50% higher in mid-winter than in summer. About half of this temporal variation is due to changes in outdoor temperatures and half is due to seasonal changes in behavior (i.e. increased use of hot water in winter).