Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr−1 in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m−2 with 90% uncertainty bounds of (+0.08, +1.27) W m−2. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m−2. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m−2 with 90% uncertainty bounds of +0.17 to +2.1 W m−2. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m−2, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (−0.50 to +1.08) W m−2 during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (−0.06 W m−2 with 90% uncertainty bounds of −1.45 to +1.29 W m−2). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

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Bounding the role of black carbon in the climate system: A scientific assessment

Many empirical questions in economics and other social sciences depend on causal effects of programs or policies. In the last two decades, much research has been done on the econometric and statistical analysis of such causal effects. This recent theoreti- cal literature has built on, and combined features of, earlier work in both the statistics and econometrics literatures. It has by now reached a level of maturity that makes it an important tool in many areas of empirical research in economics, including labor economics, public finance, development economics, industrial organization, and other areas of empirical microeconomics. In this review, we discuss some of the recent developments. We focus primarily on practical issues for empirical research- ers, as well as provide a historical overview of the area and give references to more technical research.

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Recent developments in the econometrics of program evaluation

The Lancet Commission on pollution and health

A common approach to evaluating robustness to omitted variable bias is to observe coefficient movements after inclusion of controls. This is informative only if selection on observables is informative about selection on unobservables. Although this link is known in theory in existing literature, very few empirical articles approach this formally. I develop an extension of the theory that connects bias explicitly to coefficient stability. I show that it is necessary to take into account coefficient and R-squared movements. I develop a formal bounding argument. I show two validation exercises and discuss application to the economics literature. Supplementary materials for this article are available online.

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Unobservable Selection and Coefficient Stability: Theory and Evidence

A long-standing question in social science is to what extent differences in management cause differences in firm performance. To investigate this, the authors ran a management field experiment on large Indian textile firms, providing free consulting on modern management practices to a randomly chosen set of treatment plants and compared their performance to the control plants. They find that adopting these management practices had three main effects. First, it raised average productivity by 11 percent through improved quality and efficiency and reduced inventory. Second, it increased decentralization of decision making, as better information flow enabled owners to delegate more decisions to middle managers. Third, it increased the use of computers, necessitated by the data collection and analysis involved in modern management. Since these practices were profitable this raises the question of why firms had not adopted these before. Their results suggest that informational barriers were a primary factor in explaining this lack of adoption. Modern management is a technology that diffuses slowly between firms, with many Indian firms initially unaware of its existence or impact. Since competition was limited by constraints on firm entry and growth, badly managed firms were not rapidly driven from the market.

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Does Management Matter? Evidence from India

This paper combines a randomized experiment and a structural model to test whether monitoring and financial incentives can reduce teacher absence and increase learning. In 57 schools in India, randomly chosen out of 113, a teacher’s daily attendance was verified through photographs with time and date stamps, and his salary was made a non-linear function of his attendance. The teacher absence rate changed from 42 percent in the comparison schools to 21 percent in the treatment schools. To separate the effects of the monitoring and the financial incentives, we estimate a structural dynamic labour supply model that allows for heterogeneity in preferences and auto-correlation of external shocks. The teacher response was almost entirely due to the financial incentives. The estimated elasticity of labour with respect to the incentive is 0.306. Our model accurately predicts teacher attendance in two out-of-sample tests on the comparison group and a treatment group that received different financial incentives. The program improved child learning: test scores in the treatment schools were 0.17 standard deviations higher than in the comparison schools.

Monitoring Works: Getting Teachers to Come to School

Moderate effects of pollution on health may exert an important influence on labor market decisions. We exploit exogenous variation in pollution due to the closure of a large refinery in Mexico City to understand how pollution impacts labor supply. The closure led to an 8 percent decline in pollution in the surrounding neighborhoods. We find that a one percent increase in sulfur dioxide results in a 0.61 percent decrease in the hours worked. The effects do not appear to be driven by labor demand shocks nor differential migration as a result of the closure in the areas located near the refinery.

The Effect of Pollution on Labor Supply: Evidence from a Natural Experiment in Mexico City

Using the most comprehensive developing country dataset ever compiled on air and water pollution and environmental regulations, the paper assesses India’s environmental regulations with a difference-in-differences design. The air pollution regulations are associated with substantial improvements in air quality. The most successful air regulation resulted in a modest but statistically insignificant decline in infant mortality. In contrast, the water regulations had no measurable benefits. The available evidence leads us to cautiously conclude that higher demand for air quality prompted the effective enforcement of air pollution regulations, indicating that strong public support allows environmental regulations to succeed in weak institutional settings. (JEL I12, J13, O13, Q53, Q58)

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Environmental Regulations, Air and Water Pollution, and Infant Mortality in India

Much of what we know about the marginal effect of pollution on infant mortality is derived from developed country data. However, given the lower levels of air pollution in developed countries, these estimates may not be externally valid to the developing country context if there is a non-linear dose relationship between pollution and mortality or if the costs of avoidance behaviour differ considerably between the two contexts. In this article, we estimate the relationship between pollution and infant mortality using data from Mexico. Our estimates for PM10 tend to be similar (or even smaller) than the US estimates, while our findings on CO tend to be larger than those derived from the US context.

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Does the effect of pollution on infant mortality differ between developing and developed countries? evidence from mexico city

Indoor air pollution (IAP) caused by solid fuel use and/or traditional cooking stoves is a global health threat, particularly for women and young children. The WHO World Health Report 2002 estimates that IAP is responsible for 2.7% of the loss of disability adjusted life years (DALYs) worldwide and 3.7% in high mortality developing countries. Despite the magnitude of this problem, social scientists have only recently begun to pay closer attention to this issue and to test strategies for reducing IAP. In this paper, we provide a survey of the current literature on the relationship between indoor air pollution, respiratory health and economic well-being. We then discuss the available evidence on the effectiveness of popular policy prescriptions to reduce IAP within the household.

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Rema Hanna

Papers

Monitoring Works: Getting Teachers to Come to School

The Effect of Pollution on Labor Supply: Evidence from a Natural Experiment in Mexico City

Environmental Regulations, Air and Water Pollution, and Infant Mortality in India

Does the effect of pollution on infant mortality differ between developing and developed countries? evidence from mexico city

Indoor air pollution, health and economic well-being