Impacts of improved cookstove interventions on personal exposure to carbon monoxide and particulate matter in Zambia

Eighty-four percent of sub-Saharan African households rely on polluting fuels (e.g., wood, charcoal) for cooking, leading to high levels of household air pollution (HAP). While switching to modern fuels/stoves could decrease HAP levels, they are not always available or affordable. Improved biomass cookstoves could provide an intermediate step supporting transitions from traditional biomass to clean burning fuels/stoves. We conducted two stove intervention trials in Lusaka, Zambia using targeted marketing/incentives to motivate participants to use improved biomass stoves, either the Mimi Moto (pellet) or the EcoZoom (charcoal). Before the intervention, 65% of participants exclusively used charcoal, while 27% relied on electricity to some extent for cooking. We measured 24-hour personal exposure to CO (n=747) and PM2.5 (n=90) of primary cooks. We implemented several statistical approaches to estimate the effects of interventions on exposure: household-specific endline minus baseline expos..., Data:
We conducted two stove intervention trials in Lusaka, Zambia using targeted marketing and incentives to motivate traditional biomass stove users to switch to one of two improved biomass stoves, either the pellet burning Mimi Moto or the charcoal burning EcoZoom. Exposure data for this study was collected from primary cooks in Lusaka, Zambia in 2019 and 2021. Ambient data was collected using PurpleAir PM2.5 sensors available online at the time of the study (baseline, no longer available) and installed by researchers on the project (endline). Raw and processed data are included in CSVs. Refer to the descriptions below for what is included in each CSV file. Note that household ID (HHID) is used to differentiate households/primary cooks and match exposure data to questionnaire responses.

Hourly exposure data:

ZCCS_2019_CO_hourly_CSV - hourly CO exposure in ppm for all participants in 2019 where hour_0 = 00:00, hour_1 = 01:00, etc.

ZCCS_2019_PM_hourly_CSV - hourly PM2.5 exposure in..., , # Impacts of improved cookstove interventions on personal exposure to carbon monoxide and particulate matter in Zambia

Dataset DOI: [10.5061/dryad.xd2547drx](10.5061/dryad.xd2547drx)

## Description of the data and file structure

We conducted two stove intervention trials in Lusaka, Zambia using targeted marketing and incentives to motivate traditional biomass stove users to switch to one of two improved biomass stoves, either the pellet burning Mimi Moto or the charcoal burning EcoZoom. We measured 24-hour CO (n=747) and PM2.5 (n=90) exposures of primary cooks. Primary cooks were outfitted with exposure monitors and instructed to wear them for 24 hours, unless sleeping or bathing, when they were instructed to keep the monitors nearby. Data collection also consisted of a structured household questionnaire that included questions about household demographics, cooking practices, household facilities, and economic decision making. The main decision maker (household head) and person most ...,

撒哈拉以南非洲有84%的家庭依赖污染性燃料（如木材、木炭）做饭，由此引发严重的室内空气污染（Household Air Pollution，以下简称HAP）。尽管改用清洁燃料/灶具可降低HAP水平，但这类方案并非总能获取或负担得起。改良型生物质灶具可作为过渡方案，助力使用者从传统生物质燃料逐步转向清洁燃烧燃料/灶具。

本研究在赞比亚卢萨卡开展了两项灶具干预试验，通过定向营销与激励措施，引导参与者使用两款改良型生物质灶具——分别为颗粒燃料款Mimi Moto，以及木炭燃料款EcoZoom。干预前，65%的参与者仅使用木炭做饭，另有27%的家庭在一定程度上依赖电力烹饪。研究人员测量了主要烹饪者的24小时个人暴露水平：一氧化碳（CO）暴露样本量为747，细颗粒物（PM2.5）暴露样本量为90。本研究采用多种统计方法评估干预措施对暴露水平的影响：以家庭为单位的终点随访值减去基线暴露值……

### 数据集说明
我们在赞比亚卢萨卡于2019年与2021年收集了主要烹饪者的暴露数据。环境数据采集采用了研究期间可在线获取（基线阶段数据现已不可用）的PurpleAir PM2.5传感器，以及项目研究人员在终点随访阶段安装的同款传感器。原始与处理后的数据均以CSV格式存储。请参阅下文说明，了解各CSV文件包含的内容。请注意，家庭ID（HHID）用于区分家庭与主要烹饪者，并将暴露数据与问卷结果进行匹配。

#### 每小时暴露数据：
1. ZCCS_2019_CO_hourly_CSV：2019年所有参与者的每小时CO暴露水平（单位：ppm），其中hour_0对应00:00，hour_1对应01:00，以此类推。
2. ZCCS_2019_PM_hourly_CSV：2019年参与者的每小时PM2.5暴露水平……

# 赞比亚改良灶具干预对个人一氧化碳与细颗粒物暴露水平的影响
数据集DOI：10.5061/dryad.xd2547drx

## 数据与文件结构说明
本研究在赞比亚卢萨卡开展了两项灶具干预试验，通过定向营销与激励措施，引导传统生物质灶具使用者更换为两款改良型生物质灶具之一：颗粒燃料款Mimi Moto，或是木炭燃料款EcoZoom。研究人员测量了主要烹饪者的24小时CO（样本量n=747）与PM2.5（样本量n=90）暴露水平。为每位主要烹饪者配备了暴露监测设备，并要求其佩戴24小时，仅在睡眠或沐浴时可将设备放置在附近。数据收集还包含结构化家庭问卷，内容涵盖家庭人口统计学特征、烹饪习惯、家庭设施与经济决策等。主要决策者（户主）与主要烹饪者……